chore: clean-up

---
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---

Author: kgryte

lib/node_modules/@stdlib/ndarray/base/atleastnd/README.md

@@ -20,7 +20,7 @@ limitations under the License.
 
 # atleastnd
 
-> Convert the inputs to ndarrays having at least the provided number of dimensions.
+> Convert a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.
 
 <section class="intro">
 
@@ -38,9 +38,7 @@ var atleastnd = require( '@stdlib/ndarray/base/atleastnd' );
 
 #### atleastnd( ndims, arrays )
 
-Converts the inputs to ndarrays having at least the provided number of dimensions.
-
-<!-- eslint-disable max-len -->
+Converts a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.
 
 ```javascript
 var array = require( '@stdlib/ndarray/array' );
@@ -58,14 +56,28 @@ var out = atleastnd( 3, [ x, y ] );
 The function accepts the following arguments:
 
 -   **ndims**: minimum number of dimensions.
--   **arrays**: array-like object containing a list of arrays.
+-   **arrays**: array-like object containing a list of scalars and/or ndarrays.
 
 </section>
 
 <!-- /.usage -->
 
 <section class="notes">
 
+## Notes
+
+-   If a provided ndarray has fewer dimensions than `ndims`, the returned ndarray is a view on the input ndarray data buffer. The view is typically **not** contiguous. As more than one element of a returned view may refer to the same memory location, writing to the view may affect multiple elements. If you need to write to the returned ndarray, copy the ndarray **before** performing operations which may mutate elements.
+
+-   The returned ndarray is a "base" [ndarray][@stdlib/ndarray/base/ctor], and, thus, the returned [ndarray][@stdlib/ndarray/base/ctor] does not perform bounds checking or afford any of the guarantees of the non-base [ndarray][@stdlib/ndarray/ctor] constructor. The primary intent of this function is to broadcast an ndarray-like object within internal implementations and to do so with minimal overhead.
+
+-   If provided a scalar value (i.e., a non-ndarray) and that value
+
+    -   is a number, the returned ndarray will have the [default][@stdlib/ndarray/defaults] real-valued floating-point data type.
+    -   is a boolean, the returned ndarray will have the [default][@stdlib/ndarray/defaults] boolean data type.
+    -   is a complex number object of a known data type, the data type of the returned ndarray will be the same as the provided value.
+    -   is a complex number object of an unknown data type, the returned ndarray will have the [default][@stdlib/ndarray/defaults] complex-valued floating-point data type.
+    -   is any other value type, the returned ndarray will have a `'generic'` data type.
+
 </section>
 
 <!-- /.notes -->
@@ -108,6 +120,12 @@ console.log( ndarray2array( out[ 1 ] ) );
 
 <section class="links">
 
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/base/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/ctor
+
+[@stdlib/ndarray/defaults]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/defaults
+
 </section>
 
 <!-- /.links -->

lib/node_modules/@stdlib/ndarray/base/atleastnd/docs/repl.txt

@@ -1,20 +1,20 @@
 
 {{alias}}( ndims, arrays )
-    Converts the inputs to ndarrays having at least the provided number of
-    dimensions.
+    Converts a list of values (scalars and/or ndarrays) to ndarrays having at
+    least a specified number of dimensions.
 
     Parameters
     ----------
     ndims: number
         Minimum number of dimensions.
 
     arrays: ArrayLikeObject
-        List of arrays.
+        List of scalars and/or ndarrays.
 
     Returns
