diff --git a/lib/node_modules/@stdlib/assert/has-search-symbol-support/bin/cli b/lib/node_modules/@stdlib/assert/has-search-symbol-support/bin/cli
old mode 100644
new mode 100755
diff --git a/lib/node_modules/@stdlib/assert/has-split-symbol-support/bin/cli b/lib/node_modules/@stdlib/assert/has-split-symbol-support/bin/cli
old mode 100644
new mode 100755
diff --git a/lib/node_modules/@stdlib/assert/has-to-primitive-symbol-support/bin/cli b/lib/node_modules/@stdlib/assert/has-to-primitive-symbol-support/bin/cli
old mode 100644
new mode 100755
diff --git a/lib/node_modules/@stdlib/assert/is-constantcase/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-constantcase/docs/types/index.d.ts
index de574c92d4c7..1bd9047bb372 100644
--- a/lib/node_modules/@stdlib/assert/is-constantcase/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/assert/is-constantcase/docs/types/index.d.ts
@@ -41,7 +41,7 @@
 * // returns false
 *
 * bool = isConstantcase( '' );
-* // returns false
+* // returns true
 *
 * bool = isConstantcase( null );
 * // returns false
diff --git a/lib/node_modules/@stdlib/assert/is-nonnegative-finite/docs/types/index.d.ts b/lib/node_modules/@stdlib/assert/is-nonnegative-finite/docs/types/index.d.ts
index a8180709bab6..d3f994a7125e 100644
--- a/lib/node_modules/@stdlib/assert/is-nonnegative-finite/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/assert/is-nonnegative-finite/docs/types/index.d.ts
@@ -61,19 +61,19 @@ interface IsNonNegativeFinite {
 	* @returns {boolean} boolean indicating if a value is a number primitive having a nonnegative finite value
 	*
 	* @example
-	* var bool = isNonNegativeFinite( 3.0 );
+	* var bool = isNonNegativeFinite.isPrimitive( 3.0 );
 	* // returns true
 	*
 	* @example
-	* var bool = isNonNegativeFinite( new Number( 3.0 ) );
+	* var bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) );
 	* // returns false
 	*
 	* @example
-	* var bool = isNonNegativeFinite( new Number( -5.0 ) );
+	* var bool = isNonNegativeFinite.isPrimitive( new Number( -5.0 ) );
 	* // returns false
 	*
 	* @example
-	* var bool = isNonNegativeFinite( 1.0/0.0 );
+	* var bool = isNonNegativeFinite.isPrimitive( 1.0/0.0 );
 	* // returns false
 	*/
 	isPrimitive( value: any ): boolean;
@@ -85,19 +85,19 @@ interface IsNonNegativeFinite {
 	* @returns {boolean} boolean indicating if a value is a number object having a nonnegative finite number value
 	*
 	* @example
-	* var bool = isNonNegativeFinite( 3.0 );
+	* var bool = isNonNegativeFinite.isObject( 3.0 );
 	* // returns false
 	*
 	* @example
-	* var bool = isNonNegativeFinite( new Number( 3.0 ) );
+	* var bool = isNonNegativeFinite.isObject( new Number( 3.0 ) );
 	* // returns true
 	*
 	* @example
-	* var bool = isNonNegativeFinite( new Number( -5.0 ) );
+	* var bool = isNonNegativeFinite.isObject( new Number( -5.0 ) );
 	* // returns false
 	*
 	* @example
-	* var bool = isNonNegativeFinite( 1.0/0.0 );
+	* var bool = isNonNegativeFinite.isObject( 1.0/0.0 );
 	* // returns false
 	*/
 	isObject( value: any ): boolean;
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/index.js
index b51f9f361da8..1ac6c96a2d81 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/index.js
@@ -104,14 +104,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/main.js
index 0e5d6bb0cbba..e79df1628a6a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/ccopy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var ccopy = new Routine();
 ccopy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( ccopy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/index.js
index e264c8df285c..62c2dec0857e 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/index.js
@@ -110,14 +110,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/main.js
index c2e973d74917..933ded5fc11a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/cscal/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -61,6 +63,7 @@ var Routine = require( './routine.js' );
 */
 var cscal = new Routine();
 cscal.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( cscal, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/index.js
index 562dbd263441..894c782ddcb4 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/index.js
@@ -110,14 +110,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/main.js
index f6698a5f047c..c6e0c1b9ffe1 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/csrot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -56,6 +58,7 @@ var Routine = require( './routine.js' );
 */
 var csrot = new Routine();
 csrot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( csrot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/index.js
index 747f92819637..46c5fc4badc9 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/index.js
@@ -109,14 +109,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/main.js
index 4af3661b2802..be03cdc48e09 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/cswap/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var cswap = new Routine();
 cswap.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( cswap, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/dasum/docs/types/index.d.ts
index 888ff40e1dbd..84cff917ea96 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dasum/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/docs/types/index.d.ts
@@ -218,7 +218,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
 	*
-	* var out = dasum.main( x.length, 5.0, x, 1, y, 1 );
+	* var out = dasum.main( x.length, x, 1 );
 	* // returns 15.0
 	*/
 	main( N: number, x: Float64Array, strideX: number ): number;
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/index.js
index 395ff78be943..8b062cef232a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/main.js
index 4b332108ccb3..f9908617e558 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dasum/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dasum = new Routine();
 dasum.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dasum, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/index.js
index 669e6f7be73d..22fda2de1068 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/index.js
@@ -95,14 +95,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/main.js
index 4c4079ef49e2..d0cd912151fd 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/daxpy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var daxpy = new Routine();
 daxpy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( daxpy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/index.js
index 851f73525049..cbb8b50a5df6 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/index.js
@@ -95,14 +95,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/main.js
index 67a14a191b6d..8ee67c7c6d52 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dcopy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var dcopy = new Routine();
 dcopy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dcopy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/index.js
index 2aeb3f798290..bffeeaf5b030 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/index.js
@@ -91,14 +91,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/main.js
index 29a7738657d5..90a501671d47 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/ddot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var ddot = new Routine();
 ddot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( ddot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/index.js
index 2af43808e29b..977be83cf720 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/main.js
index 03daf61599ee..303371ff16da 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dnrm2/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dnrm2 = new Routine();
 dnrm2.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dnrm2, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/index.js
index 025b08a0a25b..82d19572e7ff 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/index.js
@@ -102,14 +102,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/main.js
index 6a453a5e0f0d..1729154d6558 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/drot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var drot = new Routine();
 drot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( drot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/index.js
index d5c183d93d32..22a324e6ea48 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/index.js
@@ -106,14 +106,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/main.js
index eb901136046c..e902f7651805 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/drotm/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -59,6 +61,7 @@ var Routine = require( './routine.js' );
 */
 var drotm = new Routine();
 drotm.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( drotm, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/index.js
index 6c9a02f02f6b..bc62e804f088 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/index.js
@@ -90,14 +90,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/main.js
index 1cdd04840c31..df44dce4d261 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dscal/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dscal = new Routine();
 dscal.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dscal, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/index.js
index 5e6cc7f730f3..1b3150620a6b 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/index.js
@@ -91,14 +91,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/main.js
index 2effc363916d..a69f60ad0c6a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dsdot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var dsdot = new Routine();
 dsdot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dsdot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dswap/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/dswap/docs/types/index.d.ts
index c2525f09d657..fb53aeede907 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dswap/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dswap/docs/types/index.d.ts
@@ -75,7 +75,7 @@ interface ModuleConstructor {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -132,7 +132,7 @@ interface ModuleConstructor {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -198,7 +198,7 @@ interface Module extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -261,7 +261,7 @@ interface Module extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -369,7 +369,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/index.js
index a99cfcd039f8..9c4c9ecb3eef 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/index.js
@@ -102,14 +102,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/main.js
index e9616c56a760..aa51e3b73fb2 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dswap/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var dswap = new Routine();
 dswap.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dswap, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/docs/types/index.d.ts
index 2342513c4958..c00cb7e38da4 100755
--- a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/docs/types/index.d.ts
@@ -222,7 +222,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* // Perform operation:
 	* var out = dznrm2.main( x.length, x, 1 );
-	* // returns ~9.53
+	* // returns ~9.54
 	*/
 	main( N: number, x: Complex128Array, strideX: number ): number;
 
@@ -242,7 +242,7 @@ interface Routine extends ModuleWrapper {
 	* var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 	*
 	* var out = dznrm2.ndarray( x.length, x, 1, 0 );
-	* // returns ~9.53
+	* // returns ~9.54
 	*/
 	ndarray( N: number, x: Complex128Array, strideX: number, offsetX: number ): number;
 
@@ -303,7 +303,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 *
 * var out = dznrm2.main( x.length, x, 1 );
-* // returns ~9.53
+* // returns ~9.54
 *
 * @example
 * var Complex128Array = require( '@stdlib/array/complex128' );
@@ -312,7 +312,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 *
 * var out = dznrm2.ndarray( x.length, x, 1, 0 );
-* // returns ~9.53
+* // returns ~9.54
 */
 declare var dznrm2: Routine;
 
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/index.js
index 6efb63dc494d..398fed7b9694 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/main.js
index d39f39d4c81f..05873421c599 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/dznrm2/lib/main.js
@@ -21,7 +21,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -54,6 +56,7 @@ var Routine = require( './routine.js' );
 */
 var dznrm2 = new Routine();
 dznrm2.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dznrm2, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/index.js
index 592a244c18ff..46b85ae2feca 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/main.js
index 5edb94c13173..cf2e1e32216a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/idamax/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var idamax = new Routine();
 idamax.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( idamax, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/index.js
index 8e2c77f32cb8..2f655cb4e5bf 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/main.js
index 8439f2adbce8..741d3747c75a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/isamax/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var isamax = new Routine();
 isamax.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( isamax, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/sasum/docs/types/index.d.ts
index b1a7191e73fc..d7c17bc8bf42 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/docs/types/index.d.ts
@@ -218,7 +218,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
 	*
-	* var out = sasum.main( x.length, 5.0, x, 1, y, 1 );
+	* var out = sasum.main( x.length, x, 1 );
 	* // returns 15.0
 	*/
 	main( N: number, x: Float32Array, strideX: number ): number;
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/index.js
index cb04bc490e99..17b57b60c748 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/main.js
index af01f65aa555..e11eb86607a5 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sasum/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var sasum = new Routine();
 sasum.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sasum, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/index.js
index 1e401900486f..5f8931fa2652 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/index.js
@@ -95,14 +95,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/main.js
index c4c3ad28e6d2..916ba6c991e8 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/saxpy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var saxpy = new Routine();
 saxpy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( saxpy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/scasum/docs/types/index.d.ts
index c698c2a3ea7e..392f92b8624c 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/docs/types/index.d.ts
@@ -219,7 +219,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* var x = new Complex64Array( [ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ] );
 	*
-	* var out = scasum.main( x.length, 5.0, x, 1, y, 1 );
+	* var out = scasum.main( x.length, x, 1 );
 	* // returns 19.0
 	*/
 	main( N: number, x: Complex64Array, strideX: number ): number;
@@ -299,7 +299,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex64Array( [ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ] );
 *
 * var out = scasum.main( x.length, x, 1 );
-* // returns 21.0
+* // returns 19.0
 *
 * @example
 * var Complex64Array = require( '@stdlib/array/complex64' );
@@ -307,7 +307,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex64Array( [ 2.0, 1.0, 3.0, 5.0, 4.0, 0.0, 1.0, 3.0 ] );
 *
 * var out = scasum.ndarray( x.length, x, 1, 0 );
-* // returns 21.0
+* // returns 19.0
 */
 declare var scasum: Routine;
 
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/index.js
index 1983babffb38..0f36f8f6f866 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/main.js
index dbaebbbfe3e7..4efa6e3f0307 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scasum/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var scasum = new Routine();
 scasum.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( scasum, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/docs/types/index.d.ts
index 8c52fdbdbcc8..ac0e32abce93 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/docs/types/index.d.ts
@@ -222,7 +222,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* // Perform operation:
 	* var out = scnrm2.main( x.length, x, 1 );
-	* // returns ~9.53
+	* // returns ~9.54
 	*/
 	main( N: number, x: Complex64Array, strideX: number ): number;
 
@@ -242,7 +242,7 @@ interface Routine extends ModuleWrapper {
 	* var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 	*
 	* var out = scnrm2.ndarray( x.length, x, 1, 0 );
-	* // returns ~9.53
+	* // returns ~9.54
 	*/
 	ndarray( N: number, x: Complex64Array, strideX: number, offsetX: number ): number;
 
@@ -303,7 +303,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 *
 * var out = scnrm2.main( x.length, x, 1 );
-* // returns ~9.53
+* // returns ~9.54
 *
 * @example
 * var Complex64Array = require( '@stdlib/array/complex64' );
@@ -312,7 +312,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 *
 * var out = scnrm2.ndarray( x.length, x, 1, 0 );
-* // returns ~9.53
+* // returns ~9.54
 */
 declare var scnrm2: Routine;
 
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/index.js
index d94fe4aea5cd..1e9e183efd6b 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/main.js
index 6b7592f23f38..6c535984a0a4 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scnrm2/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var scnrm2 = new Routine();
 scnrm2.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( scnrm2, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/index.js
index 0766229adbda..1bff5665644b 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/index.js
@@ -95,14 +95,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/main.js
index 098c3fff53fa..6773ee44ceb3 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/scopy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var scopy = new Routine();
 scopy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( scopy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/index.js
index 1ef10fe9ae85..8dff63319a4e 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/index.js
@@ -91,14 +91,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/main.js
index c0c4bfa20bb5..85fd0ca58f2c 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sdot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var sdot = new Routine();
 sdot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sdot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/index.js
index a6249a8f36af..7705e17f34a3 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/index.js
@@ -91,14 +91,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/main.js
index eca8050894cd..2d94bab02b1f 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sdsdot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var sdsdot = new Routine();
 sdsdot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sdsdot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/index.js
index 97ee837ec260..f99376d8cd0b 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/index.js
@@ -82,14 +82,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/main.js
index 0ba55293f373..1b28cd97e807 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/snrm2/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var snrm2 = new Routine();
 snrm2.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( snrm2, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/index.js
index 812dfb48f0de..1e281a3b6902 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/index.js
@@ -102,14 +102,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/main.js
index 493c16777a9c..fb845e0b1b4d 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/srot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var srot = new Routine();
 srot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( srot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/index.js
index 0e89bbda0328..ad6ef839d1a9 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/index.js
@@ -106,14 +106,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/main.js
index 433d471eaf07..48fa60bdd655 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/srotm/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -59,6 +61,7 @@ var Routine = require( './routine.js' );
 */
 var srotm = new Routine();
 srotm.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( srotm, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/index.js
index 22580729f80e..62515c32caad 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/index.js
@@ -91,14 +91,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/main.js
index ff0806b6f5e5..98c327c7f9d4 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sscal/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var sscal = new Routine();
 sscal.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sscal, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/base/wasm/sswap/docs/types/index.d.ts
index f2fe05c7f591..b598600423c8 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/docs/types/index.d.ts
@@ -75,7 +75,7 @@ interface ModuleConstructor {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float32Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -132,7 +132,7 @@ interface ModuleConstructor {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float32Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -198,7 +198,7 @@ interface Module extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float32Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -261,7 +261,7 @@ interface Module extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float32Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
@@ -369,7 +369,7 @@ interface Routine extends ModuleWrapper {
 	*
 	* // Read out the results:
 	* var viewX = zeros( N, dtype );
-	* var viewY = zeros( n, dtype );
+	* var viewY = zeros( N, dtype );
 	* mod.read( xptr, viewX )
 	* mod.read( yptr, viewY );
 	* // viewX => <Float32Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/index.js
index d44d75f1353c..b3fbf2322d9a 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/index.js
@@ -102,14 +102,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/main.js
index dbbb3399fe73..d1b3460ed72b 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/sswap/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var sswap = new Routine();
 sswap.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sswap, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/index.js
index 9927b50990dd..6bbb01e69509 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/index.js
@@ -105,14 +105,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js
index cfbba68e6a70..6ae4f62ca77e 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zcopy/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var zcopy = new Routine();
 zcopy.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( zcopy, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js
index 94cf1e6a6d0c..ca25ee4f12fa 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/index.js
@@ -109,14 +109,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js
index 8232c4815919..f0812e2d9938 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zdrot/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var zdrot = new Routine();
 zdrot.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( zdrot, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/index.js
index 9094828f0e18..19e150840325 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/index.js
@@ -110,14 +110,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/main.js
index f553595b14a8..46609374ad3e 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zscal/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -61,6 +63,7 @@ var Routine = require( './routine.js' );
 */
 var zscal = new Routine();
 zscal.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( zscal, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/index.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/index.js
index bff9fe8760be..71fe3ac5406d 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/index.js
@@ -109,14 +109,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/main.js b/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/main.js
index df1f1b15abc2..364229a80466 100644
--- a/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/base/wasm/zswap/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -57,6 +59,7 @@ var Routine = require( './routine.js' );
 */
 var zswap = new Routine();
 zswap.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( zswap, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/README.md b/lib/node_modules/@stdlib/blas/ext/README.md
index b6fac8b84b21..36d60cf0b125 100644
--- a/lib/node_modules/@stdlib/blas/ext/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/README.md
@@ -50,7 +50,11 @@ The namespace contains the following:
 -   <span class="signature">[`findIndex( x[, options], clbk[, thisArg] )`][@stdlib/blas/ext/find-index]</span><span class="delimiter">: </span><span class="description">return the index of the first element along an ndarray dimension which passes a test implemented by a predicate function.</span>
 -   <span class="signature">[`findLastIndex( x[, options], clbk[, thisArg] )`][@stdlib/blas/ext/find-last-index]</span><span class="delimiter">: </span><span class="description">return the index of the last element along an ndarray dimension which passes a test implemented by a predicate function.</span>
 -   <span class="signature">[`indexOf( x, searchElement[, fromIndex][, options] )`][@stdlib/blas/ext/index-of]</span><span class="delimiter">: </span><span class="description">return the first index of a specified search element along an ndarray dimension.</span>
+-   <span class="signature">[`lastIndexOf( x, searchElement[, fromIndex][, options] )`][@stdlib/blas/ext/last-index-of]</span><span class="delimiter">: </span><span class="description">return the last index of a specified search element along an ndarray dimension.</span>
+-   <span class="signature">[`linspace( shape, start, stop[, endpoint][, options] )`][@stdlib/blas/ext/linspace]</span><span class="delimiter">: </span><span class="description">return a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.</span>
+-   <span class="signature">[`sorthp( x[, sortOrder][, options] )`][@stdlib/blas/ext/sorthp]</span><span class="delimiter">: </span><span class="description">sort an input ndarray along one or more ndarray dimensions using heapsort.</span>
 -   <span class="signature">[`sum( x[, options] )`][@stdlib/blas/ext/sum]</span><span class="delimiter">: </span><span class="description">compute the sum along one or more ndarray dimensions.</span>
+-   <span class="signature">[`toSortedhp( x[, sortOrder][, options] )`][@stdlib/blas/ext/to-sortedhp]</span><span class="delimiter">: </span><span class="description">return a new ndarray containing the elements of an input ndarray sorted along one or more ndarray dimensions using heapsort.</span>
 
 </div>
 
@@ -103,8 +107,16 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/ext/index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/index-of
 
+[@stdlib/blas/ext/last-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/last-index-of
+
+[@stdlib/blas/ext/linspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/linspace
+
+[@stdlib/blas/ext/sorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/sorthp
+
 [@stdlib/blas/ext/sum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/sum
 
+[@stdlib/blas/ext/to-sortedhp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/to-sortedhp
+
 <!-- </toc-links> -->
 
 </section>
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md b/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md
new file mode 100644
index 000000000000..16561a6f74a3
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/README.md
@@ -0,0 +1,339 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# drrss
+
+> Calculate the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] of two double-precision floating-point strided arrays.
+
+<section class="intro">
+
+The square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] is defined as
+
+<!-- <equation class="equation" label="eq:sqrt_of_residual_sum_of_squares" align="center" raw="d = \sqrt{\sum_{i=0}^{N-1} (y_i - x_i)^2}" alt="Equation for the square root of residual sum of squares."> -->
+
+```math
+d = \sqrt{\sum_{i=0}^{N-1} (y_i - x_i)^2}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="d = \sqrt{\sum_{i=0}^{N-1} (y_i - x_i)^2}" data-equation="eq:sqrt_of_residual_sum_of_squares">
+    <img src="" alt="Square root of residual sum of squares.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var drrss = require( '@stdlib/blas/ext/base/drrss' );
+```
+
+#### drrss( N, x, strideX, y, strideY )
+
+Computes the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] of two double-precision floating-point strided arrays.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+var y = new Float64Array( [ 1.0, 1.0, -4.0 ] );
+
+var z = drrss( x.length, x, 1, y, 1 );
+// returns ~6.7
+```
+
+The function has the following parameters:
+
+-   **N**: number of indexed elements.
+-   **x**: first input [`Float64Array`][@stdlib/array/float64].
+-   **strideX**: stride length for `x`.
+-   **y**: second input [`Float64Array`][@stdlib/array/float64].
+-   **strideY**: stride length for `y`.
+
+The `N` and stride parameters determine which elements in strided arrays are accessed at runtime. For example, to compute the [residual sum of squares][wikipedia-residual-sum-of-squares] of every other element in `x` and `y`
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+
+var z = drrss( x.length, x, 1, y, 1 );
+// returns ~8.485
+```
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+<!-- eslint-disable stdlib/capitalized-comments -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+var y0 = new Float64Array( [ 8.0, -2.0, 3.0, -2.0, 7.0, -2.0, 0.0, -1.0 ] );
+
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+var z = drrss( 4, x1, 2, y1, 2 );
+// returns ~7.071
+```
+
+If `N` is less than or equal to `0`, the function returns `0`.
+
+#### drrss.ndarray( N, x, strideX, offsetX,  y, strideY, offsetY )
+
+Computes the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] of two double-precision floating-point strided arrays using alternative indexing semantics.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+var y = new Float64Array( [ 1.0, 1.0, -4.0 ] );
+
+var z = drrss.ndarray( x.length, x, 1, 0, y, 1, 0 );
+// returns ~6.7
+```
+
+The function has the following additional parameters:
+
+-   **offsetX**: starting index for `x`.
+-   **offsetY**: starting index for `y`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] for every other element in `x` and `y` starting from the second element
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 6.0 ] );
+var y = new Float64Array( [ 8.0, -2.0, 3.0, -2.0, 7.0, -2.0, 0.0, -1.0, 4.0 ] );
+
+var z = drrss.ndarray( 4, x, 2, 1, y, 2, 1 );
+// returns ~7.071
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If `N <= 0`, both functions return `0.0`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var drrss = require( '@stdlib/blas/ext/base/drrss' );
+
+var opts = {
+    'dtype': 'float64'
+};
+var x = discreteUniform( 10, -50, 50, opts );
+console.log( x );
+
+var y = discreteUniform( 10, -50, 50, opts );
+console.log( y );
+
+var d = drrss( x.length, x, 1, y, 1 );
+console.log( d );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/blas/ext/base/drrss.h"
+```
+
+#### stdlib_strided_drrss( N, \*X, strideX, \*Y, strideY )
+
+Computes the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] of two double-precision floating-point strided arrays.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+const double y[] = { 1.0, 1.0, -4.0 };
+
+double z = stdlib_strided_drrss( 3, x, 1, y, 1 );
+// returns ~6.7
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` first input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Y**: `[in] double*` second input array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+
+```c
+double stdlib_strided_drrss( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY );
+```
+
+<!--lint ignore maximum-heading-length-->
+
+#### stdlib_strided_drrss_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+
+<!--lint enable maximum-heading-length-->
+
+Computes the square root of the [residual sum of squares][wikipedia-residual-sum-of-squares] of two double-precision floating-point strided arrays using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, -2.0, 2.0 };
+const double y[] = { 1.0, 1.0, -4.0 };
+
+double v = stdlib_strided_drrss_ndarray( 3, x, 1, 0, 1, 0 );
+// returns ~6.7
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` first input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Y**: `[in] double*` second input array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.
+
+```c
+double stdlib_strided_drrss_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/blas/ext/base/drrss.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create two strided arrays:
+    const double x[] = { 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 };
+    const double y[] = { 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 1;
+    const int strideY = 1;
+
+    // Compute the square root of the residual sum of squares of `x` and `y`:
+    double d = stdlib_strided_drrss( N, x, strideX, y, strideY );
+
+    // Print the result:
+    printf( "drrss: %lf\n", d );
+
+    // Specify index offsets:
+    const int offsetX = 1;
+    const int offsetY = 1;
+
+    // Compute the square root of the residual sum of squares of `x` and `y` with offsets:
+    d = stdlib_strided_drrss_ndarray( N, x, strideX, offsetX, y, strideY, offsetY );
+
+    // Print the result:
+    printf( "drrss: %lf\n", d );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[wikipedia-residual-sum-of-squares]: https://en.wikipedia.org/wiki/Residual_sum_of_squares
+
+[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.js
new file mode 100644
index 000000000000..fe696128e3b0
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.js
@@ -0,0 +1,97 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var drrss = require( './../lib/drrss.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -100.0, 100.0, options );
+	var y = uniform( len, -100.0, 100.0, options );
+	return benchmark;
+
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = drrss( x.length, x, 1, y, 1 );
+			if ( isnan( d ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( d ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..14573e81bcb7
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.native.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var drrss = tryRequire( resolve( __dirname, './../lib/drrss.native.js' ) );
+var opts = {
+	'skip': ( drrss instanceof Error )
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -100.0, 100.0, options );
+	var y = uniform( len, -100.0, 100.0, options );
+	return benchmark;
+
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = drrss( x.length, x, 1, y, 1 );
+			if ( isnan( d ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( d ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+'::native:len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..77a6f66b5e1e
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.js
@@ -0,0 +1,97 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var drrss = require( './../lib/ndarray.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -100.0, 100.0, options );
+	var y = uniform( len, -100.0, 100.0, options );
+	return benchmark;
+
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = drrss( x.length, x, 1, 0, y, 1, 0 );
+			if ( isnan( d ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( d ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':ndarray:len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.native.js
new file mode 100644
index 000000000000..ccba9b89952d
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/benchmark.ndarray.native.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var drrss = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+	'skip': ( drrss instanceof Error )
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -100.0, 100.0, options );
+	var y = uniform( len, -100.0, 100.0, options );
+	return benchmark;
+
+	function benchmark( b ) {
+		var d;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			d = drrss( x.length, x, 1, 0, y, 1, 0 );
+			if ( isnan( d ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( d ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+'::native:ndarray:len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/Makefile
new file mode 100644
index 000000000000..cce2c865d7ad
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.length.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/benchmark.length.c
new file mode 100644
index 000000000000..3ee7ff290b56
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/benchmark/c/benchmark.length.c
@@ -0,0 +1,201 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/blas/ext/base/drrss.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "drrss"
+#define ITERATIONS 1000000
+#define REPEATS 3
+#define MIN 1
+#define MAX 6
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param iterations  number of iterations
+* @param elapsed     elapsed time in seconds
+*/
+static void print_results( int iterations, double elapsed ) {
+	double rate = (double)iterations / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", iterations );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [0,1).
+*
+* @return random number
+*/
+static double rand_double( void ) {
+	int r = rand();
+	return (double)r / ( (double)RAND_MAX + 1.0 );
+}
+
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark1( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double y[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		y[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_drrss( len, x, 1, y, 1 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double y[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		y[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_drrss_ndarray( len, x, 1, 0, y, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int count;
+	int iter;
+	int len;
+	int i;
+	int j;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	count = 0;
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:len=%d\n", NAME, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	print_summary( count, count );
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/binding.gyp b/lib/node_modules/@stdlib/blas/ext/base/drrss/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/repl.txt
new file mode 100644
index 000000000000..5c50b5768108
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/repl.txt
@@ -0,0 +1,112 @@
+
+{{alias}}( N, x, strideX, y, strideY )
+    Computes the square root of the residual sum of squares of two double-
+    precision floating-point strided arrays.
+
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
+
+    Indexing is relative to the first index. To introduce an offset, use a typed
+    array view.
+
+    If `N <= 0`, the function returns `0`.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    x: Float64Array
+        First input array.
+
+    strideX: integer
+        Stride length of `x`.
+
+    y: Float64Array
+        Second input array.
+
+    strideY: integer
+        Stride length of `y`.
+
+    Returns
+    -------
+    out: number
+        Square root of the residual sum of squares.
+
+    Examples
+    --------
+    // Standard Usage:
+    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+    > var y = new {{alias:@stdlib/array/float64}}( [ 1.0, 1.0, -4.0 ] );
+    > {{alias}}( x.length, x, 1, y, 1 )
+    ~6.7
+
+    // Using `N` and `stride` parameters:
+    > x = new {{alias:@stdlib/array/float64}}( [ 1.0, 2.0, 2.0, -7.0, -2.0 ] );
+    > y = new {{alias:@stdlib/array/float64}}( [ 2.0, 1.0, 2.0, 1.0, -2.0 ] );
+    > {{alias}}( 3, x, 2, y, 2 )
+    1.0
+
+    // Using view offsets:
+    > var x0 = new {{alias:@stdlib/array/float64}}( [ 2.0, 1.0, 2.0, -2.0 ] );
+    > var y0 = new {{alias:@stdlib/array/float64}}( [ 8.0, -2.0, 3.0, -2.0 ] );
+    > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+    > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*1 );
+    > {{alias}}( 2, x1, 2, y1, 2 )
+    3
+
+
+{{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
+    Computes the square root of the residual sum of squares of two double-
+    precision floating-point strided arrays using alternative indexing
+    semantics.
+
+    While typed array views mandate a view offset based on the underlying
+    buffer, the offset parameters support indexing semantics based on starting
+    indices.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    x: Float64Array
+        First input array.
+
+    strideX: integer
+        Stride length of `x`.
+
+    offsetX: integer
+        Starting index of `x`.
+
+    y: Float64Array
+        Second input array.
+
+    strideY: integer
+        Stride length of `y`.
+
+    offsetY: integer
+        Starting index of `y`.
+
+    Returns
+    -------
+    out: number
+        Square root of the residual sum of squares.
+
+    Examples
+    --------
+    // Standard Usage:
+    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, -4.0, 5.0 ] );
+    > var y = new {{alias:@stdlib/array/float64}}( [ 5.0, 12.0, -8.0, 15.0 ] );
+    > {{alias}}.ndarray( x.length, x, 1, 0, y, 1, 0 )
+    ~18.11
+
+    // Using offset parameters:
+    > x = new {{alias:@stdlib/array/float64}}([ 2.0, 1.0,  2.0, -2.0 ]);
+    > y = new {{alias:@stdlib/array/float64}}([ 8.0, -2.0, 3.0, -2.0 ]);
+    > {{alias}}.ndarray( 2, x, 2, 1, y, 2, 1 )
+    3
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/index.d.ts
new file mode 100644
index 000000000000..fbef70b0053f
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/index.d.ts
@@ -0,0 +1,105 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Interface describing `drrss`.
+*/
+interface Routine {
+	/**
+	* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - stride length of `x`
+	* @param y - second input array
+	* @param strideY - stride length of `y`
+	* @returns square root of the residual sum of squares
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = drrss( x.length, x, 1, y, 1 );
+	* // returns ~8.485
+	*/
+	( N: number, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number;
+
+	/**
+	* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays using alternative indexing semantics.
+	*
+	* @param N - number of indexed elements
+	* @param x - first input array
+	* @param strideX - stride length of `x`
+	* @param offsetX - starting index of `x`
+	* @param y - second input array
+	* @param strideY - stride length of `y`
+	* @param offsetY - starting index of `y`
+	* @returns square root of the residual sum of squares
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+	* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var z = drrss.ndarray( x.length, x, 1, 0, y, 1, 0 );
+	* // returns ~8.485
+	*/
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number;
+}
+
+/**
+* Compute the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param N - number of indexed elements
+* @param x - first input array
+* @param strideX - stride length of `x`
+* @param y - second input array
+* @param strideY - stride length of `y`
+* @returns square root of the residual sum of squares
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var drrss = require( '@stdlib/blas/ext/base/drrss' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var y = new Float64Array( [ 1.0, 1.0, -4.0 ] );
+*
+* var out = drrss( x.length, x, 1, y, 1 );
+* // returns ~6.7
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var drrss = require( '@stdlib/blas/ext/base/drrss' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss.ndarray( x.length, x, 1, 0, y, 1, 0 );
+* // returns ~8.485
+*/
+declare var drrss: Routine;
+
+
+// EXPORTS //
+
+export = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/test.ts
new file mode 100644
index 000000000000..1704c8c84d9a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/docs/types/test.ts
@@ -0,0 +1,245 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import drrss = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss( x.length, x, 1, y, 1 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss( '10', x, 1, y, 1 ); // $ExpectError
+	drrss( true, x, 1, y, 1 ); // $ExpectError
+	drrss( false, x, 1, y, 1 ); // $ExpectError
+	drrss( null, x, 1, y, 1 ); // $ExpectError
+	drrss( undefined, x, 1, y, 1 ); // $ExpectError
+	drrss( [], x, 1, y, 1 ); // $ExpectError
+	drrss( {}, x, 1, y, 1 ); // $ExpectError
+	drrss( ( x: number ): number => x, x, 1, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss( x.length, 10, 1, y, 1 ); // $ExpectError
+	drrss( x.length, '10', 1, y, 1 ); // $ExpectError
+	drrss( x.length, true, 1, y, 1 ); // $ExpectError
+	drrss( x.length, false, 1, y, 1 ); // $ExpectError
+	drrss( x.length, null, 1, y, 1 ); // $ExpectError
+	drrss( x.length, undefined, 1, y, 1 ); // $ExpectError
+	drrss( x.length, [], 1, y, 1 ); // $ExpectError
+	drrss( x.length, {}, 1, y, 1 ); // $ExpectError
+	drrss( x.length, ( x: number ): number => x, 1, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss( x.length, x, '10', y, 1 ); // $ExpectError
+	drrss( x.length, x, true, y, 1 ); // $ExpectError
+	drrss( x.length, x, false, y, 1 ); // $ExpectError
+	drrss( x.length, x, null, y, 1 ); // $ExpectError
+	drrss( x.length, x, undefined, y, 1 ); // $ExpectError
+	drrss( x.length, x, [], y, 1 ); // $ExpectError
+	drrss( x.length, x, {}, y, 1 ); // $ExpectError
+	drrss( x.length, x, ( x: number ): number => x, y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+
+	drrss( x.length, x, 1, '10', 1 ); // $ExpectError
+	drrss( x.length, x, 1, true, 1 ); // $ExpectError
+	drrss( x.length, x, 1, false, 1 ); // $ExpectError
+	drrss( x.length, x, 1, null, 1 ); // $ExpectError
+	drrss( x.length, x, 1, undefined, 1 ); // $ExpectError
+	drrss( x.length, x, 1, [], 1 ); // $ExpectError
+	drrss( x.length, x, 1, {}, 1 ); // $ExpectError
+	drrss( x.length, x, 1, ( y: number ): number => y, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fifth argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss( x.length, x, 1, y, '10' ); // $ExpectError
+	drrss( x.length, x, 1, y, true ); // $ExpectError
+	drrss( x.length, x, 1, y, false ); // $ExpectError
+	drrss( x.length, x, 1, y, null ); // $ExpectError
+	drrss( x.length, x, 1, y, undefined ); // $ExpectError
+	drrss( x.length, x, 1, y, [] ); // $ExpectError
+	drrss( x.length, x, 1, y, {} ); // $ExpectError
+	drrss( x.length, x, 1, y, ( y: number ): number => y ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss(); // $ExpectError
+	drrss( x.length ); // $ExpectError
+	drrss( x.length, x ); // $ExpectError
+	drrss( x.length, x, 1, y ); // $ExpectError
+	drrss( x.length, x, 1, y, 1, 10 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, x, 1, 0, y, 1, 0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( '10', x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( true, x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( false, x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( null, x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( undefined, x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( [], x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( {}, x, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( ( x: number ): number => x, x, 1, 0, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, 10, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, '10', 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, true, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, false, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, null, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, undefined, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, [], 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, {}, 1, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, x, '10', 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, true, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, false, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, null, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, undefined, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, [], 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, {}, 0, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, x, 1, '10', y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, true, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, false, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, null, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, undefined, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, [], y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, {}, y, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+
+	drrss.ndarray( x.length, x, 1, 0, 10, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, '10', 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, true, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, false, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, null, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, undefined, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, [], 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, {}, 1, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, x, 1, 0, y, '10', 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, true, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, false, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, null, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, undefined, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, [], 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, {}, 0 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray( x.length, x, 1, 0, y, 1, '10' ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, true ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, false ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, null ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, undefined ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, [] ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, {} ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
+{
+	const x = new Float64Array( 10 );
+	const y = new Float64Array( 20 );
+
+	drrss.ndarray(); // $ExpectError
+	drrss.ndarray( x.length ); // $ExpectError
+	drrss.ndarray( x.length, x ); // $ExpectError
+	drrss.ndarray( x.length, x, 1 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1 ); // $ExpectError
+	drrss.ndarray( x.length, x, 1, 0, y, 1, 0, 10 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/Makefile b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/example.c b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/example.c
new file mode 100644
index 000000000000..5b75a2e3649f
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/c/example.c
@@ -0,0 +1,49 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/blas/ext/base/drrss.h"
+#include <stdio.h>
+
+int main( void ) {
+	// Create two strided arrays:
+	const double x[] = { 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 };
+	const double y[] = { 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 };
+
+	// Specify the number of elements:
+	const int N = 5;
+
+	// Specify the stride lengths:
+	const int strideX = 1;
+	const int strideY = 1;
+
+	// Compute the square root of the residual sum of squares of `x` and `y`:
+	double d = stdlib_strided_drrss( N, x, strideX, y, strideY );
+
+	// Print the result:
+	printf( "drrss: %lf\n", d );
+
+	// Specify index offsets:
+	const int offsetX = 1;
+	const int offsetY = 1;
+
+	// Compute the square root of the residual sum of squares of `x` and `y` with offsets:
+	d = stdlib_strided_drrss_ndarray( N, x, strideX, offsetX, y, strideY, offsetY );
+
+	// Print the result:
+	printf( "drrss: %lf\n", d );
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/index.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/index.js
new file mode 100644
index 000000000000..c60697e0b78a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/examples/index.js
@@ -0,0 +1,34 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var drrss = require( './../lib' );
+
+var opts = {
+	'dtype': 'float64'
+};
+var x = discreteUniform( 10, -50, 50, opts );
+console.log( x );
+
+var y = discreteUniform( 10, -50, 50, opts );
+console.log( y );
+
+var d = drrss( x.length, x, 1, y, 1 );
+console.log( d );
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/include.gypi b/lib/node_modules/@stdlib/blas/ext/base/drrss/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/include/stdlib/blas/ext/base/drrss.h b/lib/node_modules/@stdlib/blas/ext/base/drrss/include/stdlib/blas/ext/base/drrss.h
new file mode 100644
index 000000000000..cfa177b89543
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/include/stdlib/blas/ext/base/drrss.h
@@ -0,0 +1,46 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_BLAS_EXT_BASE_DRRSS_H
+#define STDLIB_BLAS_EXT_BASE_DRRSS_H
+
+#include "stdlib/blas/base/shared.h"
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*/
+double API_SUFFIX(stdlib_strided_drrss)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY );
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_drrss_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_BLAS_EXT_BASE_DRRSS_H
+
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.js
new file mode 100644
index 000000000000..8cdc57ec4b6a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.js
@@ -0,0 +1,57 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {Float64Array} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @returns {number} square root of the residual sum of squares
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss( x.length, x, 1, y, 1 );
+* // returns ~8.485
+*/
+function drrss( N, x, strideX, y, strideY ) {
+	var ox = stride2offset( N, strideX );
+	var oy = stride2offset( N, strideY );
+	return ndarray( N, x, strideX, ox, y, strideY, oy );
+}
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.native.js
new file mode 100644
index 000000000000..e58f2039b6bb
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/drrss.native.js
@@ -0,0 +1,54 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {Float64Array} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @returns {number} square root of the residual sum of squares
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss( x.length, x, 1, y, 1 );
+* // returns ~8.485
+*/
+function drrss( N, x, strideX, y, strideY ) {
+	return addon( N, x, strideX, y, strideY );
+}
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/index.js
new file mode 100644
index 000000000000..cb94af2eb3df
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/index.js
@@ -0,0 +1,70 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @module @stdlib/blas/ext/base/drrss
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var drrss = require( '@stdlib/blas/ext/base/drrss' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+* var y = new Float64Array( [ 1.0, 1.0, -4.0 ] );
+*
+* var out = drrss( x.length, x, 1, y, 1 );
+* // returns ~6.7
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var drrss = require( '@stdlib/blas/ext/base/drrss' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss.ndarray( x.length, x, 1, 0, y, 1, 0 );
+* // returns ~8.485
+*/
+
+// MODULES //
+
+var join = require( 'path' ).join;
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isError = require( '@stdlib/assert/is-error' );
+var main = require( './main.js' );
+
+
+// MAIN //
+
+var drrss;
+var tmp = tryRequire( join( __dirname, './native.js' ) );
+if ( isError( tmp ) ) {
+	drrss = main;
+} else {
+	drrss = tmp;
+}
+
+
+// EXPORTS //
+
+module.exports = drrss;
+
+// exports: { "ndarray": "drrss.ndarray" }
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/main.js
new file mode 100644
index 000000000000..2a21895b8b82
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/main.js
@@ -0,0 +1,35 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var drrss = require( './drrss.js' );
+var ndarray = require( './ndarray.js' );
+
+
+// MAIN //
+
+setReadOnly( drrss, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/native.js
new file mode 100644
index 000000000000..8f94c2bc25bc
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/native.js
@@ -0,0 +1,35 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var drrss = require( './drrss.native.js' );
+var ndarray = require( './ndarray.native.js' );
+
+
+// MAIN //
+
+setReadOnly( drrss, 'ndarray', ndarray );
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.js
new file mode 100644
index 000000000000..74a5241e4452
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.js
@@ -0,0 +1,143 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var FLOAT64_MAX = require( '@stdlib/constants/float64/max' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var abs2 = require( '@stdlib/math/base/special/abs2' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+
+
+// VARIABLES //
+
+// Blue's scaling constants:
+var tsml = 1.4916681462400413E-154;
+var tbig = 1.9979190722022350E+146;
+var ssml = 4.4989137945431964E+161;
+var sbig = 1.1113793747425387E-162;
+
+
+// MAIN //
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {NonNegativeInteger} offsetX - starting index of `x`
+* @param {Float64Array} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @param {NonNegativeInteger} offsetY - starting index of `y`
+* @returns {number} square root of the residual sum of squares
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss( x.length, x, 1, 0, y, 1, 0 );
+* // returns ~8.485
+*/
+function drrss( N, x, strideX, offsetX, y, strideY, offsetY ) {
+	var notbig;
+	var sumsq;
+	var abig;
+	var amed;
+	var asml;
+	var ymax;
+	var ymin;
+	var scl;
+	var az;
+	var ix;
+	var iy;
+	var i;
+
+	if ( N <= 0 ) {
+		return 0.0;
+	}
+	ix = offsetX;
+	iy = offsetY;
+
+	// Initialize loop values for accumulation:
+	notbig = true;
+
+	sumsq = 0.0;
+	abig = 0.0;
+	amed = 0.0;
+	asml = 0.0;
+	scl = 1.0;
+
+	// Compute the sum of squares using 3 accumulators--`abig` (sum of squares scaled down to avoid overflow), `asml` (sum of squares scaled up to avoid underflow), `amed` (sum of squares that do not require scaling)--and thresholds and multipliers--`tbig` (values bigger than this are scaled down by `sbig`) and `tsml` (values smaller than this are scaled up by `ssml`)...
+	for ( i = 0; i < N; i++ ) {
+		az = abs( x[ ix ] - y[ iy ] );
+		if ( az > tbig ) {
+			abig += abs2( az * sbig );
+			notbig = false;
+		} else if ( az < tsml ) {
+			if ( notbig ) {
+				asml += abs2( az * ssml );
+			}
+		} else {
+			amed += ( az * az );
+		}
+		ix += strideX;
+		iy += strideY;
+	}
+	// Combine `abig` and `amed` or `amed` and `asml` if more than one accumulator was used...
+	if ( abig > 0.0 ) {
+		// Combine `abig` and `amed` if `abig` > 0...
+		if ( amed > 0.0 || ( amed > FLOAT64_MAX ) || ( amed !== amed ) ) {
+			abig += ( ( amed * sbig ) * sbig );
+		}
+		scl = 1.0 / sbig;
+		sumsq = abig;
+	} else if ( asml > 0.0 ) {
+		// Combine `amed` and `asml` if `asml` > 0...
+		if ( amed > 0.0 || amed > FLOAT64_MAX || ( amed !== amed ) ) {
+			amed = sqrt( amed );
+			asml = sqrt( asml ) / ssml;
+			if ( asml > amed ) {
+				ymin = amed;
+				ymax = asml;
+			} else {
+				ymin = asml;
+				ymax = amed;
+			}
+			scl = 1.0;
+			sumsq = ( ymax * ymax ) * ( 1.0 + abs2( ymin / ymax ) );
+		} else {
+			scl = 1.0 / ssml;
+			sumsq = asml;
+		}
+	} else {
+		// All values are mid-range...
+		scl = 1.0;
+		sumsq = amed;
+	}
+	return sqrt( sumsq ) * scl;
+}
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.native.js
new file mode 100644
index 000000000000..dad44f2b3b42
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/lib/ndarray.native.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - first input array
+* @param {integer} strideX - stride length of `x`
+* @param {NonNegativeInteger} offsetX - starting index of `x`
+* @param {Float64Array} y - second input array
+* @param {integer} strideY - stride length of `y`
+* @param {NonNegativeInteger} offsetY - starting index of `y`
+* @returns {number} square root of the residual sum of squares
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+* var y = new Float64Array( [ 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var z = drrss( x.length, x, 1, 0, y, 1, 0 );
+* // returns ~8.485
+*/
+function drrss( N, x, strideX, offsetX, y, strideY, offsetY ) {
+	return addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY );
+}
+
+
+// EXPORTS //
+
+module.exports = drrss;
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/drrss/manifest.json
new file mode 100644
index 000000000000..a4a42d366f2d
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/manifest.json
@@ -0,0 +1,115 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/special/abs2",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/max",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float64array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/special/abs2",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/max"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/special/abs2",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/max"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/special/abs2",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/max"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/package.json b/lib/node_modules/@stdlib/blas/ext/base/drrss/package.json
new file mode 100644
index 000000000000..d9735ac13d9c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/package.json
@@ -0,0 +1,81 @@
+{
+  "name": "@stdlib/blas/ext/base/drrss",
+  "version": "0.0.0",
+  "description": "Compute the square root of the residual sum of squares of two double-precision floating-point strided arrays.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "browser": "./lib/main.js",
+  "gypfile": true,
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "include": "./include",
+    "lib": "./lib",
+    "src": "./src",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "mathematics",
+    "math",
+    "blas",
+    "extended",
+    "square root",
+    "sqrt",
+    "residual",
+    "residuals",
+    "sum",
+    "squares",
+    "drrss",
+    "rrss",
+    "rss",
+    "strided",
+    "array",
+    "ndarray",
+    "float64",
+    "double",
+    "float64array"
+  ],
+  "__stdlib__": {
+    "wasm": false
+  }
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/src/Makefile b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/src/addon.c b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/addon.c
new file mode 100644
index 000000000000..a9203a15084c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/blas/ext/base/drrss.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data_
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_drrss)( N, X, strideX, Y, strideY ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, API_SUFFIX(stdlib_strided_drrss_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method );
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/src/main.c b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/main.c
new file mode 100644
index 000000000000..45b19650492c
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/src/main.c
@@ -0,0 +1,136 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/blas/ext/base/drrss.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/math/base/special/abs2.h"
+#include "stdlib/math/base/special/abs.h"
+#include "stdlib/math/base/special/sqrt.h"
+#include "stdlib/constants/float64/max.h"
+#include "stdlib/strided/base/stride2offset.h"
+#include <stdbool.h>
+
+// Blue's scaling constants...
+static const double tsml = 1.4916681462400413E-154;
+static const double tbig = 1.9979190722022350E+146;
+static const double ssml = 4.4989137945431964E+161;
+static const double sbig = 1.1113793747425387E-162;
+
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays.
+*
+* @param N            number of indexed elements
+* @param X            first input array
+* @param strideX      stride length of `X`
+* @param Y            second input array
+* @param strideY      stride length of `Y`
+* @return             output value
+*/
+double API_SUFFIX(stdlib_strided_drrss)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const double *Y, const CBLAS_INT strideY ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY );
+	return API_SUFFIX(stdlib_strided_drrss_ndarray)( N, X, strideX, ox, Y, strideY, oy );
+}
+
+/**
+* Computes the square root of the residual sum of squares of two double-precision floating-point strided arrays using alternative indexing semantics.
+*
+* @param N            number of indexed elements
+* @param X            first input array
+* @param strideX      stride length of `X`
+* @param offsetX      starting index for X
+* @param Y            second input array
+* @param strideY      stride length of `Y`
+* @param offsetY      starting index for Y
+* @return             output value
+*/
+double API_SUFFIX(stdlib_strided_drrss_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) {
+	CBLAS_INT ix;
+	CBLAS_INT iy;
+	double sumsq;
+	bool notbig;
+	CBLAS_INT i;
+	double abig;
+	double amed;
+	double asml;
+	double ymax;
+	double ymin;
+	double scl;
+	double az;
+
+	if ( N <= 0 ) {
+		return 0.0;
+	}
+	ix = offsetX;
+	iy = offsetY;
+
+	// Compute the sum of squares using 3 accumulators--`abig` (sum of squares scaled down to avoid overflow), `asml` (sum of squares scaled up to avoid underflow), `amed` (sum of squares that do not require scaling)--and thresholds and multipliers--`tbig` (values bigger than this are scaled down by `sbig`) and `tsml` (values smaller than this are scaled up by `ssml`)...
+	notbig = true;
+	sumsq = 0.0;
+	abig = 0.0;
+	amed = 0.0;
+	asml = 0.0;
+	for ( i = 0; i < N; i++ ) {
+		az = stdlib_base_abs( X[ ix ] - Y[ iy ] );
+		if ( az > tbig ) {
+			abig += stdlib_base_abs2( az * sbig );
+			notbig = false;
+		} else if ( az < tsml ) {
+			if ( notbig ) {
+				asml += stdlib_base_abs2( az * ssml );
+			}
+		} else {
+			amed += stdlib_base_abs2( az );
+		}
+		ix += strideX;
+		iy += strideY;
+	}
+	// Combine `abig` and `amed` or `amed` and `asml` if more than one accumulator was used...
+	if ( abig > 0.0 ) {
+		// Combine `abig` and `amed` if `abig` > 0...
+		if ( amed > 0.0 || ( amed > STDLIB_CONSTANT_FLOAT64_MAX ) || ( amed != amed ) ) {
+			abig += ( amed * sbig ) * sbig;
+		}
+		scl = 1.0 / sbig;
+		sumsq = abig;
+	} else if ( asml > 0.0 ) {
+		// Combine `amed` and `asml` if `asml` > 0...
+		if ( amed > 0.0 || amed > STDLIB_CONSTANT_FLOAT64_MAX || ( amed != amed ) ) {
+			amed = stdlib_base_sqrt( amed );
+			asml = stdlib_base_sqrt( asml ) / ssml;
+			if ( asml > amed ) {
+				ymin = amed;
+				ymax = asml;
+			} else {
+				ymin = asml;
+				ymax = amed;
+			}
+			scl = 1.0;
+			sumsq = stdlib_base_abs2( ymax ) * ( 1.0 + stdlib_base_abs2( ymin / ymax ) );
+		} else {
+			scl = 1.0 / ssml;
+			sumsq = asml;
+		}
+	} else {
+		// All values are mid-range...
+		scl = 1.0;
+		sumsq = amed;
+	}
+	return stdlib_base_sqrt( sumsq ) * scl;
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.js
new file mode 100644
index 000000000000..d0d48f309977
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.js
@@ -0,0 +1,243 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var Float64Array = require( '@stdlib/array/float64' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var drrss = require( './../lib/drrss.js' );
+
+
+// FUNCTIONS //
+
+/**
+* Tests for element-wise approximate equality.
+*
+* @private
+* @param {Object} t - test object
+* @param {Collection} actual - actual values
+* @param {Collection} expected - expected values
+* @param {number} rtol - relative tolerance
+*/
+function isApprox( t, actual, expected, rtol ) {
+	var delta;
+	var tol;
+	var i;
+
+	t.strictEqual( actual.length, expected.length, 'returns expected value' );
+	for ( i = 0; i < expected.length; i++ ) {
+		if ( actual[ i ] === expected[ i ] ) {
+			t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' );
+		} else {
+			delta = abs( actual[ i ] - expected[ i ] );
+			tol = rtol * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof drrss, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 5', function test( t ) {
+	t.strictEqual( drrss.length, 5, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function calculates the square root of the residual sum of squares', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	y = new Float64Array( [ 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, sqrt( 418.0 ), 'returns expected value' );
+
+	x = new Float64Array( [ -4.0 ] );
+	y = new Float64Array( [ 10.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 14.0, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e150, 1.0e150, 1.0e150 ] );
+	y = new Float64Array( [ -1.0e150, 1.0e150, -1.0e150, -1.0e150 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 3.464101615137754e+150, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e-155, 1.0e-155, 1.0e-155 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e-155, -1.0e-155, -1.0e-155 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 4.0e-155, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e50, 1.0e150, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e150, -1.0e50, -1.0e150, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 2.82842712474619e+150, 1.0 );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e50, 1.0e-155, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e50, -1.0e-155, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 2.8284271247461905e+50, 1.0 );
+
+	x = new Float64Array( [ 1.4e-154, 1.5e-154, 1.4e-154, 0.0 ] );
+	y = new Float64Array( [ -1.4e-154, -1.5e-154, -1.4e-154, 0.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 4.967896939349689e-154, 1.0 );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+	y = new Float64Array( [ 3.0, -2.0, 1.0, -15.0, 3.0 ] );
+
+	z = drrss( 0, x, 1, y, 1 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	z = drrss( -1, x, 1, y, 1 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports stride parameters', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 0
+		-2.0,
+		3.0,  // 1
+		-2.0,
+		7.0,  // 2
+		-2.0,
+		0.0,  // 3
+		-1.0
+	]);
+
+	z = drrss( 4, x, 2, y, 2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative stride parameters', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 3
+		-2.0,
+		3.0,  // 2
+		-2.0,
+		7.0,  // 1
+		-2.0,
+		0.0,  // 0
+		-1.0
+	]);
+
+	z = drrss( 4, x, -2, y, -2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports view offsets', function test( t ) {
+	var x0;
+	var x1;
+	var y0;
+	var y1;
+	var z;
+
+	x0 = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0
+	]);
+	y0 = new Float64Array([
+		8.0,
+		-2.0, // 0
+		3.0,
+		-2.0, // 1
+		7.0,
+		-2.0, // 2
+		0.0,
+		-1.0, // 3
+		4.0
+	]);
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	z = drrss( 4, x1, 2, y1, 2 );
+
+	// sqrt( 9+0+16+25 ) = sqrt( 50 )
+	t.strictEqual( z, 7.0710678118654755, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.native.js
new file mode 100644
index 000000000000..6912301fd9ee
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.drrss.native.js
@@ -0,0 +1,252 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var Float64Array = require( '@stdlib/array/float64' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var drrss = tryRequire( resolve( __dirname, './../lib/drrss.native.js' ) );
+var opts = {
+	'skip': ( drrss instanceof Error )
+};
+
+
+// FUNCTIONS //
+
+/**
+* Tests for element-wise approximate equality.
+*
+* @private
+* @param {Object} t - test object
+* @param {Collection} actual - actual values
+* @param {Collection} expected - expected values
+* @param {number} rtol - relative tolerance
+*/
+function isApprox( t, actual, expected, rtol ) {
+	var delta;
+	var tol;
+	var i;
+
+	t.strictEqual( actual.length, expected.length, 'returns expected value' );
+	for ( i = 0; i < expected.length; i++ ) {
+		if ( actual[ i ] === expected[ i ] ) {
+			t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' );
+		} else {
+			delta = abs( actual[ i ] - expected[ i ] );
+			tol = rtol * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof drrss, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 5', opts, function test( t ) {
+	t.strictEqual( drrss.length, 5, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function calculates the square root of the residual sum of squares', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	y = new Float64Array( [ 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, sqrt( 418.0 ), 'returns expected value' );
+
+	x = new Float64Array( [ -4.0 ] );
+	y = new Float64Array( [ 10.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 14.0, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e150, 1.0e150, 1.0e150 ] );
+	y = new Float64Array( [ -1.0e150, 1.0e150, -1.0e150, -1.0e150 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 3.464101615137754e+150, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e-155, 1.0e-155, 1.0e-155 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e-155, -1.0e-155, -1.0e-155 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	t.strictEqual( z, 4.0e-155, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e50, 1.0e150, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e150, -1.0e50, -1.0e150, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 2.82842712474619e+150, 1.0 );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e50, 1.0e-155, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e50, -1.0e-155, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 2.8284271247461905e+50, 1.0 );
+
+	x = new Float64Array( [ 1.4e-154, 1.5e-154, 1.4e-154, 0.0 ] );
+	y = new Float64Array( [ -1.4e-154, -1.5e-154, -1.4e-154, 0.0 ] );
+
+	z = drrss( x.length, x, 1, y, 1 );
+	isApprox( t, z, 4.967896939349689e-154, 1.0 );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+	y = new Float64Array( [ 3.0, -2.0, 1.0, -15.0, 3.0 ] );
+
+	z = drrss( 0, x, 1, y, 1 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	z = drrss( -1, x, 1, y, 1 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports stride parameters', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 0
+		-2.0,
+		3.0,  // 1
+		-2.0,
+		7.0,  // 2
+		-2.0,
+		0.0,  // 3
+		-1.0
+	]);
+
+	z = drrss( 4, x, 2, y, 2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports a negative stride parameters', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 3
+		-2.0,
+		3.0,  // 2
+		-2.0,
+		7.0,  // 1
+		-2.0,
+		0.0,  // 0
+		-1.0
+	]);
+
+	z = drrss( 4, x, -2, y, -2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports view offsets', opts, function test( t ) {
+	var x0;
+	var x1;
+	var y0;
+	var y1;
+	var z;
+
+	x0 = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0
+	]);
+	y0 = new Float64Array([
+		8.0,
+		-2.0, // 0
+		3.0,
+		-2.0, // 1
+		7.0,
+		-2.0, // 2
+		0.0,
+		-1.0, // 3
+		4.0
+	]);
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	z = drrss( 4, x1, 2, y1, 2 );
+
+	// sqrt( 9+0+16+25 ) = sqrt( 50 )
+	t.strictEqual( z, 7.0710678118654755, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.js
new file mode 100644
index 000000000000..43444a1a1295
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.js
@@ -0,0 +1,82 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var proxyquire = require( 'proxyquire' );
+var IS_BROWSER = require( '@stdlib/assert/is-browser' );
+var drrss = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': IS_BROWSER
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof drrss, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is a method providing an ndarray interface', function test( t ) {
+	t.strictEqual( typeof drrss.ndarray, 'function', 'method is a function' );
+	t.end();
+});
+
+tape( 'if a native implementation is available, the main export is the native implementation', opts, function test( t ) {
+	var drrss = proxyquire( './../lib', {
+		'@stdlib/utils/try-require': tryRequire
+	});
+
+	t.strictEqual( drrss, mock, 'returns expected value' );
+	t.end();
+
+	function tryRequire() {
+		return mock;
+	}
+
+	function mock() {
+		// Mock...
+	}
+});
+
+tape( 'if a native implementation is not available, the main export is a JavaScript implementation', opts, function test( t ) {
+	var drrss;
+	var main;
+
+	main = require( './../lib/drrss.js' );
+
+	drrss = proxyquire( './../lib', {
+		'@stdlib/utils/try-require': tryRequire
+	});
+
+	t.strictEqual( drrss, main, 'returns expected value' );
+	t.end();
+
+	function tryRequire() {
+		return new Error( 'Cannot find module' );
+	}
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.js
new file mode 100644
index 000000000000..fa44d082680a
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.js
@@ -0,0 +1,239 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var Float64Array = require( '@stdlib/array/float64' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var drrss = require( './../lib/ndarray.js' );
+
+
+// FUNCTIONS //
+
+/**
+* Tests for element-wise approximate equality.
+*
+* @private
+* @param {Object} t - test object
+* @param {Collection} actual - actual values
+* @param {Collection} expected - expected values
+* @param {number} rtol - relative tolerance
+*/
+function isApprox( t, actual, expected, rtol ) {
+	var delta;
+	var tol;
+	var i;
+
+	t.strictEqual( actual.length, expected.length, 'returns expected value' );
+	for ( i = 0; i < expected.length; i++ ) {
+		if ( actual[ i ] === expected[ i ] ) {
+			t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' );
+		} else {
+			delta = abs( actual[ i ] - expected[ i ] );
+			tol = rtol * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof drrss, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 7', function test( t ) {
+	t.strictEqual( drrss.length, 7, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function calculates the square root of the residual sum of squares of two vectors', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	y = new Float64Array( [ 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, sqrt( 418.0 ), 'returns expected value' );
+
+	x = new Float64Array( [ -4.0 ] );
+	y = new Float64Array( [ 10.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 14.0, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e150, 1.0e150, 1.0e150 ] );
+	y = new Float64Array( [ -1.0e150, 1.0e150, -1.0e150, -1.0e150 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 3.464101615137754e+150, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e-155, 1.0e-155, 1.0e-155 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e-155, -1.0e-155, -1.0e-155 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 4.0e-155, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e50, 1.0e150, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e150, -1.0e50, -1.0e150, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 2.82842712474619e+150, 1.0 );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e50, 1.0e-155, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e50, -1.0e-155, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 2.8284271247461905e+50, 1.0 );
+
+	x = new Float64Array( [ 1.4e-154, 1.5e-154, 1.4e-154, 0.0 ] );
+	y = new Float64Array( [ -1.4e-154, -1.5e-154, -1.4e-154, 0.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 4.967896939349689e-154, 1.0 );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+	y = new Float64Array( [ 3.0, -2.0, 1.0, -15.0, 3.0 ] );
+
+	z = drrss( 0, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	z = drrss( -1, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports stride parameters', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 0
+		-2.0,
+		3.0,  // 1
+		-2.0,
+		7.0,  // 2
+		-2.0,
+		0.0,  // 3
+		-1.0
+	]);
+
+	z = drrss( 4, x, 2, 0, y, 2, 0 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports negative stride parameters', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 3
+		-2.0,
+		3.0,  // 2
+		-2.0,
+		7.0,  // 1
+		-2.0,
+		0.0,  // 0
+		-1.0
+	]);
+
+	z = drrss( 4, x, -2, x.length-2, y, -2, y.length-2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports offset parameters', function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0
+	]);
+	y = new Float64Array([
+		8.0,
+		-2.0, // 0
+		3.0,
+		-2.0, // 1
+		7.0,
+		-2.0, // 2
+		0.0,
+		-1.0, // 3
+		4.0
+	]);
+
+	z = drrss( 4, x, 2, 1, y, 2, 1 );
+
+	// sqrt( 9+0+16+25 ) = sqrt( 50 )
+	t.strictEqual( z, 7.0710678118654755, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.native.js b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.native.js
new file mode 100644
index 000000000000..0cd8a47e44dd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/base/drrss/test/test.ndarray.native.js
@@ -0,0 +1,248 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var Float64Array = require( '@stdlib/array/float64' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// VARIABLES //
+
+var drrss = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
+var opts = {
+	'skip': ( drrss instanceof Error )
+};
+
+
+// FUNCTIONS //
+
+/**
+* Tests for element-wise approximate equality.
+*
+* @private
+* @param {Object} t - test object
+* @param {Collection} actual - actual values
+* @param {Collection} expected - expected values
+* @param {number} rtol - relative tolerance
+*/
+function isApprox( t, actual, expected, rtol ) {
+	var delta;
+	var tol;
+	var i;
+
+	t.strictEqual( actual.length, expected.length, 'returns expected value' );
+	for ( i = 0; i < expected.length; i++ ) {
+		if ( actual[ i ] === expected[ i ] ) {
+			t.strictEqual( actual[ i ], expected[ i ], 'returns expected value' );
+		} else {
+			delta = abs( actual[ i ] - expected[ i ] );
+			tol = rtol * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. actual: '+actual[ i ]+'. expected: '+expected[ i ]+'. delta: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof drrss, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 7', opts, function test( t ) {
+	t.strictEqual( drrss.length, 7, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function calculates the square root of the residual sum of squares of two vectors', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	y = new Float64Array( [ 5.0, 12.0, -8.0, 15.0, 9.0, 0.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, sqrt( 418.0 ), 'returns expected value' );
+
+	x = new Float64Array( [ -4.0 ] );
+	y = new Float64Array( [ 10.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 14.0, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e150, 1.0e150, 1.0e150 ] );
+	y = new Float64Array( [ -1.0e150, 1.0e150, -1.0e150, -1.0e150 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 3.464101615137754e+150, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e-155, 1.0e-155, 1.0e-155 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e-155, -1.0e-155, -1.0e-155 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 4.0e-155, 'returns expected value' );
+
+	x = new Float64Array( [ 1.0e150, 1.0e50, 1.0e150, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e150, -1.0e50, -1.0e150, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 2.82842712474619e+150, 1.0 );
+
+	x = new Float64Array( [ 1.0e-155, 1.0e50, 1.0e-155, 1.0e50 ] );
+	y = new Float64Array( [ -1.0e-155, -1.0e50, -1.0e-155, -1.0e50 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 2.8284271247461905e+50, 1.0 );
+
+	x = new Float64Array( [ 1.4e-154, 1.5e-154, 1.4e-154, 0.0 ] );
+	y = new Float64Array( [ -1.4e-154, -1.5e-154, -1.4e-154, 0.0 ] );
+
+	z = drrss( x.length, x, 1, 0, y, 1, 0 );
+	isApprox( t, z, 4.967896939349689e-154, 1.0 );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the function returns `0`', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+	y = new Float64Array( [ 3.0, -2.0, 1.0, -15.0, 3.0 ] );
+
+	z = drrss( 0, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	z = drrss( -1, x, 1, 0, y, 1, 0 );
+	t.strictEqual( z, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports stride parameters', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 0
+		-2.0,
+		3.0,  // 1
+		-2.0,
+		7.0,  // 2
+		-2.0,
+		0.0,  // 3
+		-1.0
+	]);
+
+	z = drrss( 4, x, 2, 0, y, 2, 0 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports negative stride parameters', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+	y = new Float64Array([
+		8.0,  // 3
+		-2.0,
+		3.0,  // 2
+		-2.0,
+		7.0,  // 1
+		-2.0,
+		0.0,  // 0
+		-1.0
+	]);
+
+	z = drrss( 4, x, -2, x.length-2, y, -2, y.length-2 );
+
+	// sqrt( 49+1+81+16 ) = sqrt( 147 )
+	t.strictEqual( z, 12.12435565298214, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports offset parameters', opts, function test( t ) {
+	var x;
+	var y;
+	var z;
+
+	x = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0
+	]);
+	y = new Float64Array([
+		8.0,
+		-2.0, // 0
+		3.0,
+		-2.0, // 1
+		7.0,
+		-2.0, // 2
+		0.0,
+		-1.0, // 3
+		4.0
+	]);
+
+	z = drrss( 4, x, 2, 1, y, 2, 1 );
+
+	// sqrt( 9+0+16+25 ) = sqrt( 50 )
+	t.strictEqual( z, 7.0710678118654755, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json
index 090d0bc750de..ef608a7ea324 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json
+++ b/lib/node_modules/@stdlib/blas/ext/base/dsumpw/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,6 +28,7 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
         "./src/main.c"
       ],
@@ -47,6 +49,7 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
         "./src/main.c"
       ],
@@ -62,6 +65,23 @@
     },
     {
       "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/blas/base/shared"
+      ]
+    },
+    {
+      "task": "build",
+      "wasm": true,
       "src": [
         "./src/main.c"
       ],
diff --git a/lib/node_modules/@stdlib/blas/ext/base/glinspace/README.md b/lib/node_modules/@stdlib/blas/ext/base/glinspace/README.md
index cf7b2d1d11d7..e0cc6ab22111 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/glinspace/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/glinspace/README.md
@@ -119,7 +119,7 @@ glinspace.ndarray( 3, 1.0, 3.0, true, x, 1, x.length-3 );
     var x = [ 0.0, 0.0, 0.0 ];
 
     glinspace( 3, 0.0, 1.0, true, x, 1 );
-    // x =>[ 0.0, ~0.5, 1.0 ]
+    // x => [ 0.0, ~0.5, 1.0 ]
     ```
 
     where `x[1]` is only guaranteed to be approximately equal to `0.5`.
diff --git a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md
index f6d8ec43697c..99ecedd32a50 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/ndarray/README.md
@@ -49,6 +49,7 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`dcusum( arrays )`][@stdlib/blas/ext/base/ndarray/dcusum]</span><span class="delimiter">: </span><span class="description">compute the cumulative sum of a one-dimensional double-precision floating-point ndarray.</span>
 -   <span class="signature">[`dindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/dindex-of]</span><span class="delimiter">: </span><span class="description">return the first index of a search element in a one-dimensional double-precision floating-point ndarray.</span>
 -   <span class="signature">[`dlastIndexOf( arrays )`][@stdlib/blas/ext/base/ndarray/dlast-index-of]</span><span class="delimiter">: </span><span class="description">return the last index of a search element in a one-dimensional double-precision floating-point ndarray.</span>
+-   <span class="signature">[`dlinspace( arrays )`][@stdlib/blas/ext/base/ndarray/dlinspace]</span><span class="delimiter">: </span><span class="description">fill a one-dimensional double-precision floating-point ndarray with linearly spaced values over a specified interval.</span>
 -   <span class="signature">[`dsorthp( arrays )`][@stdlib/blas/ext/base/ndarray/dsorthp]</span><span class="delimiter">: </span><span class="description">sort a one-dimensional double-precision floating-point ndarray using heapsort.</span>
 -   <span class="signature">[`dsum( arrays )`][@stdlib/blas/ext/base/ndarray/dsum]</span><span class="delimiter">: </span><span class="description">compute the sum of all elements in a one-dimensional double-precision floating-point ndarray.</span>
 -   <span class="signature">[`gcusum( arrays )`][@stdlib/blas/ext/base/ndarray/gcusum]</span><span class="delimiter">: </span><span class="description">compute the cumulative sum of a one-dimensional ndarray.</span>
@@ -56,11 +57,13 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`gfindLastIndex( arrays, clbk[, thisArg] )`][@stdlib/blas/ext/base/ndarray/gfind-last-index]</span><span class="delimiter">: </span><span class="description">return the index of the last element in a one-dimensional ndarray which passes a test implemented by a predicate function.</span>
 -   <span class="signature">[`gindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/gindex-of]</span><span class="delimiter">: </span><span class="description">return the first index of a search element in a one-dimensional ndarray.</span>
 -   <span class="signature">[`glastIndexOf( arrays )`][@stdlib/blas/ext/base/ndarray/glast-index-of]</span><span class="delimiter">: </span><span class="description">return the last index of a search element in a one-dimensional ndarray.</span>
+-   <span class="signature">[`glinspace( arrays )`][@stdlib/blas/ext/base/ndarray/glinspace]</span><span class="delimiter">: </span><span class="description">fill a one-dimensional ndarray with linearly spaced values over a specified interval.</span>
 -   <span class="signature">[`gsorthp( arrays )`][@stdlib/blas/ext/base/ndarray/gsorthp]</span><span class="delimiter">: </span><span class="description">sort a one-dimensional ndarray using heapsort.</span>
 -   <span class="signature">[`gsum( arrays )`][@stdlib/blas/ext/base/ndarray/gsum]</span><span class="delimiter">: </span><span class="description">compute the sum of all elements in a one-dimensional ndarray.</span>
 -   <span class="signature">[`scusum( arrays )`][@stdlib/blas/ext/base/ndarray/scusum]</span><span class="delimiter">: </span><span class="description">compute the cumulative sum of a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`sindexOf( arrays )`][@stdlib/blas/ext/base/ndarray/sindex-of]</span><span class="delimiter">: </span><span class="description">return the first index of a search element in a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`slastIndexOf( arrays )`][@stdlib/blas/ext/base/ndarray/slast-index-of]</span><span class="delimiter">: </span><span class="description">return the last index of a search element in a one-dimensional single-precision floating-point ndarray.</span>
+-   <span class="signature">[`slinspace( arrays )`][@stdlib/blas/ext/base/ndarray/slinspace]</span><span class="delimiter">: </span><span class="description">fill a one-dimensional single-precision floating-point ndarray with linearly spaced values over a specified interval.</span>
 -   <span class="signature">[`ssorthp( arrays )`][@stdlib/blas/ext/base/ndarray/ssorthp]</span><span class="delimiter">: </span><span class="description">sort a one-dimensional single-precision floating-point ndarray using heapsort.</span>
 -   <span class="signature">[`ssum( arrays )`][@stdlib/blas/ext/base/ndarray/ssum]</span><span class="delimiter">: </span><span class="description">compute the sum of all elements in a one-dimensional single-precision floating-point ndarray.</span>
 -   <span class="signature">[`zsum( arrays )`][@stdlib/blas/ext/base/ndarray/zsum]</span><span class="delimiter">: </span><span class="description">compute the sum of all elements in a one-dimensional double-precision complex floating-point ndarray.</span>
@@ -114,6 +117,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/ext/base/ndarray/dlast-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dlast-index-of
 
+[@stdlib/blas/ext/base/ndarray/dlinspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dlinspace
+
 [@stdlib/blas/ext/base/ndarray/dsorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dsorthp
 
 [@stdlib/blas/ext/base/ndarray/dsum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/dsum
@@ -128,6 +133,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/ext/base/ndarray/glast-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/glast-index-of
 
+[@stdlib/blas/ext/base/ndarray/glinspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/glinspace
+
 [@stdlib/blas/ext/base/ndarray/gsorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gsorthp
 
 [@stdlib/blas/ext/base/ndarray/gsum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/gsum
@@ -138,6 +145,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/ext/base/ndarray/slast-index-of]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/slast-index-of
 
+[@stdlib/blas/ext/base/ndarray/slinspace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/slinspace
+
 [@stdlib/blas/ext/base/ndarray/ssorthp]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ssorthp
 
 [@stdlib/blas/ext/base/ndarray/ssum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/ext/base/ndarray/ssum
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/index.js
index 0f84687e51f1..2baf5b358fef 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/index.js
@@ -86,14 +86,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/main.js
index 6697cc407445..17f332a08016 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapx/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dapx = new Routine();
 dapx.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dapx, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/index.js
index 48c648f7df97..3f78b153afe9 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/main.js
index 2c3a67da5df8..45ca882e3cb5 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsum/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var dapxsum = new Routine();
 dapxsum.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dapxsum, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/index.js
index 32591bba49dc..481f3bd6f6ed 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/main.js
index dd1ee4a51c41..c16f7b133038 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumkbn/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dapxsumkbn = new Routine();
 dapxsumkbn.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dapxsumkbn, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/index.js
index 249944ae5df9..cddde950ce57 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/main.js
index aa1100d42e12..fa92fc84f5a6 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumors/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dapxsumors = new Routine();
 dapxsumors.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dapxsumors, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/index.js
index 3450d5d60cec..70d5fcaaa82e 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/main.js
index 01ac0f78ad66..b87134a589e1 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dapxsumpw/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dapxsumpw = new Routine();
 dapxsumpw.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dapxsumpw, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/index.js
index e6e27a7a43c5..d327de07883c 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/main.js
index ff37aaa40805..fc19bd5ba457 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dasumpw/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var dasumpw = new Routine();
 dasumpw.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dasumpw, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/docs/types/index.d.ts
index bf336a0a7c1c..2bbe6196bbc7 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/docs/types/index.d.ts
@@ -219,7 +219,7 @@ interface Routine extends ModuleWrapper {
 	* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 	*
 	* var out = dnanasumors.main( 4, x, 1 );
-	* // returns 1.0
+	* // returns 5.0
 	*/
 	main( N: number, x: Float64Array, strideX: number ): number;
 
@@ -238,7 +238,7 @@ interface Routine extends ModuleWrapper {
 	* var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 	*
 	* var out = dnanasumors.ndarray( 4, x, 2, 1 );
-	* // returns 5.0
+	* // returns 9.0
 	*/
 	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 
@@ -298,7 +298,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 *
 * var out = dnanasumors.main( 4, x, 1 );
-* // returns 1.0
+* // returns 5.0
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
@@ -306,7 +306,7 @@ interface Routine extends ModuleWrapper {
 * var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 *
 * var out = dnanasumors.ndarray( 4, x, 2, 1 );
-* // returns 5.0
+* // returns 9.0
 */
 declare var dnanasumors: Routine;
 
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/index.js
index 9644fa3d747b..8e87c741a724 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/main.js
index 4f6dce72e25e..d70ddbf77454 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnanasumors/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dnanasumors = new Routine();
 dnanasumors.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dnanasumors, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/index.js
index 89f10d287d9d..be22d1db9d58 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/index.js
@@ -80,14 +80,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/main.js
index 1c3e0b5344fc..dbaf3793c5cf 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumkbn2/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -55,6 +57,7 @@ var Routine = require( './routine.js' );
 */
 var dnansumkbn2 = new Routine();
 dnansumkbn2.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dnansumkbn2, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/docs/types/index.d.ts
index 359cee60a87f..d834ee3db452 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/docs/types/index.d.ts
@@ -216,7 +216,7 @@ interface Routine extends ModuleWrapper {
 	* @example
 	* var Float64Array = require( '@stdlib/array/float64' );
 	*
-	* var x = new Float64Array( [ 1.0, -2.0, NaN 2.0 ] );
+	* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 	*
 	* var out = dnansumpw.main( 4, x, 1 );
 	* // returns 1.0
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/index.js
index b80c0a88a47f..1faa0360a206 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/main.js
index b3aeab69329c..e3217883254f 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/dnansumpw/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var dnansumpw = new Routine();
 dnansumpw.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( dnansumpw, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/wasm/docs/types/index.d.ts
index 20cb706159a9..fb561f08f4b1 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/docs/types/index.d.ts
@@ -50,7 +50,7 @@ interface Namespace {
 	* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 	*
 	* ns.dapx.main( 3, 5.0, x, 1 );
-	* // x => Float64Array[ 6.0, 3.0, 7.0 ]
+	* // x => <Float64Array>[ 6.0, 3.0, 7.0 ]
 	*
 	* @example
 	* var Float64Array = require( '@stdlib/array/float64' );
@@ -58,7 +58,7 @@ interface Namespace {
 	* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 	*
 	* ns.dapx.ndarray( 4, 5.0, x, 2, 1 );
-	* // x => Float64Array[ 7.0, 6.0, 7.0, 3.0, 3.0, 7.0, 8.0, 9.0 ]
+	* // x => <Float64Array>[ 2.0, 6.0, 2.0, 3.0, -2.0, 7.0, 3.0, 9.0 ]
 	*/
 	dapx: typeof dapx;
 
@@ -210,7 +210,7 @@ interface Namespace {
 	* var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
 	*
 	* var out = ns.dnanasumors.main( 4, x, 1 );
-	* // returns 1.0
+	* // returns 5.0
 	*
 	* @example
 	* var Float64Array = require( '@stdlib/array/float64' );
@@ -218,7 +218,7 @@ interface Namespace {
 	* var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 	*
 	* var out = ns.dnanasumors.ndarray( 4, x, 2, 1 );
-	* // returns 5.0
+	* // returns 9.0
 	*/
 	dnanasumors: typeof dnanasumors;
 
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/index.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/index.js
index f80c8866d037..0fb505b0b467 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/main.js b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/main.js
index eaa4777f05dc..cb046a9788b7 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/main.js
+++ b/lib/node_modules/@stdlib/blas/ext/base/wasm/sapxsumkbn/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -53,6 +55,7 @@ var Routine = require( './routine.js' );
 */
 var sapxsumkbn = new Routine();
 sapxsumkbn.initializeSync(); // eslint-disable-line node/no-sync
+setReadOnly( sapxsumkbn, 'Module', Module.bind( null ) );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/lib/index.js b/lib/node_modules/@stdlib/blas/ext/lib/index.js
index 746f9a594f08..f875a2f22fa3 100644
--- a/lib/node_modules/@stdlib/blas/ext/lib/index.js
+++ b/lib/node_modules/@stdlib/blas/ext/lib/index.js
@@ -90,6 +90,15 @@ setReadOnly( ns, 'indexOf', require( '@stdlib/blas/ext/index-of' ) );
 */
 setReadOnly( ns, 'lastIndexOf', require( '@stdlib/blas/ext/last-index-of' ) );
 
