diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/README.md index b700df6f7698..a59fe2dac485 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/README.md @@ -47,11 +47,11 @@ Returns the k-means distance metric string associated with a k-means distance me ```javascript var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); -var v = str2enum( 'sqeuclidean' ); +var v = str2enum( 'squared-euclidean' ); // returns var s = enum2str( v ); -// returns 'sqeuclidean' +// returns 'squared-euclidean' ``` If unable to resolve a k-means distance metric string, the function returns `null`. @@ -85,8 +85,8 @@ var v = enum2str( -999999999 ); var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); var enum2str = require( '@stdlib/ml/base/kmeans/metric-enum2str' ); -var str = enum2str( str2enum( 'sqeuclidean' ) ); -// returns 'sqeuclidean' +var str = enum2str( str2enum( 'squared-euclidean' ) ); +// returns 'squared-euclidean' str = enum2str( str2enum( 'cosine' ) ); // returns 'cosine' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/benchmark/benchmark.js index aca482bf8893..23672516b467 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/benchmark/benchmark.js @@ -35,7 +35,7 @@ bench( pkg, function benchmark( b ) { var i; values = [ - str2enum( 'sqeuclidean' ), + str2enum( 'squared-euclidean' ), str2enum( 'cosine' ), str2enum( 'cityblock' ), str2enum( 'correlation' ) diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/repl.txt index 739ddd582f01..be55a946fe45 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/repl.txt +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/repl.txt @@ -15,8 +15,9 @@ Examples -------- - > var out = {{alias}}( {{alias:@stdlib/ml/base/kmeans/metric-str2enum}}( 'sqeuclidean' ) ) - 'sqeuclidean' + > var out = {{alias}}( {{alias:@stdlib/ml/base/kmeans/metric-str2enum}}( + ... 'squared-euclidean' ) ) + 'squared-euclidean' See Also -------- diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/types/index.d.ts index b1ba822fc941..762a33da6447 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/docs/types/index.d.ts @@ -27,11 +27,11 @@ * @example * var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); * -* var v = str2enum( 'sqeuclidean' ); +* var v = str2enum( 'squared-euclidean' ); * // returns * * var s = enum2str( v ); -* // returns 'sqeuclidean' +* // returns 'squared-euclidean' */ declare function enum2str( value: number ): string | null; diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/examples/index.js index 33a8673e3b6c..9bef59c8789c 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/examples/index.js @@ -25,6 +25,6 @@ var str = enum2str( str2enum( 'cosine' ) ); console.log( str ); // => 'cosine' -str = enum2str( str2enum( 'sqeuclidean' ) ); +str = enum2str( str2enum( 'squared-euclidean' ) ); console.log( str ); -// => 'sqeuclidean' +// => 'squared-euclidean' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/index.js index 491eb93a1950..2bfa16c33210 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/index.js @@ -27,11 +27,11 @@ * var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); * var enum2str = require( '@stdlib/ml/base/kmeans/metric-enum2str' ); * -* var v = str2enum( 'sqeuclidean' ); +* var v = str2enum( 'squared-euclidean' ); * // returns * * var s = enum2str( v ); -* // returns 'sqeuclidean' +* // returns 'squared-euclidean' */ // MODULES // diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/main.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/main.js index fd00e9214a2c..94ae4a3f3ac8 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/main.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/lib/main.js @@ -43,11 +43,11 @@ var hash = objectInverse( enumeration(), { * @example * var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); * -* var v = str2enum( 'sqeuclidean' ); +* var v = str2enum( 'squared-euclidean' ); * // returns * * var s = enum2str( v ); -* // returns 'sqeuclidean' +* // returns 'squared-euclidean' */ function enum2str( value ) { var v = hash[ value ]; diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/test/test.js index 20dde4c3da42..377245253e7f 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-enum2str/test/test.js @@ -28,7 +28,7 @@ var enum2str = require( './../lib' ); // VARIABLES // var VALUES = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'cityblock', 'correlation' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/README.md index 51f2af656672..54c95c5f7497 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/README.md @@ -47,7 +47,7 @@ Returns the enumeration constant associated with a supported k-means distance me ```javascript var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); -var v = resolve( 'sqeuclidean' ); +var v = resolve( 'squared-euclidean' ); // returns v = resolve( str2enum( 'cosine' ) ); @@ -71,7 +71,7 @@ var v = resolve( 'beep' ); ## Notes -- Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. @@ -88,7 +88,7 @@ var v = resolve( 'beep' ); ```javascript var resolve = require( '@stdlib/ml/base/kmeans/metric-resolve-enum' ); -var v = resolve( 'sqeuclidean' ); +var v = resolve( 'squared-euclidean' ); // returns v = resolve( 'cosine' ); diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/benchmark/benchmark.js index b1330c9716c5..b4156ffb00fc 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/benchmark/benchmark.js @@ -36,7 +36,7 @@ bench( format( '%s::string', pkg ), function benchmark( b ) { var i; values = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'correlation', 'cityblock' @@ -63,7 +63,7 @@ bench( format( '%s::integer', pkg ), function benchmark( b ) { var i; values = [ - str2enum( 'sqeuclidean' ), + str2enum( 'squared-euclidean' ), str2enum( 'cosine' ), str2enum( 'correlation' ), str2enum( 'cityblock' ) diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/repl.txt index db749f0d1f00..db0b0dfa2795 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/repl.txt +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/repl.txt @@ -4,8 +4,8 @@ distance metric value. Downstream consumers of this function should *not* rely on specific integer - values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in - an opaque manner. + values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be + used in an opaque manner. Parameters ---------- @@ -19,9 +19,10 @@ Examples -------- - > var out = {{alias}}( 'sqeuclidean' ) + > var out = {{alias}}( 'squared-euclidean' ) - > out = {{alias}}( {{alias:@stdlib/ml/base/kmeans/metric-str2enum}}( 'sqeuclidean' ) ) + > out = {{alias}}( {{alias:@stdlib/ml/base/kmeans/metric-str2enum}}( + ... 'squared-euclidean' ) ) See Also diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/index.d.ts index 44fa3b82f75f..23455c6734f2 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/index.d.ts @@ -23,13 +23,13 @@ * * ## Notes * -* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. * * @param value - distance metric value * @returns enumeration constant * * @example -* var v = resolve( 'sqeuclidean' ); +* var v = resolve( 'squared-euclidean' ); * // returns */ declare function resolve( value: any ): number | null; diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/test.ts b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/test.ts index 67b52da9dcf9..f67ce92da32b 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/test.ts +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/docs/types/test.ts @@ -24,5 +24,5 @@ import resolve = require( './index' ); // The function returns a number or null... { resolve( 0 ); // $ExpectType number | null - resolve( 'sqeuclidean' ); // $ExpectType number | null + resolve( 'squared-euclidean' ); // $ExpectType number | null } diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/examples/index.js index dd2a207cbcf3..6e4b046e956d 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/examples/index.js @@ -20,7 +20,7 @@ var resolve = require( './../lib' ); -var v = resolve( 'sqeuclidean' ); +var v = resolve( 'squared-euclidean' ); console.log( v ); // => diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/index.js index 7c7861583aec..89297173cb77 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/index.js @@ -26,7 +26,7 @@ * @example * var resolve = require( '@stdlib/ml/base/kmeans/metric-resolve-enum' ); * -* var v = resolve( 'sqeuclidean' ); +* var v = resolve( 'squared-euclidean' ); * // returns */ diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/main.js index 245289f0532b..3e7d1ff66b47 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/main.