     -------
     out: Array<ndarray>
-        List of arrays.
+        List of ndarrays.
 
     Examples
     --------

lib/node_modules/@stdlib/ndarray/base/atleastnd/docs/types/index.d.ts

@@ -20,14 +20,15 @@
 
 /// <reference types="@stdlib/types"/>
 
+import { ArrayLike } from '@stdlib/types/array';
 import { ndarray } from '@stdlib/types/ndarray';
 
 /**
-* Converts the inputs to ndarrays having at least the provided number of dimensions.
+* Converts a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.
 *
 * @param ndims - minimum number of dimensions
-* @param arrays - array-like object containing a list of arrays
-* @returns output arrays
+* @param arrays - array-like object containing a list of scalars and/or ndarrays
+* @returns an array of ndarrays
 *
 * @example
 * var array = require( '@stdlib/ndarray/array' );
@@ -41,7 +42,7 @@ import { ndarray } from '@stdlib/types/ndarray';
 * var out = atleastnd( 3, [ x, y ] );
 * // returns [ <ndarray>, <ndarray> ]
 */
-declare function atleastnd( ndims: number, arrays: Array<any> ): Array<ndarray>;
+declare function atleastnd( ndims: number, arrays: ArrayLike<any> ): Array<ndarray>;
 
 
 // EXPORTS //

lib/node_modules/@stdlib/ndarray/base/atleastnd/docs/types/test.ts

@@ -32,7 +32,7 @@ import atleastnd = require( './index' );
 	atleastnd( 3, [ x, y, x ] ); // $ExpectType ndarray[]
 }
 
-// The compiler throws an error if the function is not provided a first argument which is a number...
+// The compiler throws an error if the function is provided a first argument which is not a number...
 {
 	const x = zeros( [ 2, 2 ] );
 	const y = zeros( [ 2, 2, 2 ] );
@@ -46,9 +46,8 @@ import atleastnd = require( './index' );
 	atleastnd( ( x: number ): number => x, [ x, y ] ); // $ExpectError
 }
 
-// The compiler throws an error if the function is not provided a second argument which is an array ...
+// The compiler throws an error if the function is provided a second argument which is not an array ...
 {
-	atleastnd( 3, '5' ); // $ExpectError
 	atleastnd( 3, 5 ); // $ExpectError
 	atleastnd( 3, true ); // $ExpectError
 	atleastnd( 3, false ); // $ExpectError

lib/node_modules/@stdlib/ndarray/base/atleastnd/lib/index.js

@@ -19,7 +19,7 @@
 'use strict';
 
 /**
-* Convert the inputs to ndarrays having at least the provided number of dimensions.
+* Convert a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.
 *
 * @module @stdlib/ndarray/base/atleastnd
 *

lib/node_modules/@stdlib/ndarray/base/atleastnd/lib/main.js

@@ -21,6 +21,10 @@
 // MODULES //
 
 var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var isNumber = require( '@stdlib/assert/is-number' ).isPrimitive;
+var isComplexLike = require( '@stdlib/assert/is-complex-like' );
+var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
+var complexDataType = require( '@stdlib/complex/dtype' );
 var broadcastScalar = require( '@stdlib/ndarray/base/broadcast-scalar' );
 var dims = require( '@stdlib/ndarray/base/ndims' );
 var defaults = require( '@stdlib/ndarray/defaults' );
@@ -36,18 +40,20 @@ var ones = require( '@stdlib/array/base/ones' );
 
 // VARIABLES //
 
-var DTYPE = defaults.get( 'dtypes.default' );
+var DEFAULT_REAL = defaults.get( 'dtypes.real_floating_point' );
+var DEFAULT_CMPLX = defaults.get( 'dtypes.complex_floating_point' );
+var DEFAULT_BOOL = defaults.get( 'dtypes.boolean' );
 var ORDER = defaults.get( 'order' );
 
 
 // MAIN //
 
 /**
-* Converts the inputs to ndarrays having at least the provided number of dimensions.
+* Converts a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.
 *