+/**
+* @name linspace
+* @memberof ns
+* @readonly
+* @type {Function}
+* @see {@link module:@stdlib/blas/ext/linspace}
+*/
+setReadOnly( ns, 'linspace', require( '@stdlib/blas/ext/linspace' ) );
+
 /**
 * @name sorthp
 * @memberof ns
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/README.md b/lib/node_modules/@stdlib/blas/ext/linspace/README.md
new file mode 100644
index 000000000000..037849b7dc8d
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/README.md
@@ -0,0 +1,244 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# linspace
+
+> Return a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced values over a specified interval along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var linspace = require( '@stdlib/blas/ext/linspace' );
+```
+
+#### linspace( shape, start, stop\[, endpoint]\[, options] )
+
+Returns a new [ndarray][@stdlib/ndarray/ctor] filled with linearly spaced values over a specified interval along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = linspace( [ 4 ], 1.0, 4.0 );
+// returns <ndarray>
+
+var arr = ndarray2array( x );
+// returns [ 1.0, 2.0, 3.0, 4.0 ]
+```
+
+The function has the following parameters:
+
+-   **shape**: array shape.
+-   **start**: start of interval. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a start [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input shape, a start [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+-   **stop**: end of interval. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a stop [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input shape, a stop [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+-   **endpoint**: specifies whether to include the end of the interval when writing values to the output [ndarray][@stdlib/ndarray/ctor] (_optional_). May be either a boolean or an [ndarray][@stdlib/ndarray/ctor] having a boolean or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, an endpoint [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input shape, an endpoint [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor]. Default: `true`.
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **dims**: list of dimensions over which to perform operation. If not provided, the function generates linearly spaced values along the last dimension. Default: `[-1]`.
+-   **dtype**: output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes]. If both `start` and `stop` are real-valued, the output array data type may be any floating-point data type or "generic". However, if either `start` or `stop` are complex-valued, the output array type must be a complex floating-point data type or "generic". If a data type is provided, `start` and `stop` are cast to the specified data type. If a data type is not provided and both `start` and `stop` are the same type (either `'float64'`, `'complex64'`, or `'complex128'`), the default output array data type is the same type as the input values (either `'float64'`, `'complex64'`, or `'complex128'`, respectively). Otherwise, if a data type is not provided and `start` and `stop` have different types, the default output array data type is determined according to type promotion rules.
+-   **order**: specifies whether an [ndarray][@stdlib/ndarray/ctor] is `'row-major'` (C-style) or `'column-major'` (Fortran-style). If `start`, `stop`, and `endpoint` are scalar values, the default order is `'row-major'`. If `start`, `stop`, and/or `endpoint` arrays have the same memory layout, the default order is the same layout. Otherwise, the default order is `'row-major'`.
+-   **mode**: specifies how to handle indices which exceed array dimensions (see [`ndarray`][@stdlib/ndarray/ctor]). Default: `'throw'`.
+-   **submode**: a mode array which specifies for each dimension how to handle subscripts which exceed array dimensions  (see [`ndarray`][@stdlib/ndarray/ctor]). If provided fewer modes than dimensions, the constructor recycles modes using modulo arithmetic. Default: `[ options.mode ]`.
+
+By default, the function always includes the end of the interval in the list of values written to an output [ndarray][@stdlib/ndarray/ctor]. To exclude the end of the interval, provide an `endpoint` argument.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = linspace( [ 4 ], 1.0, 5.0, false );
+// returns <ndarray>
+
+var arr = ndarray2array( x );
+// returns [ 1.0, 2.0, 3.0, 4.0 ]
+```
+
+When provided scalar or zero-dimensional [ndarray][@stdlib/ndarray/ctor] `start`, `stop`, and `endpoint` arguments, the values are broadcast across all elements in the shape defined by the complement of those dimensions specified by `options.dims`. To specify separate sub-array configurations, provide non-zero-dimensional [ndarray][@stdlib/ndarray/ctor] arguments.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var BooleanArray = require( '@stdlib/array/bool' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var start = array( [ 1.0, 5.0 ] );
+var end = array( [ 3.0, 8.0 ] );
+var endpoint = array( new BooleanArray( [ true, false ] ) );
+
+var x = linspace( [ 2, 3 ], start, end, endpoint );
+// returns <ndarray>
+
+var arr = ndarray2array( x );
+// returns [ [ 1.0, 2.0, 3.0 ], [ 5.0, 6.0, 7.0 ] ]
+```
+
+By default, the function generates linearly spaced values along the last dimension of an output [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = linspace( [ 2, 2 ], 1.0, 4.0, {
+    'dims': [ 0, 1 ]
+});
+// returns <ndarray>
+
+var arr = ndarray2array( x );
+// returns [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ]
+```
+
+To specify the output [ndarray][@stdlib/ndarray/ctor] [data type][@stdlib/ndarray/dtypes], provide a `dtype` option.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+var x = linspace( [ 4 ], 1.0, 4.0, {
+    'dtype': 'float32'
+});
+// returns <ndarray>
+
+var arr = ndarray2array( x );
+// returns [ 1.0, 2.0, 3.0, 4.0 ]
+```
+
+#### linspace.assign( out, start, stop\[, endpoint]\[, options] )
+
+Fills an [ndarray][@stdlib/ndarray/ctor] with linearly spaced values over a specified interval along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+
+var x = zeros( [ 4 ] );
+// returns <ndarray>
+
+var out = linspace.assign( x, 1.0, 4.0 );
+// returns <ndarray>
+
+var arr = ndarray2array( out );
+// returns [ 1.0, 2.0, 3.0, 4.0 ]
+
+var bool = ( x === out );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **out**: output [ndarray][@stdlib/ndarray/ctor]. Must have a floating-point or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **start**: start of interval. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a start [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided output [ndarray][@stdlib/ndarray/ctor], a start [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+-   **stop**: end of interval. May be either a number, a complex number, or an [ndarray][@stdlib/ndarray/ctor] having a numeric or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, a stop [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided output [ndarray][@stdlib/ndarray/ctor], a stop [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+-   **endpoint**: specifies whether to include the end of the interval when writing values to the output [ndarray][@stdlib/ndarray/ctor] (_optional_). May be either a boolean or an [ndarray][@stdlib/ndarray/ctor] having a boolean or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, an endpoint [ndarray][@stdlib/ndarray/ctor] must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided output [ndarray][@stdlib/ndarray/ctor], an endpoint [ndarray][@stdlib/ndarray/ctor] must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor]. Default: `true`.
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **dims**: list of dimensions over which to perform operation. If not provided, the function generates linearly spaced values along the last dimension. Default: `[-1]`.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   Let `M` be the number of linearly spaced values to be written along one or more [ndarray][@stdlib/ndarray/ctor] dimensions. The spacing between values is thus given by
+
+    ```text
+    Δ = (stop-start)/(M-1)
+    ```
+
+-   If an output [ndarray][@stdlib/ndarray/ctor] has a single element and the function is supposed to include the end of the interval, the set of values written to an output [ndarray][@stdlib/ndarray/ctor] only includes the end of the interval, but not the start of the interval.
+
+-   Otherwise, when an output [ndarray][@stdlib/ndarray/ctor] has a single element and the function is not supposed to include the end of the interval, the set of values written to an output [ndarray][@stdlib/ndarray/ctor] only includes the start of the interval, but not the end of the interval.
+
+-   For a real-valued output [ndarray][@stdlib/ndarray/ctor], if the start of the interval is less than end of the interval, the set of values written to an output [ndarray][@stdlib/ndarray/ctor] will be written in ascending order, and, if the start of the interval is greater than the end of the interval, the set of written values will be in descending order.
+
+-   When an output [ndarray][@stdlib/ndarray/ctor] contains at least two values and the function is supposed to include the end of the interval, the set of values written to an output [ndarray][@stdlib/ndarray/ctor] is guaranteed to include the start and end interval values. Beware, however, that values between the interval bounds are subject to floating-point rounding errors.
+
+-   When writing to a complex floating-point output [ndarray][@stdlib/ndarray/ctor], real-valued start and stop values are treated as complex numbers having a real component equaling the provided value and having an imaginary component equaling zero.
+
+-   When generating linearly spaced complex floating-point numbers, the real and imaginary components are generated separately.
+
+-   Both `start` and `stop` are cast to the data type of the output [ndarray][@stdlib/ndarray/ctor].
+
+-   The function iterates over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of an output [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional output [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an output [ndarray][@stdlib/ndarray/ctor] to contiguous memory before filling with linearly spaced values.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var linspace = require( '@stdlib/blas/ext/linspace' );
+
+// Create two vectors defining interval bounds:
+var start = linspace( [ 5 ], 1, 5, true );
+var end = linspace( [ 5 ], 5, 9, true );
+
+// Create a grid:
+var out = linspace( [ 5, 5 ], start, end, true );
+console.log( ndarray2array( out ) );
+
+// Generate linearly spaced values over multiple dimensions:
+out = linspace( [ 5, 5 ], 1, 25, true, {
+    'dims': [ 0, 1 ]
+});
+console.log( ndarray2array( out ) );
+
+// Generate linearly spaced values over multiple dimensions in column-major order:
+out = linspace( [ 5, 5 ], 1, 25, true, {
+    'dims': [ 0, 1 ],
+    'order': 'column-major'
+});
+console.log( ndarray2array( out ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.assign.js b/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.assign.js
new file mode 100644
index 000000000000..f4075ec2fa7b
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.assign.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var pkg = require( './../package.json' ).name;
+var assign = require( './../lib/assign.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = zeros( [ len ], options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var o;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			o = assign( x, i, i+100, true );
+			if ( typeof o !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( x.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':assign:dtype='+options.dtype+',len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.js b/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.js
new file mode 100644
index 000000000000..27d339a4c013
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/benchmark/benchmark.js
@@ -0,0 +1,100 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var linspace = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var o;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			o = linspace( [ len ], i, i+100, true );
+			if ( typeof o !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( o.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':dtype='+options.dtype+',len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt b/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt
new file mode 100644
index 000000000000..ba121f3ec604
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/docs/repl.txt
@@ -0,0 +1,230 @@
+
+{{alias}}( shape, start, stop[, endpoint][, options] )
+    Returns a new ndarray filled with linearly spaced values over a specified
+    interval along one or more ndarray dimensions.
+
+    If a specified shape has a single element and the function is supposed to
+    include the end of the interval, the set of values written to an output
+    ndarray only includes the end of the interval, but not the start of the
+    interval.
+
+    Otherwise, when a specified shape has a single element and the function is
+    not supposed to include the end of the interval, the set of values written
+    to an output ndarray only includes the start of the interval, but not the
+    end of the interval.
+
+    For real-valued arrays, if the start of the interval is less than end of the
+    interval, the set of values written to an output ndarray will be written in
+    ascending order, and, if the start of the interval is greater than the end
+    of the interval, the set of written values will be in descending order.
+
+    When a specified shape contains at least two values and the function is
+    supposed to include the end of the interval, the set of values written to an
+    output ndarray is guaranteed to include the start and end interval values.
+    Beware, however, that values between the interval bounds are subject to
+    floating-point rounding errors.
+
+    When writing to a complex floating-point output array, real-valued `start`
+    and `stop` values are treated as complex numbers having a real component
+    equaling the provided value and having an imaginary component equaling zero.
+
+    When generating linearly spaced complex floating-point numbers, the real and
+    imaginary components are generated separately.
+
+    Both `start` and `stop` are cast to the data type of the output array.
+
+    Parameters
+    ----------
+    shape: Array<integer>
+        Array shape.
+
+    start: ndarray|number|Complex
+        Start of interval. May be either a number, a complex number, or an
+        ndarray having a numeric or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, a start ndarray must
+        have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input shape, a start ndarray must be a zero-dimensional ndarray.
+
+    stop: ndarray|number|Complex
+        End of interval. May be either a number, a complex number, or an
+        ndarray having a numeric or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, a stop ndarray must
+        have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input shape, a stop ndarray must be a zero-dimensional ndarray.
+
+    endpoint: ndarray|boolean (optional)
+        Boolean specifying whether to include the end of the interval when
+        writing values to the output ndarray. May be either a boolean or an
+        ndarray having a boolean or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, an endpoint ndarray
+        must have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input shape, an endpoint ndarray must be a zero-dimensional ndarray.
+        Default: true.
+
+    options: Object (optional)
+        Function options.
+
+    options.dims: Array<integer> (optional)
+        List of dimensions over which to perform operation. If not provided, the
+        function generates linearly spaced values along the last dimension.
+        Default: [-1].
+
+    options.dtype: string|DataType (optional)
+        Output array data type. If both `start` and `stop` are real-valued, the
+        output array data type may be any floating-point data type or 'generic'.
+        However, if either `start` or `stop` are complex-valued, the output
+        array type must be a complex floating-point data type or 'generic'. If
+        provided, `start` and `stop` are cast to the specified data type. If not
+        provided and both `start` and `stop` are the same type (either
+        'float64', 'complex64', or 'complex128'), the default output array data
+        type is the same type as the input values (either 'float64',
+        'complex64', or 'complex128', respectively). Otherwise, if a data type
+        is not provided and `start` and `stop` have different types, the default
+        output array data type is determined according to type promotion rules.
+
+    options.order: string (optional)
+        Specifies whether an array is row-major (C-style) or column-major
+        (Fortran-style). If `start`, `stop`, and `endpoint` are scalar values,
+        the default order is 'row-major'. If `start`, `stop`, and/or `endpoint`
+        arrays have the same memory layout, the default order is the same
+        layout. Otherwise, the default order is 'row-major'.
+
+    options.mode: string (optional)
+        Specifies how to handle indices which exceed array dimensions. If equal
+        to 'throw', an ndarray instance throws an error when an index exceeds
+        array dimensions. If equal to 'normalize', an ndarray instance
+        normalizes negative indices and throws an error when an index exceeds
+        array dimensions. If equal to 'wrap', an ndarray instance wraps around
+        indices exceeding array dimensions using modulo arithmetic. If equal to
+        'clamp', an ndarray instance sets an index exceeding array dimensions
+        to either `0` (minimum index) or the maximum index. Default: 'throw'.
+
+    options.submode: Array<string> (optional)
+        Specifies how to handle subscripts which exceed array dimensions. If a
+        mode for a corresponding dimension is equal to 'throw', an ndarray
+        instance throws an error when a subscript exceeds array dimensions. If
+        equal to 'normalize', an ndarray instance normalizes negative
+        subscripts and throws an error when a subscript exceeds array
+        dimensions. If equal to 'wrap', an ndarray instance wraps around
+        subscripts exceeding array dimensions using modulo arithmetic. If equal
+        to 'clamp', an ndarray instance sets a subscript exceeding array
+        dimensions to either `0` (minimum index) or the maximum index. If the
+        number of modes is fewer than the number of dimensions, the function
+        recycles modes using modulo arithmetic. Default: [ options.mode ].
+
+    Returns
+    -------
+    out: ndarray
+        Output array.
+
+    Examples
+    --------
+    > var out = {{alias}}( [ 4 ], 1.0, 4.0 );
+    > {{alias:@stdlib/ndarray/to-array}}( out )
+    [ 1.0, 2.0, 3.0, 4.0 ]
+
+
+{{alias}}.assign( out, start, stop[, endpoint][, options] )
+    Fills an ndarray with linearly spaced values over a specified interval along
+    one or more ndarray dimensions.
+
+    If a provided array has a single element and the function is supposed to
+    include the end of the interval, the set of values written to an output
+    ndarray only includes the end of the interval, but not the start of the
+    interval.
+
+    Otherwise, when a provided array has a single element and the function is
+    not supposed to include the end of the interval, the set of values written
+    to an output ndarray only includes the start of the interval, but not the
+    end of the interval.
+
+    For real-valued arrays, if the start of the interval is less than end of the
+    interval, the set of values written to an output ndarray will be written in
+    ascending order, and, if the start of the interval is greater than the end
+    of the interval, the set of written values will be in descending order.
+
+    When a provided array contains at least two values and the function is
+    supposed to include the end of the interval, the set of values written to an
+    output ndarray is guaranteed to include the start and end interval values.
+    Beware, however, that values between the interval bounds are subject to
+    floating-point rounding errors.
+
+    When writing to a complex floating-point output array, real-valued `start`
+    and `stop` values are treated as complex numbers having a real component
+    equaling the provided value and having an imaginary component equaling zero.
+
+    When generating linearly spaced complex floating-point numbers, the real and
+    imaginary components are generated separately.
+
+    Both `start` and `stop` are cast to the data type of the output array.
+
+    Parameters
+    ----------
+    out: ndarray
+        Output array. Must have a numeric or "generic" data type.
+
+    start: ndarray|number|Complex
+        Start of interval. May be either a number, a complex number, or an
+        ndarray having a numeric or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, a start ndarray must
+        have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input array, a start ndarray must be a zero-dimensional ndarray.
+
+    stop: ndarray|number|Complex
+        End of interval. May be either a number, a complex number, or an
+        ndarray having a numeric or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, a stop ndarray must
+        have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input array, a stop ndarray must be a zero-dimensional ndarray.
+
+    endpoint: ndarray|boolean (optional)
+        Boolean specifying whether to include the end of the interval when
+        writing values to the output ndarray. May be either a boolean or an
+        ndarray having a boolean or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, an endpoint ndarray
+        must have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input array, an endpoint ndarray must be a zero-dimensional ndarray.
+        Default: true.
+
+    options: Object (optional)
+        Function options.
+
+    options.dims: Array<integer> (optional)
+        List of dimensions over which to perform operation. If not provided, the
+        function generates linearly spaced values along the last dimension.
+        Default: [-1].
+
+    Returns
+    -------
+    out: ndarray
+        Output array.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/zeros}}( [ 4 ] );
+    > var out = {{alias}}.assign( x, 1.0, 4.0 );
+    > {{alias:@stdlib/ndarray/to-array}}( out )
+    [ 1.0, 2.0, 3.0, 4.0 ]
+    > var bool = ( out === x )
+    true
+
+    See Also
+    --------
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts
new file mode 100644
index 000000000000..b811d5c83641
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/index.d.ts
@@ -0,0 +1,388 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { ArrayLike } from '@stdlib/types/array';
+import { FloatingPointAndGenericDataType as DataType, boolndarray, realcomplexndarray, realndarray, complexndarray, genericndarray, Mode, Order } from '@stdlib/types/ndarray';
+import { ComplexLike } from '@stdlib/types/complex';
+
+/**
+* Start of interval.
+*/
+type Start = number | ComplexLike | realcomplexndarray | genericndarray<number|ComplexLike>;
+
+/**
+* Start of interval.
+*/
+type RealStart = number | realndarray | genericndarray<number>;
+
+/**
+* Start of interval.
+*/
+type ComplexStart = ComplexLike | complexndarray | genericndarray<ComplexLike>;
+
+/**
+* End of interval.
+*/
+type Stop = number | ComplexLike | realcomplexndarray | genericndarray<number|ComplexLike>;
+
+/**
+* End of interval.
+*/
+type RealStop = number | realndarray | genericndarray<number>;
+
+/**
+* End of interval.
+*/
+type ComplexStop = ComplexLike | complexndarray | genericndarray<ComplexLike>;
+
+/**
+* Specifies whether to include the end of the interval when writing values to the output ndarray.
+*/
+type Endpoint = boolean | boolndarray | genericndarray<boolean>;
+
+/**
+* Output array.
+*/
+type OutputArray = realcomplexndarray | genericndarray<number|ComplexLike>;
+
+/**
+* Output array.
+*/
+type RealOutputArray = realndarray | genericndarray<number>;
+
+/**
+* Output array.
+*/
+type ComplexOutputArray = complexndarray | genericndarray<ComplexLike>;
+
+/**
+* Interface defining "base" options.
+*/
+interface BaseOptions {
+	/**
+	* List of dimensions over which to perform operation.
+	*/
+	dims?: ArrayLike<number>;
+}
+
+/**
+* Interface defining options.
+*/
+interface Options extends BaseOptions {
+	/**
+	* Array order (either 'row-major' (C-style) or 'column-major' (Fortran-style)).
+	*/
+	order?: Order;
+
+	/**
+	* Specifies how to handle a linear index which exceeds array dimensions (default: 'throw').
+	*/
+	mode?: Mode;
+
+	/**
+	* Specifies how to handle subscripts which exceed array dimensions on a per dimension basis (default: ['throw']).
+	*/
+	submode?: Array<Mode>;
+}
+
+/**
+* Interface defining options.
+*/
+interface OptionsWithDataType extends Options {
+	/**
+	* Output ndarray data type.
+	*/
+	dtype: DataType;
+}
+
+/**
+* Interface for performing an operation on an ndarray.
+*/
+interface Linspace {
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, {
+	*     'dtype': 'float64'
+	* });
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends RealStart = RealStart, U extends RealStop = RealStop>( shape: number | ArrayLike<number>, start: T, stop: U, options: OptionsWithDataType ): OutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, {} );
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends RealStart = RealStart, U extends RealStop = RealStop>( shape: number | ArrayLike<number>, start: T, stop: U, options: Options ): RealOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, true, {
+	*     'dtype': 'float64'
+	* });
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends RealStart = RealStart, U extends RealStop = RealStop, V extends Endpoint = Endpoint>( shape: number | ArrayLike<number>, start: T, stop: U, endpoint: V, options: OptionsWithDataType ): OutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0 );
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends RealStart = RealStart, U extends RealStop = RealStop, V extends Endpoint = Endpoint>( shape: number | ArrayLike<number>, start: T, stop: U, endpoint?: V, options?: Options ): RealOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, {
+	*     'dtype': 'float64'
+	* });
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends Start = Start, U extends Stop = Stop>( shape: number | ArrayLike<number>, start: T, stop: U, options: OptionsWithDataType ): ComplexOutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, {} );
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends Start = Start, U extends Stop = Stop>( shape: number | ArrayLike<number>, start: T, stop: U, options: Options ): ComplexOutputArray; /* eslint-disable-line @typescript-eslint/unified-signatures */ // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, true, {
+	*     'dtype': 'float64'
+	* });
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends Start = Start, U extends Stop = Stop, V extends Endpoint = Endpoint>( shape: number | ArrayLike<number>, start: T, stop: U, endpoint: V, options: OptionsWithDataType ): ComplexOutputArray; // TODO: we lose some type specificity here. We could likely improve specificity here by using type maps
+
+	/**
+	* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param shape - array shape
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var out = linspace( [ 2, 4 ], 0.0, 3.0, true );
+	* // returns <ndarray>
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	<T extends Start = Start, U extends Stop = Stop, V extends Endpoint = Endpoint>( shape: number | ArrayLike<number>, start: T, stop: U, endpoint?: V, options?: Options ): ComplexOutputArray; // NOTE: we lose some type specificity here, as the output ndarray data type is determined according to type promotion rules
+
+	/**
+	* Fills an ndarray with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param out - output ndarray
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var zeros = require( '@stdlib/ndarray/zeros' );
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var x = zeros( [ 2, 4 ] );
+	* // returns <ndarray>
+	*
+	* var out = linspace.assign( x, 0.0, 3.0 );
+	* // returns <ndarray>
+	*
+	* var bool = ( out === x );
+	* // returns true
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	assign<T extends OutputArray = OutputArray>( out: T, start: Start, stop: Stop, options: BaseOptions ): T;
+
+	/**
+	* Fills an ndarray with linearly spaced values over a specified interval along one or more ndarray dimensions.
+	*
+	* @param out - output ndarray
+	* @param start - start of interval
+	* @param stop - end of interval
+	* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var zeros = require( '@stdlib/ndarray/zeros' );
+	* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+	*
+	* var x = zeros( [ 2, 4 ] );
+	* // returns <ndarray>
+	*
+	* var out = linspace.assign( x, 0.0, 3.0 );
+	* // returns <ndarray>
+	*
+	* var bool = ( out === x );
+	* // returns true
+	*
+	* var arr = ndarray2array( out );
+	* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+	*/
+	assign<T extends OutputArray = OutputArray>( out: T, start: Start, stop: Stop, endpoint?: Endpoint, options?: BaseOptions ): T;
+}
+
+/**
+* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+*
+* @param shape - array shape
+* @param start - start of interval
+* @param stop - end of interval
+* @param endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+* @param options - function options
+*
+* @example
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var out = linspace( [ 2, 4 ], 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*
+* @example
+* var zeros = require( '@stdlib/ndarray/zeros' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = zeros( [ 2, 4 ] );
+* // returns <ndarray>
+*
+* var out = linspace.assign( x, 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var bool = ( out === x );
+* // returns true
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*/
+declare const linspace: Linspace;
+
+
+// EXPORTS //
+
+export = linspace;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/test.ts b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/test.ts
new file mode 100644
index 000000000000..6d22d62afefd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/docs/types/test.ts
@@ -0,0 +1,425 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+/// <reference types="@stdlib/types"/>
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import linspace = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	linspace( [ 4 ], 1.0, 3.0 ); // $ExpectType RealOutputArray
+	linspace( [ 4 ], 1.0, 3.0, true ); // $ExpectType RealOutputArray
+	linspace( [ 4 ], 1.0, 3.0, {} ); // $ExpectType RealOutputArray
+	linspace( [ 4 ], 1.0, 3.0, true, {} ); // $ExpectType RealOutputArray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a number or an array of numbers...
+{
+	linspace( '5', 1.0, 3.0 ); // $ExpectError
+	linspace( true, 1.0, 3.0 ); // $ExpectError
+	linspace( false, 1.0, 3.0 ); // $ExpectError
+	linspace( null, 1.0, 3.0 ); // $ExpectError
+	linspace( void 0, 1.0, 3.0 ); // $ExpectError
+	linspace( {}, 1.0, 3.0 ); // $ExpectError
+	linspace( ( x: number ): number => x, 1.0, 3.0 ); // $ExpectError
+
+	linspace( '5', 1.0, 3.0, true ); // $ExpectError
+	linspace( true, 1.0, 3.0, true ); // $ExpectError
+	linspace( false, 1.0, 3.0, true ); // $ExpectError
+	linspace( null, 1.0, 3.0, true ); // $ExpectError
+	linspace( void 0, 1.0, 3.0, true ); // $ExpectError
+	linspace( {}, 1.0, 3.0, true ); // $ExpectError
+	linspace( ( x: number ): number => x, 1.0, 3.0, true ); // $ExpectError
+
+	linspace( '5', 1.0, 3.0, {} ); // $ExpectError
+	linspace( true, 1.0, 3.0, {} ); // $ExpectError
+	linspace( false, 1.0, 3.0, {} ); // $ExpectError
+	linspace( null, 1.0, 3.0, {} ); // $ExpectError
+	linspace( void 0, 1.0, 3.0, {} ); // $ExpectError
+	linspace( {}, 1.0, 3.0, {} ); // $ExpectError
+	linspace( ( x: number ): number => x, 1.0, 3.0, {} ); // $ExpectError
+
+	linspace( '5', 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( true, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( false, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( null, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( void 0, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( {}, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace( ( x: number ): number => x, 1.0, 3.0, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an ndarray or supported scalar value...
+{
+	linspace( [ 4 ], 'foo', 3.0 ); // $ExpectError
+	linspace( [ 4 ], true, 3.0 ); // $ExpectError
+	linspace( [ 4 ], false, 3.0 ); // $ExpectError
+	linspace( [ 4 ], null, 3.0 ); // $ExpectError
+	linspace( [ 4 ], void 0, 3.0 ); // $ExpectError
+	linspace( [ 4 ], [], 3.0 ); // $ExpectError
+	linspace( [ 4 ], {}, 3.0 ); // $ExpectError
+	linspace( [ 4 ], ( x: number ): number => x, 3.0 ); // $ExpectError
+
+	linspace( [ 4 ], 'foo', 3.0, true ); // $ExpectError
+	linspace( [ 4 ], true, 3.0, true ); // $ExpectError
+	linspace( [ 4 ], false, 3.0, true ); // $ExpectError
+	linspace( [ 4 ], null, 3.0, true ); // $ExpectError
+	linspace( [ 4 ], void 0, 3.0, true ); // $ExpectError
+	linspace( [ 4 ], [], 3.0, true ); // $ExpectError
+	linspace( [ 4 ], {}, 3.0, true ); // $ExpectError
+	linspace( [ 4 ], ( x: number ): number => x, 3.0, true ); // $ExpectError
+
+	linspace( [ 4 ], 'foo', 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], true, 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], false, 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], null, 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], void 0, 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], [], 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], {}, 3.0, {} ); // $ExpectError
+	linspace( [ 4 ], ( x: number ): number => x, 3.0, {} ); // $ExpectError
+
+	linspace( [ 4 ], 'foo', 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], true, 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], false, 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], null, 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], void 0, 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], [], 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], {}, 3.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], ( x: number ): number => x, 3.0, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a third argument which is not an ndarray or supported scalar value...
+{
+	linspace( [ 4 ], 1.0, 'foo' ); // $ExpectError
+	linspace( [ 4 ], 1.0, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, false ); // $ExpectError
+	linspace( [ 4 ], 1.0, null ); // $ExpectError
+	linspace( [ 4 ], 1.0, void 0 ); // $ExpectError
+	linspace( [ 4 ], 1.0, [] ); // $ExpectError
+	linspace( [ 4 ], 1.0, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, ( x: number ): number => x ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 'foo', true ); // $ExpectError
+	linspace( [ 4 ], 1.0, true, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, false, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, null, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, void 0, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, [], true ); // $ExpectError
+	linspace( [ 4 ], 1.0, {}, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, ( x: number ): number => x, true ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 'foo', {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, false, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, null, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, void 0, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, [], {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, {}, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, ( x: number ): number => x, {} ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 'foo', true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, true, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, false, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, null, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, void 0, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, [], true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, {}, true, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, ( x: number ): number => x, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a fourth argument which is not an ndarray, boolean, or options object...
+{
+	linspace( [ 4 ], 1.0, 3.0, 'foo' ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, null ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, [] ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, ( x: number ): number => x ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 3.0, 'foo', {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, null, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, [], {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, {}, {} ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a options argument which is not an object...
+{
+	linspace( [ 4 ], 1.0, 3.0, true, '5' ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, 5 ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, true ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, false ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, null ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, [] ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dtype` option...
+{
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': '5' } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': 5 } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': true } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': false } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': null } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': [] } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': {} } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': '5' } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': 5 } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': true } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': false } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': null } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': [] } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': {} } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dtype': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid `dims` option...
+{
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': '5' } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': 5 } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': true } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': false } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': null } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': {} } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, { 'dims': ( x: number ): number => x } ); // $ExpectError
+
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': '5' } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': 5 } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': true } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': false } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': null } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': {} } ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	linspace(); // $ExpectError
+	linspace( [ 4 ] ); // $ExpectError
+	linspace( [ 4 ], 1.0 ); // $ExpectError
+	linspace( [ 4 ], 1.0, 3.0, true, {}, {} ); // $ExpectError
+}
+
+// Attached to the function is an `assign` method which returns an ndarray...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, 1.0, 3.0 ); // $ExpectType float64ndarray
+	linspace.assign( x, 1.0, 3.0, true ); // $ExpectType float64ndarray
+	linspace.assign( x, 1.0, 3.0, {} ); // $ExpectType float64ndarray
+	linspace.assign( x, 1.0, 3.0, true, {} ); // $ExpectType float64ndarray
+}
+
+// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray...
+{
+	linspace.assign( '5', 1.0, 3.0 ); // $ExpectError
+	linspace.assign( 5, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( true, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( false, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( null, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( void 0, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( {}, 1.0, 3.0 ); // $ExpectError
+	linspace.assign( ( x: number ): number => x, 1.0, 3.0 ); // $ExpectError
+
+	linspace.assign( '5', 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( 5, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( true, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( false, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( null, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( void 0, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( {}, 1.0, 3.0, true ); // $ExpectError
+	linspace.assign( ( x: number ): number => x, 1.0, 3.0, true ); // $ExpectError
+
+	linspace.assign( '5', 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( 5, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( true, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( false, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( null, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( void 0, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( {}, 1.0, 3.0, {} ); // $ExpectError
+	linspace.assign( ( x: number ): number => x, 1.0, 3.0, {} ); // $ExpectError
+
+	linspace.assign( '5', 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( 5, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( true, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( false, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( null, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( void 0, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( {}, 1.0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( ( x: number ): number => x, 1.0, 3.0, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray or supported scalar value...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, '5', 3.0 ); // $ExpectError
+	linspace.assign( x, true, 3.0 ); // $ExpectError
+	linspace.assign( x, false, 3.0 ); // $ExpectError
+	linspace.assign( x, null, 3.0 ); // $ExpectError
+	linspace.assign( x, void 0, 3.0 ); // $ExpectError
+	linspace.assign( x, [], 3.0 ); // $ExpectError
+	linspace.assign( x, {}, 3.0 ); // $ExpectError
+	linspace.assign( x, ( x: number ): number => x, 3.0 ); // $ExpectError
+
+	linspace.assign( x, '5', 3.0, true ); // $ExpectError
+	linspace.assign( x, true, 3.0, true ); // $ExpectError
+	linspace.assign( x, false, 3.0, true ); // $ExpectError
+	linspace.assign( x, null, 3.0, true ); // $ExpectError
+	linspace.assign( x, void 0, 3.0, true ); // $ExpectError
+	linspace.assign( x, [], 3.0, true ); // $ExpectError
+	linspace.assign( x, {}, 3.0, true ); // $ExpectError
+	linspace.assign( x, ( x: number ): number => x, 3.0, true ); // $ExpectError
+
+	linspace.assign( x, '5', 3.0, {} ); // $ExpectError
+	linspace.assign( x, true, 3.0, {} ); // $ExpectError
+	linspace.assign( x, false, 3.0, {} ); // $ExpectError
+	linspace.assign( x, null, 3.0, {} ); // $ExpectError
+	linspace.assign( x, void 0, 3.0, {} ); // $ExpectError
+	linspace.assign( x, [], 3.0, {} ); // $ExpectError
+	linspace.assign( x, {}, 3.0, {} ); // $ExpectError
+	linspace.assign( x, ( x: number ): number => x, 3.0, {} ); // $ExpectError
+
+	linspace.assign( x, '5', 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, true, 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, false, 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, null, 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, void 0, 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, [], 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, {}, 3.0, true, {} ); // $ExpectError
+	linspace.assign( x, ( x: number ): number => x, 3.0, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a third argument which is not an ndarray or supported scalar value...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, 1.0, '5' ); // $ExpectError
+	linspace.assign( x, 1.0, true ); // $ExpectError
+	linspace.assign( x, 1.0, false ); // $ExpectError
+	linspace.assign( x, 1.0, null ); // $ExpectError
+	linspace.assign( x, 1.0, void 0 ); // $ExpectError
+	linspace.assign( x, 1.0, [] ); // $ExpectError
+	linspace.assign( x, 1.0, {} ); // $ExpectError
+	linspace.assign( x, 1.0, ( x: number ): number => x ); // $ExpectError
+
+	linspace.assign( x, 1.0, '5', true ); // $ExpectError
+	linspace.assign( x, 1.0, true, true ); // $ExpectError
+	linspace.assign( x, 1.0, false, true ); // $ExpectError
+	linspace.assign( x, 1.0, null, true ); // $ExpectError
+	linspace.assign( x, 1.0, void 0, true ); // $ExpectError
+	linspace.assign( x, 1.0, [], true ); // $ExpectError
+	linspace.assign( x, 1.0, {}, true ); // $ExpectError
+	linspace.assign( x, 1.0, ( x: number ): number => x, true ); // $ExpectError
+
+	linspace.assign( x, 1.0, '5', {} ); // $ExpectError
+	linspace.assign( x, 1.0, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, false, {} ); // $ExpectError
+	linspace.assign( x, 1.0, null, {} ); // $ExpectError
+	linspace.assign( x, 1.0, void 0, {} ); // $ExpectError
+	linspace.assign( x, 1.0, [], {} ); // $ExpectError
+	linspace.assign( x, 1.0, {}, {} ); // $ExpectError
+	linspace.assign( x, 1.0, ( x: number ): number => x, {} ); // $ExpectError
+
+	linspace.assign( x, 1.0, '5', true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, true, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, false, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, null, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, void 0, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, [], true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, {}, true, {} ); // $ExpectError
+	linspace.assign( x, 1.0, ( x: number ): number => x, true, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a fourth argument which is not an ndarray, boolean, or options object...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, 1.0, 3.0, 'foo' ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, null ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, [] ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, ( x: number ): number => x ); // $ExpectError
+
+	linspace.assign( x, 1.0, 3.0, 'foo', {} ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, null, {} ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, [], {} ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, {}, {} ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a options argument which is not an object...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, 1.0, 3.0, true, '5' ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, true ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, false ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, null ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, [] ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an invalid `dims` option...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign( x, 1.0, 3.0, { 'dims': '5' } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': 5 } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': true } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': false } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': null } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': {} } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, { 'dims': ( x: number ): number => x } ); // $ExpectError
+
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': '5' } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': 5 } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': true } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': false } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': null } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': {} } ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	linspace.assign(); // $ExpectError
+	linspace.assign( x ); // $ExpectError
+	linspace.assign( x, 1.0 ); // $ExpectError
+	linspace.assign( x, 1.0, 3.0, true, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/examples/index.js b/lib/node_modules/@stdlib/blas/ext/linspace/examples/index.js
new file mode 100644
index 000000000000..49759eca6024
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/examples/index.js
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var linspace = require( './../lib' );
+
+// Create two vectors defining interval bounds:
+var start = linspace( [ 5 ], 1, 5, true );
+var end = linspace( [ 5 ], 5, 9, true );
+
+// Create a grid:
+var out = linspace( [ 5, 5 ], start, end, true );
+console.log( ndarray2array( out ) );
+
+// Generate linearly spaced values over multiple dimensions:
+out = linspace( [ 5, 5 ], 1, 25, true, {
+	'dims': [ 0, 1 ]
+});
+console.log( ndarray2array( out ) );
+
+// Generate linearly spaced values over multiple dimensions in column-major order:
+out = linspace( [ 5, 5 ], 1, 25, true, {
+	'dims': [ 0, 1 ],
+	'order': 'column-major'
+});
+console.log( ndarray2array( out ) );
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js
new file mode 100644
index 000000000000..36e0f3baba95
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/assign.js
@@ -0,0 +1,217 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' );
+var isIntegerArray = require( '@stdlib/assert/is-integer-array' ).primitives;
+var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var isComplexLike = require( '@stdlib/assert/is-complex-like' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var contains = require( '@stdlib/array/base/assert/contains' );
+var join = require( '@stdlib/array/base/join' );
+var format = require( '@stdlib/string/format' );
+var DTYPES = require( './dtypes.js' );
+var ENUMS = require( './type_enums.js' );
+var resolveDataTypes = require( './resolve_data_types.js' );
+var normalizeArguments = require( './normalize_arguments.js' );
+var defaults = require( './defaults.js' );
+var base = require( './base.js' );
+
+
+// MAIN //
+
+/**
+* Fills an ndarray with linearly spaced values over a specified interval along one or more ndarray dimensions.
+*
+* @param {ndarrayLike} x - input ndarray
+* @param {(number|ndarrayLike)} start - start of interval
+* @param {(number|ndarrayLike)} stop - end of interval
+* @param {(boolean|ndarrayLike)} [endpoint=true] - specifies whether to include the end of the interval when writing values to the output ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims=[-1]] - list of dimensions over which to perform operation
+* @throws {TypeError} first argument must be an ndarray-like object having at least one dimension
+* @throws {TypeError} second argument must be an ndarray-like object
+* @throws {TypeError} third argument must be an ndarray-like object
+* @throws {TypeError} fourth argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {RangeError} dimension indices must not exceed input ndarray bounds
+* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var zeros = require( '@stdlib/ndarray/zeros' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var x = zeros( [ 2, 4 ] );
+* // returns <ndarray>
+*
+* var out = assign( x, 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var bool = ( out === x );
+* // returns true
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*/
+function assign( x, start, stop ) {
+	var endpoint;
+	var options;
+	var dtypes;
+	var nargs;
+	var types;
+	var opts;
+	var args;
+	var ncsh;
+	var sh;
+	var dt;
+	var o;
+
+	if ( !isndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray. Value: `%s`.', x ) );
+	}
+	sh = getShape( x );
+	if ( sh.length < 1 ) {
+		throw new TypeError( 'invalid argument. First argument must be an ndarray having at least one dimension.' );
+	}
+	dt = String( getDType( x ) );
+	if ( !contains( DTYPES.odtypes, dt ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.odtypes, '", "' ), dt ) );
+	}
+	types = [ 0, 0, 0 ]; // [ start, stop, endpoint ]
+	if ( isNumber( start ) ) {
+		types[ 0 ] = ENUMS.NUMBER;
+	} else if ( isComplexLike( start ) ) {
+		types[ 0 ] = ENUMS.COMPLEX;
+	} else if ( isndarrayLike( start ) ) {
+		types[ 0 ] = ENUMS.NDARRAY;
+		dt = String( getDType( start ) );
+		if ( !contains( DTYPES.idtypes0, dt ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes0, '", "' ), dt ) );
+		}
+	} else {
+		throw new TypeError( format( 'invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.', start ) );
+	}
+	if ( isNumber( stop ) ) {
+		types[ 1 ] = ENUMS.NUMBER;
+	} else if ( isComplexLike( stop ) ) {
+		types[ 1 ] = ENUMS.COMPLEX;
+	} else if ( isndarrayLike( stop ) ) {
+		types[ 1 ] = ENUMS.NDARRAY;
+		dt = String( getDType( stop ) );
+		if ( !contains( DTYPES.idtypes1, dt ) ) {
+			throw new TypeError( format( 'invalid argument. Third argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes1, '", "' ), dt ) );
+		}
+	} else {
+		throw new TypeError( format( 'invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.', stop ) );
+	}
+	nargs = arguments.length;
+	o = arguments[ 3 ];
+
+	options = defaults();
+
+	// Case: assign( x, start, stop )
+	if ( nargs < 4 ) {
+		endpoint = true;
+		types[ 2 ] = ENUMS.BOOLEAN;
+	}
+	// Case: assign( x, start, stop, ??? )
+	else if ( nargs === 4 ) {
+		// Case: assign( x, start, stop, endpoint_boolean )
+		if ( isBoolean( o ) ) {
+			endpoint = o;
+			types[ 2 ] = ENUMS.BOOLEAN;
+		}
+		// Case: assign( x, start, stop, endpoint_ndarray )
+		else if ( isndarrayLike( o ) ) {
+			endpoint = o;
+			dt = String( getDType( endpoint ) );
+			if ( !contains( DTYPES.idtypes2, dt ) ) {
+				throw new TypeError( format( 'invalid argument. Fourth argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes2, '", "' ), dt ) );
+			}
+			types[ 2 ] = ENUMS.NDARRAY;
+		}
+		// Case: assign( x, start, stop, options )
+		else {
+			endpoint = true;
+			types[ 2 ] = ENUMS.BOOLEAN;
+			opts = o;
+			if ( !isPlainObject( opts ) ) {
+				throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) );
+			}
+		}
+	}
+	// Case: assign( x, start, stop, endpoint, options )
+	else if ( nargs >= 5 ) {
+		endpoint = o;
+		if ( isBoolean( endpoint ) ) {
+			types[ 2 ] = ENUMS.BOOLEAN;
+		} else if ( isndarrayLike( endpoint ) ) {
+			types[ 2 ] = ENUMS.NDARRAY;
+			dt = String( getDType( endpoint ) );
+			if ( !contains( DTYPES.idtypes2, dt ) ) {
+				throw new TypeError( format( 'invalid argument. Fourth argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes2, '", "' ), dt ) );
+			}
+		} else {
+			throw new TypeError( format( 'invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.', endpoint ) );
+		}
+		opts = arguments[ 4 ];
+		if ( !isPlainObject( opts ) ) {
+			throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) );
+		}
+	}
+	// Resolve options...
+	if ( opts ) {
+		if ( hasOwnProp( opts, 'dims' ) ) {
+			if ( !isIntegerArray( opts.dims ) && !isEmptyCollection( opts.dims ) ) { // eslint-disable-line max-len
+				throw new TypeError( format( 'invalid option. `%s` option must be an array of integers. Option: `%s`.', 'dims', opts.dims ) );
+			}
+			options.dims = opts.dims;
+		}
+	}
+	args = [ start, stop, endpoint ];
+
+	// Resolve argument data types:
+	dtypes = resolveDataTypes( args.slice( 0, 2 ), types );
+	dtypes[ 3 ] = getDType( x );
+
+	// Resolve the complement of the operation dimensions:
+	ncsh = nonCoreShape( sh, options.dims );
+
+	// Normalize provided arguments to ndarrays:
+	args = normalizeArguments( args, types, dtypes, ncsh, getOrder( x ) );
+
+	// Perform operation:
+	return base( x, args[ 0 ], args[ 1 ], args[ 2 ], options );
+}
+
+
+// EXPORTS //
+
+module.exports = assign;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js
new file mode 100644
index 000000000000..78846467f161
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/base.js
@@ -0,0 +1,123 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var glinspace = require( '@stdlib/blas/ext/base/ndarray/glinspace' );
+var dlinspace = require( '@stdlib/blas/ext/base/ndarray/dlinspace' );
+var slinspace = require( '@stdlib/blas/ext/base/ndarray/slinspace' );
+var factory = require( '@stdlib/ndarray/base/nullary-strided1d-dispatch-factory' );
+var DTYPES = require( './dtypes.js' );
+
+
+// VARIABLES //
+
+var table = {
+	'types': [
+		'float64', // input/output
+		'float32'  // input/output
+	],
+	'fcns': [
+		dlinspace,
+		slinspace
+	],
+	'default': glinspace
+};
+var options = {
+	'strictTraversalOrder': true
+};
+
+
+// MAIN //
+
+/**
+* Fills an ndarray with linearly spaced values over a specified interval along one or more ndarray dimensions.
+*
+* @private
+* @name linspace
+* @type {Function}
+* @param {ndarray} x - input ndarray
+* @param {ndarray} start - start of interval
+* @param {ndarray} stop - end of interval
+* @param {ndarray} endpoint - specifies whether to include the end of the interval when writing values to the output ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform operation
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be an ndarray-like object
+* @throws {TypeError} third argument must be an ndarray-like object
+* @throws {TypeError} fourth argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {RangeError} dimension indices must not exceed input ndarray bounds
+* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var BooleanArray = require( '@stdlib/array/bool' );
+* var array = require( '@stdlib/ndarray/array' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 2, 1, 3 ];
+*
+* // Define the array strides:
+* var sx = [ 3, 3, 1 ];
+*
+* // Define the index offset:
+* var ox = 0;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Create an ndarray containing the start of the interval:
+* var start = array( new Float64Array( [ 1.0, 4.0 ] ), {
+*     'shape': [ 2, 1 ]
+* });
+*
+* // Create an ndarray containing the end of the interval:
+* var end = array( new Float64Array( [ 3.0, 6.0 ] ), {
+*     'shape': [ 2, 1 ]
+* });
+*
+* // Create an ndarray specifying whether to include the end of the interval in the output:
+* var endpoint = array( new BooleanArray( [ true, true ] ), {
+*     'shape': [ 2, 1 ]
+* });
+*
+* // Perform operation:
+* var out = linspace( x, start, end, endpoint, {
+*     'dims': [ -1 ]
+* });
+* // returns <ndarray>
+*
+* var arr = ndarray2array( out );
+* // returns [ [ [ 1.0, 2.0, 3.0 ] ], [ [ 4.0, 5.0, 6.0 ] ] ]
+*/
+var linspace = factory( table, [ DTYPES.idtypes0, DTYPES.idtypes1, DTYPES.idtypes2 ], DTYPES.odtypes, options ); // eslint-disable-line max-len
+
+
+// EXPORTS //
+
+module.exports = linspace;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/defaults.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/defaults.js
new file mode 100644
index 000000000000..9622d735a575
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/defaults.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MAIN //
+
+/**
+* Returns default options.
+*
+* @private
+* @returns {Object} default options
+*/
+function defaults() {
+	return {
+		'dims': [ -1 ] // by default, generate linearly spaced values along the last dimension
+	};
+}
+
+
+// EXPORTS //
+
+module.exports = defaults;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/dtypes.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/dtypes.js
new file mode 100644
index 000000000000..aeae25b3d21f
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/dtypes.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var dtypes = require( '@stdlib/ndarray/dtypes' );
+
+
+// MAIN //
+
+var dt = {
+	'idtypes0': dtypes( 'numeric_and_generic' ), // start of interval
+	'idtypes1': dtypes( 'numeric_and_generic' ), // end of interval
+	'idtypes2': dtypes( 'boolean_and_generic' ), // endpoint
+	'odtypes': dtypes( 'floating_point_and_generic' )
+};
+
+
+// EXPORTS //
+
+module.exports = dt;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js
new file mode 100644
index 000000000000..ebe9dd7070cb
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/index.js
@@ -0,0 +1,70 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Return a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+*
+* @module @stdlib/blas/ext/linspace
+*
+* @example
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var linspace = require( '@stdlib/blas/ext/linspace' );
+*
+* var out = linspace( [ 2, 4 ], 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*
+* @example
+* var zeros = require( '@stdlib/ndarray/zeros' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var linspace = require( '@stdlib/blas/ext/linspace' );
+*
+* var x = zeros( [ 2, 4 ] );
+* // returns <ndarray>
+*
+* var out = linspace.assign( x, 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var bool = ( out === x );
+* // returns true
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var assign = require( './assign.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'assign', assign );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "assign": "main.assign" }
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js
new file mode 100644
index 000000000000..a56a7d10413e
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/main.js
@@ -0,0 +1,242 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isPlainObject = require( '@stdlib/assert/is-plain-object' );
+var isNonNegativeIntegerArray = require( '@stdlib/assert/is-nonnegative-integer-array' ).primitives;
+var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' );
+var isIntegerArray = require( '@stdlib/assert/is-integer-array' ).primitives;
+var isNonNegativeInteger = require( '@stdlib/assert/is-nonnegative-integer' ).isPrimitive;
+var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var isComplexLike = require( '@stdlib/assert/is-complex-like' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var isOrder = require( '@stdlib/ndarray/base/assert/is-order' );
+var isDataType = require( '@stdlib/ndarray/base/assert/is-data-type' );
+var nonCoreShape = require( '@stdlib/ndarray/base/complement-shape' );
+var getDType = require( '@stdlib/ndarray/base/dtype' );
+var empty = require( '@stdlib/ndarray/empty' );
+var contains = require( '@stdlib/array/base/assert/contains' );
+var join = require( '@stdlib/array/base/join' );
+var format = require( '@stdlib/string/format' );
+var DTYPES = require( './dtypes.js' );
+var ENUMS = require( './type_enums.js' );
+var resolveDataTypes = require( './resolve_data_types.js' );
+var resolveOrder = require( './resolve_order.js' );
+var normalizeArguments = require( './normalize_arguments.js' );
+var defaults = require( './defaults.js' );
+var base = require( './base.js' );
+
+
+// MAIN //
+
+/**
+* Returns a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.
+*
+* @param {(NonNegativeInteger|NonNegativeIntegerArray)} shape - array shape
+* @param {(number|ndarrayLike)} start - start of interval
+* @param {(number|ndarrayLike)} stop - end of interval
+* @param {(boolean|ndarrayLike)} [endpoint=true] - specifies whether to include the end of the interval when writing values to the output ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims=[-1]] - list of dimensions over which to perform operation
+* @param {*} [options.dtype] - output ndarray data type
+* @param {string} [options.order] - ndarray order
+* @param {string} [options.mode="throw"] - specifies how to handle indices which exceed ndarray dimensions
+* @param {StringArray} [options.submode=["throw"]] - specifies how to handle subscripts which exceed ndarray dimensions on a per dimension basis
+* @throws {TypeError} first argument must be either a nonnegative integer or an array of nonnegative integers
+* @throws {TypeError} second argument must be an ndarray-like object
+* @throws {TypeError} third argument must be an ndarray-like object
+* @throws {TypeError} fourth argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {RangeError} dimension indices must not exceed input ndarray bounds
+* @throws {RangeError} number of dimension indices must not exceed the number of input ndarray dimensions
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+*
+* var out = linspace( [ 2, 4 ], 0.0, 3.0 );
+* // returns <ndarray>
+*
+* var arr = ndarray2array( out );
+* // returns [ [ 0.0, 1.0, 2.0, 3.0 ], [ 0.0, 1.0, 2.0, 3.0 ] ]
+*/
+function linspace( shape, start, stop ) {
+	var endpoint;
+	var options;
+	var dtypes;
+	var nargs;
+	var types;
+	var opts;
+	var args;
+	var ncsh;
+	var out;
+	var sh;
+	var dt;
+	var o;
+
+	if ( isNonNegativeInteger( shape ) ) {
+		sh = [ shape ];
+	} else if ( isNonNegativeIntegerArray( shape ) ) {
+		sh = shape; // Note: empty shape (i.e., a shape for a zero-dimensional ndarray) is not allowed
+	} else {
+		throw new TypeError( format( 'invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.', shape ) );
+	}
+	types = [ 0, 0, 0 ]; // [ start, stop, endpoint ]
+	if ( isNumber( start ) ) {
+		types[ 0 ] = ENUMS.NUMBER;
+	} else if ( isComplexLike( start ) ) {
+		types[ 0 ] = ENUMS.COMPLEX;
+	} else if ( isndarrayLike( start ) ) {
+		types[ 0 ] = ENUMS.NDARRAY;
+		dt = String( getDType( start ) );
+		if ( !contains( DTYPES.idtypes0, dt ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes0, '", "' ), dt ) );
+		}
+	} else {
+		throw new TypeError( format( 'invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.', start ) );
+	}
+	if ( isNumber( stop ) ) {
+		types[ 1 ] = ENUMS.NUMBER;
+	} else if ( isComplexLike( stop ) ) {
+		types[ 1 ] = ENUMS.COMPLEX;
+	} else if ( isndarrayLike( stop ) ) {
+		types[ 1 ] = ENUMS.NDARRAY;
+		dt = String( getDType( stop ) );
+		if ( !contains( DTYPES.idtypes1, dt ) ) {
+			throw new TypeError( format( 'invalid argument. Third argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes1, '", "' ), dt ) );
+		}
+	} else {
+		throw new TypeError( format( 'invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.', stop ) );
+	}
+	nargs = arguments.length;
+	o = arguments[ 3 ];
+
+	options = defaults();
+
+	// Case: linspace( shape, start, stop )
+	if ( nargs < 4 ) {
+		endpoint = true;
+		types[ 2 ] = ENUMS.BOOLEAN;
+	}
+	// Case: linspace( shape, start, stop, ??? )
+	else if ( nargs === 4 ) {
+		// Case: linspace( shape, start, stop, endpoint_boolean )
+		if ( isBoolean( o ) ) {
+			endpoint = o;
+			types[ 2 ] = ENUMS.BOOLEAN;
+		}
+		// Case: linspace( shape, start, stop, endpoint_ndarray )
+		else if ( isndarrayLike( o ) ) {
+			endpoint = o;
+			dt = String( getDType( endpoint ) );
+			if ( !contains( DTYPES.idtypes2, dt ) ) {
+				throw new TypeError( format( 'invalid argument. Fourth argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes2, '", "' ), dt ) );
+			}
+			types[ 2 ] = ENUMS.NDARRAY;
+		}
+		// Case: linspace( shape, start, stop, options )
+		else {
+			endpoint = true;
+			types[ 2 ] = ENUMS.BOOLEAN;
+			opts = o;
+			if ( !isPlainObject( opts ) ) {
+				throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) );
+			}
+		}
+	}
+	// Case: linspace( shape, start, stop, endpoint, options )
+	else if ( nargs >= 5 ) {
+		endpoint = o;
+		if ( isBoolean( endpoint ) ) {
+			types[ 2 ] = ENUMS.BOOLEAN;
+		} else if ( isndarrayLike( endpoint ) ) {
+			types[ 2 ] = ENUMS.NDARRAY;
+			dt = String( getDType( endpoint ) );
+			if ( !contains( DTYPES.idtypes2, dt ) ) {
+				throw new TypeError( format( 'invalid argument. Fourth argument must have one of the following data types: "%s". Data type: `%s`.', join( DTYPES.idtypes2, '", "' ), dt ) );
+			}
+		} else {
+			throw new TypeError( format( 'invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.', endpoint ) );
+		}
+		opts = arguments[ 4 ];
+		if ( !isPlainObject( opts ) ) {
+			throw new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', opts ) );
+		}
+	}
+	// Resolve options...
+	if ( opts ) {
+		if ( hasOwnProp( opts, 'dtype' ) ) {
+			if ( !isDataType( opts.dtype ) || !contains( DTYPES.odtypes, String( opts.dtype ) ) ) { // eslint-disable-line max-len
+				throw new TypeError( format( 'invalid option. `%s` option must be one of the following: "%s". Option: `%s`.', 'dtype', join( DTYPES.odtypes, '", "' ), opts.dtype ) );
+			}
+			options.dtype = opts.dtype;
+		}
+		if ( hasOwnProp( opts, 'order' ) ) {
+			if ( !isOrder( opts.order ) ) {
+				throw new TypeError( format( 'invalid option. `%s` option must be a supported order. Option: `%s`.', 'order', opts.order ) );
+			}
+			options.order = opts.order;
+		}
+		if ( hasOwnProp( opts, 'mode' ) ) {
+			// Defer to `empty` to validate below...
+			options.mode = opts.mode;
+		}
+		if ( hasOwnProp( opts, 'submode' ) ) {
+			// Defer to `empty` to validate below...
+			options.submode = opts.submode;
+		}
+		if ( hasOwnProp( opts, 'dims' ) ) {
+			if ( !isIntegerArray( opts.dims ) && !isEmptyCollection( opts.dims ) ) { // eslint-disable-line max-len
+				throw new TypeError( format( 'invalid option. `%s` option must be an array of integers. Option: `%s`.', 'dims', opts.dims ) );
+			}
+			options.dims = opts.dims;
+		}
+	}
+	args = [ start, stop, endpoint ];
+
+	// Resolve argument data types:
+	dtypes = resolveDataTypes( args.slice( 0, 2 ), types );
+	options.dtype = options.dtype || dtypes[ 3 ];
+	dtypes[ 3 ] = options.dtype;
+
+	// Resolve the output array order:
+	options.order = options.order || resolveOrder( args, types );
+
+	// Resolve the complement of the operation dimensions:
+	ncsh = nonCoreShape( sh, options.dims );
+
+	// Normalize provided arguments to ndarrays:
+	args = normalizeArguments( args, types, dtypes, ncsh, options.order );
+
+	// Create an output ndarray:
+	out = empty( sh, options );
+
+	// Perform operation:
+	return base( out, args[ 0 ], args[ 1 ], args[ 2 ], options );
+}
+
+
+// EXPORTS //
+
+module.exports = linspace;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/normalize_arguments.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/normalize_arguments.js
new file mode 100644
index 000000000000..482c0f5e0dc0
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/normalize_arguments.js
@@ -0,0 +1,105 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isMostlySafeCast = require( '@stdlib/ndarray/base/assert/is-mostly-safe-data-type-cast' );
+var isEqualDataType = require( '@stdlib/ndarray/base/assert/is-equal-data-type' );
+var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
+var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
+var getOrder = require( '@stdlib/ndarray/base/order' );
+var getShape = require( '@stdlib/ndarray/base/shape' );
+var baseEmpty = require( '@stdlib/ndarray/base/empty' );
+var assign = require( '@stdlib/ndarray/base/assign' );
+var format = require( '@stdlib/string/format' );
+var ENUMS = require( './type_enums.js' );
+
+
+// MAIN //
+
+/**
+* Normalizes a list of arguments to a list of ndarrays.
+*
+* @private
+* @param {Array} args - list of arguments
+* @param {Array} types - argument types
+* @param {Array} dtypes - argument data types
+* @param {NonNegativeIntegerArray} shape - array shape
+* @param {string} order - array order
+* @throws {TypeError} only (mostly) safe casts are supported
+* @returns {Array<ndarray>} list of ndarrays
+*/
+function normalizeArguments( args, types, dtypes, shape, order ) {
+	var odt;
+	var out;
+	var N;
+	var t;
+	var v;
+	var i;
+
+	N = args.length;
+	out = [ null, null, null ]; // [ start, stop, endpoint ]
+	odt = dtypes[ 3 ];
+	for ( i = 0; i < N; i++ ) {
+		t = types[ i ];
+
+		// Case: args[ i ] === endpoint
+		if ( t === ENUMS.BOOLEAN ) {
+			out[ i ] = broadcastScalar( args[ i ], dtypes[ i ], shape, order );
+		}
+		// Case: args[ i ] === <number>
+		else if ( t === ENUMS.NUMBER ) {
+			// A number primitive should be able to cast to any supported output data type (real or complex):
+			out[ i ] = broadcastScalar( args[ i ], odt, shape, order );
+		}
+		// Case: args[ i ] === <ndarray>
+		else if ( t === ENUMS.NDARRAY ) {
+			// Case: args[ i ] === endpoint || start/stop which have the same dtype as the output dtype
+			if ( i === 2 || isEqualDataType( dtypes[ i ], odt ) ) {
+				out[ i ] = maybeBroadcastArray( args[ i ], shape );
+			}
+			// Case: args[ i ] === start/stop which have different dtype than output dtype
+			else if ( isMostlySafeCast( dtypes[ i ], odt ) ) {
+				// If we have unequal data types, we need to perform a copy...
+				v = baseEmpty( odt, getShape( args[ i ], false ), getOrder( args[ i ] ) ); // eslint-disable-line max-len
+				assign( [ args[ i ], v ] );
+				out[ i ] = maybeBroadcastArray( v, shape );
+			}
+			// Case: disallowed complex-to-real data type cast
+			else {
+				throw new TypeError( format( 'invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.', i+1, String( odt ), String( dtypes[ i ] ) ) );
+			}
+		}
+		// Case: args[ i ] === <complex>
+		else {
+			// Complex number scalars should only be able to cast to complex data types...
+			if ( !isMostlySafeCast( dtypes[ i ], odt ) ) {
+				throw new TypeError( format( 'invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.', i+1, String( odt ), String( dtypes[ i ] ) ) );
+			}
+			out[ i ] = broadcastScalar( args[ i ], odt, shape, order );
+		}
+	}
+	return out;
+}
+
+
+// EXPORTS //
+
+module.exports = normalizeArguments;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_data_types.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_data_types.js
new file mode 100644
index 000000000000..70e0a054a79f
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_data_types.js
@@ -0,0 +1,77 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var promoteDataTypes = require( '@stdlib/ndarray/base/promote-dtypes' );
+var getDType = require( '@stdlib/ndarray/base/dtype' );
+var complexDataType = require( '@stdlib/complex/dtype' );
+var ENUMS = require( './type_enums.js' );
+
+
+// MAIN //
+
+/**
+* Resolves argument data types.
+*
+* @private
+* @param {Array} args - list of arguments
+* @param {Array} types - argument types
+* @returns {Array} data types
+*/
+function resolveDataTypes( args, types ) {
+	var out;
+	var dt;
+	var N;
+	var t;
+	var i;
+
+	N = args.length;
+
+	// Initialize a data type array: [ start, stop, endpoint, out ]
+	out = [ '', '', 'bool', '' ];
+
+	// Resolve the data types for `start` and `stop`...
+	for ( i = 0; i < N; i++ ) {
+		t = types[ i ];
+		if ( t === ENUMS.NUMBER ) {
+			// Why 'float64'? Because we don't have any way of knowing whether a number primitive is intended to be 'float32' or 'float64', and, in order to preserve precision, we simply assume 'float64'. Note that this may lead to undesired type promotion when resolving an output data type...
+			dt = 'float64';
+		} else if ( t === ENUMS.NDARRAY ) {
+			dt = getDType( args[ i ] );
+		} else { // t === ENUMS.COMPLEX
+			dt = complexDataType( args[ i ] );
+			if ( dt === null ) {
+				// Why 'complex128'? Because we don't have any way of knowing whether a complex-like object is intended to be 'complex64' or 'complex128', and, in order to preserve precision, we simply assume 'complex128'. Note that this may lead to undesired type promotion when resolving an output data type...
+				dt = 'complex128';
+			}
+		}
+		out[ i ] = dt;
+	}
+	// To resolve the output array data type, apply type promotion to the `start` and `stop` data types:
+	out[ 3 ] = promoteDataTypes( out.slice( 0, 2 ) );
+
+	return out;
+}
+
+
+// EXPORTS //
+
+module.exports = resolveDataTypes;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_order.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_order.js
new file mode 100644
index 000000000000..5cd74f2b1ce8
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/resolve_order.js
@@ -0,0 +1,76 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var getOrder = require( '@stdlib/ndarray/base/order' );
+var defaults = require( '@stdlib/ndarray/defaults' );
+
+
+// VARIABLES //
+
+var ORDER = defaults.get( 'order' );
+var ENUMS = require( './type_enums.js' );
+
+
+// MAIN //
+
+/**
+* Resolves an output array order based on a provided list of input arguments.
+*
+* @private
+* @param {Array} args - list of arguments
+* @param {Array} types - argument types
+* @returns {string} order
+*/
+function resolveOrder( args, types ) {
+	var ord;
+	var N;
+	var i;
+
+	N = args.length;
+
+	// Find the first array...
+	for ( i = 0; i < N; i++ ) {
+		if ( types[ i ] === ENUMS.NDARRAY ) {
+			break;
+		}
+	}
+	// If no argument was an array, return the default memory layout...
+	if ( i === N ) {
+		return ORDER;
+	}
+	// Resolve the order of the first array argument:
+	ord = getOrder( args[ i ] );
+
+	// Determine whether we have a consensus order among provided input array arguments...
+	for ( i += 1; i < N; i++ ) {
+		if ( types[ i ] === ENUMS.NDARRAY && ord !== getOrder( args[ i ] ) ) {
+			// If we don't have a consensus order, fallback to the default memory layout:
+			return ORDER;
+		}
+	}
+	return ord;
+}
+
+
+// EXPORTS //
+
+module.exports = resolveOrder;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/lib/type_enums.js b/lib/node_modules/@stdlib/blas/ext/linspace/lib/type_enums.js
new file mode 100644
index 000000000000..ae8eb1ca3091
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/lib/type_enums.js
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MAIN //
+
+var ENUMS = {
+	'NUMBER': 1,
+	'COMPLEX': 2,
+	'NDARRAY': 3,
+	'BOOLEAN': 4
+};
+
+
+// EXPORTS //
+
+module.exports = ENUMS;
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/package.json b/lib/node_modules/@stdlib/blas/ext/linspace/package.json
new file mode 100644
index 000000000000..5564f520a3b8
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/blas/ext/linspace",
+  "version": "0.0.0",
+  "description": "Return a new ndarray filled with linearly spaced values over a specified interval along one or more ndarray dimensions.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "arrange",
+    "arange",
+    "linspace",
+    "linear",
+    "sequence",
+    "seq",
+    "ndarray",
+    "numpy",
+    "matlab"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/test/test.assign.js b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.assign.js
new file mode 100644
index 000000000000..45d68ed1aede
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.assign.js
@@ -0,0 +1,1560 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var Int32Array = require( '@stdlib/array/int32' );
+var BooleanArray = require( '@stdlib/array/bool' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var array = require( '@stdlib/ndarray/array' );
+var assign = require( './../lib/assign.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof assign, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (start=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, scalar2ndarray( 1.0 ), 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (stop=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, scalar2ndarray( 3.0 ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (endpoint=scalar)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (endpoint=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0, scalar2ndarray( true ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (start=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, scalar2ndarray( 1.0 ), 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (stop=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, scalar2ndarray( 3.0 ), {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (endpoint=scalar, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray having a supported data type (endpoint=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 1.0 ),
+		array( new BooleanArray( [ true, false ] ) )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( value, 1.0, 3.0, scalar2ndarray( true ), {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (stop=ndarray)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, scalar2ndarray( 3.0 ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (endpoint=scalar)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (endpoint, options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (start=ndarray)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, scalar2ndarray( 1.0 ), value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (endpoint, options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a fourth argument which is not a boolean, an ndarray having a supported data type, or an options object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		[ '1' ],
+		function noop() {},
+		scalar2ndarray( 3.14 )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a fourth argument which is not a boolean or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 3.14 )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, true, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ -10 ],
+		[ 0, 20 ],
+		[ 20 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ -10 ],
+		[ 0, 20 ],
+		[ 20 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ],
+		[ 0, 1, 0 ],
+		[ 1, 0, 1 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ],
+		[ 0, 1, 0 ],
+		[ 1, 0, 1 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which cannot be safely cast to an output data type', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float32'
+	});
+
+	values = [
+		scalar2ndarray( 1, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which cannot be safely cast to an output data type (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float32'
+	});
+
+	values = [
+		scalar2ndarray( 1, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, value, 3.0, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which cannot be safely cast to an output data type', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float32'
+	});
+
+	values = [
+		scalar2ndarray( 3, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which cannot be safely cast to an output data type (endpoint)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = zeros( [ 2, 2 ], {
+		'dtype': 'float32'
+	});
+
+	values = [
+		scalar2ndarray( 3, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			assign( x, 1.0, value, true );
+		};
+	}
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 3.0 );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' );
+
+	actual = assign( x, 1.0, 3.0 );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (start=0d)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, scalar2ndarray( 1.0 ), 3.0 );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (stop=0d)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, scalar2ndarray( 3.0 ) );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (start/stop=ndarray)', function test( t ) {
+	var endpoint;
+	var expected;
+	var actual;
+	var start;
+	var xbuf;
+	var end;
+	var x;
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'row-major'
+	});
+
+	actual = assign( x, start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'column-major'
+	});
+
+	actual = assign( x, start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'column-major'
+	});
+
+	actual = assign( x, start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'row-major'
+	});
+
+	actual = assign( x, start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	// Type promotion semantics...
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( new Float32Array( [ 1.0, 10.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+	end = array( new Float32Array( [ 3.0, 30.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+	x = new ndarray( 'float64', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	start = array( new Float32Array( [ 1.0, 10.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+	end = array( new Int32Array( [ 3, 30 ] ), {
+		'order': 'row-major',
+		'dtype': 'int32'
+	});
+
+	actual = assign( x, start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (all dimensions, row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 6.0, {
+		'dims': [ 0, 1 ]
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (all dimensions, column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 1, 2 ], 0, 'column-major' );
+
+	actual = assign( x, 1.0, 6.0, {
+		'dims': [ 0, 1 ]
+	});
+	expected = [ [ 1.0, 3.0, 5.0 ], [ 2.0, 4.0, 6.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (no dimensions, row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ -1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': []
+	});
+	expected = [ [ 3.0, 3.0, 3.0 ], [ 3.0, 3.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function fills an ndarray with linearly spaced values (no dimensions, column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ -1.0, 2.0, -3.0, 4.0, -5.0, 6.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'column-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': []
+	});
+	expected = [ [ 3.0, 3.0, 3.0 ], [ 3.0, 3.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (row-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 3, 2 ], [ 2, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': [ 0 ]
+	});
+	expected = [ [ 1.0, 1.0 ], [ 2.0, 2.0 ], [ 3.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': [ -1 ]
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (column-major)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 3, 2 ], [ 2, 1 ], 0, 'column-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': [ 0 ]
+	});
+	expected = [ [ 1.0, 1.0 ], [ 2.0, 2.0 ], [ 3.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'column-major' );
+
+	actual = assign( x, 1.0, 3.0, {
+		'dims': [ -1 ]
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	actual = assign( x, 1.0, 3.0, true );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = assign( x, 1.0, 4.0, false );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (ndarray)', function test( t ) {
+	var endpoint;
+	var expected;
+	var actual;
+	var xbuf;
+	var end;
+	var x;
+
+	xbuf = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+	x = new ndarray( 'generic', xbuf, [ 2, 3 ], [ 3, 1 ], 0, 'row-major' );
+
+	end = array( [ 3.0, 4.0 ] );
+	endpoint = array( new BooleanArray( [ true, false ] ) );
+
+	actual = assign( x, 1.0, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( actual, x, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/test/test.js b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.js
new file mode 100644
index 000000000000..8cfc380dae37
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.js
@@ -0,0 +1,39 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isMethod = require( '@stdlib/assert/is-method' );
+var linspace = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof linspace, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is an `assign` method', function test( t ) {
+	t.strictEqual( isMethod( linspace, 'assign' ), true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/linspace/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.main.js
new file mode 100644
index 000000000000..e286dde0b3fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/blas/ext/linspace/test/test.main.js
@@ -0,0 +1,1660 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isEqualDataType = require( '@stdlib/ndarray/base/assert/is-equal-data-type' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var array = require( '@stdlib/ndarray/array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var getDType = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' );
+var getOrder = require( '@stdlib/ndarray/order' );
+var BooleanArray = require( '@stdlib/array/bool' );
+var Float32Array = require( '@stdlib/array/float32' );
+var Int32Array = require( '@stdlib/array/int32' );
+var linspace = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof linspace, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (start=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, scalar2ndarray( 1.0 ), 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (stop=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, scalar2ndarray( 3.0 ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (endpoint=scalar)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (endpoint=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0, scalar2ndarray( true ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (start=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, scalar2ndarray( 1.0 ), 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (stop=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, scalar2ndarray( 3.0 ), {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (endpoint=scalar, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not a nonnegative integer or an array of nonnegative integers (endpoint=ndarray, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5.5,
+		-1,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( value, 1.0, 3.0, scalar2ndarray( true ), {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (stop=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, scalar2ndarray( 3.0 ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (endpoint=scalar)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not a number, complex number, or an ndarray having a supported data type (endpoint, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (start=ndarray)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], scalar2ndarray( 1.0 ), value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value, true );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not a number, complex number, or an ndarray having a supported data type (endpoint, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( true )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value, true, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a fourth argument which is not a boolean, an ndarray having a supported data type, or an options object', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		[ '1' ],
+		function noop() {},
+		scalar2ndarray( 3.14 )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a fourth argument which is not a boolean or an ndarray having a supported data type (options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		[ '1' ],
+		{},
+		function noop() {},
+		scalar2ndarray( 3.14 )
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ '1' ],
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, true, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which is not an array-like object of integers (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ -10 ],
+		[ 0, 20 ],
+		[ 20 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains out-of-bounds indices (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ -10 ],
+		[ 0, 20 ],
+		[ 20 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 2, 2 ], 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains too many indices (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 2, 2 ], 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ],
+		[ 0, 1, 0 ],
+		[ 1, 0, 1 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 2, 2 ], 1.0, 3.0, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a `dims` option which contains duplicate indices (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ],
+		[ 0, 1, 0 ],
+		[ 1, 0, 1 ]
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 2, 2 ], 1.0, 3.0, true, {
+				'dims': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an invalid `dtype` option', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		'foo',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, {
+				'dtype': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an invalid `dtype` option (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		'foo',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, true, {
+				'dtype': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an invalid `order` option', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		'foo',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, {
+				'order': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an invalid `order` option (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		'foo',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[ 'a' ],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, 3.0, true, {
+				'order': value
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which cannot be safely cast to an output data type', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		scalar2ndarray( 1, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0, {
+				'dtype': 'float32'
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which cannot be safely cast to an output data type (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		scalar2ndarray( 1, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], value, 3.0, true, {
+				'dtype': 'float32'
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which cannot be safely cast to an output data type', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		scalar2ndarray( 3, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value, {
+				'dtype': 'float32'
+			});
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which cannot be safely cast to an output data type (endpoint)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		scalar2ndarray( 3, {
+			'dtype': 'int32'
+		})
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			linspace( [ 4 ], 1.0, value, true, {
+				'dtype': 'float32'
+			});
+		};
+	}
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( 3, 1.0, 3.0 );
+	expected = [ 1.0, 2.0, 3.0 ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 3 ], 1.0, 3.0 );
+	expected = [ 1.0, 2.0, 3.0 ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0 );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (row-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'order': 'row-major'
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (column-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'order': 'column-major'
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (start=0d)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], scalar2ndarray( 1.0 ), 3.0 );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (stop=0d)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, scalar2ndarray( 3.0 ) );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (start/stop=ndarray)', function test( t ) {
+	var endpoint;
+	var expected;
+	var actual;
+	var start;
+	var end;
+
+	// Order inference...
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'row-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'column-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'row-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'row-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'column-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( [ 1.0, 10.0 ], {
+		'order': 'column-major'
+	});
+	end = array( [ 3.0, 30.0 ], {
+		'order': 'column-major'
+	});
+	endpoint = array( new BooleanArray( [ true ] ), {
+		'order': 'row-major'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	// Type promotion semantics...
+
+	start = array( new Float32Array( [ 1.0, 10.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+	end = array( new Float32Array( [ 3.0, 30.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float32' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	start = array( new Float32Array( [ 1.0, 10.0 ] ), {
+		'order': 'row-major',
+		'dtype': 'float32'
+	});
+	end = array( new Int32Array( [ 3, 30 ] ), {
+		'order': 'row-major',
+		'dtype': 'int32'
+	});
+
+	actual = linspace( [ 2, 3 ], start, end );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 10.0, 20.0, 30.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (all dimensions, row-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 6.0, {
+		'dims': [ 0, 1 ]
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 4.0, 5.0, 6.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (all dimensions, column-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 6.0, {
+		'dims': [ 0, 1 ],
+		'order': 'column-major'
+	});
+	expected = [ [ 1.0, 3.0, 5.0 ], [ 2.0, 4.0, 6.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (no dimensions, row-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'dims': []
+	});
+	expected = [ [ 3.0, 3.0, 3.0 ], [ 3.0, 3.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns an ndarray containing linearly spaced values (no dimensions, column-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'dims': [],
+		'order': 'column-major'
+	});
+	expected = [ [ 3.0, 3.0, 3.0 ], [ 3.0, 3.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (row-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 3, 2 ], 1.0, 3.0, {
+		'dims': [ 0 ]
+	});
+	expected = [ [ 1.0, 1.0 ], [ 2.0, 2.0 ], [ 3.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 3, 2 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'dims': [ -1 ]
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying operation dimensions (column-major)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 3, 2 ], 1.0, 3.0, {
+		'dims': [ 0 ],
+		'order': 'column-major'
+	});
+	expected = [ [ 1.0, 1.0 ], [ 2.0, 2.0 ], [ 3.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 3, 2 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'dims': [ -1 ],
+		'order': 'column-major'
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'column-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (scalar)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, true );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 2, 3 ], 1.0, 4.0, false );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (scalar, options)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, true, {} );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	actual = linspace( [ 2, 3 ], 1.0, 4.0, false, {} );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (ndarray)', function test( t ) {
+	var endpoint;
+	var expected;
+	var actual;
+	var end;
+
+	end = array( [ 3.0, 4.0 ] );
+	endpoint = array( new BooleanArray( [ true, false ] ) );
+
+	actual = linspace( [ 2, 3 ], 1.0, end, endpoint );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying whether to include the end of the interval in generated values (ndarray, options)', function test( t ) {
+	var endpoint;
+	var expected;
+	var actual;
+	var end;
+
+	end = array( [ 3.0, 4.0 ] );
+	endpoint = array( new BooleanArray( [ true, false ] ) );
+
+	actual = linspace( [ 2, 3 ], 1.0, end, endpoint, {} );
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float64' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying an output data type', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 3.0, {
+		'dtype': 'float32'
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float32' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying an output data type (endpoint)', function test( t ) {
+	var expected;
+	var actual;
+
+	actual = linspace( [ 2, 3 ], 1.0, 4.0, false, {
+		'dtype': 'float32'
+	});
+	expected = [ [ 1.0, 2.0, 3.0 ], [ 1.0, 2.0, 3.0 ] ];
+
+	t.strictEqual( isEqualDataType( getDType( actual ), 'float32' ), true, 'returns expected value' );
+	t.deepEqual( getShape( actual ), [ 2, 3 ], 'returns expected value' );
+	t.strictEqual( getOrder( actual ), 'row-major', 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying array index modes and submodes', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+
+	opts = {
+		'mode': 'clamp',
+		'submode': [ 'wrap' ]
+	};
+	actual = linspace( [ 2, 2, 3 ], 1.0, 3.0, opts );
+	expected = [
+		[
+			// 0    1    2
+			[ 1.0, 2.0, 3.0 ],
+
+			// 3    4    5
+			[ 1.0, 2.0, 3.0 ]
+		],
+		[
+			// 6    7    8
+			[ 1.0, 2.0, 3.0 ],
+
+			// 9   10   11
+			[ 1.0, 2.0, 3.0 ]
+		]
+	];
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	// Clamped:
+	t.strictEqual( actual.iget( actual.length+10 ), 3.0, 'returns expected value' );
+	actual.iset( actual.length+10, 10.0 );
+	t.strictEqual( actual.iget( actual.length+10 ), 10.0, 'returns expected value' );
+
+	// Wrapped:
+	t.strictEqual( actual.get( 2, 2, 3 ), 1.0, 'returns expected value' );
+	actual.set( 2, 2, 3, 30.0 );
+	t.strictEqual( actual.get( 0, 0, 0 ), 30.0, 'returns expected value' );
+	t.strictEqual( actual.get( 2, 2, 3 ), 30.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js
index 47e1a0d3ca35..620270654deb 100644
--- a/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js
+++ b/lib/node_modules/@stdlib/blas/ext/sorthp/lib/base.js
@@ -29,8 +29,7 @@ var factory = require( '@stdlib/ndarray/base/nullary-strided1d-dispatch-factory'
 
 // VARIABLES //
 
-var idtypes0 = dtypes( 'real_and_generic' ); // input ndarray
-var idtypes1 = dtypes( 'real_and_generic' ); // sortOrder ndarray
+var idtypes0 = dtypes( 'real_and_generic' ); // sortOrder ndarray
 var odtypes = dtypes( 'real_and_generic' );
 var table = {
 	'types': [
@@ -101,7 +100,7 @@ var options = {
 * var arr = ndarray2array( out );
 * // returns [ [ [ -5.0, -3.0 ] ], [ [ 1.0, 2.0 ] ], [ [ 4.0, 6.0 ] ] ]
 */
-var sorthp = factory( table, [ idtypes0, idtypes1 ], odtypes, options );
+var sorthp = factory( table, [ idtypes0 ], odtypes, options );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.main.js b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.main.js
index 6218c9d2b171..d236b40ece51 100644
--- a/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.main.js
+++ b/lib/node_modules/@stdlib/blas/ext/to-sortedhp/test/test.main.js
@@ -23,6 +23,9 @@
 var tape = require( 'tape' );
 var isEqualDataType = require( '@stdlib/ndarray/base/assert/is-equal-data-type' );
 var isSameArray = require( '@stdlib/assert/is-same-array' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var Int8Array = require( '@stdlib/array/int8' );
 var resolveStr = require( '@stdlib/ndarray/base/dtype-resolve-str' );
 var ndarray = require( '@stdlib/ndarray/ctor' );
 var zeros = require( '@stdlib/ndarray/zeros' );
@@ -1710,7 +1713,7 @@ tape( 'the function supports specifying an output data type', function test( t )
 	var xbuf;
 	var x;
 
-	xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+	xbuf = new Float32Array( [ -1.0, 2.0, -3.0, 4.0 ] );
 	x = new ndarray( 'float32', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
 
 	actual = toSortedhp( x, {
@@ -1733,7 +1736,7 @@ tape( 'the function supports specifying an output data type (sortOrder=scalar)',
 	var xbuf;
 	var x;
 
-	xbuf = [ -1.0, 2.0, -3.0, 4.0 ];
+	xbuf = new Float64Array( [ -1.0, 2.0, -3.0, 4.0 ] );
 	x = new ndarray( 'float64', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
 
 	actual = toSortedhp( x, 1.0, {
@@ -1756,7 +1759,7 @@ tape( 'the function supports specifying an output data type (sortOrder=string)',
 	var xbuf;
 	var x;
 