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/lib/main.js @@ -31,13 +31,13 @@ var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); * * ## Notes * -* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. * * @param {*} value - distance metric value * @returns {(integer|null)} enumeration constant or null * * @example -* var v = resolve( 'sqeuclidean' ); +* var v = resolve( 'squared-euclidean' ); * // returns */ function resolve( value ) { diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/test/test.js index c8e7283fbb8b..1c6a49d3ce74 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-enum/test/test.js @@ -28,7 +28,7 @@ var resolve = require( './../lib' ); // VARIABLES // var VALUES = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'correlation', 'cityblock' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/README.md index 9884888cc772..88ba1073fbca 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/README.md @@ -88,8 +88,8 @@ var resolve = require( '@stdlib/ml/base/kmeans/metric-resolve-str' ); var v = resolve( str2enum( 'cosine' ) ); // returns 'cosine' -v = resolve( str2enum( 'sqeuclidean' ) ); -// returns 'sqeuclidean' +v = resolve( str2enum( 'squared-euclidean' ) ); +// returns 'squared-euclidean' ``` diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/benchmark/benchmark.js index 7010c972692f..5fd4c37e2426 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/benchmark/benchmark.js @@ -36,7 +36,7 @@ bench( format( '%s::string', pkg ), function benchmark( b ) { var i; values = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'correlation', 'cityblock' @@ -63,7 +63,7 @@ bench( format( '%s::integer', pkg ), function benchmark( b ) { var i; values = [ - str2enum( 'sqeuclidean' ), + str2enum( 'squared-euclidean' ), str2enum( 'cosine' ), str2enum( 'correlation' ), str2enum( 'cityblock' ) diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/examples/index.js index a600926821ee..f297d3846c98 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/examples/index.js @@ -25,6 +25,6 @@ var v = resolve( str2enum( 'cosine' ) ); console.log( v ); // => 'cosine' -v = resolve( str2enum( 'sqeuclidean' ) ); +v = resolve( str2enum( 'squared-euclidean' ) ); console.log( v ); -// => 'sqeuclidean' +// => 'squared-euclidean' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/test/test.js index eae463ded814..06fa2e41f1f2 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-resolve-str/test/test.js @@ -28,7 +28,7 @@ var resolve = require( './../lib' ); // VARIABLES // var VALUES = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'correlation', 'cityblock' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/README.md index 948efe17ec39..3f6585ac7267 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/README.md @@ -66,7 +66,7 @@ var v = str2enum( 'beep' ); ## Notes -- Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +- Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. @@ -86,7 +86,7 @@ var str2enum = require( '@stdlib/ml/base/kmeans/metric-str2enum' ); var v = str2enum( 'cosine' ); // returns -v = str2enum( 'sqeuclidean' ); +v = str2enum( 'squared-euclidean' ); // returns ``` diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/benchmark/benchmark.js index e28f652d9084..365b7d6cbf66 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/benchmark/benchmark.js @@ -34,7 +34,7 @@ bench( pkg, function benchmark( b ) { var i; values = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'cityblock', 'correlation' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/repl.txt index b443e00e22df..cefff9d05fa9 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/repl.txt +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/repl.txt @@ -4,8 +4,8 @@ string. Downstream consumers of this function should *not* rely on specific integer - values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in - an opaque manner. + values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be + used in an opaque manner. Parameters ---------- diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/types/index.d.ts index 170c07945465..899e7f865e47 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/docs/types/index.d.ts @@ -23,7 +23,7 @@ * * ## Notes * -* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. * * @param metric - distance metric string * @returns enumeration constant diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/examples/index.js index e00bd0a188bd..84817a7827cf 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/examples/index.js @@ -24,6 +24,6 @@ var v = str2enum( 'cosine' ); console.log( v ); // => -v = str2enum( 'sqeuclidean' ); +v = str2enum( 'squared-euclidean' ); console.log( v ); // => diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/lib/main.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/lib/main.js index 328b12d1718e..bdc74debcfb7 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/lib/main.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/lib/main.js @@ -36,7 +36,7 @@ var ENUM = enumeration(); * * ## Notes * -* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQEUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. +* - Downstream consumers of this function should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 0`). Instead, the function should be used in an opaque manner. * * @param {string} metric - distance metric string * @returns {(integer|null)} integer value or null diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/test/test.js index c4bd0244f201..6865ee488ea6 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metric-str2enum/test/test.js @@ -29,7 +29,7 @@ var str2enum = require( './../lib' ); var VALUES = [ 'cosine', - 'sqeuclidean', + 'squared-euclidean', 'cityblock', 'correlation' ]; diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/README.md index 7208171d174f..95d8241ec108 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/README.md @@ -46,12 +46,12 @@ Returns a list of k-means distance metrics. ```javascript var out = metrics(); -// e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ] +// e.g., returns [ 'squared-euclidean', 'cosine', 'cityblock', 'correlation' ] ``` The output array contains the following metrics: -- `sqeuclidean`: squared euclidean distance. +- `squared-euclidean`: squared euclidean distance. - `cosine`: cosine distance. - `cityblock`: cityblock (taxicab) distance. - `correlation`: correlation distance. @@ -82,7 +82,7 @@ var metrics = require( '@stdlib/ml/base/kmeans/metrics' ); var isMetric = contains( metrics() ); -var bool = isMetric( 'sqeuclidean' ); +var bool = isMetric( 'squared-euclidean' ); // returns true bool = isMetric( 'cosine' ); @@ -126,7 +126,7 @@ bool = isMetric( 'beep' ); An enumeration of k-means distance metrics with the following fields: -- **STDLIB_ML_KMEANS_SQEUCLIDEAN**: squared euclidean distance. +- **STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN**: squared euclidean distance. - **STDLIB_ML_KMEANS_COSINE**: cosine distance. - **STDLIB_ML_KMEANS_CITYBLOCK**: cityblock (taxicab) distance. - **STDLIB_ML_KMEANS_CORRELATION**: correlation distance. @@ -134,7 +134,7 @@ An enumeration of k-means distance metrics with the following fields: ```c #include "stdlib/ml/base/kmeans/metrics.h" -const enum STDLIB_ML_KMEANS_METRIC v = STDLIB_ML_KMEANS_SQEUCLIDEAN; +const enum STDLIB_ML_KMEANS_METRIC v = STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN; ``` diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/repl.txt b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/repl.txt index 5106571c9f40..ff21c1dd4f76 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/repl.txt +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/repl.txt @@ -4,7 +4,7 @@ The output array contains the following metrics: - - sqeuclidean: squared euclidean distance. + - squared-euclidean: squared euclidean distance. - cosine: cosine