 * @param {NonNegativeInteger} ndims - minimum number of dimensions
-* @param {ArrayLikeObject<Object>} arrays - array-like object containing a list of arrays
-* @returns {ArrayLikeObject<Object>} output arrays
+* @param {ArrayLikeObject<Object>} arrays - array-like object containing a list of scalars and/or ndarrays
+* @returns {Array<Object>} list of ndarrays
 *
 * @example
 * var array = require( '@stdlib/ndarray/array' );
@@ -67,36 +73,54 @@ function atleastnd( ndims, arrays ) {
 	var out;
 	var sh;
 	var st;
+	var dt;
+	var v;
 	var N;
-	var n;
 	var i;
 	var j;
 
 	out = [];
 	for ( i = 0; i < arrays.length; i++ ) {
-		if ( isndarrayLike( arrays[ i ] ) ) {
-			N = dims( arrays[ i ] );
+		v = arrays[ i ];
+		if ( isndarrayLike( v ) ) {
+			N = dims( v );
 			if ( N >= ndims ) {
-				out.push( arrays[ i ] );
-			} else {
-				sh = getShape( arrays[ i ], false );
-				n = ndims - N;
-				st = getStrides( arrays[ i ], false );
-				shape = [];
-				strides = [];
-				for ( j = 0; j < n; j++ ) {
-					shape.push( 1 );
-					strides.push( st[ 0 ] );
-				}
-				for ( j = 0; j < sh.length; j++ ) {
-					shape.push( sh[ j ] );
-					strides.push( st[ j ] );
-				}
-				out.push( ndarray( getDType( arrays[ i ] ), getData( arrays[ i ] ), shape, strides, getOffset( arrays[ i ] ), getOrder( arrays[ i ] ) ) ); // eslint-disable-line max-len
+				out.push( v );
+				continue;
+			}
+			sh = getShape( v, false );
+			st = getStrides( v, false );
+
+			shape = [];
+			strides = [];
+
+			// Prepend singleton dimensions...
+			for ( j = 0; j < ndims-N; j++ ) {
+				shape.push( 1 );
+				strides.push( st[ 0 ] );
+			}
+			// Copy remaining dimensions...
+			for ( j = 0; j < sh.length; j++ ) {
+				shape.push( sh[ j ] );
+				strides.push( st[ j ] );
+			}
+			out.push( new ndarray( getDType( v ), getData( v ), shape, strides, getOffset( v ), getOrder( v ) ) ); // eslint-disable-line max-len
+			continue;
+		}
+		// For scalar values, resolve a corresponding ndarray data type...
+		if ( isNumber( v ) ) { // TODO: consider abstracting this logic to an `ndarray/base/scalar-dtype` (???) package, as this logic is found elsewhere (e.g., `ndarray/from-scalar`) and it would be good to avoid duplication, especially as we add support for more ndarray data types
+			dt = DEFAULT_REAL;
+		} else if ( isBoolean( v ) ) {
+			dt = DEFAULT_BOOL;
+		} else if ( isComplexLike( v ) ) {
+			dt = complexDataType( v );
+			if ( dt === null ) {
+				dt = DEFAULT_CMPLX;
 			}
 		} else {
-			out.push( broadcastScalar( arrays[ i ], DTYPE, ones( ndims ), ORDER ) ); // eslint-disable-line max-len
+			dt = 'generic';
 		}
+		out.push( broadcastScalar( v, dt, ones( ndims ), ORDER ) );
 	}
 	return out;
 }

lib/node_modules/@stdlib/ndarray/base/atleastnd/package.json

@@ -1,7 +1,7 @@
 {
   "name": "@stdlib/ndarray/base/atleastnd",
   "version": "0.0.0",
-  "description": "Coverts the inputs to ndarrays having at least the provided number of dimensions.",
+  "description": "Convert a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions.",
   "license": "Apache-2.0",
   "author": {
     "name": "The Stdlib Authors",

lib/node_modules/@stdlib/ndarray/base/atleastnd/test/test.js

@@ -25,6 +25,7 @@ var isArray = require( '@stdlib/assert/is-array' );
 var getShape = require( '@stdlib/ndarray/base/shape' );
 var zeros = require( '@stdlib/ndarray/zeros' );
 var ndarray = require( '@stdlib/ndarray/base/ctor' );
+var Complex128 = require( '@stdlib/complex/float64/ctor' );
 var atleastnd = require( './../lib' );
 
 
@@ -36,33 +37,56 @@ tape( 'main export is a function', function test( t ) {