-	xbuf = [ -1, 2, -3, 4 ];
+	xbuf = new Int8Array( [ -1, 2, -3, 4 ] );
 	x = new ndarray( 'int8', xbuf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );
 
 	actual = toSortedhp( x, 'desc', {
diff --git a/lib/node_modules/@stdlib/complex/float32/base/package.json b/lib/node_modules/@stdlib/complex/float32/base/package.json
index d113306f12f2..0d003d33d269 100644
--- a/lib/node_modules/@stdlib/complex/float32/base/package.json
+++ b/lib/node_modules/@stdlib/complex/float32/base/package.json
@@ -58,5 +58,10 @@
     "ns",
     "float32",
     "base"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_complex64_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/complex/float64/base/package.json b/lib/node_modules/@stdlib/complex/float64/base/package.json
index 2d3f356e47f8..394a68e4bd4b 100644
--- a/lib/node_modules/@stdlib/complex/float64/base/package.json
+++ b/lib/node_modules/@stdlib/complex/float64/base/package.json
@@ -58,5 +58,10 @@
     "ns",
     "float64",
     "base"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_complex128_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.csv b/lib/node_modules/@stdlib/error/tools/database/data/data.csv
index 49f43321fbec..09fb19c09086 100644
--- a/lib/node_modules/@stdlib/error/tools/database/data/data.csv
+++ b/lib/node_modules/@stdlib/error/tools/database/data/data.csv
@@ -1215,3 +1215,13 @@
 "Ja","invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).","TypeError"
 "Jb","invalid argument. Second argument must be a negative integer. Value: `%s`.","TypeError"
 "Jc","invalid argument. First argument cannot be safely cast to the output data type. Data types: [%s, %s].","TypeError"
+"Jd","invalid option. First argument cannot be safely cast to the specified data type. Input data type: %s. Option: `%s`.","TypeError"
+"Je","invalid argument. First argument must be an ndarray having at least one dimension.","TypeError"
+"Jf","invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.","TypeError"
+"Jg","invalid argument. Third argument must have one of the following data types: ""%s"". Data type: `%s`.","TypeError"
+"Jh","invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.","TypeError"
+"Ji","invalid argument. Fourth argument must have one of the following data types: ""%s"". Data type: `%s`.","TypeError"
+"Jj","invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.","TypeError"
+"Jk","invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","TypeError"
+"Jl","invalid option. `%s` option must be a supported order. Option: `%s`.","TypeError"
+"Jm","invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s.","TypeError"
diff --git a/lib/node_modules/@stdlib/error/tools/database/data/data.json b/lib/node_modules/@stdlib/error/tools/database/data/data.json
index ca052cc1b96e..21b64b4175f7 100644
--- a/lib/node_modules/@stdlib/error/tools/database/data/data.json
+++ b/lib/node_modules/@stdlib/error/tools/database/data/data.json
@@ -1 +1 @@
-{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument.  Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #<Object>","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `<section class=\"related\">` and closing `</section>\\n\\n<!-- /.related -->`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`.","HG":"invalid argument. First argument must be a valid index ndarray.","HH":"invalid operation. This ndarray index instance has already been freed and can no longer be used.","HI":"invalid operation. Unrecognized ndarray index type. Value: `%s`.","HJ":"invalid operation. Index exceeds ndarray bounds.","HK":"invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","HL":"invalid operation. Unable to resolve ndarray index. Value: `%s`.","HM":"invalid argument. First argument is not compatible with the specified index \"kind\". Type: %s. Kind: %s.","HN":"invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","HO":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","HP":"invalid argument. Must provide unique dimension indices. Value: `[%s]`.","HQ":"invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","HR":"invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","HS":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","HT":"invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","HU":"invalid argument. First argument must be a valid action name. Value: `%s`.","HV":"invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`","HW":"invalid argument. Second argument must be an array of data types. Value: `%s`.","HX":"invalid argument. Third argument must be an array of data types. Value: `%s`.","HY":"invalid argument. Fourth argument must be a supported output data type policy. Value: `%s`.","HZ":"invalid argument. First argument must have one of the following data types: \"%s\". Data type: `%s`.","Ha":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d.","Hb":"invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].","Hc":"invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].","Hd":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].","He":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.","Hf":"invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).","Hg":"invalid argument. The second argument cannot be safely cast to the input array data type. Data type: %s. Value: `%s`.","Hh":"invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.","Hi":"invalid argument. Second argument cannot be safely cast to the input array data type. Value: `%s`.","Hj":"invalid argument. Third argument must be an ndarray-like object. Value: `%s`.","Hk":"invalid option. `%s` option must be an array of integers. Option: `%s`.","Hl":"invalid option. `%s` option contains an out-of-bounds dimension index. Option: [%s].","Hm":"invalid option. `%s` option specifies more dimensions than exists in the input array. Number of dimensions: %d. Option: [%s].","Hn":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].","Ho":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).","Hp":"invalid argument. Second argument must be an ndarray-like object. Value: `%s`.","Hq":"invalid argument. Second argument must have one of the following data types: \"%s\". Data type: `%s`.","Hr":"invalid argument. Fourteenth argument must be non-zero. Value: `%d`.","Hs":"invalid argument. Seventeenth argument must be non-zero. Value: `%d`.","Ht":"invalid argument. Eighteenth argument must be non-zero. Value: `%d`.","Hu":"invalid option. `%s` option contains duplicate indices. Option: [%s].","Hv":"invalid argument. First argument must be an object having a \"default\" property and an associated method.","Hw":"invalid argument. Second argument must contain arrays of data types. Value: `%s`.","Hx":"invalid argument. Argument %d must have one of the following data types: \"%s\". Data type: `%s`.","Hy":"invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.","Hz":"invalid arguments. Input and output arrays must have the same shape.","I0":"invalid argument. First argument specifies an unexpected number of types. A pair of input and output ndarray data types must be specified for each provided strided function.","I1":"invalid argument. First argument specifies an unexpected number of types. An input ndarray data type must be specified for each provided strided function.","I2":"invalid argument. Array arguments after the first two arrays must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","I3":"invalid argument. Loop dimensions must be consistent across all provided arrays. Input array shape: [%s]. Loop dimension indices: [%s]. Loop dimensions: [%s]. Array shape: [%s] (index: %d).","I4":"invalid argument. First argument must be an object having a \"types\" property whose associated value is an array-like object.","I5":"invalid argument. First argument must be an object having a \"fcns\" property whose associated value is an array-like object containing functions.","I6":"invalid argument. Fourth argument must be an object having a supported output data type policy. Value: `%s`.","I7":"invalid argument. Fourth argument must be an object having a supported casting policy. Value: `%s`.","I8":"invalid operation. Unable to promote the input and output data types. Input data type: %s. Output data type: %s.","I9":"invalid argument. Third argument must be a supported casting policy. Value: `%s`.","IA":"invalid option. `%s` option must be an object containing properties having values which are objects. Option: `%s`.","IB":"invalid option. `%s` option must be an object having %s `%s` property which is an array of strings. Option: `%s`.","IC":"invalid option. `%s` option must have %s `%s` property.","ID":"invalid argument. Second argument must be either an ndarray or a numeric scalar value. Value: `%s`.","IE":"invalid argument. Eleventh argument must be non-zero. Value: `%d`.","IF":"invalid option. `%s` option must be a valid memory layout. Option: `%s`.","IG":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d.","IH":"invalid argument. Unable to resolve an output data type. The output data type policy is \"same\" and yet the input data types are not equal. Data types: [%s].","II":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input data types can be safely cast. Data types: [%s].","IJ":"invalid argument. %s argument must have one of the following data types: \"%s\". Data type: `%s`.","IK":"invalid option. `%s` option must be a valid index mode. Option: `%s`.","IL":"invalid option. `%s` option must be a memory layout. Option: `%s`.","IM":"invalid argument. ArrayBuffer is incompatible with the specified data type. Value: `%s`.","IN":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, iterable, data type, or options object. Value: `%s`.","IO":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or iterable. Value: `%s`.","IP":"invalid argument. Third argument must be a recognized/supported data type. Value: `%s`.","IQ":"invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.","IR":"invalid argument. Fifth argument must be greater than or equal to max(1,%d). Value: `%d`.","IS":"invalid argument. Second argument must have an integer data type. Value: `%s`.","IT":"invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.","IU":"invalid argument. Union types may only be initialized by a single member.","IV":"invalid invocation. `this` is not a struct instance.","IW":"invalid operation. struct does not have any fields.","IX":"unexpected error. Unrecognized data type. Value: `%s`.","IY":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Data types: [%s, %s].","IZ":"invalid argument. Field objects must have the following properties: \"%s\". Value: `%s`.","Ia":"invalid argument. Union types cannot contain nested union types. Value: `%s`.","Ib":"invalid argument. Union types can only contain one field with a default value. Value: `%s`.","Ic":"invalid argument. Union types must contain fields having the same byte length. Value: `%s`.","Id":"invalid argument. `%s` field must be a string. Value: `%s`.","Ie":"invalid argument. `%s` field must be a boolean. Value: `%s`.","If":"invalid argument. `%s` field must be a positive integer. Value: `%s`.","Ig":"invalid assignment. `%s` must be a `struct` instance. Value: `%s`.","Ih":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Value: `%s`.","Ii":"invalid assignment. `%s` must be a `struct` instance having the same byte length.","Ij":"invalid assignment. `%s` must be an array-like object. Value: `%s`.","Ik":"invalid assignment. `%s` must be an array-like object having length %u.","Il":"invalid argument. Byte length must be a nonnegative integer. Value: `%s`.","Im":"invalid argument. ArrayBuffer has insufficient capacity. Minimum capacity: `%u`.","In":"invalid argument. First argument must be a `struct` instance. Value: `%s`.","Io":"invalid argument. `%s` field must be one of the following: \"%s\". Value: `%s`.","Ip":"invalid argument. First argument must be an array of objects having unique field names. Value: `%s`.","Iq":"invalid argument. `%s` field must be a non-empty string. Value: `%s`.","Ir":"invalid argument. First argument must be an array of objects. Value: `%s`. Index: `%d`.","Is":"invalid argument. Union types must be an array of objects. Value: `%s`. Index: `%d`.","It":"invalid argument. Field name must be one of the following: \"%s\". Value: `%s`.","Iu":"invalid argument. `%s` field must be either a struct type or one of the following: \"%s\". Value: `%s`.","Iv":"invalid assignment. `%s` must be an array-like object containing `struct` instances having the same byte length.","Iw":"invalid argument. First argument must be one of the following: \"%s\". Value: `%s`.","Ix":"invalid argument. First argument must be an ArrayBuffer or a data object. Value: `%s`.","Iy":"invalid argument. First argument must be either a struct constructor or struct schema. Value: `%s`.","Iz":"invalid argument. Each element of a provided input array must be a valid object or a struct instance having the same layout as elements in the desired output array.","J0":"invalid argument. Environment lacks Symbol.iterator support. First argument must be a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","J1":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","J2":"invalid argument. Each element of a provided input iterable must be either a valid object or a struct instance having the same layout as elements in the desired output array.","J3":"invalid argument. Second argument must be a multiple of %u. Value: `%u`.","J4":"invalid argument. Second argument exceeds the bounds of the ArrayBuffer. Value: `%s`.","J5":"invalid argument. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","J6":"invalid invocation. `this` is not a %s.","J7":"invalid argument. Must provide either a valid object or a struct instance. Value: `%s`.","J8":"invalid argument. First argument must be a valid orientation. Value: `%s`.","J9":"invalid argument. Second argument must be a valid orientation. Value: `%s`.","JA":"invalid argument. The first argument must be an ndarray. Value: `%s`.","JB":"invalid argument. Second argument must be either an ndarray or a scalar value. Value: `%s`.","JC":"invalid argument. Third argument must be an ndarray. Value: `%s`.","JD":"invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.","JE":"invalid operation. Environment lacks support for HTTP/2. Ensure that you are running on a Node.js version which supports HTTP/2 and has been built to include support for the Node.js `crypto` module.","JF":"invalid argument. Input arrays must have the same number of dimensions. First array dimensions: %d. Second array dimensions: %d.","JG":"invalid argument. Input arrays must have the same shape. First array shape: [%s]. Second array shape: [%s].","JH":"invalid argument. Output array must have the same number of non-reduced dimensions as input arrays. Input array shape: [%s]. Number of non-reduced dimensions: %d. Output array shape: [%s].","JI":"invalid argument. Array arguments after the first array must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","JJ":"invalid argument. Second argument contains an out-of-bounds index. Array shape: (%s). Value: `[%s]`.","JK":"invalid argument. Thirteenth argument must be non-zero. Value: `%d`.","JL":"invalid argument. Sixth argument must be greater than or equal to max(1,%d). Value: `%d`.","JM":"invalid argument. Fifth argument must be non-zero. Value: `%s`.","JN":"invalid argument. Sixth argument must be non-zero. Value: `%s`.","JO":"invalid arguments. Unable to resolve an ndarray function supporting the provided argument data types.","JP":"invalid argument. First argument specifies an unexpected number of types. Two input ndarray data types must be specified for each provided strided function.","JQ":"invalid argument. First argument specifies an unexpected number of types. An output ndarray data type must be specified for each provided strided function.","JR":"invalid operation. Unable to promote the input and output data types. Input data types: [%s]. Output data type: %s.","JS":"invalid argument. Fourth argument must be a supported casting policy. Value: `%s`.","JT":"invalid argument. Fourth argument must be an ndarray. Value: `%s`.","JU":"invalid option. `%s` option must be a supported data type. Option: `%s`.","JV":"invalid argument. First argument must be either a supported data type string, a struct constructor, or another data type instance. Value: `%s`.","JW":"invalid argument. Second argument must be a valid sort order. Value: `%s`.","JX":"invalid argument. Second argument must be either an ndarray, a numeric scalar value, or a supported string. Value: `%s`.","JY":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input ndarrays can be safely cast. Data types: [%s].","JZ":"invalid argument. The list of input ndarrays cannot be safely cast to the data of the output ndarray. Input data types: [%s]. Output data type: %s.","Ja":"invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).","Jb":"invalid argument. Second argument must be a negative integer. Value: `%s`.","Jc":"invalid argument. First argument cannot be safely cast to the output data type. Data types: [%s, %s]."}
+{"10":"invalid operation. Cannot reset a REPL which has already closed.","11":"invalid operation. Cannot clear a REPL which has already closed.","12":"invalid operation. Cannot clear the line of a REPL which has already closed.","13":"invalid operation. Cannot clear the command buffer of a REPL which has already closed.","14":"invalid argument. Provided command either does not contain an `await` expression or contains a top-level `return` which is not allowed.","15":"invalid argument. Must provide a program AST node.","16":"invalid invocation. Insufficient arguments. Must provide a REPL instance.","17":"invalid operation. No presentation to reload. Use the `load()` method to load a presentation.","18":"invalid operation. No presentation file to watch. Use the `load()` method to load a presentation.","19":"unexpected error. Encountered a \"rename\" event for the source presentation file. No longer watching source presentation file for changes.","20":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user is watching, an access token.","21":"unexpected error. Unable to resolve package directory as unable to find a `package.json` in a parent directory.","22":"invalid argument. Source code does not contain JSDoc comment with function options.","23":"unexpected error. Unable to resolve root project directory.","24":"invalid argument. An iterator must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","25":"invalid argument. Callback must return either a two-element array containing real and imaginary components or a complex number. Value: `%s`.","26":"invalid argument. Array-like object arguments must have a length which is a multiple of two. Length: `%u`.","27":"invalid argument. Array-like object and typed array arguments must have a length which is a multiple of two. Length: `%u`.","28":"invalid argument. ArrayBuffer byte length must be a multiple of `%u`. Byte length: `%u`.","29":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","30":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%s`.","31":"invalid argument. Fifth argument must be a function. Value: `%s`.","32":"invalid argument. Fourth argument must be a function. Value: `%s`.","33":"invalid argument. Second argument must be either an integer (starting index) or a callback function. Value: `%s`.","34":"invalid argument. Third argument must be either an integer (ending index) or a callback function. Value: `%s`.","35":"invalid argument. Second argument must be either an integer (starting view index) or a callback function. Value: `%s`.","36":"invalid argument. Third argument must be either an integer (ending view index) or a callback function. Value: `%s`.","37":"invalid argument. Second argument must be a recognized data type. Value: `%s`.","38":"invalid argument. First argument must be array-like. Value: `%s`.","39":"invalid argument. Second argument must be a string. Value: `%s`.","40":"invalid argument. Must provide either a Date object, a JavaScript timestamp (i.e., a nonnegative integer), or a date string. Value: `%s`.","41":"invalid option. Unrecognized rounding mode. Option: `%s`.","42":"invalid argument. Third argument must be either a nonnegative integer or an options object. Value: `%s`.","43":"invalid argument. Fourth argument must be an object. Value: `%s`.","44":"invalid argument. First argument must an iterator protocol-compliant object. Value: `%s`.","45":"invalid argument. Second argument must be a positive integer. Value: `%s`.","46":"invalid argument. First argument must be an iterator protocol-compliant object. Value: `%s`.","47":"invalid argument. Must provide an object. Value: `%s`.","48":"invalid argument. Object property values must be functions. Key: `%s`. Value: `%s`.","49":"invalid argument. First argument must be a number. Value: `%s`.","50":"invalid option. Second `%s` parameter option must be a positive integer. Option: `%s`.","51":"invalid argument. First argument must be an array. Value: `%s`.","52":"invalid argument. First argument must be an array of length `%u`. Value: `%s`.","53":"invalid argument. First argument must be an array of length %u. Value: `%s`.","54":"unexpected error. Scaling weight vector by nonpositive value, likely due to too large value of eta * lambda. Value: `%f`.","55":"invalid argument. Second argument must be a boolean. Value: `%s`.","56":"invalid argument. Must provide either a valid data source, options argument, or both. Value: `%s`.","57":"invalid option. `%s` option must be an array-like object, typed-array-like, a Buffer, or an ndarray. Option: `%s`.","58":"invalid option. Data source must be an array-like object, typed-array-like, a Buffer, or an ndarray. Value: `%s`.","59":"invalid option. `%s` option must be a recognized casting mode. Option: `%s`.","60":"invalid argument. Input string must have a length equal to %u. Value: `%s`.","61":"invalid assignment. `%s` must be a boolean. Value: `%s`.","62":"invalid assignment. `%s` must be a string. Value: `%s`.","63":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","64":"invalid assignment. `%s` must be a positive number. Value: `%s`.","65":"invalid assignment. `%s` must be either an array of strings or an empty array. Value: `%s`.","66":"invalid assignment. `%s` must be a number or number array. Value: `%s`.","67":"invalid assignment. A `%s` must be a number on the interval: [0, 1]. Value: `%f`.","68":"invalid assignment. `%s` must be a string or a string array. Value: `%s`","69":"invalid assignment. Unsupported/unrecognized line style. Must be one of the following: \"%s\". Value: `%s`.","70":"invalid argument. Must provide a Uint32Array. Value: `%s`.","71":"invalid argument. First argument must be a positive number. Value: `%s`.","72":"invalid argument. Second argument must be a positive number. Value: `%s`.","73":"invalid argument. Second argument must be a probability. Value: `%s`.","74":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%s`.","75":"invalid option. `%s` option must have a `MIN` property specifying the minimum possible pseudorandom integer value.","76":"invalid option. `%s` option must have a `MAX` property specifying the maximum possible pseudorandom integer value.","77":"invalid argument. First argument must be an integer and not NaN. Value: `%s`.","78":"invalid argument. Second argument must be an integer and not NaN. Value: `%s`.","79":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d,%d]`.","80":"invalid argument. First argument must be either a string containing presentation text or an options object specifying a presentation file to load. Value: `%s`.","81":"invalid argument. Second argument must be an options object. Value: `%s`.","82":"invalid argument. Invalid presentation identifier. Must be either a string or nonnegative integer. Value: `%s`.","83":"invalid argument. Workspace name already exists. Value: `%s`.","84":"invalid argument. Must provide a string, regular expression, nonnegative integer, or an array of nonnegative integers. Value: `%s`.","85":"invalid argument. Unrecognized tutorial name. Value: `%s`.","86":"invalid argument. Documentation argument must be a string. Value: `%s`.","87":"invalid option. `%s` option must be a regular expression. Option: `%s`.","88":"internal error. Unrecognized pattern type: `%s`.","89":"invalid option. `%s` option must be a readable stream. Option: `%s`.","90":"invalid argument. Denominator degrees of freedom must be a positive number. Value: `%s`.","91":"invalid argument. Scale parameter must be a number. Value: `%s`.","92":"invalid argument. Mean parameter `%s` must be a probability. Value: `%s`.","93":"invalid argument. Population size must be a nonnegative integer. Value: `%s`.","94":"invalid argument. Subpopulation size must be a nonnegative integer. Value: `%s`.","95":"invalid argument. Number of draws must be a nonnegative integer. Value: `%s`.","96":"invalid assignment. Must be a nonnegative integer. Value: `%s`.","97":"invalid assignment. Must be larger than or equal to %u. Value: `%u`.","98":"invalid assignment. Must be less than or equal to %u. Value: `%u`.","99":"invalid argument. Number of trials until experiment is stopped must be a positive number. Value: `%s`.","00":"not implemented","01":"invalid invocation. `this` context must be a constructor.","02":"invalid invocation. `this` is not a complex number array.","03":"invalid arguments. Target array lacks sufficient storage to accommodate source values.","04":"invalid arguments. Creating a generic array from an ArrayBuffer is not supported.","05":"invalid arguments. Must provide a length, typed array, array-like object, or an iterable.","06":"invalid arguments. Generated array exceeds maximum array length.","07":"invalid arguments. If either of the first two arguments are complex numbers, the output array must be a complex number array or a \"generic\" array-like object.","08":"invalid arguments. If either of the first two arguments are complex numbers, the output array data type must be a complex number data type or \"generic\".","09":"not supported. The current environment does not support SharedArrayBuffers, and, unfortunately, SharedArrayBuffers cannot be polyfilled. For shared memory applications, upgrade your runtime environment to one which supports SharedArrayBuffers.","0A":"insufficient arguments. Must provide a search value.","0B":"invalid argument. Attempted to add duplicate listener.","0C":"exception","0D":"unexpected error. Benchmark failed.","0E":"unexpected error. Invalid benchmark.","0F":"unexpected error.","0G":"invalid invocation. Constructor must be called with the `new` keyword.","0H":"unexpected error. Max retries exceeded. Too many open files.","0I":"insufficient arguments. Must provide two or more iterators.","0J":"insufficient arguments. Must provide both an iterator and a static value.","0K":"invalid invocation. `this` is not a fluent interface iterator.","0L":"insufficient arguments. Must provide a hash function.","0M":"invalid argument. Iterator arguments must be iterator protocol-compliant objects.","0N":"insufficient arguments. Must provide at least one iterator function.","0O":"invalid argument. Providing a number is not supported.","0P":"invalid argument. Providing a complex number is not supported.","0Q":"invalid argument. Providing an ndarray is not supported.","0R":"invalid argument. Providing an array-like object is not supported.","0S":"invalid argument. If the first argument is an ndarray, the second argument must be an ndarray.","0T":"invalid argument. Output array must have the same number of elements (i.e., length) as the input array.","0U":"invalid argument. If the first argument is an array-like object, the second argument must be an array-like object.","0V":"invalid argument. Providing a number is not supported. Consider providing a zero-dimensional ndarray containing the numeric value.","0W":"invalid argument. Providing a complex number is not supported. Consider providing a zero-dimensional ndarray containing the complex number value.","0X":"invalid arguments. Must provide either a data source, array shape, or both.","0Y":"invalid arguments. Array shape is incompatible with provided data source. Number of data source elements does not match array shape.","0Z":"invalid argument. Cannot broadcast an array to a shape having fewer dimensions. Arrays can only be broadcasted to shapes having the same or more dimensions.","0a":"invalid argument. First argument must contain at least one element.","0b":"invalid arguments. The length of the first argument is incompatible with the second and third arguments.","0c":"invalid argument. Must provide an ndarray having two or more dimensions.","0d":"invalid arguments. Arrays must have the same shape.","0e":"invalid invocation. Cannot write to a read-only array.","0f":"invalid argument. Fourth argument length must be equal to 1 when creating a zero-dimensional ndarray.","0g":"invalid arguments. The input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","0h":"invalid arguments. Interface must accept at least one input and/or output ndarray. Based on the provided arguments, `nin+nout` equals `0`.","0i":"invalid arguments. Fourth argument does not equal the number of input and output ndarrays.","0j":"invalid argument. Unexpected number of types. A type must be specified for each input and output ndarray for each provided ndarray function.","0k":"invalid argument. The third argument must have the same number of elements as the first argument.","0l":"invalid invocation. Insufficient arguments.","0m":"invalid invocation. Too many arguments.","0n":"invalid arguments. Unable to resolve an ndarray function supporting the provided array argument data types.","0o":"invalid operation. Unable to load Electron. Ensure Electron is installed and try again.","0p":"invalid operation. A browser environment has no support for changing the current working directory.","0q":"invalid operation. The environment does not support reading from `stdin`.","0r":"unexpected error. PRNG returned NaN.","0s":"invalid argument. Third argument must be less than or equal to the first argument.","0t":"invalid argument. Second argument must be less than or equal to the first argument.","0u":"invalid operation. Cannot delete the `base` workspace.","0v":"invalid invocation. Must provide either a string containing presentation text or an options object specifying a presentation file to load.","0w":"invalid argument. When not provided presentation text, an options argument must specify a presentation file to load.","0x":"invalid invocation. Not currently in a presentation workspace. Must provide either a string or nonnegative integer which corresponds to the identifier of the presentation to be stopped.","0y":"unexpected error. Command execution terminated.","0z":"invalid operation. Cannot load a file into a REPL which has already closed.","1A":"invalid arguments. First and second arguments must be arrays having the same length.","1B":"invalid arguments. Subpopulation size must be less than or equal to population size.","1C":"invalid arguments. Number of draws must be less than or equal to population size.","1D":"invalid argument. First argument must contain at least one element greater than zero (i.e., the total number number of observations must be greater than zero).","1E":"invalid arguments. First and second arguments must have the same length.","1F":"invalid arguments. First and second arguments must be arrays having the same length.","1G":"invalid arguments. First and second argument must have the same length.","1H":"invalid arguments. Not enough observations. First and second arguments must contain at least four observations.","1I":"invalid arguments. The first and second arguments must have the same length.","1J":"`x` or `x - y` cannot be zero for all elements.","1K":"invalid arguments. Strided array parameters are incompatible with the provided array-like object. Linear index exceeds array bounds.","1L":"invalid arguments. Unable to resolve a strided array function supporting the provided array argument data types.","1M":"invalid arguments. Interface must accept at least one strided input and/or output array. Based on the provided arguments, `nin+nout` equals `0`.","1N":"invalid argument. Unexpected number of types. A type must be specified for each strided input and output array for each provided strided array function.","1O":"invalid argument. Fourth argument is incompatible with the number of strided input and output arrays.","1P":"invalid argument. Input array offset must be a nonnegative integer.","1Q":"invalid argument. Output array offset must be a nonnegative integer.","1R":"invalid argument. Input array must be an array-like object.","1S":"invalid argument. Output array must be an array-like object.","1T":"invalid argument. Input array has insufficient elements based on the associated stride and the number of indexed elements.","1U":"invalid argument. Output array has insufficient elements based on the associated stride and the number of indexed elements.","1V":"insufficient arguments. Must provide either an array of code points or one or more code points as separate arguments.","1W":"invalid argument. Third argument must not be an empty string.","1X":"invalid argument. Pad string must not be an empty string.","1Y":"insufficient arguments. Must provide multiple functions to compose.","1Z":"insufficient arguments. Must provide multiple functions to execute sequentially.","1a":"invalid arguments. First and last arguments must be the same length.","1b":"insufficient arguments. Must provide at least two objects.","1c":"invalid invocation. `this` is not a compact adjacency matrix.","1d":"invalid argument. Cannot specify one or more accessors and a value or writable attribute in the property descriptor.","1e":"invalid argument. The list does not contain the provided list node.","1f":"unexpected error. Unable to resolve global object.","1g":"invalid argument. The output ndarray must be writable. Cannot write to a read-only ndarray.","1h":"invalid arguments. Input and output arrays must have the same length.","1i":"invalid arguments. Input and output arrays must have the same number of elements (i.e., length).","1j":"invalid arguments. Input ndarrays must be broadcast compatible.","1k":"invalid arguments. Input arrays must have the same number of elements (i.e., length).","1l":"insufficient arguments. Must provide both a target object and one or more source objects.","1m":"invalid invocation. `this` is not host tuple.","1n":"invalid invocation. `this` is not the host tuple factory.","1o":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented.","1p":"invalid argument. Second argument must have a length equal to the size of the outermost input array dimension.","1q":"evaluation error. Did not receive timing results.","1r":"evaluation error. Unable to retrieve evaluation results. Ensure that the provided snippet does not return prematurely.","1s":"invalid argument. Must provide a zipped array.","1t":"invalid argument. Array must only contain arrays.","1u":"invalid argument. Indices must be specified as an array.","1v":"invalid argument. All indices must be integers.","1w":"invalid argument. Must provide valid indices (i.e., an index must be on the interval [0, len], where len is the tuple length).","1x":"insufficient arguments. Must provide at least one array.","1y":"invalid argument. Must provide a username or, to get who an authenticated user is following, an access token.","1z":"invalid argument. Must provide a username or, to get a list of repositories an authenticated user has starred, an access token.","2A":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","2B":"invalid argument. First argument must be an ArrayBuffer. Value: `%s`.","2C":"invalid argument. Byte offset must be a nonnegative integer. Value: `%s`.","2D":"invalid argument. Byte offset must be a multiple of `%u`. Value: `%u`.","2E":"invalid arguments. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","2F":"invalid argument. Length must be a nonnegative integer. Value: `%s`.","2G":"invalid arguments. ArrayBuffer has insufficient capacity. Either decrease the array length or provide a bigger buffer. Minimum capacity: `%u`.","2H":"invalid argument. Second argument must be a function. Value: `%s`.","2I":"invalid argument. First argument must have a length which is a multiple of two. Length: `%u`.","2J":"invalid argument. First argument must be an array-like object or an iterable. Value: `%s`.","2K":"invalid argument. Must provide a nonnegative integer. Value: `%s`.","2L":"invalid argument. Index argument must be a nonnegative integer. Value: `%s`.","2M":"invalid argument. Index argument is out-of-bounds. Value: `%u`.","2N":"invalid argument. First argument must be either a complex number, an array-like object, or a complex number array. Value: `%s`.","2O":"invalid argument. First argument must be an array-like object. Value: `%s`.","2P":"invalid argument. Second argument must be a recognized array data type. Value: `%s`.","2Q":"invalid argument. Second argument must have a recognized/supported data type. Type: `%s`. Value: `%s`.","2R":"invalid argument. Unable to parse %s date.","2S":"invalid argument. Numeric %s date must be either a Unix or JavaScript timestamp.","2T":"invalid argument. %s date must either be a date string, Date object, Unix timestamp, or JavaScript timestamp.","2U":"invalid argument. Length must be a positive integer. Value: `%s`.","2V":"invalid argument. Options argument must be an object. Value: `%s`.","2W":"invalid option. `%s` option must be a string. Option: `%s`.","2X":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","2Y":"invalid argument. Must provide a recognized data type. Value: `%s`.","2Z":"invalid argument. Environment lacks Symbol.iterator support. Must provide a length, typed array, or array-like object. Value: `%s`.","2a":"invalid argument. Must provide a length, typed array, array-like object, or an iterable. Value: `%s`.","2b":"invalid argument. Callback argument must be a function. Value: `%s`.","2c":"invalid argument. Iterator argument must be an iterator protocol-compliant object. Value: `%s`.","2d":"invalid argument. First argument must be a nonnegative integer. Value: `%s`.","2e":"invalid argument. Third argument must be a recognized data type. Value: `%s`.","2f":"invalid argument. First argument must be either an array, typed array, or complex typed array. Value: `%s`.","2g":"invalid argument. Start must be numeric. Value: `%s`.","2h":"invalid argument. Stop must be numeric. Value: `%s`.","2i":"invalid argument. Increment must be numeric. Value: `%s`.","2j":"invalid argument. First argument must be either a real or complex number. Value: `%s`.","2k":"invalid argument. Second argument must be either a real or complex number. Value: `%s`.","2l":"invalid argument. Third argument must be an array-like object. Value: `%s`.","2m":"invalid argument. Third argument must be a nonnegative integer. Value: `%s`.","2n":"invalid option. `%s` option must be a real or complex floating-point data type or \"generic\". Option: `%s`.","2o":"invalid option. `%s` option must be a boolean. Option: `%s`.","2p":"invalid argument. Exponent of start value must be numeric. Value: `%s`.","2q":"invalid argument. Exponent of stop value must be numeric. Value: `%s`.","2r":"invalid argument. First argument must be either an array length or an array-like object. Value: `%s`.","2s":"invalid argument. Must provide a typed array or ArrayBuffer. Value: `%s`.","2t":"invalid option. `%s` option must be a nonnegative integer. Option: `%s`.","2u":"invalid argument. Must provide an array-like object. Value: `%s`.","2v":"invalid option. `%s` option must be either `1` or `-1`. Option: `%s`.","2w":"invalid argument. Second argument must be either a function or an options object. Value: `%s`.","2x":"invalid argument. Must provide a typed array. Value: `%s`.","2y":"invalid argument. Second argument must be an array-like object. Value: `%s`.","2z":"invalid argument. Third argument must be an integer. Value: `%s`.","3A":"invalid argument. Key path must be a string or a key array. Value: `%s`.","3B":"invalid argument. Must provide a string. Value: `%s`.","3C":"invalid argument. Must provide a valid position (i.e., a nonnegative integer). Value: `%s`.","3D":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%u`.","3E":"invalid argument. Second argument must be callable. Value: `%s`.","3F":"invalid argument. First argument must be a string. Value: `%s`.","3G":"invalid argument. Fourth argument must be one of the following: \"%s\". Value: `%s`.","3H":"invalid argument. Fifth argument must be one of the following: \"%s\". Value: `%s`.","3I":"invalid argument. Second argument must be either an object (except null) or a function. Value: `%s`.","3J":"invalid argument. Must provide a function. Value: `%s`.","3K":"invalid argument. Must provide either an options object or a callback function. Value: `%s`.","3L":"invalid argument. First argument must be an object. Value: `%s`.","3M":"invalid option. `%s` option must be a writable stream. Option: `%s`.","3N":"invalid argument. Third argument must be a function. Value: `%s`.","3O":"invalid option. `%s` option must be either a positive integer or `null`. Option: `%s`.","3P":"invalid option. `%s` option must be a positive integer. Option: `%s`.","3Q":"invalid argument. First argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3R":"invalid argument. Second argument must be a 1-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","3S":"invalid argument. Arrays must be the same length. First argument length: `%u`. Second argument length: `%u`.","3T":"invalid argument. First argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3U":"invalid argument. Second argument must be either an array-like object or a one-dimensional ndarray. Value: `%s`.","3V":"invalid argument. First argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3W":"invalid argument. Second argument must be a 1-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","3X":"invalid argument. Second argument must be a nonnegative integer. Value: `%s`.","3Y":"invalid argument. Second argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3Z":"invalid argument. Last argument must be a nonnegative integer. Value: `%s`.","3a":"invalid argument. Last argument must not exceed the number of bytes in the input ArrayBuffer. Value: `%s`.","3b":"invalid argument. Must provide a Buffer. Value: `%s`.","3c":"invalid argument. First argument must be a function. Value: `%s`.","3d":"invalid argument. Third argument must be a constructor function. Value: `%s`.","3e":"invalid argument. Real component must be a number. Value: `%s`.","3f":"invalid argument. Imaginary component must be a number. Value: `%s`.","3g":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","3h":"invalid argument. Unsupported/unrecognized dataset name. Value: `%s`.","3i":"invalid option. Unrecognized `%s`. Option: `[%s]`.","3j":"invalid option. `%s` option must be a string or an array of strings. Option: `%s`.","3k":"invalid option. `%s` option must be a positive integer or an array of positive integers. Option: `%s`.","3l":"invalid option. `%s` option must be a positive integer array of length two. Option: `%s`.","3m":"invalid option. `%s` option cannot be less than 1790. Option: `%s`.","3n":"invalid option. `%s` option cannot be greater than 5000. Option: `%s`.","3o":"invalid argument. Must provide an error object. Value: `%s`.","3p":"invalid argument. First argument must be a valid file descriptor (i.e., nonnegative integer). Value: `%s`.","3q":"invalid argument. Last argument must be a function. Value: `%s`.","3r":"invalid argument. Must provide a valid file descriptor (i.e., a nonnegative integer). Value: `%s`.","3s":"invalid argument. First argument must be an array of strings. Value: `%s`.","3t":"invalid argument. Options argument must be either a string or an object. Value: `%s`.","3u":"invalid argument. Predicate function must be a function. Value: `%s`.","3v":"invalid argument. First argument must be an iterator. Value: `%s`.","3w":"invalid argument. Must provide an iterator. Value: `%s`.","3x":"invalid argument. Must provide an iterator protocol-compliant object. Argument: `%u`. Value: `%s`.","3y":"invalid argument. Must provide an iterator protocol-compliant object. Value: `%s`.","3z":"invalid argument. Unable to parse date string. Value: `%s`.","4A":"invalid argument. Second argument must be a number. Value: `%s`.","4B":"invalid argument. Third argument must be a number. Value: `%s`.","4C":"invalid argument. Hash function argument must be a function. Value: `%s`.","4D":"invalid option. `%s` option must be a positive number. Option: `%s`.","4E":"invalid argument. Third argument must be either a nonnegative integer or an object. Value: `%s`.","4F":"invalid arguments. All arguments must be functions. Value: `%s`.","4G":"invalid argument. Each iterator function, except the last iterator function, within an iterator pipeline must return an iterator. Value: `%s`.","4H":"invalid argument. Must provide an an iterator. Value: `%s`.","4I":"invalid return value. Callback function must return an integer. Value: `%s`.","4J":"invalid argument. Fourth argument must be a boolean. Value: `%s`.","4K":"invalid return value. Callback function must return a positive integer. Value: `%s`.","4L":"invalid argument. Fifth argument must be a callback function. Value: `%s`.","4M":"invalid argument. Third argument must be either an integer (starting index) or a callback function. Value: `%s`.","4N":"invalid argument. Fourth argument must be either an integer (ending index) or a callback function. Value: `%s`.","4O":"invalid argument. Unrecognized/unsupported scale function. Value: `%s`.","4P":"invalid argument. Must provide an iterator protocol-compliant object or a number. Argument: `%u`. Value: `%s`.","4Q":"invalid argument. First argument must be a finite number. Value: `%s`.","4R":"invalid option. `%s` option must be a positive finite number. Option: `%s`.","4S":"invalid option. `%s` option must be one of the following: \"%s\". Option: `%s`.","4T":"invalid option. `%s` option must be less than or equal to 79. Option: `%u`.","4U":"invalid option. `%s` option must be less than or equal to 77. Option: `%u`.","4V":"invalid argument. Must provide an argument having a supported data type. Value: `%s`.","4W":"invalid option. Unsupported policy for determining an output array data type. Option: `%s`.","4X":"invalid option. `%s` option must be a recognized/supported data type. Option: `%s`.","4Y":"invalid option. `%s` option must be a recognized/supported output array data type policy. Option: `%s`.","4Z":"invalid argument. Resolution table must be an object. Value: `%s`.","4a":"invalid argument. Resolution table `%s` field value must be either a function or null. Value: `%s`.","4b":"invalid argument. First argument must be a positive integer. Value: `%s`.","4c":"invalid argument. First argument must be a one-dimensional ndarray. Value: `%s`.","4d":"invalid argument. Second argument must be either +1 or -1. Value: `%s`.","4e":"invalid argument. First argument must be a one-dimensional ndarray of length %u. Actual length: `%u`.","4f":"invalid argument. First argument must be an ndarray. Value: `%s`.","4g":"invalid argument. First argument must be an ndarray whose last dimension is of size `%u`. Actual size: `%u`.","4h":"invalid argument. Second argument is incompatible with model loss function. Probability predictions are only supported when the loss function is one of the following: \"%s\". Model loss function: `%s`.","4i":"invalid argument. Second argument must be a string value equal to either \"label\", \"probability\", or \"linear\". Value: `%s`.","4j":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of `eta*lambda`. Value: `%f`.","4k":"invalid option. `%s` option must be a nonnegative number. Option: `%s`.","4l":"invalid option. `%s` option must be an array-like object. Option: `%s`.","4m":"invalid option. First `%s` option must be one of the following: \"%s\". Option: `%s`.","4n":"invalid option. Second `%s` option must be a positive number. Option: `%s`.","4o":"invalid option. Third `%s` option must be a number. Option: `%s`.","4p":"invalid argument. Argument specifying number of dimensions must be a positive integer. Value: `%s`.","4q":"invalid argument. First argument must either be a positive integer specifying the number of clusters or a matrix containing initial centroids. Value: `%s`.","4r":"invalid option. First `%s` parameter option must be greater than or equal to the number of clusters. Options: `%f`.","4s":"invalid argument. Must provide a 1-dimensional ndarray. Value: `%s`.","4t":"invalid argument. Vector length must match centroid dimensions. Expected: `%u``. Actual: `%u``.","4u":"invalid argument. Output argument must be a 1-dimensional ndarray. Value: `%s`.","4v":"invalid argument. Must provide a 2-dimensional ndarray. Value: `%s`.","4w":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u``. Actual: `%u`.","4x":"invalid argument. Output vector length must match the number of data points. Expected: `%u`. Actual: `%u`.","4y":"invalid option. `%s` option method must be one of the following: \"%s\". Option: `%s`.","4z":"invalid option. First `%s` parameter option must be a positive integer. Option: `%s`.","5A":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","5B":"invalid option. Data type cast is not allowed. Casting mode: `%s`. From: `%s`. To: `%s`.","5C":"invalid option. `%s` option must be a recognized order. Option: `%s`.","5D":"invalid option. `%s` option must be an array-like object containing nonnegative integers. Option: `%s`.","5E":"invalid argument. Linear index must not exceed array dimensions. Number of array elements: `%u`. Value: `%d`.","5F":"invalid argument. Input array cannot be broadcast to the specified shape, as the specified shape has a dimension whose size is less than the size of the corresponding dimension in the input array. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5G":"invalid argument. Input array and the specified shape are broadcast incompatible. Array shape: (%s). Desired shape: (%s). Dimension: %u.","5H":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u-1, %u]. Value: `%d`.","5I":"invalid argument. Index must be on the interval: [0, %f]. Value: `%f`.","5J":"invalid argument. Subscripts must not exceed array dimensions. Subscript: `%u`. Value: `%d`.","5K":"invalid argument. First argument must be a recognized data type. Value: `%s`.","5L":"invalid argument. First argument must have a recognized data type. Value: `%s`.","5M":"invalid arguments. Number of indices must match the number of dimensions. ndims: `%u`. nargs: `%u`.","5N":"invalid argument. Indices must be integer valued. Argument: `%u`. Value: `%s`.","5O":"invalid argument. Index must be an integer. Value: `%s`.","5P":"invalid argument. First argument must be a supported ndarray data type. Value: `%s`.","5Q":"invalid argument. Second argument must be an array-like object, typed-array-like, or a Buffer. Value: `%s`.","5R":"invalid argument. Second argument `get` and `set` properties must be functions. Value: `%s`.","5S":"invalid argument. Third argument must be an array-like object containing nonnegative integers. Value: `%s`.","5T":"invalid argument. Number of dimensions must not exceed %u due to stack limits. Value: `%u`.","5U":"invalid argument. Fourth argument must be an array-like object containing integers. Value: `%s`.","5V":"invalid argument. Fourth argument length must match the number of dimensions. Expected number of dimensions: `%u`. Strides length: `%u`.","5W":"invalid argument. Fourth argument must contain a single element equal to `0`. Value: `%d`.","5X":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%s`.","5Y":"invalid argument. Sixth argument must be a supported order. Value: `%s`.","5Z":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%u`.","5a":"invalid option. `%s` option must be a recognized mode. Option: `%s`.","5b":"invalid option. `%s` option must be an array containing recognized modes. Option: `%s`.","5c":"invalid option. Each submode must be a recognized mode. Option: `%s`.","5d":"invalid argument. First argument must be either a function or an array of functions. Value: `%s`.","5e":"invalid argument. Third argument must be an array-like object or null. Value: `%s`.","5f":"invalid argument. Fourth argument must be a positive integer. Value: `%s`.","5g":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%s`.","5h":"invalid argument. Input array must be an ndarray-like object. Value: `%s`.","5i":"invalid argument. Output array must be an ndarray-like object. Value: `%s`.","5j":"invalid argument. Output argument must be either an array, typed array, or object. Value: `%s`.","5k":"invalid argument. Shape argument must be an array-like object containing nonnegative integers. Value: `%s`.","5l":"invalid argument. Linear index must be integer valued. Value: `%s`.","5m":"invalid option. `%s` option must be a supported/recognized mode. Option: `%s`.","5n":"invalid option. `%s` option must be a supported/recognized order. Option: `%s`.","5o":"invalid argument. First argument must be an array-like object containing nonnegative integers. Value: `%s`.","5p":"invalid argument. Number of provided subscripts must match the number of dimensions. ndims: `%u`. Number of subscripts: `%u`.","5q":"invalid argument. Subscripts must be integer valued. Argument: `%u`. Value: `%s`.","5r":"invalid option. `%s` option cannot be an empty array.","5s":"invalid argument. First argument must be either a nonnegative integer or an array of nonnegative integers. Value: `%s`.","5t":"invalid argument. First argument must be an ndarray-like object. Value: `%s`.","5u":"invalid option. `%s` option must either be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","5v":"invalid option. `%s` option must be either a Buffer or a string. Option: `%s`.","5w":"invalid argument. Request listener must be a function. Value: `%s`.","5x":"invalid argument. Third argument must be a positive integer. Value: `%s`.","5y":"invalid argument. Number of topics must be a positive integer. Value: `%s`.","5z":"invalid argument. First argument must be a nonnegative integer which is less than the total number of topics. Value: `%s`.","6A":"invalid assignment. `%s` must be a nonnegative integer or nonnegative integer array. Value: `%s`.","6B":"invalid assignment. `%s` must be a nonnegative integer. Value: `%s`.","6C":"invalid assignment. Unrecognized/unsupported `%s`. Must be one of the following: \"%s\". Value: `%s`.","6D":"invalid assignment. Unrecognized/unsupported `%s`. Value: `%s`.","6E":"invalid assignment. `%s` must be a nonnegative integer or null. Value: `%s`.","6F":"invalid assignment. `%s` must be a string or null. Value: `%s`.","6G":"invalid argument. Must provide a supported viewer. Value: `%s`.","6H":"invalid assignment. `%s` must be a function. Value: `%s`.","6I":"invalid assignment. `%s` must be either null or an array. Value: `%s`.","6J":"invalid assignment. `%s` must be a string, function, or null. Value: `%s`.","6K":"invalid argument. `options` argument must be an object. Value: `%s`.","6L":"invalid assignment. `%s` must be a number. Value: `%s`.","6M":"invalid assignment. `%s` must be a number on the interval `[0,1]`. Value: `%f`.","6N":"invalid assignment. `%s` must be array-like. Value: `%s`.","6O":"invalid arguments. Must provide equal length array-like objects. x length: `%u`, y length: `%u`.","6P":"invalid assignment. `%s` must be a string or a function. Value: `%s`.","6Q":"invalid assignment. `%s` must be a number or a function. Value: `%s`.","6R":"invalid assignment. `%s` must be one of the following: \"%s\". Value: `%s`.","6S":"invalid assignment. `%s` must be a nonnegative integer or a function. Value: `%s`.","6T":"invalid assignment. `%s` must be a supported symbol. Symbols: \"%s\". Value: `%s`.","6U":"invalid argument. `options` argument must be a plain object. Value: `%s`.","6V":"invalid assignment. `%s` must be either a string or a string array. Value: `%s`.","6W":"invalid assignment. `%s` must be a string or a string array. Value: `%s`.","6X":"invalid assignment. `%s` must be a string or string array. Value: `%s`.","6Y":"invalid assignment. Unrecognized/unsupported symbol. Value: `[%s]`.","6Z":"invalid assignment. `%s` must be an array. Value: `%s`.","6a":"invalid assignment. `%s` must be either a finite number, Date, or null. Value: `%s`.","6b":"invalid assignment. `%s` must be a boolean or boolean array. Value: `%s`.","6c":"invalid assignment. `%s` must be either a string or string array. Value: `%s`.","6d":"invalid assignment. Unrecognized/unsupported orientation. A `%s` value must be one of the following: \"%s\". Value: `%s`.","6e":"invalid assignment. `%s` must be either a finite number or null. Value: `%s`.","6f":"invalid state. x and y are different lengths. x length: `%u`, y length: `%u`.","6g":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[","6h":"invalid assignment. `%s` must be a positive integer or null. Value: `%s`.","6i":"invalid assignment. `%s` size is smaller than the number of data elements. Number of elements: `%u`. Value: `%u`.","6j":"invalid assignment. `%s` must be an array-like object or an ndarray. Value: `%s`.","6k":"invalid assignment. `%s` length exceeds maximum data buffer size. Buffer size: `%u`. Length: `%u`.","6l":"invalid assignment. `%s` must be a finite number or null. Value: `%s`.","6m":"invalid assignment. `%s` must be a finite number or null. Value: `%s.","6n":"invalid assignment. Must be an array or typed array. Value: `%s`.","6o":"invalid option. `%s` option must be an array or typed array. Option: `%s`.","6p":"invalid option. `%s` option must be a function. Option: `%s`.","6q":"invalid argument. Encoding argument must be a string. Value: `%s`.","6r":"invalid argument. Must provide either a string, nonnegative integer, or an options object. Value: `%s`.","6s":"invalid argument. First argument must be either a string or nonnegative integer. Value: `%s`.","6t":"invalid argument. Unable to parse mask expression. Ensure the expression is properly formatted, only uses the class letters \"u\", \"g\", \"o\", and \"a\", only uses the operators \"+\", \"-\", and \"=\", and only uses the permission symbols \"r\", \"w\", and \"x\". Value: `%s`.","6u":"invalid option. `%s` option must be a pseudorandom number generator function. Option: `%s`.","6v":"invalid argument. First argument must be a number and not NaN. Value: `%s`.","6w":"invalid argument. Second argument must be a number and not NaN. Value: `%s`.","6x":"invalid argument. Minimum support must be less than maximum support. Value: `[%f,%f]`.","6y":"invalid argument. First argument must be a probability. Value: `%s`.","6z":"invalid option. `%s` option must be a Uint32Array. Option: `%s`.","7A":"invalid argument. First argument must be a positive number and not NaN. Value: `%s`.","7B":"invalid argument. Second argument must be a positive number and not NaN. Value: `%s`.","7C":"invalid argument. Third argument must be a number and not NaN. Value: `%s`.","7D":"invalid argument. Third argument must be less than or equal to the first argument. Value: `%u`.","7E":"invalid argument. Second argument must be less than or equal to the first argument. Value: `%u`.","7F":"invalid %s. State array has insufficient length.","7G":"invalid %s. State array has an incompatible schema version. Expected: `%s`. Actual: `%s`.","7H":"invalid %s. State array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","7I":"invalid %s. State array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7J":"invalid %s. State array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7K":"invalid option. `%s` option must be an Int32Array. Option: `%s`.","7L":"invalid option. `%s` option must be a positive integer less than the maximum signed 32-bit integer. Option: `%u`.","7M":"invalid option. `%s` option must be either a positive integer less than the maximum signed 32-bit integer or an array-like object containing integer values less than the maximum signed 32-bit integer. Option: `%s`.","7N":"invalid argument. Must provide an Int32Array. Value: `%s`.","7O":"invalid %s. State array has an incompatible table length. Expected: `%s`. Actual: `%s`.","7P":"invalid %s. `state` array has insufficient length.","7Q":"invalid %s. `state` array has an incompatible schema version. Expected: %s. Actual: %s.","7R":"invalid %s. `state` array has an incompatible number of sections. Expected: %s. Actual: %s.","7S":"invalid %s. `state` array has an incompatible state length. Expected: `%u`. Actual: `%u`.","7T":"invalid %s. `state` array has an incompatible section length. Expected: `%u`. Actual: `%u`.","7U":"invalid %s. `state` array length is incompatible with seed section length. Expected: `%u`. Actual: `%u`.","7V":"invalid option. `%s` option must be a positive integer less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7W":"invalid option. `%s` option must be either a positive integer less than or equal to the maximum unsigned 32-bit integer or an array-like object containing integer values less than or equal to the maximum unsigned 32-bit integer. Option: `%u`.","7X":"invalid argument. Second argument must be on the interval: (0, 1). Value: `%f`.","7Y":"invalid option. `%s` option cannot be undefined. Option: `%s`.","7Z":"invalid option. Unrecognized/unsupported PRNG. Option: `%s`.","7a":"invalid argument. First argument must be a positive number or an options object. Value: `%s`.","7b":"invalid arguments. Parameters must satisfy the following condition: %s. Value: `[%f, %f, %f]`.","7c":"invalid argument. Scale parameter must be a positive number. Value: `%s`.","7d":"invalid argument. Shape parameter must be a positive number. Value: `%s`.","7e":"invalid argument. First argument must be an integer. Value: `%s`.","7f":"invalid argument. Second argument must be an integer. Value: `%s`.","7g":"invalid argument. `n` must be less than or equal to `N`. Value: `%u`.","7h":"invalid argument. `K` must be less than or equal to `N`. Value: `%u`.","7i":"invalid argument. `%s` argument must be array-like. Value: `%s`.","7j":"invalid input option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","7k":"invalid input option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","7l":"invalid option. `%s` option must be an array of probabilities that sum to one. Option: `%s`.","7m":"invalid argument. Minimum support must be less than maximum support. Value: `[%s,%s]`.","7n":"invalid option. `%s` option must be a string or null. Option: `%s`.","7o":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%s,%s]`.","7p":"invalid argument. Must be one of the following: \"%s\". Value: `%s`.","7q":"invalid argument. Mode must be one of the following: \"%s\". Value: `%s`.","7r":"invalid argument.  Must be one of the following: \"%s\". Value: `%s`.","7s":"invalid operation. Alias already exists in the provided context. Alias: `%s`. Value: `%s`.","7t":"invalid argument. Unrecognized workspace name. Value: `%s`.","7u":"invalid operation. Cannot read from write-only variable `%s`.","7v":"Cannot assign to read only property %s of object #<Object>","7w":"invalid option. `%s` option must be a regular expression or an array-like object. Option: `%s`.","7x":"invalid option. `%s` option must be one of `%s`. Option: `%s`.","7y":"invalid argument. Must provide either an options object or a workspace name. Value: `%s`.","7z":"invalid argument. Must provide either a string or regular expression. Value: `%s`.","8A":"invalid argument. Must provide an integer. Value: `%s`.","8B":"invalid argument. Must provide a positive integer. Value: `%s`.","8C":"invalid argument. Presentation text must be a string. Value: `%s`.","8D":"invalid argument. REPL argument must be a REPL instance. Value: `%s`.","8E":"unexpected error. Unable to reload presentation. Error: %s","8F":"unexpected error. Unable to watch presentation source file. Error: %s","8G":"invalid option. `%s` option must be either a recognized string or boolean. Option: `%s`.","8H":"invalid option. `%s` option must be either a positive integer or null. Option: `%s`.","8I":"invalid operation. Alias already exists in REPL context. Alias: `%s`. Value: `%s`.","8J":"invalid argument. Third argument must be an object. Value: `%s`.","8K":"invalid option. `%s` option must be less than or equal to the period. Option: `%u`.","8L":"invalid option. `%s` option must be greater than 2. Option: `%s`.","8M":"invalid option. `%s` option must be an integer. Option: `%s`.","8N":"invalid option. `%s` option must be an positive integer. Option: `%s`.","8O":"invalid option. `%s` option must be less than the period. Option: `%s`.","8P":"invalid option. `%s` option must be a number. Option: `%s`.","8Q":"invalid option. `%s` option must be an positive even integer. Option: `%s`.","8R":"invalid argument. First argument must be a numeric array. Value: `%s`.","8S":"invalid argument. First argument must contain at least two elements. Value: `%s`.","8T":"invalid argument. Second argument must be an array. Value: `%s`.","8U":"invalid argument. Second argument must contain at least two unique elements. Value: `%s`.","8V":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%f`.","8W":"invalid option. `%s` option must be an array containing at least two unique elements. Option: `%s`.","8X":"invalid argument. Must provide array-like arguments. Value: `%s`.","8Y":"invalid argument. Supplied arrays cannot be empty. Value: `%s`.","8Z":"invalid option. `%s` option must be an array. Option: `%s`.","8a":"invalid argument. Minimum support must be a number. Value: `%s`.","8b":"invalid argument. Maximum support must be a number. Value: `%s`.","8c":"invalid arguments. Minimum support must be less than maximum support. Value: `%f, %f`.","8d":"invalid assignment. Must be a number. Value: `%s`.","8e":"invalid assignment. Must be less than %f. Value: `%f`.","8f":"invalid assignment. Must be greater than %f. Value: `%f`.","8g":"invalid argument. Mean parameter `p` must be a probability. Value: `%s`.","8h":"invalid assignment. Must be a probability. Value: `%s`.","8i":"invalid argument. First shape parameter must be a positive number. Value: `%s`.","8j":"invalid argument. Second shape parameter must be a positive number. Value: `%s`.","8k":"invalid assignment. Must be a positive number. Value: `%s`.","8l":"invalid argument. Number of trials must be a positive integer. Value: `%s`.","8m":"invalid argument. Success probability must be a number between 0 and 1. Value: `%s`.","8n":"invalid assignment. Must be a positive integer. Value: `%s`.","8o":"invalid assignment. Must be a number on the interval: [0, 1]. Value: `%s`.","8p":"invalid argument. Location parameter must be a number. Value: `%s`.","8q":"invalid argument. Rate parameter must be a positive number. Value: `%s`.","8r":"invalid argument. Mean parameter `%s` must be a number. Value: `%s`.","8s":"invalid argument. Minimum support must be an integer. Value: `%s`.","8t":"invalid argument. Maximum support must be an integer. Value: `%s`.","8u":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `%d, %d`.","8v":"invalid assignment. Must be an integer. Value: `%s`.","8w":"invalid assignment. Must be less than or equal to %u. Value: `%d`.","8x":"invalid assignment. Must be greater than or equal to %u. Value: `%s`.","8y":"invalid argument. Shape parameter must be a positive integer. Value: `%s`.","8z":"invalid argument. Numerator degrees of freedom must be a positive number. Value: `%s`.","9A":"invalid argument. Mean parameter `lambda` must be a positive number. Value: `%s`.","9B":"invalid argument. Mode must be a number. Value: `%s`.","9C":"invalid arguments. Parameters must satisfy the following condition: %s. a: `%f`. b: `%f`. c: `%f`.","9D":"invalid assignment. Must be less than or equal to both the maximum support and the mode. Value: `%f`.","9E":"invalid assignment. Must be greater than or equal to both the minimum support and the mode. Value: `%f`.","9F":"invalid assignment. Must be greater than or equal to the minimum support and less than or equal to the maximum support. Value: `%f`.","9G":"invalid argument. An array argument must contain two elements. Value: `%s`.","9H":"invalid argument. Must provide a nonnegative integer or a two-element array. Value: `%s`.","9I":"invalid arguments. Number of successes cannot be larger than the total number of observations. x: `%u`. n: `%u`.","9J":"invalid option. `%s` option must be a probability. Option: `%f`.","9K":"invalid argument. Unsupported/unrecognized distribution name. Value: `%s`.","9L":"invalid argument. First argument must contain nonnegative integers. Index: `%u`. Value: `%s`.","9M":"invalid argument. Probability mass function (PMF) arguments must be numbers. Argument: `%u`. Value: `%s`.","9N":"invalid argument. Second argument must be either an array-like object (or one-dimensional ndarray) of probabilities summing to one, an array-like object (or one-dimensional ndarray) of expected frequencies, or a discrete probability distribution name. Value: `%s`.","9O":"invalid argument. Second argument must only contain numbers. Index: `%u`. Value: `%s`.","9P":"invalid argument. Second argument must only contain nonnegative numbers. Index: `%u`. Value: `%d`.","9Q":"invalid option. `%s` option must be a number on the interval: [0, 1]. Value: `%s`.","9R":"invalid argument. First argument must be an array of arrays or ndarray-like object with dimension two. Value: `%s`.","9S":"invalid argument. First argument must contain nonnegative integers. Value: `%s`.","9T":"invalid argument. First argument must either specify the order of the covariance matrix or be a square 2-dimensional ndarray for storing the covariance matrix. Value: `%s`.","9U":"invalid argument. Second argument must be a 1-dimensional ndarray. Value: `%s`.","9V":"invalid argument. The number of elements (means) in the second argument must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9W":"invalid argument. Vector length must match covariance matrix dimensions. Expected: `%u`. Actual: `%u`.","9X":"invalid argument. Must provide a number. Value: `%s`.","9Y":"invalid argument. Must provide a nonnegative number. Value: `%s`.","9Z":"invalid argument. Must provide a nonnegative number on the interval [0,1]. Value: `%f`.","9a":"invalid argument. Output argument must be an array-like object. Value: `%s`.","9b":"invalid argument. Window size must be a positive integer. Value: `%s`.","9c":"invalid argument. Window size must be greater than or equal to 3. Value: `%s`.","9d":"invalid option. `%s` option must be on the interval [0,1]. Option: `%f`.","9e":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square 2-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","9f":"invalid argument. The number of elements (means) in the second argument must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9g":"invalid argument. Vector length must match correlation matrix dimensions. Expected: `%u`. Actual: `%u`.","9h":"invalid argument. Vector length must match correlation distance matrix dimensions. Expected: `%u`. Actual: `%u`.","9i":"invalid argument. First argument must either specify the order of the correlation matrix or be a square 2-dimensional ndarray for storing the correlation matrix. Value: `%s`.","9j":"invalid argument. Unsupported/unrecognized kernel. Value: `%s`.","9k":"invalid argument. Second argument must be a numeric array. Value: `%s`.","9l":"invalid option. Lower bound `%s` must be strictly less than the upper bound `%s`.","9m":"invalid option. `%s` option must be an array of positive numbers. Option: `%s`.","9n":"invalid option. `%s` option must be an array of length two. Option: `%s`.","9o":"invalid option. `%s` option must be a string denoting a known kernel function or a custom function. Option: `%s`.","9p":"invalid arguments. First argument and `%s` must be arrays having the same length.","9q":"invalid invocation. Incorrect number of arguments. Must provide at least two array-like arguments. Value: `%s`.","9r":"invalid option. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","9s":"invalid argument. First argument must be a typed array or number array. Value: `%s`.","9t":"invalid argument. Second argument must be either a CDF function or a string. Value: `%s`.","9u":"invalid argument. Distribution parameter must be a number. Value: `%s`.","9v":"invalid option. `%s` option must contain at least two unique elements. Value: `%s`.","9w":"invalid argument. Provided arrays cannot be empty. Value: `%s`.","9x":"invalid argument. First argument must be an array of probabilities. Value: `%s`.","9y":"invalid argument. When specified, `%s` arguments must contain at least a length of %u. Value: `%u`.","9z":"invalid argument. Second argument must be one of the following: %s. Value: `%s`.","A0":"invalid option. `%s` option must be a number in `[0,1]`. Option: `%s`.","A1":"invalid option. `%s` option must be a number on the interval: [-1, 1]. Option: `%s`.","A2":"invalid argument. First argument must contain at least two elements. Value: `%s`.","A3":"invalid argument. Second argument must be either a numeric array or an options object. Value: `%s`.","A4":"invalid option. `%s` option must be either `equal` or `unequal`. Option: `%s`.","A5":"invalid argument. `%s` argument must be a numeric array. Value: `%s`.","A6":"invalid option. `%s` option must be one of the following: %s. Option: `%s`.","A7":"invalid argument. Third argument must be a positive number. Value: `%s`.","A8":"invalid argument. Fourth argument must be a positive number. Value: `%s`.","A9":"invalid operation. Serialization function must return a string or Buffer. Value: `%s`.","AA":"invalid argument. In binary mode, a provided value must be a string, Buffer, or Uint8Array. Value: `%s`.","AB":"invalid option. `%s` option must be either a string or a regular expression. Option: `%s`.","AC":"invalid argument. First input array offset must be a nonnegative integer. Value: `%s`.","AD":"invalid argument. Second input array offset must be a nonnegative integer. Value: `%s`.","AE":"invalid argument. Output array offset must be a nonnegative integer. Value: `%s`.","AF":"invalid argument. Must provided recognized data types. Unable to resolve a data type string. Value: `%s`.","AG":"invalid argument. Input array offset must be a nonnegative integer. Value: `%s`.","AH":"invalid argument. Input array stride must be an integer. Value: `%s`.","AI":"invalid argument. Output array stride must be an integer. Value: `%s`.","AJ":"invalid option. `%s` option must be an array of strings. Option: `%s`.","AK":"invalid argument. Must provide a valid position (i.e., within string bounds). Value: `%s`.","AL":"invalid argument. Third argument must be a boolean. Value: `%s`.","AM":"invalid argument. Must provide valid code points (i.e., nonnegative integers). Value: `%s`.","AN":"invalid argument. Must provide a valid code point (cannot exceed max). Value: `%s`.","AO":"invalid argument. Third argument must be a string. Value: `%s`.","AP":"invalid argument. Output string length exceeds maximum allowed string length. Value: `%u`.","AQ":"invalid argument. Third argument must be a string or an array of strings. Value: `%s`.","AR":"invalid argument. At least one padding option must have a length greater than 0. Left padding: `%s`. Right padding: `%s`.","AS":"invalid argument. Second argument must be an array of strings. Value: `%s`.","AT":"invalid argument. Second argument must be a string or regular expression. Value: `%s`.","AU":"invalid argument. Third argument must be a string or replacement function. Value: `%s`.","AV":"invalid argument. Must provide a string or an array of strings. Value: `%s`.","AW":"invalid argument. If only providing a single argument, must provide a Date object. Value: `%s`.","AX":"invalid argument. First argument must be either a string or integer. Value: `%s`.","AY":"invalid argument. Day number must be on the interval: `[1, %u]`. Value: `%d`.","AZ":"invalid argument. First argument must be either a string, integer, or Date object. Value: `%s`.","Aa":"invalid argument. An integer month value must be on the interval: [1, 12]. Value: `%s`.","Ab":"invalid argument. Must provide a recognized month. Value: `%s`.","Ac":"invalid argument. Must provide either an integer or a `Date` object. Value: `%s`.","Ad":"invalid argument. Must provide either a string, integer, or Date object. Value: `%s`.","Ae":"invalid argument. Must provide an array of nonnegative integers. Value: `%s`.","Af":"invalid argument. Input array must contain two elements. Value: `%s`.","Ag":"invalid argument. Must provide a collection. Value: `%s`.","Ah":"invalid argument. First argument must be a collection. Value: `%s`.","Ai":"invalid argument. First argument must be either an array, typed array, or an array-like object. Value: `%s`.","Aj":"invalid argument. All arguments must be functions. Value: `%s`.","Ak":"invalid argument. Number of function invocations must be a nonnegative integer. Value: `%s`.","Al":"invalid argument. First argument must be an array of functions. Value: `%s`.","Am":"invalid argument. Last argument must be a collection. Value: `%s`.","An":"invalid argument. Must provide either a valid buffer size (i.e., a positive integer) or an array-like object which can serve as the underlying buffer. Value: `%s`.","Ao":"invalid argument. An iterator must return an array-like object containing vertices. Value: `%s`.","Ap":"invalid argument. Callback must return an array-like object containing vertices. Value: `%s`.","Aq":"invalid argument. Callback must return an array-like object. Value: `%s`.","Ar":"invalid argument. Each element of the adjacency list must be an array-like object. Value: `%s`.","As":"invalid argument. Each element of the edge list must be an array-like object. Value: `%s`.","At":"invalid argument. Second argument must be an array-like object or an iterable. Value: `%s`.","Au":"invalid argument. First argument exceeds matrix dimensions. Value: `%u`.","Av":"invalid argument. Second argument exceeds matrix dimensions. Value: `%u`.","Aw":"invalid argument. Vertex cannot exceed matrix dimensions. Value: `%u`.","Ax":"invalid argument. Second argument must be a recognized output path convention. Value: `%s`.","Ay":"invalid argument. Cannot convert Windows extended-length paths to POSIX paths. Value: `%s`.","Az":"invalid argument. Arity argument must be a positive integer. Value: `%s`.","B0":"invalid argument. Property descriptor must be an object. Value: `%s`.","B1":"invalid argument. The `value` property of the property descriptor must be a function. Value: `%s`.","B2":"invalid argument. Second argument must be an object of property descriptors. Value: `%s`.","B3":"invalid argument. Path must be a string. Value: `%s`.","B4":"invalid argument. Third argument must be a recognized location. Value: `%s`.","B5":"invalid argument. Must provide a recognized iteration direction. Value: `%s`.","B6":"invalid argument. Must provide an object-like value. Value: `%s`.","B7":"invalid argument. Must provide a regular expression string. Value: `%s`.","B8":"invalid argument. Filename must be a string. Value: `%s`.","B9":"invalid argument. First argument must be an array of positive integers. Value: `%s`.","BA":"invalid argument. First argument must be object-like. Value: `%s`.","BB":"invalid argument. Must provide an array of arrays. Value: `%s`.","BC":"invalid argument. Must provide a boolean. Value: `%s`.","BD":"invalid argument. Second argument must have a prototype from which another object can inherit. Value: `%s`.","BE":"invalid argument. A provided constructor must be either an object (except null) or a function. Value: `%s`.","BF":"invalid argument. If the input array is an ndarray, the output array must also be an ndarray. Value: `%s`.","BG":"invalid argument. If the input array is an array-like object, the output array must also be an array-like object. Value: `%s`.","BH":"invalid argument. First argument must be an array-like object or an ndarray. Value: `%s`.","BI":"invalid argument. If the first input array is an ndarray, the second input array must also be an ndarray. Value: `%s`.","BJ":"invalid argument. If the input arrays are ndarrays, the output array must also be an ndarray. Value: `%s`.","BK":"invalid argument. If the first input array is an array-like object, the second input array must also be an array-like object. Value: `%s`.","BL":"invalid argument. If the input arrays are array-like objects, the output array must also be an array-like object. Value: `%s`.","BM":"invalid argument. First argument must be an array-like object containing array-like objects. Index: `%u`. Value: `%s`.","BN":"invalid argument. First argument must be a three-dimensional nested array. Index: `%u`. Value: `%s`.","BO":"invalid argument. First argument must be a four-dimensional nested array. Index: `%u`. Value: `%s`.","BP":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BQ":"invalid argument. First argument must be a four-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BR":"invalid argument. First argument must be a five-dimensional nested array. Index: `%u`. Value: `%s`.","BS":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u). Value: `%s`.","BT":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u). Value: `%s`.","BU":"invalid argument. First argument must be a five-dimensional nested array. Indices: (%u, %u, %u, %u). Value: `%s`.","BV":"invalid argument. A merge source must be an object. Value: `%s`.","BW":"invalid option. `%s` option must be either a boolean or a function. Option: `%s`.","BX":"invalid argument. Source argument must be an object. Value: `%s`.","BY":"invalid argument. Target argument must be an object. Value: `%s`.","BZ":"invalid argument. Must provide an array of strings. Value: `%s`.","Ba":"invalid argument. Field names must be distinct. Value: `%s`.","Bb":"invalid argument. Provided field name is reserved. Name: `%s`.","Bc":"invalid arguments. Arguments are incompatible with the number of tuple fields. Number of fields: `%u`. Number of data elements: `%u`.","Bd":"invalid argument. Source is incompatible with the number of tuple fields. Number of fields: `%u`. Source length: `%u`.","Be":"invalid invocation. Number of arguments is incompatible with the number of tuple fields. Number of fields: `%u`. Number of arguments: `%u`.","Bf":"invalid option. `%s` option must be a recognized data type. Option: `%s`.","Bg":"invalid argument. Second argument must be either a string or an array of strings. Value: `%s`.","Bh":"invalid argument. Must provide a valid URI. Value: `%s`.","Bi":"unexpected error. Child process failed with exit code: `%u`.","Bj":"unexpected error. Child process failed due to termination signal: `%s`.","Bk":"invalid argument. Reviver argument must be a function. Value: `%s`.","Bl":"invalid argument. Second argument must be an array-like object containing nonnegative integers. Value: `%s`.","Bm":"invalid argument. Must provide either an array, typed array, or an array-like object. Value: `%s`.","Bn":"invalid argument. Must provide a recognized type. Value: `%s`.","Bo":"invalid argument. Second argument must be an array containing only nonnegative integers. Value: `%s`.","Bp":"invalid invocation. Unexpected number of input arguments. Expected: `%u`. Actual: `%u`.","Bq":"evaluation error. Encountered an error when evaluating snippet. %s","Br":"invalid option. `%s` option must be a positive integer or null. Option: `%s`.","Bs":"insufficient arguments. Expected %u argument(s) and only received %u argument(s).","Bt":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: %u. Actual: %u.","Bu":"invalid invocation. Number of arguments exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bv":"invalid invocation. The configured arity exceeds the number of possible curried function invocations. Expected: `%u`. Actual: `%u`.","Bw":"invalid argument. Must provide array arguments. Value: `%s`.","Bx":"invalid argument. Last argument must be either an array or an options object. Value: `%s`.","By":"invalid argument. Repository slug must be a string. Value: `%s`.","Bz":"invalid argument. Issue title must be a string. Value: `%s`.","C0":"invalid option. `%s` must be one of the following: \"%s\". Option: `%s`.","C1":"invalid argument. Repository name must be a string. Value: `%s`.","C2":"invalid option. `%s` option must be a valid URI. Option: `%s`.","C3":"invalid option. `%s` option must be a 20-character string. Option: `%s`.","C4":"invalid option. `%s` option must be a 40-character string. Option: `%s`.","C5":"invalid argument. Token id must be a nonnegative integer. Value: `%s`.","C6":"invalid argument. Workflow identifier must be a string. Value: `%s`.","C7":"invalid option. `%s` option must be an object of input key-value pairs. Option: `%s`.","C8":"invalid option. `%s` option must be a positive integer or \"last\". Option: `%s`.","C9":"invalid option. `%s` organization name option must be a string. Option: `%s`.","CA":"invalid option. Unknown method. Option: `%s`.","CB":"invalid option. Unrecognized `%s` option. Must be one of the following: \"%s\". Option: `%s`.","CC":"invalid argument. Repository slug must consist of an owner and a repository (e.g., \"stdlib-js/utils\"). Value: `%s`.","CD":"invalid argument. Topics argument must be an array of strings. Value: `%s`.","CE":"invalid option. `%s` option must be one of the following: \"%s\" or \"%s\". Option: `%s`.","CF":"invalid argument. Must provide a supported license SPDX identifier. Value: `%s`.","CG":"invalid argument. Must provide a supported file type. Value: `%s`.","CH":"invalid argument. First argument must be either a string or Buffer. Value: `%s`.","CI":"invalid argument. Second argument must be either a string or Buffer. Value: `%s`.","CJ":"invalid argument. A header object must map each filename extension to a license header string. `%s: %s`. Value: `%s`.","CK":"invalid argument. Second argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CL":"invalid argument. Second argument must be either a string, Buffer, or regular expression. Value: `%s`.","CM":"invalid argument. A header object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CN":"invalid argument. Second argument must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Value: `%s`.","CO":"invalid argument. Third argument must be either a string or Buffer. Value: `%s`.","CP":"invalid argument. Third argument must be either a string or an object whose keys are filename extensions and whose values are header strings. Value: `%s`.","CQ":"invalid argument. Database already contains an entry for the provided URI: `%s`.","CR":"invalid argument. Database already contains an entry for the provided id: `%s`.","CS":"invalid argument. First argument must be a URI. Value: `%s`.","CT":"invalid argument. Second argument must be either a string or regular expression. Value: `%s`.","CU":"invalid option. A `%s` option object must map each filename extension to a license header string or regular expression. `%s: %s`. Value: `%s`.","CV":"invalid option. `%s` option must be either a string, a regular expression, or an object whose keys are filename extensions and whose values are header strings or regular expressions. Option: `%s`.","CW":"invalid option. `%s` option must end with \"package.json\". Option: `%s`.","CX":"invalid argument. Last argument must be a callback function. Value: `%s`.","CY":"invalid option. `%s` option must be an array of package names. Option: `%s`.","CZ":"invalid argument. Version argument must be a string. Value: `%s`.","Ca":"invalid argument. Must provide either a string or a Buffer. Value: `%s`.","Cb":"invalid argument. Must provide either a string or Buffer. Value: `%s`.","Cc":"invalid argument. First argument must be either a string or array of strings. Value: `%s`.","Cd":"invalid option. `%s` option must be an object. Option: `%s`.","Ce":"unexpected error. File does not exist. Unable to resolve file: %s.","Cf":"invalid argument. Must provide either a string or an array of strings. Value: `%s`.","Cg":"invalid argument. Must provide either a string or an array of strings. Value: `%s`. Index: `%u`.","Ch":"unexpected error. Failed to sort packages. Detected the following dependency chain containing a cycle: `%s`.","Ci":"invalid node. Equation comments must have a valid label. Node: `%s`.","Cj":"invalid node. Equation comments must have valid alternate text. Node: `%s`.","Ck":"invalid node. Equation comments must have valid raw equation text. Node: `%s`.","Cl":"invalid node. Invalid equation comment. Ensure that the Markdown file includes both starting and ending equation comments. Node: `%s`.","Cm":"invalid node. Equation element must have a valid label. Node: `%s`.","Cn":"unexpected error. Code block configuration settings should be provided as comma-separated `key:value` pairs (e.g., `foo:true, bar:\"string\", baz:[\"error\",2]`). Value: `%s`.","Co":"unexpected error. Code block configuration values should be parseable as JSON. Value: `%s`.","Cp":"unexpected error. Encountered an error when executing code block. File: `%s`. Message: `%s`.","Cq":"unexpected error. Expected code block to throw an exception. File: `%s`.","Cr":"invalid node. Ensure that the Markdown file includes both a starting `<section class=\"related\">` and closing `</section>\\n\\n<!-- /.related -->`. Node: `%s`.","Cs":"invalid node. Equation comments must have valid equation text. Node: `%s`.","Ct":"invalid node. Equation comments must have valid labels. Node: `%s`.","Cu":"invalid option. `%s` option must begin with \"@stdlib/\". Option: `%s`.","Cv":"invalid argument. First argument must be a list of file paths. Value: `%s`.","Cw":"invalid arguments. Subpopulation size must be less than or equal to the population size.","Cx":"invalid arguments. Number of draws must be less than or equal to the population size.","Cy":"invalid arguments. Fourth argument is not compatible with the number of input and output ndarrays.","Cz":"invalid arguments. Input buffer is incompatible with the specified meta data. Ensure that the offset is valid with regard to the strides array and that the buffer has enough elements to satisfy the desired array shape.","D0":"invalid arguments. Length of the first argument is incompatible with the second and third arguments.","D1":"invalid argument. Provided collections must have the same length.","D2":"invalid argument. First argument must be an array-like object containing nonnegative integers.","D3":"invalid arguments. Input arrays must have the same length.","D4":"invalid argument. Must provide valid indices (i.e., must be a nonnegative integer less than or equal to the tuple length).","D5":"not implemented. Please post an issue on the @stdlib/stdlib issue tracker if you would like this to be implemented. https://github.com/stdlib-js/stdlib/issues/new/choose","D6":"invalid operation. Parser is unable to parse new chunks, as the parser has been closed. To parse new chunks, create a new parser instance.","D7":"invalid operation. Parser is in an unrecoverable error state. To parse new chunks, create a new parser instance.","D8":"invalid argument. First argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","D9":"invalid argument. Second argument must be a one-dimensional ndarray containing double-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float64Array). Value: `%s`.","DA":"invalid argument. First argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DB":"invalid argument. Second argument must be a one-dimensional ndarray containing single-precision floating-point numbers (i.e., an ndarray whose underlying data buffer is a Float32Array). Value: `%s`.","DC":"invalid assignment. `%s` size is less than the number of data elements. Number of elements: `%u`. Value: `%u`.","DD":"invalid assignment. `%s` must be a string or an array of strings. Value: `%s`.","DE":"invalid assignment. `%s` must be a number or an array of numbers. Value: `%s`.","DF":"invalid assignment. `%s` must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","DG":"invalid assignment. `%s` must be a finite number, Date, or null. Value: `%s`.","DH":"invalid assignment. `%s` must be a boolean or an array of booleans. Value: `%s`.","DI":"invalid assignment. `%s` must be a number or null. Value: `%s`.","DJ":"invalid assignment. `%s` must be an array of strings or an empty array. Value: `%s`.","DK":"invalid state. x and y are different lengths. x length: `%u`. y length: `%u`.","DL":"invalid state. Each `x[i]:y[i]` pair must be the same length. x[%u].length: `%u`, y[%u].length: `%u`.","DM":"invalid assignment. `%s` must be a number on the interval: [0, 1]. Value: `%f`.","DN":"invalid assignment. `%s` must be null or an array. Value: `%s`.","DO":"invalid arguments. Must provide equal length array-like objects. x length: `%u`. y length: `%u`.","DP":"invalid argument. The number of comparisons must be greater or equal to the number of p-values to be adjusted. Value: `%u`.","DQ":"invalid argument. Second argument must be one of the following: \"%s\". Value: `%s`.","DR":"invalid option. `%s` option must be a number on the interval: [0, 1]. Option: `%s`.","DS":"invalid argument. First argument must contain nonnegative integers. Indices: (%s). Value: `%s`.","DT":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Number of input array dimensions: %u.","DU":"invalid argument. First argument must be an array of arrays or a two-dimensional ndarray-like object. Value: `%s`.","DV":"invalid arguments. Minimum support must be less than maximum support. Value: `(%f, %f)`.","DW":"invalid arguments. Minimum support must be less than or equal to maximum support. Value: `(%d, %d)`.","DX":"invalid argument. Mean parameter must be a positive number. Value: `%s`.","DY":"invalid argument. Mean parameter must be a probability. Value: `%s`.","DZ":"invalid option. `%s` option must be on the interval: [0, 1]. Option: `%f`.","Da":"invalid argument. Must provide a nonnegative number on the interval: [0, 1]. Value: `%f`.","Db":"invalid argument. First argument must either specify the order of the covariance matrix or be a square two-dimensional ndarray for storing the covariance matrix. Value: `%s`.","Dc":"invalid argument. Second argument must be a one-dimensional ndarray. Value: `%s`.","Dd":"invalid argument. Must provide a one-dimensional ndarray. Value: `%s`.","De":"invalid argument. First argument must either specify the order of the correlation distance matrix or be a square two-dimensional ndarray for storing the correlation distance matrix. Value: `%s`.","Df":"invalid argument. First argument must either specify the order of the correlation matrix or be a square two-dimensional ndarray for storing the correlation matrix. Value: `%s`.","Dg":"invalid argument. Input array must be an array-like object. Value: `%s`.","Dh":"invalid argument. Output array must be an array-like object. Value: `%s`.","Di":"invalid argument. Mask array offset must be a nonnegative integer. Value: `%s`.","Dj":"invalid argument. Must provide recognized data types. Unable to resolve a data type string. Value: `%s`.","Dk":"invalid option. `%s` option must be one of the following: ['%s']. Option: `%s`.","Dl":"invalid argument. Database already contains an entry for the provided URI. Value: `%s`.","Dm":"invalid argument. Database already contains an entry for the provided id. Value: `%s`.","Dn":"invalid argument. First argument must be an array of objects. Value: `%s`.","Do":"unexpected error. File does not exist. Unable to resolve file: `%s`.","Dp":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`.","Dq":"invalid argument. First argument must be either a string or an array of strings. Value: `%s`. Index: `%u`.","Dr":"invalid argument. Must provide either an options object or a function. Value: `%s`.","Ds":"invalid option. `%s` option must be a nonnegative integer or an array of nonnegative integers. Option: `%s`.","Dt":"invalid argument. Fourth argument must contain a single element equal to 0. Value: `%d`.","Du":"invalid argument. Indices must be integer valued. Argument: `%i`. Value: `%s`.","Dv":"invalid argument. Must provide an ndarray. Value: `%s`.","Dw":"invalid argument. Second argument must be a supported data type policy. Value: `%s`.","Dx":"invalid argument. Must provide either an integer or a Date object. Value: `%s`.","Dy":"invalid argument. Must provide a valid duration string. Value: `%s`.","Dz":"invalid argument. Day number must be on the interval: [1, %u]. Value: `%d`.","E0":"invalid argument. First argument must be a string or integer. Value: `%s`.","E1":"invalid option. `%s` option must be one of the following: \"%s\". Value: `%s`.","E2":"invalid argument. Third argument must be either an integer (starting index) or a function. Value: `%s`.","E3":"invalid argument. Fourth argument must be either an integer (ending index) or a function. Value: `%s`.","E4":"invalid argument. Second argument must be a valid position (i.e., be within string bounds). Value: `%d`.","E5":"invalid argument. Must provide a valid code point (i.e., cannot exceed %u). Value: `%s`.","E6":"invalid argument. First argument must be astring. Value: `%s`.","E7":"invalid argument. Second argument must be either an integer (starting index) or a function. Value: `%s`.","E8":"invalid argument. Third argument must be either an integer (ending index) or a function. Value: `%s`.","E9":"invalid argument. ArrayBuffer byte length must be a multiple of %u. Byte length: `%u`.","EA":"invalid argument. Byte offset must be a multiple of %u. Value: `%u`.","EB":"invalid argument. First argument must have a length which is a multiple of %u. Length: `%u`.","EC":"invalid argument. Second argument must be a supported data type. Value: `%s`.","ED":"invalid argument. First argument must be one of the following data types: \"%s\". Value: `%s`.","EE":"invalid argument. Second argument must be either an integer (starting view index) or a function. Value: `%s`.","EF":"invalid argument. Third argument must be either an integer (ending view index) or a function. Value: `%s`.","EG":"invalid option. `size` option must be less than or equal to the length of `x` when `replace` is `false`. Option: `%s`.","EH":"invalid option. `size` option must be less than or equal to the population size when `replace` is `false`. Option: `%s`.","EI":"invalid argument. Second argument must be either a scalar or an ndarray-like object. Value: `%s`.","EJ":"invalid argument. Minimum support must be less than maximum support. Value: `[%f, %f]`.","EK":"invalid argument. Minimum support must be less than or equal to maximum support. Value: `[%d, %d]`.","EL":"invalid %s. `state` array has an incompatible schema version. Expected: `%s`. Actual: `%s.`","EM":"invalid %s. `state` array has an incompatible number of sections. Expected: `%s`. Actual: `%s`.","EN":"invalid argument. Number of draws must be less than or equal to the population size. Value: `%u`.","EO":"invalid argument. Subpopulation size must be less than or equal to the population size. Value: `%u`.","EP":"invalid argument. Must provide a regular expression. Value: `%s`.","EQ":"invalid argument. Second argument must be an object containing property descriptors. Value: `%s`.","ER":"invalid argument. Must provide an object (except null). Value: `%s`.","ES":"invalid argument. First argument must be an object (except null). Value: `%s`.","ET":"unexpected error. Encountered an invalid record. Field %d on line %d contains a closing quote which is not immediately followed by a delimiter or newline.","EU":"unexpected error. Encountered an invalid record. Field %d on line %d contains an opening quote which does not immediately follow a delimiter or newline.","EV":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence which is not immediately followed by a special character sequence.","EW":"unexpected error. Encountered an invalid record. Field %d on line %d contains an escape sequence within a quoted field which is not immediately followed by a quote sequence.","EX":"invalid argument. First argument must be a function having at least one parameter. Value: `%s`.","EY":"invalid argument. All arguments must be objects. Index: `%u`. Value: `%s`.","EZ":"invalid argument. First argument must be a non-null object. Value: `%s`.","Ea":"invalid argument. First argument must be an ndarray whose last dimension is of size %u. Actual size: `%u`.","Eb":"invalid argument. Attempting to scale a weight vector by a nonpositive value. This is likely due to too large a value of eta * lambda. Value: `%f`.","Ec":"invalid argument. Output argument must be a one-dimensional ndarray. Value: `%s`.","Ed":"invalid argument. Must provide a two-dimensional ndarray. Value: `%s`.","Ee":"invalid argument. Number of matrix columns must match centroid dimensions. Expected: `%u`. Actual: `%u`.","Ef":"invalid argument. First argument must be an integer, null, or undefined. Value: `%s`.","Eg":"invalid argument. Second argument must be an integer, null, or undefined. Value: `%s`.","Eh":"invalid argument. Third argument must be an integer, null, or undefined. Value: `%s`.","Ei":"invalid argument. Third argument cannot be zero. Value: `%s`.","Ej":"invalid argument. First argument must be a valid subsequence string. Value: `%s`.","Ek":"invalid argument. A subsequence string must have a non-zero increment. Value: `%s`.","El":"invalid argument. The subsequence string resolves to a slice which exceeds index bounds. Value: `%s`.","Em":"invalid argument. Provided arguments must be either a Slice, integer, null, or undefined. Argument: `%d`. Value: `%s`.","En":"invalid operation. Unsupported slice operation. Value: `%s`.","Eo":"invalid operation. Number of array dimensions does not match the number of slice dimensions. Array shape: (%s). Slice dimensions: %u.","Ep":"invalid operation. Slice exceeds array bounds. Array shape: (%s).","Eq":"invalid operation. A subsequence increment must be a non-zero integer. Value: `%s`.","Er":"invalid operation. A subsequence may only include a single ellipsis. Value: `%s`.","Es":"invalid argument. Cannot write to a read-only array.","Et":"invalid argument. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Eu":"invalid argument. Slice arguments must be either a Slice, integer, null, or undefined. Value: `%s`.","Ev":"invalid operation. Number of slice dimensions does not match the number of array dimensions. Array shape: (%s). Slice dimensions: %u.","Ew":"invalid operation. Assigned value cannot be safely cast to the target array data type. Data types: [%s, %s].","Ex":"invalid operation. Unsupported target array data type. Data type: `%s`.","Ey":"invalid argument. Index must be on the interval: [0, %d]. Value: `%d`.","Ez":"invalid argument. Slice exceeds array bounds. Array shape: (%s).","F0":"invalid argument. Input array values cannot be safely cast to the output array data type. Data types: [%s, %s].","F1":"invalid argument. Second argument must be an ndarray. Value: `%s`.","F2":"invalid argument. First argument must be an ndarray having at least two dimensions.","F3":"invalid argument. Second argument must be an array of nonnegative integers. Value: `%s`.","F4":"invalid option. Cannot write to read-only array.","F5":"invalid argument. First argument must be an array of nonnegative integers. Value: `%s`.","F6":"invalid argument. Must provide an ndarray having a supported data type. Value: `%s`.","F7":"invalid argument. First argument must be an ndarray having one or more dimensions. Number of dimensions: %d.","F8":"invalid argument. Dimension index exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","F9":"invalid argument. Third argument must be either a Slice, integer, null, or undefined. Value: `%s`.","FA":"invalid argument. First argument must be an ndarray having at least three dimensions.","FB":"invalid argument. Index must resolve to a value on the interval: [0, %d]. Value: `%d`.","FC":"invalid argument. First argument must be a recognized index mode. Value: `%s`.","FD":"invalid argument. Third argument exceeds the number of dimensions. Number of dimensions: %d. Value: `%d`.","FE":"invalid argument. Number of indices does not match the number of array dimensions. Array shape: (%s). Number of indices: %u.","FF":"invalid argument. Each index argument must be either an integer, null, or undefined. Value: `%s`.","FG":"invalid argument. First argument must be a complex number. Value: `%s`.","FH":"invalid arguments. Input arrays must be broadcast compatible.","FI":"invalid argument. The first and second arguments must have the same length.","FJ":"invalid argument. First argument must be either an ndarray or an array of ndarrays. Value: `%s`.","FK":"invalid argument. An ndarray argument must be an ndarray. Value: `%s`.","FL":"invalid argument. Second argument must be a valid property name. Value: `%s`.","FM":"invalid argument. First argument must have a `%s` method.","FN":"invalid argument. Second argument must an array of strings. Value: `%s`.","FO":"invalid argument. Third argument must be a supported data type. Value: `%s`.","FP":"invalid argument. Index argument is out-of-bounds. Value: `%s`.","FQ":"invalid argument. Second argument must be a complex number. Value: `%s`.","FR":"invalid argument. Index arguments must be integers. Value: `%s`.","FS":"invalid argument. Slice exceeds array bounds. Array length: %d.","FT":"invalid argument. Input array and the output array slice are broadcast incompatible. Array length: %u. Desired length: %u.","FU":"invalid operation. Slice exceeds array bounds.","FV":"invalid argument. First argument must be a valid index array.","FW":"invalid operation. This array index instance has already been freed and can no longer be used.","FX":"invalid argument. First argument must be a complex-valued floating-point array. Value: `%s`.","FY":"invalid operation. Index exceeds array bounds.","FZ":"invalid operation. Unrecognized array index type. Value: `%s`.","Fa":"invalid operation. Unable to resolve array index. Value: `%s`.","Fb":"invalid option. `%s` option is missing a `%s` method. Option: `%s`.","Fc":"invalid operation. If not provided an initial value, an array must contain at least one element.","Fd":"invalid arguments. Must provide equal length array-like objects.","Fe":"Index out of bounds","Ff":"invalid option. `%s` option must be less than or equal to 64. Option: `%u`.","Fg":"invalid argument. Unable to parse input string as a complex number. Value: `%s`.","Fh":"invalid operation. Cannot access settings for a REPL which has already closed.","Fi":"invalid argument. First argument must be a recognized setting. Value: `%s`.","Fj":"invalid invocation. `this` is not a boolean array.","Fk":"invalid argument. Unable to parse commits for package: `%s`.","Fl":"invalid argument. Unrecognized release type: `%s`.","Fm":"invalid argument. First argument must be a supported BLAS memory layout. Value: `%s`.","Fn":"invalid argument. First argument must be an existing theme name. Value: `%s`.","Fo":"invalid argument. First argument must not be the default theme name. Value: `%s`.","Fp":"invalid argument. Second argument must be an object. Value: `%s`.","Fq":"invalid arguments. Number of values does not equal the number of falsy values in the mask array.","Fr":"invalid arguments. Insufficient values to satisfy mask array.","Fs":"invalid arguments. Input arguments are not broadcast compatible.","Ft":"invalid arguments. Number of values does not equal the number of truthy values in the mask array.","Fu":"invalid argument. Third argument cannot be safely cast to the input array data type. Data types: [%s, %s].","Fv":"invalid argument. First argument must be a boolean. Value: `%s`.","Fw":"invalid argument. The third argument must be broadcast compatible with the second argument. Array shape: (%d). Desired shape: (%d).","Fx":"invalid argument. First argument must be a valid order. Value: `%s`.","Fy":"invalid argument. Second argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","Fz":"invalid argument. Third argument must be a nonnegative integer. Value: `%d`.","G0":"invalid argument. Eighth argument must be non-zero. Value: `%d`.","G1":"invalid argument. Twelfth argument must be non-zero. Value: `%d`.","G2":"invalid argument. Seventh argument must be non-zero. Value: `%d`.","G3":"invalid argument. Tenth argument must be non-zero. Value: `%d`.","G4":"invalid argument. Fourth argument must be greater than or equal to max(1,%d). Value: `%d`.","G5":"invalid argument. First argument must be a string or an array of strings. Value: `%s`.","G6":"invalid option. `%s` option must be a valid mode. Option: `%s`.","G7":"invalid argument. First argument must be a nonnegative integer. Value: `%d`.","G8":"invalid argument. Sixth argument must be greater than or equal to %d. Value: `%d`.","G9":"invalid argument. Eighth argument must be greater than or equal to %d. Value: `%d`.","GA":"invalid argument. Second argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GB":"invalid argument. Sixth argument must be non-zero. Value: `%d`.","GC":"invalid argument. Tenth argument must be greater than or equal to max(1,%d). Value: `%d`.","GD":"invalid argument. First argument must specify whether the reference the lower or upper triangular matrix. Value: `%s`.","GE":"invalid argument. Second argument must be a nonnegative integer. Value: `%d`.","GF":"invalid argument. Fifth argument must be non-zero. Value: `%d`.","GG":"invalid argument. Second argument must be a valid transpose operation. Value: `%s`.","GH":"invalid argument. Fourth argument must be a nonnegative integer. Value: `%d`.","GI":"invalid argument. Ninth argument must be non-zero.","GJ":"invalid argument. Twelfth argument must be non-zero.","GK":"invalid argument. Eleventh argument must be non-zero.","GL":"invalid argument. Fifteenth argument must be non-zero.","GM":"invalid argument. Eighth argument must be greater than or equal to max(1,%d). Value: `%d`.","GN":"invalid argument. First argument must specify whether to reference the lower or upper triangular matrix. Value: `%s`.","GO":"invalid argument. Third argument must be a valid transpose operation. Value: `%s`.","GP":"invalid argument. Fourth argument must be a valid diagonal type. Value: `%s`.","GQ":"invalid argument. Fifth argument must be a nonnegative integer. Value: `%d`.","GR":"invalid argument. Seventh argument must be greater than or equal to max(1,%d). Value: `%d`.","GS":"invalid argument. Ninth argument must be non-zero. Value: `%d`.","GT":"invalid argument. First argument must specify whether the lower or upper triangular matrix is supplied. Value: `%s`.","GU":"invalid argument. Third argument must be a valid diagonal type. Value: `%s`.","GV":"invalid argument. First argument must be a valid transpose operation. Value: `%s`.","GW":"invalid argument. Tenth argument must be non-zero.","GX":"invalid argument. Fourteenth argument must be non-zero.","GY":"invalid arguments. Array must have the same shape.","GZ":"invalid argument. Second argument must be an array of integers. Value: `%s`.","Ga":"invalid argument. First argument must be an ndarray having at least %d dimensions.","Gb":"invalid argument. Dimension indices must be sorted in ascending order. Value: `%s`.","Gc":"invalid argument. Dimension indices must be unique. Value: `%s`.","Gd":"invalid argument. First argument must be an array of ndarrays. Value: `%s`.","Ge":"invalid argument. First argument must be an array of ndarrays which are broadcast-compatible. Value: `%s`.","Gf":"invalid argument. First argument must be an array of ndarrays having at least %d dimensions after broadcasting.","Gg":"invalid argument. Index argument is out-of-bounds. Value: `%d`.","Gh":"invalid argument. Sixth argument must be a nonnegative integer. Value: `%d`.","Gi":"invalid argument. Ninth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gj":"invalid argument. Eleventh argument must be greater than or equal to max(1,%d). Value: `%d`.","Gk":"invalid argument. Fourteenth argument must be greater than or equal to max(1,%d). Value: `%d`.","Gl":"invalid argument. First argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gm":"invalid argument. Second argument must be an ndarray containing double-precision floating-point numbers. Value: `%s`.","Gn":"invalid argument. First argument must have at least one dimension.","Go":"invalid argument. Second argument must have at least one dimension.","Gp":"invalid argument. Third argument must be a negative integer. Value: `%s`.","Gq":"invalid argument. Third argument must be a value on the interval: [%d,%d]. Value: `%d`.","Gr":"invalid argument. The size of the contracted dimension must be the same for both input ndarrays. Dim(%s,%d) = %d. Dim(%s,%d) = %d.","Gs":"invalid arguments. Input ndarrays must be broadcast compatible. Shape(%s) = (%s). Shape(%s) = (%s).","Gt":"invalid argument. Cannot write to read-only array.","Gu":"invalid arguments. The first and second arguments must have the same shape.","Gv":"unexpected error. Environment does not support WebAssembly.","Gw":"invalid invocation. Unable to perform write operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gx":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Resize the underlying memory instance in order to accommodate the list of provided values.","Gy":"invalid invocation. Unable to perform read operation, as the WebAssembly module is not bound to an underlying WebAssembly memory instance.","Gz":"invalid argument. Second argument is incompatible with the specified byte offset and available memory. Not enough values to fill the provided output array.","H0":"invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.","H1":"invalid argument. First argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H2":"invalid argument. Second argument must be an ndarray containing single-precision floating-point numbers. Value: `%s`.","H3":"invalid invocation. `this` is not a Float64ArrayFE.","H4":"invalid argument. First argument must be a supported byte order. Value: `%s`.","H5":"invalid argument. Second argument must a data type. Value: `%s`.","H6":"invalid argument. First argument must be an ndarray-like object having a supported data type. Value: `%s`.","H7":"invalid argument. Second argument must be an ndarray-like object having a supported data type. Value: `%s`.","H8":"invalid invocation. `this` is not %s %s.","H9":"invalid argument. First argument must be a supported data type. Value: `%s`.","HA":"invalid argument. Must provide an ArrayBuffer. Value: `%s`.","HB":"invalid argument. Second argument must be a data type. Value: `%s`.","HC":"invalid option. Each key object must have a `name` property. Value: `%s`.","HD":"invalid option. Each key object's `name` property must be a string. Value: `%s`.","HE":"invalid option. Each key object's `%s` property must be a boolean. Value: `%s`.","HF":"invalid option. Each action must be an array of objects. Value: `%s`.","HG":"invalid argument. First argument must be a valid index ndarray.","HH":"invalid operation. This ndarray index instance has already been freed and can no longer be used.","HI":"invalid operation. Unrecognized ndarray index type. Value: `%s`.","HJ":"invalid operation. Index exceeds ndarray bounds.","HK":"invalid operation. Number of indices does not match the number of array dimensions. Array shape: (%s). Index dimensions: %u.","HL":"invalid operation. Unable to resolve ndarray index. Value: `%s`.","HM":"invalid argument. First argument is not compatible with the specified index \"kind\". Type: %s. Kind: %s.","HN":"invalid argument. First argument must be greater than or equal to the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `%d`.","HO":"invalid argument. Specified dimension index is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `[%s]`.","HP":"invalid argument. Must provide unique dimension indices. Value: `[%s]`.","HQ":"invalid argument. Must provide the same number of dimension indices as the number of dimensions in the input ndarray. Number of dimensions: %d. Value: `[%s]`.","HR":"invalid argument. Must provide dimension indices which resolve to nonnegative indices arranged in ascending order. Value: `[%s]`.","HS":"invalid argument. Specified axis is out-of-bounds. Must be on the interval: [-%u, %u]. Value: `%d`.","HT":"invalid argument. Each key in the keybindings argument must correspond to a single action. Value: `%s`","HU":"invalid argument. First argument must be a valid action name. Value: `%s`.","HV":"invalid argument. Each key in the keys argument must correspond to a single action. Value: `%s`","HW":"invalid argument. Second argument must be an array of data types. Value: `%s`.","HX":"invalid argument. Third argument must be an array of data types. Value: `%s`.","HY":"invalid argument. Fourth argument must be a supported output data type policy. Value: `%s`.","HZ":"invalid argument. First argument must have one of the following data types: \"%s\". Data type: `%s`.","Ha":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d.","Hb":"invalid argument. Third argument contains an out-of-bounds dimension index. Value: [%s].","Hc":"invalid argument. Third argument must contain a list of unique dimension indices. Value: [%s].","Hd":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. ndims(x) == %d. Value: [%s].","He":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. ndims(x) == %d. Number of reduced dimensions: %d. ndims(arrays[%d]) == %d.","Hf":"invalid argument. Non-reduced dimensions must be consistent across all provided arrays. Input array shape: [%s]. Non-reduced dimension indices: [%s]. Non-reduced dimensions: [%s]. Array shape: [%s] (index: %d).","Hg":"invalid argument. The second argument cannot be safely cast to the input array data type. Data type: %s. Value: `%s`.","Hh":"invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.","Hi":"invalid argument. Second argument cannot be safely cast to the input array data type. Value: `%s`.","Hj":"invalid argument. Third argument must be an ndarray-like object. Value: `%s`.","Hk":"invalid option. `%s` option must be an array of integers. Option: `%s`.","Hl":"invalid option. `%s` option contains an out-of-bounds dimension index. Option: [%s].","Hm":"invalid option. `%s` option specifies more dimensions than exists in the input array. Number of dimensions: %d. Option: [%s].","Hn":"invalid argument. Number of specified dimensions cannot exceed the number of dimensions in the input array. Number of dimensions: %d. Value: [%s].","Ho":"invalid argument. Arrays which are not being reduced must have the same number of non-reduced dimensions. Input array shape: [%s]. Number of non-reduced dimensions: %d. Array shape: [%s] (index: %d).","Hp":"invalid argument. Second argument must be an ndarray-like object. Value: `%s`.","Hq":"invalid argument. Second argument must have one of the following data types: \"%s\". Data type: `%s`.","Hr":"invalid argument. Fourteenth argument must be non-zero. Value: `%d`.","Hs":"invalid argument. Seventeenth argument must be non-zero. Value: `%d`.","Ht":"invalid argument. Eighteenth argument must be non-zero. Value: `%d`.","Hu":"invalid option. `%s` option contains duplicate indices. Option: [%s].","Hv":"invalid argument. First argument must be an object having a \"default\" property and an associated method.","Hw":"invalid argument. Second argument must contain arrays of data types. Value: `%s`.","Hx":"invalid argument. Argument %d must have one of the following data types: \"%s\". Data type: `%s`.","Hy":"invalid argument. Argument %d must be an ndarray-like object. Value: `%s`.","Hz":"invalid arguments. Input and output arrays must have the same shape.","I0":"invalid argument. First argument specifies an unexpected number of types. A pair of input and output ndarray data types must be specified for each provided strided function.","I1":"invalid argument. First argument specifies an unexpected number of types. An input ndarray data type must be specified for each provided strided function.","I2":"invalid argument. Array arguments after the first two arrays must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","I3":"invalid argument. Loop dimensions must be consistent across all provided arrays. Input array shape: [%s]. Loop dimension indices: [%s]. Loop dimensions: [%s]. Array shape: [%s] (index: %d).","I4":"invalid argument. First argument must be an object having a \"types\" property whose associated value is an array-like object.","I5":"invalid argument. First argument must be an object having a \"fcns\" property whose associated value is an array-like object containing functions.","I6":"invalid argument. Fourth argument must be an object having a supported output data type policy. Value: `%s`.","I7":"invalid argument. Fourth argument must be an object having a supported casting policy. Value: `%s`.","I8":"invalid operation. Unable to promote the input and output data types. Input data type: %s. Output data type: %s.","I9":"invalid argument. Third argument must be a supported casting policy. Value: `%s`.","IA":"invalid option. `%s` option must be an object containing properties having values which are objects. Option: `%s`.","IB":"invalid option. `%s` option must be an object having %s `%s` property which is an array of strings. Option: `%s`.","IC":"invalid option. `%s` option must have %s `%s` property.","ID":"invalid argument. Second argument must be either an ndarray or a numeric scalar value. Value: `%s`.","IE":"invalid argument. Eleventh argument must be non-zero. Value: `%d`.","IF":"invalid option. `%s` option must be a valid memory layout. Option: `%s`.","IG":"invalid arguments. Arrays must have the same number of dimensions (i.e., same rank). ndims(x) == %d. ndims(y) == %d. ndims(z) == %d.","IH":"invalid argument. Unable to resolve an output data type. The output data type policy is \"same\" and yet the input data types are not equal. Data types: [%s].","II":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input data types can be safely cast. Data types: [%s].","IJ":"invalid argument. %s argument must have one of the following data types: \"%s\". Data type: `%s`.","IK":"invalid option. `%s` option must be a valid index mode. Option: `%s`.","IL":"invalid option. `%s` option must be a memory layout. Option: `%s`.","IM":"invalid argument. ArrayBuffer is incompatible with the specified data type. Value: `%s`.","IN":"invalid argument. Must provide a length, ArrayBuffer, typed array, array-like object, iterable, data type, or options object. Value: `%s`.","IO":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or iterable. Value: `%s`.","IP":"invalid argument. Third argument must be a recognized/supported data type. Value: `%s`.","IQ":"invalid argument. Fourth argument must be a recognized/supported data type. Value: `%s`.","IR":"invalid argument. Fifth argument must be greater than or equal to max(1,%d). Value: `%d`.","IS":"invalid argument. Second argument must have an integer data type. Value: `%s`.","IT":"invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.","IU":"invalid argument. Union types may only be initialized by a single member.","IV":"invalid invocation. `this` is not a struct instance.","IW":"invalid operation. struct does not have any fields.","IX":"unexpected error. Unrecognized data type. Value: `%s`.","IY":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Data types: [%s, %s].","IZ":"invalid argument. Field objects must have the following properties: \"%s\". Value: `%s`.","Ia":"invalid argument. Union types cannot contain nested union types. Value: `%s`.","Ib":"invalid argument. Union types can only contain one field with a default value. Value: `%s`.","Ic":"invalid argument. Union types must contain fields having the same byte length. Value: `%s`.","Id":"invalid argument. `%s` field must be a string. Value: `%s`.","Ie":"invalid argument. `%s` field must be a boolean. Value: `%s`.","If":"invalid argument. `%s` field must be a positive integer. Value: `%s`.","Ig":"invalid assignment. `%s` must be a `struct` instance. Value: `%s`.","Ih":"invalid assignment. Assigned value cannot be cast to the data type of `%s`. Value: `%s`.","Ii":"invalid assignment. `%s` must be a `struct` instance having the same byte length.","Ij":"invalid assignment. `%s` must be an array-like object. Value: `%s`.","Ik":"invalid assignment. `%s` must be an array-like object having length %u.","Il":"invalid argument. Byte length must be a nonnegative integer. Value: `%s`.","Im":"invalid argument. ArrayBuffer has insufficient capacity. Minimum capacity: `%u`.","In":"invalid argument. First argument must be a `struct` instance. Value: `%s`.","Io":"invalid argument. `%s` field must be one of the following: \"%s\". Value: `%s`.","Ip":"invalid argument. First argument must be an array of objects having unique field names. Value: `%s`.","Iq":"invalid argument. `%s` field must be a non-empty string. Value: `%s`.","Ir":"invalid argument. First argument must be an array of objects. Value: `%s`. Index: `%d`.","Is":"invalid argument. Union types must be an array of objects. Value: `%s`. Index: `%d`.","It":"invalid argument. Field name must be one of the following: \"%s\". Value: `%s`.","Iu":"invalid argument. `%s` field must be either a struct type or one of the following: \"%s\". Value: `%s`.","Iv":"invalid assignment. `%s` must be an array-like object containing `struct` instances having the same byte length.","Iw":"invalid argument. First argument must be one of the following: \"%s\". Value: `%s`.","Ix":"invalid argument. First argument must be an ArrayBuffer or a data object. Value: `%s`.","Iy":"invalid argument. First argument must be either a struct constructor or struct schema. Value: `%s`.","Iz":"invalid argument. Each element of a provided input array must be a valid object or a struct instance having the same layout as elements in the desired output array.","J0":"invalid argument. Environment lacks Symbol.iterator support. First argument must be a length, ArrayBuffer, typed array, or array-like object. Value: `%s`.","J1":"invalid argument. First argument must be a length, ArrayBuffer, typed array, array-like object, or an iterable. Value: `%s`.","J2":"invalid argument. Each element of a provided input iterable must be either a valid object or a struct instance having the same layout as elements in the desired output array.","J3":"invalid argument. Second argument must be a multiple of %u. Value: `%u`.","J4":"invalid argument. Second argument exceeds the bounds of the ArrayBuffer. Value: `%s`.","J5":"invalid argument. ArrayBuffer view byte length must be a multiple of %u. View byte length: `%u`.","J6":"invalid invocation. `this` is not a %s.","J7":"invalid argument. Must provide either a valid object or a struct instance. Value: `%s`.","J8":"invalid argument. First argument must be a valid orientation. Value: `%s`.","J9":"invalid argument. Second argument must be a valid orientation. Value: `%s`.","JA":"invalid argument. The first argument must be an ndarray. Value: `%s`.","JB":"invalid argument. Second argument must be either an ndarray or a scalar value. Value: `%s`.","JC":"invalid argument. Third argument must be an ndarray. Value: `%s`.","JD":"invalid argument. Third argument must be either an ndarray or an integer. Value: `%s`.","JE":"invalid operation. Environment lacks support for HTTP/2. Ensure that you are running on a Node.js version which supports HTTP/2 and has been built to include support for the Node.js `crypto` module.","JF":"invalid argument. Input arrays must have the same number of dimensions. First array dimensions: %d. Second array dimensions: %d.","JG":"invalid argument. Input arrays must have the same shape. First array shape: [%s]. Second array shape: [%s].","JH":"invalid argument. Output array must have the same number of non-reduced dimensions as input arrays. Input array shape: [%s]. Number of non-reduced dimensions: %d. Output array shape: [%s].","JI":"invalid argument. Array arguments after the first array must have the same number of loop dimensions. Input array shape: [%s]. Number of loop dimensions: %d. Array shape: [%s] (index: %d).","JJ":"invalid argument. Second argument contains an out-of-bounds index. Array shape: (%s). Value: `[%s]`.","JK":"invalid argument. Thirteenth argument must be non-zero. Value: `%d`.","JL":"invalid argument. Sixth argument must be greater than or equal to max(1,%d). Value: `%d`.","JM":"invalid argument. Fifth argument must be non-zero. Value: `%s`.","JN":"invalid argument. Sixth argument must be non-zero. Value: `%s`.","JO":"invalid arguments. Unable to resolve an ndarray function supporting the provided argument data types.","JP":"invalid argument. First argument specifies an unexpected number of types. Two input ndarray data types must be specified for each provided strided function.","JQ":"invalid argument. First argument specifies an unexpected number of types. An output ndarray data type must be specified for each provided strided function.","JR":"invalid operation. Unable to promote the input and output data types. Input data types: [%s]. Output data type: %s.","JS":"invalid argument. Fourth argument must be a supported casting policy. Value: `%s`.","JT":"invalid argument. Fourth argument must be an ndarray. Value: `%s`.","JU":"invalid option. `%s` option must be a supported data type. Option: `%s`.","JV":"invalid argument. First argument must be either a supported data type string, a struct constructor, or another data type instance. Value: `%s`.","JW":"invalid argument. Second argument must be a valid sort order. Value: `%s`.","JX":"invalid argument. Second argument must be either an ndarray, a numeric scalar value, or a supported string. Value: `%s`.","JY":"invalid argument. Unable to apply type promotion rules when resolving a data type to which the input ndarrays can be safely cast. Data types: [%s].","JZ":"invalid argument. The list of input ndarrays cannot be safely cast to the data of the output ndarray. Input data types: [%s]. Output data type: %s.","Ja":"invalid argument. Second argument is not broadcast compatible with the list of input ndarrays. Array shape: (%s). Desired shape: (%s).","Jb":"invalid argument. Second argument must be a negative integer. Value: `%s`.","Jc":"invalid argument. First argument cannot be safely cast to the output data type. Data types: [%s, %s].","Jd":"invalid option. First argument cannot be safely cast to the specified data type. Input data type: %s. Option: `%s`.","Je":"invalid argument. First argument must be an ndarray having at least one dimension.","Jf":"invalid argument. Second argument must be either a number, complex number, or an ndarray. Value: `%s`.","Jg":"invalid argument. Third argument must have one of the following data types: \"%s\". Data type: `%s`.","Jh":"invalid argument. Third argument must be either a number, complex number, or an ndarray. Value: `%s`.","Ji":"invalid argument. Fourth argument must have one of the following data types: \"%s\". Data type: `%s`.","Jj":"invalid argument. Fourth argument must be either a boolean or an ndarray. Value: `%s`.","Jk":"invalid argument. First argument must be a nonnegative integer or an array of nonnegative integers. Value: `%s`.","Jl":"invalid option. `%s` option must be a supported order. Option: `%s`.","Jm":"invalid argument. Argument %d cannot be safely cast to the desired output data type. Output data type: %s. Argument data type: %s."}
diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv
index fe0b3735b9db..23a59879f511 100644
--- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv
+++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.csv
@@ -963,6 +963,8 @@
 "03B",@stdlib/assert-has-generator-support
 "03C",@stdlib/assert/has-globalthis-support
 "03D",@stdlib/assert-has-globalthis-support
+"2XY",@stdlib/assert/has-has-instance-symbol-support
+"2XZ",@stdlib/assert-has-has-instance-symbol-support
 "03E",@stdlib/assert/has-int16array-support
 "03F",@stdlib/assert-has-int16array-support
 "03G",@stdlib/assert/has-int32array-support
@@ -975,6 +977,8 @@
 "03L",@stdlib/assert-has-iterator-symbol-support
 "03M",@stdlib/assert/has-map-support
 "03N",@stdlib/assert-has-map-support
+"2Xa",@stdlib/assert/has-match-symbol-support
+"2Xb",@stdlib/assert-has-match-symbol-support
 "03O",@stdlib/assert/has-node-buffer-support
 "03P",@stdlib/assert-has-node-buffer-support
 "03Q",@stdlib/assert/has-own-property
@@ -983,12 +987,20 @@
 "03T",@stdlib/assert-has-property
 "03U",@stdlib/assert/has-proxy-support
 "03V",@stdlib/assert-has-proxy-support
+"2Xc",@stdlib/assert/has-replace-symbol-support
+"2Xd",@stdlib/assert-has-replace-symbol-support
+"2Xe",@stdlib/assert/has-search-symbol-support
+"2Xf",@stdlib/assert-has-search-symbol-support
 "03W",@stdlib/assert/has-set-support
 "03X",@stdlib/assert-has-set-support
 "03Y",@stdlib/assert/has-sharedarraybuffer-support
 "03Z",@stdlib/assert-has-sharedarraybuffer-support
+"2Xg",@stdlib/assert/has-split-symbol-support
+"2Xh",@stdlib/assert-has-split-symbol-support
 "03a",@stdlib/assert/has-symbol-support
 "03b",@stdlib/assert-has-symbol-support
+"2Xi",@stdlib/assert/has-to-primitive-symbol-support
+"2Xj",@stdlib/assert-has-to-primitive-symbol-support
 "03c",@stdlib/assert/has-tostringtag-support
 "03d",@stdlib/assert-has-tostringtag-support
 "03e",@stdlib/assert/has-uint16array-support
@@ -1926,6 +1938,8 @@
 "2Nl",@stdlib/blas-ext-base-dindex-of
 "2Nm",@stdlib/blas/ext/base/dlast-index-of
 "2Nn",@stdlib/blas-ext-base-dlast-index-of
+"2Xk",@stdlib/blas/ext/base/dlinspace
+"2Xl",@stdlib/blas-ext-base-dlinspace
 "0Ck",@stdlib/blas/ext/base/dnanasum
 "0Cl",@stdlib/blas-ext-base-dnanasum
 "0Cm",@stdlib/blas/ext/base/dnanasumors
@@ -1954,6 +1968,8 @@
 "0D7",@stdlib/blas-ext-base-dnansumpw
 "0D8",@stdlib/blas/ext/base/drev
 "0D9",@stdlib/blas-ext-base-drev
+"2YQ",@stdlib/blas/ext/base/drrss
+"2YR",@stdlib/blas-ext-base-drrss
 "0DA",@stdlib/blas/ext/base/dsapxsum
 "0DB",@stdlib/blas-ext-base-dsapxsum
 "0DC",@stdlib/blas/ext/base/dsapxsumpw
@@ -2032,6 +2048,8 @@
 "2Np",@stdlib/blas-ext-base-gindex-of
 "2Nq",@stdlib/blas/ext/base/glast-index-of
 "2Nr",@stdlib/blas-ext-base-glast-index-of
+"2Xm",@stdlib/blas/ext/base/glinspace
+"2Xn",@stdlib/blas-ext-base-glinspace
 "0EG",@stdlib/blas/ext/base/gnannsumkbn
 "0EH",@stdlib/blas-ext-base-gnannsumkbn
 "2Hw",@stdlib/blas/ext/base/gnannsumpw
@@ -2078,6 +2096,8 @@
 "2Nt",@stdlib/blas-ext-base-ndarray-dindex-of
 "2Nu",@stdlib/blas/ext/base/ndarray/dlast-index-of
 "2Nv",@stdlib/blas-ext-base-ndarray-dlast-index-of
+"2Xo",@stdlib/blas/ext/base/ndarray/dlinspace
+"2Xp",@stdlib/blas-ext-base-ndarray-dlinspace
 "2T2",@stdlib/blas/ext/base/ndarray/dsorthp
 "2T3",@stdlib/blas-ext-base-ndarray-dsorthp
 "2FG",@stdlib/blas/ext/base/ndarray/dsum
@@ -2092,6 +2112,8 @@
 "2Nx",@stdlib/blas-ext-base-ndarray-gindex-of
 "2Ny",@stdlib/blas/ext/base/ndarray/glast-index-of
 "2Nz",@stdlib/blas-ext-base-ndarray-glast-index-of
+"2Xq",@stdlib/blas/ext/base/ndarray/glinspace
+"2Xr",@stdlib/blas-ext-base-ndarray-glinspace
 "2T8",@stdlib/blas/ext/base/ndarray/gsorthp
 "2T9",@stdlib/blas-ext-base-ndarray-gsorthp
 "2FK",@stdlib/blas/ext/base/ndarray/gsum
@@ -2104,6 +2126,8 @@
 "2O1",@stdlib/blas-ext-base-ndarray-sindex-of
 "2O2",@stdlib/blas/ext/base/ndarray/slast-index-of
 "2O3",@stdlib/blas-ext-base-ndarray-slast-index-of
+"2Xs",@stdlib/blas/ext/base/ndarray/slinspace
+"2Xt",@stdlib/blas-ext-base-ndarray-slinspace
 "2TA",@stdlib/blas/ext/base/ndarray/ssorthp
 "2TB",@stdlib/blas-ext-base-ndarray-ssorthp
 "2FQ",@stdlib/blas/ext/base/ndarray/ssum
@@ -2154,6 +2178,8 @@
 "2O5",@stdlib/blas-ext-base-sindex-of
 "2O6",@stdlib/blas/ext/base/slast-index-of
 "2O7",@stdlib/blas-ext-base-slast-index-of
+"2Xu",@stdlib/blas/ext/base/slinspace
+"2Xv",@stdlib/blas-ext-base-slinspace
 "0FU",@stdlib/blas/ext/base/snansum
 "0FV",@stdlib/blas-ext-base-snansum
 "0FW",@stdlib/blas/ext/base/snansumkbn
@@ -2226,6 +2252,8 @@
 "2Rp",@stdlib/blas-ext-index-of
 "2VK",@stdlib/blas/ext/last-index-of
 "2VL",@stdlib/blas-ext-last-index-of
+"2YS",@stdlib/blas/ext/linspace
+"2YT",@stdlib/blas-ext-linspace
 "0G2",@stdlib/blas/ext
 "0G3",@stdlib/blas-ext
 "2WM",@stdlib/blas/ext/sorthp
@@ -4755,6 +4783,8 @@
 "0iJ",@stdlib/ndarray-base-char2dtype
 "0iK",@stdlib/ndarray/base/clamp-index
 "0iL",@stdlib/ndarray-base-clamp-index
+"2Xw",@stdlib/ndarray/base/complement-shape
+"2Xx",@stdlib/ndarray-base-complement-shape
 "2Wq",@stdlib/ndarray/base/copy
 "2Wr",@stdlib/ndarray-base-copy
 "2Ie",@stdlib/ndarray/base/count-falsy
@@ -5031,6 +5061,8 @@
 "0jn",@stdlib/ndarray-casting-modes
 "2Wy",@stdlib/ndarray/concat
 "2Wz",@stdlib/ndarray-concat
+"2Xy",@stdlib/ndarray/copy
+"2Xz",@stdlib/ndarray-copy
 "2Iu",@stdlib/ndarray/count-falsy
 "2Iv",@stdlib/ndarray-count-falsy
 "2Iw",@stdlib/ndarray/count-if
@@ -5184,6 +5216,8 @@
 "1jV",@stdlib/ndarray-slice
 "2J0",@stdlib/ndarray/some-by
 "2J1",@stdlib/ndarray-some-by
+"2YU",@stdlib/ndarray/some
+"2YV",@stdlib/ndarray-some
 "1mk",@stdlib/ndarray/stride
 "1ml",@stdlib/ndarray-stride
 "1kC",@stdlib/ndarray/strides
@@ -5340,6 +5374,8 @@
 "28P",@stdlib/number-float64-base-sub
 "0lQ",@stdlib/number/float64/base/to-binary-string
 "0lR",@stdlib/number-float64-base-to-binary-string
+"2YW",@stdlib/number/float64/base/to-float16
+"2YX",@stdlib/number-float64-base-to-float16
 "0lS",@stdlib/number/float64/base/to-float32
 "0lT",@stdlib/number-float64-base-to-float32
 "0lU",@stdlib/number/float64/base/to-int32
@@ -5360,6 +5396,8 @@
 "1dn",@stdlib/number-float64-to-json
 "2Ts",@stdlib/number/int16/base/identity
 "2Tt",@stdlib/number-int16-base-identity
+"2YY",@stdlib/number/int16/base
+"2YZ",@stdlib/number-int16-base
 "2Tu",@stdlib/number/int32/base/identity
 "2Tv",@stdlib/number-int32-base-identity
 "2Ai",@stdlib/number/int32/base/mul
@@ -5374,6 +5412,8 @@
 "0lj",@stdlib/number-int32
 "2Tw",@stdlib/number/int8/base/identity
 "2Tx",@stdlib/number-int8-base-identity
+"2Ya",@stdlib/number/int8/base
+"2Yb",@stdlib/number-int8-base
 "0ll",@stdlib/number
 "2L8",@stdlib/number/uint16/base/add
 "2L9",@stdlib/number-uint16-base-add
@@ -7225,16 +7265,30 @@
 "2Vn",@stdlib/stats-base-ndarray-dmaxsorted
 "2UE",@stdlib/stats/base/ndarray/dmean
 "2UF",@stdlib/stats-base-ndarray-dmean
+"2Y0",@stdlib/stats/base/ndarray/dmeankbn
+"2Y1",@stdlib/stats-base-ndarray-dmeankbn
+"2Y2",@stdlib/stats/base/ndarray/dmeankbn2
+"2Y3",@stdlib/stats-base-ndarray-dmeankbn2
+"2Y4",@stdlib/stats/base/ndarray/dmeanli
+"2Y5",@stdlib/stats-base-ndarray-dmeanli
+"2Y6",@stdlib/stats/base/ndarray/dmeanlipw
+"2Y7",@stdlib/stats-base-ndarray-dmeanlipw
 "2Pe",@stdlib/stats/base/ndarray/dmin
 "2Pf",@stdlib/stats-base-ndarray-dmin
 "2UG",@stdlib/stats/base/ndarray/dminabs
 "2UH",@stdlib/stats-base-ndarray-dminabs
+"2Y8",@stdlib/stats/base/ndarray/dminsorted
+"2Y9",@stdlib/stats-base-ndarray-dminsorted
 "2UI",@stdlib/stats/base/ndarray/dnanmax
 "2UJ",@stdlib/stats-base-ndarray-dnanmax
+"2Yc",@stdlib/stats/base/ndarray/dnanmaxabs
+"2Yd",@stdlib/stats-base-ndarray-dnanmaxabs
 "2VA",@stdlib/stats/base/ndarray/dnanmean
 "2VB",@stdlib/stats-base-ndarray-dnanmean
 "2UK",@stdlib/stats/base/ndarray/dnanmin
 "2UL",@stdlib/stats-base-ndarray-dnanmin
+"2Ye",@stdlib/stats/base/ndarray/dnanminabs
+"2Yf",@stdlib/stats-base-ndarray-dnanminabs
 "2Pg",@stdlib/stats/base/ndarray/drange
 "2Ph",@stdlib/stats-base-ndarray-drange
 "2Pi",@stdlib/stats/base/ndarray/dztest
@@ -7275,26 +7329,40 @@
 "2XT",@stdlib/stats-base-ndarray-minsorted
 "2XU",@stdlib/stats/base/ndarray/mskmax
 "2XV",@stdlib/stats-base-ndarray-mskmax
+"2YA",@stdlib/stats/base/ndarray/mskmin
+"2YB",@stdlib/stats-base-ndarray-mskmin
 "2US",@stdlib/stats/base/ndarray/nanmax
 "2UT",@stdlib/stats-base-ndarray-nanmax
+"2Yg",@stdlib/stats/base/ndarray/nanmaxabs
+"2Yh",@stdlib/stats-base-ndarray-nanmaxabs
 "2VC",@stdlib/stats/base/ndarray/nanmean
 "2VD",@stdlib/stats-base-ndarray-nanmean
 "2UU",@stdlib/stats/base/ndarray/nanmin
 "2UV",@stdlib/stats-base-ndarray-nanmin
+"2Yi",@stdlib/stats/base/ndarray/nanminabs
+"2Yj",@stdlib/stats-base-ndarray-nanminabs
 "2F2",@stdlib/stats/base/ndarray
 "2F3",@stdlib/stats-base-ndarray
+"2YC",@stdlib/stats/base/ndarray/range-by
+"2YD",@stdlib/stats-base-ndarray-range-by
 "2Po",@stdlib/stats/base/ndarray/range
 "2Pp",@stdlib/stats-base-ndarray-range
 "2UW",@stdlib/stats/base/ndarray/scovarmtk
 "2UX",@stdlib/stats-base-ndarray-scovarmtk
 "2G6",@stdlib/stats/base/ndarray/scumax
 "2G7",@stdlib/stats-base-ndarray-scumax
+"2Yk",@stdlib/stats/base/ndarray/scumaxabs
+"2Yl",@stdlib/stats-base-ndarray-scumaxabs
 "2Pq",@stdlib/stats/base/ndarray/scumin
 "2Pr",@stdlib/stats-base-ndarray-scumin
+"2Ym",@stdlib/stats/base/ndarray/scuminabs
+"2Yn",@stdlib/stats-base-ndarray-scuminabs
 "2F4",@stdlib/stats/base/ndarray/smax
 "2F5",@stdlib/stats-base-ndarray-smax
 "2UY",@stdlib/stats/base/ndarray/smaxabs
 "2UZ",@stdlib/stats-base-ndarray-smaxabs
+"2YE",@stdlib/stats/base/ndarray/smaxabssorted
+"2YF",@stdlib/stats-base-ndarray-smaxabssorted
 "2Vq",@stdlib/stats/base/ndarray/smaxsorted
 "2Vr",@stdlib/stats-base-ndarray-smaxsorted
 "2Ua",@stdlib/stats/base/ndarray/smean
@@ -7303,12 +7371,18 @@
 "2Pt",@stdlib/stats-base-ndarray-smin
 "2Uc",@stdlib/stats/base/ndarray/sminabs
 "2Ud",@stdlib/stats-base-ndarray-sminabs
+"2YG",@stdlib/stats/base/ndarray/sminsorted
+"2YH",@stdlib/stats-base-ndarray-sminsorted
 "2Ue",@stdlib/stats/base/ndarray/snanmax
 "2Uf",@stdlib/stats-base-ndarray-snanmax
+"2YI",@stdlib/stats/base/ndarray/snanmaxabs
+"2YJ",@stdlib/stats-base-ndarray-snanmaxabs
 "2VE",@stdlib/stats/base/ndarray/snanmean
 "2VF",@stdlib/stats-base-ndarray-snanmean
 "2Ug",@stdlib/stats/base/ndarray/snanmin
 "2Uh",@stdlib/stats-base-ndarray-snanmin
+"2YK",@stdlib/stats/base/ndarray/snanminabs
+"2YL",@stdlib/stats-base-ndarray-snanminabs
 "2Pu",@stdlib/stats/base/ndarray/srange
 "2Pv",@stdlib/stats-base-ndarray-srange
 "2Pw",@stdlib/stats/base/ndarray/sztest
@@ -7543,6 +7617,8 @@
 "2Wh",@stdlib/stats-incr-nanhmean
 "2GU",@stdlib/stats/incr/nanmaxabs
 "2GV",@stdlib/stats-incr-nanmaxabs
+"2Yo",@stdlib/stats/incr/nanmcv
+"2Yp",@stdlib/stats-incr-nanmcv
 "2As",@stdlib/stats/incr/nanmean
 "2At",@stdlib/stats-incr-nanmean
 "2Au",@stdlib/stats/incr/nanmeanabs
@@ -8140,6 +8216,8 @@
 "2RZ",@stdlib/stats-strided-varianceyc
 "2GY",@stdlib/stats/strided/wasm/dmeanors
 "2GZ",@stdlib/stats-strided-wasm-dmeanors
+"2Yq",@stdlib/stats/strided/wasm/dmeanpw
+"2Yr",@stdlib/stats-strided-wasm-dmeanpw
 "2KC",@stdlib/stats/strided/wasm/dmeanwd
 "2KD",@stdlib/stats-strided-wasm-dmeanwd
 "2WK",@stdlib/stats/strided/wasm/dnanvariancewd
@@ -8342,6 +8420,8 @@
 "1ff",@stdlib/string-base-capitalize
 "1fg",@stdlib/string/base/code-point-at
 "1fh",@stdlib/string-base-code-point-at
+"2Ys",@stdlib/string/base/concat
+"2Yt",@stdlib/string-base-concat
 "1fi",@stdlib/string/base/constantcase
 "1fj",@stdlib/string-base-constantcase
 "1n0",@stdlib/string/base/distances/hamming
@@ -8573,11 +8653,17 @@
 "1Pz",@stdlib/symbol-async-iterator
 "1Q0",@stdlib/symbol/ctor
 "1Q1",@stdlib/symbol-ctor
+"2YM",@stdlib/symbol/has-instance
+"2YN",@stdlib/symbol-has-instance
 "2XW",@stdlib/symbol/is-concat-spreadable
 "2XX",@stdlib/symbol-is-concat-spreadable
 "1Q2",@stdlib/symbol/iterator
 "1Q3",@stdlib/symbol-iterator
 "1Q5",@stdlib/symbol
+"2Yu",@stdlib/symbol/replace
+"2Yv",@stdlib/symbol-replace
+"2YO",@stdlib/symbol/to-primitive
+"2YP",@stdlib/symbol-to-primitive
 "1h2",@stdlib/time/base
 "1h3",@stdlib/time-base
 "1h4",@stdlib/time/base/parse-duration
diff --git a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json
index 7d76c9dd958a..1840b67b9e51 100644
--- a/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json
+++ b/lib/node_modules/@stdlib/error/tools/id2pkg/data/data.json
@@ -1 +1 @@
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diff --git a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv
index 52088fcb84c5..afacdf8539a3 100644
--- a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv
+++ b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.csv
@@ -9719,3 +9719,89 @@
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diff --git a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.json b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.json
index aa23315dbca0..f9f9debd0769 100644
--- a/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.json
+++ b/lib/node_modules/@stdlib/error/tools/pkg2id/data/data.json
@@ -1 +1 @@
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rray-concat":"2Wz","@stdlib/ndarray/find":"2X0","@stdlib/ndarray-find":"2X1","@stdlib/ndarray/flatten-from":"2X2","@stdlib/ndarray-flatten-from":"2X3","@stdlib/ndarray/pop":"2X4","@stdlib/ndarray-pop":"2X5","@stdlib/ndarray/reverse-dimension":"2X6","@stdlib/ndarray-reverse-dimension":"2X7","@stdlib/ndarray/reverse":"2X8","@stdlib/ndarray-reverse":"2X9","@stdlib/ndarray/shift":"2XA","@stdlib/ndarray-shift":"2XB","@stdlib/ndarray/to-reversed":"2XC","@stdlib/ndarray-to-reversed":"2XD","@stdlib/stats/base/ndarray/meankbn":"2XE","@stdlib/stats-base-ndarray-meankbn":"2XF","@stdlib/stats/base/ndarray/meankbn2":"2XG","@stdlib/stats-base-ndarray-meankbn2":"2XH","@stdlib/stats/base/ndarray/meanors":"2XI","@stdlib/stats-base-ndarray-meanors":"2XJ","@stdlib/stats/base/ndarray/meanpn":"2XK","@stdlib/stats-base-ndarray-meanpn":"2XL","@stdlib/stats/base/ndarray/meanpw":"2XM","@stdlib/stats-base-ndarray-meanpw":"2XN","@stdlib/stats/base/ndarray/meanwd":"2XO","@stdlib/stats-base-ndarray-meanwd":"2XP","@stdlib/stats/base/ndarray/mediansorted":"2XQ","@stdlib/stats-base-ndarray-mediansorted":"2XR","@stdlib/stats/base/ndarray/minsorted":"2XS","@stdlib/stats-base-ndarray-minsorted":"2XT","@stdlib/stats/base/ndarray/mskmax":"2XU","@stdlib/stats-base-ndarray-mskmax":"2XV","@stdlib/symbol/is-concat-spreadable":"2XW","@stdlib/symbol-is-concat-spreadable":"2XX","@stdlib/assert/has-has-instance-symbol-support":"2XY","@stdlib/assert-has-has-instance-symbol-support":"2XZ","@stdlib/assert/has-match-symbol-support":"2Xa","@stdlib/assert-has-match-symbol-support":"2Xb","@stdlib/assert/has-replace-symbol-support":"2Xc","@stdlib/assert-has-replace-symbol-support":"2Xd","@stdlib/assert/has-search-symbol-support":"2Xe","@stdlib/assert-has-search-symbol-support":"2Xf","@stdlib/assert/has-split-symbol-support":"2Xg","@stdlib/assert-has-split-symbol-support":"2Xh","@stdlib/assert/has-to-primitive-symbol-support":"2Xi","@stdlib/assert-has-to-primitive-symbol-support":"2Xj","@stdlib/blas/ext/base/dlinspace":"2Xk","@stdlib/blas-ext-base-dlinspace":"2Xl","@stdlib/blas/ext/base/glinspace":"2Xm","@stdlib/blas-ext-base-glinspace":"2Xn","@stdlib/blas/ext/base/ndarray/dlinspace":"2Xo","@stdlib/blas-ext-base-ndarray-dlinspace":"2Xp","@stdlib/blas/ext/base/ndarray/glinspace":"2Xq","@stdlib/blas-ext-base-ndarray-glinspace":"2Xr","@stdlib/blas/ext/base/ndarray/slinspace":"2Xs","@stdlib/blas-ext-base-ndarray-slinspace":"2Xt","@stdlib/blas/ext/base/slinspace":"2Xu","@stdlib/blas-ext-base-slinspace":"2Xv","@stdlib/ndarray/base/complement-shape":"2Xw","@stdlib/ndarray-base-complement-shape":"2Xx","@stdlib/ndarray/copy":"2Xy","@stdlib/ndarray-copy":"2Xz","@stdlib/stats/base/ndarray/dmeankbn":"2Y0","@stdlib/stats-base-ndarray-dmeankbn":"2Y1","@stdlib/stats/base/ndarray/dmeankbn2":"2Y2","@stdlib/stats-base-ndarray-dmeankbn2":"2Y3","@stdlib/stats/base/ndarray/dmeanli":"2Y4","@stdlib/stats-base-ndarray-dmeanli":"2Y5","@stdlib/stats/base/ndarray/dmeanlipw":"2Y6","@stdlib/stats-base-ndarray-dmeanlipw":"2Y7","@stdlib/stats/base/ndarray/dminsorted":"2Y8","@stdlib/stats-base-ndarray-dminsorted":"2Y9","@stdlib/stats/base/ndarray/mskmin":"2YA","@stdlib/stats-base-ndarray-mskmin":"2YB","@stdlib/stats/base/ndarray/range-by":"2YC","@stdlib/stats-base-ndarray-range-by":"2YD","@stdlib/stats/base/ndarray/smaxabssorted":"2YE","@stdlib/stats-base-ndarray-smaxabssorted":"2YF","@stdlib/stats/base/ndarray/sminsorted":"2YG","@stdlib/stats-base-ndarray-sminsorted":"2YH","@stdlib/stats/base/ndarray/snanmaxabs":"2YI","@stdlib/stats-base-ndarray-snanmaxabs":"2YJ","@stdlib/stats/base/ndarray/snanminabs":"2YK","@stdlib/stats-base-ndarray-snanminabs":"2YL","@stdlib/symbol/has-instance":"2YM","@stdlib/symbol-has-instance":"2YN","@stdlib/symbol/to-primitive":"2YO","@stdlib/symbol-to-primitive":"2YP","@stdlib/blas/ext/base/drrss":"2YQ","@stdlib/blas-ext-base-drrss":"2YR","@stdlib/blas/ext/linspace":"2YS","@stdlib/blas-ext-linspace":"2YT","@stdlib/ndarray/some":"2YU","@stdlib/ndarray-some":"2YV","@stdlib/number/float64/base/to-float16":"2YW","@stdlib/number-float64-base-to-float16":"2YX","@stdlib/number/int16/base":"2YY","@stdlib/number-int16-base":"2YZ","@stdlib/number/int8/base":"2Ya","@stdlib/number-int8-base":"2Yb","@stdlib/stats/base/ndarray/dnanmaxabs":"2Yc","@stdlib/stats-base-ndarray-dnanmaxabs":"2Yd","@stdlib/stats/base/ndarray/dnanminabs":"2Ye","@stdlib/stats-base-ndarray-dnanminabs":"2Yf","@stdlib/stats/base/ndarray/nanmaxabs":"2Yg","@stdlib/stats-base-ndarray-nanmaxabs":"2Yh","@stdlib/stats/base/ndarray/nanminabs":"2Yi","@stdlib/stats-base-ndarray-nanminabs":"2Yj","@stdlib/stats/base/ndarray/scumaxabs":"2Yk","@stdlib/stats-base-ndarray-scumaxabs":"2Yl","@stdlib/stats/base/ndarray/scuminabs":"2Ym","@stdlib/stats-base-ndarray-scuminabs":"2Yn","@stdlib/stats/incr/nanmcv":"2Yo","@stdlib/stats-incr-nanmcv":"2Yp","@stdlib/stats/strided/wasm/dmeanpw":"2Yq","@stdlib/stats-strided-wasm-dmeanpw":"2Yr","@stdlib/string/base/concat":"2Ys","@stdlib/string-base-concat":"2Yt","@stdlib/symbol/replace":"2Yu","@stdlib/symbol-replace":"2Yv"}
diff --git a/lib/node_modules/@stdlib/math/base/special/ceilf/README.md b/lib/node_modules/@stdlib/math/base/special/ceilf/README.md
index 6562c36127a9..a2647debe2aa 100644
--- a/lib/node_modules/@stdlib/math/base/special/ceilf/README.md
+++ b/lib/node_modules/@stdlib/math/base/special/ceilf/README.md
@@ -168,7 +168,7 @@ int main( void ) {
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/math/base/special/floorf`][@stdlib/math/base/special/floorf]</span><span class="delimiter">: </span><span class="description">round a single-precision floating-point numeric value toward negative infinity.</span>
+-   <span class="package-name">[`@stdlib/math/base/special/floorf`][@stdlib/math/base/special/floorf]</span><span class="delimiter">: </span><span class="description">round a single-precision floating-point number toward negative infinity.</span>
 