distance. - cityblock: cityblock (taxicab) distance. - correlation: correlation distance. @@ -17,7 +17,7 @@ Examples -------- > var out = {{alias}}() - [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ] + [ 'squared-euclidean', 'cosine', 'cityblock', 'correlation' ] See Also -------- diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/types/index.d.ts index 7abbe1fa4e12..5ba304a5e3ce 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/docs/types/index.d.ts @@ -25,7 +25,7 @@ * * @example * var list = metrics(); -* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ] +* // e.g., returns [ 'squared-euclidean', 'cosine', 'cityblock', 'correlation' ] */ declare function metrics(): Array; diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/examples/index.js index bf828d8a4144..062131e1f1aa 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/examples/index.js @@ -23,7 +23,7 @@ var metrics = require( './../lib' ); var isMetric = contains( metrics() ); -var bool = isMetric( 'sqeuclidean' ); +var bool = isMetric( 'squared-euclidean' ); console.log( bool ); // => true diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/include/stdlib/ml/base/kmeans/metrics.h b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/include/stdlib/ml/base/kmeans/metrics.h index 2c8a593f5631..a99cdf0b22dc 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/include/stdlib/ml/base/kmeans/metrics.h +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/include/stdlib/ml/base/kmeans/metrics.h @@ -24,7 +24,7 @@ */ enum STDLIB_ML_KMEANS_METRIC { // Squared euclidean distance: - STDLIB_ML_KMEANS_SQEUCLIDEAN = 0, + STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN = 0, // Cosine distance: STDLIB_ML_KMEANS_COSINE, diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/data.json b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/data.json index 9d38e90c954d..285bd22f4aea 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/data.json +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/data.json @@ -1,5 +1,5 @@ [ - "sqeuclidean", + "squared-euclidean", "cosine", "cityblock", "correlation" diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/enum.js b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/enum.js index 5d7e7d3674d8..3b2ba0a94308 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/enum.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/enum.js @@ -25,7 +25,7 @@ * * ## Notes * -* - 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. +* - Downstream consumers of this mapping should **not** rely on specific integer values (e.g., `SQUARED_EUCLIDEAN == 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 @@ -38,7 +38,7 @@ function enumerated() { // NOTE: the following should match the C `metrics.h` enumeration!!!! return { // Squared euclidean distance: - 'sqeuclidean': 0, + 'squared-euclidean': 0, // Cosine distance: 'cosine': 1, diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/index.js index 30bd521ee439..9f00030b5003 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/index.js @@ -27,7 +27,7 @@ * var metrics = require( '@stdlib/ml/base/kmeans/metrics' ); * * var list = metrics(); -* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ] +* // e.g., returns [ 'squared-euclidean', 'cosine', 'cityblock', 'correlation' ] */ // MODULES // diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/main.js b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/main.js index 7a35a7c16d82..6a8f6ce317aa 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/main.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/lib/main.js @@ -32,7 +32,7 @@ var DATA = require( './data.json' ); * * @example * var list = metrics(); -* // e.g., returns [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ] +* // e.g., returns [ 'squared-euclidean', 'cosine', 'cityblock', 'correlation' ] */ function metrics() { return DATA.slice(); diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/test/test.js index 664fff31ec6b..2ea99745c198 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/metrics/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/metrics/test/test.js @@ -39,7 +39,7 @@ tape( 'the function returns a list of metrics', function test( t ) { var actual; expected = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'cityblock', 'correlation' @@ -63,7 +63,7 @@ tape( 'attached to the main function is an `enum` method to return an object map // List of values which should be supported... o = [ - 'sqeuclidean', + 'squared-euclidean', 'cosine', 'cityblock', 'correlation' diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/README.md b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/README.md index d5d9cddf8757..9f1a44fb5452 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/README.md +++ b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/README.md @@ -90,7 +90,7 @@ var Struct = structFactory( 'float64' ); var results = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': 3.28, @@ -108,7 +108,7 @@ Struct = structFactory( 'float32' ); results = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': f32( 3.28 ), diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/examples/index.js b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/examples/index.js index ca4dd8576be6..a4ddc2746eb2 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/examples/index.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/examples/index.js @@ -27,7 +27,7 @@ var Struct = structFactory( 'float64' ); var results = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': 3.28, @@ -45,7 +45,7 @@ Struct = structFactory( 'float32' ); results = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': f32( 3.28 ), diff --git a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/test/test.js b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/test/test.js index 638048290fe0..7e53b167bc14 100644 --- a/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/test/test.js +++ b/lib/node_modules/@stdlib/ml/base/kmeans/results/struct-factory/test/test.js @@ -75,7 +75,7 @@ tape( 'the function returns a constructor for creating a fixed-width results obj actual = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': 3.28, @@ -87,7 +87,7 @@ tape( 'the function returns a constructor for creating a fixed-width results obj expected = { 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': 3.28, @@ -120,7 +120,7 @@ tape( 'the function returns a constructor for creating a fixed-width results obj actual = new Struct({ 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': f32( 3.28 ), @@ -132,7 +132,7 @@ tape( 'the function returns a constructor for creating a fixed-width results obj expected = { 'replicates': 4, 'replicate': 2, - 'metric': metricResolveEnum( 'sqeuclidean' ), + 'metric': metricResolveEnum( 'squared-euclidean' ), 'iterations': 10, 'algorithm': algorithmResolveEnum( 'lloyd' ), 'inertia': f32( 3.28 ), diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/README.md b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/README.md index f28df7fa55db..1abeaf7a1a74 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/README.md +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/README.md @@ -46,7 +46,7 @@ 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); +var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); // returns 72.0 ``` @@ -67,7 +67,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] ); -var z = dkmeansDistance( 3, 'sqeuclidean', x, 2, y, -1 ); +var z = dkmeansDistance( 3, 'squared-euclidean', x, 2, y, -1 ); // returns 20.0 ``` @@ -86,7 +86,7 @@ var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); 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*3 ); // start at 4th element -var z = dkmeansDistance( 3, 'sqeuclidean', x1, 1, y1, 1 ); +var z = dkmeansDistance( 3, 'squared-euclidean', x1, 1, y1, 1 ); // returns 192.0 ``` @@ -100,7 +100,7 @@ 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 = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); +var z = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // returns 72.0 ``` @@ -117,7 +117,7 @@ var Float64Array = require( '@stdlib/array/float64' ); var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] ); var