feat: add new correlation metric

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Author: nakul-krishnakumar

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/README.md

@@ -46,12 +46,12 @@ Returns a list of KMeans distance metrics.
 
 ```javascript
 var out = metrics();
-// e.g., returns [ 'euclidean', 'cosine', 'cityblock' ]
+// e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock' , 'correlation' ]
 ```
 
 The output array contains the following metrics:
 
--   `euclidean`: squared euclidean distance.
+-   `sqeuclidean`: squared euclidean distance.
 -   `cosine`: cosine distance.
 -   `cityblock`: cityblock (taxicab) distance.
 
@@ -81,7 +81,7 @@ var metrics = require( '@stdlib/ml/base/cluster/kmeans/metrics' );
 
 var isMetric = contains( metrics() );
 
-var bool = isMetric( 'euclidean' );
+var bool = isMetric( 'sqeuclidean' );
 // returns true
 
 bool = isMetric( 'cosine' );
@@ -125,14 +125,14 @@ bool = isMetric( 'beep' );
 
 An enumeration of KMeans distance metrics with the following fields:
 
--   **STDLIB_ML_CLUSTER_KMEANS_EUCLIDEAN**: squared euclidean distance.
+-   **STDLIB_ML_CLUSTER_KMEANS_SQEUCLIDEAN**: squared euclidean distance.
 -   **STDLIB_ML_CLUSTER_KMEANS_COSINE**: cosine distance.
 -   **STDLIB_ML_CLUSTER_KMEANS_CITYBLOCK**: cityblock (taxicab) distance.
 
 ```c
 #include "stdlib/ml/base/cluster/kmeans/metrics.h"
 
-const enum STDLIB_ML_CLUSTER_KMEANS_METRIC v = STDLIB_ML_CLUSTER_KMEANS_EUCLIDEAN;
+const enum STDLIB_ML_CLUSTER_KMEANS_METRIC v = STDLIB_ML_CLUSTER_KMEANS_SQEUCLIDEAN;
 ```
 
 </section>

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/docs/repl.txt

@@ -16,7 +16,7 @@
     Examples
     --------
     > var out = {{alias}}()
-    [ 'euclidean', 'cosine', 'cityblock' ]
+    [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ]
 
     See Also
     --------

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/docs/types/index.d.ts

@@ -25,7 +25,7 @@
 *
 * @example
 * var list = metrics();
-* // e.g., returns [ 'euclidean', 'cosine', 'cityblock' ]
+* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ]
 */
 declare function metrics(): Array<string>;
 

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/examples/index.js

@@ -21,16 +21,16 @@
 var contains = require( '@stdlib/array/base/assert/contains' ).factory;
 var metrics = require( './../lib' );
 
-var isAlternative = contains( metrics() );
+var isMetric = contains( metrics() );
 
-var bool = isAlternative( 'euclidean' );
+var bool = isMetric( 'sqeuclidean' );
 console.log( bool );
 // => true
 
-bool = isAlternative( 'cosine' );
+bool = isMetric( 'cosine' );
 console.log( bool );
 // => true
 
-bool = isAlternative( 'beep' );
+bool = isMetric( 'beep' );
 console.log( bool );
 // => false

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/include/stdlib/ml/cluster/base/kmeans/metrics.h

@@ -23,8 +23,8 @@
 * Enumeration of distance metrics.
 */
 enum STDLIB_ML_CLUSTER_KMEANS_METRICS {
-	// Euclidean distance:
-	STDLIB_ML_CLUSTER_KMEANS_EUCLIDEAN = 0,
+	// Squared euclidean distance:
+	STDLIB_ML_CLUSTER_KMEANS_SQEUCLIDEAN = 0,
 
 	// Cosine distance:
 	STDLIB_ML_CLUSTER_KMEANS_COSINE,

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/lib/data.json

@@ -1,5 +1,6 @@
 [
-  "euclidean",
+  "sqeuclidean",
   "cosine",
-  "cityblock"
+  "cityblock",
+  "correlation"
 ]

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/lib/enum.js

@@ -25,7 +25,7 @@
 *
 * ## Notes
 *
-* -   Downstream consumers of this mapping should **not** rely on specific integer values (e.g., `EUCLIDEAN == 0`). Instead, the object should be used in an opaque manner.
+* -   Downstream consumers of this mapping should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the object should be used in an opaque manner.
 * -   The main purpose of this function is JavaScript and C inter-operation.
 *
 * @returns {Object} object mapping supported metrics to integer values
@@ -37,14 +37,17 @@
 function enumerated() {
 	// NOTE: the following should match the C `metrics.h` enumeration!!!!
 	return {
-		// Euclidean distance:
-		'euclidean': 0,
+		// Squared euclidean distance:
+		'sqeuclidean': 0,
 
 		// Cosine distance:
 		'cosine': 1,
 
 		// Cityblock (taxicab) distance:
-		'cityblock': 2
+		'cityblock': 2,
+
+		// Correlation distance:
+		'correlation': 3
 	};
 }
 

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/lib/index.js

@@ -27,7 +27,7 @@
 * var metrics = require( '@stdlib/ml/base/cluster/kmeans/metrics' );
 *
 * var list = metrics();
-* // e.g., returns [ 'euclidean', 'cosine', 'cityblock' ]
+* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock' , 'correlation' ]
 */
 
 // MODULES //

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/lib/main.js

@@ -32,7 +32,7 @@ var DATA = require( './data.json' );
 *
 * @example
 * var list = metrics();
-* // e.g., returns [ 'euclidean', 'cosine', 'cityblock' ]
+* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock' , 'correlation' ]
 */
 function metrics() {
 	return DATA.slice();

lib/node_modules/@stdlib/ml/base/cluster/kmeans/metrics/test/test.js

@@ -39,9 +39,10 @@ tape( 'the function returns a list of metrics', function test( t ) {
 	var actual;
 
 	expected = [
-		'euclidean',
+		'sqeuclidean',
 		'cosine',
-		'cityblock'
+		'cityblock',
+		'correlation'
 	];
 	actual = metrics();
 
@@ -62,9 +63,10 @@ tape( 'attached to the main function is an `enum` method to return an object map
 
 	// List of values which should be supported...
 	o = [
-		'euclidean',
+		'sqeuclidean',
 		'cosine',
-		'cityblock'
+		'cityblock',
+		'correlation'
 	];
 	for ( i = 0; i < o.length; i++ ) {
 		t.strictEqual( hasOwnProp( obj, o[ i ] ), true, 'has property `' + o[ i ] + '`' );