 </section>
 
diff --git a/lib/node_modules/@stdlib/math/base/special/csignum/package.json b/lib/node_modules/@stdlib/math/base/special/csignum/package.json
index f6800f2d1e02..f7283e8570be 100644
--- a/lib/node_modules/@stdlib/math/base/special/csignum/package.json
+++ b/lib/node_modules/@stdlib/math/base/special/csignum/package.json
@@ -60,5 +60,76 @@
     "complex",
     "cmplx",
     "number"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "$schema": "math/base@v1.0",
+      "base_alias": "csignum",
+      "alias": "csignum",
+      "pkg_desc": "evaluate the signum function of a double-precision complex floating-point number",
+      "desc": "evaluates the signum function of a double-precision complex floating-point number",
+      "short_desc": "signum function of a complex number",
+      "parameters": [
+        {
+          "name": "z",
+          "desc": "complex number",
+          "type": {
+            "javascript": "Complex128",
+            "jsdoc": "Complex128",
+            "c": "stdlib_complex128_t",
+            "dtype": "complex128"
+          },
+          "domain": [
+            {
+              "min": "-infinity",
+              "max": "infinity"
+            }
+          ],
+          "rand": {
+            "prng": "random/base/box-muller",
+            "parameters": []
+          },
+          "example_values": [
+            5.0,
+            3.0,
+            -5.0,
+            2.0,
+            -2.0,
+            1.0,
+            -1.0,
+            4.0,
+            -4.0,
+            6.0,
+            -6.0,
+            7.0,
+            -7.0,
+            8.0,
+            -8.0,
+            9.0,
+            -9.0,
+            10.0,
+            -10.0,
+            11.0
+          ]
+        }
+      ],
+      "returns": {
+        "desc": "result",
+        "type": {
+          "javascript": "Complex128",
+          "jsdoc": "Complex128",
+          "c": "stdlib_complex128_t",
+          "dtype": "complex128"
+        }
+      },
+      "keywords": [
+        "signum",
+        "sign",
+        "sgn",
+        "complex",
+        "cmplx"
+      ],
+      "extra_keywords": []
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/math/base/special/package.json b/lib/node_modules/@stdlib/math/base/special/package.json
index 59fb2077e1e5..094e8ac1ece5 100644
--- a/lib/node_modules/@stdlib/math/base/special/package.json
+++ b/lib/node_modules/@stdlib/math/base/special/package.json
@@ -56,5 +56,10 @@
     "lib",
     "mathematics",
     "math"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/math/special/data/unary.json b/lib/node_modules/@stdlib/math/special/data/unary.json
index ce8cb2c79f24..8485fea4e6c2 100644
--- a/lib/node_modules/@stdlib/math/special/data/unary.json
+++ b/lib/node_modules/@stdlib/math/special/data/unary.json
@@ -5089,6 +5089,141 @@
       "math.cbrt"
     ]
   },
+  "@stdlib/math/base/special/ccis": {
+    "$schema": "math/base@v1.0",
+    "base_alias": "cis",
+    "alias": "ccis",
+    "pkg_desc": "compute the cis function for a double-precision complex floating-point number",
+    "desc": "computes the cis function for a double-precision complex floating-point number",
+    "short_desc": "cis function",
+    "parameters": [
+      {
+        "name": "z",
+        "desc": "input value",
+        "type": {
+          "javascript": "Complex128",
+          "jsdoc": "Complex128",
+          "c": "stdlib_complex128_t",
+          "dtype": "complex128"
+        },
+        "domain": null,
+        "rand": {
+          "prng": "random/base/uniform",
+          "parameters": [
+            [
+              -50,
+              50
+            ],
+            [
+              -50,
+              50
+            ]
+          ]
+        },
+        "example_values": [
+          {
+            "re": 0,
+            "im": 0
+          },
+          {
+            "re": 1,
+            "im": 0
+          },
+          {
+            "re": -3.14,
+            "im": -1.5
+          },
+          {
+            "re": -1.5,
+            "im": 2.5
+          },
+          {
+            "re": 2.5,
+            "im": -1.5
+          },
+          {
+            "re": 0,
+            "im": -3.7
+          },
+          {
+            "re": 4.2,
+            "im": 0
+          },
+          {
+            "re": 21.2,
+            "im": 3
+          },
+          {
+            "re": 11,
+            "im": -5
+          },
+          {
+            "re": 33,
+            "im": -14.67
+          },
+          {
+            "re": -42,
+            "im": 9.3
+          },
+          {
+            "re": -3,
+            "im": 3
+          },
+          {
+            "re": 73,
+            "im": 31
+          },
+          {
+            "re": -2.45,
+            "im": 1.23
+          },
+          {
+            "re": 2.45,
+            "im": -1.23
+          },
+          {
+            "re": 1.77,
+            "im": -3.14
+          },
+          {
+            "re": -7.5,
+            "im": 8.2
+          },
+          {
+            "re": 5.5,
+            "im": -12.3
+          },
+          {
+            "re": -15.8,
+            "im": 0.4
+          },
+          {
+            "re": 0.99,
+            "im": -0.99
+          }
+        ]
+      }
+    ],
+    "returns": {
+      "desc": "result",
+      "type": {
+        "javascript": "Complex128",
+        "jsdoc": "Complex128",
+        "c": "stdlib_complex128_t",
+        "dtype": "complex128"
+      }
+    },
+    "keywords": [
+      "cis",
+      "arithmetic",
+      "complex",
+      "exponential",
+      "euler"
+    ],
+    "extra_keywords": [
+      "exp"
+    ]
+  },
   "@stdlib/number/int8/base/identity": {},
   "@stdlib/number/int16/base/identity": {},
   "@stdlib/number/int32/base/identity": {},
@@ -6998,6 +7133,8 @@
       "math.sin"
     ]
   },
+  "@stdlib/math/base/special/cphasef": {},
+  "@stdlib/math/base/special/cphase": {},
   "@stdlib/math/base/special/cscf": {
     "$schema": "math/base@v1.0",
     "base_alias": "csc",
diff --git a/lib/node_modules/@stdlib/math/special/data/unary_function_database.json b/lib/node_modules/@stdlib/math/special/data/unary_function_database.json
index 1748e288f6cb..82d64a34c04e 100644
--- a/lib/node_modules/@stdlib/math/special/data/unary_function_database.json
+++ b/lib/node_modules/@stdlib/math/special/data/unary_function_database.json
@@ -9,6 +9,7 @@
       "uint8c",
       "complex32"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int32": "@stdlib/math/base/special/labs",
       "uint8": "@stdlib/number/uint8/base/identity",
@@ -35,6 +36,7 @@
       "uint8c",
       "complex32"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/abs2f",
       "float64": "@stdlib/math/base/special/abs2",
@@ -56,6 +58,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/absgammalnf",
       "float64": "@stdlib/math/base/special/gammaln",
@@ -75,6 +78,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acosf",
       "float64": "@stdlib/math/base/special/acos",
@@ -94,6 +98,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acosdf",
       "float64": "@stdlib/math/base/special/acosd",
@@ -113,6 +118,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/acosh",
       "generic": "@stdlib/math/base/special/acosh"
@@ -131,6 +137,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acotf",
       "float64": "@stdlib/math/base/special/acot",
@@ -150,6 +157,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acotdf",
       "float64": "@stdlib/math/base/special/acotd",
@@ -169,6 +177,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/acoth",
       "generic": "@stdlib/math/base/special/acoth"
@@ -187,6 +196,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acovercosf",
       "float64": "@stdlib/math/base/special/acovercos",
@@ -206,6 +216,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acoversinf",
       "float64": "@stdlib/math/base/special/acoversin",
@@ -225,6 +236,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acscf",
       "float64": "@stdlib/math/base/special/acsc",
@@ -244,6 +256,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/acscdf",
       "float64": "@stdlib/math/base/special/acscd",
@@ -263,6 +276,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/acsch",
       "generic": "@stdlib/math/base/special/acsch"
@@ -281,6 +295,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/ahavercosf",
       "float64": "@stdlib/math/base/special/ahavercos",
@@ -300,6 +315,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/ahaversinf",
       "float64": "@stdlib/math/base/special/ahaversin",
@@ -319,6 +335,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/asecf",
       "float64": "@stdlib/math/base/special/asec",
@@ -338,6 +355,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/asecdf",
       "float64": "@stdlib/math/base/special/asecd",
@@ -357,6 +375,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/asech",
       "generic": "@stdlib/math/base/special/asech"
@@ -375,6 +394,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/asinf",
       "float64": "@stdlib/math/base/special/asin",
@@ -394,6 +414,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/asindf",
       "float64": "@stdlib/math/base/special/asind",
@@ -413,6 +434,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/asinh",
       "generic": "@stdlib/math/base/special/asinh"
@@ -431,6 +453,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/atanf",
       "float64": "@stdlib/math/base/special/atan",
@@ -450,6 +473,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/atandf",
       "float64": "@stdlib/math/base/special/atand",
@@ -469,6 +493,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/atanh",
       "generic": "@stdlib/math/base/special/atanh"
@@ -487,6 +512,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/avercosf",
       "float64": "@stdlib/math/base/special/avercos",
@@ -506,6 +532,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/aversinf",
       "float64": "@stdlib/math/base/special/aversin",
@@ -525,6 +552,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/bernoullif",
       "float64": "@stdlib/math/base/special/bernoulli",
@@ -544,6 +572,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/besselj0",
       "generic": "@stdlib/math/base/special/besselj0"
@@ -562,6 +591,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/besselj1",
       "generic": "@stdlib/math/base/special/besselj1"
@@ -580,6 +610,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/bessely0",
       "generic": "@stdlib/math/base/special/bessely0"
@@ -598,6 +629,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/bessely1",
       "generic": "@stdlib/math/base/special/bessely1"
@@ -616,6 +648,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/binet",
       "generic": "@stdlib/math/base/special/binet"
@@ -634,6 +667,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cbrtf",
       "float64": "@stdlib/math/base/special/cbrt",
@@ -644,6 +678,26 @@
       "casting": "none"
     }
   },
+  "ccis": {
+    "input_dtypes": "complex_floating_point",
+    "output_dtypes": "complex_floating_point_and_generic",
+    "excluded_dtypes": [
+      "float16",
+      "uint8c",
+      "int64",
+      "uint64",
+      "complex32"
+    ],
+    "primary_dtype": "complex128",
+    "scalar_kernels": {
+      "complex128": "@stdlib/math/base/special/ccis",
+      "generic": "@stdlib/math/base/special/ccis"
+    },
+    "policies": {
+      "output": "complex_floating_point_and_generic",
+      "casting": "none"
+    }
+  },
   "ceil": {
     "input_dtypes": "numeric_and_generic",
     "output_dtypes": "numeric_and_generic",
@@ -654,6 +708,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -682,6 +737,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -707,6 +763,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -731,6 +788,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cosf",
       "float64": "@stdlib/math/base/special/cos",
@@ -750,6 +808,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cosdf",
       "float64": "@stdlib/math/base/special/cosd",
@@ -769,6 +828,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/cosh",
       "generic": "@stdlib/math/base/special/cosh"
@@ -787,6 +847,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cosm1f",
       "float64": "@stdlib/math/base/special/cosm1",
@@ -806,6 +867,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cospif",
       "float64": "@stdlib/math/base/special/cospi",
@@ -825,6 +887,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cotf",
       "float64": "@stdlib/math/base/special/cot",
@@ -844,6 +907,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/cotd",
       "generic": "@stdlib/math/base/special/cotd"
@@ -862,6 +926,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/coth",
       "generic": "@stdlib/math/base/special/coth"
@@ -880,6 +945,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/covercosf",
       "float64": "@stdlib/math/base/special/covercos",
@@ -899,6 +965,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/coversinf",
       "float64": "@stdlib/math/base/special/coversin",
@@ -909,6 +976,26 @@
       "casting": "none"
     }
   },
+  "cphase": {
+    "input_dtypes": "complex_floating_point",
+    "output_dtypes": "real_floating_point_and_generic",
+    "excluded_dtypes": [
+      "float16",
+      "uint8c",
+      "int64",
+      "uint64",
+      "complex32"
+    ],
+    "primary_dtype": "complex128",
+    "scalar_kernels": {
+      "complex64": "@stdlib/math/base/special/cphasef",
+      "complex128": "@stdlib/math/base/special/cphase"
+    },
+    "policies": {
+      "output": "real_floating_point_and_generic",
+      "casting": "none"
+    }
+  },
   "csc": {
     "input_dtypes": "real_and_generic",
     "output_dtypes": "real_floating_point_and_generic",
@@ -918,6 +1005,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/cscf",
       "float64": "@stdlib/math/base/special/csc",
@@ -937,6 +1025,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/cscd",
       "generic": "@stdlib/math/base/special/cscd"
@@ -955,6 +1044,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/csch",
       "generic": "@stdlib/math/base/special/csch"
@@ -973,6 +1063,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/deg2radf",
       "float64": "@stdlib/math/base/special/deg2rad",
@@ -992,6 +1083,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/digamma",
       "generic": "@stdlib/math/base/special/digamma"
@@ -1010,6 +1102,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/dirac-deltaf",
       "float64": "@stdlib/math/base/special/dirac-delta",
@@ -1029,6 +1122,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/dirichlet-eta",
       "generic": "@stdlib/math/base/special/dirichlet-eta"
@@ -1047,6 +1141,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/ellipe",
       "generic": "@stdlib/math/base/special/ellipe"
@@ -1065,6 +1160,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/ellipk",
       "generic": "@stdlib/math/base/special/ellipk"
@@ -1083,6 +1179,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/erf",
       "generic": "@stdlib/math/base/special/erf"
@@ -1101,6 +1198,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/erfc",
       "generic": "@stdlib/math/base/special/erfc"
@@ -1119,6 +1217,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/erfcinv",
       "generic": "@stdlib/math/base/special/erfcinv"
@@ -1137,6 +1236,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/erfcx",
       "generic": "@stdlib/math/base/special/erfcx"
@@ -1155,6 +1255,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/erfinv",
       "generic": "@stdlib/math/base/special/erfinv"
@@ -1174,6 +1275,7 @@
       "uint64",
       "complex32"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/exp",
       "complex128": "@stdlib/math/base/special/cexp",
@@ -1193,6 +1295,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/exp10",
       "generic": "@stdlib/math/base/special/exp10"
@@ -1211,6 +1314,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/exp2",
       "generic": "@stdlib/math/base/special/exp2"
@@ -1229,6 +1333,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/expit",
       "generic": "@stdlib/math/base/special/expit"
@@ -1247,6 +1352,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/expm1",
       "generic": "@stdlib/math/base/special/expm1"
@@ -1265,6 +1371,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/expm1rel",
       "generic": "@stdlib/math/base/special/expm1rel"
@@ -1283,6 +1390,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/factorial",
       "generic": "@stdlib/math/base/special/factorial"
@@ -1301,6 +1409,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/factorial2f",
       "float64": "@stdlib/math/base/special/factorial2",
@@ -1320,6 +1429,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/factoriallnf",
       "float64": "@stdlib/math/base/special/factorialln",
@@ -1339,6 +1449,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/fibonaccif",
       "float64": "@stdlib/math/base/special/fibonacci",
@@ -1358,6 +1469,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/fibonacci-indexf",
       "float64": "@stdlib/math/base/special/fibonacci-index",
@@ -1378,6 +1490,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -1406,6 +1519,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -1431,6 +1545,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -1449,19 +1564,20 @@
   "fresnel": {
     "input_dtypes": "real_and_generic",
     "output_dtypes": "real_floating_point_and_generic",
-    "policies": {
-      "output": "real_floating_point_and_generic",
-      "casting": "none"
-    },
     "excluded_dtypes": [
       "float16",
       "uint8c",
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/fresnel",
       "generic": "@stdlib/math/base/special/fresnel"
+    },
+    "policies": {
+      "output": "real_floating_point_and_generic",
+      "casting": "none"
     }
   },
   "fresnelc": {
@@ -1473,6 +1589,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/fresnelc",
       "generic": "@stdlib/math/base/special/fresnelc"
@@ -1491,6 +1608,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/fresnels",
       "generic": "@stdlib/math/base/special/fresnels"
@@ -1509,6 +1627,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/gamma",
       "generic": "@stdlib/math/base/special/gamma"
@@ -1527,6 +1646,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/gamma-lanczos-sum",
       "generic": "@stdlib/math/base/special/gamma-lanczos-sum"
@@ -1545,6 +1665,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/gamma-lanczos-sum-expg-scaledf",
       "float64": "@stdlib/math/base/special/gamma-lanczos-sum-expg-scaled",
@@ -1564,6 +1685,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/gamma1pm1",
       "generic": "@stdlib/math/base/special/gamma1pm1"
@@ -1582,6 +1704,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/gammasgnf",
       "float64": "@stdlib/math/base/special/gammasgn",
@@ -1601,6 +1724,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/hacovercosf",
       "float64": "@stdlib/math/base/special/hacovercos",
@@ -1620,6 +1744,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/hacoversinf",
       "float64": "@stdlib/math/base/special/hacoversin",
@@ -1639,6 +1764,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/havercosf",
       "float64": "@stdlib/math/base/special/havercos",
@@ -1658,6 +1784,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/haversinf",
       "float64": "@stdlib/math/base/special/haversin",
@@ -1678,6 +1805,7 @@
       "uint64",
       "complex32"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/invf",
       "float64": "@stdlib/math/base/special/inv",
@@ -1699,6 +1827,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/lnf",
       "float64": "@stdlib/math/base/special/ln",
@@ -1718,6 +1847,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log10",
       "generic": "@stdlib/math/base/special/log10"
@@ -1736,6 +1866,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log1mexp",
       "generic": "@stdlib/math/base/special/log1mexp"
@@ -1754,6 +1885,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log1p",
       "generic": "@stdlib/math/base/special/log1p"
@@ -1772,6 +1904,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log1pexp",
       "generic": "@stdlib/math/base/special/log1pexp"
@@ -1790,6 +1923,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log1pmx",
       "generic": "@stdlib/math/base/special/log1pmx"
@@ -1808,6 +1942,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/log2",
       "generic": "@stdlib/math/base/special/log2"
@@ -1826,6 +1961,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/logitf",
       "float64": "@stdlib/math/base/special/logit",
@@ -1845,6 +1981,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/lucasf",
       "float64": "@stdlib/math/base/special/lucas",
@@ -1864,6 +2001,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/negafibonaccif",
       "float64": "@stdlib/math/base/special/negafibonacci",
@@ -1883,6 +2021,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/negalucasf",
       "float64": "@stdlib/math/base/special/negalucas",
@@ -1902,6 +2041,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/nonfibonaccif",
       "float64": "@stdlib/math/base/special/nonfibonacci",
@@ -1921,6 +2061,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/rad2degf",
       "float64": "@stdlib/math/base/special/rad2deg",
@@ -1940,6 +2081,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/rampf",
       "float64": "@stdlib/math/base/special/ramp",
@@ -1959,6 +2101,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/rcbrtf",
       "float64": "@stdlib/math/base/special/rcbrt",
@@ -1978,6 +2121,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/riemann-zeta",
       "generic": "@stdlib/math/base/special/riemann-zeta"
@@ -1997,6 +2141,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2025,6 +2170,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2050,6 +2196,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2075,6 +2222,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2099,6 +2247,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/rsqrtf",
       "float64": "@stdlib/math/base/special/rsqrt",
@@ -2118,6 +2267,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/secf",
       "float64": "@stdlib/math/base/special/sec",
@@ -2137,6 +2287,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/secd",
       "generic": "@stdlib/math/base/special/secd"
@@ -2155,6 +2306,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/sech",
       "generic": "@stdlib/math/base/special/sech"
@@ -2174,6 +2326,7 @@
       "uint64",
       "complex32"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2201,6 +2354,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sinf",
       "float64": "@stdlib/math/base/special/sin",
@@ -2220,6 +2374,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sincf",
       "float64": "@stdlib/math/base/special/sinc",
@@ -2239,6 +2394,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sindf",
       "float64": "@stdlib/math/base/special/sind",
@@ -2258,6 +2414,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/sinh",
       "generic": "@stdlib/math/base/special/sinh"
@@ -2276,6 +2433,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sinpif",
       "float64": "@stdlib/math/base/special/sinpi",
@@ -2295,6 +2453,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/spencef",
       "float64": "@stdlib/math/base/special/spence",
@@ -2314,6 +2473,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sqrtf",
       "float64": "@stdlib/math/base/special/sqrt",
@@ -2333,6 +2493,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/sqrt1pm1",
       "generic": "@stdlib/math/base/special/sqrt1pm1"
@@ -2351,6 +2512,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/sqrtpif",
       "float64": "@stdlib/math/base/special/sqrtpi",
@@ -2370,6 +2532,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/tanf",
       "float64": "@stdlib/math/base/special/tan",
@@ -2389,6 +2552,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/tandf",
       "float64": "@stdlib/math/base/special/tand",
@@ -2408,6 +2572,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float64": "@stdlib/math/base/special/tanh",
       "generic": "@stdlib/math/base/special/tanh"
@@ -2426,6 +2591,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/tribonaccif",
       "float64": "@stdlib/math/base/special/tribonacci",
@@ -2445,6 +2611,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/trigammaf",
       "float64": "@stdlib/math/base/special/trigamma",
@@ -2465,6 +2632,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2491,6 +2659,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2516,6 +2685,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "int8": "@stdlib/number/int8/base/identity",
       "int16": "@stdlib/number/int16/base/identity",
@@ -2540,6 +2710,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/vercosf",
       "float64": "@stdlib/math/base/special/vercos",
@@ -2559,6 +2730,7 @@
       "int64",
       "uint64"
     ],
+    "primary_dtype": "float64",
     "scalar_kernels": {
       "float32": "@stdlib/math/base/special/versinf",
       "float64": "@stdlib/math/base/special/versin",
diff --git a/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.1d.js
index 77abf14267a8..1b8a5027897a 100644
--- a/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.1d.js
@@ -140,7 +140,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.2d.js
index e7a3bc08f162..5ff0cf829265 100644
--- a/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/any-by/benchmark/benchmark.2d.js
@@ -144,17 +144,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.1d.js
index 38ec63f95d1c..1374747824b3 100644
--- a/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.1d.js
@@ -124,7 +124,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.2d.js
index 0a1407a01c9e..dd78bf29b7d0 100644
--- a/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/any/benchmark/benchmark.2d.js
@@ -128,17 +128,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/base/README.md b/lib/node_modules/@stdlib/ndarray/base/README.md
index 042158800470..52e31c43cb78 100644
--- a/lib/node_modules/@stdlib/ndarray/base/README.md
+++ b/lib/node_modules/@stdlib/ndarray/base/README.md
@@ -67,6 +67,7 @@ var o = ns;
 -   <span class="signature">[`bytesPerElement( dtype )`][@stdlib/ndarray/base/bytes-per-element]</span><span class="delimiter">: </span><span class="description">return the number of bytes per element for a provided underlying ndarray data type.</span>
 -   <span class="signature">[`char2dtype( [ch] )`][@stdlib/ndarray/base/char2dtype]</span><span class="delimiter">: </span><span class="description">return the data type string associated with a provided single letter character abbreviation.</span>
 -   <span class="signature">[`clampIndex( idx, max )`][@stdlib/ndarray/base/clamp-index]</span><span class="delimiter">: </span><span class="description">restrict an index to the interval `[0,max]`.</span>
+-   <span class="signature">[`complementShape( shape, dims )`][@stdlib/ndarray/base/complement-shape]</span><span class="delimiter">: </span><span class="description">return the shape defined by the dimensions which are not included in a list of dimensions.</span>
 -   <span class="signature">[`copy( x )`][@stdlib/ndarray/base/copy]</span><span class="delimiter">: </span><span class="description">copy an input ndarray to a new ndarray having the same shape and data type.</span>
 -   <span class="signature">[`countFalsy( arrays )`][@stdlib/ndarray/base/count-falsy]</span><span class="delimiter">: </span><span class="description">count the number of falsy elements in an ndarray.</span>
 -   <span class="signature">[`countIf( arrays, predicate[, thisArg] )`][@stdlib/ndarray/base/count-if]</span><span class="delimiter">: </span><span class="description">count the number of elements in an ndarray which pass a test implemented by a predicate function.</span>
@@ -303,6 +304,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/ndarray/base/clamp-index]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/clamp-index
 
+[@stdlib/ndarray/base/complement-shape]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/complement-shape
+
 [@stdlib/ndarray/base/copy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/copy
 
 [@stdlib/ndarray/base/count-falsy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/count-falsy
diff --git a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major/examples/index.js b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major/examples/index.js
index 13e6c0bc321b..805b43067c8b 100644
--- a/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major/examples/index.js
+++ b/lib/node_modules/@stdlib/ndarray/base/assert/is-row-major/examples/index.js
@@ -25,7 +25,7 @@ var shape = [ 10, 10, 10 ];
 
 var strides = shape2strides( shape, 'row-major' );
 console.log( 'Strides: %s', strides.join( ',' ) );
-// => Strides: 100,10,1
+// => 'Strides: 100,10,1'
 
 var bool = isRowMajor( strides );
 console.log( bool );
@@ -33,7 +33,7 @@ console.log( bool );
 
 strides = shape2strides( shape, 'column-major' );
 console.log( 'Strides: %s', strides.join( ',' ) );
-// => Strides: 1,10,100
+// => 'Strides: 1,10,100'
 
 bool = isRowMajor( strides );
 console.log( bool );
diff --git a/lib/node_modules/@stdlib/ndarray/base/complement-shape/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/base/complement-shape/docs/types/index.d.ts
index 6b2d35290444..2933e431e99e 100644
--- a/lib/node_modules/@stdlib/ndarray/base/complement-shape/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/ndarray/base/complement-shape/docs/types/index.d.ts
@@ -42,9 +42,6 @@ import { Collection } from '@stdlib/types/array';
 * sh = complementShape( [ 3, 2 ], [ 0 ] );
 * // returns [ 2 ]
 *
-* sh = complementShape( [ 3 ], [ 0 ] );
-* // returns []
-*
 * sh = complementShape( [], [] );
 * // returns []
 */
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/lib/main.js
index 5cd82577c9f9..a85021693670 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-falsy/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/lib/main.js
@@ -274,7 +274,7 @@ function countFalsy( arrays ) {
 	}
 	// Check whether we were provided an empty ndarray...
 	if ( len === 0 ) {
-		return true;
+		return 0;
 	}
 	// Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array...
 	if ( ndims === 1 ) {
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.0d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.0d.js
index 6b9f504b739f..a0cb49031d34 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.0d.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.0d.js
@@ -62,12 +62,12 @@ tape( 'the function counts the number of falsy elements in a 0-dimensional ndarr
 	var actual;
 	var x;
 
-	x = ndarray( 'float64', toAccessorArray( new Float64Array( [ 0.0 ] ) ), [], [ 0 ], 0, 'row-major' );
+	x = ndarray( 'generic', toAccessorArray( new Float64Array( [ 0.0 ] ) ), [], [ 0 ], 0, 'row-major' );
 
 	actual = countFalsy( [ x ] );
 	t.strictEqual( actual, 1, 'returns expected value' );
 
-	x = ndarray( 'float64', toAccessorArray( new Float64Array( [ 1.0 ] ) ), [], [ 0 ], 0, 'row-major' );
+	x = ndarray( 'generic', toAccessorArray( new Float64Array( [ 1.0 ] ) ), [], [ 0 ], 0, 'row-major' );
 
 	actual = countFalsy( [ x ] );
 	t.strictEqual( actual, 0, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.10d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.10d.js
new file mode 100644
index 000000000000..703154b7e2f1
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.10d.js
@@ -0,0 +1,2867 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-bsize*4,
+		bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		-bsize*8,
+		bsize*16,
+		-bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		4,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		bsize*4,
+		bsize*4,
+		-bsize*8,
+		bsize*8,
+		-bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		4,
+		-bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		4,
+		-bsize*8,
+		bsize*8,
+		-bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-bsize*4,
+		-bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.1d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.1d.js
new file mode 100644
index 000000000000..410ec410c151
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.1d.js
@@ -0,0 +1,88 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 1-dimensional ndarray', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', zeros( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( 'float64', ones( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 1-dimensional ndarray (accessors)', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'generic', toAccessorArray( zeros( 8, 'generic' ) ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( 'generic', toAccessorArray( ones( 8, 'generic' ) ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 1-dimensional ndarray (complex)', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'complex128', zeros( 6, 'complex128' ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( 'complex128', ones( 6, 'complex128' ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.2d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.2d.js
new file mode 100644
index 000000000000..bcf7140b098e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.2d.js
@@ -0,0 +1,1197 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ 2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -2, bsize*2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ 2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -2, bsize*2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ 2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.3d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.3d.js
new file mode 100644
index 000000000000..25f92fe3de80
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.3d.js
@@ -0,0 +1,1383 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ bsize*8, bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -4, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ -bsize*8, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -3, -2, 1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ bsize*8, bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -1, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ 2, -2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, -2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ 2, -2, bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, -2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 1, -2, -3 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -2, -2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.4d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.4d.js
new file mode 100644
index 000000000000..5ad29547b406
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.4d.js
@@ -0,0 +1,1569 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, bsize*4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, bsize*4, -bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ -bsize*4, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ bsize*4, bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ 2, 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ 2, -2, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 1, 2 ];
+	st = [ 2, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, -4, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ 1, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ 2, 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ 2, 2, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 1, 2 ];
+	st = [ 2, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.5d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.5d.js
new file mode 100644
index 000000000000..969e24555143
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.5d.js
@@ -0,0 +1,1745 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2, 2 ];
+	st = [ -8, -4, -4, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, bsize*8, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2, 2 ];
+	st = [ -1, -2, -4, -4, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -2, 4, -bsize*8, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, 4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ -2, 4, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 2, 1, 1 ];
+	st = [ -2, 4, -bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, -4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 2, 1, 1 ];
+	st = [ -2, 4, -bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, -4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.6d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.6d.js
new file mode 100644
index 000000000000..573cb8a28fe7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.6d.js
@@ -0,0 +1,1929 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ bsize*8, -4, -4, 4, 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ -bsize*8, -4, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ -bsize*8, -4, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, -2, 2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.7d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.7d.js
new file mode 100644
index 000000000000..d91cc4f04d8a
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.7d.js
@@ -0,0 +1,2113 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -16, 16, -16, -8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, -2, 2, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.8d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.8d.js
new file mode 100644
index 000000000000..310735a12eb8
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.8d.js
@@ -0,0 +1,2333 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.9d.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.9d.js
new file mode 100644
index 000000000000..f9b0c0d0f1ea
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.9d.js
@@ -0,0 +1,2533 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.js
index 959d9e74dbea..8b2c4a41bb4e 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.js
@@ -21,6 +21,8 @@
 // MODULES //
 
 var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
 var countFalsy = require( './../lib' );
 