y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] ); -var z = dkmeansDistance.ndarray( 3, 'sqeuclidean', x, 2, 1, y, -1, y.length-1 ); +var z = dkmeansDistance.ndarray( 3, 'squared-euclidean', x, 2, 1, y, -1, y.length-1 ); // returns 165.0 ``` @@ -154,7 +154,7 @@ console.log( x ); var y = discreteUniform( x.length, 0, 10, opts ); console.log( y ); -var out = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, -1, y.length-1 ); +var out = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, -1, y.length-1 ); console.log( out ); ``` @@ -198,7 +198,7 @@ Computes the distance between two double-precision floating-point strided arrays const double x[] = { 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 }; const double y[] = { 2.0, 1.0, 2.0, 1.0, -2.0, 2.0, 3.0, 4.0 }; -double v = stdlib_strided_dkmeans_distance( 8, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, 1, y, 1 ); +double v = stdlib_strided_dkmeans_distance( 8, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, 1, y, 1 ); // returns 72.0 ``` @@ -229,7 +229,7 @@ Computes the distance between two double-precision floating-point strided arrays const double x[] = { 4.0, 2.0, -3.0, 5.0, -1.0 }; const double y[] = { 2.0, 6.0, -1.0, -4.0, 8.0 }; -double v = stdlib_strided_dkmeans_distance_ndarray( 5, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, -1, 4, y, -1, 4 ); +double v = stdlib_strided_dkmeans_distance_ndarray( 5, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, -1, 4, y, -1, 4 ); // returns 186.0 ``` @@ -284,13 +284,13 @@ int main( void ) { const int strideY = -1; // Compute the distance between `x` and `y`: - double d = stdlib_strided_dkmeans_distance( N, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, strideX, y, strideY ); + double d = stdlib_strided_dkmeans_distance( N, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, strideX, y, strideY ); // Print the result: printf( "Distance: %lf\n", d ); // Compute the distance between `x` and `y` with offsets: - d = stdlib_strided_dkmeans_distance_ndarray( N, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, strideX, 0, y, strideY, N-1 ); + d = stdlib_strided_dkmeans_distance_ndarray( N, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, strideX, 0, y, strideY, N-1 ); // Print the result: printf( "Distance: %lf\n", d ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.js index 0a88f66cc1e3..2fe69e12cf37 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.js @@ -62,7 +62,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - d = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + d = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); if ( isnan( d ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.native.js index a1c49bb4d162..001396ca2a39 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.native.js @@ -67,7 +67,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - d = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + d = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); if ( isnan( d ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.js index 8709f2441c7e..1c5c6cb8f8c9 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.js @@ -62,7 +62,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - d = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + d = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); if ( isnan( d ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.native.js index 1c612234ff1a..ec8fb9cd7dea 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/benchmark.ndarray.native.js @@ -67,7 +67,7 @@ function createBenchmark( len ) { b.tic(); for ( i = 0; i < b.iterations; i++ ) { - d = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + d = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); if ( isnan( d ) ) { b.fail( 'should not return NaN' ); } diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/c/benchmark.length.c index 877219572db1..b6f413bd5509 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/c/benchmark.length.c +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/benchmark/c/benchmark.length.c @@ -114,7 +114,7 @@ static double benchmark1( int iterations, int len ) { z = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - z = stdlib_strided_dkmeans_distance( len, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, 1, y, 1 ); + z = stdlib_strided_dkmeans_distance( len, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, 1, y, 1 ); if ( z != z ) { printf( "should not return NaN\n" ); break; @@ -153,7 +153,7 @@ static double benchmark2( int iterations, int len ) { z = 0.0; t = tic(); for ( i = 0; i < iterations; i++ ) { - z = stdlib_strided_dkmeans_distance_ndarray( len, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, 1, 0, y, 1, 0 ); + z = stdlib_strided_dkmeans_distance_ndarray( len, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, 1, 0, y, 1, 0 ); if ( z != z ) { printf( "should not return NaN\n" ); break; diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/repl.txt b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/repl.txt index c7ce9fffd49d..32fe917855d3 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/repl.txt +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/repl.txt @@ -41,13 +41,13 @@ // 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, 'sqeuclidean', x, 1, y, 1 ) + > {{alias}}( x.length, 'squared-euclidean', x, 1, y, 1 ) 45.0 // 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, 'sqeuclidean', x, 2, y, 2 ) + > {{alias}}( 3, 'squared-euclidean', x, 2, y, 2 ) 1.0 // Using view offsets: @@ -55,7 +55,7 @@ > 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, 'sqeuclidean', x1, 2, y1, 2 ) + > {{alias}}( 2, 'squared-euclidean', x1, 2, y1, 2 ) 9.0 @@ -104,13 +104,13 @@ // 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, 'sqeuclidean', x, 1, 0, y, 1, 0 ) + > {{alias}}.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ) 328.0 // 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, 'sqeuclidean', x, 2, 1, y, 2, 1 ) + > {{alias}}.ndarray( 2, 'squared-euclidean', x, 2, 1, y, 2, 1 ) 9.0 See Also diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/index.d.ts b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/index.d.ts index aabc6ae90e2d..967cd518557a 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/index.d.ts +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/index.d.ts @@ -39,7 +39,7 @@ interface Routine { * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + * var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); * // returns 72.0 */ ( N: number, metric: string, x: Float64Array, strideX: number, y: Float64Array, strideY: number ): number; @@ -63,7 +63,7 @@ interface Routine { * 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 = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + * var z = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); * // returns 72.0 */ ndarray( N: number, metric: string, x: Float64Array, strideX: number, offsetX: number, y: Float64Array, strideY: number, offsetY: number ): number; @@ -86,7 +86,7 @@ interface Routine { * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); * // returns 72.0 * * @example @@ -95,7 +95,7 @@ interface Routine { * 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 = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); +* var z = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); * // returns 72.0 */ declare var dkmeansDistance: Routine; diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/test.ts b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/test.ts index 52866241f1af..ebbfeab3f314 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/test.ts +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/docs/types/test.ts @@ -26,7 +26,7 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); // $ExpectType number + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); // $ExpectType number } // The compiler throws an error if the function is provided a first argument which is not a number... @@ -34,14 +34,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance( '10', 