 	t.end();
 });
 
-tape( 'the function converts the inputs to ndarrays having at least the provided number of dimensions.', function test( t ) {
+tape( 'the function a list of values (scalars and/or ndarrays) to ndarrays having at least a specified number of dimensions', function test( t ) {
 	var out;
 	var x;
 	var y;
 	var z;
+	var w;
+	var u;
+	var v;
+	var s;
 
 	x = zeros( [ 2, 2 ] );
 	y = zeros( [ 2 ] );
 	z = 10.0;
+	w = true;
+	u = new Complex128( 1.0, 2.0 );
+	v = {
+		're': 3.0,
+		'im': 4.0
+	};
+	s = 'beep';
 
-	out = atleastnd( 3, [ x, y, z ] );
+	out = atleastnd( 3, [ x, y, z, w, u, v, s ] );
 
 	t.strictEqual( isArray( out ), true, 'returns expected value' );
 	t.deepEqual( getShape( out[ 0 ] ), [ 1, 2, 2 ], 'returns expected value' );
 	t.deepEqual( getShape( out[ 1 ] ), [ 1, 1, 2 ], 'returns expected value' );
 	t.deepEqual( getShape( out[ 2 ] ), [ 1, 1, 1 ], 'returns expected value' );
-	t.notEqual( out[ 0 ], x, 'returns new instance' );
-	t.notEqual( out[ 1 ], y, 'returns new instance' );
-	t.notEqual( out[ 2 ], z, 'returns new instance' );
+	t.deepEqual( getShape( out[ 3 ] ), [ 1, 1, 1 ], 'returns expected value' );
+	t.deepEqual( getShape( out[ 4 ] ), [ 1, 1, 1 ], 'returns expected value' );
+	t.deepEqual( getShape( out[ 5 ] ), [ 1, 1, 1 ], 'returns expected value' );
+	t.deepEqual( getShape( out[ 6 ] ), [ 1, 1, 1 ], 'returns expected value' );
+	t.notEqual( out[ 0 ], x, 'returns expected value' );
+	t.notEqual( out[ 1 ], y, 'returns expected value' );
+	t.notEqual( out[ 2 ], z, 'returns expected value' );
+	t.notEqual( out[ 3 ], w, 'returns expected value' );
+	t.notEqual( out[ 4 ], u, 'returns expected value' );
+	t.notEqual( out[ 5 ], v, 'returns expected value' );
+	t.notEqual( out[ 6 ], s, 'returns expected value' );
 	t.strictEqual( out[ 0 ] instanceof ndarray, true, 'returns expected value' );
 	t.strictEqual( out[ 1 ] instanceof ndarray, true, 'returns expected value' );
 	t.strictEqual( out[ 2 ] instanceof ndarray, true, 'returns expected value' );
+	t.strictEqual( out[ 3 ] instanceof ndarray, true, 'returns expected value' );
+	t.strictEqual( out[ 4 ] instanceof ndarray, true, 'returns expected value' );
+	t.strictEqual( out[ 5 ] instanceof ndarray, true, 'returns expected value' );
+	t.strictEqual( out[ 6 ] instanceof ndarray, true, 'returns expected value' );
 
 	t.end();
 });
 
-tape( 'the function returns the same ndarray if provided an ndarray having dimensions more than or equal to `ndims`', function test( t ) {
+tape( 'the function returns an ndarray unchanged if an ndarray has at least a specified number of dimensions', function test( t ) {
 	var out;
 	var x;
 	var y;
@@ -78,9 +102,9 @@ tape( 'the function returns the same ndarray if provided an ndarray having dimen
 	t.deepEqual( getShape( out[ 0 ] ), [ 1, 2, 2 ], 'returns expected value' );
 	t.deepEqual( getShape( out[ 1 ] ), [ 3, 2, 2 ], 'returns expected value' );
 	t.deepEqual( getShape( out[ 2 ] ), [ 1, 3, 2, 2 ], 'returns expected value' );
-	t.notEqual( out[ 0 ], x, 'returns new instance' );
-	t.strictEqual( out[ 1 ], y, 'returns new instance' );
-	t.strictEqual( out[ 2 ], z, 'returns new instance' );
+	t.notEqual( out[ 0 ], x, 'returns expected value' );
+	t.strictEqual( out[ 1 ], y, 'returns expected value' );
+	t.strictEqual( out[ 2 ], z, 'returns expected value' );
 	t.strictEqual( out[ 0 ] instanceof ndarray, true, 'returns expected value' );
 	t.strictEqual( out[ 1 ] instanceof ndarray, true, 'returns expected value' );
 	t.strictEqual( out[ 2 ] instanceof ndarray, true, 'returns expected value' );