 
@@ -31,3 +33,14 @@ tape( 'main export is a function', function test( t ) {
 	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
 	t.end();
 });
+
+tape( 'the function returns `0` if the input is an empty ndarray', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', zeros( 8, 'float64' ), [ 0 ], [ 1 ], 0, 'row-major' );
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.nd.js b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.nd.js
new file mode 100644
index 000000000000..7f3f55f8f5de
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-falsy/test/test.nd.js
@@ -0,0 +1,824 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countFalsy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countFalsy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of falsy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countFalsy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/count-if/lib/main.js
index 5695a2388adc..debb122e9e6f 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-if/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/lib/main.js
@@ -193,7 +193,7 @@ function countIf( arrays, predicate, thisArg ) {
 	}
 	// Check whether we were provided an empty ndarray...
 	if ( numel( shx ) === 0 ) {
-		return true;
+		return 0;
 	}
 	// Determine whether we can avoid blocked iteration...
 	if ( ndims <= MAX_DIMS && iterationOrder( x.strides ) !== 0 ) {
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.10d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.10d.js
new file mode 100644
index 000000000000..0fd984a21a06
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.10d.js
@@ -0,0 +1,2655 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -16, -16, -16, -16, -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -2, -2, -2, -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		bsize*4,
+		-bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		-2,
+		-4,
+		4,
+		4,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		-2,
+		-bsize*4,
+		bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		4,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1, 1, 1 ];
+	st = [
+		2,
+		4,
+		-4,
+		4,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 10-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.1d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.1d.js
new file mode 100644
index 000000000000..32557faa66ab
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.1d.js
@@ -0,0 +1,202 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var ones = require( '@stdlib/array/ones' );
+var zeros = require( '@stdlib/array/zeros' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 1-dimensional ndarray which pass a test implemented by a predicate function', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', zeros( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( 'float64', ones( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 1-dimensional ndarray which pass a test implemented by a predicate function (accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var x;
+
+	xbuf = zeros( 6*2, 'float64' );
+	x = ndarray( 'complex128', new Complex128Array( xbuf ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 6*2, 'float64' );
+	x = ndarray( 'complex128', new Complex128Array( xbuf ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var x;
+
+	x = new ndarray( 'float64', ones( 8, 'float64'), [ 4 ], [ 2 ], 0, 'row-major' );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0 ],
+		[ 1 ],
+		[ 2 ],
+		[ 3 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var x;
+
+	xbuf = ones( 6*2, 'float64' );
+	x = ndarray( 'complex128', new Complex128Array( xbuf ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0 ],
+		[ 1 ],
+		[ 2 ],
+		[ 3 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.2d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.2d.js
new file mode 100644
index 000000000000..2054de0e2e3f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.2d.js
@@ -0,0 +1,1285 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0 ],
+		[ 0, 1 ],
+		[ 1, 0 ],
+		[ 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0 ],
+		[ 0, 1 ],
+		[ 1, 0 ],
+		[ 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -4, -2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0 ],
+		[ 1, 0 ],
+		[ 0, 1 ],
+		[ 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0 ],
+		[ 1, 0 ],
+		[ 0, 1 ],
+		[ 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ 2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -2, bsize*2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 2-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ 2, -4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.3d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.3d.js
new file mode 100644
index 000000000000..d01d0ccdad6a
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.3d.js
@@ -0,0 +1,1479 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0 ],
+		[ 0, 0, 1 ],
+		[ 0, 1, 0 ],
+		[ 0, 1, 1 ],
+		[ 1, 0, 0 ],
+		[ 1, 0, 1 ],
+		[ 1, 1, 0 ],
+		[ 1, 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0 ],
+		[ 0, 0, 1 ],
+		[ 0, 1, 0 ],
+		[ 0, 1, 1 ],
+		[ 1, 0, 0 ],
+		[ 1, 0, 1 ],
+		[ 1, 1, 0 ],
+		[ 1, 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1 ];
+	st = [ bsize*4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ bsize*4, -bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1 ];
+	st = [ bsize*4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ bsize*4, -bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0 ],
+		[ 1, 0, 0 ],
+		[ 0, 1, 0 ],
+		[ 1, 1, 0 ],
+		[ 0, 0, 1 ],
+		[ 1, 0, 1 ],
+		[ 0, 1, 1 ],
+		[ 1, 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0 ],
+		[ 1, 0, 0 ],
+		[ 0, 1, 0 ],
+		[ 1, 1, 0 ],
+		[ 0, 0, 1 ],
+		[ 1, 0, 1 ],
+		[ 0, 1, 1 ],
+		[ 1, 1, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, 2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1 ];
+	st = [ -2, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ -2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, -2, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -2, bsize*4, bsize*4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1 ];
+	st = [ 2, -4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 3-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.4d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.4d.js
new file mode 100644
index 000000000000..423b5fdac090
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.4d.js
@@ -0,0 +1,1577 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0 ],
+		[ 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0 ],
+		[ 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ bsize*4, -2, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ bsize*4, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ bsize*4, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ bsize*4, -2, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ bsize*4, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ bsize*4, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0 ],
+		[ 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 4, 'returns expected value' );
+	t.strictEqual( ctx.count, 4, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0 ],
+		[ 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -1, 2, -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ -2, 4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ -2, 4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ -2, 4, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -1, -2, 2, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -2, bsize*4, bsize*4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 4-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.5d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.5d.js
new file mode 100644
index 000000000000..3d023ae96a87
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.5d.js
@@ -0,0 +1,1771 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1 ],
+		[ 0, 0, 1, 0, 0 ],
+		[ 0, 0, 1, 0, 1 ],
+		[ 1, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 1 ],
+		[ 1, 0, 1, 0, 0 ],
+		[ 1, 0, 1, 0, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1 ],
+		[ 0, 0, 1, 0, 0 ],
+		[ 0, 0, 1, 0, 1 ],
+		[ 1, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 1 ],
+		[ 1, 0, 1, 0, 0 ],
+		[ 1, 0, 1, 0, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, -4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0 ],
+		[ 1, 0, 1, 0, 0 ],
+		[ 0, 0, 0, 0, 1 ],
+		[ 1, 0, 0, 0, 1 ],
+		[ 0, 0, 1, 0, 1 ],
+		[ 1, 0, 1, 0, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0 ],
+		[ 1, 0, 1, 0, 0 ],
+		[ 0, 0, 0, 0, 1 ],
+		[ 1, 0, 0, 0, 1 ],
+		[ 0, 0, 1, 0, 1 ],
+		[ 1, 0, 1, 0, 1 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, 2, -4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -2, -4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, 4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, -4, 4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, -4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, -bsize*4, bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, 4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 5-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.6d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.6d.js
new file mode 100644
index 000000000000..ab4c1249e661
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.6d.js
@@ -0,0 +1,1917 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0 ],
+		[ 1, 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 1, 0 ],
+		[ 1, 0, 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0 ],
+		[ 1, 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 1, 0 ],
+		[ 1, 0, 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*8, -4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0 ],
+		[ 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0 ],
+		[ 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0 ],
+		[ 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0 ],
+		[ 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0 ],
+		[ 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0 ],
+		[ 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, 4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ -2, -4, 4, 4, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ -2, -4, 4, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, 4, -4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, 4, -4, 4, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 6-dimensional ndarray which pass the test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.7d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.7d.js
new file mode 100644
index 000000000000..11b9e1175149
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.7d.js
@@ -0,0 +1,2063 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*8, -4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -16, -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, 4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ -2, -4, 4, 4, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, 4, -4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, 4, -4, 4, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 7-dimensional ndarray which pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.8d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.8d.js
new file mode 100644
index 000000000000..73686f063225
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.8d.js
@@ -0,0 +1,2209 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -16, -16, -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -2, -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 2, bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, 4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ -2, -4, 4, 4, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, 4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, 4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an 8-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.9d.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.9d.js
new file mode 100644
index 000000000000..a97f1a295e1d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.9d.js
@@ -0,0 +1,2435 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -16, -16, -16, -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -8, 8, 4, 4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -4, -4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, 2, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*8,
+		-bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -2, -2, -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		2,
+		bsize*4,
+		-bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1 ];
+	st = [ 2, -4, 4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1, 1 ];
+	st = [ -2, -4, 4, 4, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [ -2, -4, 4, 8, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		-2,
+		-bsize*4,
+		bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 1, 1, 1 ];
+	st = [ 2, 4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 1, 1, 1 ];
+	st = [ 2, 4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in a 9-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, 8, 8, 8, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.js
index 509fad85a45e..1d769246b667 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.js
@@ -21,6 +21,8 @@
 // MODULES //
 
 var tape = require( 'tape' );
+var ones = require( '@stdlib/array/ones' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
 var countIf = require( './../lib' );
 
 
@@ -31,3 +33,19 @@ tape( 'main export is a function', function test( t ) {
 	t.strictEqual( typeof countIf, 'function', 'main export is a function' );
 	t.end();
 });
+
+tape( 'the function returns `0` if provided an empty input ndarray', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', ones( 8, 'float64' ), [ 0 ], [ 1 ], 0, 'row-major' );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0.0;
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.nd.js b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.nd.js
new file mode 100644
index 000000000000..ed8e90532d6d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-if/test/test.nd.js
@@ -0,0 +1,1040 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var real = require( '@stdlib/complex/float64/real' );
+var imag = require( '@stdlib/complex/float64/imag' );
+var Complex128Array = require( '@stdlib/array/complex128' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countIf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countIf, 'function', 'main export is a function');
+	t.end();
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (row-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 16, 8, -8, -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, 16, 16, 16, 16, 8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -16, -16, -16, -16, -16, -8, 8, 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0,
+		1.0
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( v );
+		indices.push( idx );
+		arrays.push( arr );
+		return v !== 0.0;
+	}
+});
+
+tape( 'the function supports specifying the callback execution context (column-major, contiguous, accessors)', function test( t ) {
+	var expected;
+	var indices;
+	var values;
+	var arrays;
+	var actual;
+	var xbuf;
+	var ctx;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	indices = [];
+	values = [];
+	arrays = [];
+
+	ctx = {
+		'count': 0
+	};
+	actual = countIf( [ x ], clbk, ctx );
+
+	t.strictEqual( actual, 8, 'returns expected value' );
+	t.strictEqual( ctx.count, 8, 'returns expected value' );
+
+	expected = [
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ],
+		[ 1.0, 1.0 ]
+	];
+	t.deepEqual( values, expected, 'returns expected value' );
+
+	expected = [
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 0, 0, 1, 0, 1, 0 ],
+		[ 0, 0, 0, 0, 0, 1, 0, 1, 0, 1, 0 ]
+	];
+	t.deepEqual( indices, expected, 'returns expected value' );
+
+	expected = [
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x,
+		x
+	];
+	t.deepEqual( arrays, expected, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v, idx, arr ) {
+		this.count += 1; // eslint-disable-line no-invalid-this
+		values.push( [ real( v ), imag( v ) ] );
+		indices.push( idx );
+		arrays.push( arr );
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -1, -1, -2, -2, 4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -2, -2, -2, -2, -2, -2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*4, dt ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return v !== 0;
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -1, -1, -1, -1, -1, -2, -2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( numel( sh )*2, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
+
+tape( 'the function counts the number of elements in an n-dimensional ndarray pass a test implemented by a predicate function (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var xbuf;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, -4, 4, 8, 8, 16 ];
+	o = strides2offset( sh, st );
+
+	xbuf = zeros( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	xbuf = ones( 8*4, 'float64' );
+	x = ndarray( dt, new Complex128Array( xbuf ), sh, st, o, ord );
+
+	actual = countIf( [ x ], clbk );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+
+	function clbk( v ) {
+		return ( real( v ) !== 0.0 && imag( v ) !== 0.0 );
+	}
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/lib/main.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/lib/main.js
index e66613bfa3f4..3631bf4fe4eb 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-truthy/lib/main.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/lib/main.js
@@ -274,7 +274,7 @@ function countTruthy( arrays ) {
 	}
 	// Check whether we were provided an empty ndarray...
 	if ( len === 0 ) {
-		return true;
+		return 0;
 	}
 	// Determine whether the ndarray is one-dimensional and thus readily translates to a one-dimensional strided array...
 	if ( ndims === 1 ) {
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.0d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.0d.js
index 308721384384..0a3bd59f98cc 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.0d.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.0d.js
@@ -62,12 +62,12 @@ tape( 'the function counts the number of truthy elements in a 0-dimensional ndar
 	var actual;
 	var x;
 
-	x = ndarray( 'float64', toAccessorArray( new Float64Array( [ 0.0 ] ) ), [], [ 0 ], 0, 'row-major' );
+	x = ndarray( 'generic', toAccessorArray( new Float64Array( [ 0.0 ] ) ), [], [ 0 ], 0, 'row-major' );
 
 	actual = countTruthy( [ x ] );
 	t.strictEqual( actual, 0, 'returns expected value' );
 
-	x = ndarray( 'float64', toAccessorArray( new Float64Array( [ 1.0 ] ) ), [], [ 0 ], 0, 'row-major' );
+	x = ndarray( 'generic', toAccessorArray( new Float64Array( [ 1.0 ] ) ), [], [ 0 ], 0, 'row-major' );
 
 	actual = countTruthy( [ x ] );
 	t.strictEqual( actual, 1, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.10d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.10d.js
new file mode 100644
index 000000000000..2c042a9810b6
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.10d.js
@@ -0,0 +1,2916 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-bsize*4,
+		bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		bsize*8,
+		-bsize*8,
+		bsize*16,
+		-bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		4,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16,
+		bsize*16
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		bsize*4,
+		bsize*4,
+		-bsize*8,
+		bsize*8,
+		-bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		4,
+		-bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		4,
+		-bsize*8,
+		bsize*8,
+		-bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-bsize*4,
+		-bsize*4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-bsize*8,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1, 1 ];
+	st = [
+		2,
+		-4,
+		-4,
+		4,
+		bsize*8,
+		bsize*8,
+		bsize*16,
+		bsize*32,
+		bsize*32,
+		bsize*32
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 10-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.1d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.1d.js
new file mode 100644
index 000000000000..270f68868882
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.1d.js
@@ -0,0 +1,88 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 1-dimensional ndarray', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', zeros( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( 'float64', ones( 8, 'float64' ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 1-dimensional ndarray (accessors)', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'generic', toAccessorArray( zeros( 8, 'generic' ) ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( 'generic', toAccessorArray( ones( 8, 'generic' ) ), [ 4 ], [ 2 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 1-dimensional ndarray (complex)', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'complex128', zeros( 6, 'complex128' ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( 'complex128', ones( 6, 'complex128' ), [ 4 ], [ 1 ], 1, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.2d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.2d.js
new file mode 100644
index 000000000000..1b653c379b2f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.2d.js
@@ -0,0 +1,1197 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2 ];
+	st = [ 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 4, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ 2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -2, bsize*2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ 2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -1, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ 2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2 ];
+	st = [ -2, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2 ];
+	st = [ -2, bsize*2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 2-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2 ];
+	st = [ 2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.3d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.3d.js
new file mode 100644
index 000000000000..9827746ceb55
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.3d.js
@@ -0,0 +1,1383 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ bsize*8, bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -4, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ -bsize*8, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -3, -2, 1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2 ];
+	st = [ bsize*8, bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 4, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -1, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2 ];
+	st = [ 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ 2, -2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, -2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ 2, -2, bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2, 2 ];
+	st = [ -1, -2, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 2, 4, 4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2 ];
+	st = [ 1, -2, -3 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2 ];
+	st = [ -2, -2, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 3-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2 ];
+	st = [ 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.4d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.4d.js
new file mode 100644
index 000000000000..0aed5ba1069c
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.4d.js
@@ -0,0 +1,1569 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, bsize*4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, bsize*4, -bsize*4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ -bsize*4, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 4, -4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ -4, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 2, 1 ];
+	st = [ -bsize*8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ bsize*4, bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ 2, 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ 2, -2, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 1, 2 ];
+	st = [ 2, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, -4, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 8, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1 ];
+	st = [ 1, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1 ];
+	st = [ 2, 4, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2 ];
+	st = [ -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, 4, 4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 8, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, bsize*2 ];
+	st = [ 2, 2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, bsize*2, 1 ];
+	st = [ 2, 2, -4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, bsize*2, 1, 2 ];
+	st = [ 2, 2, -bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 4-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, -bsize*4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*4, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.5d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.5d.js
new file mode 100644
index 000000000000..e31c925a18cc
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.5d.js
@@ -0,0 +1,1755 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 2, 1, 2, 2 ];
+	st = [ -8, -4, -4, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1 ];
+	st = [ bsize*8, bsize*8, -bsize*4, -2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 8, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ 8, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -bsize*8, -4, 4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 2, 1, 2, 2 ];
+	st = [ -1, -2, -4, -4, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2 ];
+	st = [ -2, 4, -bsize*8, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, 4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ -2, 4, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 2, 1, 1 ];
+	st = [ -2, 4, -bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, -4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, 4, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2 ];
+	st = [ -2, bsize*4, -bsize*4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 2, 1, 1 ];
+	st = [ -2, 4, -bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2 ];
+	st = [ -2, 4, -4, bsize*8, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2 ];
+	st = [ -2, -4, -4, 4, bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 5-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, 4, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.6d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.6d.js
new file mode 100644
index 000000000000..a70386ada3d7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.6d.js
@@ -0,0 +1,1941 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ bsize*8, -4, -4, 4, 4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ -bsize*8, -4, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 8, -4, -4, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 8, -8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ -bsize*8, -4, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ bsize*8, bsize*8, -4, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 1, bsize*2, 2 ];
+	st = [ bsize*8, -bsize*8, -bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ bsize*8, -bsize*8, -bsize*4, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, -2, 2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ -1, -1, -1, -2, -4, -4 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 1, 2 ];
+	st = [ 2, 4, bsize*8, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 1, 2 ];
+	st = [ 2, 4, 4, -bsize*8, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2 ];
+	st = [ 2, 4, 4, -4, bsize*8, -bsize*8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, bsize*2, 1 ];
+	st = [ 2, 4, 4, -4, 8, -bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 6-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, 4, 4, -8, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*8, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.7d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.7d.js
new file mode 100644
index 000000000000..917a0979a3ca
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.7d.js
@@ -0,0 +1,2127 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -16, 16, -16, -8, -4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, -2, 2, -4, 8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -4, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 7-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.8d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.8d.js
new file mode 100644
index 000000000000..936b84a45819
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.8d.js
@@ -0,0 +1,2340 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [ bsize*16, bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an 8-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.9d.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.9d.js
new file mode 100644
index 000000000000..d254a058f5cc
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.9d.js
@@ -0,0 +1,2569 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var blockSize = require( '@stdlib/ndarray/base/nullary-tiling-block-size' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -8, 8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, bsize*8, bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		-bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -8, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, bsize*16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*16, -bsize*8, bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 16, -16, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ -bsize*16, -8, 8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -8, 8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, bsize*2, 1, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, 4, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, -bsize*8, -bsize*8, -4, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, 2, 1, bsize*2, 2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*16, bsize*8, -bsize*8, 4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ bsize*16, -bsize*16, bsize*8, bsize*8, -bsize*4, bsize*4, 2, 2, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, bsize*2, 1 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		2,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (row-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+
+	bsize = blockSize( dt );
+	sh = [ 1, 2, 1, 2, 1, 2, 1, 1, bsize*2 ];
+	st = [
+		bsize*16,
+		bsize*16,
+		-bsize*16,
+		bsize*8,
+		bsize*8,
+		-bsize*4,
+		bsize*4,
+		bsize*4,
+		2
+	];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -bsize*4, bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 2, 1, 2, 1, 1, 1 ];
+	st = [ 2, -4, bsize*8, -bsize*8, bsize*16, -bsize*16, bsize*32, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, bsize*4, bsize*4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, 4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, 4, -bsize*8, bsize*8, -bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, complex)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh )*2, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ bsize*2, 1, 2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -bsize*4, -bsize*4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, bsize*2, 1, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -bsize*8, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, bsize*2, 1, 2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, bsize*8, bsize*8, bsize*16, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 1, bsize*2, 1, 2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 4, bsize*8, bsize*8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, bsize*2, 1, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, bsize*16, bsize*16, bsize*16, bsize*16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 1, bsize*2, 2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 8, bsize*16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, bsize*2, 1, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, bsize*32, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, bsize*2, 1 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, bsize*32 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in a 9-dimensional ndarray (column-major, non-contiguous, large arrays, accessors)', function test( t ) {
+	var actual;
+	var bsize;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+
+	bsize = blockSize( dt );
+	sh = [ 2, 1, 2, 1, 2, 1, 1, 1, bsize*2 ];
+	st = [ 2, -4, -4, 8, 8, 16, 16, 16, 16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh )*2, dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, bsize*16, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.js
index 5ed366f4bb19..6ec89dce1050 100644
--- a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.js
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.js
@@ -21,6 +21,8 @@
 // MODULES //
 
 var tape = require( 'tape' );
+var ones = require( '@stdlib/array/ones' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
 var countTruthy = require( './../lib' );
 
 
@@ -31,3 +33,15 @@ tape( 'main export is a function', function test( t ) {
 	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
 	t.end();
 });
+
+tape( 'the function returns `0` if the input is an empty ndarray', function test( t ) {
+	var actual;
+	var x;
+
+	x = ndarray( 'float64', ones( 8, 'float64' ), [ 0 ], [ 1 ], 0, 'row-major' );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.nd.js b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.nd.js
new file mode 100644
index 000000000000..64457cff015d
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/base/count-truthy/test/test.nd.js
@@ -0,0 +1,824 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var toAccessorArray = require( '@stdlib/array/base/to-accessor-array' );
+var zeros = require( '@stdlib/array/zeros' );
+var ones = require( '@stdlib/array/ones' );
+var numel = require( '@stdlib/ndarray/base/numel' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var strides2offset = require( '@stdlib/ndarray/base/strides2offset' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var countTruthy = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof countTruthy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 4, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ -8, -8, -8, -8, -8, -8, -8, -4, -2, -2, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, -16, 8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 16, -16, -8, -4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 2, 1, 2, 1, 2, 1, 2, 1 ];
+	st = [ -8, -8, -8, -8, -8, -4, -4, -2, -2, -1, -1 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, 16, 16, 16, 8, 4, 4, 2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (row-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'row-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 16, 16, 16, 16, -16, 16, -16, 8, -4, -2, -2 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, singleton dimensions)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, singleton dimensions, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 4 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous, negative strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'float64';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, -2, 2, -2, 4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous, negative strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -8, -8, -8, -8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( numel( sh ), dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides, complex)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'complex128';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, -2, -2, -4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, zeros( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, ones( 16, dt ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = shape2strides( sh, ord );
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, contiguous, negative strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 2, 1, 2, 1, 2, 1, 2, 1, 1, 1, 1 ];
+	st = [ -1, -2, -2, -4, -4, -8, -8, -16, -16, -16, -16 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( numel( sh ), dt ) ), sh, st, o, ord ); // eslint-disable-line max-len
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 16, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, same sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 1 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, 2, 4, 8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 4, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function counts the number of truthy elements in an n-dimensional ndarray (column-major, non-contiguous, mixed sign strides, accessors)', function test( t ) {
+	var actual;
+	var ord;
+	var sh;
+	var st;
+	var dt;
+	var o;
+	var x;
+
+	dt = 'generic';
+	ord = 'column-major';
+	sh = [ 1, 1, 1, 1, 1, 1, 1, 2, 2, 1, 2 ];
+	st = [ 2, 2, 2, 2, 2, 2, 2, -2, -4, -8, 8 ];
+	o = strides2offset( sh, st );
+
+	x = ndarray( dt, toAccessorArray( zeros( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 0, 'returns expected value' );
+
+	x = ndarray( dt, toAccessorArray( ones( 16, dt ) ), sh, st, o, ord );
+
+	actual = countTruthy( [ x ] );
+	t.strictEqual( actual, 8, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.1d.js
index d091e336b263..9f7a131506df 100644
--- a/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.1d.js
@@ -127,7 +127,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.2d.js
index 8a45a9f1b45c..c377747c4eb5 100644
--- a/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-falsy/benchmark/benchmark.2d.js
@@ -131,17 +131,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.1d.js
index f6b7929389f3..ff5f8c3bb171 100644
--- a/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.1d.js
@@ -131,7 +131,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.2d.js
index 8e2be458465e..0e564e744453 100644
--- a/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-if/benchmark/benchmark.2d.js
@@ -135,17 +135,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.1d.js
index 7b440b8f3bb5..aec5c7e04005 100644
--- a/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.1d.js
@@ -127,7 +127,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.2d.js
index 3677a259c8c3..78f39a009fa8 100644
--- a/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/count-truthy/benchmark/benchmark.2d.js
@@ -131,17 +131,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.1d.js
index a8557aaf5ff9..da3da51d45c5 100644
--- a/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.1d.js
@@ -127,7 +127,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.2d.js
index b349813cafae..e5740ada0e7f 100644
--- a/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/every/benchmark/benchmark.2d.js
@@ -131,17 +131,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.1d.js
index fae35ff1e899..a32bbd0c36a1 100644
--- a/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.1d.js
@@ -142,7 +142,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.2d.js
index 3d7ddf63fa75..a140de7c0fa4 100644
--- a/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/find/benchmark/benchmark.2d.js
@@ -149,7 +149,7 @@ function main() {
 						continue;
 					}
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.1d.js
index 547eaed8285b..3b4723e95024 100644
--- a/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.1d.js
@@ -127,7 +127,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.2d.js
index 5a5bc37eac21..438cc4766091 100644
--- a/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/includes/benchmark/benchmark.2d.js
@@ -131,17 +131,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/some-by/README.md b/lib/node_modules/@stdlib/ndarray/some-by/README.md
index 0aba7a07603d..6cc6eb326f50 100644
--- a/lib/node_modules/@stdlib/ndarray/some-by/README.md
+++ b/lib/node_modules/@stdlib/ndarray/some-by/README.md
@@ -55,8 +55,8 @@ var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
 var out = someBy( x, 2, predicate );
 // returns <ndarray>
 