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( true, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( false, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( null, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( undefined, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( [], 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( {}, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError - dkmeansDistance( ( x: number ): number => x, 'sqeuclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( '10', 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( true, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( false, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( null, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( undefined, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( [], 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( {}, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError + dkmeansDistance( ( x: number ): number => x, 'squared-euclidean', x, 1, y, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a second argument which is not a string... @@ -64,15 +64,15 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance( x.length, 'sqeuclidean', 10, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', '10', 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', true, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', false, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', null, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', undefined, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', [], 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', {}, 1, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', ( x: number ): number => x, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', 10, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', '10', 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', true, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', false, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', null, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', undefined, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', [], 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', {}, 1, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', ( x: number ): number => x, 1, y, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a fourth argument which is not a number... @@ -80,29 +80,29 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance( x.length, 'sqeuclidean', x, '10', y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, true, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, false, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, null, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, undefined, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, [], y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, {}, y, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, ( x: number ): number => x, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, '10', y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, true, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, false, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, null, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, undefined, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, [], y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, {}, y, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, ( x: number ): number => x, y, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a fifth argument which is not a Float64Array... { const x = new Float64Array( 10 ); - dkmeansDistance( x.length, 'sqeuclidean', x, 1, 10, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, '10', 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, true, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, false, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, null, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, undefined, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, [], 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, {}, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, ( x: number ): number => x, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, 10, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, '10', 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, true, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, false, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, null, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, undefined, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, [], 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, {}, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, ( x: number ): number => x, 1 ); // $ExpectError } // The compiler throws an error if the function is provided a sixth argument which is not a number... @@ -110,14 +110,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, '10' ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, true ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, false ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, null ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, undefined ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, [] ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, {} ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, ( x: number ): number => x ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, '10' ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, true ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, false ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, null ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, undefined ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, [] ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, {} ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, ( x: number ): number => x ); // $ExpectError } // The compiler throws an error if the function is provided an unsupported number of arguments... @@ -127,11 +127,11 @@ import dkmeansDistance = require( './index' ); dkmeansDistance(); // $ExpectError dkmeansDistance( x.length ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean' ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1 ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y ); // $ExpectError - dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1, 10 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean' ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1 ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y ); // $ExpectError + dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1, 10 ); // $ExpectError } // Attached to main export is an `ndarray` method which returns a number... @@ -139,7 +139,7 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectType number + dkmeansDistance.ndarray( x.length, 'squared-euclidean', 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... @@ -147,14 +147,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( '10', 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( true, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( false, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( null, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( undefined, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( [], 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( {}, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( ( x: number ): number => x, 'sqeuclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( '10', 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( true, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( false, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( null, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( undefined, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( [], 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( {}, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( ( x: number ): number => x, 'squared-euclidean', 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 string... @@ -177,15 +177,15 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', 10, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', '10', 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', true, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', false, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', null, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', undefined, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', [], 