-console.log( out.get() );
-// => true
+var v = out.get();
+// returns true
 ```
 
 The function accepts the following arguments:
diff --git a/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.1d.js
index 7595e65130a5..7c0627a12f4e 100644
--- a/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.1d.js
+++ b/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.1d.js
@@ -131,7 +131,7 @@ function main() {
 
 					sh = [ len ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.2d.js
index 4fe00d34c721..bbf2725a97b4 100644
--- a/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.2d.js
+++ b/lib/node_modules/@stdlib/ndarray/some-by/benchmark/benchmark.2d.js
@@ -135,17 +135,17 @@ function main() {
 
 					sh = [ len/2, 2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					sh = [ 2, len/2 ];
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 
 					len = floor( sqrt( len ) );
 					sh = [ len, len ];
 					len *= len;
 					f = createBenchmark( len, sh, t1, ord, dims );
-					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',' )+']', f );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
 				}
 			}
 		}
diff --git a/lib/node_modules/@stdlib/ndarray/some-by/test/test.assign.js b/lib/node_modules/@stdlib/ndarray/some-by/test/test.assign.js
index 1cdd01aafdba..0d31697fdfa2 100644
--- a/lib/node_modules/@stdlib/ndarray/some-by/test/test.assign.js
+++ b/lib/node_modules/@stdlib/ndarray/some-by/test/test.assign.js
@@ -22,6 +22,7 @@
 
 var tape = require( 'tape' );
 var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
 var ndarray = require( '@stdlib/ndarray/ctor' );
 var empty = require( '@stdlib/ndarray/empty' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
@@ -504,7 +505,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -534,7 +535,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -564,7 +565,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -594,7 +595,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
diff --git a/lib/node_modules/@stdlib/ndarray/some-by/test/test.main.js b/lib/node_modules/@stdlib/ndarray/some-by/test/test.main.js
index a0e2c66fe972..9a165eaa3bb2 100644
--- a/lib/node_modules/@stdlib/ndarray/some-by/test/test.main.js
+++ b/lib/node_modules/@stdlib/ndarray/some-by/test/test.main.js
@@ -23,6 +23,7 @@
 var tape = require( 'tape' );
 var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
 var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
 var ndarray = require( '@stdlib/ndarray/ctor' );
 var empty = require( '@stdlib/ndarray/empty' );
 var ndarray2array = require( '@stdlib/ndarray/to-array' );
@@ -447,7 +448,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -473,7 +474,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -499,7 +500,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
@@ -525,7 +526,7 @@ tape( 'the function throws an error if provided a second argument which is an nd
 
 	values = [
 		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
-		new ndarray( 'float32', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
 	];
 
 	for ( i = 0; i < values.length; i++ ) {
diff --git a/lib/node_modules/@stdlib/ndarray/some/README.md b/lib/node_modules/@stdlib/ndarray/some/README.md
new file mode 100644
index 000000000000..78e239048160
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/README.md
@@ -0,0 +1,245 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# some
+
+> Test whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var some = require( '@stdlib/ndarray/some' );
+```
+
+#### some( x, n\[, options] )
+
+Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+// Perform reduction:
+var out = some( x, 3 );
+// returns <ndarray>
+
+var v= out.get();
+// returns true
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [`ndarray`][@stdlib/ndarray/ctor].
+-   **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **dims**: list of dimensions over which to perform a reduction.
+-   **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [`ndarray`][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.
+
+By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var opts = {
+    'dims': [ 0, 1 ]
+};
+
+// Perform reduction:
+var out = some( x, 2, opts );
+// returns <ndarray>
+
+var v = ndarray2array( out );
+// returns [ true, true ]
+```
+
+By default, the function returns an [`ndarray`][@stdlib/ndarray/ctor] having a shape matching only the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor] (i.e., the reduced dimensions are dropped). To include the reduced dimensions as singleton dimensions in the output [`ndarray`][@stdlib/ndarray/ctor], set the `keepdims` option to `true`.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var opts = {
+    'dims': [ 0, 1 ],
+    'keepdims': true
+};
+
+// Perform reduction:
+var out = some( x, 2, opts );
+// returns <ndarray>
+
+var v = ndarray2array( out );
+// returns [ [ [ true, true ] ] ]
+```
+
+#### some.assign( x, n, out\[, options] )
+
+Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy and assigns the results to an output [`ndarray`][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var empty = require( '@stdlib/ndarray/empty' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+// Create an output ndarray:
+var y = empty( [], {
+    'dtype': 'bool'
+});
+
+// Perform reduction:
+var out = some.assign( x, 3, y );
+// returns <ndarray>
+
+var bool = ( out === y );
+// returns true
+
+var v = y.get();
+// returns true
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [`ndarray`][@stdlib/ndarray/ctor].
+-   **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
+-   **out**: output [`ndarray`][@stdlib/ndarray/ctor]. The output [`ndarray`][@stdlib/ndarray/ctor] must have a shape matching the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor].
+-   **options**: function options (_optional_).
+
+The function accepts the following `options`:
+
+-   **dims**: list of dimensions over which to perform a reduction.
+
+By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+// Create an output ndarray:
+var y = empty( [ 2 ], {
+    'dtype': 'bool'
+});
+
+var opts = {
+    'dims': [ 0, 1 ]
+};
+
+// Perform reduction:
+var out = some.assign( x, 2, y, opts );
+// returns <ndarray>
+
+var bool = ( out === y );
+// returns true
+
+var v = ndarray2array( out );
+// returns [ true, true ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var fillBy = require( '@stdlib/ndarray/fill-by' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var some = require( '@stdlib/ndarray/some' );
+
+var x = zeros( [ 2, 4, 5 ], {
+    'dtype': 'float64'
+});
+x = fillBy( x, discreteUniform( 0, 10 ) );
+console.log( ndarray2array( x ) );
+
+var n = scalar2ndarray( 4, {
+    'dtype': 'int8'
+});
+var y = some( x, n );
+console.log( y.get() );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.1d.js b/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.1d.js
new file mode 100644
index 000000000000..30226722e467
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.1d.js
@@ -0,0 +1,140 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var pkg = require( './../package.json' ).name;
+var some = require( './../lib' );
+
+
+// VARIABLES //
+
+var types = [ 'float64' ];
+var orders = [ 'row-major', 'column-major' ];
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - ndarray length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - ndarray data type
+* @param {string} order - memory layout
+* @param {NonNegativeIntegerArray} dims - list of dimensions to reduce
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype, order, dims ) {
+	var x;
+
+	x = discreteUniform( len, 0, 10 );
+	x = new ndarray( xtype, x, shape, shape2strides( shape, order ), 0, order );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var opts;
+		var out;
+		var i;
+
+		opts = {
+			'dims': dims
+		};
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			out = some( x, len, opts );
+			if ( typeof out !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( !isndarrayLike( out ) ) {
+			b.fail( 'should return an ndarray' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var dims;
+	var len;
+	var min;
+	var max;
+	var ord;
+	var sh;
+	var t1;
+	var f;
+	var i;
+	var j;
+	var k;
+	var n;
+	var d;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	d = [
+		[ 0 ],
+		[]
+	];
+
+	for ( n = 0; n < d.length; n++ ) {
+		dims = d[ n ];
+		for ( k = 0; k < orders.length; k++ ) {
+			ord = orders[ k ];
+			for ( j = 0; j < types.length; j++ ) {
+				t1 = types[ j ];
+				for ( i = min; i <= max; i++ ) {
+					len = pow( 10, i );
+
+					sh = [ len ];
+					f = createBenchmark( len, sh, t1, ord, dims );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
+				}
+			}
+		}
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.2d.js b/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.2d.js
new file mode 100644
index 000000000000..4e73062106f7
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.2d.js
@@ -0,0 +1,154 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var floor = require( '@stdlib/math/base/special/floor' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var pkg = require( './../package.json' ).name;
+var some = require( './../lib' );
+
+
+// VARIABLES //
+
+var types = [ 'float64' ];
+var orders = [ 'row-major', 'column-major' ];
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - ndarray length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - ndarray data type
+* @param {string} order - memory layout
+* @param {NonNegativeIntegerArray} dims - list of dimensions to reduce
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype, order, dims ) {
+	var x;
+
+	x = discreteUniform( len, 0, 10 );
+	x = new ndarray( xtype, x, shape, shape2strides( shape, order ), 0, order );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var opts;
+		var out;
+		var i;
+
+		opts = {
+			'dims': dims
+		};
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			out = some( x, len, opts );
+			if ( typeof out !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( !isndarrayLike( out ) ) {
+			b.fail( 'should return an ndarray' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var dims;
+	var len;
+	var min;
+	var max;
+	var ord;
+	var sh;
+	var t1;
+	var f;
+	var i;
+	var j;
+	var k;
+	var n;
+	var d;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	d = [
+		[ 0, 1 ],
+		[ 0 ],
+		[ 1 ],
+		[]
+	];
+
+	for ( n = 0; n < d.length; n++ ) {
+		dims = d[ n ];
+		for ( k = 0; k < orders.length; k++ ) {
+			ord = orders[ k ];
+			for ( j = 0; j < types.length; j++ ) {
+				t1 = types[ j ];
+				for ( i = min; i <= max; i++ ) {
+					len = pow( 10, i );
+
+					sh = [ len/2, 2 ];
+					f = createBenchmark( len, sh, t1, ord, dims );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
+
+					sh = [ 2, len/2 ];
+					f = createBenchmark( len, sh, t1, ord, dims );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
+
+					len = floor( sqrt( len ) );
+					sh = [ len, len ];
+					len *= len;
+					f = createBenchmark( len, sh, t1, ord, dims );
+					bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
+				}
+			}
+		}
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/ndarray/some/docs/repl.txt b/lib/node_modules/@stdlib/ndarray/some/docs/repl.txt
new file mode 100644
index 000000000000..23a26de4734a
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/docs/repl.txt
@@ -0,0 +1,93 @@
+
+{{alias}}( x, n[, options] )
+    Tests whether at least `n` elements along one or more ndarray dimensions are
+    truthy.
+
+    Parameters
+    ----------
+    x: ndarray
+        Input ndarray.
+
+    n: ndarray|integer
+        Number of elements which must be truthy. Must be broadcast compatible
+        with the non-reduced dimensions of input ndarray. Must have an integer
+        data type.
+
+    options: Object (optional)
+        Function options.
+
+    options.dims: Array<integer> (optional)
+        List of dimensions over which to perform a reduction. If not provided,
+        the function performs a reduction over all elements in a provided input
+        ndarray.
+
+    options.keepdims: boolean (optional)
+        Boolean indicating whether the reduced dimensions should be included in
+        the returned ndarray as singleton dimensions. Default: false.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray. When performing a reduction over all elements, the
+        function returns a zero-dimensional ndarray containing the result.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 0 ], [ 3, 4 ] ] );
+    > var y = {{alias}}( x, 3 )
+    <ndarray>
+    > y.get()
+    true
+    > y = {{alias}}( x, 3, { 'keepdims': true } )
+    <ndarray>
+    > {{alias:@stdlib/ndarray/to-array}}( y )
+    [ [ true ] ]
+    > y.get( 0, 0 )
+    true
+
+
+{{alias}}.assign( x, n, y[, options] )
+    Tests whether at least `n` elements along one or more ndarray dimensions are
+    truthy and assigns the results to a provided output ndarray.
+
+    Parameters
+    ----------
+    x: ndarray
+        Input ndarray.
+
+    n: ndarray|integer
+        Number of elements which must be truthy. Must be broadcast compatible
+        with the non-reduced dimensions of input ndarray. Must have an integer
+        data type.
+
+    y: ndarray
+        Output ndarray. The output shape must match the shape of the non-reduced
+        dimensions of the input ndarray.
+
+    options: Object (optional)
+        Function options.
+
+    options.dims: Array<integer> (optional)
+        List of dimensions over which to perform a reduction. If not provided,
+        the function performs a reduction over all elements in a provided input
+        ndarray.
+
+    Returns
+    -------
+    y: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ [ 1, 0 ], [ 3, 4 ] ] );
+    > var y = {{alias:@stdlib/ndarray/from-scalar}}( false );
+    > var out = {{alias}}.assign( x, 3, y )
+    <ndarray>
+    > var bool = ( out === y )
+    true
+    > y.get()
+    true
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/ndarray/some/docs/types/index.d.ts b/lib/node_modules/@stdlib/ndarray/some/docs/types/index.d.ts
new file mode 100644
index 000000000000..71778579ea54
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/docs/types/index.d.ts
@@ -0,0 +1,206 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { ArrayLike } from '@stdlib/types/array';
+import { ndarray, boolndarray, integerndarray, typedndarray } from '@stdlib/types/ndarray';
+
+/**
+* Input array.
+*/
+type InputArray<T> = typedndarray<T>;
+
+/**
+* Base options.
+*/
+interface BaseOptions {
+	/**
+	* List of dimensions over which to perform the reduction.
+	*/
+	dims?: ArrayLike<number>;
+}
+
+/**
+* Options.
+*/
+interface Options extends BaseOptions {
+	/**
+	* Boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: `false`.
+	*/
+	keepdims?: boolean;
+}
+
+/**
+* Interface describing `some`.
+*/
+interface Some {
+	/**
+	* Tests whether at least `n` elements along one or more ndarray dimensions are truthy.
+	*
+	* @param x - input ndarray
+	* @param n - number of elements which must be truthy
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	* var ndarray = require( '@stdlib/ndarray/ctor' );
+	*
+	* // Create a data buffer:
+	* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+	*
+	* // Define the shape of the input array:
+	* var sh = [ 3, 1, 2 ];
+	*
+	* // Define the array strides:
+	* var sx = [ 4, 4, 1 ];
+	*
+	* // Define the index offset:
+	* var ox = 1;
+	*
+	* // Create an input ndarray:
+	* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+	*
+	* // Perform reduction:
+	* var out = some( x, 3 );
+	* // returns <ndarray>
+	*
+	* var v = out.get();
+	* // returns true
+	*/
+	<T = unknown>( x: InputArray<T>, n: integerndarray | number, options?: Options ): boolndarray;
+
+	/**
+	* Tests whether at least `n` elements along one or more ndarray dimensions are truthy and assigns the results to an output ndarray.
+	*
+	* @param x - input ndarray
+	* @param n - number of elements which must be truthy
+	* @param y - output ndarray
+	* @param options - function options
+	* @returns output ndarray
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	* var ndarray = require( '@stdlib/ndarray/ctor' );
+	* var empty = require( '@stdlib/ndarray/empty' );
+	*
+	* // Create a data buffer:
+	* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+	*
+	* // Define the shape of the input array:
+	* var shape = [ 3, 1, 2 ];
+	*
+	* // Define the array strides:
+	* var sx = [ 4, 4, 1 ];
+	*
+	* // Define the index offset:
+	* var ox = 1;
+	*
+	* // Create an input ndarray:
+	* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
+	*
+	* // Create an output ndarray:
+	* var y = empty( [], {
+	*     'dtype': 'bool'
+	* });
+	*
+	* // Perform reduction:
+	* var out = some.assign( x, 3, y );
+	* // returns <ndarray>
+	*
+	* var v = out.get();
+	* // returns true
+	*/
+	assign<T extends ndarray>( x: InputArray<unknown>, n: integerndarray | number, y: T, options?: BaseOptions ): T;
+}
+
+/**
+* Tests whether at least `n` elements along one or more ndarray dimensions are truthy.
+*
+* @param x - input ndarray
+* @param n - number of elements which must be truthy
+* @param options - function options
+* @returns output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform reduction:
+* var out = some( x, 3 );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var empty = require( '@stdlib/ndarray/empty' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var shape = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var y = empty( [], {
+*     'dtype': 'bool'
+* });
+*
+* // Perform reduction:
+* var out = some.assign( x, 3, y );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*/
+declare var some: Some;
+
+
+// EXPORTS //
+
+export = some;
diff --git a/lib/node_modules/@stdlib/ndarray/some/docs/types/test.ts b/lib/node_modules/@stdlib/ndarray/some/docs/types/test.ts
new file mode 100644
index 000000000000..af6b85b2a10f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/docs/types/test.ts
@@ -0,0 +1,306 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+/// <reference types="@stdlib/types"/>
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import empty = require( '@stdlib/ndarray/empty' );
+import some = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 2, 2 ] );
+	const n = zeros( [], {
+		'dtype': 'int32'
+	});
+
+	some( x, 2 ); // $ExpectType boolndarray
+	some( x, 2, { 'keepdims': true } ); // $ExpectType boolndarray
+	some( x, 2, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+
+	some( x, n ); // $ExpectType boolndarray
+	some( x, n, { 'keepdims': true } ); // $ExpectType boolndarray
+	some( x, n, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an ndarray...
+{
+	some( 5, 2 ); // $ExpectError
+	some( true, 2 ); // $ExpectError
+	some( false, 2 ); // $ExpectError
+	some( null, 2 ); // $ExpectError
+	some( undefined, 2 ); // $ExpectError
+	some( {}, 2 ); // $ExpectError
+	some( [ 1 ], 2 ); // $ExpectError
+	some( ( x: number ): number => x, 2 ); // $ExpectError
+
+	some( 5, 2, {} ); // $ExpectError
+	some( true, 2, {} ); // $ExpectError
+	some( false, 2, {} ); // $ExpectError
+	some( null, 2, {} ); // $ExpectError
+	some( undefined, 2, {} ); // $ExpectError
+	some( {}, 2, {} ); // $ExpectError
+	some( [ 1 ], 2, {} ); // $ExpectError
+	some( ( x: number ): number => x, 2, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not an ndarray or a number...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some( x, true ); // $ExpectError
+	some( x, false ); // $ExpectError
+	some( x, null ); // $ExpectError
+	some( x, undefined ); // $ExpectError
+	some( x, [] ); // $ExpectError
+	some( x, {} ); // $ExpectError
+	some( x, ( x: number ): number => x ); // $ExpectError
+
+	some( x, true, {} ); // $ExpectError
+	some( x, false, {} ); // $ExpectError
+	some( x, null, {} ); // $ExpectError
+	some( x, undefined, {} ); // $ExpectError
+	some( x, [], {} ); // $ExpectError
+	some( x, {}, {} ); // $ExpectError
+	some( x, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an options argument which is not an object...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some( x, 2, null ); // $ExpectError
+	some( x, 2, 'abc' ); // $ExpectError
+	some( x, 2, 1 ); // $ExpectError
+	some( x, 2, true ); // $ExpectError
+	some( x, 2, false ); // $ExpectError
+	some( x, 2, [] ); // $ExpectError
+	some( x, 2, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a `keepdims` option which is not a boolean...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some( x, 2, { 'keepdims': '5' } ); // $ExpectError
+	some( x, 2, { 'keepdims': 5 } ); // $ExpectError
+	some( x, 2, { 'keepdims': null } ); // $ExpectError
+	some( x, 2, { 'keepdims': [ 1 ] } ); // $ExpectError
+	some( x, 2, { 'keepdims': {} } ); // $ExpectError
+	some( x, 2, { 'keepdims': ( x: number ): number => x } ); // $ExpectError
+
+	some( x, 2, { 'keepdims': '5' } ); // $ExpectError
+	some( x, 2, { 'keepdims': 5 } ); // $ExpectError
+	some( x, 2, { 'keepdims': null } ); // $ExpectError
+	some( x, 2, { 'keepdims': [ 1 ] } ); // $ExpectError
+	some( x, 2, { 'keepdims': {} } ); // $ExpectError
+	some( x, 2, { 'keepdims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a `dims` option which is not an array of numbers...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some( x, 2, { 'dims': '5' } ); // $ExpectError
+	some( x, 2, { 'dims': 5 } ); // $ExpectError
+	some( x, 2, { 'dims': null } ); // $ExpectError
+	some( x, 2, { 'dims': true } ); // $ExpectError
+	some( x, 2, { 'dims': false } ); // $ExpectError
+	some( x, 2, { 'dims': {} } ); // $ExpectError
+	some( x, 2, { 'dims': ( x: number ): number => x } ); // $ExpectError
+
+	some( x, 2, { 'dims': '5' } ); // $ExpectError
+	some( x, 2, { 'dims': 5 } ); // $ExpectError
+	some( x, 2, { 'dims': null } ); // $ExpectError
+	some( x, 2, { 'dims': true } ); // $ExpectError
+	some( x, 2, { 'dims': false } ); // $ExpectError
+	some( x, 2, { 'dims': {} } ); // $ExpectError
+	some( x, 2, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some(); // $ExpectError
+	some( x ); // $ExpectError
+	some( x, 2, {}, {} ); // $ExpectError
+}
+
+// Attached to the function is an `assign` method which returns an ndarray...
+{
+	const x = zeros( [ 2, 2 ] );
+	const n = zeros( [], {
+		'dtype': 'int32'
+	});
+	const y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	some.assign( x, 2, y ); // $ExpectType boolndarray
+	some.assign( x, 2, y, {} ); // $ExpectType boolndarray
+	some.assign( x, 2, y, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+
+	some.assign( x, 2, y ); // $ExpectType boolndarray
+	some.assign( x, 2, y, {} ); // $ExpectType boolndarray
+	some.assign( x, 2, y, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+
+	some.assign( x, n, y ); // $ExpectType boolndarray
+	some.assign( x, n, y, {} ); // $ExpectType boolndarray
+	some.assign( x, n, y, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+
+	some.assign( x, n, y ); // $ExpectType boolndarray
+	some.assign( x, n, y, {} ); // $ExpectType boolndarray
+	some.assign( x, n, y, { 'dims': [ 0 ] } ); // $ExpectType boolndarray
+}
+
+// The compiler throws an error if the `assign` method is provided a first argument which is not an ndarray...
+{
+	const y = empty( [] );
+
+	some.assign( 5, 2, y ); // $ExpectError
+	some.assign( true, 2, y ); // $ExpectError
+	some.assign( false, 2, y ); // $ExpectError
+	some.assign( null, 2, y ); // $ExpectError
+	some.assign( undefined, 2, y ); // $ExpectError
+	some.assign( {}, 2, y ); // $ExpectError
+	some.assign( [ 1 ], 2, y ); // $ExpectError
+
+	some.assign( 5, 2, y, {} ); // $ExpectError
+	some.assign( true, 2, y, {} ); // $ExpectError
+	some.assign( false, 2, y, {} ); // $ExpectError
+	some.assign( null, 2, y, {} ); // $ExpectError
+	some.assign( undefined, 2, y, {} ); // $ExpectError
+	some.assign( {}, 2, y, {} ); // $ExpectError
+	some.assign( [ 1 ], 2, y, {} ); // $ExpectError
+	some.assign( ( x: number ): number => x, 2, y, {} ); // $ExpectError
+	some.assign( ( x: number ): number => x, 2, y, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a second argument which is not an ndarray or a number...
+{
+	const x = zeros( [ 2, 2 ] );
+	const y = empty( [] );
+
+	some.assign( x, '5', y ); // $ExpectError
+	some.assign( x, true, y ); // $ExpectError
+	some.assign( x, false, y ); // $ExpectError
+	some.assign( x, null, y ); // $ExpectError
+	some.assign( x, undefined, y ); // $ExpectError
+	some.assign( x, [], y ); // $ExpectError
+	some.assign( x, {}, y ); // $ExpectError
+	some.assign( x, ( x: number ): number => x, y ); // $ExpectError
+
+	some.assign( x, '5', y, {} ); // $ExpectError
+	some.assign( x, true, y, {} ); // $ExpectError
+	some.assign( x, false, y, {} ); // $ExpectError
+	some.assign( x, null, y, {} ); // $ExpectError
+	some.assign( x, undefined, y, {} ); // $ExpectError
+	some.assign( x, [], y, {} ); // $ExpectError
+	some.assign( x, {}, y, {} ); // $ExpectError
+	some.assign( x, ( x: number ): number => x, y, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided a third argument which is not an ndarray...
+{
+	const x = zeros( [ 2, 2 ] );
+
+	some.assign( x, 2, '5' ); // $ExpectError
+	some.assign( x, 2, 5 ); // $ExpectError
+	some.assign( x, 2, true ); // $ExpectError
+	some.assign( x, 2, false ); // $ExpectError
+	some.assign( x, 2, null ); // $ExpectError
+	some.assign( x, 2, undefined ); // $ExpectError
+	some.assign( x, 2, {} ); // $ExpectError
+	some.assign( x, 2, [ 1 ] ); // $ExpectError
+	some.assign( x, 2, ( x: number ): number => x ); // $ExpectError
+
+	some.assign( x, 2, '5', {} ); // $ExpectError
+	some.assign( x, 2, 5, {} ); // $ExpectError
+	some.assign( x, 2, true, {} ); // $ExpectError
+	some.assign( x, 2, false, {} ); // $ExpectError
+	some.assign( x, 2, null, {} ); // $ExpectError
+	some.assign( x, 2, undefined, {} ); // $ExpectError
+	some.assign( x, 2, {}, {} ); // $ExpectError
+	some.assign( x, 2, [ 1 ], {} ); // $ExpectError
+	some.assign( x, 2, ( x: number ): number => x, {} ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an options argument which is not an object...
+{
+	const x = zeros( [ 2, 2 ] );
+	const y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	some.assign( x, 2, y, '5' ); // $ExpectError
+	some.assign( x, 2, y, 5 ); // $ExpectError
+	some.assign( x, 2, y, true ); // $ExpectError
+	some.assign( x, 2, y, false ); // $ExpectError
+	some.assign( x, 2, y, null ); // $ExpectError
+	some.assign( x, 2, y, [ 1 ] ); // $ExpectError
+	some.assign( x, 2, y, ( x: number ): number => x ); // $ExpectError
+
+	some.assign( x, 2, y, '5' ); // $ExpectError
+	some.assign( x, 2, y, 5 ); // $ExpectError
+	some.assign( x, 2, y, true ); // $ExpectError
+	some.assign( x, 2, y, false ); // $ExpectError
+	some.assign( x, 2, y, null ); // $ExpectError
+	some.assign( x, 2, y, [ 1 ] ); // $ExpectError
+	some.assign( x, 2, y, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a `dims` option which is not an array of numbers...
+{
+	const x = zeros( [ 2, 2 ] );
+	const y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	some.assign( x, 2, y, { 'dims': '5' } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': 5 } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': null } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': true } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': false } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': {} } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': ( x: number ): number => x } ); // $ExpectError
+
+	some.assign( x, 2, y, { 'dims': '5' } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': 5 } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': null } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': true } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': false } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': {} } ); // $ExpectError
+	some.assign( x, 2, y, { 'dims': ( x: number ): number => x } ); // $ExpectError
+}
+
+// The compiler throws an error if the `assign` method is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 2, 2 ] );
+	const y = empty( [] );
+
+	some.assign(); // $ExpectError
+	some.assign( x ); // $ExpectError
+	some.assign( x, 2 ); // $ExpectError
+	some.assign( x, 2, y, {}, {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/ndarray/some/examples/index.js b/lib/node_modules/@stdlib/ndarray/some/examples/index.js
new file mode 100644
index 000000000000..731e0a7691a6
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/examples/index.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var fillBy = require( '@stdlib/ndarray/fill-by' );
+var zeros = require( '@stdlib/ndarray/zeros' );
+var some = require( './../lib' );
+
+var x = zeros( [ 2, 4, 5 ], {
+	'dtype': 'float64'
+});
+x = fillBy( x, discreteUniform( 0, 10 ) );
+console.log( ndarray2array( x ) );
+
+var n = scalar2ndarray( 4, {
+	'dtype': 'int8'
+});
+var y = some( x, n );
+console.log( y.get() );
diff --git a/lib/node_modules/@stdlib/ndarray/some/lib/assign.js b/lib/node_modules/@stdlib/ndarray/some/lib/assign.js
new file mode 100644
index 000000000000..45e6e929d5ef
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/lib/assign.js
@@ -0,0 +1,147 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive;
+var isIntegerDataType = require( '@stdlib/ndarray/base/assert/is-integer-data-type' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var unaryReduceSubarray = require( '@stdlib/ndarray/base/unary-reduce-subarray' );
+var ndims = require( '@stdlib/ndarray/ndims' );
+var base = require( '@stdlib/ndarray/base/some' );
+var getDtype = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' ); // note: non-base accessor is intentional due to the input arrays originating in userland
+var getOrder = require( '@stdlib/ndarray/base/order' );
+var defaults = require( '@stdlib/ndarray/defaults' );
+var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
+var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
+var objectAssign = require( '@stdlib/object/assign' );
+var zeroTo = require( '@stdlib/array/base/zero-to' );
+var format = require( '@stdlib/string/format' );
+var DEFAULTS = require( './defaults.json' );
+var validate = require( './validate.js' );
+
+
+// VARIABLES //
+
+var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
+
+
+// MAIN //
+
+/**
+* Tests whether at least `n` elements along one or more ndarray dimensions are truthy and assigns the results to an output ndarray.
+*
+* @param {ndarray} x - input ndarray
+* @param {(ndarray|integer)} n - number of elements which must be truthy
+* @param {ndarray} y - output ndarray
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {Error} second argument must be broadcast-compatible with the non-reduced dimensions of the input ndarray
+* @throws {TypeError} third argument must be an ndarray-like object
+* @throws {TypeError} options argument must be an object
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var empty = require( '@stdlib/ndarray/empty' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var shape = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var y = empty( [], {
+*     'dtype': 'bool'
+* });
+*
+* // Perform reduction:
+* var out = assign( x, 6, y );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*/
+function assign( x, n, y, options ) {
+	var opts;
+	var err;
+	var ord;
+	var N;
+	var v;
+
+	if ( !isndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+	}
+	if ( !isndarrayLike( y ) ) {
+		throw new TypeError( format( 'invalid argument. Third argument must be an ndarray-like object. Value: `%s`.', y ) );
+	}
+	N = ndims( x );
+	opts = objectAssign( {}, DEFAULTS );
+	if ( arguments.length > 3 ) {
+		err = validate( opts, N, options );
+		if ( err ) {
+			throw err;
+		}
+	}
+	// When a list of dimensions is not provided, reduce the entire input array across all dimensions...
+	if ( opts.dims === null ) {
+		opts.dims = zeroTo( N );
+	}
+	// Resolve input array meta data:
+	ord = getOrder( x );
+
+	if ( isndarrayLike( n ) ) {
+		if ( !isIntegerDataType( getDtype( n ) ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must have an integer data type. Value: `%s`.', n ) );
+		}
+		try {
+			v = maybeBroadcastArray( n, getShape( y ) );
+		} catch ( err ) { // eslint-disable-line no-unused-vars
+			throw new Error( 'invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.' );
+		}
+	} else {
+		if ( !isInteger( n ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.', n ) );
+		}
+		v = broadcastScalar( n, DEFAULT_DTYPE, getShape( y ), ord );
+	}
+	// Perform the reduction:
+	unaryReduceSubarray( base, [ x, y, v ], opts.dims ); // note: we assume that this lower-level function handles further validation of the output ndarray (e.g., expected shape, etc)
+	return y;
+}
+
+
+// EXPORTS //
+
+module.exports = assign;
diff --git a/lib/node_modules/@stdlib/ndarray/some/lib/defaults.json b/lib/node_modules/@stdlib/ndarray/some/lib/defaults.json
new file mode 100644
index 000000000000..08433b373a0e
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/lib/defaults.json
@@ -0,0 +1,4 @@
+{
+  "dims": null,
+  "keepdims": false
+}
diff --git a/lib/node_modules/@stdlib/ndarray/some/lib/index.js b/lib/node_modules/@stdlib/ndarray/some/lib/index.js
new file mode 100644
index 000000000000..04fb70a232e6
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/lib/index.js
@@ -0,0 +1,103 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Test whether at least `n` elements along one or more ndarray dimensions are truthy.
+*
+* @module @stdlib/ndarray/some
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var some = require( '@stdlib/ndarray/some' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform reduction:
+* var out = some( x, 6 );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+* var empty = require( '@stdlib/ndarray/empty' );
+* var some = require( '@stdlib/ndarray/some' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var shape = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, shape, sx, ox, 'row-major' );
+*
+* // Create an output ndarray:
+* var y = empty( [], {
+*     'dtype': 'bool'
+* });
+*
+* // Perform reduction:
+* var out = some.assign( x, 6, y );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var assign = require( './assign.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'assign', assign );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "assign": "main.assign" }
diff --git a/lib/node_modules/@stdlib/ndarray/some/lib/main.js b/lib/node_modules/@stdlib/ndarray/some/lib/main.js
new file mode 100644
index 000000000000..56147046ebc1
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/lib/main.js
@@ -0,0 +1,174 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isInteger = require( '@stdlib/assert/is-integer' ).isPrimitive;
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var isIntegerDataType = require( '@stdlib/ndarray/base/assert/is-integer-data-type' );
+var unaryReduceSubarray = require( '@stdlib/ndarray/base/unary-reduce-subarray' );
+var base = require( '@stdlib/ndarray/base/some' );
+var spreadDimensions = require( '@stdlib/ndarray/base/spread-dimensions' );
+var indicesComplement = require( '@stdlib/array/base/indices-complement' );
+var getDtype = require( '@stdlib/ndarray/dtype' );
+var getShape = require( '@stdlib/ndarray/shape' ); // note: non-base accessor is intentional due to the input array originating in userland
+var getOrder = require( '@stdlib/ndarray/base/order' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var getStrides = require( '@stdlib/ndarray/base/strides' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var defaults = require( '@stdlib/ndarray/defaults' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarrayCtor = require( '@stdlib/ndarray/base/ctor' );
+var maybeBroadcastArray = require( '@stdlib/ndarray/base/maybe-broadcast-array' );
+var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
+var reinterpretBoolean = require( '@stdlib/strided/base/reinterpret-boolean' );
+var takeIndexed = require( '@stdlib/array/base/take-indexed' );
+var zeroTo = require( '@stdlib/array/base/zero-to' );
+var objectAssign = require( '@stdlib/object/assign' );
+var format = require( '@stdlib/string/format' );
+var DEFAULTS = require( './defaults.json' );
+var validate = require( './validate.js' );
+
+
+// VARIABLES //
+
+var DEFAULT_DTYPE = defaults.get( 'dtypes.integer_index' );
+
+
+// MAIN //
+
+/**
+* Tests whether at least `n` elements along one or more ndarray dimensions are truthy.
+*
+* @param {ndarray} x - input ndarray
+* @param {(ndarray|integer)} n - number of elements which must be truthy
+* @param {Options} [options] - function options
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction
+* @param {boolean} [options.keepdims=false] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions
+* @throws {TypeError} first argument must be an ndarray-like object
+* @throws {TypeError} second argument must be an ndarray-like object or a scalar value
+* @throws {TypeError} options argument must be an object
+* @throws {RangeError} dimension indices must not exceed input ndarray bounds
+* @throws {Error} dimension indices must be unique
+* @throws {Error} must provide valid options
+* @returns {ndarray} output ndarray
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/ctor' );
+*
+* // Create a data buffer:
+* var xbuf = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+*
+* // Define the shape of the input array:
+* var sh = [ 3, 1, 2 ];
+*
+* // Define the array strides:
+* var sx = [ 4, 4, 1 ];
+*
+* // Define the index offset:
+* var ox = 1;
+*
+* // Create an input ndarray:
+* var x = new ndarray( 'float64', xbuf, sh, sx, ox, 'row-major' );
+*
+* // Perform reduction:
+* var out = some( x, 3 );
+* // returns <ndarray>
+*
+* var v = out.get();
+* // returns true
+*/
+function some( x, n, options ) {
+	var opts;
+	var view;
+	var err;
+	var idx;
+	var shx;
+	var shy;
+	var ord;
+	var N;
+	var v;
+	var y;
+
+	if ( !isndarrayLike( x ) ) {
+		throw new TypeError( format( 'invalid argument. First argument must be an ndarray-like object. Value: `%s`.', x ) );
+	}
+	shx = getShape( x );
+	N = shx.length;
+
+	opts = objectAssign( {}, DEFAULTS );
+	if ( arguments.length > 2 ) {
+		err = validate( opts, N, options );
+		if ( err ) {
+			throw err;
+		}
+	}
+	// When a list of dimensions is not provided, reduce the entire input array across all dimensions...
+	if ( opts.dims === null ) {
+		opts.dims = zeroTo( N );
+	}
+	// Resolve the list of non-reduced dimensions:
+	idx = indicesComplement( N, opts.dims );
+
+	// Resolve the output array shape:
+	shy = takeIndexed( shx, idx );
+
+	// Resolve input array meta data:
+	ord = getOrder( x );
+
+	if ( isndarrayLike( n ) ) {
+		if ( !isIntegerDataType( getDtype( n ) ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must have an integer data type. Value: `%s`.', n ) );
+		}
+		try {
+			v = maybeBroadcastArray( n, shy );
+		} catch ( err ) { // eslint-disable-line no-unused-vars
+			throw new Error( 'invalid argument. Second argument must be broadcast-compatible with the non-reduced dimensions of the input array.' );
+		}
+	} else {
+		if ( !isInteger( n ) ) {
+			throw new TypeError( format( 'invalid argument. Second argument must be an integer or an ndarray-like object. Value: `%s`.', n ) );
+		}
+		v = broadcastScalar( n, DEFAULT_DTYPE, shy, ord );
+	}
+	// Initialize an output array whose shape matches that of the non-reduced dimensions and which has the same memory layout as the input array:
+	y = empty( shy, {
+		'dtype': 'bool',
+		'order': ord
+	});
+
+	// Reinterpret the output array as an "indexed" array to ensure faster element access:
+	view = new ndarrayCtor( 'uint8', reinterpretBoolean( getData( y ), 0 ), shy, getStrides( y, false ), getOffset( y ), getOrder( y ) );
+
+	// Perform the reduction:
+	unaryReduceSubarray( base, [ x, view, v ], opts.dims );
+
+	// Check whether we need to reinsert singleton dimensions which can be useful for broadcasting the returned output array to the shape of the original input array...
+	if ( opts.keepdims ) {
+		y = spreadDimensions( N, y, idx );
+	}
+	return y;
+}
+
+
+// EXPORTS //
+
+module.exports = some;
diff --git a/lib/node_modules/@stdlib/ndarray/some/lib/validate.js b/lib/node_modules/@stdlib/ndarray/some/lib/validate.js
new file mode 100644
index 000000000000..b7985b72461f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/lib/validate.js
@@ -0,0 +1,87 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isObject = require( '@stdlib/assert/is-plain-object' );
+var hasOwnProp = require( '@stdlib/assert/has-own-property' );
+var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var isIntegerArray = require( '@stdlib/assert/is-integer-array' ).primitives;
+var isEmptyCollection = require( '@stdlib/assert/is-empty-collection' );
+var normalizeIndices = require( '@stdlib/ndarray/base/to-unique-normalized-indices' );
+var join = require( '@stdlib/array/base/join' );
+var format = require( '@stdlib/string/format' );
+
+
+// MAIN //
+
+/**
+* Validates function options.
+*
+* @private
+* @param {Object} opts - destination object
+* @param {NonNegativeInteger} ndims - number of input ndarray dimensions
+* @param {Options} options - function options
+* @param {boolean} [options.keepdims] - boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions
+* @param {IntegerArray} [options.dims] - list of dimensions over which to perform a reduction
+* @returns {(Error|null)} null or an error object
+*
+* @example
+* var opts = {};
+* var options = {
+*     'keepdims': true
+* };
+* var err = validate( opts, 3, options );
+* if ( err ) {
+*     throw err;
+* }
+*/
+function validate( opts, ndims, options ) {
+	var tmp;
+	if ( !isObject( options ) ) {
+		return new TypeError( format( 'invalid argument. Options argument must be an object. Value: `%s`.', options ) );
+	}
+	if ( hasOwnProp( options, 'keepdims' ) ) {
+		opts.keepdims = options.keepdims;
+		if ( !isBoolean( opts.keepdims ) ) {
+			return new TypeError( format( 'invalid option. `%s` option must be a boolean. Option: `%s`.', 'keepdims', opts.keepdims ) );
+		}
+	}
+	if ( hasOwnProp( options, 'dims' ) ) {
+		opts.dims = options.dims;
+		if ( !isIntegerArray( opts.dims ) && !isEmptyCollection( opts.dims ) ) {
+			return new TypeError( format( 'invalid option. `%s` option must be an array of integers. Option: `%s`.', 'dims', opts.dims ) );
+		}
+		tmp = normalizeIndices( opts.dims, ndims-1 );
+		if ( tmp === null ) {
+			return new RangeError( format( 'invalid option. `%s` option contains an out-of-bounds dimension index. Option: [%s].', 'dims', join( opts.dims, ',' ) ) );
+		}
+		if ( tmp.length !== opts.dims.length ) {
+			return new Error( format( 'invalid option. `%s` option contains duplicate indices. Option: [%s].', 'dims', join( opts.dims, ',' ) ) );
+		}
+		opts.dims = tmp;
+	}
+	return null;
+}
+
+
+// EXPORTS //
+
+module.exports = validate;
diff --git a/lib/node_modules/@stdlib/ndarray/some/package.json b/lib/node_modules/@stdlib/ndarray/some/package.json
new file mode 100644
index 000000000000..2b5c1db07db9
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/ndarray/some",
+  "version": "0.0.0",
+  "description": "Test whether at least `n` elements along one or more ndarray dimensions are truthy.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "strided",
+    "array",
+    "ndarray",
+    "some",
+    "count",
+    "search",
+    "utility",
+    "utils",
+    "truthy",
+    "reduce",
+    "reduction"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/ndarray/some/test/test.assign.js b/lib/node_modules/@stdlib/ndarray/some/test/test.assign.js
new file mode 100644
index 000000000000..bf57f3bffc7b
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/test/test.assign.js
@@ -0,0 +1,991 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var some = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof some.assign, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=scalar)', function test( t ) {
+	var values;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( value, 1, y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=ndarray)', function test( t ) {
+	var values;
+	var opts;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some.assign( value, scalar2ndarray( 1, opts ), y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=scalar, options)', function test( t ) {
+	var values;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( value, 1, y, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=ndarray, options)', function test( t ) {
+	var values;
+	var opts;
+	var y;
+	var i;
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some.assign( value, scalar2ndarray( 1, opts ), y, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer or ndarray-like object', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer or ndarray-like object (options)', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not an ndarray-like object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, 1, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a third argument which is not an ndarray-like object (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, 1, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is an ndarray with a non-integer data type', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is an ndarray with a non-integer data type (options)', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object (n=scalar)', function test( t ) {
+	var values;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, 1, y, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object (n=ndarray)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some.assign( x, scalar2ndarray( 1, opts ), y, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dims': value
+			};
+			some.assign( x, 1, y, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'dims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not broadcast-compatible with the output array', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	values = [
+		empty( [ 2, 2 ], opts ),
+		empty( [ 2, 2, 2 ], opts ),
+		empty( [ 1, 1, 1, 4 ], opts ),
+		empty( [ 3, 3, 3, 3, 3 ], opts )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not broadcast-compatible with the output array (options)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var y;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	values = [
+		empty( [ 2, 2 ], opts ),
+		empty( [ 2, 2, 2 ], opts ),
+		empty( [ 1, 1, 1, 4 ], opts ),
+		empty( [ 3, 3, 3, 3, 3 ], opts )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some.assign( x, value, y, {} );
+		};
+	}
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (row-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, 2, y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, 5, y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (row-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	actual = some.assign( x, scalar2ndarray( 2, opts ), y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, scalar2ndarray( 5, opts ), y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (column-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, 2, y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, 3, y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (column-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	actual = some.assign( x, scalar2ndarray( 2, opts ), y );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+
+	actual = some.assign( x, scalar2ndarray( 3, opts ), y );
+	expected = false;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 0.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ true, false, true, false ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ true, true ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ]
+	};
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = true;
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts = {
+		'dims': []
+	};
+	y = empty( [ 2, 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts1;
+	var opts2;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 0.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts2 = {
+		'dtype': 'int32'
+	};
+
+	opts1 = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ true, false, true, false ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ true, true ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ]
+	};
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = true;
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': []
+	};
+	y = empty( [ 2, 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ true, true, true, true ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ true, false ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ]
+	};
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts = {
+		'dims': []
+	};
+	y = empty( [ 2, 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, 1, y, opts );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts1;
+	var opts2;
+	var x;
+	var y;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts2 = {
+		'dtype': 'int32'
+	};
+
+	opts1 = {
+		'dims': [ 0 ]
+	};
+	y = empty( [ 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ true, true, true, true ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ]
+	};
+	y = empty( [ 2 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ true, false ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ]
+	};
+	y = empty( [], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = true;
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': []
+	};
+	y = empty( [ 2, 4 ], {
+		'dtype': 'bool'
+	});
+	actual = some.assign( x, scalar2ndarray( 1, opts2 ), y, opts1 );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+
+	t.strictEqual( actual, y, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/some/test/test.js b/lib/node_modules/@stdlib/ndarray/some/test/test.js
new file mode 100644
index 000000000000..c47d1fb1908f
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/test/test.js
@@ -0,0 +1,39 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isMethod = require( '@stdlib/assert/is-method' );
+var some = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof some, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is an `assign` method', function test( t ) {
+	t.strictEqual( isMethod( some, 'assign' ), true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/ndarray/some/test/test.main.js b/lib/node_modules/@stdlib/ndarray/some/test/test.main.js
new file mode 100644
index 000000000000..d22856922737
--- /dev/null
+++ b/lib/node_modules/@stdlib/ndarray/some/test/test.main.js
@@ -0,0 +1,1186 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var empty = require( '@stdlib/ndarray/empty' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var some = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof some, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=scalar)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( value, 1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=ndarray)', function test( t ) {
+	var values;
+	var opts;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some( value, scalar2ndarray( 1, opts ) );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=scalar, options)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( value, 1, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a first argument which is not an ndarray-like object (n=ndarray, options)', function test( t ) {
+	var values;
+	var opts;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some( value, scalar2ndarray( 1, opts ), {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer or ndarray-like object', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not an integer or ndarray-like object (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is an ndarray with a non-integer data type', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is an ndarray with a non-integer data type (options)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		new ndarray( 'float64', new Float64Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' ),
+		new ndarray( 'float32', new Float32Array( [ 1 ] ), [ 1 ], [ 1 ], 0, 'row-major' )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value, {} );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object (n=scalar)', function test( t ) {
+	var values;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, 1, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument which is not an object (n=ndarray)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts ), value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dims': value
+			};
+			some( x, 1, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `dims` property (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		3.14,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'dims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts2 ), opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains out-of-bounds dimensions (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 1, 3 ],
+		[ 3, 0 ],
+		[ 0, 2 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dims': value
+			};
+			some( x, 1, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains out-of-bounds dimensions (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 1, 3 ],
+		[ 3, 0 ],
+		[ 0, 2 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'dims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts2 ), opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains duplicate dimensions (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dims': value
+			};
+			some( x, 1, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains duplicate dimensions (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 0 ],
+		[ 1, 1 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'dims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts2 ), opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains more dimensions than are present in the input ndarray (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ],
+		[ 0, 1, 2, 3, 4 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'dims': value
+			};
+			some( x, 1, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with a `dims` property which contains more dimensions than are present in the input ndarray (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		[ 0, 1, 2 ],
+		[ 0, 1, 2, 3 ],
+		[ 0, 1, 2, 3, 4 ]
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), RangeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'dims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts2 ), opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `keepdims` property (n=scalar)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts = {
+				'keepdims': value
+			};
+			some( x, 1, opts );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided an options argument with an invalid `keepdims` property (n=ndarray)', function test( t ) {
+	var values;
+	var opts1;
+	var opts2;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+
+	values = [
+		'5',
+		5,
+		NaN,
+		null,
+		void 0,
+		{},
+		[],
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			opts1 = {
+				'keepdims': value
+			};
+			opts2 = {
+				'dtype': 'int32'
+			};
+			some( x, scalar2ndarray( 1, opts2 ), opts1 );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not broadcast-compatible with the non-reduced dimensions of the input array', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	values = [
+		empty( [ 2, 2 ], opts ),
+		empty( [ 2, 2, 2 ], opts ),
+		empty( [ 1, 1, 1, 4 ], opts ),
+		empty( [ 3, 3, 3, 3, 3 ], opts )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value );
+		};
+	}
+});
+
+tape( 'the function throws an error if provided a second argument which is not broadcast-compatible with the non-reduced dimensions of the input array (options)', function test( t ) {
+	var values;
+	var opts;
+	var x;
+	var i;
+
+	x = empty( [ 2, 2 ], {
+		'dtype': 'float64'
+	});
+	opts = {
+		'dtype': 'int32'
+	};
+
+	values = [
+		empty( [ 2, 2 ], opts ),
+		empty( [ 2, 2, 2 ], opts ),
+		empty( [ 1, 1, 1, 4 ], opts ),
+		empty( [ 3, 3, 3, 3, 3 ], opts )
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), Error, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			some( x, value, {} );
+		};
+	}
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (row-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+
+	actual = some( x, 2 );
+	expected = true;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	actual = some( x, 5 );
+	expected = false;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (row-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] ), [ 4 ], [ 1 ], 0, 'row-major' );
+	opts = {
+		'dtype': 'int32'
+	};
+
+	actual = some( x, scalar2ndarray( 2, opts ) );
+	expected = true;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	actual = some( x, scalar2ndarray( 5, opts ) );
+	expected = false;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (column-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+
+	actual = some( x, 2 );
+	expected = true;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	actual = some( x, 3 );
+	expected = false;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function tests whether at least `n` elements along one or more ndarray dimensions are truthy (column-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0 ] ), [ 4 ], [ 1 ], 0, 'column-major' );
+
+	opts = {
+		'dtype': 'int32'
+	};
+	actual = some( x, scalar2ndarray( 2, opts ) );
+	expected = true;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	actual = some( x, scalar2ndarray( 3, opts ) );
+	expected = false;
+
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 0.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	actual = some( x, 1, opts );
+	expected = [ true, false, true, false ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, false, true, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	actual = some( x, 1, opts );
+	expected = [ true, true ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true ], [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ]
+	};
+	actual = some( x, 1, opts );
+	expected = true;
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': []
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (row-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts1;
+	var opts2;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 0.0, 0.0 ] ), [ 2, 4 ], [ 4, 1 ], 0, 'row-major' );
+
+	opts1 = {
+		'dims': [ 0 ]
+	};
+	opts2 = {
+		'dtype': 'int32'
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ true, false, true, false ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, false, true, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ]
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ true, true ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true ], [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ]
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = true;
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.strictEqual( actual.get(), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': []
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, false, true, false ], [ true, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major, n=scalar)', function test( t ) {
+	var expected;
+	var actual;
+	var opts;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts = {
+		'dims': [ 0 ]
+	};
+	actual = some( x, 1, opts );
+	expected = [ true, true, true, true ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, true, true, true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ]
+	};
+	actual = some( x, 1, opts );
+	expected = [ true, false ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true ], [ false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ]
+	};
+	actual = some( x, 1, opts );
+	expected = true;
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [ 0, 1 ],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': []
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts = {
+		'dims': [],
+		'keepdims': true
+	};
+	actual = some( x, 1, opts );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports specifying reduction dimensions (column-major, n=ndarray)', function test( t ) {
+	var expected;
+	var actual;
+	var opts1;
+	var opts2;
+	var x;
+
+	x = new ndarray( 'float64', new Float64Array( [ 1.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0 ] ), [ 2, 4 ], [ 1, 2 ], 0, 'column-major' );
+
+	opts1 = {
+		'dims': [ 0 ]
+	};
+	opts2 = {
+		'dtype': 'int32'
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ true, true, true, true ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, true, true, true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ]
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ true, false ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 1 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true ], [ false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ]
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = true;
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( actual.get(), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [ 0, 1 ],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': []
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	opts1 = {
+		'dims': [],
+		'keepdims': true
+	};
+	actual = some( x, scalar2ndarray( 1, opts2 ), opts1 );
+	expected = [ [ true, true, true, true ], [ false, false, false, false ] ];
+	t.strictEqual( isndarrayLike( actual ), true, 'returns expected value' );
+	t.deepEqual( ndarray2array( actual ), expected, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/number/float32/base/package.json b/lib/node_modules/@stdlib/number/float32/base/package.json
index 202272711e8a..dc2c6f72708d 100644
--- a/lib/node_modules/@stdlib/number/float32/base/package.json
+++ b/lib/node_modules/@stdlib/number/float32/base/package.json
@@ -62,5 +62,10 @@
     "number",
     "32-bit",
     "ieee754"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_float32_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/number/float64/base/package.json b/lib/node_modules/@stdlib/number/float64/base/package.json
index e2832c60c4f4..8687def9b5d0 100644
--- a/lib/node_modules/@stdlib/number/float64/base/package.json
+++ b/lib/node_modules/@stdlib/number/float64/base/package.json
@@ -61,5 +61,10 @@
     "number",
     "64-bit",
     "ieee754"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_float64_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/README.md b/lib/node_modules/@stdlib/number/float64/base/to-float16/README.md
new file mode 100644
index 000000000000..cffc92c6572a
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/README.md
@@ -0,0 +1,98 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# toFloat16
+
+> Convert a [double-precision floating-point number][ieee754] to the nearest [half-precision floating-point number][half-precision-floating-point-format].
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var float64ToFloat16 = require( '@stdlib/number/float64/base/to-float16' );
+```
+
+#### float64ToFloat16( x )
+
+Converts a [double-precision floating-point number][ieee754] to the nearest [half-precision floating-point number][ieee754].
+
+```javascript
+var y = float64ToFloat16( 1.337 );
+// returns 1.3369140625
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   This function may be used as a polyfill for the ES2025 built-in [`Math.f16round`][math-f16round].
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/array/uniform' );
+var logEachMap = require( '@stdlib/console/log-each-map' );
+var float64ToFloat16 = require( '@stdlib/number/float64/base/to-float16' );
+
+// Generate an array of random numbers:
+var x = uniform( 100, 0.0, 100.0 );
+
+// Convert each double-precision floating-point number to the nearest half-precision floating-point number:
+logEachMap( 'float64: %f => float16: %f', x, float64ToFloat16 );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[ieee754]: https://en.wikipedia.org/wiki/IEEE_754-1985
+
+[half-precision-floating-point-format]: https://en.wikipedia.org/wiki/Half-precision_floating-point_format
+
+[math-f16round]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Math/f16round
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/benchmark/benchmark.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/benchmark/benchmark.js
new file mode 100644
index 000000000000..48d4bf6bb75b
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/benchmark/benchmark.js
@@ -0,0 +1,104 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var float64ToFloat16 = require( './../lib' );
+var polyfill = require( './../lib/polyfill.js' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': ( typeof Math.f16round === 'undefined' ) // eslint-disable-line stdlib/no-builtin-math
+};
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var x;
+	var y;
+	var i;
+
+	x = uniform( 100, -5.0e4, 5.0e4 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = float64ToFloat16( x[ i%x.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::polyfill', function benchmark( b ) {
+	var x;
+	var y;
+	var i;
+
+	x = uniform( 100, -5.0e4, 5.0e4 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = polyfill( x[ i%x.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::builtin', opts, function benchmark( b ) {
+	var x;
+	var y;
+	var i;
+
+	x = uniform( 100, -5.0e4, 5.0e4 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = Math.f16round( x[ i%x.length ] ); // eslint-disable-line stdlib/no-builtin-math
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/repl.txt b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/repl.txt
new file mode 100644
index 000000000000..265c97a6b182
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/repl.txt
@@ -0,0 +1,22 @@
+
+{{alias}}( x )
+    Converts a double-precision floating-point number to the nearest half-
+    precision floating-point number.
+
+    Parameters
+    ----------
+    x: number
+        Double-precision floating-point number.
+
+    Returns
+    -------
+    out: float
+        Nearest half-precision floating-point number.
+
+    Examples
+    --------
+    > var y = {{alias}}( 1.337 )
+    1.3369140625
+
+    See Also
+    --------
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/index.d.ts b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/index.d.ts
new file mode 100644
index 000000000000..d98c71169ff9
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/index.d.ts
@@ -0,0 +1,36 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Converts a double-precision floating-point number to the nearest half-precision floating-point number.
+*
+* @param x - double-precision floating-point number
+* @returns nearest half-precision floating-point number
+*
+* @example
+* var y = float64ToFloat16( 1.337 );
+* // returns 1.3369140625
+*/
+declare function float64ToFloat16( x: number ): number;
+
+
+// EXPORTS //
+
+export = float64ToFloat16;
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/test.ts b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/test.ts
new file mode 100644
index 000000000000..264b4e781add
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/docs/types/test.ts
@@ -0,0 +1,43 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import float64ToFloat16 = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	float64ToFloat16( 3.14 ); // $ExpectType number
+	float64ToFloat16( 0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a value other than a number...
+{
+	float64ToFloat16( true ); // $ExpectError
+	float64ToFloat16( false ); // $ExpectError
+	float64ToFloat16( '5' ); // $ExpectError
+	float64ToFloat16( [] ); // $ExpectError
+	float64ToFloat16( {} ); // $ExpectError
+	float64ToFloat16( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided insufficient arguments...
+{
+	float64ToFloat16(); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/examples/index.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/examples/index.js
new file mode 100644
index 000000000000..adef4ad5c290
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/examples/index.js
@@ -0,0 +1,29 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/array/uniform' );
+var logEachMap = require( '@stdlib/console/log-each-map' );
+var float64ToFloat16 = require( './../lib' );
+
+// Generate an array of random numbers:
+var x = uniform( 100, 0.0, 100.0 );
+
+// Convert each double-precision floating-point number to the nearest half-precision floating-point number:
+logEachMap( 'float64: %f => float16: %f', x, float64ToFloat16 );
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/index.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/index.js
new file mode 100644
index 000000000000..730dbe87fceb
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/index.js
@@ -0,0 +1,51 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Convert a double-precision floating-point number to the nearest half-precision floating-point number.
+*
+* @module @stdlib/number/float64/base/to-float16
+*
+* @example
+* var float64ToFloat16 = require( '@stdlib/number/float64/base/to-float16' );
+*
+* var y = float64ToFloat16( 1.337 );
+* // returns 1.3369140625
+*/
+
+// MODULES //
+
+var builtin = require( './main.js' );
+var polyfill = require( './polyfill.js' );
+
+
+// MAIN //
+
+var main;
+if ( typeof builtin === 'function' ) {
+	main = builtin;
+} else {
+	main = polyfill;
+}
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/main.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/main.js
new file mode 100644
index 000000000000..f3c3cceb750c
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/main.js
@@ -0,0 +1,28 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MAIN //
+
+var f16round = ( typeof Math.f16round === 'function' ) ? Math.f16round : null; // eslint-disable-line stdlib/no-builtin-math
+
+
+// EXPORTS //
+
+module.exports = f16round;
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/polyfill.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/polyfill.js
new file mode 100644
index 000000000000..cd6990557efe
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/lib/polyfill.js
@@ -0,0 +1,93 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isFiniteNumber = require( '@stdlib/math/base/assert/is-finite' );
+var FLOAT16_EPSILON = require( '@stdlib/constants/float16/eps' );
+var FLOAT16_MAX = require( '@stdlib/constants/float16/max' );
+var FLOAT16_MIN = require( '@stdlib/constants/float16/smallest-normal' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var abs = require( '@stdlib/math/base/special/abs' );
+
+
+// VARIABLES //
+
+var INVERSE_EPSILON = 1.0 / EPS;
+
+
+// FUNCTIONS //
+
+/**
+* Performs banker's rounding (round-half-to-even) via floating-point arithmetic.
+*
+* @private
+* @param {number} n - input value
+* @returns {number} rounded value
+*/
+function roundTiesToEven( n ) {
+	return ( n + INVERSE_EPSILON ) - INVERSE_EPSILON;
+}
+
+
+// MAIN //
+
+/**
+* Converts a double-precision floating-point number to the nearest half-precision floating-point number.
+*
+* @param {number} x - double-precision floating-point number
+* @returns {number} nearest half-precision floating-point number
+*
+* @example
+* var y = float64ToFloat16( 1.337 );
+* // returns 1.3369140625
+*/
+function float64ToFloat16( x ) {
+	var res;
+	var mod;
+	var a;
+	var s;
+
+	if ( x === 0.0 || isNaN( x ) || !isFiniteNumber( x ) ) {
+		return x;
+	}
+	if ( x < 0.0 ) {
+		s = -1.0;
+	} else {
+		s = 1.0;
+	}
+	mod = abs( x );
+	if ( mod < FLOAT16_MIN ) {
+		return s * roundTiesToEven( mod/FLOAT16_MIN/FLOAT16_EPSILON ) * FLOAT16_MIN * FLOAT16_EPSILON; // eslint-disable-line max-len
+	}
+	// Leverage Veltkamp's algorithm for splitting a number into two numbers to generate an approximation to `x` which fits in a smaller number of bits:
+	a = ( 1 + ( FLOAT16_EPSILON/EPS ) ) * mod;
+	res = a - ( a - mod );
+	if ( res > FLOAT16_MAX || isNaN( res ) ) {
+		return s * PINF;
+	}
+	return s * res;
+}
+
+
+// EXPORTS //
+
+module.exports = float64ToFloat16;
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/package.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/package.json
new file mode 100644
index 000000000000..62e9a2fa603c
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/package.json
@@ -0,0 +1,72 @@
+{
+  "name": "@stdlib/number/float64/base/to-float16",
+  "version": "0.0.0",
+  "description": "Convert a double-precision floating-point number to the nearest half-precision floating-point number.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdtypes",
+    "base",
+    "utilities",
+    "utility",
+    "utils",
+    "util",
+    "types",
+    "type",
+    "cast",
+    "convert",
+    "float64",
+    "double",
+    "dbl",
+    "float16",
+    "float",
+    "to",
+    "bits",
+    "number"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/REQUIRE b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/REQUIRE
new file mode 100644
index 000000000000..308c3be89c85
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/REQUIRE
@@ -0,0 +1,2 @@
+julia 1.5
+JSON 0.21
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_large.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_large.json
new file mode 100644
index 000000000000..90c76d6f9e75
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_large.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_normal.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_normal.json
new file mode 100644
index 000000000000..4ba9531a4dfb
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_normal.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_small.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_small.json
new file mode 100644
index 000000000000..0ad42fbbd0e1
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_small.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_subnormal.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_subnormal.json
new file mode 100644
index 000000000000..5ddf1dcdda7f
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_subnormal.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_tiny.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_tiny.json
new file mode 100644
index 000000000000..e7790540f2c1
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/negative_tiny.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_large.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_large.json
new file mode 100644
index 000000000000..7fddeabbe3af
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_large.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_normal.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_normal.json
new file mode 100644
index 000000000000..87c183bd0743
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_normal.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_small.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_small.json
new file mode 100644
index 000000000000..7e33ea173668
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_small.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_subnormal.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_subnormal.json
new file mode 100644
index 000000000000..dc4d68726942
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_subnormal.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_tiny.json b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_tiny.json
new file mode 100644
index 000000000000..97bde82880bb
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/positive_tiny.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/runner.jl b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/runner.jl
new file mode 100644
index 000000000000..7544051e983e
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/fixtures/julia/runner.jl
@@ -0,0 +1,105 @@
+#!/usr/bin/env julia
+#
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import JSON
+
+"""
+	gen( x, name )
+
+Generate fixture data and write to file.
+
+# Arguments
+
+* `x`: domain
+* `name::AbstractString`: output filename
+
+# Examples
+
+``` julia
+julia> x = range( -1000, stop = 1000, length = 2001 );
+julia> gen( x, \"data.json\" );
+```
+"""
+function gen( x, name )
+	y = zeros( length(x) );
+	for i in eachindex(x)
+		# Mimic implicit type promotion in JavaScript:
+		y[i] = convert( Float64, convert( Float16, x[i] ) );
+	end
+
+	# Store data to be written to file as a collection:
+	data = Dict([
+		("x", x),
+		("expected", y)
+	]);
+
+	# Based on the script directory, create an output filepath:
+	filepath = joinpath( dir, name );
+
+	# Write the data to the output filepath as JSON:
+	outfile = open( filepath, "w" );
+	write( outfile, JSON.json(data) );
+	write( outfile, "\n" );
+	close( outfile );
+end
+
+# Get the filename:
+file = @__FILE__;
+
+# Extract the directory in which this file resides:
+dir = dirname( file );
+
+# Positive normal values:
+x = range( 0, stop = 1001, length = 500 );
+gen( x, "positive_normal.json" );
+
+# Negative normal values:
+x = range( -1001, stop = 0, length = 500 );
+gen( x, "negative_normal.json" );
+
+# Positive small values:
+x = range( 0, stop = 1, length = 500 );
+gen( x, "positive_small.json" );
+
+# Negative small values:
+x = range( -1, stop = 0, length = 500 );
+gen( x, "negative_small.json" );
+
+# Positive tiny values:
+x = range( 1e-4, stop = 1e-3, length = 500 );
+gen( x, "positive_tiny.json" );
+
+# Negative tiny values:
+x = range( -1e-4, stop = -1e-3, length = 500 );
+gen( x, "negative_tiny.json" );
+
+# Positive subnormal values:
+x = range( 1e-7, stop = 6e-5, length = 500 );
+gen( x, "positive_subnormal.json" );
+
+# Negative subnormal values:
+x = range( -1e-7, stop = -6e-5, length = 500 );
+gen( x, "negative_subnormal.json" );
+
+# Large positive values:
+x = range( 1e3, stop = 6.5e4, length = 500 );
+gen( x, "positive_large.json" );
+
+# Large negative values:
+x = range( -1e3, stop = -6.5e4, length = 500 );
+gen( x, "negative_large.json" );
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.js
new file mode 100644
index 000000000000..ed09c81c278a
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.js
@@ -0,0 +1,260 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var proxyquire = require( 'proxyquire' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var polyfill = require( './../lib/polyfill.js' );
+var float64ToFloat16 = require( './../lib' );
+
+
+// FIXTURES //
+
+var negativeLarge = require( './fixtures/julia/negative_large.json' );
+var negativeNormal = require( './fixtures/julia/negative_normal.json' );
+var negativeSmall = require( './fixtures/julia/negative_small.json' );
+var negativeSubnormal = require( './fixtures/julia/negative_subnormal.json' );
+var negativeTiny = require( './fixtures/julia/negative_tiny.json' );
+var positiveLarge = require( './fixtures/julia/positive_large.json' );
+var positiveNormal = require( './fixtures/julia/positive_normal.json' );
+var positiveSmall = require( './fixtures/julia/positive_small.json' );
+var positiveSubnormal = require( './fixtures/julia/positive_subnormal.json' );
+var positiveTiny = require( './fixtures/julia/positive_tiny.json' );
+
+
+// NOTES //
+
+/*
+* => In many comparisons, we rely on implicit promotion of half-precision floating-point numbers to double-precision equivalents; e.g., +-infinity, NaN. This stems from comparison operators defaulting to float64 operands.
+*/
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof float64ToFloat16, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if an environment supports `Math.f16round` (ES2025+), the main export is the built-in method', function test( t ) {
+	var float64ToFloat16 = proxyquire( './../lib', {
+		'./main.js': foo
+	});
+	t.strictEqual( float64ToFloat16, foo, 'returns expected value' );
+	t.end();
+
+	function foo() {
+		// No-op...
+	}
+});
+
+tape( 'if an environment does not support `Math.f16round` (non-ES2025+), the main export is a polyfill', function test( t ) {
+	var float64ToFloat16 = proxyquire( './../lib', {
+		'./main.js': false
+	});
+	t.strictEqual( float64ToFloat16, polyfill, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `0`, the function returns `0`', function test( t ) {
+	var v = float64ToFloat16( 0.0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `-0`, the function returns `-0`', function test( t ) {
+	var v = float64ToFloat16( -0.0 );
+	t.strictEqual( isNegativeZero( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `+infinity`, the function returns `+infinity`', function test( t ) {
+	var v = float64ToFloat16( PINF );
+	t.strictEqual( v, PINF, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `-infinity`, the function returns `-infinity`', function test( t ) {
+	var v = float64ToFloat16( NINF );
+	t.strictEqual( v, NINF, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `NaN`, the function returns `NaN`', function test( t ) {
+	var v = float64ToFloat16( NaN );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+large values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveLarge.x;
+	expected = positiveLarge.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+normal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveNormal.x;
+	expected = positiveNormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+small values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveSmall.x;
+	expected = positiveSmall.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+tiny values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveTiny.x;
+	expected = positiveTiny.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+subnormal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveSubnormal.x;
+	expected = positiveSubnormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-large values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeLarge.x;
+	expected = negativeLarge.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-normal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeNormal.x;
+	expected = negativeNormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-small values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeSmall.x;
+	expected = negativeSmall.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-tiny values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeTiny.x;
+	expected = negativeTiny.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-subnormal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeSubnormal.x;
+	expected = negativeSubnormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.polyfill.js b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.polyfill.js
new file mode 100644
index 000000000000..e310fd48a00e
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/float64/base/to-float16/test/test.polyfill.js
@@ -0,0 +1,238 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var float64ToFloat16 = require( './../lib/polyfill.js' );
+
+
+// FIXTURES //
+
+var negativeLarge = require( './fixtures/julia/negative_large.json' );
+var negativeNormal = require( './fixtures/julia/negative_normal.json' );
+var negativeSmall = require( './fixtures/julia/negative_small.json' );
+var negativeSubnormal = require( './fixtures/julia/negative_subnormal.json' );
+var negativeTiny = require( './fixtures/julia/negative_tiny.json' );
+var positiveLarge = require( './fixtures/julia/positive_large.json' );
+var positiveNormal = require( './fixtures/julia/positive_normal.json' );
+var positiveSmall = require( './fixtures/julia/positive_small.json' );
+var positiveSubnormal = require( './fixtures/julia/positive_subnormal.json' );
+var positiveTiny = require( './fixtures/julia/positive_tiny.json' );
+
+
+// NOTES //
+
+/*
+* => In many comparisons, we rely on implicit promotion of half-precision floating-point numbers to double-precision equivalents; e.g., +-infinity, NaN. This stems from comparison operators defaulting to float64 operands.
+*/
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof float64ToFloat16, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `0`, the function returns `0`', function test( t ) {
+	var v = float64ToFloat16( 0.0 );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `-0`, the function returns `-0`', function test( t ) {
+	var v = float64ToFloat16( -0.0 );
+	t.strictEqual( isNegativeZero( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `+infinity`, the function returns `+infinity`', function test( t ) {
+	var v = float64ToFloat16( PINF );
+	t.strictEqual( v, PINF, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `-infinity`, the function returns `-infinity`', function test( t ) {
+	var v = float64ToFloat16( NINF );
+	t.strictEqual( v, NINF, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `NaN`, the function returns `NaN`', function test( t ) {
+	var v = float64ToFloat16( NaN );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+large values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveLarge.x;
+	expected = positiveLarge.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+normal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveNormal.x;
+	expected = positiveNormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+small values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveSmall.x;
+	expected = positiveSmall.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+tiny values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveTiny.x;
+	expected = positiveTiny.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (+subnormal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = positiveSubnormal.x;
+	expected = positiveSubnormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-large values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeLarge.x;
+	expected = negativeLarge.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-normal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeNormal.x;
+	expected = negativeNormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-small values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeSmall.x;
+	expected = negativeSmall.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-tiny values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeTiny.x;
+	expected = negativeTiny.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function returns the nearest half-precision floating-point number (-subnormal values)', function test( t ) {
+	var expected;
+	var x;
+	var y;
+	var i;
+
+	x = negativeSubnormal.x;
+	expected = negativeSubnormal.expected;
+	for ( i = 0; i < x.length; i++ ) {
+		y = float64ToFloat16( x[ i ] );
+		t.strictEqual( y, expected[ i ], 'y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/number/int16/base/lib/index.js b/lib/node_modules/@stdlib/number/int16/base/lib/index.js
new file mode 100644
index 000000000000..4e7b02c0327c
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int16/base/lib/index.js
@@ -0,0 +1,51 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/*
+* When adding modules to the namespace, ensure that they are added in alphabetical order according to module name.
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-read-only-property' );
+
+
+// MAIN //
+
+/**
+* Top-level namespace.
+*
+* @namespace ns
+*/
+var ns = {};
+
+/**
+* @name identity
+* @memberof ns
+* @readonly
+* @type {Function}
+* @see {@link module:@stdlib/number/int16/base/identity}
+*/
+setReadOnly( ns, 'identity', require( '@stdlib/number/int16/base/identity' ) );
+
+
+// EXPORTS //
+
+module.exports = ns;
diff --git a/lib/node_modules/@stdlib/number/int16/base/package.json b/lib/node_modules/@stdlib/number/int16/base/package.json
new file mode 100644
index 000000000000..31b64df7cae8
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int16/base/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/number/int16/base",
+  "version": "0.0.0",
+  "description": "Base utilities for signed 16-bit integers.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "lib/index.js",
+  "directories": {
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdtypes",
+    "types",
+    "base",
+    "namespace",
+    "ns",
+    "int16",
+    "signed",
+    "integer",
+    "int",
+    "16-bit"
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_int16_"
+    }
+  }
+}
diff --git a/lib/node_modules/@stdlib/number/int16/base/test/test.js b/lib/node_modules/@stdlib/number/int16/base/test/test.js
new file mode 100644
index 000000000000..85de573de8c2
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int16/base/test/test.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var objectKeys = require( '@stdlib/utils/keys' );
+var ns = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is an object', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof ns, 'object', 'main export is an object' );
+	t.end();
+});
+
+tape( 'the exported object contains key-value pairs', function test( t ) {
+	var keys = objectKeys( ns );
+	t.strictEqual( keys.length > 0, true, 'has keys' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/number/int32/base/package.json b/lib/node_modules/@stdlib/number/int32/base/package.json
index d1334e7a8a13..df4021de8203 100644
--- a/lib/node_modules/@stdlib/number/int32/base/package.json
+++ b/lib/node_modules/@stdlib/number/int32/base/package.json
@@ -59,5 +59,10 @@
     "integer",
     "int",
     "32-bit"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_int32_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/number/int8/base/lib/index.js b/lib/node_modules/@stdlib/number/int8/base/lib/index.js
new file mode 100644
index 000000000000..afdbdd4ee779
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int8/base/lib/index.js
@@ -0,0 +1,51 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/*
+* When adding modules to the namespace, ensure that they are added in alphabetical order according to module name.
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-read-only-property' );
+
+
+// MAIN //
+
+/**
+* Top-level namespace.
+*
+* @namespace ns
+*/
+var ns = {};
+
+/**
+* @name identity
+* @memberof ns
+* @readonly
+* @type {Function}
+* @see {@link module:@stdlib/number/int8/base/identity}
+*/
+setReadOnly( ns, 'identity', require( '@stdlib/number/int8/base/identity' ) );
+
+
+// EXPORTS //
+
+module.exports = ns;
diff --git a/lib/node_modules/@stdlib/number/int8/base/package.json b/lib/node_modules/@stdlib/number/int8/base/package.json
new file mode 100644
index 000000000000..b1ca6776b7ba
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int8/base/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/number/int8/base",
+  "version": "0.0.0",
+  "description": "Base utilities for signed 8-bit integers.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "lib/index.js",
+  "directories": {
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdtypes",
+    "types",
+    "base",
+    "namespace",
+    "ns",
+    "int8",
+    "signed",
+    "integer",
+    "int",
+    "8-bit"
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_int8_"
+    }
+  }
+}
diff --git a/lib/node_modules/@stdlib/number/int8/base/test/test.js b/lib/node_modules/@stdlib/number/int8/base/test/test.js
new file mode 100644
index 000000000000..85de573de8c2
--- /dev/null
+++ b/lib/node_modules/@stdlib/number/int8/base/test/test.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var objectKeys = require( '@stdlib/utils/keys' );
+var ns = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is an object', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof ns, 'object', 'main export is an object' );
+	t.end();
+});
+
+tape( 'the exported object contains key-value pairs', function test( t ) {
+	var keys = objectKeys( ns );
+	t.strictEqual( keys.length > 0, true, 'has keys' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/number/uint16/base/package.json b/lib/node_modules/@stdlib/number/uint16/base/package.json
index 2462d6bec7f4..a034bfabae6a 100644
--- a/lib/node_modules/@stdlib/number/uint16/base/package.json
+++ b/lib/node_modules/@stdlib/number/uint16/base/package.json
@@ -59,5 +59,10 @@
     "integer",
     "int",
     "16-bit"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_uint16_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/number/uint32/base/package.json b/lib/node_modules/@stdlib/number/uint32/base/package.json
index e4fd30edd82d..401b3f4dd5f0 100644
--- a/lib/node_modules/@stdlib/number/uint32/base/package.json
+++ b/lib/node_modules/@stdlib/number/uint32/base/package.json
@@ -59,5 +59,10 @@
     "integer",
     "int",
     "32-bit"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_uint32_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/number/uint8/base/package.json b/lib/node_modules/@stdlib/number/uint8/base/package.json
index 7db588fe3443..893c962e0f33 100644
--- a/lib/node_modules/@stdlib/number/uint8/base/package.json
+++ b/lib/node_modules/@stdlib/number/uint8/base/package.json
@@ -59,5 +59,10 @@
     "integer",
     "int",
     "8-bit"
-  ]
+  ],
+  "__stdlib__": {
+    "scaffold": {
+      "alias_prefix": "stdlib_base_uint8_"
+    }
+  }
 }
diff --git a/lib/node_modules/@stdlib/stats/bartlett-test/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/bartlett-test/docs/types/index.d.ts
index bbc9d1e9c474..356a11af72bb 100644
--- a/lib/node_modules/@stdlib/stats/bartlett-test/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/bartlett-test/docs/types/index.d.ts
@@ -99,7 +99,7 @@ interface Results {
 *     'b', 'b', 'b', 'b',
 *     'c', 'c', 'c', 'c', 'c'
 * ];
-* varout = bartlettTest( arr, {
+* var out = bartlettTest( arr, {
 *     'groups': groups
 * });
 * // returns {...}
diff --git a/lib/node_modules/@stdlib/stats/base/cumax/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/cumax/docs/types/index.d.ts
index 54bffaeb349d..80f11c88f528 100644
--- a/lib/node_modules/@stdlib/stats/base/cumax/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/cumax/docs/types/index.d.ts
@@ -95,7 +95,7 @@ interface Routine {
 * // y => [ 1.0, 1.0, 2.0 ]
 *
 * @example
-* var x = [ 1.0, -2.0, 2.0 ] );
+* var x = [ 1.0, -2.0, 2.0 ];
 * var y = [ 0.0, 0.0, 0.0 ];
 *
 * cumax.ndarray( x.length, x, 1, 0, y, 1, 0 );
diff --git a/lib/node_modules/@stdlib/stats/base/cumaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/cumaxabs/docs/types/index.d.ts
index fe147ddd2a12..f1cae676badd 100644
--- a/lib/node_modules/@stdlib/stats/base/cumaxabs/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/cumaxabs/docs/types/index.d.ts
@@ -95,7 +95,7 @@ interface Routine {
 * // y => [ 1.0, 2.0, 2.0 ]
 *
 * @example
-* var x = [ 1.0, -2.0, 2.0 ] );
+* var x = [ 1.0, -2.0, 2.0 ];
 * var y = [ 0.0, 0.0, 0.0 ];
 *
 * cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
diff --git a/lib/node_modules/@stdlib/stats/base/cumin/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/cumin/docs/types/index.d.ts
index 09820cdf5a93..64cdda35d55f 100644
--- a/lib/node_modules/@stdlib/stats/base/cumin/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/cumin/docs/types/index.d.ts
@@ -51,7 +51,7 @@ interface Routine {
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* cumin( x.length, x, 1, y, 1 );
-	* // y => [ 1.0, 1.0, 2.0 ]
+	* // y => [ 1.0, -2.0, -2.0 ]
 	*/
 	<T extends OutputArray>( N: number, x: InputArray, strideX: number, y: T, strideY: number ): T;
 
@@ -72,7 +72,7 @@ interface Routine {
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* cumin.ndarray( x.length, x, 1, 0, y, 1, 0 );
-	* // y => [ 1.0, 1.0, 2.0 ]
+	* // y => [ 1.0, -2.0, -2.0 ]
 	*/
 	ndarray<T extends OutputArray>( N: number, x: InputArray, strideX: number, offsetX: number, y: T, strideY: number, offsetY: number ): T;
 }
@@ -92,14 +92,14 @@ interface Routine {
 * var y = [ 0.0, 0.0, 0.0 ];
 *
 * cumin( x.length, x, 1, y, 1 );
-* // y => [ 1.0, 1.0, 2.0 ]
+* // y => [ 1.0, -2.0, -2.0 ]
 *
 * @example
-* var x = [ 1.0, -2.0, 2.0 ] );
+* var x = [ 1.0, -2.0, 2.0 ];
 * var y = [ 0.0, 0.0, 0.0 ];
 *
 * cumin.ndarray( x.length, x, 1, 0, y, 1, 0 );
-* // y => [ 1.0, 1.0, 2.0 ]
+* // y => [ 1.0, -2.0, -2.0 ]
 */
 declare var cumin: Routine;
 
diff --git a/lib/node_modules/@stdlib/stats/base/cuminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/cuminabs/docs/types/index.d.ts
index becc70e98334..87416b8d8fbf 100644
--- a/lib/node_modules/@stdlib/stats/base/cuminabs/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/cuminabs/docs/types/index.d.ts
@@ -95,7 +95,7 @@ interface Routine {
 * // y => [ 1.0, 1.0, 1.0 ]
 *
 * @example
-* var x = [ 1.0, -2.0, 2.0 ] );
+* var x = [ 1.0, -2.0, 2.0 ];
 * var y = [ 0.0, 0.0, 0.0 ];
 *
 * cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/mgf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/beta/mgf/docs/types/index.d.ts
index 817d1cda6d05..d2cb3e200bdf 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/beta/mgf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/beta/mgf/docs/types/index.d.ts
@@ -131,7 +131,7 @@ interface MGF {
 * var myMGF = mgf.factory( 0.5, 0.5 );
 *
 * y = myMGF( 0.8 );
-* // returns ~1.522
+* // returns ~1.552
 *
 * y = myMGF( 0.3 );
 * // returns ~1.168
diff --git a/lib/node_modules/@stdlib/stats/base/dists/beta/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/beta/quantile/docs/types/index.d.ts
index 657fe3b4baa3..b3fc6089afe0 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/beta/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/beta/quantile/docs/types/index.d.ts
@@ -124,7 +124,7 @@ interface Quantile {
 * // returns ~0.713
 *
 * y = myQuantile( 0.4 );
-* // returns ~0.5
+* // returns ~0.433
 */
 declare var quantile: Quantile;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/betaprime/docs/types/index.d.ts
index 2224b7ab22a9..535ceca995b1 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/docs/types/index.d.ts
@@ -130,10 +130,10 @@ interface Namespace {
 	* var mylogcdf = ns.logcdf.factory( 0.5, 0.5 );
 	*
 	* var y = mylogcdf( 0.8 );
-	* // returns ~-0.766
+	* // returns ~-0.767
 	*
 	* y = mylogcdf( 0.3 );
-	* // returns ~-1.142
+	* // returns ~-1.143
 	*/
 	logcdf: typeof logcdf;
 
@@ -155,10 +155,10 @@ interface Namespace {
 	* var mylogpdf = ns.logpdf.factory( 0.5, 0.5 );
 	*
 	* var y = mylogpdf( 0.8 );
-	* // returns ~-0.228
+	* // returns ~-1.62
 	*
 	* y = mylogpdf( 0.3 );
-	* // returns ~-0.364
+	* // returns ~-0.805
 	*/
 	logpdf: typeof logpdf;
 
@@ -295,7 +295,7 @@ interface Namespace {
 	* var myQuantile = ns.quantile.factory( 2.0, 2.0 );
 	*
 	* var y = myQuantile( 0.8 );
-	* // returns ~2.482
+	* // returns ~2.483
 	*
 	* y = myQuantile( 0.4 );
 	* // returns ~0.763
diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logcdf/docs/types/index.d.ts
index 55e1c38c692c..18d0cec18c99 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logcdf/docs/types/index.d.ts
@@ -121,10 +121,10 @@ interface LogCDF {
 * var mylogcdf = logcdf.factory( 0.5, 0.5 );
 *
 * var y = mylogcdf( 0.8 );
-* // returns ~-0.766
+* // returns ~-0.767
 *
 * y = mylogcdf( 0.3 );
-* // returns ~-1.142
+* // returns ~-1.143
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/docs/types/index.d.ts
index 32d119515be7..fea4362a6f9f 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/logpdf/docs/types/index.d.ts
@@ -121,10 +121,10 @@ interface LogPDF {
 * var mylogpdf = logpdf.factory( 0.5, 0.5 );
 *
 * var y = mylogpdf( 0.8 );
-* // returns ~-0.228
+* // returns ~-1.62
 *
 * y = mylogpdf( 0.3 );
-* // returns ~-0.364
+* // returns ~-0.805
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/betaprime/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/betaprime/quantile/docs/types/index.d.ts
index 39b41aab080a..69b2a7e674e2 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/betaprime/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/betaprime/quantile/docs/types/index.d.ts
@@ -121,7 +121,7 @@ interface Quantile {
 * var myQuantile = quantile.factory( 2.0, 2.0 );
 *
 * var y = myQuantile( 0.8 );
-* // returns ~2.482
+* // returns ~2.483
 *
 * y = myQuantile( 0.4 );
 * // returns ~0.763
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/docs/types/index.d.ts
index fb9e73f0ae37..1a60d1a66c60 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/cdf/docs/types/index.d.ts
@@ -126,7 +126,7 @@ interface CDF {
 * // returns ~0.834
 *
 * y = cdf( 0.0, 10, 0.4 );
-* // returns ~0.06
+* // returns ~0.006
 *
 * var mycdf = cdf.factory( 10, 0.5 );
 *
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/ctor/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/ctor/docs/types/index.d.ts
index d3edc6d0bbec..403dc57b0306 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/ctor/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/ctor/docs/types/index.d.ts
@@ -51,10 +51,10 @@ declare class Binomial {
 	* var binomial = new Binomial();
 	*
 	* var y = binomial.cdf( 0.8 );
-	* // returns ~0.9
+	* // returns 0.5
 	*
 	* var v = binomial.mode;
-	* // returns 0.0
+	* // returns 1.0
 	*/
 	constructor();
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts
index 807114e207e1..e5f346abe1b3 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/docs/types/index.d.ts
@@ -58,7 +58,7 @@ interface Namespace {
 	* // returns ~0.834
 	*
 	* y = ns.cdf( 0.0, 10, 0.4 );
-	* // returns ~0.06
+	* // returns ~0.006
 	*
 	* var mycdf = ns.cdf.factory( 10, 0.5 );
 	*
@@ -167,7 +167,7 @@ interface Namespace {
 	* var mylogpmf = ns.logpmf.factory( 10, 0.5 );
 	*
 	* y = mylogpmf( 3.0 );
-	* // returns ~-2.146
+	* // returns ~-2.144
 	*
 	* y = mylogpmf( 5.0 );
 	* // returns ~-1.402
@@ -320,7 +320,7 @@ interface Namespace {
 	* // returns ~0.201
 	*
 	* y = ns.pmf( 0.0, 10, 0.4 );
-	* // returns ~0.06
+	* // returns ~0.006
 	*
 	* var mypmf = ns.pmf.factory( 10, 0.5 );
 	*
@@ -342,7 +342,7 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.quantile( 0.4, 20, 0.2 );
-	* // returns 2
+	* // returns 3
 	*
 	* y = ns.quantile( 0.8, 20, 0.2 );
 	* // returns 5
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/logpmf/docs/types/index.d.ts
index 50c8ac5b4424..12494e549506 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/logpmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/logpmf/docs/types/index.d.ts
@@ -131,7 +131,7 @@ interface LogPMF {
 * var mylogpmf = logpmf.factory( 10, 0.5 );
 *
 * y = mylogpmf( 3.0 );
-* // returns ~-2.146
+* // returns ~-2.144
 *
 * y = mylogpmf( 5.0 );
 * // returns ~-1.402
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/pmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/pmf/docs/types/index.d.ts
index 0c98d8577a7c..c5d87056d3e8 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/pmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/pmf/docs/types/index.d.ts
@@ -126,7 +126,7 @@ interface PMF {
 * // returns ~0.201
 *
 * y = pmf( 0.0, 10, 0.4 );
-* // returns ~0.06
+* // returns ~0.006
 *
 * var mypmf = pmf.factory( 10, 0.5 );
 *
diff --git a/lib/node_modules/@stdlib/stats/base/dists/binomial/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/binomial/quantile/docs/types/index.d.ts
index b16e24a6c204..a073d3cb728d 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/binomial/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/binomial/quantile/docs/types/index.d.ts
@@ -126,7 +126,7 @@ interface Quantile {
 *
 * @example
 * var y = quantile( 0.4, 20, 0.2 );
-* // returns 2
+* // returns 3
 *
 * y = quantile( 0.8, 20, 0.2 );
 * // returns 5
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cauchy/docs/types/index.d.ts
index 005ef40720e0..c9c311a04e51 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/docs/types/index.d.ts
@@ -98,7 +98,7 @@ interface Namespace {
 	* var mylogcdf = ns.logcdf.factory( 1.5, 3.0 );
 	*
 	* y = mylogcdf( 1.0 );
-	* // returns ~-0.805
+	* // returns ~-0.804
 	*/
 	logcdf: typeof logcdf;
 
@@ -112,12 +112,12 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 2.0, 0.0, 1.0 );
-	* // returns ~-2.765
+	* // returns ~-2.754
 	*
 	* var mylogpdf = ns.logpdf.factory( 10.0, 2.0 );
 	*
 	* y = mylogpdf( 10.0 );
-	* // returns ~-1.839
+	* // returns ~-1.838
 	*/
 	logpdf: typeof logpdf;
 
@@ -181,9 +181,9 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.pdf( 2.0, 0.0, 1.0 );
-	* // returns ~0.063
+	* // returns ~0.064
 	*
-	* var mypdf = factory( 10.0, 2.0 );
+	* var mypdf = ns.pdf.factory( 10.0, 2.0 );
 	*
 	* y = mypdf( 10.0 );
 	* // returns ~0.159
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logcdf/docs/types/index.d.ts
index 1179be05f118..5a68e7fe265e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logcdf/docs/types/index.d.ts
@@ -102,7 +102,7 @@ interface LogCDF {
 * var mylogcdf = logcdf.factory( 1.5, 3.0 );
 *
 * y = mylogcdf( 1.0 );
-* // returns ~-0.805
+* // returns ~-0.804
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/docs/types/index.d.ts
index 56c7327e3131..a5cb239ef5de 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/logpdf/docs/types/index.d.ts
@@ -102,12 +102,12 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 0.0, 1.0 );
-* // returns ~-2.765
+* // returns ~-2.754
 *
 * var mylogpdf = logpdf.factory( 10.0, 2.0 );
 *
 * y = mylogpdf( 10.0 );
-* // returns ~-1.839
+* // returns ~-1.838
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/docs/types/index.d.ts
index c53cfecc6b7d..084cb82c8cdd 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cauchy/pdf/docs/types/index.d.ts
@@ -102,9 +102,9 @@ interface PDF {
 *
 * @example
 * var y = pdf( 2.0, 0.0, 1.0 );
-* // returns ~0.063
+* // returns ~0.064
 *
-* var mypdf = factory( 10.0, 2.0 );
+* var mypdf = pdf.factory( 10.0, 2.0 );
 *
 * y = mypdf( 10.0 );
 * // returns ~0.159
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/chi/docs/types/index.d.ts
index ac68bd7ba9b9..08004bdf5efc 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/chi/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/chi/docs/types/index.d.ts
@@ -136,7 +136,7 @@ interface Namespace {
 	* var mylogpdf = ns.logpdf.factory( 6.0 );
 	*
 	* y = mylogpdf( 3.0 );
-	* // returns ~-1.088
+	* // returns ~-1.086
 	*/
 	logpdf: typeof logpdf;
 
@@ -228,7 +228,7 @@ interface Namespace {
 	* var myquantile = ns.quantile.factory( 2.0 );
 	*
 	* var y = myquantile( 0.3 );
-	* // returns ~0.844
+	* // returns ~0.8446
 	*
 	* y = myquantile( 0.7 );
 	* // returns ~1.552
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/docs/types/index.d.ts
index 9c0a384ba627..1529bc4596ff 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/chi/logpdf/docs/types/index.d.ts
@@ -100,7 +100,7 @@ interface LogPDF {
 * var mylogpdf = logpdf.factory( 6.0 );
 *
 * y = mylogpdf( 3.0 );
-* // returns ~-1.088
+* // returns ~-1.086
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chi/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/chi/quantile/docs/types/index.d.ts
index 6dbdefe2fd1d..4922485b4d99 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/chi/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/chi/quantile/docs/types/index.d.ts
@@ -113,7 +113,7 @@ interface Quantile {
 * var myquantile = quantile.factory( 2.0 );
 *
 * var y = myquantile( 0.3 );
-* // returns ~0.844
+* // returns ~0.845
 *
 * y = myquantile( 0.7 );
 * // returns ~1.552
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/chisquare/docs/types/index.d.ts
index d9fd32dfe11e..b4d887e03be2 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/docs/types/index.d.ts
@@ -138,7 +138,7 @@ interface Namespace {
 	* var mylogpdf = ns.logpdf.factory( 6.0 );
 	*
 	* y = mylogpdf( 3.0 );
-	* // returns ~-2.071
+	* // returns ~-2.075
 	*/
 	logpdf: typeof logpdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/chisquare/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/chisquare/logpdf/docs/types/index.d.ts
index 1b811e2cdd72..8db34257f9ff 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/chisquare/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/chisquare/logpdf/docs/types/index.d.ts
@@ -100,7 +100,7 @@ interface LogPDF {
 * var mylogpdf = logpdf.factory( 6.0 );
 *
 * y = mylogpdf( 3.0 );
-* // returns ~-2.071
+* // returns ~-2.075
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cosine/docs/types/index.d.ts
index ed5c14b80499..66ef82d4c6e7 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/docs/types/index.d.ts
@@ -111,7 +111,7 @@ interface Namespace {
 	* var mylogcdf = ns.logcdf.factory( 3.0, 1.5 );
 	*
 	* y = mylogcdf( 4.0 );
-	* // returns ~--0.029
+	* // returns ~-0.029
 	*/
 	logcdf: typeof logcdf;
 
@@ -125,7 +125,7 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 2.0, 0.0, 1.0 );
-	* // returns ~-2.254
+	* // returns -Infinity
 	*
 	* var mylogpdf = ns.logpdf.factory( 10.0, 2.0 );
 	* y = mylogpdf( 10.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/types/index.d.ts
index 1c212dbfa6b6..8d32bc708a64 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logcdf/docs/types/index.d.ts
@@ -102,7 +102,7 @@ interface LogCDF {
 * var mylogcdf = logcdf.factory( 3.0, 1.5 );
 *
 * y = mylogcdf( 4.0 );
-* // returns ~--0.029
+* // returns ~-0.029
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/docs/types/index.d.ts
index 634cdc380051..dd0fe6884843 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/logpdf/docs/types/index.d.ts
@@ -105,7 +105,7 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 0.0, 1.0 );
-* // returns ~-2.254
+* // returns -Infinity
 *
 * var mylogpdf = logpdf.factory( 10.0, 2.0 );
 * y = mylogpdf( 10.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/erlang/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/erlang/docs/types/index.d.ts
index 4748cf2e6e8d..a4322d6eed49 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/erlang/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/erlang/docs/types/index.d.ts
@@ -173,7 +173,7 @@ interface Namespace {
 	*
 	* var myLogPDF = ns.logpdf.factory( 6, 7.0 );
 	* y = myLogPDF( 7.0 );
-	* // returns ~-1.864
+	* // returns ~-32.38
 	*/
 	logpdf: typeof logpdf;
 
@@ -304,8 +304,8 @@ interface Namespace {
 	* // returns ~0.895
 	*
 	* var myPDF = ns.pdf.factory( 6, 7.0 );
-	* y = myPDF( 7.0 );
-	* // returns ~0.155
+	* y = myPDF( 2.0 );
+	* // returns ~0.026
 	*/
 	pdf: typeof pdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/erlang/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/erlang/logpdf/docs/types/index.d.ts
index a954c107ede9..cdd4409c986c 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/erlang/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/erlang/logpdf/docs/types/index.d.ts
@@ -122,7 +122,7 @@ interface LogPDF {
 *
 * var myLogPDF = logpdf.factory( 6, 7.0 );
 * y = myLogPDF( 7.0 );
-* // returns ~-1.864
+* // returns ~-32.382
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/erlang/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/erlang/pdf/docs/types/index.d.ts
index a132d5b83a9a..1cc0f0924f0a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/erlang/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/erlang/pdf/docs/types/index.d.ts
@@ -122,7 +122,7 @@ interface PDF {
 *
 * var myPDF = pdf.factory( 6, 7.0 );
 * y = myPDF( 7.0 );
-* // returns ~0.155
+* // returns ~8.639e-15
 */
 declare var pdf: PDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/frechet/docs/types/index.d.ts
index 4d7431735ac2..70ff5da6e00e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/frechet/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/docs/types/index.d.ts
@@ -163,7 +163,7 @@ interface Namespace {
 	* // returns ~-0.216
 	*
 	* y = mylogcdf( 7.0 );
-	* // returns ~-3.381
+	* // returns ~-3.375
 	*/
 	logcdf: typeof logcdf;
 
@@ -318,17 +318,17 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.pdf( 10.0, 2.0, 3.0, 5.0 );
-	* // returns ~0.698
+	* // returns ~0.1
 	*
 	* y = ns.pdf( 0.0, 2.0, 3.0, 2.0 );
 	* // returns 0.0
 	*
 	* var mypdf = ns.pdf.factory( 3.0, 3.0, 5.0 );
 	* y = mypdf( 10.0 );
-	* // returns ~0.806
+	* // returns ~0.104
 	*
 	* y = mypdf( 7.0 );
-	* // returns ~0.034
+	* // returns ~0.173
 	*/
 	pdf: typeof pdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/docs/types/index.d.ts
index 4c8cbf2346c9..24b351890297 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/logcdf/docs/types/index.d.ts
@@ -122,7 +122,7 @@ interface LogCDF {
 * // returns ~-0.216
 *
 * y = mylogcdf( 7.0 );
-* // returns ~-3.381
+* // returns ~-3.375
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/frechet/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/frechet/pdf/docs/types/index.d.ts
index 2a5535179469..44a819d18032 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/frechet/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/frechet/pdf/docs/types/index.d.ts
@@ -112,17 +112,17 @@ interface PDF {
 *
 * @example
 * var y = pdf( 10.0, 2.0, 3.0, 5.0 );
-* // returns ~0.698
+* // returns ~0.1
 *
 * y = pdf( 0.0, 2.0, 3.0, 2.0 );
 * // returns 0.0
 *
 * var mypdf = pdf.factory( 3.0, 3.0, 5.0 );
 * y = mypdf( 10.0 );
-* // returns ~0.806
+* // returns ~0.104
 *
 * y = mypdf( 7.0 );
-* // returns ~0.034
+* // returns ~0.173
 */
 declare var pdf: PDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gamma/mgf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/gamma/mgf/docs/types/index.d.ts
index cbe19140c998..e1677705288a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/gamma/mgf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/gamma/mgf/docs/types/index.d.ts
@@ -124,7 +124,7 @@ interface MGF {
 * var mymgf = mgf.factory( 3.0, 1.5 );
 *
 * y = mymgf( 1.0 );
-* // returns ~26.999
+* // returns ~27.0
 *
 * y = mymgf( 0.5 );
 * // returns ~3.375
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/ctor/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/gumbel/ctor/docs/types/index.d.ts
index 27a04a8449b5..31b08858f13d 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/ctor/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/ctor/docs/types/index.d.ts
@@ -34,10 +34,10 @@ declare class Gumbel {
 	* var gumbel = new Gumbel( 0.0, 1.0 );
 	*
 	* var y = gumbel.cdf( 0.8 );
-	* // returns ~0.295
+	* // returns ~0.638
 	*
 	* var mu = gumbel.mean;
-	* // returns ~1.577
+	* // returns ~0.577
 	*/
 	constructor( mu: number, beta: number );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/gumbel/docs/types/index.d.ts
index 622e3f4636ad..77ea85221692 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/docs/types/index.d.ts
@@ -169,14 +169,14 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 2.0, 0.0, 1.0 );
-	* // returns ~-2.137
+	* // returns ~-2.135
 	*
 	* var mylogpdf = ns.logpdf.factory( 10.0, 2.0 );
 	* y = mylogpdf( 10.0 );
 	* // returns ~-1.693
 	*
 	* y = mylogpdf( 12.0 );
-	* // returns ~-2.064
+	* // returns ~-2.061
 	*/
 	logpdf: typeof logpdf;
 
@@ -256,21 +256,21 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.mgf( 0.5, 0.5, 1.0 );
-	* // returns ~1.414
+	* // returns ~2.276
 	*
 	* y = ns.mgf( 0.1, 1.0, 1.0 );
-	* // returns ~1.111
+	* // returns ~1.181
 	*
 	* y = ns.mgf( -1.0, 4.0, 2.0 );
-	* // returns ~0.198
+	* // returns ~0.037
 	*
 	* var mymgf = ns.mgf.factory( 3.0, 1.5 );
 	*
-	* y = mymgf( 1.0 );
-	* // returns ~26.999
+	* y = mymgf( 0.1 );
+	* // returns ~1.502
 	*
 	* y = mymgf( 0.5 );
-	* // returns ~3.375
+	* // returns ~16.25
 	*/