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', {}, 1, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', 10, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', '10', 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', true, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', false, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', null, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', undefined, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', [], 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', {}, 1, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', ( x: number ): number => x, 1, 0, y, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a fourth argument which is not a number... @@ -193,14 +193,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, '10', 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, true, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, false, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, null, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, undefined, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, [], 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, {}, 0, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, '10', 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, true, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, false, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, null, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, undefined, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, [], 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, {}, 0, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, ( x: number ): number => x, 0, y, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a fifth argument which is not a number... @@ -208,29 +208,29 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, '10', y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, true, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, false, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, null, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, undefined, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, [], y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, {}, y, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, '10', y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, true, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, false, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, null, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, undefined, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, [], y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, {}, y, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, ( x: number ): number => x, y, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a sixth argument which is not a Float64Array... { const x = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, 10, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, '10', 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, true, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, false, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, null, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, undefined, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, [], 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, {}, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, 10, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, '10', 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, true, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, false, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, null, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, undefined, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, [], 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, {}, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, ( x: number ): number => x, x, 1, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a seventh argument which is not a number... @@ -238,14 +238,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, '10', 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, true, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, false, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, null, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, undefined, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, [], 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, {}, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, '10', 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, true, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, false, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, null, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, undefined, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, [], 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, {}, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, ( x: number ): number => x, 0 ); // $ExpectError } // The compiler throws an error if the `ndarray` method is provided a eighth argument which is not a number... @@ -253,14 +253,14 @@ import dkmeansDistance = require( './index' ); const x = new Float64Array( 10 ); const y = new Float64Array( 10 ); - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, '10' ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, true ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, false ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, null ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, undefined ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, [] ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, {} ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, ( x: number ): number => x ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, '10' ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, true ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, false ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, null ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, undefined ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, [] ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, {} ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', 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... @@ -270,11 +270,11 @@ import dkmeansDistance = require( './index' ); dkmeansDistance.ndarray(); // $ExpectError dkmeansDistance.ndarray( x.length ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean' ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1 ); // $ExpectError - dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0, 10 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean' ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1 ); // $ExpectError + dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0, 10 ); // $ExpectError } diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/c/example.c b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/c/example.c index 279873d01ed4..e99c5948f148 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/c/example.c +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/c/example.c @@ -33,13 +33,13 @@ int main( void ) { const int strideY = -1; // Compute the distance between `x` and `y`: - double d = stdlib_strided_dkmeans_distance( N, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, strideX, y, strideY ); + double d = stdlib_strided_dkmeans_distance( N, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, strideX, y, strideY ); // Print the result: printf( "Distance: %lf\n", d ); // Compute the distance between `x` and `y` with offsets: - d = stdlib_strided_dkmeans_distance_ndarray( N, STDLIB_ML_KMEANS_SQEUCLIDEAN, x, strideX, 0, y, strideY, N-1 ); + d = stdlib_strided_dkmeans_distance_ndarray( N, STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN, x, strideX, 0, y, strideY, N-1 ); // Print the result: printf( "Distance: %lf\n", d ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/index.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/index.js index c7dbad23c0c8..3877b1a315e4 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/index.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/examples/index.js @@ -30,5 +30,5 @@ console.log( x ); var y = discreteUniform( x.length, 0, 10, opts ); console.log( y ); -var out = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, -1, y.length-1 ); +var out = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, -1, y.length-1 ); console.log( out ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.js index 4a2d864436dd..9373b7b15bff 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.js @@ -44,7 +44,7 @@ var TABLE = require( './metrics.js' ); * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); * // returns 72.0 */ function dkmeansDistance( N, metric, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.native.js index 27a8c877a7dd..077ee240db74 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/dkmeans_distance.native.js @@ -45,7 +45,7 @@ var addon = require( './../src/addon.node' ); * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); * // returns 72.0 */ function dkmeansDistance( N, metric, x, strideX, y, strideY ) { diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/index.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/index.js index 1deeade2e907..eb9ac34b8c2b 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/index.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/index.js @@ -30,7 +30,7 @@ * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); * // returns 72.0 * * @example @@ -40,7 +40,7 @@ * 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 = dkmeansDistance.ndarray( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); +* var z = dkmeansDistance.ndarray( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); * // returns 72.0 */ diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/metrics.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/metrics.js index 73c1d4b3d5de..93770ee22fda 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/metrics.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/metrics.js @@ -36,7 +36,7 @@ var dcosine = require( '@stdlib/stats/strided/distances/dcosine-distance' ); * @type {Object} */ var metric2strided = { - 'sqeuclidean': dsquaredEuclidean, + 'squared-euclidean': dsquaredEuclidean, 'correlation': dcorrelation, 'cityblock': dcityblock, 'cosine': dcosine diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.js index 04cbddeeb615..867b227e679d 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.js @@ -46,7 +46,7 @@ var TABLE = require( './metrics.js' ); * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); * // returns 72.0 */ function dkmeansDistance( N, metric, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.native.js index ebe1873eaa2e..7ba14f30833e 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/lib/ndarray.native.js @@ -47,7 +47,7 @@ var addon = require( './../src/addon.node' ); * 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); +* var z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); * // returns 72.0 */ function dkmeansDistance( N, metric, x, strideX, offsetX, y, strideY, offsetY ) { diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/package.json b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/package.json index 9742ee6fde82..3432cbb9b671 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/package.json +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/package.json @@ -60,7 +60,7 @@ "dkmeans", "distance", "metric", - "sqeuclidean", + "squared-euclidean", "cosine", "correlation", "cityblock", diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/src/main.c b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/src/main.c index b56e39d6362a..78703e40e4aa 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/src/main.c +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/src/main.c @@ -56,7 +56,7 @@ double API_SUFFIX(stdlib_strided_dkmeans_distance)( const CBLAS_INT N, const enu * @return distance */ double API_SUFFIX(stdlib_strided_dkmeans_distance_ndarray)( const CBLAS_INT N, const enum STDLIB_ML_KMEANS_METRIC metric, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) { - if ( metric == STDLIB_ML_KMEANS_SQEUCLIDEAN ) { + if ( metric == STDLIB_ML_KMEANS_SQUARED_EUCLIDEAN ) { return API_SUFFIX(stdlib_strided_dsquared_euclidean_ndarray)( N, X, strideX, offsetX, Y, strideY, offsetY ); } if ( metric == STDLIB_ML_KMEANS_COSINE ) { diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.js index 59b2ce275ab3..6859dc4b2e43 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.js @@ -48,7 +48,7 @@ tape( 'the function calculates the distance according to a specified distance me 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); // 16+196+16+100+81+9 = 418 t.strictEqual( isAlmostSameValue( z, 418.0, 1 ), true, 'returns expected value' ); @@ -56,37 +56,37 @@ tape( 'the function calculates the distance according to a specified distance me x = new Float64Array( [ -4.0 ] ); y = new Float64Array( [ 10.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 196.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e10, 1.0e10, 1.0e10 ] ); y = new Float64Array( [ -1.0e10, 1.0e10, -1.0e10, -1.0e10 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 1.2e+21, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e-15, 1.0e-15, 1.0e-15 ] ); y = new Float64Array( [ -1.0e-15, -1.0e-15, -1.0e-15, -1.0e-15 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 1.6e-29, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e5, 1.0e10, 1.0e5 ] ); y = new Float64Array( [ -1.0e10, -1.0e5, -1.0e10, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 8.0000000008e+20, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e5, 1.0e-15, 1.0e5 ] ); y = new Float64Array( [ -1.0e-15, -1.0e5, -1.0e-15, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 80000000000.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.4e-14, 1.5e-14, 1.4e-14, 0.0 ] ); y = new Float64Array( [ -1.4e-14, -1.5e-14, -1.4e-14, 0.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 2.468e-27, 1 ), true, 'returns expected value' ); t.end(); @@ -100,10 +100,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu 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 = dkmeansDistance( 0, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( 0, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); - z = dkmeansDistance( -1, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( -1, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); t.end(); @@ -135,7 +135,7 @@ tape( 'the function supports stride parameters', function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, y, 2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, y, 2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -168,7 +168,7 @@ tape( 'the function supports a negative stride parameters', function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, -2, y, -2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, -2, y, -2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -207,7 +207,7 @@ tape( 'the function supports view offsets', function test( t ) { 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 = dkmeansDistance( 4, 'sqeuclidean', x1, 2, y1, 2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x1, 2, y1, 2 ); // 9+0+16+25 = 50 t.strictEqual( isAlmostSameValue( z, 50.0, 1 ), true, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.native.js index 37b58803f109..6c49457f865f 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.dkmeans_distance.native.js @@ -57,7 +57,7 @@ tape( 'the function calculates the distance according to a specified distance me 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); // 16+196+16+100+81+9 = 418 t.strictEqual( isAlmostSameValue( z, 418.0, 1 ), true, 'returns expected value' ); @@ -65,37 +65,37 @@ tape( 'the function calculates the distance according to a specified distance me x = new Float64Array( [ -4.0 ] ); y = new Float64Array( [ 10.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 196.