 	mgf: typeof mgf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/docs/types/index.d.ts
index 3f9d5c336866..9d804cf49e99 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/logpdf/docs/types/index.d.ts
@@ -98,14 +98,14 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 0.0, 1.0 );
-* // returns ~-2.137
+* // returns ~-2.135
 *
 * var mylogpdf = logpdf.factory( 10.0, 2.0 );
 * y = mylogpdf( 10.0 );
 * // returns ~-1.693
 *
 * y = mylogpdf( 12.0 );
-* // returns ~-2.064
+* // returns ~-2.061
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/docs/types/index.d.ts
index 16a0c25316f6..8e43195d4032 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/gumbel/mgf/docs/types/index.d.ts
@@ -102,21 +102,21 @@ interface MGF {
 *
 * @example
 * var y = mgf( 0.5, 0.5, 1.0 );
-* // returns ~1.414
+* // returns ~2.276
 *
 * y = mgf( 0.1, 1.0, 1.0 );
-* // returns ~1.111
+* // returns ~1.181
 *
 * y = mgf( -1.0, 4.0, 2.0 );
-* // returns ~0.198
+* // returns ~0.037
 *
 * var mymgf = mgf.factory( 3.0, 1.5 );
 *
-* y = mymgf( 1.0 );
-* // returns ~26.999
+* y = mymgf( 0.1 );
+* // returns ~1.502
 *
 * y = mymgf( 0.5 );
-* // returns ~3.375
+* // returns ~16.249
 */
 declare var mgf: MGF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/docs/types/index.d.ts
index 4e534feff65b..363cd354fcd6 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/docs/types/index.d.ts
@@ -150,7 +150,7 @@ interface Namespace {
 	* // returns ~-1.079
 	*
 	* y = mylogpmf( 1.0 );
-	* // returns ~-3.54
+	* // returns ~-3.524
 	*/
 	logpmf: typeof logpmf;
 
@@ -266,30 +266,24 @@ interface Namespace {
 	* @returns evaluated PMF
 	*
 	* @example
-	* var y = ns.pmf( 5.0, 20.0, 0.8 );
-	* // returns ~0.157
+	* var y = ns.pmf( 1.0, 8, 4, 2 );
+	* // returns ~0.571
 	*
-	* y = ns.pmf( 21.0, 20.0, 0.5 );
-	* // returns ~0.06
-	*
-	* y = ns.pmf( 5.0, 10.0, 0.4 );
-	* // returns ~0.016
-	*
-	* y = ns.pmf( 0.0, 10.0, 0.9 );
-	* // returns ~0.349
+	* y = ns.pmf( 2.0, 8, 4, 2 );
+	* // returns ~0.214
 	*
-	* y = ns.pmf( 21.0, 15.5, 0.5 );
-	* // returns ~0.037
+	* y = ns.pmf( 0.0, 8, 4, 2 );
+	* // returns ~0.214
 	*
-	* y = ns.pmf( 5.0, 7.4, 0.4 );
-	* // returns ~0.051
+	* y = ns.pmf( 1.5, 8, 4, 2 );
+	* // returns 0.0
 	*
-	* var mypmf = ns.pmf.factory( 10, 0.5 );
-	* y = mypmf( 3.0 );
-	* // returns ~0.027
+	* var mypmf = ns.pmf.factory( 30, 20, 5 );
+	* y = mypmf( 4.0 );
+	* // returns ~0.34
 	*
-	* y = mypmf( 5.0 );
-	* // returns ~0.061
+	* y = mypmf( 1.0 );
+	* // returns ~0.029
 	*/
 	pmf: typeof pmf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/logpmf/docs/types/index.d.ts
index 6bc95bec54d6..c9d4fd107a0f 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/logpmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/logpmf/docs/types/index.d.ts
@@ -144,7 +144,7 @@ interface LogPMF {
 * // returns ~-1.079
 *
 * y = mylogpmf( 1.0 );
-* // returns ~-3.54
+* // returns ~-3.524
 */
 declare var logpmf: LogPMF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/docs/types/index.d.ts
index c1882f318f25..33aa2ff4204c 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/hypergeometric/pmf/docs/types/index.d.ts
@@ -127,30 +127,24 @@ interface PMF {
 * @returns evaluated PMF
 *
 * @example
-* var y = pmf( 5.0, 20.0, 0.8 );
-* // returns ~0.157
+* var y = pmf( 1.0, 8, 4, 2 );
+* // returns ~0.571
 *
-* y = pmf( 21.0, 20.0, 0.5 );
-* // returns ~0.06
+* y = pmf( 2.0, 8, 4, 2 );
+* // returns ~0.214
 *
-* y = pmf( 5.0, 10.0, 0.4 );
-* // returns ~0.016
+* y = pmf( 0.0, 8, 4, 2 );
+* // returns ~0.214
 *
-* y = pmf( 0.0, 10.0, 0.9 );
-* // returns ~0.349
+* y = pmf( 1.5, 8, 4, 2 );
+* // returns 0.0
 *
-* y = pmf( 21.0, 15.5, 0.5 );
-* // returns ~0.037
+* var mypmf = pmf.factory( 30, 20, 5 );
+* y = mypmf( 4.0 );
+* // returns ~0.34
 *
-* y = pmf( 5.0, 7.4, 0.4 );
-* // returns ~0.051
-*
-* var mypmf = pmf.factory( 10, 0.5 );
-* y = mypmf( 3.0 );
-* // returns ~0.027
-*
-* y = mypmf( 5.0 );
-* // returns ~0.061
+* y = mypmf( 1.0 );
+* // returns ~0.029
 */
 declare var pmf: PMF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/invgamma/cdf/docs/types/index.d.ts
index d8c3b08e24c5..de7ce3e9a1e1 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/cdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/cdf/docs/types/index.d.ts
@@ -123,7 +123,7 @@ interface CDF {
 * // returns ~0.736
 *
 * y = mycdf( 2.0 );
-* // returns ~0.973
+* // returns ~0.974
 */
 declare var cdf: CDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/invgamma/docs/types/index.d.ts
index f77aedefb8aa..7a8dddc2c60c 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/docs/types/index.d.ts
@@ -57,7 +57,7 @@ interface Namespace {
 	* // returns ~0.736
 	*
 	* y = mycdf( 2.0 );
-	* // returns ~0.973
+	* // returns ~0.974
 	*/
 	cdf: typeof cdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/types/index.d.ts
index 7005234c8951..de8384c70cff 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/invgamma/pdf/docs/types/index.d.ts
@@ -92,7 +92,7 @@ interface PDF {
 	* // returns ~0.377
 	*
 	* y = myPDF( 4.0 );
-	* // returns ~0.067
+	* // returns ~0.005
 	*/
 	factory( alpha: number, beta: number ): Unary;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/docs/types/index.d.ts
index ea4553706f53..6b23c90f574b 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/docs/types/index.d.ts
@@ -130,7 +130,7 @@ interface Namespace {
 	* // returns ~-0.393
 	*
 	* y = mylogcdf( 0.3 );
-	* // returns ~-1.118
+	* // returns ~-1.116
 	*/
 	logcdf: typeof logcdf;
 
@@ -155,7 +155,7 @@ interface Namespace {
 	* // returns ~-0.151
 	*
 	* y = mylogpdf( 0.3 );
-	* // returns ~-0.387
+	* // returns ~-0.388
 	*/
 	logpdf: typeof logpdf;
 
@@ -326,7 +326,7 @@ interface Namespace {
 	* y = ns.quantile( 0.5, 2.0, 4.0 );
 	* // returns ~0.399
 	*
-	* var myQuantile = factory( 0.5, 0.5 );
+	* var myQuantile = ns.quantile.factory( 0.5, 0.5 );
 	*
 	* y = myQuantile( 0.8 );
 	* // returns ~0.922
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/docs/types/index.d.ts
index ab011bfee61e..b216c8bad09e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/logcdf/docs/types/index.d.ts
@@ -128,7 +128,7 @@ interface LogCDF {
 * // returns ~-0.393
 *
 * y = mylogcdf( 0.3 );
-* // returns ~-1.118
+* // returns ~-1.116
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/quantile/docs/types/index.d.ts
index 60329be999a1..7aa5063ba52d 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/kumaraswamy/quantile/docs/types/index.d.ts
@@ -123,7 +123,7 @@ interface Quantile {
 * y = quantile( 0.5, 2.0, 4.0 );
 * // returns ~0.399
 *
-* var myQuantile = factory( 0.5, 0.5 );
+* var myQuantile = quantile.factory( 0.5, 0.5 );
 *
 * y = myQuantile( 0.8 );
 * // returns ~0.922
diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/laplace/docs/types/index.d.ts
index 77979bd6b1a1..ae209a6288d7 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/laplace/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/docs/types/index.d.ts
@@ -152,7 +152,7 @@ interface Namespace {
 	*
 	* var mylogcdf = ns.logcdf.factory( 2.0, 3.0 );
 	* y = mylogcdf( 10.0 );
-	* // returns ~-0.036
+	* // returns ~-0.0354
 	*
 	* y = mylogcdf( 2.0 );
 	* // returns ~-0.693
@@ -169,11 +169,11 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 2.0, 0.0, 1.0 );
-	* // returns ~-2.688
+	* // returns ~-2.693
 	*
 	* var mylogpdf = ns.logpdf.factory( 10.0, 2.0 );
 	* y = mylogpdf( 10.0 );
-	* // returns -1.386
+	* // returns ~-1.386
 	*/
 	logpdf: typeof logpdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/laplace/logcdf/docs/types/index.d.ts
index a8cd37eda2ba..a8f53b650087 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/laplace/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/logcdf/docs/types/index.d.ts
@@ -105,7 +105,7 @@ interface LogCDF {
 *
 * var mylogcdf = logcdf.factory( 2.0, 3.0 );
 * y = mylogcdf( 10.0 );
-* // returns ~-0.036
+* // returns ~-0.035
 *
 * y = mylogcdf( 2.0 );
 * // returns ~-0.693
diff --git a/lib/node_modules/@stdlib/stats/base/dists/laplace/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/laplace/logpdf/docs/types/index.d.ts
index c633009d7129..4c8569f1e898 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/laplace/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/laplace/logpdf/docs/types/index.d.ts
@@ -105,11 +105,11 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 0.0, 1.0 );
-* // returns ~-2.688
+* // returns ~-2.693
 *
 * var mylogpdf = logpdf.factory( 10.0, 2.0 );
 * y = mylogpdf( 10.0 );
-* // returns -1.386
+* // returns ~-1.386
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/levy/docs/types/index.d.ts
index a9aa4455b99d..15afce31dc2b 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/levy/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/levy/docs/types/index.d.ts
@@ -115,7 +115,7 @@ interface Namespace {
 	* // returns ~-0.538
 	*
 	* y = ns.logcdf( 0.3, 0.0, 3.0 );
-	* // returns ~-6.215
+	* // returns ~-6.4596
 	*
 	* var mylogcdf = ns.logcdf.factory( 2.0, 3.0 );
 	* var y = mylogcdf( 100.0 );
@@ -274,7 +274,7 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.quantile( 0.8, 0.0, 1.0 );
-	* // returns ~1.386
+	* // returns ~15.58
 	*
 	* var myQuantile = ns.quantile.factory( 10.0, 2.0 );
 	*
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/levy/logcdf/docs/types/index.d.ts
index faa83c4e8959..8aed95070023 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/levy/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/levy/logcdf/docs/types/index.d.ts
@@ -105,7 +105,7 @@ interface LogCDF {
 * // returns ~-0.538
 *
 * y = logcdf( 0.3, 0.0, 3.0 );
-* // returns ~-6.215
+* // returns ~-6.4596
 *
 * var mylogcdf = logcdf.factory( 2.0, 3.0 );
 * var y = mylogcdf( 100.0 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/levy/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/levy/quantile/docs/types/index.d.ts
index 5d5d2bc59db6..608dbac57b31 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/levy/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/levy/quantile/docs/types/index.d.ts
@@ -110,7 +110,7 @@ interface Quantile {
 *
 * @example
 * var y = quantile( 0.8, 0.0, 1.0 );
-* // returns ~1.386
+* // returns ~15.58
 *
 * var myQuantile = quantile.factory( 10.0, 2.0 );
 *
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/logistic/logpdf/docs/types/index.d.ts
index 2d580a71e15b..183cb35e7e56 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/logpdf/docs/types/index.d.ts
@@ -109,7 +109,7 @@ interface LogPDF {
 *
 * var mylogpdf = logpdf.factory( 10.0, 2.0 );
 * y = mylogpdf( 10.0 );
-* // returns -2.079
+* // returns ~-2.079
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/logistic/pdf/docs/types/index.d.ts
index a1055fbab7ae..94e45134b51f 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/pdf/docs/types/index.d.ts
@@ -85,11 +85,11 @@ interface PDF {
 	* @returns PDF
 	*
 	* @example
-	* var pdf = factory( 10.0, 2.0 );
-	* var y = pdf( 10.0 );
+	* var mypdf = pdf.factory( 10.0, 2.0 );
+	* var y = mypdf( 10.0 );
 	* // returns 0.125
 	*
-	* y = pdf( 5.0 );
+	* y = mypdf( 5.0 );
 	* // returns ~0.035
 	*/
 	factory( mu: number, s: number ): Unary;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/ctor/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/ctor/docs/types/index.d.ts
index 71d15ff1d761..a234c4cb0550 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/ctor/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/ctor/docs/types/index.d.ts
@@ -43,17 +43,17 @@ declare class NegativeBinomial {
 	constructor( r: number, p: number );
 
 	/**
-	* Binomial distribution constructor.
+	* Negative binomial distribution constructor.
 	*
 	* @returns distribution instance
 	*
 	* @example
-	* var binomial = new Binomial();
+	* var nbinomial = new NegativeBinomial();
 	*
-	* var y = binomial.cdf( 0.8 );
-	* // returns ~0.9
+	* var y = nbinomial.cdf( 0.8 );
+	* // returns 0.5
 	*
-	* var v = binomial.mode;
+	* var v = nbinomial.mode;
 	* // returns 0.0
 	*/
 	constructor();
diff --git a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/docs/types/index.d.ts
index 7cabc8ef33ae..55a7e6da1458 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/docs/types/index.d.ts
@@ -130,24 +130,24 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpmf( 3.0, 20, 0.2 );
-	* // returns ~-1.583
+	* // returns ~-25.519
 	*
 	* y = ns.logpmf( 21.0, 20, 0.2 );
-	* // returns -Infinity
+	* // returns ~-11.274
 	*
 	* y = ns.logpmf( 5.0, 10, 0.4 );
-	* // returns ~-1.606
+	* // returns ~-4.115
 	*
 	* y = ns.logpmf( 0.0, 10, 0.4 );
-	* // returns ~-5.108
+	* // returns ~-9.163
 	*
 	* var mylogpmf = ns.logpmf.factory( 10, 0.5 );
 	*
 	* y = mylogpmf( 3.0 );
-	* // returns ~-2.146
+	* // returns ~-3.617
 	*
 	* y = mylogpmf( 5.0 );
-	* // returns ~-1.402
+	* // returns ~-2.795
 	*/
 	logpmf: typeof logpmf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/logpmf/docs/types/index.d.ts
index f1a0032cc29d..c4041a925abf 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/logpmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/negative-binomial/logpmf/docs/types/index.d.ts
@@ -125,24 +125,24 @@ interface LogPMF {
 *
 * @example
 * var y = logpmf( 3.0, 20, 0.2 );
-* // returns ~-1.583
+* // returns ~-25.519
 *
 * y = logpmf( 21.0, 20, 0.2 );
-* // returns -Infinity
+* // returns ~-11.274
 *
 * y = logpmf( 5.0, 10, 0.4 );
-* // returns ~-1.606
+* // returns ~-4.115
 *
 * y = logpmf( 0.0, 10, 0.4 );
-* // returns ~-5.108
+* // returns ~-9.163
 *
 * var mylogpmf = logpmf.factory( 10, 0.5 );
 *
 * y = mylogpmf( 3.0 );
-* // returns ~-2.146
+* // returns ~-3.617
 *
 * y = mylogpmf( 5.0 );
-* // returns ~-1.402
+* // returns ~-2.795
 */
 declare var logpmf: LogPMF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/index.d.ts
index aea0579cff2b..bdb1ab583c20 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/index.d.ts
@@ -21,7 +21,7 @@
 /**
 * Pareto (Type I) distribution.
 */
-declare class Pareto {
+declare class Pareto1 {
 	/**
 	* Pareto (Type I) distribution constructor.
 	*
@@ -152,4 +152,4 @@ declare class Pareto {
 
 // EXPORTS //
 
-export = Pareto;
+export = Pareto1;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/test.ts
index 2d14c88d21ba..2f9b2834260d 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/test.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/ctor/docs/types/test.ts
@@ -18,36 +18,36 @@
 
 /* eslint-disable @typescript-eslint/no-unused-expressions */
 
-import Pareto = require( './index' );
+import Pareto1 = require( './index' );
 
 
 // TESTS //
 
 // The function returns a distribution instance...
 {
-	new Pareto(); // $ExpectType Pareto
-	new Pareto( 1.0, 2.0 ); // $ExpectType Pareto
+	new Pareto1(); // $ExpectType Pareto1
+	new Pareto1( 1.0, 2.0 ); // $ExpectType Pareto1
 }
 
 // The compiler throws an error if the function is provided values other than two numbers...
 {
-	new Pareto( true, 2.0 ); // $ExpectError
-	new Pareto( false, 2.0 ); // $ExpectError
-	new Pareto( '5', 2.0 ); // $ExpectError
-	new Pareto( [], 2.0 ); // $ExpectError
-	new Pareto( {}, 2.0 ); // $ExpectError
-	new Pareto( ( x: number ): number => x, 2.0 ); // $ExpectError
-
-	new Pareto( 1.0, true ); // $ExpectError
-	new Pareto( 1.0, false ); // $ExpectError
-	new Pareto( 1.0, '5' ); // $ExpectError
-	new Pareto( 1.0, [] ); // $ExpectError
-	new Pareto( 1.0, {} ); // $ExpectError
-	new Pareto( 1.0, ( x: number ): number => x ); // $ExpectError
+	new Pareto1( true, 2.0 ); // $ExpectError
+	new Pareto1( false, 2.0 ); // $ExpectError
+	new Pareto1( '5', 2.0 ); // $ExpectError
+	new Pareto1( [], 2.0 ); // $ExpectError
+	new Pareto1( {}, 2.0 ); // $ExpectError
+	new Pareto1( ( x: number ): number => x, 2.0 ); // $ExpectError
+
+	new Pareto1( 1.0, true ); // $ExpectError
+	new Pareto1( 1.0, false ); // $ExpectError
+	new Pareto1( 1.0, '5' ); // $ExpectError
+	new Pareto1( 1.0, [] ); // $ExpectError
+	new Pareto1( 1.0, {} ); // $ExpectError
+	new Pareto1( 1.0, ( x: number ): number => x ); // $ExpectError
 }
 
 // The compiler throws an error if the function is provided an unsupported number of arguments...
 {
-	new Pareto( 1.0 ); // $ExpectError
-	new Pareto( 1.0, 1.0, 2.0 ); // $ExpectError
+	new Pareto1( 1.0 ); // $ExpectError
+	new Pareto1( 1.0, 1.0, 2.0 ); // $ExpectError
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/docs/types/index.d.ts
index 1122fc0ffafd..9b40746a6991 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/docs/types/index.d.ts
@@ -188,7 +188,7 @@ interface Namespace {
 	* // returns ~-0.017
 	*
 	* y = mylogcdf( 2.5 );
-	* // returns ~-0.113
+	* // returns ~-0.114
 	*/
 	logcdf: typeof logcdf;
 
@@ -354,7 +354,7 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.pdf( 4.0, 1.0, 1.0 );
-	* // returns ~0.044
+	* // returns 0.0625
 	*
 	* y = ns.pdf( 20.0, 1.0, 10.0 );
 	* // returns 0.025
@@ -388,7 +388,7 @@ interface Namespace {
 	* // returns ~50.0
 	*
 	* y = ns.quantile( 0.1, 1.0, 10.0 );
-	* // returns ~10.541
+	* // returns ~11.111
 	*
 	* var myquantile = ns.quantile.factory( 2.5, 0.5 );
 	* y = myquantile( 0.5 );
diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/logcdf/docs/types/index.d.ts
index eda75de40209..fee32ca4fe81 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/logcdf/docs/types/index.d.ts
@@ -131,7 +131,7 @@ interface LogCDF {
 * // returns ~-0.017
 *
 * y = mylogcdf( 2.5 );
-* // returns ~-0.113
+* // returns ~-0.114
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/pdf/docs/types/index.d.ts
index 5b04595ab502..a27339bf826a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/pareto-type1/pdf/docs/types/index.d.ts
@@ -117,7 +117,7 @@ interface PDF {
 *
 * @example
 * var y = pdf( 4.0, 1.0, 1.0 );
-* // returns ~0.044
+* // returns ~0.063
 *
 * y = pdf( 20.0, 1.0, 10.0 );
 * // returns 0.025
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/docs/types/index.d.ts
index 789bdfa4012e..fe04ce728629 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/pmf/docs/types/index.d.ts
@@ -75,12 +75,12 @@ interface PMF {
 	* @returns PMF
 	*
 	* @example
-	* var pmf = factory( 0.5 );
-	* var y = pmf( 3.0 );
-	* // returns ~0.0879
+	* var mypmf = pmf.factory( 0.5 );
+	* var y = mypmf( 3.0 );
+	* // returns ~0.0878
 	*
-	* y = pmf( 1.0 );
-	* // returns ~0.2386
+	* y = mypmf( 1.0 );
+	* // returns ~0.239
 	*/
 	factory( lambda: number ): Unary;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/poisson/docs/types/index.d.ts
index e2afcc521f63..b2f234d21b42 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/poisson/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/docs/types/index.d.ts
@@ -145,7 +145,7 @@ interface Namespace {
 	*
 	* var mylogpmf = ns.logpmf.factory( 1.0 );
 	* y = mylogpmf( 3.0 );
-	* // returns ~-2.797
+	* // returns ~-2.792
 	*
 	* y = mylogpmf( 1.0 );
 	* // returns ~-1.0
diff --git a/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/docs/types/index.d.ts
index f9be2a00f78d..9e64c5f511a9 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/poisson/logpmf/docs/types/index.d.ts
@@ -104,7 +104,7 @@ interface LogPMF {
 *
 * var mylogpmf = logpmf.factory( 1.0 );
 * y = mylogpmf( 3.0 );
-* // returns ~-2.797
+* // returns ~-2.792
 *
 * y = mylogpmf( 1.0 );
 * // returns ~-1.0
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/cdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/cdf/docs/types/index.d.ts
index 1846ca7d41ed..4366165c55a3 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/cdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/cdf/docs/types/index.d.ts
@@ -94,11 +94,11 @@ interface CDF {
 *
 * @example
 * var y = cdf( 2.0, 0.0, 1.0 );
-* // returns ~0.977
+* // returns 1.0
 *
 * var myCDF = cdf.factory( 10.0, 2.0 );
 * y = myCDF( 10.0 );
-* // returns 0.5
+* // returns ~0.393
 */
 declare var cdf: CDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/docs/types/index.d.ts
index ed6b1393bfb6..630f25d8a135 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/docs/types/index.d.ts
@@ -49,11 +49,11 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.cdf( 2.0, 0.0, 1.0 );
-	* // returns ~0.977
+	* // returns 1.0
 	*
 	* var myCDF = ns.cdf.factory( 10.0, 2.0 );
 	* y = myCDF( 10.0 );
-	* // returns 0.5
+	* // returns ~0.393
 	*/
 	cdf: typeof cdf;
 
@@ -131,14 +131,14 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logcdf( 2.0, 5.0 );
-	* // returns ~-2.564
+	* // returns ~-2.565
 	*
 	* var mylogcdf = ns.logcdf.factory( 0.5 );
 	* y = mylogcdf( 1.0 );
 	* // returns ~-0.145
 	*
 	* y = mylogcdf( 0.5 );
-	* // returns ~-0.934
+	* // returns ~-0.933
 	*/
 	logcdf: typeof logcdf;
 
@@ -151,15 +151,15 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 2.0, 4.0 );
-	* // returns ~-2.207
+	* // returns ~-2.204
 	*
 	* var mylogpdf = ns.logpdf.factory( 4.0 );
 	*
 	* y = mylogpdf( 6.0 );
-	* // returns ~-2.104
+	* // returns ~-2.106
 	*
 	* y = mylogpdf( 4.0 );
-	* // returns ~-1.884
+	* // returns ~-1.886
 	*/
 	logpdf: typeof logpdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logcdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logcdf/docs/types/index.d.ts
index f49a9d9bb34a..5a227f58eb79 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logcdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logcdf/docs/types/index.d.ts
@@ -94,14 +94,14 @@ interface LogCDF {
 *
 * @example
 * var y = logcdf( 2.0, 5.0 );
-* // returns ~-2.564
+* // returns ~-2.565
 *
 * var mylogcdf = logcdf.factory( 0.5 );
 * y = mylogcdf( 1.0 );
 * // returns ~-0.145
 *
 * y = mylogcdf( 0.5 );
-* // returns ~-0.934
+* // returns ~-0.933
 */
 declare var logcdf: LogCDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/docs/types/index.d.ts
index 2f964044c9cd..a996d0fdf268 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/logpdf/docs/types/index.d.ts
@@ -94,15 +94,15 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 4.0 );
-* // returns ~-2.207
+* // returns ~-2.204
 *
 * var mylogpdf = logpdf.factory( 4.0 );
 *
 * y = mylogpdf( 6.0 );
-* // returns ~-2.104
+* // returns ~-2.106
 *
 * y = mylogpdf( 4.0 );
-* // returns ~-1.884
+* // returns ~-1.886
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/docs/types/index.d.ts
index 9976e0b20d51..1ba10669cc67 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/studentized-range/quantile/docs/types/index.d.ts
@@ -41,15 +41,15 @@ interface Quantile {
 	*
 	* @example
 	* var y = quantile( 0.5, 3.0, 2.0 );
-	* // returns ~0.0644
+	* // returns ~1.908
 	*
 	* @example
 	* var y = quantile( 0.9, 17.0, 2.0 );
-	* // returns ~0.913
+	* // returns ~11.237
 	*
 	* @example
 	* var y = quantile( 0.5, 3.0, 2.0, 2 );
-	* // returns ~0.01
+	* // returns ~2.549
 	*/
 	( p: number, r: number, v: number, nranges?: number ): number;
 
@@ -63,14 +63,14 @@ interface Quantile {
 	* @returns quantile function
 	*
 	* @example
-	* var quantile = factory( 3.0, 3.0 );
-	* var y = quantile( 0.5 );
+	* var myquantile = quantile.factory( 3.0, 3.0 );
+	* var y = myquantile( 0.5 );
 	* // returns ~1.791
 	*
-	* y = quantile( 0.8 );
+	* y = myquantile( 0.8 );
 	* // returns ~3.245
 	*
-	* y = quantile( 1.0 );
+	* y = myquantile( 1.0 );
 	* // returns Infinity
 	*/
 	factory( r: number, v: number, nranges?: number ): Unary;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/t/docs/types/index.d.ts
index e9e4b3351de4..abf2015bf2e0 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/t/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/t/docs/types/index.d.ts
@@ -167,11 +167,11 @@ interface Namespace {
 	*
 	* @example
 	* var y = ns.logpdf( 3.0, 1.0 );
-	* // returns ~-3.442
+	* // returns ~-3.447
 	*
 	* var mylogPDF = ns.logpdf.factory( 3.0 );
 	* y = mylogPDF( 1.0 );
-	* // returns ~-1.575
+	* // returns ~-1.576
 	*/
 	logpdf: typeof logpdf;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/t/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/t/logpdf/docs/types/index.d.ts
index 671b40f466b2..bb713531ea76 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/t/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/t/logpdf/docs/types/index.d.ts
@@ -93,11 +93,11 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 3.0, 1.0 );
-* // returns ~-3.442
+* // returns ~-3.447
 *
 * var mylogPDF = logpdf.factory( 3.0 );
 * y = mylogPDF( 1.0 );
-* // returns ~-1.575
+* // returns ~-1.576
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/docs/types/index.d.ts
index ca00b172d87e..31ab8e24f224 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/docs/types/index.d.ts
@@ -42,7 +42,7 @@ interface Namespace {
 	*
 	* var mypdf = ns.pdf.factory( -1.0, 1.0, 0.0, 1.0 );
 	* y = mypdf( 0.9 );
-	* // returns ~0.5896
+	* // returns ~0.39
 	*/
 	pdf: typeof pdf;
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/docs/types/index.d.ts
index 66abfad401b9..c2bf043ad12a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/truncated-normal/pdf/docs/types/index.d.ts
@@ -72,22 +72,22 @@ interface PDF {
 	* @returns PDF
 	*
 	* @example
-	* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
+	* var myPDF = pdf.factory( 0.0, 1.0, 0.0, 1.0 );
 	* var y = myPDF( 0.8 );
 	* // returns ~0.849
 	*
 	* @example
-	* var myPDF = factory( 0.0, 1.0, 0.5, 1.0 );
+	* var myPDF = pdf.factory( 0.0, 1.0, 0.5, 1.0 );
 	* var y = myPDF( 0.8 );
 	* // returns ~0.996
 	*
 	* @example
-	* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
+	* var myPDF = pdf.factory( 0.0, 1.0, 0.0, 1.0 );
 	* var y = myPDF( 2.0 );
 	* // returns 0.0
 	*
 	* @example
-	* var myPDF = factory( 0.0, 1.0, 0.0, 1.0 );
+	* var myPDF = pdf.factory( 0.0, 1.0, 0.0, 1.0 );
 	* var y = myPDF( -1.0 );
 	* // returns 0.0
 	*/
@@ -110,7 +110,7 @@ interface PDF {
 *
 * var mypdf = pdf.factory( -1.0, 1.0, 0.0, 1.0 );
 * y = mypdf( 0.9 );
-* // returns ~0.5896
+* // returns ~0.3898
 */
 declare var pdf: PDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/docs/types/index.d.ts
index e6d1eeee3cdc..515eba50964f 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dists/weibull/logpdf/docs/types/index.d.ts
@@ -100,11 +100,11 @@ interface LogPDF {
 *
 * @example
 * var y = logpdf( 2.0, 1.0, 0.5 );
-* // returns ~-3.297
+* // returns ~-3.307
 *
 * var mylogpdf = logpdf.factory( 7.0, 6.0 );
 * y = mylogpdf( 7.0 );
-* // returns ~-1.864
+* // returns ~-1.863
 */
 declare var logpdf: LogPDF;
 
diff --git a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
index e355dc5e9602..4dd4edb05918 100644
--- a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
@@ -75,7 +75,7 @@ interface Namespace {
 	* // y => [ 1.0, 1.0, 2.0 ]
 	*
 	* @example
-	* var x = [ 1.0, -2.0, 2.0 ] );
+	* var x = [ 1.0, -2.0, 2.0 ];
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* ns.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 );
@@ -101,7 +101,7 @@ interface Namespace {
 	* // y => [ 1.0, 2.0, 2.0 ]
 	*
 	* @example
-	* var x = [ 1.0, -2.0, 2.0 ] );
+	* var x = [ 1.0, -2.0, 2.0 ];
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* ns.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
@@ -124,14 +124,14 @@ interface Namespace {
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* ns.cumin( x.length, x, 1, y, 1 );
-	* // y => [ 1.0, 1.0, 2.0 ]
+	* // y => [ 1.0, -2.0, -2.0 ]
 	*
 	* @example
-	* var x = [ 1.0, -2.0, 2.0 ] );
+	* var x = [ 1.0, -2.0, 2.0 ];
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* ns.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 );
-	* // y => [ 1.0, 1.0, 2.0 ]
+	* // y => [ 1.0, -2.0, -2.0 ]
 	*/
 	cumin: typeof cumin;
 
@@ -153,7 +153,7 @@ interface Namespace {
 	* // y => [ 1.0, 1.0, 1.0 ]
 	*
 	* @example
-	* var x = [ 1.0, -2.0, 2.0 ] );
+	* var x = [ 1.0, -2.0, 2.0 ];
 	* var y = [ 0.0, 0.0, 0.0 ];
 	*
 	* ns.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/README.md
new file mode 100644
index 000000000000..0dd77aa006f7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/README.md
@@ -0,0 +1,119 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# dnanmaxabs
+
+> Compute the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dnanmaxabs = require( '@stdlib/stats/base/ndarray/dnanmaxabs' );
+```
+
+#### dnanmaxabs( arrays )
+
+Computes the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = dnanmaxabs( [ x ] );
+// returns 2.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dnanmaxabs = require( '@stdlib/stats/base/ndarray/dnanmaxabs' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float64', rand );
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dnanmaxabs( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..5bedd2c0cf01
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/benchmark/benchmark.js
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var dnanmaxabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = filledarrayBy( len, 'float64', rand );
+	x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dnanmaxabs( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/repl.txt
new file mode 100644
index 000000000000..23a25d76b91d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+    Computes the maximum absolute value of a one-dimensional double-precision
+    floating-point ndarray, ignoring `NaN` values.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Maximum absolute value.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+    > var dt = 'float64';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    2.0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..5a73c785cb89
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/index.d.ts
@@ -0,0 +1,46 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns maximum absolute value
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanmaxabs( [ x ] );
+* // returns 2.0
+*/
+declare function dnanmaxabs( arrays: [ float64ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = dnanmaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/test.ts
new file mode 100644
index 000000000000..d6571402aeeb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import dnanmaxabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float64'
+	});
+
+	dnanmaxabs( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	dnanmaxabs( '10' ); // $ExpectError
+	dnanmaxabs( 10 ); // $ExpectError
+	dnanmaxabs( true ); // $ExpectError
+	dnanmaxabs( false ); // $ExpectError
+	dnanmaxabs( null ); // $ExpectError
+	dnanmaxabs( undefined ); // $ExpectError
+	dnanmaxabs( [] ); // $ExpectError
+	dnanmaxabs( {} ); // $ExpectError
+	dnanmaxabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float64'
+	});
+
+	dnanmaxabs(); // $ExpectError
+	dnanmaxabs( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/examples/index.js
new file mode 100644
index 000000000000..166b6ff772af
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dnanmaxabs = require( './../lib' );
+
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float64', rand );
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dnanmaxabs( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/index.js
new file mode 100644
index 000000000000..aaca1cb3a95b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/index.js
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @module @stdlib/stats/base/ndarray/dnanmaxabs
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var dnanmaxabs = require( '@stdlib/stats/base/ndarray/dnanmaxabs' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanmaxabs( [ x ] );
+* // returns 2.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/main.js
new file mode 100644
index 000000000000..85e7fecbef78
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/lib/main.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/dnanmaxabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
+* @returns {number} maximum absolute value
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanmaxabs( [ x ] );
+* // returns 2.0
+*/
+function dnanmaxabs( arrays ) {
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = dnanmaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json
new file mode 100644
index 000000000000..d48dfde608b4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/stats/base/ndarray/dnanmaxabs",
+  "version": "0.0.0",
+  "description": "Compute the maximum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "maximum",
+    "max",
+    "absolute",
+    "abs",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/test/test.js
new file mode 100644
index 000000000000..0f8e812b5856
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanmaxabs/test/test.js
@@ -0,0 +1,180 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var dnanmaxabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Float64Array} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dnanmaxabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( dnanmaxabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the maximum absolute value of a one-dimensional ndarray', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] );
+	v = dnanmaxabs( [ vector( x, 7, 1, 0 ) ] );
+	t.strictEqual( v, 5.0, 'returns expected value' );
+
+	x = new Float64Array( [ -4.0, NaN, -5.0 ] );
+	v = dnanmaxabs( [ vector( x, 3, 1, 0 ) ] );
+	t.strictEqual( v, 5.0, 'returns expected value' );
+
+	x = new Float64Array( [-0.0, 0.0, NaN, -0.0 ] );
+	v = dnanmaxabs( [ vector( x, 4, 1, 0 ) ] );
+	t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+	x = new Float64Array( [ NaN ] );
+	v = dnanmaxabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = new Float64Array( [ NaN, NaN ] );
+	v = dnanmaxabs( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [] );
+
+	v = dnanmaxabs( [ vector( x, 0, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0 ] );
+
+	v = dnanmaxabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	]);
+
+	v = dnanmaxabs( [ vector( x, 5, 2, 0 ) ] );
+
+	t.strictEqual( v, 4.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		NaN,  // 4
+		NaN,
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+
+	v = dnanmaxabs( [ vector( x, 5, -2, 8 ) ] );
+
+	t.strictEqual( v, 4.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0,
+		NaN,  // 4
+		NaN
+	]);
+
+	v = dnanmaxabs( [ vector( x, 5, 2, 1 ) ] );
+	t.strictEqual( v, 4.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/README.md
new file mode 100644
index 000000000000..c8b24415f1e4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/README.md
@@ -0,0 +1,119 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# dnanminabs
+
+> Compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dnanminabs = require( '@stdlib/stats/base/ndarray/dnanminabs' );
+```
+
+#### dnanminabs( arrays )
+
+Computes the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = dnanminabs( [ x ] );
+// returns 1.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dnanminabs = require( '@stdlib/stats/base/ndarray/dnanminabs' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float64', rand );
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dnanminabs( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..eaaff9de5709
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/benchmark/benchmark.js
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var dnanminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = filledarrayBy( len, 'float64', rand );
+	x = new ndarray( 'float64', xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dnanminabs( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/repl.txt
new file mode 100644
index 000000000000..08166c929632
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+    Computes the minimum absolute value of a one-dimensional double-precision
+    floating-point ndarray, ignoring `NaN` values.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Minimum absolute value.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+    > var dt = 'float64';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    1.0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..b2a013a10067
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/index.d.ts
@@ -0,0 +1,46 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float64ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns minimum absolute value
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanminabs( [ x ] );
+* // returns 1.0
+*/
+declare function dnanminabs( arrays: [ float64ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = dnanminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/test.ts
new file mode 100644
index 000000000000..a1a92ae24dd2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import dnanminabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float64'
+	});
+
+	dnanminabs( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	dnanminabs( '10' ); // $ExpectError
+	dnanminabs( 10 ); // $ExpectError
+	dnanminabs( true ); // $ExpectError
+	dnanminabs( false ); // $ExpectError
+	dnanminabs( null ); // $ExpectError
+	dnanminabs( undefined ); // $ExpectError
+	dnanminabs( [] ); // $ExpectError
+	dnanminabs( {} ); // $ExpectError
+	dnanminabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float64'
+	});
+
+	dnanminabs(); // $ExpectError
+	dnanminabs( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/examples/index.js
new file mode 100644
index 000000000000..1348104b19f9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dnanminabs = require( './../lib' );
+
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'float64', rand );
+var x = new ndarray( 'float64', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = dnanminabs( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/index.js
new file mode 100644
index 000000000000..5b84d75356b3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/index.js
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @module @stdlib/stats/base/ndarray/dnanminabs
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var dnanminabs = require( '@stdlib/stats/base/ndarray/dnanminabs' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanminabs( [ x ] );
+* // returns 1.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/main.js
new file mode 100644
index 000000000000..360fe9c769fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/lib/main.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/dnanminabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the minimum absolute value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
+* @returns {number} minimum absolute value
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
+* var x = new ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = dnanminabs( [ x ] );
+* // returns 1.0
+*/
+function dnanminabs( arrays ) {
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = dnanminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json
new file mode 100644
index 000000000000..411ddd6bf374
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/stats/base/ndarray/dnanminabs",
+  "version": "0.0.0",
+  "description": "Compute the minimum value of a one-dimensional double-precision floating-point ndarray, ignoring `NaN` values.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "minimum",
+    "min",
+    "absolute",
+    "abs",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/test/test.js
new file mode 100644
index 000000000000..4e3faf8ecf2e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/dnanminabs/test/test.js
@@ -0,0 +1,179 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var dnanminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Float64Array} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float64', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dnanminabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( dnanminabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the minimum absolute value of a one-dimensional ndarray', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ] );
+	v = dnanminabs( [ vector( x, 7, 1, 0 ) ] );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = new Float64Array( [ -4.0, NaN, -5.0 ] );
+	v = dnanminabs( [ vector( x, 3, 1, 0 ) ] );
+	t.strictEqual( v, 4.0, 'returns expected value' );
+
+	x = new Float64Array( [-0.0, 0.0, NaN, -0.0 ] );
+	v = dnanminabs( [ vector( x, 4, 1, 0 ) ] );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = new Float64Array( [ NaN ] );
+	v = dnanminabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = new Float64Array( [ NaN, NaN ] );
+	v = dnanminabs( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [] );
+
+	v = dnanminabs( [ vector( x, 0, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0 ] );
+
+	v = dnanminabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	]);
+
+	v = dnanminabs( [ vector( x, 5, 2, 0 ) ] );
+
+	t.strictEqual( v, 1.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		NaN,  // 4
+		NaN,
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+
+	v = dnanminabs( [ vector( x, 5, -2, 8 ) ] );
+
+	t.strictEqual( v, 1.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0,
+		NaN,  // 4
+		NaN
+	]);
+
+	v = dnanminabs( [ vector( x, 5, 2, 1 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/README.md
new file mode 100644
index 000000000000..de38ad170de6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/README.md
@@ -0,0 +1,118 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# nanmaxabs
+
+> Compute the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var nanmaxabs = require( '@stdlib/stats/base/ndarray/nanmaxabs' );
+```
+
+#### nanmaxabs( arrays )
+
+Computes the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+
+```javascript
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = nanmaxabs( [ x ] );
+// returns 2.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var nanmaxabs = require( '@stdlib/stats/base/ndarray/nanmaxabs' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'generic', rand );
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = nanmaxabs( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..7837729489d0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/benchmark/benchmark.js
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var nanmaxabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = filledarrayBy( len, 'generic', rand );
+	x = new ndarray( 'generic', xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = nanmaxabs( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/repl.txt
new file mode 100644
index 000000000000..bd49807e25ac
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+    Computes the maximum absolute value of a one-dimensional ndarray, ignoring
+    `NaN` values.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Maximum absolute value.
+
+    Examples
+    --------
+    > var xbuf = [ 1.0, -2.0, 2.0 ];
+    > var dt = 'generic';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    2.0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..0c6df0b5ef5c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/index.d.ts
@@ -0,0 +1,45 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns maximum absolute value
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanmaxabs( [ x ] );
+* // returns 2.0
+*/
+declare function nanmaxabs<T extends ndarray = ndarray>( arrays: [ T ] ): number;
+
+
+// EXPORTS //
+
+export = nanmaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/test.ts
new file mode 100644
index 000000000000..b8453540c94b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import nanmaxabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'generic'
+	});
+
+	nanmaxabs( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	nanmaxabs( '10' ); // $ExpectError
+	nanmaxabs( 10 ); // $ExpectError
+	nanmaxabs( true ); // $ExpectError
+	nanmaxabs( false ); // $ExpectError
+	nanmaxabs( null ); // $ExpectError
+	nanmaxabs( undefined ); // $ExpectError
+	nanmaxabs( [] ); // $ExpectError
+	nanmaxabs( {} ); // $ExpectError
+	nanmaxabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'generic'
+	});
+
+	nanmaxabs(); // $ExpectError
+	nanmaxabs( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/examples/index.js
new file mode 100644
index 000000000000..4aa586c96792
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var nanmaxabs = require( './../lib' );
+
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'generic', rand );
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = nanmaxabs( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/index.js
new file mode 100644
index 000000000000..92425eb011c6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/index.js
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @module @stdlib/stats/base/ndarray/nanmaxabs
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var nanmaxabs = require( '@stdlib/stats/base/ndarray/nanmaxabs' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanmaxabs( [ x ] );
+* // returns 2.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/main.js
new file mode 100644
index 000000000000..4142de264861
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/lib/main.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/nanmaxabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
+* @returns {number} maximum absolute value
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanmaxabs( [ x ] );
+* // returns 2.0
+*/
+function nanmaxabs( arrays ) {
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = nanmaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json
new file mode 100644
index 000000000000..bdaa0573294e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/stats/base/ndarray/nanmaxabs",
+  "version": "0.0.0",
+  "description": "Compute the maximum absolute value of a one-dimensional ndarray, ignoring `NaN` values.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "maximum",
+    "max",
+    "absolute",
+    "abs",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/test/test.js
new file mode 100644
index 000000000000..72f395daeb74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanmaxabs/test/test.js
@@ -0,0 +1,179 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var nanmaxabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof nanmaxabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( nanmaxabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the maximum absolute value of a one-dimensional ndarray', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ];
+	v = nanmaxabs( [ vector( x, 7, 1, 0 ) ] );
+	t.strictEqual( v, 5.0, 'returns expected value' );
+
+	x = [ -4.0, NaN, -5.0 ];
+	v = nanmaxabs( [ vector( x, 3, 1, 0 ) ] );
+	t.strictEqual( v, 5.0, 'returns expected value' );
+
+	x = [-0.0, 0.0, NaN, -0.0 ];
+	v = nanmaxabs( [ vector( x, 4, 1, 0 ) ] );
+	t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+	x = [ NaN ];
+	v = nanmaxabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = [ NaN, NaN ];
+	v = nanmaxabs( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = [];
+
+	v = nanmaxabs( [ vector( x, 0, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0 ];
+
+	v = nanmaxabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanmaxabs( [ vector( x, 5, 2, 0 ) ] );
+
+	t.strictEqual( v, 4.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		NaN,  // 4
+		NaN,
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	];
+
+	v = nanmaxabs( [ vector( x, 5, -2, 8 ) ] );
+
+	t.strictEqual( v, 4.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanmaxabs( [ vector( x, 5, 2, 1 ) ] );
+	t.strictEqual( v, 4.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/README.md
new file mode 100644
index 000000000000..b1039c7fba37
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/README.md
@@ -0,0 +1,118 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# nanminabs
+
+> Compute the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var nanminabs = require( '@stdlib/stats/base/ndarray/nanminabs' );
+```
+
+#### nanminabs( arrays )
+
+Computes the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+
+```javascript
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = nanminabs( [ x ] );
+// returns 1.0
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var nanminabs = require( '@stdlib/stats/base/ndarray/nanminabs' );
+
+function rand() {
+    if ( bernoulli( 0.8 ) < 1 ) {
+        return NaN;
+    }
+    return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'generic', rand );
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = nanminabs( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..86ccc91f6a75
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/benchmark/benchmark.js
@@ -0,0 +1,110 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var nanminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a random number.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = filledarrayBy( len, 'generic', rand );
+	x = new ndarray( 'generic', xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = nanminabs( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/repl.txt
new file mode 100644
index 000000000000..3ccc437217fd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+    Computes the minimum absolute value of a one-dimensional ndarray,
+    ignoring `NaN` values.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Minimum absolute value.
+
+    Examples
+    --------
+    > var xbuf = [ 1.0, -2.0, 2.0 ];
+    > var dt = 'generic';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    1.0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..70b10ae9756b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/index.d.ts
@@ -0,0 +1,45 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns minimum absolute value
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanminabs( [ x ] );
+* // returns 1.0
+*/
+declare function nanminabs<T extends ndarray = ndarray>( arrays: [ T ] ): number;
+
+
+// EXPORTS //
+
+export = nanminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/test.ts
new file mode 100644
index 000000000000..ff7f0fcd4cdf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import nanminabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'generic'
+	});
+
+	nanminabs( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	nanminabs( '10' ); // $ExpectError
+	nanminabs( 10 ); // $ExpectError
+	nanminabs( true ); // $ExpectError
+	nanminabs( false ); // $ExpectError
+	nanminabs( null ); // $ExpectError
+	nanminabs( undefined ); // $ExpectError
+	nanminabs( [] ); // $ExpectError
+	nanminabs( {} ); // $ExpectError
+	nanminabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'generic'
+	});
+
+	nanminabs(); // $ExpectError
+	nanminabs( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/examples/index.js
new file mode 100644
index 000000000000..1bd5c0cceb1b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/examples/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/base/uniform' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var nanminabs = require( './../lib' );
+
+function rand() {
+	if ( bernoulli( 0.8 ) < 1 ) {
+		return NaN;
+	}
+	return uniform( -50.0, 50.0 );
+}
+
+var xbuf = filledarrayBy( 10, 'generic', rand );
+var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = nanminabs( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/index.js
new file mode 100644
index 000000000000..9bc4520c63db
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/index.js
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @module @stdlib/stats/base/ndarray/nanminabs
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var nanminabs = require( '@stdlib/stats/base/ndarray/nanminabs' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanminabs( [ x ] );
+* // returns 1.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/main.js
new file mode 100644
index 000000000000..20f60cb5ec94
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/lib/main.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/nanminabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
+* @returns {number} minimum absolute value
+*
+* @example
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = [ 1.0, -2.0, NaN, 2.0 ];
+* var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = nanminabs( [ x ] );
+* // returns 1.0
+*/
+function nanminabs( arrays ) {
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = nanminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json
new file mode 100644
index 000000000000..3db3a7259477
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/stats/base/ndarray/nanminabs",
+  "version": "0.0.0",
+  "description": "Compute the minimum absolute value of a one-dimensional ndarray, ignoring `NaN` values.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "minimum",
+    "min",
+    "absolute",
+    "abs",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/test/test.js
new file mode 100644
index 000000000000..d263062bba33
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/nanminabs/test/test.js
@@ -0,0 +1,179 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var nanminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'generic', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof nanminabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( nanminabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the minimum absolute value of a one-dimensional ndarray', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0, -2.0, -4.0, NaN, 5.0, 0.0, 3.0 ];
+	v = nanminabs( [ vector( x, 7, 1, 0 ) ] );
+	t.strictEqual( v, 0.0, 'returns expected value' );
+
+	x = [ -4.0, NaN, -5.0 ];
+	v = nanminabs( [ vector( x, 3, 1, 0 ) ] );
+	t.strictEqual( v, 4.0, 'returns expected value' );
+
+	x = [ -0.0, 0.0, NaN, -0.0 ];
+	v = nanminabs( [ vector( x, 4, 1, 0 ) ] );
+	t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+	x = [ NaN ];
+	v = nanminabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = [ NaN, NaN ];
+	v = nanminabs( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = [];
+
+	v = nanminabs( [ vector( x, 0, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+	var x;
+	var v;
+
+	x = [ 1.0 ];
+
+	v = nanminabs( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanminabs( [ vector( x, 5, 2, 0 ) ] );
+
+	t.strictEqual( v, 1.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		NaN,  // 4
+		NaN,
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	];
+
+	v = nanminabs( [ vector( x, 5, -2, 8 ) ] );
+
+	t.strictEqual( v, 1.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var x;
+	var v;
+
+	x = [
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0,
+		NaN,  // 4
+		NaN
+	];
+
+	v = nanminabs( [ vector( x, 5, 2, 1 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/README.md
new file mode 100644
index 000000000000..d506dc60fda8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/README.md
@@ -0,0 +1,126 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# scumaxabs
+
+> Compute the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var scumaxabs = require( '@stdlib/stats/base/ndarray/scumaxabs' );
+```
+
+#### scumaxabs( arrays )
+
+Computes the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = scumaxabs( [ x, y ] );
+// returns <ndarray>
+
+var bool = ( v === y );
+// returns true
+
+var arr = ndarray2array( v );
+// returns [ 1.0, 3.0, 4.0, 4.0 ]
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray and a one-dimensional output ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scumaxabs = require( '@stdlib/stats/base/ndarray/scumaxabs' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = zerosLike( x );
+console.log( ndarray2array( y ) );
+
+var v = scumaxabs( [ x, y ] );
+console.log( ndarray2array( v ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..3f8a477b93d9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/benchmark/benchmark.js
@@ -0,0 +1,108 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var zeros = require( '@stdlib/array/zeros' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var scumaxabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	ybuf = zeros( len, options.dtype );
+	y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = scumaxabs( [ x, y ] );
+			if ( typeof v !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnanf( v.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/repl.txt
new file mode 100644
index 000000000000..7deb4107c51b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/repl.txt
@@ -0,0 +1,37 @@
+
+{{alias}}( arrays )
+    Computes the cumulative maximum absolute value of a one-dimensional
+    single-precision floating-point ndarray.
+
+    If provided an empty input ndarray, the function returns the output ndarray
+    unchanged.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray and a one-
+        dimensional output ndarray.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
+    > var ybuf = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0 ] );
+    > var dt = 'float32';
+    > var sh = [ xbuf.length ];
+    > var st = [ 1 ];
+    > var oo = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
+    > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord );
+    > {{alias}}( [ x, y ] );
+    > {{alias:@stdlib/ndarray/to-array}}( y )
+    [ 1.0, 2.0, 2.0 ]
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..abd148f9c121
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/index.d.ts
@@ -0,0 +1,56 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @param arrays - array-like object containing an input ndarray and an output ndarray
+* @returns output ndarray
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scumaxabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 3.0, 4.0, 4.0 ]
+*/
+declare function scumaxabs( arrays: [ float32ndarray, float32ndarray ] ): float32ndarray;
+
+
+// EXPORTS //
+
+export = scumaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/test.ts
new file mode 100644
index 000000000000..ec0614c51032
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/docs/types/test.ts
@@ -0,0 +1,63 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import scumaxabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	scumaxabs( [ x, y ] ); // $ExpectType float32ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	scumaxabs( '10' ); // $ExpectError
+	scumaxabs( 10 ); // $ExpectError
+	scumaxabs( true ); // $ExpectError
+	scumaxabs( false ); // $ExpectError
+	scumaxabs( null ); // $ExpectError
+	scumaxabs( undefined ); // $ExpectError
+	scumaxabs( [] ); // $ExpectError
+	scumaxabs( {} ); // $ExpectError
+	scumaxabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	scumaxabs(); // $ExpectError
+	scumaxabs( [ x, y ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/examples/index.js
new file mode 100644
index 000000000000..b0913bd6018c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/examples/index.js
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scumaxabs = require( './../lib' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+	'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = zerosLike( x );
+console.log( ndarray2array( y ) );
+
+var v = scumaxabs( [ x, y ] );
+console.log( ndarray2array( v ) );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/index.js
new file mode 100644
index 000000000000..fc9b176fb9fb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/index.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @module @stdlib/stats/base/ndarray/scumaxabs
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var scumaxabs = require( '@stdlib/stats/base/ndarray/scumaxabs' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scumaxabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 3.0, 4.0, 4.0 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/main.js
new file mode 100644
index 000000000000..e0c5984df850
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/lib/main.js
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/scumaxabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and an output ndarray
+* @returns {ndarrayLike} output ndarray
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scumaxabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 3.0, 4.0, 4.0 ]
+*/
+function scumaxabs( arrays ) {
+	var x = arrays[ 0 ];
+	var y = arrays[ 1 ];
+	strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len
+	return y;
+}
+
+
+// EXPORTS //
+
+module.exports = scumaxabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/package.json
new file mode 100644
index 000000000000..412a36dab41f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/package.json
@@ -0,0 +1,72 @@
+{
+  "name": "@stdlib/stats/base/ndarray/scumaxabs",
+  "version": "0.0.0",
+  "description": "Compute the cumulative maximum absolute value of a one-dimensional single-precision floating-point ndarray.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "cumulative",
+    "accumulate",
+    "maximum",
+    "max",
+    "abs",
+    "absolute",
+    "absolute value",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/test/test.js
new file mode 100644
index 000000000000..d3c3bf9464e2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scumaxabs/test/test.js
@@ -0,0 +1,273 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var scumaxabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Float32Array} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof scumaxabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( scumaxabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the cumulative maximum absolute value of a one-dimensional ndarray', function test( t ) {
+	var expected;
+	var xbuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	x = vector( xbuf, 6, 1, 0 );
+	y = zerosLike( x );
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [ 1.0, 2.0, 4.0, 5.0, 5.0, 5.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ -4.0, -5.0 ] );
+	x = vector( xbuf, 2, 1, 0 );
+	y = zerosLike( x );
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [ 4.0, 5.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ -0.0, 0.0, -0.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = zerosLike( x );
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [ 0.0, 0.0, 0.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ NaN ] );
+	x = vector( xbuf, 1, 1, 0 );
+	y = zerosLike( x );
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [ NaN ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ NaN, NaN ] );
+	x = vector( xbuf, 2, 1, 0 );
+	y = zerosLike( x );
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [ NaN, NaN ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns the output array unchanged', function test( t ) {
+	var expected;
+	var xbuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array( [] );
+	x = vector( xbuf, 0, 1, 0 );
+	y = zerosLike( x );
+
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array( [] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	x = vector( xbuf, 4, 2, 0 );
+
+	ybuf = new Float32Array([
+		0.0,  // 0
+		0.0,
+		0.0,  // 1
+		0.0,
+		0.0,  // 2
+		0.0,
+		0.0,  // 3
+		0.0
+	]);
+	y = vector( ybuf, 4, 2, 0 );
+
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array([
+		1.0,  // 0
+		0.0,
+		2.0,  // 1
+		0.0,
+		2.0,  // 2
+		0.0,
+		4.0,  // 3
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		1.0,  // 2
+		-2.0,
+		3.0,  // 1
+		4.0,
+		-5.0  // 0
+	]);
+	x = vector( xbuf, 3, -2, 4 );
+
+	ybuf = new Float32Array([
+		0.0, // 2
+		0.0, // 1
+		0.0, // 0
+		0.0,
+		0.0
+	]);
+	y = vector( ybuf, 3, -1, 2 );
+
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array([
+		5.0,  // 2
+		5.0,  // 1
+		5.0, // 0
+		0.0,
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0   // 3
+	]);
+	x = vector( xbuf, 4, 2, 1 );
+
+	ybuf = new Float32Array([
+		0.0,
+		0.0,
+		0.0,  // 0
+		0.0,  // 1
+		0.0,  // 2
+		0.0,  // 3
+		0.0,
+		0.0
+	]);
+	y = vector( ybuf, 4, 1, 2 );
+
+	v = scumaxabs( [ x, y ] );
+
+	expected = new Float32Array([
+		0.0,
+		0.0,
+		1.0,  // 0
+		2.0,  // 1
+		2.0,  // 2
+		4.0,  // 3
+		0.0,
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/README.md
new file mode 100644
index 000000000000..287f17072389
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/README.md
@@ -0,0 +1,126 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# scuminabs
+
+> Compute the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var scuminabs = require( '@stdlib/stats/base/ndarray/scuminabs' );
+```
+
+#### scuminabs( arrays )
+
+Computes the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = scuminabs( [ x, y ] );
+// returns <ndarray>
+
+var bool = ( v === y );
+// returns true
+
+var arr = ndarray2array( v );
+// returns [ 1.0, 1.0, 1.0, 1.0 ]
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray and a one-dimensional output ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scuminabs = require( '@stdlib/stats/base/ndarray/scuminabs' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = zerosLike( x );
+console.log( ndarray2array( y ) );
+
+var v = scuminabs( [ x, y ] );
+console.log( ndarray2array( v ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js
new file mode 100644
index 000000000000..5d810a9b4038
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/benchmark/benchmark.js
@@ -0,0 +1,108 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var zeros = require( '@stdlib/array/zeros' );
+var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( './../package.json' ).name;
+var scuminabs = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	ybuf = zeros( len, options.dtype );
+	y = new ndarray( options.dtype, ybuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = scuminabs( [ x, y ] );
+			if ( typeof v !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnanf( v.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/repl.txt
new file mode 100644
index 000000000000..a21db2ad9b72
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/repl.txt
@@ -0,0 +1,37 @@
+
+{{alias}}( arrays )
+    Computes the cumulative minimum absolute value of a one-dimensional
+    single-precision floating-point ndarray.
+
+    If provided an empty input ndarray, the function returns the output ndarray
+    unchanged.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray and a one-
+        dimensional output ndarray.
+
+    Returns
+    -------
+    out: ndarray
+        Output ndarray.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
+    > var ybuf = new {{alias:@stdlib/array/float32}}( [ 0.0, 0.0, 0.0 ] );
+    > var dt = 'float32';
+    > var sh = [ xbuf.length ];
+    > var st = [ 1 ];
+    > var oo = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, st, oo, ord );
+    > var y = new {{alias:@stdlib/ndarray/ctor}}( dt, ybuf, sh, st, oo, ord );
+    > {{alias}}( [ x, y ] );
+    > {{alias:@stdlib/ndarray/to-array}}( y )
+    [ 1.0, 1.0, 1.0 ]
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/index.d.ts
new file mode 100644
index 000000000000..8a3842e90acb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/index.d.ts
@@ -0,0 +1,56 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @param arrays - array-like object containing an input ndarray and an output ndarray
+* @returns output ndarray
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scuminabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 1.0, 1.0, 1.0 ]
+*/
+declare function scuminabs( arrays: [ float32ndarray, float32ndarray ] ): float32ndarray;
+
+
+// EXPORTS //
+
+export = scuminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/test.ts
new file mode 100644
index 000000000000..d31d8f6dba3f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/docs/types/test.ts
@@ -0,0 +1,63 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import scuminabs = require( './index' );
+
+
+// TESTS //
+
+// The function returns an ndarray...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	scuminabs( [ x, y ] ); // $ExpectType float32ndarray
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	scuminabs( '10' ); // $ExpectError
+	scuminabs( 10 ); // $ExpectError
+	scuminabs( true ); // $ExpectError
+	scuminabs( false ); // $ExpectError
+	scuminabs( null ); // $ExpectError
+	scuminabs( undefined ); // $ExpectError
+	scuminabs( [] ); // $ExpectError
+	scuminabs( {} ); // $ExpectError
+	scuminabs( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+	const y = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	scuminabs(); // $ExpectError
+	scuminabs( [ x, y ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/examples/index.js
new file mode 100644
index 000000000000..67952680b4e4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/examples/index.js
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var scuminabs = require( './../lib' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+	'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = zerosLike( x );
+console.log( ndarray2array( y ) );
+
+var v = scuminabs( [ x, y ] );
+console.log( ndarray2array( v ) );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/index.js
new file mode 100644
index 000000000000..88f3b5caa336
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/index.js
@@ -0,0 +1,55 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @module @stdlib/stats/base/ndarray/scuminabs
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var scuminabs = require( '@stdlib/stats/base/ndarray/scuminabs' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scuminabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 1.0, 1.0, 1.0 ]
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/main.js
new file mode 100644
index 000000000000..73ac30a34dbe
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/lib/main.js
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/scuminabs' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray and an output ndarray
+* @returns {ndarrayLike} output ndarray
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray2array = require( '@stdlib/ndarray/to-array' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
+* var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = scuminabs( [ x, y ] );
+* // returns <ndarray>
+*
+* var bool = ( v === y );
+* // returns true
+*
+* var arr = ndarray2array( v );
+* // returns [ 1.0, 1.0, 1.0, 1.0 ]
+*/
+function scuminabs( arrays ) {
+	var x = arrays[ 0 ];
+	var y = arrays[ 1 ];
+	strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ), getData( y ), getStride( y, 0 ), getOffset( y ) ); // eslint-disable-line max-len
+	return y;
+}
+
+
+// EXPORTS //
+
+module.exports = scuminabs;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/package.json
new file mode 100644
index 000000000000..fef4766dd84e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/package.json
@@ -0,0 +1,72 @@
+{
+  "name": "@stdlib/stats/base/ndarray/scuminabs",
+  "version": "0.0.0",
+  "description": "Compute the cumulative minimum absolute value of a one-dimensional single-precision floating-point ndarray.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "cumulative",
+    "accumulate",
+    "minimum",
+    "min",
+    "abs",
+    "absolute",
+    "absolute value",
+    "range",
+    "extremes",
+    "domain",
+    "extent",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/test/test.js
new file mode 100644
index 000000000000..46817130d217
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/scuminabs/test/test.js
@@ -0,0 +1,273 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isSameFloat32Array = require( '@stdlib/assert/is-same-float32array' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var zerosLike = require( '@stdlib/ndarray/zeros-like' );
+var getData = require( '@stdlib/ndarray/data-buffer' );
+var scuminabs = require( './../lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Float32Array} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof scuminabs, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( scuminabs.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the cumulative minimum absolute value of a one-dimensional ndarray', function test( t ) {
+	var expected;
+	var xbuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	x = vector( xbuf, 6, 1, 0 );
+	y = zerosLike( x );
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 0.0, 0.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ -4.0, -5.0 ] );
+	x = vector( xbuf, 2, 1, 0 );
+	y = zerosLike( x );
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [ 4.0, 4.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ -0.0, 0.0, -0.0 ] );
+	x = vector( xbuf, 3, 1, 0 );
+	y = zerosLike( x );
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [ 0.0, 0.0, 0.0 ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ NaN ] );
+	x = vector( xbuf, 1, 1, 0 );
+	y = zerosLike( x );
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [ NaN ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	xbuf = new Float32Array( [ NaN, NaN ] );
+	x = vector( xbuf, 2, 1, 0 );
+	y = zerosLike( x );
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [ NaN, NaN ] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns the output array unchanged', function test( t ) {
+	var expected;
+	var xbuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array( [] );
+	x = vector( xbuf, 0, 1, 0 );
+	y = zerosLike( x );
+
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array( [] );
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+	x = vector( xbuf, 4, 2, 0 );
+
+	ybuf = new Float32Array([
+		0.0,  // 0
+		0.0,
+		0.0,  // 1
+		0.0,
+		0.0,  // 2
+		0.0,
+		0.0,  // 3
+		0.0
+	]);
+	y = vector( ybuf, 4, 2, 0 );
+
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array([
+		1.0,   // 0
+		0.0,
+		1.0,   // 1
+		0.0,
+		1.0,  // 2
+		0.0,
+		1.0,  // 3
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		1.0,  // 2
+		-2.0,
+		3.0,  // 1
+		4.0,
+		-5.0  // 0
+	]);
+	x = vector( xbuf, 3, -2, 4 );
+
+	ybuf = new Float32Array([
+		0.0, // 2
+		0.0, // 1
+		0.0, // 0
+		0.0,
+		0.0
+	]);
+	y = vector( ybuf, 3, -1, 2 );
+
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array([
+		1.0,  // 2
+		3.0,  // 1
+		5.0,  // 0
+		0.0,
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var expected;
+	var xbuf;
+	var ybuf;
+	var x;
+	var y;
+	var v;
+
+	xbuf = new Float32Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0   // 3
+	]);
+	x = vector( xbuf, 4, 2, 1 );
+
+	ybuf = new Float32Array([
+		0.0,
+		0.0,
+		0.0,  // 0
+		0.0,  // 1
+		0.0,  // 2
+		0.0,  // 3
+		0.0,
+		0.0
+	]);
+	y = vector( ybuf, 4, 1, 2 );
+
+	v = scuminabs( [ x, y ] );
+
+	expected = new Float32Array([
+		0.0,
+		0.0,
+		1.0,   // 0
+		1.0,  // 1
+		1.0,  // 2
+		1.0,  // 3
+		0.0,
+		0.0
+	]);
+	t.strictEqual( v, y, 'returns expected value' );
+	t.strictEqual( isSameFloat32Array( getData( v ), expected ), true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/README.md b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/README.md
new file mode 100644
index 000000000000..a0927055aeca
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/README.md
@@ -0,0 +1,129 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# smeankbn2
+
+> Compute the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
+
+<section class="intro">
+
+The [arithmetic mean][arithmetic-mean] is defined as
+
+<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" alt="Equation for the arithmetic mean."> -->
+
+```math
+\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\mu = \frac{1}{n} \sum_{i=0}^{n-1} x_i" data-equation="eq:arithmetic_mean">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@42d8f64d805113ab899c79c7c39d6c6bac7fe25c/lib/node_modules/@stdlib/stats/base/ndarray/mean/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2' );
+```
+
+#### smeankbn2( arrays )
+
+Computes the [arithmetic mean][arithmetic-mean] of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
+
+```javascript
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+
+var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+
+var v = smeankbn2( [ x ] );
+// returns ~2.5
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing a one-dimensional input ndarray.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If provided an empty one-dimensional ndarray, the function returns `NaN`.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+    'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = smeankbn2( [ x ] );
+console.log( v );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js
new file mode 100644
index 000000000000..201d51f26168
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/benchmark/benchmark.js
@@ -0,0 +1,102 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var pkg = require( '@stdlib/stats/base/ndarray/smeankbn2/package.json' ).name;
+var smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2/lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var xbuf;
+	var x;
+
+	xbuf = uniform( len, -10.0, 10.0, options );
+	x = new ndarray( options.dtype, xbuf, [ len ], [ 1 ], 0, 'row-major' );
+
+	return benchmark;
+
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = smeankbn2( [ x ] );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/img/equation_arithmetic_mean.svg
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diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/repl.txt
new file mode 100644
index 000000000000..a02bef2d9214
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/repl.txt
@@ -0,0 +1,32 @@
+
+{{alias}}( arrays )
+    Computes the arithmetic mean of a one-dimensional single-precision floating-
+    point ndarray using a second-order iterative Kahan–Babuška algorithm.
+
+    If provided an empty ndarray, the function returns `NaN`.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing a one-dimensional input ndarray.
+
+    Returns
+    -------
+    out: number
+        Arithmetic mean.
+
+    Examples
+    --------
+    > var xbuf = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 2.0 ] );
+    > var dt = 'float32';
+    > var sh = [ xbuf.length ];
+    > var sx = [ 1 ];
+    > var ox = 0;
+    > var ord = 'row-major';
+    > var x = new {{alias:@stdlib/ndarray/ctor}}( dt, xbuf, sh, sx, ox, ord );
+    > {{alias}}( [ x ] )
+    ~0.3333
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/index.d.ts
new file mode 100644
index 000000000000..1f53e824af40
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/index.d.ts
@@ -0,0 +1,46 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { float32ndarray } from '@stdlib/types/ndarray';
+
+/**
+* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
+*
+* @param arrays - array-like object containing an input ndarray
+* @returns arithmetic mean
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = smeankbn2( [ x ] );
+* // returns ~2.5
+*/
+declare function smeankbn2( arrays: [ float32ndarray ] ): number;
+
+
+// EXPORTS //
+
+export = smeankbn2;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/test.ts
new file mode 100644
index 000000000000..0a388c802852
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import zeros = require( '@stdlib/ndarray/zeros' );
+import smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2/docs/types' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	smeankbn2( [ x ] ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
+{
+	smeankbn2( '10' ); // $ExpectError
+	smeankbn2( 10 ); // $ExpectError
+	smeankbn2( true ); // $ExpectError
+	smeankbn2( false ); // $ExpectError
+	smeankbn2( null ); // $ExpectError
+	smeankbn2( undefined ); // $ExpectError
+	smeankbn2( [] ); // $ExpectError
+	smeankbn2( {} ); // $ExpectError
+	smeankbn2( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	const x = zeros( [ 10 ], {
+		'dtype': 'float32'
+	});
+
+	smeankbn2(); // $ExpectError
+	smeankbn2( [ x ], {} ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/examples/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/examples/index.js
new file mode 100644
index 000000000000..c3f64a10ea2a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/examples/index.js
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var smeankbn2 = require( './../lib' );
+
+var xbuf = discreteUniform( 10, -50, 50, {
+	'dtype': 'float32'
+});
+var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var v = smeankbn2( [ x ] );
+console.log( v );
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/index.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/index.js
new file mode 100644
index 000000000000..d1316c47ab2c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/index.js
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
+*
+* @module @stdlib/stats/base/ndarray/smeankbn2
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+* var smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = smeankbn2( [ x ] );
+* // returns ~2.5
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/main.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/main.js
new file mode 100644
index 000000000000..7c3746d4d113
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/lib/main.js
@@ -0,0 +1,56 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var numelDimension = require( '@stdlib/ndarray/base/numel-dimension' );
+var getStride = require( '@stdlib/ndarray/base/stride' );
+var getOffset = require( '@stdlib/ndarray/base/offset' );
+var getData = require( '@stdlib/ndarray/base/data-buffer' );
+var strided = require( '@stdlib/stats/strided/smeankbn2' ).ndarray;
+
+
+// MAIN //
+
+/**
+* Computes the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.
+*
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing an input ndarray
+* @returns {number} arithmetic mean
+*
+* @example
+* var Float32Array = require( '@stdlib/array/float32' );
+* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+*
+* var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
+* var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
+*
+* var v = smeankbn2( [ x ] );
+* // returns ~2.5
+*/
+function smeankbn2( arrays ) {
+	var x = arrays[ 0 ];
+	return strided( numelDimension( x, 0 ), getData( x ), getStride( x, 0 ), getOffset( x ) ); // eslint-disable-line max-len
+}
+
+
+// EXPORTS //
+
+module.exports = smeankbn2;
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/package.json b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/package.json
new file mode 100644
index 000000000000..477e2fdab7ba
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/package.json
@@ -0,0 +1,71 @@
+{
+  "name": "@stdlib/stats/base/ndarray/smeankbn2",
+  "version": "0.0.0",
+  "description": "Compute the arithmetic mean of a one-dimensional single-precision floating-point ndarray using a second-order iterative Kahan–Babuška algorithm.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "average",
+    "avg",
+    "mean",
+    "arithmetic mean",
+    "float32",
+    "single",
+    "float32array",
+    "kahan",
+    "kbn",
+    "kbn2",
+    "ndarray"
+  ],
+  "__stdlib__": {}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/test/test.js b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/test/test.js
new file mode 100644
index 000000000000..289c755bea2f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/ndarray/smeankbn2/test/test.js
@@ -0,0 +1,173 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var Float32Array = require( '@stdlib/array/float32' );
+var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var smeankbn2 = require( '@stdlib/stats/base/ndarray/smeankbn2/lib' );
+
+
+// FUNCTIONS //
+
+/**
+* Returns a one-dimensional ndarray.
+*
+* @private
+* @param {Collection} buffer - underlying data buffer
+* @param {NonNegativeInteger} length - number of indexed elements
+* @param {integer} stride - stride length
+* @param {NonNegativeInteger} offset - index offset
+* @returns {ndarray} one-dimensional ndarray
+*/
+function vector( buffer, length, stride, offset ) {
+	return new ndarray( 'float32', buffer, [ length ], [ stride ], offset, 'row-major' );
+}
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof smeankbn2, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function has an arity of 1', function test( t ) {
+	t.strictEqual( smeankbn2.length, 1, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the function calculates the arithmetic mean of a one-dimensional ndarray', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	v = smeankbn2( [ vector( x, 6, 1, 0 ) ] );
+	t.strictEqual( v, 0.5, 'returns expected value' );
+
+	x = new Float32Array( [ -4.0, -5.0 ] );
+	v = smeankbn2( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( v, -4.5, 'returns expected value' );
+
+	x = new Float32Array( [ -0.0, 0.0, -0.0 ] );
+	v = smeankbn2( [ vector( x, 3, 1, 0 ) ] );
+	t.strictEqual( isPositiveZero( v ), true, 'returns expected value' );
+
+	x = new Float32Array( [ NaN ] );
+	v = smeankbn2( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	x = new Float32Array( [ NaN, NaN ] );
+	v = smeankbn2( [ vector( x, 2, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an empty vector, the function returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array( [] );
+
+	v = smeankbn2( [ vector( x, 0, 1, 0 ) ] );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a vector containing a single element, the function returns that element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array( [ 1.0 ] );
+
+	v = smeankbn2( [ vector( x, 1, 1, 0 ) ] );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-unit strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+
+	v = smeankbn2( [ vector( x, 4, 2, 0 ) ] );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having negative strides', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+
+	v = smeankbn2( [ vector( x, 4, -2, 6 ) ] );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function supports one-dimensional ndarrays having non-zero offsets', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float32Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0   // 3
+	]);
+
+	v = smeankbn2( [ vector( x, 4, 2, 1 ) ] );
+	t.strictEqual( v, 1.25, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/to-json/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/to-json/docs/types/index.d.ts
index 3e2bcb9eb5d8..7e8ea4930deb 100644
--- a/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/to-json/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/ztest/one-sample/results/to-json/docs/types/index.d.ts
@@ -89,7 +89,7 @@ interface Results {
 *     'method': 'One-sample Z-test'
 * };
 *
-* var obj = toJSON( results );
+* var obj = res2json( results );
 * // returns {...}
 */
 declare function res2json( results: Results ): Results;
diff --git a/lib/node_modules/@stdlib/stats/fligner-test/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/fligner-test/docs/types/index.d.ts
index 0d5959258560..3cdbb1dd1545 100644
--- a/lib/node_modules/@stdlib/stats/fligner-test/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/fligner-test/docs/types/index.d.ts
@@ -99,7 +99,7 @@ interface Results {
 *     'b', 'b', 'b', 'b',
 *     'c', 'c', 'c', 'c', 'c'
 * ];
-* varout = flignerTest( arr, {
+* var out = flignerTest( arr, {
 *     'groups': groups
 * });
 * // returns {...}
diff --git a/lib/node_modules/@stdlib/stats/incr/mcv/README.md b/lib/node_modules/@stdlib/stats/incr/mcv/README.md
index 154e5de82597..3f1affca48a9 100644
--- a/lib/node_modules/@stdlib/stats/incr/mcv/README.md
+++ b/lib/node_modules/@stdlib/stats/incr/mcv/README.md
@@ -58,10 +58,14 @@ The [coefficient of variation][coefficient-of-variation] (also known as **relati
 
 <!-- <equation class="equation" label="eq:coefficient_of_variation" align="center" raw="c_v = \frac{s}{\bar{x}}" alt="Equation for the coefficient of variation (CV)."> -->
 
-<div class="equation" align="center" data-raw-text="c_v = \frac{s}{\bar{x}}" data-equation="eq:coefficient_of_variation">
-    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/mcv/docs/img/equation_coefficient_of_variation.svg"Equation for the coefficient of variation (CV).">
+```math
+c_v = \frac{s}{\bar{x}}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="c_v = \frac{s}{\bar{x}}" data-equation="eq:coefficient_of_variation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/mcv/docs/img/equation_coefficient_of_variation.svg" alt="Equation for the coefficient of variation (CV).">
     <br>
-</div>
+</div> -->
 
 <!-- </equation> -->
 
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/README.md b/lib/node_modules/@stdlib/stats/incr/nanmcv/README.md
new file mode 100644
index 000000000000..f9f072110126
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/README.md
@@ -0,0 +1,205 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# incrnanmcv
+
+> Compute a moving [coefficient of variation][coefficient-of-variation] (CV) incrementally, ignoring `NaN` values.
+
+<section class="intro">
+
+For a window of size `W`, the [corrected sample standard deviation][standard-deviation] is defined as
+
+<!-- <equation class="equation" label="eq:corrected_sample_standard_deviation" align="center" raw="s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}" alt="Equation for the corrected sample standard deviation."> -->
+
+```math
+s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="s = \sqrt{\frac{1}{W-1} \sum_{i=0}^{W-1} ( x_i - \bar{x} )^2}" data-equation="eq:corrected_sample_standard_deviation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_corrected_sample_standard_deviation.svg" alt="Equation for the corrected sample standard deviation.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+and the [arithmetic mean][arithmetic-mean] is defined as
+
+<!-- <equation class="equation" label="eq:arithmetic_mean" align="center" raw="\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i" alt="Equation for the arithmetic mean."> -->
+
+```math
+\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i
+```
+
+<!-- <div class="equation" align="center" data-raw-text="\bar{x} = \frac{1}{W} \sum_{i=0}^{W-1} x_i" data-equation="eq:arithmetic_mean">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@4cf17e4e25cc2244d5154bd5d251f4bd023748da/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_arithmetic_mean.svg" alt="Equation for the arithmetic mean.">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+The [coefficient of variation][coefficient-of-variation] (also known as **relative standard deviation**, RSD) is defined as
+
+<!-- <equation class="equation" label="eq:coefficient_of_variation" align="center" raw="c_v = \frac{s}{\bar{x}}" alt="Equation for the coefficient of variation (CV)."> -->
+
+```math
+c_v = \frac{s}{\bar{x}}
+```
+
+<!-- <div class="equation" align="center" data-raw-text="c_v = \frac{s}{\bar{x}}" data-equation="eq:coefficient_of_variation">
+    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@eed6b690d7c37249b04544b3f5fd36ad8eb3187f/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_coefficient_of_variation.svg" alt="Equation for the coefficient of variation (CV).">
+    <br>
+</div> -->
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var incrnanmcv = require( '@stdlib/stats/incr/nanmcv' );
+```
+
+#### incrnanmcv( window\[, mean] )
+
+Returns an accumulator function which incrementally computes a moving [coefficient of variation][coefficient-of-variation].
+
+```javascript
+var accumulator = incrnanmcv( 3 );
+```
+
+The function supports the following parameters:
+
+-   **window**: defines the number of values over which to compute the moving [coefficient of variation][coefficient-of-variation].
+-   **mean**: known mean.
+
+If the mean is already known, provide a `mean` argument.
+
+```javascript
+var accumulator = incrnanmcv( 3, 5.0 );
+```
+
+#### accumulator( \[x] )
+
+If provided an input value `x`, the accumulator function returns an updated accumulated value. If not provided an input value `x`, the accumulator function returns the current accumulated value.
+
+```javascript
+var accumulator = incrnanmcv( 3 );
+
+var cv = accumulator();
+// returns null
+
+// Fill the window...
+cv = accumulator( 2.0 ); // [2.0]
+// returns 0.0
+
+cv = accumulator( NaN ); // [2.0]
+// returns 0.0
+
+cv = accumulator( 3.0 ); // [2.0, 3.0]
+// returns ~0.28
+
+cv = accumulator( 1.0 ); // [2.0, 3.0, 1.0]
+// returns ~0.50
+
+// Window begins sliding...
+cv = accumulator( NaN ); // [2.0, 3.0, 1.0]
+// returns ~0.50
+
+cv = accumulator( 7.0 ); // [3.0, 1.0, 7.0]
+// returns ~0.83
+
+cv = accumulator( 5.0 ); // [1.0, 7.0, 5.0]
+// returns ~0.71
+
+cv = accumulator( NaN ); // [1.0, 7.0, 5.0]
+// returns ~0.71
+
+cv = accumulator();
+// returns ~0.71
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   Input values are not type checked. If non-numeric inputs are possible, you are advised to type check and handle accordingly **before** passing the value to the accumulator function.
+-   As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.
+-   The [coefficient of variation][coefficient-of-variation] is typically computed on nonnegative values. The measure may lack meaning for data which can assume both positive and negative values.
+-   For small and moderately sized samples, the accumulated value tends to be too low and is thus a **biased** estimator. Provided the generating distribution is known (e.g., a normal distribution), you may want to adjust the accumulated value or use an alternative implementation providing an unbiased estimator.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanmcv = require( '@stdlib/stats/incr/nanmcv' );
+
+// Initialize an accumulator with window size 5:
+var accumulator = incrnanmcv( 5 );
+
+// For each simulated datum, update the moving coefficient of variation...
+var i;
+for ( i = 0; i < 100; i++ ) {
+    accumulator( ( randu() < 0.2 ) ? NaN : randu()*100.0 );
+}
+console.log( accumulator() );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[coefficient-of-variation]: https://en.wikipedia.org/wiki/Coefficient_of_variation
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[standard-deviation]: https://en.wikipedia.org/wiki/Standard_deviation
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js
new file mode 100644
index 000000000000..f9e0b14bbac3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/benchmark/benchmark.js
@@ -0,0 +1,91 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isnan = require( '@stdlib/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var incrnanmcv = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var f;
+	var i;
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		f = incrnanmcv( (i%5)+1 );
+		if ( typeof f !== 'function' ) {
+			b.fail( 'should return a function' );
+		}
+	}
+	b.toc();
+	if ( typeof f !== 'function' ) {
+		b.fail( 'should return a function' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::accumulator', function benchmark( b ) {
+	var acc;
+	var v;
+	var i;
+
+	acc = incrnanmcv( 5 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = acc( i+1 );
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( v ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::accumulator,known_mean', function benchmark( b ) {
+	var acc;
+	var v;
+	var i;
+
+	acc = incrnanmcv( 5, 0.5 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = acc( i+1 );
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( v ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_arithmetic_mean.svg b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_arithmetic_mean.svg
new file mode 100644
index 000000000000..1a89a2bfb996
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/img/equation_arithmetic_mean.svg
@@ -0,0 +1,43 @@
+<svg xmlns:xlink="http://www.w3.org/1999/xlink" width="14.426ex" height="7.343ex" style="vertical-align: -3.005ex;" viewBox="0 -1867.7 6211 3161.4" role="img" focusable="false" xmlns="http://www.w3.org/2000/svg" aria-labelledby="MathJax-SVG-1-Title">
+<title id="MathJax-SVG-1-Title">x overbar equals StartFraction 1 Over upper W EndFraction sigma-summation Underscript i equals 0 Overscript upper W minus 1 Endscripts x Subscript i</title>
+<defs aria-hidden="true">
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+</g>
+</g>
+</g>
+</svg>
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/repl.txt b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/repl.txt
new file mode 100644
index 000000000000..2304094cedd8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/repl.txt
@@ -0,0 +1,49 @@
+
+{{alias}}( W[, mean] )
+    Returns an accumulator function which incrementally computes a moving
+    coefficient of variation (CV), ignoring `NaN` values.
+
+    The `W` parameter defines the number of values over which to compute the
+    moving coefficient of variation.
+
+    If provided a value, the accumulator function returns an updated moving
+    coefficient of variation. If not provided a value, the accumulator function
+    returns the current moving coefficient of variation.
+
+    As `W` values are needed to fill the window buffer, the first `W-1` returned
+    values are calculated from smaller sample sizes. Until the window is full,
+    each returned value is calculated from all provided values which are not
+    `NaN`.
+
+    Parameters
+    ----------
+    W: integer
+        Window size.
+
+    mean: number (optional)
+        Known mean.
+
+    Returns
+    -------
+    acc: Function
+        Accumulator function.
+
+    Examples
+    --------
+    > var accumulator = {{alias}}( 3 );
+    > var cv = accumulator()
+    null
+    > cv = accumulator( 2.0 )
+    0.0
+    > cv = accumulator( 1.0 )
+    ~0.47
+    > cv = accumulator( 3.0 )
+    0.5
+    > cv = accumulator( 7.0 )
+    ~0.83
+    > cv = accumulator()
+    ~0.83
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/index.d.ts
new file mode 100644
index 000000000000..4f42c4d19b55
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/index.d.ts
@@ -0,0 +1,79 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+/**
+* If provided a value, returns an updated accumulated value; otherwise, returns the current accumulated value.
+*
+* @param x - value
+* @returns accumulated value or null
+*/
+type accumulator = ( x?: number ) => number | null;
+
+/**
+* Returns an accumulator function which incrementally computes a moving coefficient of variation (CV), ignoring `NaN` values.
+*
+* ## Notes
+*
+* -   The `W` parameter defines the number of values over which to compute the moving coefficient of variation.
+* -   As `W` values are needed to fill the window buffer, the first `W-1` returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values which are not `NaN`.
+*
+* @param W - window size
+* @param mean - mean value
+* @throws first argument must be a positive integer
+* @returns accumulator function
+*
+* @example
+* var accumulator = incrnanmcv( 3 );
+*
+* var cv = accumulator();
+* // returns null
+*
+* cv = accumulator( 2.0 );
+* // returns 0.0
+*
+* cv = accumulator( NaN );
+* // returns 0.0
+*
+* cv = accumulator( 1.0 );
+* // returns ~0.47
+*
+* cv = accumulator( 3.0 );
+* // returns 0.5
+*
+* cv = accumulator( NaN );
+* // returns 0.5
+*
+* cv = accumulator( 7.0 );
+* // returns ~0.83
+*
+* cv = accumulator();
+* // returns ~0.83
+*
+* @example
+* var accumulator = incrnanmcv( 3, 2.0 );
+*/
+declare function incrnanmcv( W: number, mean?: number ): accumulator;
+
+
+// EXPORTS //
+
+export = incrnanmcv;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/test.ts b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/test.ts
new file mode 100644
index 000000000000..132e1f64ffc0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/docs/types/test.ts
@@ -0,0 +1,67 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import incrnanmcv = require( './index' );
+
+
+// TESTS //
+
+// The function returns an accumulator function...
+{
+	incrnanmcv( 3 ); // $ExpectType accumulator
+	incrnanmcv( 3, 0.0 ); // $ExpectType accumulator
+}
+
+// The compiler throws an error if the function is provided an argument that is not a number...
+{
+	incrnanmcv( '5' ); // $ExpectError
+	incrnanmcv( true ); // $ExpectError
+	incrnanmcv( false ); // $ExpectError
+	incrnanmcv( null ); // $ExpectError
+	incrnanmcv( [] ); // $ExpectError
+	incrnanmcv( {} ); // $ExpectError
+	incrnanmcv( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an invalid number of arguments...
+{
+	incrnanmcv(); // $ExpectError
+	incrnanmcv( 2, 3, 1 ); // $ExpectError
+}
+
+// The function returns an accumulator function which returns an accumulated result...
+{
+	const acc = incrnanmcv( 3 );
+
+	acc(); // $ExpectType number | null
+	acc( 3.14 ); // $ExpectType number | null
+	acc( NaN ); // $ExpectType number | null
+}
+
+// The compiler throws an error if the returned accumulator function is provided invalid arguments...
+{
+	const acc = incrnanmcv( 3 );
+
+	acc( '5' ); // $ExpectError
+	acc( true ); // $ExpectError
+	acc( false ); // $ExpectError
+	acc( null ); // $ExpectError
+	acc( [] ); // $ExpectError
+	acc( {} ); // $ExpectError
+	acc( ( x: number ): number => x ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/examples/index.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/examples/index.js
new file mode 100644
index 000000000000..5c7d40f872af
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/examples/index.js
@@ -0,0 +1,32 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var randu = require( '@stdlib/random/base/randu' );
+var incrnanmcv = require( './../lib' );
+
+// Initialize an accumulator with window size 5:
+var accumulator = incrnanmcv( 5 );
+
+// For each simulated datum, update the moving coefficient of variation...
+var i;
+for ( i = 0; i < 100; i++ ) {
+	accumulator( ( randu() < 0.2 ) ? NaN : randu()*100.0 );
+}
+console.log( accumulator() );
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/index.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/index.js
new file mode 100644
index 000000000000..6cc3c404d56b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/index.js
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Compute a moving coefficient of variation (CV) incrementally, ignoring `NaN` values.
+*
+* @module @stdlib/stats/incr/nanmcv
+*
+* @example
+* var incrnanmcv = require( '@stdlib/stats/incr/nanmcv' );
+*
+* var accumulator = incrnanmcv( 3 );
+*
+* var cv = accumulator();
+* // returns null
+*
+* cv = accumulator( 2.0 );
+* // returns 0.0
+*
+* cv = accumulator( NaN );
+* // returns 0.0
+*
+* cv = accumulator( 1.0 );
+* // returns ~0.47
+*
+* cv = accumulator( 3.0 );
+* // returns 0.5
+*
+* cv = accumulator( 7.0 );
+* // returns ~0.83
+*
+* cv = accumulator();
+* // returns ~0.83
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/main.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/main.js
new file mode 100644
index 000000000000..7c75599199fa
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/lib/main.js
@@ -0,0 +1,92 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var incrmcv = require( '@stdlib/stats/incr/mcv' );
+
+
+// MAIN //
+
+/**
+* Returns an accumulator function which incrementally computes a moving coefficient of variation (CV), ignoring `NaN` values.
+*
+* @param {PositiveInteger} W - window size
+* @param {number} [mean] - mean value
+* @throws {TypeError} first argument must be a positive integer
+* @throws {TypeError} second argument must be a number
+* @returns {Function} accumulator function
+*
+* @example
+* var accumulator = incrnanmcv( 3 );
+*
+* var cv = accumulator();
+* // returns null
+*
+* cv = accumulator( 2.0 );
+* // returns 0.0
+*
+* cv = accumulator( NaN );
+* // returns 0.0
+*
+* cv = accumulator( 1.0 );
+* // returns ~0.47
+*
+* cv = accumulator( 3.0 );
+* // returns 0.5
+*
+* cv = accumulator( 7.0 );
+* // returns ~0.83
+*
+* cv = accumulator();
+* // returns ~0.83
+*
+* @example
+* var accumulator = incrnanmcv( 3, 2.0 );
+*/
+function incrnanmcv( W, mean ) {
+	var acc;
+	if ( arguments.length > 1 ) {
+		acc = incrmcv( W, mean );
+	} else {
+		acc = incrmcv( W );
+	}
+	return accumulator;
+
+	/**
+	* If provided a value, the accumulator function returns an updated accumulated value. If not provided a value, the accumulator function returns the current accumulated value.
+	*
+	* @private
+	* @param {number} [x] - input value
+	* @returns {(number|null)} accumulated value or null
+	*/
+	function accumulator( x ) {
+		if ( arguments.length === 0 || isnan( x ) ) {
+			return acc();
+		}
+		return acc( x );
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = incrnanmcv;
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/package.json b/lib/node_modules/@stdlib/stats/incr/nanmcv/package.json
new file mode 100644
index 000000000000..5a7262b38a23
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/package.json
@@ -0,0 +1,77 @@
+{
+  "name": "@stdlib/stats/incr/nanmcv",
+  "version": "0.0.0",
+  "description": "Compute a moving coefficient of variation (CV) incrementally, ignoring NaN values.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "stdev",
+    "std",
+    "variance",
+    "var",
+    "standard",
+    "deviation",
+    "dispersion",
+    "relative",
+    "rsd",
+    "cv",
+    "mean",
+    "ratio",
+    "incremental",
+    "accumulator",
+    "sliding window",
+    "sliding",
+    "window",
+    "moving"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/incr/nanmcv/test/test.js b/lib/node_modules/@stdlib/stats/incr/nanmcv/test/test.js
new file mode 100644
index 000000000000..122963bc347a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/incr/nanmcv/test/test.js
@@ -0,0 +1,576 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var randu = require( '@stdlib/random/base/randu' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var sqrt = require( '@stdlib/math/base/special/sqrt' );
+var zeros = require( '@stdlib/array/base/zeros' );
+var incrnanmcv = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof incrnanmcv, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function throws an error if not provided a positive integer for the window size', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		-5.0,
+		0.0,
+		3.14,
+		true,
+		null,
+		void 0,
+		NaN,
+		[],
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			incrnanmcv( value );
+		};
+	}
+});
+
+tape( 'the function throws an error if not provided a positive integer for the window size (known mean)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		-5.0,
+		0.0,
+		3.14,
+		true,
+		null,
+		void 0,
+		NaN,
+		[],
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			incrnanmcv( value, 3.0 );
+		};
+	}
+});
+
+tape( 'the function throws an error if not provided a number as the mean value', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[i] ), TypeError, 'throws an error when provided '+values[i] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			incrnanmcv( 3, value );
+		};
+	}
+});
+
+tape( 'the function returns an accumulator function', function test( t ) {
+	t.strictEqual( typeof incrnanmcv( 3 ), 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function returns an accumulator function (known mean)', function test( t ) {
+	t.strictEqual( typeof incrnanmcv( 3, 3.0 ), 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'the accumulator function computes a moving coefficient of variation incrementally', function test( t ) {
+	var expected;
+	var actual;
+	var data;
+	var acc;
+	var N;
+	var i;
+
+	data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ];
+	N = data.length;
+
+	expected = [
+		0.0/2.0,
+		sqrt( 0.5 )/2.5,
+		sqrt( 1.0 )/3.0,
+		sqrt( 7.0 )/2.0,
+		sqrt( 7.0 )/2.0,
+		sqrt( 4.0 )/1.0
+	];
+
+	acc = incrnanmcv( 3 );
+
+	actual = zeros( N );
+	for ( i = 0; i < N; i++ ) {
+		actual[ i ] = acc( data[ i ] );
+	}
+	t.deepEqual( actual, expected, 'returns expected results' );
+	t.end();
+});
+
+tape( 'the accumulator function computes a moving coefficient of variation incrementally (known mean)', function test( t ) {
+	var expected;
+	var actual;
+	var data;
+	var acc;
+	var N;
+	var i;
+
+	data = [ 2.0, 3.0, 4.0, -1.0, 3.0, 1.0 ];
+	N = data.length;
+
+	acc = incrnanmcv( 3, 2.0 );
+
+	actual = zeros( N );
+	for ( i = 0; i < N; i++ ) {
+		actual[ i ] = acc( data[ i ] );
+	}
+	expected = [
+		0.0/2.0,
+		sqrt( 0.5 )/2.0,
+		sqrt( 1.6666666666666667 )/2.0,
+		sqrt( 4.666666666666667 )/2.0,
+		sqrt( 4.666666666666667 )/2.0,
+		sqrt( 3.6666666666666665 )/2.0
+	];
+	t.deepEqual( actual, expected, 'returns expected results' );
+	t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current accumulated value', function test( t ) {
+	var expected;
+	var actual;
+	var delta;
+	var data;
+	var tol;
+	var acc;
+	var i;
+
+	data = [ 2.0, 3.0, 10.0 ];
+	acc = incrnanmcv( 3 );
+	for ( i = 0; i < data.length-1; i++ ) {
+		acc( data[ i ] );
+	}
+	t.strictEqual( acc(), sqrt( 0.5 )/2.5, 'returns expected value' );
+
+	acc( data[ data.length-1 ] );
+
+	expected = sqrt( 19.0 )/5.0;
+	actual = acc();
+	delta = abs( actual - expected );
+	tol = EPS * expected;
+
+	t.strictEqual( delta < tol, true, 'expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+	t.end();
+});
+
+tape( 'if not provided an input value, the accumulator function returns the current accumulated value (known mean)', function test( t ) {
+	var expected;
+	var actual;
+	var delta;
+	var data;
+	var tol;
+	var acc;
+	var i;
+
+	data = [ 2.0, 3.0, 10.0 ];
+	acc = incrnanmcv( 3, 5.0 );
+	for ( i = 0; i < data.length-1; i++ ) {
+		acc( data[ i ] );
+	}
+	t.strictEqual( acc(), sqrt( 6.5 )/5.0, 'returns expected value' );
+
+	acc( data[ data.length-1 ] );
+
+	expected = sqrt( 12.666666666666666 )/5.0;
+	actual = acc();
+	delta = abs( actual - expected );
+	tol = EPS * expected;
+
+	t.strictEqual( delta < tol, true, 'expected: '+expected+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+	t.end();
+});
+
+tape( 'if data has yet to be provided, the accumulator function returns `null`', function test( t ) {
+	var acc = incrnanmcv( 3 );
+	t.strictEqual( acc(), null, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if data has yet to be provided, the accumulator function returns `null` (known mean)', function test( t ) {
+	var acc = incrnanmcv( 3, 3.0 );
+	t.strictEqual( acc(), null, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if only one datum has been provided and the mean is unknown, the accumulator function returns `0`', function test( t ) {
+	var acc = incrnanmcv( 3 );
+	acc( 2.0 );
+	t.strictEqual( acc(), 0.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if only one datum has been provided and the mean is known, the accumulator function may not return `0`', function test( t ) {
+	var acc = incrnanmcv( 3, 30 );
+	acc( 2.0 );
+	t.notEqual( acc(), 0.0, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if the window size is `1` and the mean is unknown, the accumulator function always returns `0`', function test( t ) {
+	var acc;
+	var cv;
+	var i;
+
+	acc = incrnanmcv( 1 );
+	for ( i = 0; i < 100; i++ ) {
+		cv = acc( randu() * 100.0 );
+		t.strictEqual( cv, 0.0, 'returns expected value' );
+	}
+	t.end();
+});
+
+tape( 'if the window size is `1` and the mean is known, the accumulator function may not always return `0`', function test( t ) {
+	var acc;
+	var cv;
+	var i;
+
+	acc = incrnanmcv( 1, 500.0 ); // mean is outside the range of simulated values so the variance should never be zero
+	for ( i = 0; i < 100; i++ ) {
+		cv = acc( randu() * 100.0 );
+		t.notEqual( cv, 0.0, 'returns expected value' );
+	}
+	t.end();
+});
+
+tape( 'if provided `NaN`, the value is ignored (unknown mean)', function test( t ) {
+	var expected;
+	var actual;
+	var delta;
+	var data;
+	var acc;
+	var tol;
+	var i;
+
+	acc = incrnanmcv( 3 );
+
+	data = [
+		NaN,
+		3.2,
+		3.0,
+		NaN,
+		1.66,
+		2.72,
+		1.41,
+		NaN,
+		3.8,
+		10.0,
+		1.5,
+		NaN,
+		1.71,
+		3.66,
+		NaN,
+		NaN,
+		NaN,
+		NaN,
+		3.0
+	];
+
+	expected = [
+		null,                 // []                 (NaN ignored)
+		0.0,                  // [3.2]
+		0.045619792334616015, // [3.2, 3.0]
+		0.045619792334616015, // [3.2, 3.0]         (NaN ignored)
+		0.31960948725890576,  // [3.2, 3.0, 1.66]
+		0.28732678125320804,  // [3.0, 1.66, 2.72]
+		0.360355151282696,    // [1.66, 2.72, 1.41]
+		0.360355151282696,    // [1.66, 2.72, 1.41] (NaN ignored)
+		0.4527779582477939,   // [2.72, 1.41, 3.8]
+		0.8744748938856596,   // [1.41, 3.8, 10.0]
+		0.8620763896855141,   // [3.8, 10.0, 1.5]
+		0.8620763896855141,   // [3.8, 10.0, 1.5]   (NaN ignored)
+		1.1009824477893335,   // [10.0, 1.5, 1.71]
+		0.5201274829686575,   // [1.5, 1.71, 3.66]
+		0.5201274829686575,   // [1.5, 1.71, 3.66]  (NaN ignored)
+		0.5201274829686575,   // [1.5, 1.71, 3.66]  (NaN ignored)
+		0.5201274829686575,   // [1.5, 1.71, 3.66]  (NaN ignored)
+		0.5201274829686575,   // [1.5, 1.71, 3.66]  (NaN ignored)
+		0.35548979042616236   // [1.71, 3.66, 3.0]
+	];
+
+	for ( i = 0; i < data.length; i++ ) {
+		actual = acc( data[ i ] );
+		if ( expected[ i ] === null ) {
+			t.strictEqual( actual, null, 'returns expected value for window '+i );
+			t.strictEqual( acc(), null, 'returns expected value for window '+i );
+		} else {
+			delta = abs( actual - expected[ i ] );
+			tol = EPS * expected[ i ];
+			t.strictEqual( delta <= tol, true, 'expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+			t.strictEqual( acc(), actual, 'returns expected value for window '+i );
+		}
+	}
+	t.end();
+});
+
+tape( 'if provided `NaN`, the value is ignored (known mean)', function test( t ) {
+	var expected;
+	var actual;
+	var delta;
+	var data;
+	var acc;
+	var tol;
+	var i;
+
+	acc = incrnanmcv( 3, 3.14 );
+
+	data = [
+		NaN,
+		3.14,
+		2.5,
+		NaN,
+		4.0,
+		5.5,
+		3.0,
+		NaN,
+		2.2,
+		7.7,
+		4.4,
+		NaN,
+		3.3,
+		6.6,
+		NaN,
+		NaN,
+		NaN,
+		NaN,
+		3.9
+	];
+
+	expected = [
+		null,                // []                (NaN ignored)
+		0.0,                 // [3.14]
+		0.1441236751463027,  // [3.14, 2.5]
+		0.1441236751463027,  // [3.14, 2.5]       (NaN ignored)
+		0.19710948953515298, // [3.14, 2.5, 4.0]
+		0.47660169366956523, // [2.5, 4.0, 5.5]
+		0.4625624880347849,  // [4.0, 5.5, 3.0]
+		0.4625624880347849,  // [4.0, 5.5, 3.0]   (NaN ignored)
+		0.4677952618338482,  // [5.5, 3.0, 2.2]
+		0.856460952268003,   // [3.0, 2.2, 7.7]
+		0.8868688195149519,  // [2.2, 7.7, 4.4]
+		0.8868688195149519,  // [2.2, 7.7, 4.4]   (NaN ignored)
+		0.8703614427753308,  // [7.7, 4.4, 3.3]
+		0.6776982264009902,  // [4.4, 3.3, 6.6]
+		0.6776982264009902,  // [4.4, 3.3, 6.6]   (NaN ignored)
+		0.6776982264009902,  // [4.4, 3.3, 6.6]   (NaN ignored)
+		0.6776982264009902,  // [4.4, 3.3, 6.6]   (NaN ignored)
+		0.6776982264009902,  // [4.4, 3.3, 6.6]   (NaN ignored)
+		0.6520190246234627   // [3.3, 6.6, 3.9]
+	];
+
+	for ( i = 0; i < data.length; i++ ) {
+		actual = acc( data[ i ] );
+		if ( expected[ i ] === null ) {
+			t.strictEqual( actual, null, 'returns expected value for window '+i );
+			t.strictEqual( acc(), null, 'returns expected value for window '+i );
+		} else {
+			delta = abs( actual - expected[ i ] );
+			tol = EPS * expected[ i ];
+			t.strictEqual( delta <= tol, true, 'expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+			t.strictEqual( acc(), actual, 'returns expected value for window '+i );
+		}
+	}
+	t.end();
+});
+
+tape( 'if provided `NaN`, the value is ignored (unknown mean, W=1)', function test( t ) {
+	var expected;
+	var actual;
+	var data;
+	var acc;
+	var i;
+
+	acc = incrnanmcv( 1 );
+
+	data = [
+		NaN,
+		2.0,
+		3.5,
+		NaN,
+		4.2,
+		3.3,
+		5.5,
+		NaN,
+		1.1,
+		2.2,
+		6.6,
+		NaN,
+		7.7,
+		8.8,
+		NaN,
+		NaN,
+		NaN,
+		NaN,
+		9.9
+	];
+
+	expected = [
+		null, // []      (NaN ignored)
+		0.0,  // [2.0]
+		0.0,  // [3.5]
+		0.0,  // [3.5]   (NaN ignored)
+		0.0,  // [4.2]
+		0.0,  // [3.3]
+		0.0,  // [5.5]
+		0.0,  // [5.5]   (NaN ignored)
+		0.0,  // [1.1]
+		0.0,  // [2.2]
+		0.0,  // [6.6]
+		0.0,  // [6.6]   (NaN ignored)
+		0.0,  // [7.7]
+		0.0,  // [8.8]
+		0.0,  // [8.8]   (NaN ignored)
+		0.0,  // [8.8]   (NaN ignored)
+		0.0,  // [8.8]   (NaN ignored)
+		0.0,  // [8.8]   (NaN ignored)
+		0.0   // [9.9]
+	];
+
+	for ( i = 0; i < data.length; i++ ) {
+		actual = acc( data[ i ] );
+		if ( expected[ i ] === null ) {
+			t.strictEqual( actual, null, 'returns expected value for window '+i );
+			t.strictEqual( acc(), null, 'returns expected value for window '+i );
+		} else {
+			t.strictEqual( actual, expected[ i ], 'returns expected value for window '+i );
+			t.strictEqual( acc(), expected[ i ], 'returns expected value for window '+i );
+		}
+	}
+	t.end();
+});
+
+tape( 'if provided `NaN`, the value is ignored (known mean, W=1)', function test( t ) {
+	var expected;
+	var actual;
+	var delta;
+	var data;
+	var acc;
+	var tol;
+	var i;
+
+	acc = incrnanmcv( 1, 3.14 );
+
+	data = [
+		NaN,
+		3.14,
+		4.0,
+		NaN,
+		2.0,
+		5.0,
+		6.0,
+		NaN,
+		3.5,
+		2.5,
+		1.5,
+		NaN,
+		4.5,
+		5.5,
+		NaN,
+		NaN,
+		NaN,
+		NaN,
+		2.2
+	];
+
+	expected = [
+		null,                // []      (NaN ignored)
+		0.0,                 // [3.14]
+		0.2738853503184713,  // [4.0]
+		0.2738853503184713,  // [4.0]   (NaN ignored)
+		0.36305732484076436, // [2.0]
+		0.5923566878980892,  // [5.0]
+		0.9108280254777069,  // [6.0]
+		0.9108280254777069,  // [6.0]   (NaN ignored)
+		0.1146496815286624,  // [3.5]
+		0.20382165605095545, // [2.5]
+		0.5222929936305732,  // [1.5]
+		0.5222929936305732,  // [1.5]   (NaN ignored)
+		0.4331210191082802,  // [4.5]
+		0.751592356687898,   // [5.5]
+		0.751592356687898,   // [5.5]   (NaN ignored)
+		0.751592356687898,   // [5.5]   (NaN ignored)
+		0.751592356687898,   // [5.5]   (NaN ignored)
+		0.751592356687898,   // [5.5]   (NaN ignored)
+		0.29936305732484053  // [2.2]
+	];
+
+	for ( i = 0; i < data.length; i++ ) {
+		actual = acc( data[ i ] );
+		if ( expected[ i ] === null ) {
+			t.strictEqual( actual, null, 'returns expected value for window '+i );
+			t.strictEqual( acc(), null, 'returns expected value for window '+i );
+		} else {
+			delta = abs( actual - expected[ i ] );
+			tol = EPS * expected[ i ];
+			t.strictEqual( delta <= tol, true, 'expected: '+expected[i]+'. actual: '+actual+'. tol: '+tol+'. delta: '+delta+'.' );
+			t.strictEqual( acc(), actual, 'returns expected value for window '+i );
+		}
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/kruskal-test/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/kruskal-test/docs/types/index.d.ts
index 5180abf910b8..e481119117ba 100644
--- a/lib/node_modules/@stdlib/stats/kruskal-test/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/kruskal-test/docs/types/index.d.ts
@@ -99,7 +99,7 @@ interface Results {
 *     'b', 'b', 'b', 'b',
 *     'c', 'c', 'c', 'c', 'c'
 * ];
-* varout = kruskalTest( arr, {
+* var out = kruskalTest( arr, {
 *     'groups': groups
 * });
 * // returns {...}
diff --git a/lib/node_modules/@stdlib/stats/strided/dmeanpw/manifest.json b/lib/node_modules/@stdlib/stats/strided/dmeanpw/manifest.json
index 455803ffaf83..314a0404b4b0 100644
--- a/lib/node_modules/@stdlib/stats/strided/dmeanpw/manifest.json
+++ b/lib/node_modules/@stdlib/stats/strided/dmeanpw/manifest.json
@@ -83,7 +83,7 @@
       ]
     },
     {
-      "task": "",
+      "task": "build",
       "wasm": true,
       "src": [
         "./src/main.c"
diff --git a/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts
index 2f18eb34f715..874bcb3f4a8e 100644
--- a/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/strided/docs/types/index.d.ts
@@ -5917,7 +5917,7 @@ interface Namespace {
 	* @returns results object
 	*
 	* @example
-	* var Results = require( '@stdlib/stats/base/ns.ztest/one-sample/results/float64' );
+	* var Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' );
 	*
 	* var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
 	*
@@ -5929,7 +5929,7 @@ interface Namespace {
 	* // returns true
 	*
 	* @example
-	* var Results = require( '@stdlib/stats/base/ns.ztest/one-sample/results/float64' );
+	* var Results = require( '@stdlib/stats/base/ztest/one-sample/results/float64' );
 	*
 	* var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
 	*
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js
index 16ba68e4b2f9..a2d2b8f50e8d 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/main.js
index c5fc62c85cf8..c95b1f6d83ad 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanors/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -52,6 +54,7 @@ var Routine = require( './routine.js' );
 * // returns 1.25
 */
 var dmeanors = new Routine();
+setReadOnly( dmeanors, 'Module', Module.bind( null ) );
 dmeanors.initializeSync(); // eslint-disable-line node/no-sync
 
 
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md
new file mode 100644
index 000000000000..8d3d0733e578
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/README.md
@@ -0,0 +1,291 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# dmeanpw
+
+> Compute the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' );
+```
+
+#### dmeanpw.main( N, x, strideX )
+
+Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+
+var y = dmeanpw.main( x.length, x, 1 );
+// returns ~0.3333
+```
+
+The function has the following parameters:
+
+-   **N**: number of indexed elements.
+-   **x**: input [`Float64Array`][@stdlib/array/float64].
+-   **strideX**: stride length for `x`.
+
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element in `x`,
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
+
+var y = dmeanpw.main( 4, x, 2 );
+// returns 1.25
+```
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+<!-- eslint-disable stdlib/capitalized-comments -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+var y = dmeanpw.main( 4, x1, 2 );
+// returns 1.25
+```
+
+#### dmeanpw.ndarray( N, x, strideX, offsetX )
+
+Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+
+var y = dmeanpw.ndarray( x.length, x, 1, 0 );
+// returns ~0.3333
+```
+
+The function has the following additional parameters:
+
+-   **offsetX**: starting index for `x`.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access every other element starting from the second element:
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+
+var y = dmeanpw.ndarray( 4, x, 2, 1 );
+// returns 1.25
+```
+
+* * *
+
+### Module
+
+#### dmeanpw.Module( memory )
+
+Returns a new WebAssembly [module wrapper][@stdlib/wasm/module-wrapper] instance which uses the provided WebAssembly [memory][@stdlib/wasm/memory] instance as its underlying memory.
+
+<!-- eslint-disable node/no-sync -->
+
+```javascript
+var Memory = require( '@stdlib/wasm/memory' );
+
+// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+var mem = new Memory({
+    'initial': 10,
+    'maximum': 100
+});
+
+// Create a new routine:
+var mod = new dmeanpw.Module( mem );
+// returns <Module>
+
+// Initialize the routine:
+mod.initializeSync();
+```
+
+#### dmeanpw.Module.prototype.main( N, xp, sx )
+
+Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation.
+
+<!-- eslint-disable node/no-sync -->
+
+```javascript
+var Memory = require( '@stdlib/wasm/memory' );
+var oneTo = require( '@stdlib/array/one-to' );
+
+// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+var mem = new Memory({
+    'initial': 10,
+    'maximum': 100
+});
+
+// Create a new routine:
+var mod = new dmeanpw.Module( mem );
+// returns <Module>
+
+// Initialize the routine:
+mod.initializeSync();
+
+// Define a vector data type:
+var dtype = 'float64';
+
+// Specify a vector length:
+var N = 3;
+
+// Define a pointer (i.e., byte offset) for storing the input vector:
+var xptr = 0;
+
+// Write vector values to module memory:
+mod.write( xptr, oneTo( N, dtype ) );
+
+// Perform computation:
+var y = mod.main( N, xptr, 1 );
+// returns 2.0
+```
+
+The function has the following parameters:
+
+-   **N**: number of indexed elements.
+-   **xp**: input [`Float64Array`][@stdlib/array/float64] pointer (i.e., byte offset).
+-   **sx**: stride length for `x`.
+
+#### dmeanpw.Module.prototype.ndarray( N, alpha, xp, sx, ox )
+
+Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+
+<!-- eslint-disable node/no-sync -->
+
+```javascript
+var Memory = require( '@stdlib/wasm/memory' );
+var oneTo = require( '@stdlib/array/one-to' );
+
+// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+var mem = new Memory({
+    'initial': 10,
+    'maximum': 100
+});
+
+// Create a new routine:
+var mod = new dmeanpw.Module( mem );
+// returns <Module>
+
+// Initialize the routine:
+mod.initializeSync();
+
+// Define a vector data type:
+var dtype = 'float64';
+
+// Specify a vector length:
+var N = 3;
+
+// Define a pointer (i.e., byte offset) for storing the input vector:
+var xptr = 0;
+
+// Write vector values to module memory:
+mod.write( xptr, oneTo( N, dtype ) );
+
+// Perform computation:
+var y = mod.ndarray( N, xptr, 1, 0 );
+// returns 2.0
+```
+
+The function has the following additional parameters:
+
+-   **ox**: starting index for `x`.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+* * *
+
+## Notes
+
+-   If `N <= 0`, both `main` and `ndarray` methods return `0.0`.
+-   This package implements routines using WebAssembly. When provided arrays which are not allocated on a `dmeanpw` module memory instance, data must be explicitly copied to module memory prior to computation. Data movement may entail a performance cost, and, thus, if you are using arrays external to module memory, you should prefer using [`@stdlib/stats/strided/dmeanpw`][@stdlib/stats/strided/dmeanpw]. However, if working with arrays which are allocated and explicitly managed on module memory, you can achieve better performance when compared to the pure JavaScript implementations found in [`@stdlib/stats/strided/dmeanpw`][@stdlib/stats/strided/dmeanpw]. Beware that such performance gains may come at the cost of additional complexity when having to perform manual memory management. Choosing between implementations depends heavily on the particular needs and constraints of your application, with no one choice universally better than the other.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+* * *
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' );
+
+var opts = {
+    'dtype': 'float64'
+};
+var x = discreteUniform( 10, 0, 100, opts );
+console.log( x );
+
+var y = dmeanpw.ndarray( x.length, x, 1, 0 );
+console.log( y );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[arithmetic-mean]: https://en.wikipedia.org/wiki/Arithmetic_mean
+
+[@stdlib/array/float64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/float64
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[@stdlib/wasm/memory]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/wasm/memory
+
+[@stdlib/wasm/module-wrapper]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/wasm/module-wrapper
+
+[@stdlib/stats/strided/dmeanpw]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/stats/strided/dmeanpw
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js
new file mode 100644
index 000000000000..ed8fc2105b8d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.js
@@ -0,0 +1,106 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dmeanpw = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasWebAssemblySupport()
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -10.0, 10.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dmeanpw.main( x.length, x, 1 );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js
new file mode 100644
index 000000000000..17db603bc1ea
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.js
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var Memory = require( '@stdlib/wasm/memory' );
+var pkg = require( './../package.json' ).name;
+var dmeanpw = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasWebAssemblySupport()
+};
+
+
+// MAIN //
+
+bench( pkg+':Module:constructor', opts, function benchmark( b ) {
+	var values;
+	var o;
+	var v;
+	var i;
+
+	o = {
+		'initial': 0
+	};
+	values = [
+		new Memory( o ),
+		new Memory( o )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		v = new dmeanpw.Module( values[ i%values.length ] );
+		if ( typeof v !== 'object' ) {
+			b.fail( 'should return an object' );
+		}
+	}
+	b.toc();
+	if ( typeof v !== 'object' ) {
+		b.fail( 'should return an object' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js
new file mode 100644
index 000000000000..ed2983f52ac1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.main.js
@@ -0,0 +1,130 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var Memory = require( '@stdlib/wasm/memory' );
+var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dmeanpw = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasWebAssemblySupport()
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var xptr;
+		var mod;
+		var mem;
+		var nb;
+		var v;
+		var i;
+
+		// Create a new routine interface:
+		mem = new Memory({
+			'initial': 0
+		});
+		mod = new dmeanpw.Module( mem );
+
+		// Initialize the module:
+		mod.initializeSync(); // eslint-disable-line node/no-sync
+
+		// Reallocate the underlying memory to allow storing a vector:
+		nb = bytesPerElement( options.dtype );
+		mod.realloc( len*nb );
+
+		// Define a pointer (i.e., byte offset) to the first vector element:
+		xptr = 0;
+
+		// Write random values to module memory:
+		mod.write( xptr, uniform( len, -10.0, 10.0, options ) );
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = mod.main( len, xptr, 1 );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+'::module,pointers:len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js
new file mode 100644
index 000000000000..7477ce1ef0c4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.module.ndarray.js
@@ -0,0 +1,130 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var Memory = require( '@stdlib/wasm/memory' );
+var bytesPerElement = require( '@stdlib/ndarray/base/bytes-per-element' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dmeanpw = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasWebAssemblySupport()
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var xptr;
+		var mod;
+		var mem;
+		var nb;
+		var v;
+		var i;
+
+		// Create a new routine interface:
+		mem = new Memory({
+			'initial': 0
+		});
+		mod = new dmeanpw.Module( mem );
+
+		// Initialize the module:
+		mod.initializeSync(); // eslint-disable-line node/no-sync
+
+		// Reallocate the underlying memory to allow storing a vector:
+		nb = bytesPerElement( options.dtype );
+		mod.realloc( len*nb );
+
+		// Define a pointer (i.e., byte offset) to the first vector element:
+		xptr = 0;
+
+		// Write random values to module memory:
+		mod.write( xptr, uniform( len, -10.0, 10.0, options ) );
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = mod.ndarray( len, xptr, 1, 0 );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+'::module,pointers:ndarray:len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js
new file mode 100644
index 000000000000..6af793b6f12f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/benchmark/benchmark.ndarray.js
@@ -0,0 +1,106 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var pkg = require( './../package.json' ).name;
+var dmeanpw = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasWebAssemblySupport()
+};
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -10.0, 10.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var v;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			v = dmeanpw.ndarray( x.length, x, 1, 0 );
+			if ( isnan( v ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( v ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( pkg+':ndarray:len='+len, opts, f );
+	}
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/repl.txt b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/repl.txt
new file mode 100644
index 000000000000..a2ef0868918b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/repl.txt
@@ -0,0 +1,498 @@
+
+{{alias}}.main( N, x, strideX )
+    Computes the arithmetic mean of a double-precision floating-point strided
+    array using pairwise summation.
+
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
+
+    Indexing is relative to the first index. To introduce an offset, use a typed
+    array view.
+
+    If `N <= 0`, the function returns `0.0`.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    x: Float64Array
+        Input array.
+
+    strideX: integer
+        Stride length.
+
+    Returns
+    -------
+    out: number
+        The arithmetic mean.
+
+    Examples
+    --------
+    // Standard Usage:
+    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+    > {{alias}}.main( x.length, x, 1 )
+    ~0.3333
+
+    // Using `N` and stride parameters:
+    > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
+    > {{alias}}.main( 3, x, 2 )
+    3
+
+    // Using view offsets:
+    > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
+    > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
+    > {{alias}}.main( 3, x1, 2)
+    ~-0.3333
+
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
+    Computes the arithmetic mean of a double-precision floating-point strided
+    array using pairwise summation and alternative indexing semantics.
+
+    While typed array views mandate a view offset based on the underlying
+    buffer, the offset parameter supports indexing semantics based on a starting
+    index.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    x: Float64Array
+        Input array.
+
+    strideX: integer
+        Stride length.
+
+    offsetX: integer
+        Starting index.
+
+    Returns
+    -------
+    out: number
+        The arithmetic mean.
+
+    Examples
+    --------
+    // Standard Usage:
+    > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 2.0 ] );
+    > {{alias}}.ndarray( x.length, x, 1, 0 )
+    ~0.3333
+
+    // Using offset parameter:
+    > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
+    > {{alias}}.ndarray( 3, x, 2, 1 )
+    ~-0.3333
+
+
+{{alias}}.Module( memory )
+    Returns a new WebAssembly module wrapper which uses the provided WebAssembly
+    memory instance as its underlying memory.
+
+    Parameters
+    ----------
+    memory: Memory
+        WebAssembly memory instance.
+
+    Returns
+    -------
+    mod: Module
+        WebAssembly module wrapper.
+
+    Examples
+    --------
+    // Create a new memory instance:
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+
+    // Create a new routine:
+    > var mod = new {{alias}}.Module( mem );
+
+    // Initialize the routine:
+    > mod.initializeSync();
+
+
+{{alias}}.Module.prototype.binary
+    Read-only property which returns WebAssembly binary code.
+
+    Returns
+    -------
+    out: Uint8Array
+        WebAssembly binary code.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.binary
+    <Uint8Array>
+
+
+{{alias}}.Module.prototype.memory
+    Read-only property which returns WebAssembly memory.
+
+    Returns
+    -------
+    mem: Memory|null
+        WebAssembly memory.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.memory
+    <Memory>
+
+
+{{alias}}.Module.prototype.buffer
+    Read-only property which returns a WebAssembly memory buffer as a
+    Uint8Array.
+
+    Returns
+    -------
+    buf: Uint8Array|null
+        WebAssembly memory buffer.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.buffer
+    <Uint8Array>
+
+
+{{alias}}.Module.prototype.view
+    Read-only property which returns a WebAsssembly memory buffer as a DataView.
+
+    Returns
+    -------
+    view: DataView|null
+        WebAssembly memory view.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.view
+    <DataView>
+
+
+{{alias}}.Module.prototype.exports
+    Read-only property which returns "raw" WebAssembly module exports.
+
+    Returns
+    -------
+    out: Object|null
+        WebAssembly module exports.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.exports
+    {...}
+
+
+{{alias}}.Module.prototype.initialize()
+    Asynchronously initializes a WebAssembly module instance.
+
+    Returns
+    -------
+    p: Promise
+        Promise which resolves upon initializing a WebAssembly module instance.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initialize();
+
+
+{{alias}}.Module.prototype.initializeAsync( clbk )
+    Asynchronously initializes a WebAssembly module instance.
+
+    Parameters
+    ----------
+    clbk: Function
+        Callback to invoke upon initializing a WebAssembly module instance.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > function clbk() { console.log( 'done' ) };
+    > mod.initializeAsync( clbk );
+
+
+{{alias}}.Module.prototype.initializeSync()
+    Synchronously initializes a WebAssembly module instance.
+
+    In web browsers, JavaScript engines may raise an exception when attempting
+    to synchronously compile large WebAssembly binaries due to concerns about
+    blocking the main thread. Hence, to initialize WebAssembly modules having
+    large binaries (e.g., >4KiB), consider using asynchronous initialization
+    methods in browser contexts.
+
+    Returns
+    -------
+    mod: Module
+        Module wrapper instance.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+
+
+{{alias}}.Module.prototype.realloc( nbytes )
+    Reallocates the underlying WebAssembly memory instance to a specified number
+    of bytes.
+
+    WebAssembly memory can only *grow*, not shrink. Hence, if provided a number
+    of bytes which is less than or equal to the size of the current memory, the
+    function does nothing.
+
+    When non-shared memory is resized, the underlying the `ArrayBuffer` is
+    detached, consequently invalidating any associated typed array views. Before
+    resizing non-shared memory, ensure that associated typed array views no
+    longer need byte access and can be garbage collected.
+
+    Parameters
+    ----------
+    nbytes: integer
+        Memory size (in bytes).
+
+    Returns
+    -------
+    bool: boolean
+        Boolean indicating whether the resize operation was successful.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.realloc( 100 )
+    <boolean>
+
+
+{{alias}}.Module.prototype.hasCapacity( byteOffset, values )
+    Returns a boolean indicating whether the underlying WebAssembly memory
+    instance has the capacity to store a provided list of values starting from a
+    specified byte offset.
+
+    Parameters
+    ----------
+    byteOffset: integer
+        Byte offset at which to start writing values.
+
+    values: ArrayLikeObject
+        Input array containing values to write.
+
+    Returns
+    -------
+    bool: boolean
+        Boolean indicating whether the underlying WebAssembly memory instance
+        has enough capacity.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.realloc( 100 );
+    > mod.hasCapacity( 0, [ 1, 2, 3, 4 ] )
+    true
+
+
+{{alias}}.Module.prototype.isView( values )
+    Returns a boolean indicating whether a provided list of values is a view of
+    the underlying memory of the WebAssembly module.
+
+    Parameters
+    ----------
+    values: ArrayLikeObject
+        Input array.
+
+    Returns
+    -------
+    bool: boolean
+        Boolean indicating whether the list is a memory view.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.realloc( 100 );
+    > mod.isView( [ 1, 2, 3, 4 ] )
+    false
+
+
+{{alias}}.Module.prototype.write( byteOffset, values )
+    Writes values to the underlying WebAssembly memory instance.
+
+    The function infers element size (i.e., number of bytes per element) from
+    the data type of the input array. For example, if provided a Float32Array,
+    the function writes each element as a single-precision floating-point number
+    to the underlying WebAssembly memory instance.
+
+    In order to write elements as a different data type, you need to perform an
+    explicit cast *before* calling this method. For example, in order to write
+    single-precision floating-point numbers contained in a Float32Array as
+    signed 32-bit integers, you must first convert the Float32Array to an
+    Int32Array before passing the values to this method.
+
+    If provided an array having an unknown or "generic" data type, elements are
+    written as double-precision floating-point numbers.
+
+    Parameters
+    ----------
+    byteOffset: integer
+        Byte offset at which to start writing values.
+
+    values: ArrayLikeObject
+        Input array containing values to write.
+
+    Returns
+    -------
+    mod: Module
+        Module wrapper instance.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.realloc( 100 );
+    > mod.write( 0, [ 1, 2, 3, 4 ] );
+
+
+{{alias}}.Module.prototype.read( byteOffset, out )
+    Reads values from the underlying WebAssembly memory instance.
+
+    The function infers element size (i.e., number of bytes per element) from
+    the data type of the output array. For example, if provided a Float32Array,
+    the function reads each element as a single-precision floating-point number
+    from the underlying WebAssembly memory instance.
+
+    In order to read elements as a different data type, you need to perform an
+    explicit cast *after* calling this method. For example, in order to read
+    single-precision floating-point numbers contained in a Float32Array as
+    signed 32-bit integers, you must convert the Float32Array to an Int32Array
+    after reading memory values using this method.
+
+    If provided an output array having an unknown or "generic" data type,
+    elements are read as double-precision floating-point numbers.
+
+    Parameters
+    ----------
+    byteOffset: integer
+        Byte offset at which to start reading values.
+
+    out: ArrayLikeObject
+        Output array for storing read values.
+
+    Returns
+    -------
+    mod: Module
+        Module wrapper instance.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 0 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+    > mod.realloc( 100 );
+    > mod.write( 0, [ 1, 2, 3, 4 ] );
+    > var out = [ 0, 0, 0, 0 ];
+    > mod.read( 0, out );
+    > out
+    [ 1, 2, 3, 4 ]
+
+
+{{alias}}.Module.prototype.main( N, xp, sx )
+    Computes the arithmetic mean of a double-precision floating-point strided
+    array using pairwise summation.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    xp: integer
+        Input array pointer (i.e., byte offset).
+
+    sx: integer
+        Stride length.
+
+    Returns
+    -------
+    out: number
+        The arithmetic mean.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 1 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+
+    // Define a "pointer" (i.e., byte offset) into module memory:
+    > var xptr = 0;
+
+    // Write data to module memory:
+    > mod.write( xptr, {{alias:@stdlib/array/one-to}}( 3, 'float64' ) );
+
+    // Perform computation:
+    > var s = mod.main( 3, xptr, 1 )
+    2.0
+
+
+{{alias}}.Module.prototype.ndarray( N, xp, sx, ox )
+    Computes the arithmetic mean of a double-precision floating-point strided
+    array using pairwise summation and alternative indexing semantics.
+
+    Parameters
+    ----------
+    N: integer
+        Number of indexed elements.
+
+    xp: integer
+        Input array pointer (i.e., byte offset).
+
+    sx: integer
+        Stride length.
+
+    ox: integer
+        Starting index.
+
+    Returns
+    -------
+    out: number
+        The arithmetic mean.
+
+    Examples
+    --------
+    > var mem = new {{alias:@stdlib/wasm/memory}}( { 'initial': 1 } );
+    > var mod = new {{alias}}.Module( mem );
+    > mod.initializeSync();
+
+    // Define a "pointer" (i.e., byte offset) into module memory:
+    > var xptr = 0;
+
+    // Write data to module memory:
+    > mod.write( xptr, {{alias:@stdlib/array/one-to}}( 3, 'float64' ) );
+
+    // Perform computation:
+    > var s = mod.ndarray( 3, xptr, 1, 0 )
+    2.0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/index.d.ts
new file mode 100644
index 000000000000..848dcad0ab82
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/index.d.ts
@@ -0,0 +1,316 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/// <reference types="@stdlib/types"/>
+
+import { ModuleWrapper, Memory } from '@stdlib/types/wasm';
+
+/**
+* Interface defining a module constructor which is both "newable" and "callable".
+*/
+interface ModuleConstructor {
+	/**
+	* Returns a new WebAssembly module wrapper instance which uses the provided WebAssembly memory instance as its underlying memory.
+	*
+	* @param mem - WebAssembly memory instance
+	* @returns module wrapper instance
+	*
+	* @example
+	* var Memory = require( '@stdlib/wasm/memory' );
+	* var oneTo = require( '@stdlib/array/one-to' );
+	*
+	* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	* var mem = new Memory({
+	*     'initial': 10,
+	*     'maximum': 100
+	* });
+	*
+	* // Create a new routine:
+	* var mod = new dmeanpw.Module( mem );
+	* // returns <Module>
+	*
+	* // Initialize the routine:
+	* mod.initializeSync();
+	*
+	* // Define a vector data type:
+	* var dtype = 'float64';
+	*
+	* // Specify a vector length:
+	* var N = 3;
+	*
+	* // Define a pointer (i.e., byte offset) to the first vector element:
+	* var xptr = 0;
+	*
+	* // Write vector values to module memory:
+	* mod.write( xptr, oneTo( N, dtype ) );
+	*
+	* // Perform computation:
+	* var y = mod.main( N, xptr, 1 );
+	* // returns 2.0
+	*/
+	new( mem: Memory ): Module; // newable
+
+	/**
+	* Returns a new WebAssembly module wrapper instance which uses the provided WebAssembly memory instance as its underlying memory.
+	*
+	* @param mem - WebAssembly memory instance
+	* @returns module wrapper instance
+	*
+	* @example
+	* var Memory = require( '@stdlib/wasm/memory' );
+	* var oneTo = require( '@stdlib/array/one-to' );
+	*
+	* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	* var mem = new Memory({
+	*     'initial': 10,
+	*     'maximum': 100
+	* });
+	*
+	* // Create a new routine:
+	* var mod = dmeanpw.Module( mem );
+	* // returns <Module>
+	*
+	* // Initialize the routine:
+	* mod.initializeSync();
+	*
+	* // Define a vector data type:
+	* var dtype = 'float64';
+	*
+	* // Specify a vector length:
+	* var N = 3;
+	*
+	* // Define a pointer (i.e., byte offset) to the first vector element:
+	* var xptr = 0;
+	*
+	* // Write vector values to module memory:
+	* mod.write( xptr, oneTo( N, dtype ) );
+	*
+	* // Perform computation:
+	* var y = mod.main( N, xptr, 1 );
+	* // returns 2.0
+	*/
+	( mem: Memory ): Module; // callable
+}
+
+/**
+* Interface describing a `dmeanpw` WebAssembly module.
+*/
+interface Module extends ModuleWrapper {
+	/**
+	* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+	*
+	* @param N - number of indexed elements
+	* @param xptr - input array pointer (i.e., byte offset)
+	* @param strideX - stride length
+	* @returns arithmetic mean
+	*
+	* @example
+	* var Memory = require( '@stdlib/wasm/memory' );
+	* var oneTo = require( '@stdlib/array/one-to' );
+	*
+	* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	* var mem = new Memory({
+	*     'initial': 10,
+	*     'maximum': 100
+	* });
+	*
+	* // Create a new routine:
+	* var mod = new dmeanpw.Module( mem );
+	* // returns <Module>
+	*
+	* // Initialize the routine:
+	* mod.initializeSync();
+	*
+	* // Define a vector data type:
+	* var dtype = 'float64';
+	*
+	* // Specify a vector length:
+	* var N = 3;
+	*
+	* // Define a pointer (i.e., byte offset) to the first vector element:
+	* var xptr = 0;
+	*
+	* // Write vector values to module memory:
+	* mod.write( xptr, oneTo( N, dtype ) );
+	*
+	* // Perform computation:
+	* var y = mod.main( N, xptr, 1 );
+	* // returns 2.0
+	*/
+	main( N: number, xptr: number, strideX: number ): number;
+
+	/**
+	* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+	*
+	* @param N - number of indexed elements
+	* @param xptr - input array pointer (i.e., byte offset)
+	* @param strideX - stride length
+	* @param offsetX - starting index
+	* @returns arithmetic mean
+	*
+	* @example
+	* var Memory = require( '@stdlib/wasm/memory' );
+	* var oneTo = require( '@stdlib/array/one-to' );
+	*
+	* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	* var mem = new Memory({
+	*     'initial': 10,
+	*     'maximum': 100
+	* });
+	*
+	* // Create a new routine:
+	* var mod = new dmeanpw.Module( mem );
+	* // returns <Module>
+	*
+	* // Initialize the routine:
+	* mod.initializeSync();
+	*
+	* // Define a vector data type:
+	* var dtype = 'float64';
+	*
+	* // Specify a vector length:
+	* var N = 3;
+	*
+	* // Define a pointer (i.e., byte offset) to the first vector element:
+	* var xptr = 0;
+	*
+	* // Write vector values to module memory:
+	* mod.write( xptr, oneTo( N, dtype ) );
+	*
+	* // Perform computation:
+	* var y = mod.ndarray( N, xptr, 1, 0 );
+	* // returns 2.0
+	*/
+	ndarray( N: number, xptr: number, strideX: number, offsetX: number ): number;
+}
+
+/**
+* Interface describing `dmeanpw`.
+*/
+interface Routine extends ModuleWrapper {
+	/**
+	* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+	*
+	* @param N - number of indexed elements
+	* @param x - input array
+	* @param strideX - stride length
+	* @returns arithmetic mean
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+	*
+	* var y = dmeanpw.main( 3, x, 1 );
+	* // returns ~0.3333
+	*/
+	main( N: number, x: Float64Array, strideX: number ): number;
+
+	/**
+	* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+	*
+	* @param N - number of indexed elements
+	* @param x - input array
+	* @param strideX - stride length
+	* @param offsetX - starting index
+	* @returns arithmetic mean
+	*
+	* @example
+	* var Float64Array = require( '@stdlib/array/float64' );
+	*
+	* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+	*
+	* var out = dmeanpw.ndarray( 4, x, 2, 1 );
+	* // returns 1.25
+	*/
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
+
+	/**
+	* Returns a new WebAssembly module wrapper instance which uses the provided WebAssembly memory instance as its underlying memory.
+	*
+	* @param mem - WebAssembly memory instance
+	* @returns module wrapper instance
+	*
+	* @example
+	* var Memory = require( '@stdlib/wasm/memory' );
+	* var oneTo = require( '@stdlib/array/one-to' );
+	*
+	* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	* var mem = new Memory({
+	*     'initial': 10,
+	*     'maximum': 100
+	* });
+	*
+	* // Create a new routine:
+	* var mod = new dmeanpw.Module( mem );
+	* // returns <Module>
+	*
+	* // Initialize the routine:
+	* mod.initializeSync();
+	*
+	* // Define a vector data type:
+	* var dtype = 'float64';
+	*
+	* // Specify a vector length:
+	* var N = 3;
+	*
+	* // Define a pointer (i.e., byte offset) to the first vector element:
+	* var xptr = 0;
+	*
+	* // Write vector values to module memory:
+	* mod.write( xptr, oneTo( N, dtype ) );
+	*
+	* // Perform computation:
+	* var y = mod.main( N, xptr, 1 );
+	* // returns 2.0
+	*/
+	Module: ModuleConstructor;
+}
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+*
+* @param N - number of indexed elements
+* @param x - input array
+* @param strideX - stride length
+* @returns arithmetic mean
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+*
+* var y = dmeanpw.main( 3, x, 1 );
+* // returns ~0.3333
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* var y = dmeanpw.ndarray( 4, x, 2, 1 );
+* // returns 1.25
+*/
+declare var dmeanpw: Routine;
+
+
+// EXPORTS //
+
+export = dmeanpw;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/test.ts b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/test.ts
new file mode 100644
index 000000000000..3157ac8b95eb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/docs/types/test.ts
@@ -0,0 +1,347 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable space-in-parens */
+
+import Memory = require( '@stdlib/wasm/memory' );
+import dmeanpw = require( './index' );
+
+
+// TESTS //
+
+// Attached to the main export is a `main` method which returns a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.main( x.length, x, 1 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `main` method is provided a first argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.main( '10', x, 1 ); // $ExpectError
+	dmeanpw.main( true, x, 1 ); // $ExpectError
+	dmeanpw.main( false, x, 1 ); // $ExpectError
+	dmeanpw.main( null, x, 1 ); // $ExpectError
+	dmeanpw.main( undefined, x, 1 ); // $ExpectError
+	dmeanpw.main( [], x, 1 ); // $ExpectError
+	dmeanpw.main( {}, x, 1 ); // $ExpectError
+	dmeanpw.main( ( x: number ): number => x, x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method is provided a second argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.main( x.length, 10, 1 ); // $ExpectError
+	dmeanpw.main( x.length, '10', 1 ); // $ExpectError
+	dmeanpw.main( x.length, true, 1 ); // $ExpectError
+	dmeanpw.main( x.length, false, 1 ); // $ExpectError
+	dmeanpw.main( x.length, null, 1 ); // $ExpectError
+	dmeanpw.main( x.length, undefined, 1 ); // $ExpectError
+	dmeanpw.main( x.length, [], 1 ); // $ExpectError
+	dmeanpw.main( x.length, {}, 1 ); // $ExpectError
+	dmeanpw.main( x.length, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method is provided a third argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.main( x.length, x, '10' ); // $ExpectError
+	dmeanpw.main( x.length, x, true ); // $ExpectError
+	dmeanpw.main( x.length, x, false ); // $ExpectError
+	dmeanpw.main( x.length, x, null ); // $ExpectError
+	dmeanpw.main( x.length, x, undefined ); // $ExpectError
+	dmeanpw.main( x.length, x, [] ); // $ExpectError
+	dmeanpw.main( x.length, x, {} ); // $ExpectError
+	dmeanpw.main( x.length, x, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method is provided an unsupported number of arguments...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.main(); // $ExpectError
+	dmeanpw.main( x.length ); // $ExpectError
+	dmeanpw.main( x.length, x ); // $ExpectError
+	dmeanpw.main( x.length, x, 1, 10 ); // $ExpectError
+}
+
+// Attached to main export is an `ndarray` method which returns a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray( x.length, x, 1, 0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `ndarray` method is provided a first argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray( '10', x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( true, x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( false, x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( null, x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( undefined, x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( [], x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( {}, x, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( ( x: number ): number => x, x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a second argument which is not a Float64Array...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray( x.length, 10, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, '10', 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, true, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, false, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, null, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, undefined, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, [], 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, {}, 1, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a third argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray( x.length, x, '10', 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, true, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, false, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, null, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, undefined, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, [], 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, {}, 0 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray( x.length, x, 1, '10' ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, true ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, false ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, null ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, undefined ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, [] ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, {} ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method is provided an unsupported number of arguments...
+{
+	const x = new Float64Array( 10 );
+
+	dmeanpw.ndarray(); // $ExpectError
+	dmeanpw.ndarray( x.length ); // $ExpectError
+	dmeanpw.ndarray( x.length, x ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1 ); // $ExpectError
+	dmeanpw.ndarray( x.length, x, 1, 0, 10 ); // $ExpectError
+}
+
+// Attached to the main export is a `Module` constructor which returns a module...
+{
+	const mem = new Memory({
+		'initial': 0
+	});
+
+	dmeanpw.Module( mem ); // $ExpectType Module
+}
+
+// The compiler throws an error if the `Module` constructor is not provided a WebAssembly memory instance...
+{
+	dmeanpw.Module( '10' ); // $ExpectError
+	dmeanpw.Module( true ); // $ExpectError
+	dmeanpw.Module( false ); // $ExpectError
+	dmeanpw.Module( null ); // $ExpectError
+	dmeanpw.Module( undefined ); // $ExpectError
+	dmeanpw.Module( [] ); // $ExpectError
+	dmeanpw.Module( {} ); // $ExpectError
+	dmeanpw.Module( ( x: number ): number => x ); // $ExpectError
+}
+
+// The `Module` constructor returns a module instance having a `main` method which returns a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.main( 10, 0, 1 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `main` method of a module instance is provided a first argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.main( '10', 0, 1 ); // $ExpectError
+	mod.main( true, 0, 1 ); // $ExpectError
+	mod.main( false, 0, 1 ); // $ExpectError
+	mod.main( null, 0, 1 ); // $ExpectError
+	mod.main( undefined, 0, 1 ); // $ExpectError
+	mod.main( [], 0, 1 ); // $ExpectError
+	mod.main( {}, 0, 1 ); // $ExpectError
+	mod.main( ( x: number ): number => x, 0, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method of a module instance is provided a second argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.main( 10, '10', 1 ); // $ExpectError
+	mod.main( 10, true, 1 ); // $ExpectError
+	mod.main( 10, false, 1 ); // $ExpectError
+	mod.main( 10, null, 1 ); // $ExpectError
+	mod.main( 10, undefined, 1 ); // $ExpectError
+	mod.main( 10, [], 1 ); // $ExpectError
+	mod.main( 10, {}, 1 ); // $ExpectError
+	mod.main( 10, ( x: number ): number => x, 1 ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method of a module instance is provided a third argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.main( 10, 0, '10' ); // $ExpectError
+	mod.main( 10, 0, true ); // $ExpectError
+	mod.main( 10, 0, false ); // $ExpectError
+	mod.main( 10, 0, null ); // $ExpectError
+	mod.main( 10, 0, undefined ); // $ExpectError
+	mod.main( 10, 0, [] ); // $ExpectError
+	mod.main( 10, 0, {} ); // $ExpectError
+	mod.main( 10, 0, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `main` method of a module instance is provided an unsupported number of arguments...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.main(); // $ExpectError
+	mod.main( 10 ); // $ExpectError
+	mod.main( 10, 0 ); // $ExpectError
+	mod.main( 10, 0, 1, 5 ); // $ExpectError
+}
+
+// The `Module` constructor returns a module instance having an `ndarray` method which returns a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray( 10, 0, 1, 0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the `ndarray` method of a module instance is provided a first argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray( '10', 0, 1, 0 ); // $ExpectError
+	mod.ndarray( true, 0, 1, 0 ); // $ExpectError
+	mod.ndarray( false, 0, 1, 0 ); // $ExpectError
+	mod.ndarray( null, 0, 1, 0 ); // $ExpectError
+	mod.ndarray( undefined, 0, 1, 0 ); // $ExpectError
+	mod.ndarray( [], 0, 1, 0 ); // $ExpectError
+	mod.ndarray( {}, 0, 1, 0 ); // $ExpectError
+	mod.ndarray( ( x: number ): number => x, 0, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method of a module instance is provided a second argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray( 10, '10', 1, 0 ); // $ExpectError
+	mod.ndarray( 10, true, 1, 0 ); // $ExpectError
+	mod.ndarray( 10, false, 1, 0 ); // $ExpectError
+	mod.ndarray( 10, null, 1, 0 ); // $ExpectError
+	mod.ndarray( 10, undefined, 1, 0 ); // $ExpectError
+	mod.ndarray( 10, [], 1, 0 ); // $ExpectError
+	mod.ndarray( 10, {}, 1, 0 ); // $ExpectError
+	mod.ndarray( 10, ( x: number ): number => x, 1, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method of a module instance is provided a third argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray( 10, 0, '10', 0 ); // $ExpectError
+	mod.ndarray( 10, 0, true, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, false, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, null, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, undefined, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, [], 0 ); // $ExpectError
+	mod.ndarray( 10, 0, {}, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, ( x: number ): number => x, 0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method of a module instance is provided a fourth argument which is not a number...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray( 10, 0, 1, '10' ); // $ExpectError
+	mod.ndarray( 10, 0, 1, true ); // $ExpectError
+	mod.ndarray( 10, 0, 1, false ); // $ExpectError
+	mod.ndarray( 10, 0, 1, null ); // $ExpectError
+	mod.ndarray( 10, 0, 1, undefined ); // $ExpectError
+	mod.ndarray( 10, 0, 1, [] ); // $ExpectError
+	mod.ndarray( 10, 0, 1, {} ); // $ExpectError
+	mod.ndarray( 10, 0, 1, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `ndarray` method of a module instance is provided an unsupported number of arguments...
+{
+	const mem = new Memory({
+		'initial': 1
+	});
+	const mod = dmeanpw.Module( mem );
+
+	mod.ndarray(); // $ExpectError
+	mod.ndarray( 10 ); // $ExpectError
+	mod.ndarray( 10, 0 ); // $ExpectError
+	mod.ndarray( 10, 0, 1 ); // $ExpectError
+	mod.ndarray( 10, 0, 1, 0, 10 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/index.js
new file mode 100644
index 000000000000..e8de2cd98c74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/index.js
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var oneTo = require( '@stdlib/array/one-to' );
+var dmeanpw = require( './../lib' );
+
+function main() {
+	if ( !hasWebAssemblySupport() ) {
+		console.error( 'Environment does not support WebAssembly.' );
+		return;
+	}
+	// Specify a vector length:
+	var N = 3;
+
+	// Create an input array:
+	var x = oneTo( N, 'float64' );
+
+	// Perform computation:
+	var v = dmeanpw.ndarray( N, x, 1, 0 );
+
+	// Print the result:
+	console.log( v );
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/little_endian_arrays.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/little_endian_arrays.js
new file mode 100644
index 000000000000..7e7a948e3de6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/little_endian_arrays.js
@@ -0,0 +1,65 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var Memory = require( '@stdlib/wasm/memory' );
+var discreteUniform = require( '@stdlib/random/base/discrete-uniform' ).factory;
+var gfillBy = require( '@stdlib/blas/ext/base/gfill-by' );
+var Float64ArrayLE = require( '@stdlib/array/little-endian-float64' );
+var dmeanpw = require( './../lib' );
+
+function main() {
+	if ( !hasWebAssemblySupport() ) {
+		console.error( 'Environment does not support WebAssembly.' );
+		return;
+	}
+	// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	var mem = new Memory({
+		'initial': 10,
+		'maximum': 100
+	});
+
+	// Create a new routine:
+	var mod = new dmeanpw.Module( mem );
+	// returns <Module>
+
+	// Initialize the routine:
+	mod.initializeSync(); // eslint-disable-line node/no-sync
+
+	// Specify a vector length:
+	var N = 3;
+
+	// Define a pointer (i.e., byte offset) for storing the input vector:
+	var xptr = 0;
+
+	// Create a typed array view over module memory:
+	var x = new Float64ArrayLE( mod.memory.buffer, xptr, N );
+
+	// Write values to module memory:
+	gfillBy( N, x, 1, discreteUniform( -10.0, 10.0 ) );
+
+	// Perform computation:
+	var v = mod.ndarray( N, xptr, 1, 0 );
+
+	// Print the result:
+	console.log( v );
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/module.js
new file mode 100644
index 000000000000..231f4e7f6794
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/examples/module.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var hasWebAssemblySupport = require( '@stdlib/assert/has-wasm-support' );
+var Memory = require( '@stdlib/wasm/memory' );
+var oneTo = require( '@stdlib/array/one-to' );
+var dmeanpw = require( './../lib' );
+
+function main() {
+	if ( !hasWebAssemblySupport() ) {
+		console.error( 'Environment does not support WebAssembly.' );
+		return;
+	}
+	// Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+	var mem = new Memory({
+		'initial': 10,
+		'maximum': 100
+	});
+
+	// Create a new routine:
+	var mod = new dmeanpw.Module( mem );
+	// returns <Module>
+
+	// Initialize the routine:
+	mod.initializeSync(); // eslint-disable-line node/no-sync
+
+	// Define a vector data type:
+	var dtype = 'float64';
+
+	// Specify a vector length:
+	var N = 3;
+
+	// Define a pointer (i.e., byte offset) for storing the input vector:
+	var xptr = 0;
+
+	// Write vector values to module memory:
+	mod.write( xptr, oneTo( N, dtype ) );
+
+	// Perform computation:
+	var v = mod.ndarray( N, xptr, 1, 0 );
+
+	// Print the result:
+	console.log( v );
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.browser.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.browser.js
new file mode 100644
index 000000000000..11adb82dd1e6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.browser.js
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var base64ToUint8Array = require( '@stdlib/string/base/base64-to-uint8array' );
+
+
+// MAIN //
+
+var wasm = base64ToUint8Array( 'AGFzbQEAAAAADwhkeWxpbmsuMAEEAAAAAAETA2AEf39/fwF8YAAAYAN/f38BfAIPAQNlbnYGbWVtb3J5AgAAAwUEAQIAAAdPAxFfX3dhc21fY2FsbF9jdG9ycwAAFnN0ZGxpYl9zdHJpZGVkX2RtZWFucHcAAR5zdGRsaWJfc3RyaWRlZF9kbWVhbnB3X25kYXJyYXkAAgrCBAQDAAELGgAgACABIAJBASAAayACbEEAIAJBAEwbEAILPAAgAEEATARARAAAAAAAAPh/DwsgAEEBR0EAIAIbRQRAIAEgA0EDdGorAwAPCyAAIAEgAiADEAMgALijC+MDAgp/CHwgAEEATARARAAAAAAAAAAADwsCQCAAQQdNBEADQCAAIARGDQIgBEEBaiEEIA4gASADQQN0aisDAKAhDiACIANqIQMMAAsACyAAQYABTQRAIAEgA0EDdGoiBCACQThsIghqKwMAIQ4gBCACQTBsIglqKwMAIQ8gBCACQShsIgpqKwMAIRAgBCACQQV0IgtqKwMAIREgBCACQRhsIgxqKwMAIRIgBCACQQR0Ig1qKwMAIRMgBCACQQN0IgZqKwMAIRQgAEH4AXEhByAEKwMAIRVBCCEFA0AgAyAGaiEDIAUgB09FBEAgDiABIANBA3RqIgQgCGorAwCgIQ4gDyAEIAlqKwMAoCEPIBAgBCAKaisDAKAhECARIAQgC2orAwCgIREgEiAEIAxqKwMAoCESIBMgBCANaisDAKAhEyAUIAQgBmorAwCgIRQgBUEIaiEFIBUgBCsDAKAhFQwBCwsgFSAUoCATIBKgoCARIBCgIA8gDqCgoCEOIAdBAWtBeHFBCGohBANAIAAgBEwNAiAEQQFqIQQgDiABIANBA3RqKwMAoCEOIAIgA2ohAwwACwALIABBAXZB+P///wNxIgQgASACIAMQAyAAIARrIAEgAiADIAIgBGxqEAOgIQ4LIA4L' );
+
+
+// EXPORTS //
+
+module.exports = wasm;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.js
new file mode 100644
index 000000000000..2b83fe651780
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/binary.js
@@ -0,0 +1,34 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var readWASM = require( '@stdlib/fs/read-wasm' ).sync;
+
+
+// MAIN //
+
+var wasm = readWASM( resolve( __dirname, '..', 'src', 'main.wasm' ) );
+
+
+// EXPORTS //
+
+module.exports = wasm;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js
new file mode 100644
index 000000000000..1417ad7a1d58
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/index.js
@@ -0,0 +1,93 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* WebAssembly routine to compute the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+*
+* @module @stdlib/stats/strided/wasm/dmeanpw
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' );
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.main( x.length, x, 1 );
+* // returns ~0.3333
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+* var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' );
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.ndarray( 4, x, 2, 1 );
+* // returns 1.25
+*
+* @example
+* var Memory = require( '@stdlib/wasm/memory' );
+* var oneTo = require( '@stdlib/array/one-to' );
+* var zeros = require( '@stdlib/array/zeros' );
+* var dmeanpw = require( '@stdlib/stats/strided/wasm/dmeanpw' );
+*
+* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+* var mem = new Memory({
+*     'initial': 10,
+*     'maximum': 100
+* });
+*
+* // Create a new routine:
+* var mod = new dmeanpw.Module( mem );
+* // returns <Module>
+*
+* // Initialize the routine:
+* mod.initializeSync();
+*
+* // Define a vector data type:
+* var dtype = 'float64';
+*
+* // Specify a vector length:
+* var N = 3;
+*
+* // Define a pointer (i.e., byte offset) for storing the input vector:
+* var xptr = 0;
+*
+* // Write vector values to module memory:
+* mod.write( xptr, oneTo( N, dtype ) );
+*
+* // Perform computation:
+* var v = mod.main( 3, xptr, 1 );
+* // returns 2.0
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
+
+// exports: { "Module": "main.Module" }
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/main.js
new file mode 100644
index 000000000000..d1ffa0d90dd1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/main.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var Routine = require( './routine.js' );
+var Module = require( './module.js' );
+
+
+// MAIN //
+
+/**
+* WebAssembly routine to compute the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+*
+* @name dmeanpw
+* @type {Routine}
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.main( 3, x, 1 );
+* // returns ~0.3333
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.ndarray( 4, x, 2, 1 );
+* // returns 1.25
+*/
+var dmeanpw = new Routine();
+setReadOnly( dmeanpw, 'Module', Module.bind( null ) );
+dmeanpw.initializeSync(); // eslint-disable-line node/no-sync
+
+
+// EXPORTS //
+
+module.exports = dmeanpw;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/module.js
new file mode 100644
index 000000000000..ba0762ed78b8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/module.js
@@ -0,0 +1,198 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable no-restricted-syntax, no-invalid-this */
+
+'use strict';
+
+// MODULES //
+
+var isWebAssemblyMemory = require( '@stdlib/assert/is-wasm-memory' );
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var inherits = require( '@stdlib/utils/inherit' );
+var WasmModule = require( '@stdlib/wasm/module-wrapper' );
+var format = require( '@stdlib/string/format' );
+var wasmBinary = require( './binary.js' );
+
+
+// MAIN //
+
+/**
+* WebAssembly module wrapper constructor.
+*
+* @constructor
+* @param {Object} memory - WebAssembly memory instance
+* @throws {TypeError} must provide a WebAssembly memory instance
+* @returns {Module} module instance
+*
+* @example
+* var Memory = require( '@stdlib/wasm/memory' );
+* var oneTo = require( '@stdlib/array/one-to' );
+*
+* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+* var mem = new Memory({
+*     'initial': 10,
+*     'maximum': 100
+* });
+*
+* // Create a new routine:
+* var dmeanpw = new Module( mem );
+* // returns <Module>
+*
+* // Initialize the routine:
+* dmeanpw.initializeSync();
+*
+* // Define a vector data type:
+* var dtype = 'float64';
+*
+* // Specify a vector length:
+* var N = 3;
+*
+* // Define a pointer (i.e., byte offset) for storing the input vector:
+* var xptr = 0;
+*
+* // Write vector values to module memory:
+* dmeanpw.write( xptr, oneTo( N, dtype ) );
+*
+* // Perform computation:
+* var v = dmeanpw.main( N, xptr, 1 );
+* // returns 2.0
+*/
+function Module( memory ) {
+	if ( !( this instanceof Module ) ) {
+		return new Module( memory );
+	}
+	if ( !isWebAssemblyMemory( memory ) ) {
+		throw new TypeError( format( 'invalid argument. Must provide a WebAssembly memory instance. Value: `%s`.', memory ) );
+	}
+	// Call the parent constructor:
+	WasmModule.call( this, wasmBinary, memory, {
+		'env': {
+			'memory': memory
+		}
+	});
+
+	return this;
+}
+
+// Inherit from the parent constructor:
+inherits( Module, WasmModule );
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+*
+* @name main
+* @memberof Module.prototype
+* @readonly
+* @type {Function}
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - input array
+* @param {integer} strideX - stride length
+* @returns {number} arithmetic mean
+*
+* @example
+* var Memory = require( '@stdlib/wasm/memory' );
+* var oneTo = require( '@stdlib/array/one-to' );
+*
+* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+* var mem = new Memory({
+*     'initial': 10,
+*     'maximum': 100
+* });
+*
+* // Create a new routine:
+* var dmeanpw = new Module( mem );
+* // returns <Module>
+*
+* // Initialize the routine:
+* dmeanpw.initializeSync();
+*
+* // Define a vector data type:
+* var dtype = 'float64';
+*
+* // Specify a vector length:
+* var N = 3;
+*
+* // Define a pointer (i.e., byte offset) for storing the input vector:
+* var xptr = 0;
+*
+* // Write vector values to module memory:
+* dmeanpw.write( xptr, oneTo( N, dtype ) );
+*
+* // Perform computation:
+* var v = dmeanpw.main( N, xptr, 1 );
+* // returns 2.0
+*/
+setReadOnly( Module.prototype, 'main', function dmeanpw( N, x, strideX ) {
+	return this._instance.exports.stdlib_strided_dmeanpw( N, x, strideX );
+});
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+*
+* @name ndarray
+* @memberof Module.prototype
+* @readonly
+* @type {Function}
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - input array
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
+* @returns {number} arithmetic mean
+*
+* @example
+* var Memory = require( '@stdlib/wasm/memory' );
+* var oneTo = require( '@stdlib/array/one-to' );
+*
+* // Create a new memory instance with an initial size of 10 pages (640KiB) and a maximum size of 100 pages (6.4MiB):
+* var mem = new Memory({
+*     'initial': 10,
+*     'maximum': 100
+* });
+*
+* // Create a new routine:
+* var dmeanpw = new Module( mem );
+* // returns <Module>
+*
+* // Initialize the routine:
+* dmeanpw.initializeSync();
+*
+* // Define a vector data type:
+* var dtype = 'float64';
+*
+* // Specify a vector length:
+* var N = 3;
+*
+* // Define a pointer (i.e., byte offset) for storing the input vector:
+* var xptr = 0;
+*
+* // Write vector values to module memory:
+* dmeanpw.write( xptr, oneTo( N, dtype ) );
+*
+* // Perform computation:
+* var sum = dmeanpw.ndarray( N, xptr, 1, 0 );
+* // returns 2.0
+*/
+setReadOnly( Module.prototype, 'ndarray', function dmeanpw( N, x, strideX, offsetX ) {
+	return this._instance.exports.stdlib_strided_dmeanpw_ndarray( N, x, strideX, offsetX ); // eslint-disable-line max-len
+});
+
+
+// EXPORTS //
+
+module.exports = Module;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/routine.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/routine.js
new file mode 100644
index 000000000000..ca6eea82c2b9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/lib/routine.js
@@ -0,0 +1,166 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable max-len, no-restricted-syntax, no-invalid-this */
+
+'use strict';
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var inherits = require( '@stdlib/utils/inherit' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var Memory = require( '@stdlib/wasm/memory' );
+var arrays2ptrs = require( '@stdlib/wasm/base/arrays2ptrs' );
+var strided2object = require( '@stdlib/wasm/base/strided2object' );
+var Module = require( './module.js' );
+
+
+// MAIN //
+
+/**
+* Routine constructor.
+*
+* @private
+* @constructor
+* @returns {Routine} routine instance
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Create a new routine:
+* var dmeanpw = new Routine();
+*
+* // Initialize the module:
+* dmeanpw.initializeSync();
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.main( 3, x, 1 );
+* // returns ~0.3333
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Create a new routine:
+* var dmeanpw = new Routine();
+*
+* // Initialize the module:
+* dmeanpw.initializeSync();
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* // Perform operation:
+* var sum = dmeanpw.ndarray( 4, x, 2, 1 );
+* // returns 1.25
+*/
+function Routine() {
+	if ( !( this instanceof Routine ) ) {
+		return new Routine();
+	}
+	Module.call( this, new Memory({
+		'initial': 0
+	}));
+	return this;
+}
+
+// Inherit from the parent constructor:
+inherits( Routine, Module );
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation.
+*
+* @name main
+* @memberof Routine.prototype
+* @readonly
+* @type {Function}
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - input array
+* @param {integer} strideX - stride length
+* @returns {number} arithmetic mean
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Create a new routine:
+* var dmeanpw = new Routine();
+*
+* // Initialize the module:
+* dmeanpw.initializeSync();
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.main( 3, x, 1 );
+* // returns ~0.3333
+*/
+setReadOnly( Routine.prototype, 'main', function dmeanpw( N, x, strideX ) {
+	return this.ndarray( N, x, strideX, stride2offset( N, strideX ) );
+});
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array using pairwise summation and alternative indexing semantics.
+*
+* @name ndarray
+* @memberof Routine.prototype
+* @readonly
+* @type {Function}
+* @param {PositiveInteger} N - number of indexed elements
+* @param {Float64Array} x - input array
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
+* @returns {number} arithmetic mean
+*
+* @example
+* var Float64Array = require( '@stdlib/array/float64' );
+*
+* // Create a new routine:
+* var dmeanpw = new Routine();
+*
+* // Initialize the module:
+* dmeanpw.initializeSync();
+*
+* // Define a strided array:
+* var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
+*
+* // Perform operation:
+* var v = dmeanpw.ndarray( 4, x, 2, 1 );
+* // returns 1.25
+*/
+setReadOnly( Routine.prototype, 'ndarray', function dmeanpw( N, x, strideX, offsetX ) {
+	var ptrs;
+	var p0;
+
+	// Convert the input arrays to "pointers" in the module's memory:
+	ptrs = arrays2ptrs( this, [
+		strided2object( N, x, strideX, offsetX )
+	]);
+	p0 = ptrs[ 0 ];
+
+	// Perform computation by calling the corresponding parent method:
+	return Module.prototype.ndarray.call( this, N, p0.ptr, p0.stride, p0.offset );
+});
+
+
+// EXPORTS //
+
+module.exports = Routine;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/manifest.json b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/manifest.json
new file mode 100644
index 000000000000..f2119fbaaa62
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/manifest.json
@@ -0,0 +1,36 @@
+{
+  "options": {},
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "src": [],
+      "include": [],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/strided/dmeanpw"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/package.json b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/package.json
new file mode 100644
index 000000000000..f383ca7ced5f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/package.json
@@ -0,0 +1,84 @@
+{
+  "name": "@stdlib/stats/strided/wasm/dmeanpw",
+  "version": "0.0.0",
+  "description": "Calculate the arithmetic mean of a double-precision floating-point strided array using pairwise summation.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "browser": {
+    "./lib/binary.js": "./lib/binary.browser.js"
+  },
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "scripts": "./scripts",
+    "src": "./src",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "mathematics",
+    "math",
+    "average",
+    "avg",
+    "mean",
+    "arithmetic mean",
+    "central tendency",
+    "pairwise",
+    "summation",
+    "pw",
+    "strided",
+    "strided array",
+    "typed",
+    "array",
+    "float64",
+    "double",
+    "float64array",
+    "webassembly",
+    "wasm"
+  ],
+  "__stdlib__": {
+    "wasm": true
+  }
+}
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/build.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/build.js
new file mode 100644
index 000000000000..66bf9650b6d6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/build.js
@@ -0,0 +1,66 @@
+#!/usr/bin/env node
+
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var readFile = require( '@stdlib/fs/read-file' ).sync;
+var writeFile = require( '@stdlib/fs/write-file' ).sync;
+var replace = require( '@stdlib/string/replace' );
+var currentYear = require( '@stdlib/time/current-year' );
+
+
+// VARIABLES //
+
+var wpath = resolve( __dirname, '..', 'src', 'main.wasm' );
+var tpath = resolve( __dirname, 'template.txt' );
+var opath = resolve( __dirname, '..', 'lib', 'binary.browser.js' );
+
+var opts = {
+	'encoding': 'utf8'
+};
+
+var PLACEHOLDER = '{{WASM_BASE64}}';
+var YEAR = '{{YEAR}}';
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var wasm;
+	var tmpl;
+
+	wasm = readFile( wpath );
+	tmpl = readFile( tpath, opts );
+
+	tmpl = replace( tmpl, YEAR, currentYear().toString() );
+	tmpl = replace( tmpl, PLACEHOLDER, wasm.toString( 'base64' ) );
+
+	writeFile( opath, tmpl, opts );
+}
+
+main();
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/template.txt b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/template.txt
new file mode 100644
index 000000000000..f66cdb9735b1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/scripts/template.txt
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) {{YEAR}} The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var base64ToUint8Array = require( '@stdlib/string/base/base64-to-uint8array' );
+
+
+// MAIN //
+
+var wasm = base64ToUint8Array( '{{WASM_BASE64}}' );
+
+
+// EXPORTS //
+
+module.exports = wasm;
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile
new file mode 100644
index 000000000000..1b1f35347760
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/Makefile
@@ -0,0 +1,243 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+#/
+# To compile targets listed in this Makefile, use top-level project `make`
+# commands rather than commands listed in this Makefile. The top-level project
+# `make` commands will ensure that various environment variables and flags are
+# appropriately set.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files to WebAssembly:
+ifdef EMCC_COMPILER
+	EMCC := $(EMCC_COMPILER)
+else
+	EMCC := emcc
+endif
+
+# Define the program used for compiling WebAssembly files to the WebAssembly text format:
+ifdef WASM2WAT
+	WASM_TO_WAT := $(WASM2WAT)
+else
+	WASM_TO_WAT := wasm2wat
+endif
+
+# Define the program used for compiling WebAssembly files to JavaScript:
+ifdef WASM2JS
+	WASM_TO_JS := $(WASM2JS)
+else
+	WASM_TO_JS := wasm2js
+endif
+
+# Define the path to the Node.js executable:
+ifdef NODE
+	NODEJS := $(NODE)
+else
+	NODEJS := node
+endif
+
+# Define the integer size:
+ifdef CBLAS_INT
+	INT_TYPE := $(CBLAS_INT)
+else
+	INT_TYPE := int32_t
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-flto \
+	-Wall \
+	-pedantic \
+	-D CBLAS_INT=$(INT_TYPE)
+
+# Define the command-line options when compiling C files to WebAssembly and asm.js:
+EMCCFLAGS ?= $(CFLAGS)
+
+# Define shared `emcc` flags:
+EMCC_SHARED_FLAGS := \
+	-Oz \
+	-fwasm-exceptions \
+	-s SUPPORT_LONGJMP=1 \
+	-s SIDE_MODULE=2 \
+	-s EXPORTED_FUNCTIONS="$(shell cat exports.json | tr -d ' \t\n' | sed s/\"/\'/g)"
+
+# Define WebAssembly `emcc` flags:
+EMCC_WASM_FLAGS := $(EMCC_SHARED_FLAGS) \
+	-s WASM=1 \
+	-s WASM_BIGINT=0
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of WebAssembly targets:
+wasm_targets := main.wasm
+
+# List of WebAssembly WAT targets:
+wat_targets := main.wat
+
+# List of WebAssembly JavaScript targets:
+wasm_js_targets := main.wasm.js
+
+# List of other JavaScript targets:
+browser_js_targets := ./../lib/binary.browser.js
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [EMCC_COMPILER] - EMCC compiler (e.g., `emcc`)
+# @param {string} [EMCCFLAGS] - EMCC compiler options
+# @param {string} [WASM2WAT] - WebAssembly text format compiler (e.g., `wasm2wat`)
+# @param {string} [WASM2JS] - WebAssembly JavaScript compiler (e.g., `wasm2js`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: wasm
+
+.PHONY: all
+
+#/
+# Compiles source files to WebAssembly.
+#
+# @param {string} [EMCC_COMPILER] - EMCC compiler (e.g., `emcc`)
+# @param {string} [EMCCFLAGS] - EMCC compiler options
+# @param {string} [WASM2WAT] - WebAssembly text format compiler (e.g., `wasm2wat`)
+# @param {string} [WASM2JS] - WebAssembly JavaScript compiler (e.g., `wasm2js`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make wasm
+#/
+wasm: $(wasm_targets) $(wat_targets) $(browser_js_targets)
+
+.PHONY: wasm
+
+#/
+# Compiles C source files to WebAssembly binaries.
+#
+# @private
+# @param {string} EMCC - EMCC compiler (e.g., `emcc`)
+# @param {string} EMCCFLAGS - EMCC compiler options
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(wasm_targets):
+	$(QUIET) $(EMCC) $(EMCCFLAGS) $(EMCC_WASM_FLAGS) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) $(LIBRARIES)
+
+#/
+# Compiles WebAssembly binary files to the WebAssembly text format.
+#
+# @private
+# @param {string} WASM2WAT - WAT compiler (e.g., `wasm2wat`)
+#/
+$(wat_targets): %.wat: %.wasm
+	$(QUIET) $(WASM_TO_WAT) -o $@ $(wasm_targets)
+
+#/
+# Compiles WebAssembly binary files to JavaScript.
+#
+# @private
+# @param {string} WASM2JS - JavaScript compiler (e.g., `wasm2js`)
+#/
+$(wasm_js_targets): %.wasm.js: %.wasm
+	$(QUIET) $(WASM_TO_JS) -o $@ $(wasm_targets)
+
+#/
+# Generates an inline WebAssembly build for use in bundlers.
+#
+# @private
+# @param {string} NODE - Node.js executable
+#/
+$(browser_js_targets): $(wasm_targets)
+	$(QUIET) $(NODEJS) ./../scripts/build.js
+
+#/
+# Removes generated WebAssembly files.
+#
+# @example
+# make clean-wasm
+#/
+clean-wasm:
+	$(QUIET) -rm -f *.wasm *.wat *.wasm.js $(browser_js_targets)
+
+.PHONY: clean-wasm
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-wasm
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/exports.json b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/exports.json
new file mode 100644
index 000000000000..3d4e33b8b5e2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/exports.json
@@ -0,0 +1,4 @@
+[
+  "_stdlib_strided_dmeanpw",
+  "_stdlib_strided_dmeanpw_ndarray"
+]
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wasm b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wasm
new file mode 100755
index 000000000000..9a56d9271faa
Binary files /dev/null and b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wasm differ
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wat b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wat
new file mode 100644
index 000000000000..71ebe173620f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/src/main.wat
@@ -0,0 +1,338 @@
+;; @license Apache-2.0
+;;
+;; Copyright (c) 2025 The Stdlib Authors.
+;;
+;; Licensed under the Apache License, Version 2.0 (the "License");
+;; you may not use this file except in compliance with the License.
+;; You may obtain a copy of the License at
+;;
+;;    http://www.apache.org/licenses/LICENSE-2.0
+;;
+;; Unless required by applicable law or agreed to in writing, software
+;; distributed under the License is distributed on an "AS IS" BASIS,
+;; WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+;; See the License for the specific language governing permissions and
+;; limitations under the License.
+
+(module
+  (type (;0;) (func (param i32 i32 i32 i32) (result f64)))
+  (type (;1;) (func))
+  (type (;2;) (func (param i32 i32 i32) (result f64)))
+  (import "env" "memory" (memory (;0;) 0))
+  (func (;0;) (type 1)
+    nop)
+  (func (;1;) (type 2) (param i32 i32 i32) (result f64)
+    local.get 0
+    local.get 1
+    local.get 2
+    i32.const 1
+    local.get 0
+    i32.sub
+    local.get 2
+    i32.mul
+    i32.const 0
+    local.get 2
+    i32.const 0
+    i32.le_s
+    select
+    call 2)
+  (func (;2;) (type 0) (param i32 i32 i32 i32) (result f64)
+    local.get 0
+    i32.const 0
+    i32.le_s
+    if  ;; label = @1
+      f64.const nan (;=nan;)
+      return
+    end
+    local.get 0
+    i32.const 1
+    i32.ne
+    i32.const 0
+    local.get 2
+    select
+    i32.eqz
+    if  ;; label = @1
+      local.get 1
+      local.get 3
+      i32.const 3
+      i32.shl
+      i32.add
+      f64.load
+      return
+    end
+    local.get 0
+    local.get 1
+    local.get 2
+    local.get 3
+    call 3
+    local.get 0
+    f64.convert_i32_u
+    f64.div)
+  (func (;3;) (type 0) (param i32 i32 i32 i32) (result f64)
+    (local i32 i32 i32 i32 i32 i32 i32 i32 i32 i32 f64 f64 f64 f64 f64 f64 f64 f64)
+    local.get 0
+    i32.const 0
+    i32.le_s
+    if  ;; label = @1
+      f64.const 0x0p+0 (;=0;)
+      return
+    end
+    block  ;; label = @1
+      local.get 0
+      i32.const 7
+      i32.le_u
+      if  ;; label = @2
+        loop  ;; label = @3
+          local.get 0
+          local.get 4
+          i32.eq
+          br_if 2 (;@1;)
+          local.get 4
+          i32.const 1
+          i32.add
+          local.set 4
+          local.get 14
+          local.get 1
+          local.get 3
+          i32.const 3
+          i32.shl
+          i32.add
+          f64.load
+          f64.add
+          local.set 14
+          local.get 2
+          local.get 3
+          i32.add
+          local.set 3
+          br 0 (;@3;)
+        end
+        unreachable
+      end
+      local.get 0
+      i32.const 128
+      i32.le_u
+      if  ;; label = @2
+        local.get 1
+        local.get 3
+        i32.const 3
+        i32.shl
+        i32.add
+        local.tee 4
+        local.get 2
+        i32.const 56
+        i32.mul
+        local.tee 8
+        i32.add
+        f64.load
+        local.set 14
+        local.get 4
+        local.get 2
+        i32.const 48
+        i32.mul
+        local.tee 9
+        i32.add
+        f64.load
+        local.set 15
+        local.get 4
+        local.get 2
+        i32.const 40
+        i32.mul
+        local.tee 10
+        i32.add
+        f64.load
+        local.set 16
+        local.get 4
+        local.get 2
+        i32.const 5
+        i32.shl
+        local.tee 11
+        i32.add
+        f64.load
+        local.set 17
+        local.get 4
+        local.get 2
+        i32.const 24
+        i32.mul
+        local.tee 12
+        i32.add
+        f64.load
+        local.set 18
+        local.get 4
+        local.get 2
+        i32.const 4
+        i32.shl
+        local.tee 13
+        i32.add
+        f64.load
+        local.set 19
+        local.get 4
+        local.get 2
+        i32.const 3
+        i32.shl
+        local.tee 6
+        i32.add
+        f64.load
+        local.set 20
+        local.get 0
+        i32.const 248
+        i32.and
+        local.set 7
+        local.get 4
+        f64.load
+        local.set 21
+        i32.const 8
+        local.set 5
+        loop  ;; label = @3
+          local.get 3
+          local.get 6
+          i32.add
+          local.set 3
+          local.get 5
+          local.get 7
+          i32.ge_u
+          i32.eqz
+          if  ;; label = @4
+            local.get 14
+            local.get 1
+            local.get 3
+            i32.const 3
+            i32.shl
+            i32.add
+            local.tee 4
+            local.get 8
+            i32.add
+            f64.load
+            f64.add
+            local.set 14
+            local.get 15
+            local.get 4
+            local.get 9
+            i32.add
+            f64.load
+            f64.add
+            local.set 15
+            local.get 16
+            local.get 4
+            local.get 10
+            i32.add
+            f64.load
+            f64.add
+            local.set 16
+            local.get 17
+            local.get 4
+            local.get 11
+            i32.add
+            f64.load
+            f64.add
+            local.set 17
+            local.get 18
+            local.get 4
+            local.get 12
+            i32.add
+            f64.load
+            f64.add
+            local.set 18
+            local.get 19
+            local.get 4
+            local.get 13
+            i32.add
+            f64.load
+            f64.add
+            local.set 19
+            local.get 20
+            local.get 4
+            local.get 6
+            i32.add
+            f64.load
+            f64.add
+            local.set 20
+            local.get 5
+            i32.const 8
+            i32.add
+            local.set 5
+            local.get 21
+            local.get 4
+            f64.load
+            f64.add
+            local.set 21
+            br 1 (;@3;)
+          end
+        end
+        local.get 21
+        local.get 20
+        f64.add
+        local.get 19
+        local.get 18
+        f64.add
+        f64.add
+        local.get 17
+        local.get 16
+        f64.add
+        local.get 15
+        local.get 14
+        f64.add
+        f64.add
+        f64.add
+        local.set 14
+        local.get 7
+        i32.const 1
+        i32.sub
+        i32.const -8
+        i32.and
+        i32.const 8
+        i32.add
+        local.set 4
+        loop  ;; label = @3
+          local.get 0
+          local.get 4
+          i32.le_s
+          br_if 2 (;@1;)
+          local.get 4
+          i32.const 1
+          i32.add
+          local.set 4
+          local.get 14
+          local.get 1
+          local.get 3
+          i32.const 3
+          i32.shl
+          i32.add
+          f64.load
+          f64.add
+          local.set 14
+          local.get 2
+          local.get 3
+          i32.add
+          local.set 3
+          br 0 (;@3;)
+        end
+        unreachable
+      end
+      local.get 0
+      i32.const 1
+      i32.shr_u
+      i32.const 1073741816
+      i32.and
+      local.tee 4
+      local.get 1
+      local.get 2
+      local.get 3
+      call 3
+      local.get 0
+      local.get 4
+      i32.sub
+      local.get 1
+      local.get 2
+      local.get 3
+      local.get 2
+      local.get 4
+      i32.mul
+      i32.add
+      call 3
+      f64.add
+      local.set 14
+    end
+    local.get 14)
+  (export "__wasm_call_ctors" (func 0))
+  (export "stdlib_strided_dmeanpw" (func 1))
+  (export "stdlib_strided_dmeanpw_ndarray" (func 2)))
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.js
new file mode 100644
index 000000000000..3a10d08e6110
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.js
@@ -0,0 +1,53 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var dmeanpw = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is an object', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dmeanpw, 'object', 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to the main export is a `main` method', function test( t ) {
+	t.strictEqual( typeof dmeanpw.main, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to the main export is an `ndarray` method', function test( t ) {
+	t.strictEqual( typeof dmeanpw.ndarray, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to the main export is a `Module` constructor', function test( t ) {
+	t.strictEqual( typeof dmeanpw.Module, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'the main export is a `Module` instance', function test( t ) {
+	t.strictEqual( dmeanpw instanceof dmeanpw.Module, true, 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.main.js
new file mode 100644
index 000000000000..3e1ab4ea5fe7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.main.js
@@ -0,0 +1,165 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanpw = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is an object', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dmeanpw, 'object', 'main export is an object' );
+	t.end();
+});
+
+tape( 'the `main` method has an arity of 3', function test( t ) {
+	t.strictEqual( dmeanpw.main.length, 3, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the `main` method calculates the arithmetic mean of a strided array', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	v = dmeanpw.main( x.length, x, 1 );
+	t.strictEqual( v, 0.5, 'returns expected value' );
+
+	x = new Float64Array( [ -4.0, -4.0 ] );
+	v = dmeanpw.main( x.length, x, 1 );
+	t.strictEqual( v, -4.0, 'returns expected value' );
+
+	x = new Float64Array( [ NaN, 4.0 ] );
+	v = dmeanpw.main( x.length, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the `main` method returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.main( 0, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = dmeanpw.main( -1, x, 1 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the `main` method returns the first element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.main( 1, x, 1 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the `main` method supports a `stride` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+
+	v = dmeanpw.main( 4, x, 2 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the `main` method supports a negative `stride` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+
+	v = dmeanpw.main( 4, x, -2 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the `main` method returns the first element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.main( x.length, x, 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the `main` method supports view offsets', function test( t ) {
+	var x0;
+	var x1;
+	var v;
+
+	x0 = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0,  // 3
+		6.0
+	]);
+
+	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+	v = dmeanpw.main( 4, x1, 2 );
+	t.strictEqual( v, 1.25, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.js
new file mode 100644
index 000000000000..0cdcd97ef151
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.js
@@ -0,0 +1,154 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Memory = require( '@stdlib/wasm/memory' );
+var ModuleWrapper = require( '@stdlib/wasm/module-wrapper' );
+var Module = require( './../lib' ).Module;
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof Module, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function is a constructor', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+	t.strictEqual( mod instanceof Module, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function is a constructor which does not require `new`', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = Module( mem ); // eslint-disable-line new-cap
+	t.strictEqual( mod instanceof Module, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the module constructor throws an error if provided a first argument which is not a WebAssembly memory instance (new)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			return new Module( value );
+		};
+	}
+});
+
+tape( 'the module constructor throws an error if provided a first argument which is not a WebAssembly memory instance (no new)', function test( t ) {
+	var values;
+	var i;
+
+	values = [
+		'5',
+		5,
+		NaN,
+		true,
+		false,
+		null,
+		void 0,
+		[],
+		{},
+		function noop() {}
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		t.throws( badValue( values[ i ] ), TypeError, 'throws an error when provided ' + values[ i ] );
+	}
+	t.end();
+
+	function badValue( value ) {
+		return function badValue() {
+			return Module( value ); // eslint-disable-line new-cap
+		};
+	}
+});
+
+tape( 'the module instance returned by the module constructor inherits from a module wrapper', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+
+	t.strictEqual( mod instanceof ModuleWrapper, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to a module instance is a `main` method', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+
+	t.strictEqual( typeof mod.main, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to a module instance is an `ndarray` method', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+
+	t.strictEqual( typeof mod.ndarray, 'function', 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.main.js
new file mode 100644
index 000000000000..b94da9e37287
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.main.js
@@ -0,0 +1,209 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable node/no-sync */
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Memory = require( '@stdlib/wasm/memory' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Module = require( './../lib' ).Module;
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof Module, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'a module instance has a `main` method which has an arity of 3', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+	t.strictEqual( mod.main.length, 3, 'returns expected value' );
+	t.end();
+});
+
+tape( 'a module instance has a `main` method which calculates the arithmetic mean of a strided array', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ) );
+
+	y = mod.main( 6, xp, 1 );
+	t.strictEqual( y, 0.5, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, a module instance has a `main` method which returns `NaN`', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+
+	y = mod.main( 0, xp, 1 );
+	t.strictEqual( isnan( y ), true, 'returns expected value' );
+
+	y = mod.main( -1, xp, 1 );
+	t.strictEqual( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, a module instance has a `main` method which returns the first element', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+
+	y = mod.main( 1, xp, 1 );
+	t.strictEqual( y, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'a module instance has a `main` method which supports a `stride` parameter', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]));
+	N = 4;
+
+	y = mod.main( N, xp, 2 );
+	t.strictEqual( y, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'a module instance has a `main` method which supports a negative `stride` parameter', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]));
+	N = 4;
+
+	y = mod.main( N, xp, -2 );
+	t.strictEqual( y, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, a module instance has a `main` method returns the first element', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+	N = 5;
+
+	y = mod.main( N, xp, 0 );
+	t.strictEqual( y, 1.0, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.ndarray.js
new file mode 100644
index 000000000000..26f700f2de1c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.module.ndarray.js
@@ -0,0 +1,242 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable node/no-sync */
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var Memory = require( '@stdlib/wasm/memory' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var Module = require( './../lib' ).Module;
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof Module, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'a module instance has an `ndarray` method which has an arity of 4', function test( t ) {
+	var mem;
+	var mod;
+
+	mem = new Memory({
+		'initial': 0
+	});
+	mod = new Module( mem );
+	t.strictEqual( mod.ndarray.length, 4, 'returns expected value' );
+	t.end();
+});
+
+tape( 'a module instance has an `ndarray` method which calculates the arithmetic mean of a strided array', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] ) );
+
+	y = mod.ndarray( 6, xp, 1, 0 );
+	t.strictEqual( y, 0.5, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, a module instance has an `ndarray` method which returns `NaN`', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+
+	y = mod.ndarray( 0, xp, 1, 0 );
+	t.strictEqual( isnan( y ), true, 'returns expected value' );
+
+	y = mod.ndarray( -1, xp, 1, 0 );
+	t.strictEqual( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, a module instance has an `ndarray` method which returns the first indexed element', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+
+	y = mod.ndarray( 1, xp, 1, 0 );
+	t.strictEqual( y, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'a module instance has an `ndarray` method which supports a `stride` parameter', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]));
+	N = 4;
+
+	y = mod.ndarray( N, xp, 2, 0 );
+	t.strictEqual( y, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'a module instance has an `ndarray` method which supports a negative `stride` parameter', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]));
+	N = 4;
+
+	y = mod.ndarray( N, xp, -2, 6 );
+	t.strictEqual( y, 1.25, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, a module instance has an `ndarray` method which returns the first element', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] ) );
+	N = 5;
+
+	y = mod.ndarray( N, xp, 0, 0 );
+	t.strictEqual( y, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'a module instance has an `ndarray` method which supports an `offset` parameter', function test( t ) {
+	var mem;
+	var mod;
+	var xp;
+	var y;
+	var N;
+
+	mem = new Memory({
+		'initial': 1
+	});
+	mod = new Module( mem );
+	mod.initializeSync();
+
+	xp = 0;
+
+	mod.write( xp, new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0   // 3
+	]));
+	N = 4;
+
+	y = mod.ndarray( N, xp, 2, 1 );
+	t.strictEqual( y, 1.25, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.ndarray.js
new file mode 100644
index 000000000000..377d92ba4680
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.ndarray.js
@@ -0,0 +1,161 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
+var dmeanpw = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is an object', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof dmeanpw, 'object', 'main export is an object' );
+	t.end();
+});
+
+tape( 'the `ndarray` method has an arity of 4', function test( t ) {
+	t.strictEqual( dmeanpw.ndarray.length, 4, 'has expected arity' );
+	t.end();
+});
+
+tape( 'the `ndarray` method calculates the arithmetic mean of a strided array', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 0.0, 3.0 ] );
+	v = dmeanpw.ndarray( x.length, x, 1, 0 );
+	t.strictEqual( v, 0.5, 'returns expected value' );
+
+	x = new Float64Array( [ -4.0, -4.0 ] );
+	v = dmeanpw.ndarray( x.length, x, 1, 0 );
+	t.strictEqual( v, -4.0, 'returns expected value' );
+
+	x = new Float64Array( [ NaN, 4.0 ] );
+	v = dmeanpw.ndarray( x.length, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter less than or equal to `0`, the `ndarray` method returns `NaN`', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.ndarray( 0, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	v = dmeanpw.ndarray( -1, x, 1, 0 );
+	t.strictEqual( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided an `N` parameter equal to `1`, the `ndarray` method returns the first indexed element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.ndarray( 1, x, 1, 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the `ndarray` method supports a `stride` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 0
+		2.0,
+		2.0,  // 1
+		-7.0,
+		-2.0, // 2
+		3.0,
+		4.0,  // 3
+		2.0
+	]);
+
+	v = dmeanpw.ndarray( 4, x, 2, 0 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the `ndarray` method supports a negative `stride` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		1.0,  // 3
+		2.0,
+		2.0,  // 2
+		-7.0,
+		-2.0, // 1
+		3.0,
+		4.0,  // 0
+		2.0
+	]);
+
+	v = dmeanpw.ndarray( 4, x, -2, 6 );
+
+	t.strictEqual( v, 1.25, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a `stride` parameter equal to `0`, the `ndarray` method returns the first indexed element', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array( [ 1.0, -2.0, -4.0, 5.0, 3.0 ] );
+
+	v = dmeanpw.ndarray( x.length, x, 0, 0 );
+	t.strictEqual( v, 1.0, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the `ndarray` method supports an `offset` parameter', function test( t ) {
+	var x;
+	var v;
+
+	x = new Float64Array([
+		2.0,
+		1.0,  // 0
+		2.0,
+		-2.0, // 1
+		-2.0,
+		2.0,  // 2
+		3.0,
+		4.0   // 3
+	]);
+
+	v = dmeanpw.ndarray( 4, x, 2, 1 );
+	t.strictEqual( v, 1.25, 'returns expected value' );
+
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.routine.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.routine.js
new file mode 100644
index 000000000000..806b3de987e3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanpw/test/test.routine.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var ModuleWrapper = require( '@stdlib/wasm/module-wrapper' );
+var Module = require( './../lib/module.js' );
+var Routine = require( './../lib/routine.js' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof Routine, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function is a constructor', function test( t ) {
+	var mod = new Routine();
+	t.strictEqual( mod instanceof Routine, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the function is a constructor which does not require `new`', function test( t ) {
+	var mod = Routine(); // eslint-disable-line new-cap
+	t.strictEqual( mod instanceof Routine, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the module instance returned by the constructor inherits from a module wrapper', function test( t ) {
+	var mod = new Routine();
+	t.strictEqual( mod instanceof ModuleWrapper, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'the module instance returned by the constructor inherits from a routine module', function test( t ) {
+	var mod = new Routine();
+	t.strictEqual( mod instanceof Module, true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to a module instance is a `main` method', function test( t ) {
+	var mod = new Routine();
+	t.strictEqual( typeof mod.main, 'function', 'returns expected value' );
+	t.end();
+});
+
+tape( 'attached to a module instance is an `ndarray` method', function test( t ) {
+	var mod = new Routine();
+	t.strictEqual( typeof mod.ndarray, 'function', 'returns expected value' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js
index 69af16c81ed7..99781ff9d5b8 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/main.js
index 342aa6f8bff2..197484edd23e 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dmeanwd/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -52,6 +54,7 @@ var Routine = require( './routine.js' );
 * // returns 1.25
 */
 var dmeanwd = new Routine();
+setReadOnly( dmeanwd, 'Module', Module.bind( null ) );
 dmeanwd.initializeSync(); // eslint-disable-line node/no-sync
 
 
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js
index f6104ffa2cd4..37e77050fa30 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/index.js
@@ -83,14 +83,7 @@
 
 // MODULES //
 
-var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var main = require( './main.js' );
-var Module = require( './module.js' );
-
-
-// MAIN //
-
-setReadOnly( main, 'Module', Module );
 
 
 // EXPORTS //
diff --git a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/main.js b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/main.js
index 73c17d40f10b..c53594a1736a 100644
--- a/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/strided/wasm/dnanvariancewd/lib/main.js
@@ -20,7 +20,9 @@
 
 // MODULES //
 
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
 var Routine = require( './routine.js' );
+var Module = require( './module.js' );
 
 
 // MAIN //
@@ -52,6 +54,7 @@ var Routine = require( './routine.js' );
 * // returns 6.25
 */
 var dnanvariancewd = new Routine();
+setReadOnly( dnanvariancewd, 'Module', Module.bind( null ) );
 dnanvariancewd.initializeSync(); // eslint-disable-line node/no-sync
 
 
diff --git a/lib/node_modules/@stdlib/string/base/concat/README.md b/lib/node_modules/@stdlib/string/base/concat/README.md
new file mode 100644
index 000000000000..b3132b2d8202
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/README.md
@@ -0,0 +1,95 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# concat
+
+> Concatenate two strings.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var concat = require( '@stdlib/string/base/concat' );
+```
+
+#### concat( str1, str2 )
+
+Concatenates two strings.
+
+```javascript
+var out = concat( 'beep', 'boop' );
+// returns 'beepboop'
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var concat = require( '@stdlib/string/base/concat' );
+
+var str = concat( 'beep', 'boop' );
+// returns 'beepboop'
+
+str = concat( 'foo', 'bar' );
+// returns 'foobar'
+
+str = concat( 'hello', 'world' );
+// returns 'helloworld'
+
+str = concat( '', 'abc' );
+// returns 'abc'
+
+str = concat( '123', '' );
+// returns '123'
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/string/base/concat/benchmark/benchmark.js b/lib/node_modules/@stdlib/string/base/concat/benchmark/benchmark.js
new file mode 100644
index 000000000000..1f73f939bb08
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/benchmark/benchmark.js
@@ -0,0 +1,77 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var isString = require( '@stdlib/assert/is-string' ).isPrimitive;
+var pkg = require( './../package.json' ).name;
+var concat = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var values1;
+	var values2;
+	var out;
+	var i;
+
+	values1 = [ 'BEEP', 'FOO', 'HELLO' ];
+	values2 = [ 'BOOP', 'BAR', 'WORLD' ];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = concat( values1[ i%values1.length ], values2[ i%values2.length ] ); // eslint-disable-line max-len
+		if ( typeof out !== 'string' ) {
+			b.fail( 'should return a string' );
+		}
+	}
+	b.toc();
+	if ( !isString( out ) ) {
+		b.fail( 'should return a string' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg + '::builtin', function benchmark( b ) {
+	var values1;
+	var values2;
+	var out;
+	var i;
+
+	values1 = [ 'BEEP', 'FOO', 'HELLO' ];
+	values2 = [ 'BOOP', 'BAR', 'WORLD' ];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		out = values1[ i%values1.length ].concat( values2[ i%values2.length ] );
+		if ( typeof out !== 'string' ) {
+			b.fail( 'should return a string' );
+		}
+	}
+	b.toc();
+	if ( !isString( out ) ) {
+		b.fail( 'should return a string' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/string/base/concat/docs/repl.txt b/lib/node_modules/@stdlib/string/base/concat/docs/repl.txt
new file mode 100644
index 000000000000..92bb45607c04
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/docs/repl.txt
@@ -0,0 +1,24 @@
+
+{{alias}}( str1, str2 )
+    Concatenates two strings.
+
+    Parameters
+    ----------
+    str1: string
+        First input string.
+
+    str2: string
+        Second input string.
+
+    Returns
+    -------
+    out: string
+        Concatenated string.
+
+    Examples
+    --------
+    > var out = {{alias}}( 'beep', 'boop' )
+    'beepboop'
+
+    See Also
+    --------
diff --git a/lib/node_modules/@stdlib/string/base/concat/docs/types/index.d.ts b/lib/node_modules/@stdlib/string/base/concat/docs/types/index.d.ts
new file mode 100644
index 000000000000..9e291dab1f8b
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/docs/types/index.d.ts
@@ -0,0 +1,37 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Concatenates two strings.
+*
+* @param str1 - first string
+* @param str2 - second string
+* @returns concatenated string
+*
+* @example
+* var out = concat( 'beep', 'boop' );
+* // returns 'beepboop'
+*/
+declare function concat<S1 extends string, S2 extends string>( str1: S1, str2: S2 ): `${S1}${S2}`;
+
+
+// EXPORTS //
+
+export = concat;
diff --git a/lib/node_modules/@stdlib/string/base/concat/docs/types/test.ts b/lib/node_modules/@stdlib/string/base/concat/docs/types/test.ts
new file mode 100644
index 000000000000..d7beea4cb005
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/docs/types/test.ts
@@ -0,0 +1,57 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import concat = require( './index' );
+
+
+// TESTS //
+
+// The function returns a string...
+{
+	concat( 'beep', 'boop' ); // $ExpectType "beepboop"
+	concat( 'foo', 'bar' ); // $ExpectType "foobar"
+	concat( 'abc' as string, 'xyz' as string ); // $ExpectType string
+}
+
+// The compiler throws an error if the function is provided a first argument which is not a string...
+{
+	concat( true, 'boop' ); // $ExpectError
+	concat( null, 'boop' ); // $ExpectError
+	concat( undefined, 'boop' ); // $ExpectError
+	concat( 123, 'boop' ); // $ExpectError
+	concat( {}, 'boop' ); // $ExpectError
+	concat( [], 'boop' ); // $ExpectError
+	concat( ( x: number ): number => x, 'boop' ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided a second argument which is not a string...
+{
+	concat( 'beep', true ); // $ExpectError
+	concat( 'beep', null ); // $ExpectError
+	concat( 'beep', undefined ); // $ExpectError
+	concat( 'beep', 123 ); // $ExpectError
+	concat( 'beep', {} ); // $ExpectError
+	concat( 'beep', [] ); // $ExpectError
+	concat( 'beep', ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided insufficient arguments...
+{
+	concat(); // $ExpectError
+	concat( 'beep' ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/string/base/concat/examples/index.js b/lib/node_modules/@stdlib/string/base/concat/examples/index.js
new file mode 100644
index 000000000000..96c9151daef2
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/examples/index.js
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var concat = require( './../lib' );
+
+var str = concat( 'beep', 'boop' );
+console.log( str );
+// => 'beepboop'
+
+str = concat( 'foo', 'bar' );
+console.log( str );
+// => 'foobar'
+
+str = concat( 'Hello, ', 'world!' );
+console.log( str );
+// => 'Hello, world!'
+
+str = concat( '', 'empty' );
+console.log( str );
+// => 'empty'
+
+str = concat( 'test', '' );
+console.log( str );
+// => 'test'
diff --git a/lib/node_modules/@stdlib/string/base/concat/lib/index.js b/lib/node_modules/@stdlib/string/base/concat/lib/index.js
new file mode 100644
index 000000000000..6707d888e0e1
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/lib/index.js
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Concatenate two strings.
+*
+* @module @stdlib/string/base/concat
+*
+* @example
+* var concat = require( '@stdlib/string/base/concat' );
+*
+* var str = concat( 'beep', 'boop' );
+* // returns 'beepboop'
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/string/base/concat/lib/main.js b/lib/node_modules/@stdlib/string/base/concat/lib/main.js
new file mode 100644
index 000000000000..1e4c9e305d9b
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/lib/main.js
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MAIN //
+
+/**
+* Concatenates two strings.
+*
+* @param {string} str1 - first string
+* @param {string} str2 - second string
+* @returns {string} concatenated string
+*
+* @example
+* var str = concat( 'beep', 'boop' );
+* // returns 'beepboop'
+*/
+function concat( str1, str2 ) {
+	return str1 + str2;
+}
+
+
+// EXPORTS //
+
+module.exports = concat;
diff --git a/lib/node_modules/@stdlib/string/base/concat/package.json b/lib/node_modules/@stdlib/string/base/concat/package.json
new file mode 100644
index 000000000000..f40f3955bd19
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/package.json
@@ -0,0 +1,66 @@
+{
+  "name": "@stdlib/string/base/concat",
+  "version": "0.0.0",
+  "description": "Concatenate two strings.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdstring",
+    "utilities",
+    "utility",
+    "utils",
+    "util",
+    "base",
+    "concat",
+    "concatenate",
+    "join",
+    "combine",
+    "string",
+    "str"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/string/base/concat/test/test.js b/lib/node_modules/@stdlib/string/base/concat/test/test.js
new file mode 100644
index 000000000000..0a59ec7476cf
--- /dev/null
+++ b/lib/node_modules/@stdlib/string/base/concat/test/test.js
@@ -0,0 +1,62 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var concat = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof concat, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function concatenates two strings', function test( t ) {
+	var expected;
+	var values;
+	var actual;
+	var i;
+
+	values = [
+		[ 'beep', 'boop' ],
+		[ 'foo', 'bar' ],
+		[ 'Hello, ', 'World!' ],
+		[ '', 'empty' ],
+		[ 'non-empty', '' ],
+		[ '', '' ]
+	];
+	expected = [
+		'beepboop',
+		'foobar',
+		'Hello, World!',
+		'empty',
+		'non-empty',
+		''
+	];
+	for ( i = 0; i < values.length; i++ ) {
+		actual = concat( values[i][0], values[i][1] );
+		t.strictEqual( actual, expected[i], 'returns expected value' );
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/symbol/README.md b/lib/node_modules/@stdlib/symbol/README.md
index 6efb78ffb4f4..d74cfa3cfd06 100644
--- a/lib/node_modules/@stdlib/symbol/README.md
+++ b/lib/node_modules/@stdlib/symbol/README.md
@@ -50,6 +50,8 @@ The namespace contains the following:
 -   <span class="signature">[`HasInstanceSymbol`][@stdlib/symbol/has-instance]</span><span class="delimiter">: </span><span class="description">has instance symbol which is used to determine if a constructor object recognizes an object as its instance.</span>
 -   <span class="signature">[`IsConcatSpreadableSymbol`][@stdlib/symbol/is-concat-spreadable]</span><span class="delimiter">: </span><span class="description">concat spreadable symbol which specifies whether an array-like object should be flattened to its array elements during concatenation.</span>
 -   <span class="signature">[`IteratorSymbol`][@stdlib/symbol/iterator]</span><span class="delimiter">: </span><span class="description">iterator symbol which specifies the default iterator for an object.</span>
+-   <span class="signature">[`ReplaceSymbol`][@stdlib/symbol/replace]</span><span class="delimiter">: </span><span class="description">symbol which provides a method for replacing substrings matched by the current object.</span>
+-   <span class="signature">[`ToPrimitiveSymbol`][@stdlib/symbol/to-primitive]</span><span class="delimiter">: </span><span class="description">symbol which specifies a method for converting an object to a primitive value.</span>
 
 </div>
 
@@ -102,6 +104,10 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/symbol/iterator]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/symbol/iterator
 
+[@stdlib/symbol/replace]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/symbol/replace
+
+[@stdlib/symbol/to-primitive]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/symbol/to-primitive
+
 <!-- </toc-links> -->
 
 </section>
diff --git a/lib/node_modules/@stdlib/symbol/lib/index.js b/lib/node_modules/@stdlib/symbol/lib/index.js
index 3991329d5e81..699064d0d783 100644
--- a/lib/node_modules/@stdlib/symbol/lib/index.js
+++ b/lib/node_modules/@stdlib/symbol/lib/index.js
@@ -81,6 +81,24 @@ setReadOnly( ns, 'IsConcatSpreadableSymbol', require( '@stdlib/symbol/is-concat-
 */
 setReadOnly( ns, 'IteratorSymbol', require( '@stdlib/symbol/iterator' ) );
 
+/**
+* @name ReplaceSymbol
+* @memberof ns
+* @readonly
+* @type {(symbol|null)}
+* @see {@link module:@stdlib/symbol/replace}
+*/
+setReadOnly( ns, 'ReplaceSymbol', require( '@stdlib/symbol/replace' ) );
+
+/**
+* @name ToPrimitiveSymbol
+* @memberof ns
+* @readonly
+* @type {(symbol|null)}
+* @see {@link module:@stdlib/symbol/to-primitive}
+*/
+setReadOnly( ns, 'ToPrimitiveSymbol', require( '@stdlib/symbol/to-primitive' ) );
+
 
 // EXPORTS //
 
diff --git a/lib/node_modules/@stdlib/symbol/replace/README.md b/lib/node_modules/@stdlib/symbol/replace/README.md
new file mode 100644
index 000000000000..afae349bb07e
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/README.md
@@ -0,0 +1,130 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# ReplaceSymbol
+
+> [Symbol][mdn-symbol] which provides a method for replacing substrings matched by the current object.
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- Package usage documentation. -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var ReplaceSymbol = require( '@stdlib/symbol/replace' );
+```
+
+#### ReplaceSymbol
+
+[`symbol`][mdn-symbol] which provides a method for replacing substrings matched by the current object.
+
+```javascript
+var s = typeof ReplaceSymbol;
+// e.g., returns 'symbol'
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+## Notes
+
+-   The [symbol][mdn-symbol] is only supported in environments which support [symbols][mdn-symbol]. In non-supporting environments, the value is `null`.
+-   When calling `String.prototype.replace` and `String.prototype.replaceAll` and the `pattern` argument is an object with a `[ReplaceSymbol]()` method, this method is called with the target string and replacement as arguments.
+
+</section>
+
+<!-- /.notes -->
+
+<!-- Package usage examples. -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var defineProperty = require( '@stdlib/utils/define-property' );
+var ReplaceSymbol = require( '@stdlib/symbol/replace' );
+
+function replace( str, replacement ) {
+    return replacement;
+}
+
+var obj = {};
+
+defineProperty( obj, ReplaceSymbol, {
+    'configurable': true,
+    'value': null
+});
+
+var str = 'beep';
+console.log( str.replace( obj, 'boop' ) );
+
+defineProperty( obj, ReplaceSymbol, {
+    'configurable': true,
+    'value': replace
+});
+console.log( str.replace( obj, 'boop' ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[mdn-symbol]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/Symbol
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/symbol/replace/docs/repl.txt b/lib/node_modules/@stdlib/symbol/replace/docs/repl.txt
new file mode 100644
index 000000000000..6ec46c2deb10
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/docs/repl.txt
@@ -0,0 +1,18 @@
+
+{{alias}}
+    Replace symbol.
+
+    This symbol provides a method for replacing substrings matched by the
+    current object.
+
+    The symbol is only supported in ES6/ES2015+ environments. For non-supporting
+    environments, the value is `null`.
+
+    Examples
+    --------
+    > var s = {{alias}}
+    e.g., <symbol>
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/symbol/replace/docs/types/index.d.ts b/lib/node_modules/@stdlib/symbol/replace/docs/types/index.d.ts
new file mode 100644
index 000000000000..ffba2a96a502
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/docs/types/index.d.ts
@@ -0,0 +1,31 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+// EXPORTS //
+
+/**
+* Replace symbol.
+*
+* ## Notes
+*
+* -   This symbol provides a method for replacing substrings matched by the current object.
+* -   The symbol is only supported in ES6/ES2015+ environments. For non-supporting environments, the value is `null`.
+*/
+export = Symbol.replace;
diff --git a/lib/node_modules/@stdlib/symbol/replace/docs/types/test.ts b/lib/node_modules/@stdlib/symbol/replace/docs/types/test.ts
new file mode 100644
index 000000000000..814e87822e26
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/docs/types/test.ts
@@ -0,0 +1,29 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+/* eslint-disable @typescript-eslint/no-unused-expressions */
+
+import ReplaceSymbol = require( './index' );
+
+
+// TESTS //
+
+// The exported value is the `replace` symbol...
+{
+	ReplaceSymbol;
+}
diff --git a/lib/node_modules/@stdlib/symbol/replace/examples/index.js b/lib/node_modules/@stdlib/symbol/replace/examples/index.js
new file mode 100644
index 000000000000..860f005202de
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/examples/index.js
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var defineProperty = require( '@stdlib/utils/define-property' );
+var ReplaceSymbol = require( './../lib' );
+
+function replace( str, replacement ) {
+	return replacement;
+}
+
+var obj = {};
+
+defineProperty( obj, ReplaceSymbol, {
+	'configurable': true,
+	'value': null
+});
+
+var str = 'beep';
+console.log( str.replace( obj, 'boop' ) );
+
+defineProperty( obj, ReplaceSymbol, {
+	'configurable': true,
+	'value': replace
+});
+console.log( str.replace( obj, 'boop' ) );
diff --git a/lib/node_modules/@stdlib/symbol/replace/lib/index.js b/lib/node_modules/@stdlib/symbol/replace/lib/index.js
new file mode 100644
index 000000000000..9e44afcf7fde
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/lib/index.js
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Symbol which provides a method for replacing substrings matched by the current object.
+*
+* @module @stdlib/symbol/replace
+*
+* @example
+* var ReplaceSymbol = require( '@stdlib/symbol/replace' );
+*
+* function replace( str, replacement ) {
+*     return replacement;
+* }
+*
+* var obj = {};
+* obj[ ReplaceSymbol ] = replace;
+*/
+
+// MAIN //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/symbol/replace/lib/main.js b/lib/node_modules/@stdlib/symbol/replace/lib/main.js
new file mode 100644
index 000000000000..ca959710b730
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/lib/main.js
@@ -0,0 +1,48 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var hasReplaceSymbolSupport = require( '@stdlib/assert/has-replace-symbol-support' );
+
+
+// MAIN //
+
+/**
+* Replace symbol.
+*
+* @name ReplaceSymbol
+* @constant
+* @type {(symbol|null)}
+*
+* @example
+* function replace( str, replacement ) {
+*     return replacement;
+* }
+*
+* var obj = {};
+* obj[ ReplaceSymbol ] = replace;
+*/
+var ReplaceSymbol = ( hasReplaceSymbolSupport() ) ? Symbol.replace : null;
+
+
+// EXPORTS //
+
+module.exports = ReplaceSymbol;
diff --git a/lib/node_modules/@stdlib/symbol/replace/package.json b/lib/node_modules/@stdlib/symbol/replace/package.json
new file mode 100644
index 000000000000..27f886ca8ff0
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/package.json
@@ -0,0 +1,58 @@
+{
+  "name": "@stdlib/symbol/replace",
+  "version": "0.0.0",
+  "description": "Replace symbol.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "symbol",
+    "sym",
+    "replace",
+    "replacer",
+    "string"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/symbol/replace/test/test.js b/lib/node_modules/@stdlib/symbol/replace/test/test.js
new file mode 100644
index 000000000000..8914633188a4
--- /dev/null
+++ b/lib/node_modules/@stdlib/symbol/replace/test/test.js
@@ -0,0 +1,52 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var hasReplaceSymbolSupport = require( '@stdlib/assert/has-replace-symbol-support' );
+var isSymbol = require( '@stdlib/assert/is-symbol' );
+var Sym = require( './../lib' );
+
+
+// VARIABLES //
+
+var opts = {
+	'skip': !hasReplaceSymbolSupport()
+};
+
+
+// TESTS //
+
+tape( 'main export is a symbol in supporting environments (ES6/2015+) or otherwise null', function test( t ) {
+	t.ok( true, __filename );
+	if ( opts.skip ) {
+		t.strictEqual( Sym, null, 'main export is null' );
+	} else {
+		t.strictEqual( typeof Sym, 'symbol', 'main export is a symbol' );
+		t.strictEqual( isSymbol( Sym ), true, 'main export is a symbol' );
+	}
+	t.end();
+});
+
+tape( 'the main export is an alias for `Symbol.replace`', opts, function test( t ) {
+	t.strictEqual( Sym, Symbol.replace, 'returns expected value' );
+	t.end();
+});