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e10, 1.0e10, 1.0e10 ] ); y = new Float64Array( [ -1.0e10, 1.0e10, -1.0e10, -1.0e10 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 1.2e+21, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e-15, 1.0e-15, 1.0e-15 ] ); y = new Float64Array( [ -1.0e-15, -1.0e-15, -1.0e-15, -1.0e-15 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 1.6e-29, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e5, 1.0e10, 1.0e5 ] ); y = new Float64Array( [ -1.0e10, -1.0e5, -1.0e10, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 8.0000000008e+20, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e5, 1.0e-15, 1.0e5 ] ); y = new Float64Array( [ -1.0e-15, -1.0e5, -1.0e-15, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 80000000000.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.4e-14, 1.5e-14, 1.4e-14, 0.0 ] ); y = new Float64Array( [ -1.4e-14, -1.5e-14, -1.4e-14, 0.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, 2.468e-27, 1 ), true, 'returns expected value' ); t.end(); @@ -109,10 +109,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu 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 = dkmeansDistance( 0, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( 0, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); - z = dkmeansDistance( -1, 'sqeuclidean', x, 1, y, 1 ); + z = dkmeansDistance( -1, 'squared-euclidean', x, 1, y, 1 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); t.end(); @@ -144,7 +144,7 @@ tape( 'the function supports stride parameters', opts, function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, y, 2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, y, 2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -177,7 +177,7 @@ tape( 'the function supports a negative stride parameters', opts, function test( -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, -2, y, -2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, -2, y, -2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -216,7 +216,7 @@ tape( 'the function supports view offsets', opts, function test( t ) { 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 = dkmeansDistance( 4, 'sqeuclidean', x1, 2, y1, 2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x1, 2, y1, 2 ); // 9+0+16+25 = 50 t.strictEqual( isAlmostSameValue( z, 50.0, 1 ), true, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.js index 8867fd2d50f7..0e16b218fb34 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.js @@ -48,7 +48,7 @@ tape( 'the function calculates the distance according to a specified distance me 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // 16+196+16+100+81+9 = 418 t.strictEqual( isAlmostSameValue( z, 418.0, 1 ), true, 'returns expected value' ); @@ -56,37 +56,37 @@ tape( 'the function calculates the distance according to a specified distance me x = new Float64Array( [ -4.0 ] ); y = new Float64Array( [ 10.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 196.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e10, 1.0e10, 1.0e10 ] ); y = new Float64Array( [ -1.0e10, 1.0e10, -1.0e10, -1.0e10 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 1.2e+21, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e-15, 1.0e-15, 1.0e-15 ] ); y = new Float64Array( [ -1.0e-15, -1.0e-15, -1.0e-15, -1.0e-15 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 1.6e-29, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e5, 1.0e10, 1.0e5 ] ); y = new Float64Array( [ -1.0e10, -1.0e5, -1.0e10, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 8.0000000008e+20, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e5, 1.0e-15, 1.0e5 ] ); y = new Float64Array( [ -1.0e-15, -1.0e5, -1.0e-15, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 80000000000.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.4e-14, 1.5e-14, 1.4e-14, 0.0 ] ); y = new Float64Array( [ -1.4e-14, -1.5e-14, -1.4e-14, 0.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 2.468e-27, 1 ), true, 'returns expected value' ); t.end(); @@ -100,10 +100,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu 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 = dkmeansDistance( 0, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( 0, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); - z = dkmeansDistance( -1, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( -1, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); t.end(); @@ -135,7 +135,7 @@ tape( 'the function supports stride parameters', function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, 0, y, 2, 0 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, 0, y, 2, 0 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -168,7 +168,7 @@ tape( 'the function supports negative stride parameters', function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, -2, x.length-2, y, -2, y.length-2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, -2, x.length-2, y, -2, y.length-2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -203,7 +203,7 @@ tape( 'the function supports offset parameters', function test( t ) { 4.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, 1, y, 2, 1 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, 1, y, 2, 1 ); // 9+0+16+25 = 50 t.strictEqual( isAlmostSameValue( z, 50.0, 1 ), true, 'returns expected value' ); diff --git a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.native.js b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.native.js index 11f86e4181c4..29209704a29c 100644 --- a/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.native.js +++ b/lib/node_modules/@stdlib/ml/strided/dkmeans-distance/test/test.ndarray.native.js @@ -57,7 +57,7 @@ tape( 'the function calculates the distance according to a specified distance me 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 = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); // 16+196+16+100+81+9 = 418 t.strictEqual( isAlmostSameValue( z, 418.0, 1 ), true, 'returns expected value' ); @@ -65,37 +65,37 @@ tape( 'the function calculates the distance according to a specified distance me x = new Float64Array( [ -4.0 ] ); y = new Float64Array( [ 10.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 196.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e10, 1.0e10, 1.0e10 ] ); y = new Float64Array( [ -1.0e10, 1.0e10, -1.0e10, -1.0e10 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 1.2e+21, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e-15, 1.0e-15, 1.0e-15 ] ); y = new Float64Array( [ -1.0e-15, -1.0e-15, -1.0e-15, -1.0e-15 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 1.6e-29, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e10, 1.0e5, 1.0e10, 1.0e5 ] ); y = new Float64Array( [ -1.0e10, -1.0e5, -1.0e10, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 8.0000000008e+20, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.0e-15, 1.0e5, 1.0e-15, 1.0e5 ] ); y = new Float64Array( [ -1.0e-15, -1.0e5, -1.0e-15, -1.0e5 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 80000000000.0, 1 ), true, 'returns expected value' ); x = new Float64Array( [ 1.4e-14, 1.5e-14, 1.4e-14, 0.0 ] ); y = new Float64Array( [ -1.4e-14, -1.5e-14, -1.4e-14, 0.0 ] ); - z = dkmeansDistance( x.length, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( x.length, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, 2.468e-27, 1 ), true, 'returns expected value' ); t.end(); @@ -109,10 +109,10 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu 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 = dkmeansDistance( 0, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( 0, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); - z = dkmeansDistance( -1, 'sqeuclidean', x, 1, 0, y, 1, 0 ); + z = dkmeansDistance( -1, 'squared-euclidean', x, 1, 0, y, 1, 0 ); t.strictEqual( isAlmostSameValue( z, NaN, 0 ), true, 'returns expected value' ); t.end(); @@ -144,7 +144,7 @@ tape( 'the function supports stride parameters', opts, function test( t ) { -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, 0, y, 2, 0 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, 0, y, 2, 0 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -177,7 +177,7 @@ tape( 'the function supports negative stride parameters', opts, function test( t -1.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, -2, x.length-2, y, -2, y.length-2 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, -2, x.length-2, y, -2, y.length-2 ); // 49+1+81+16 = 147 t.strictEqual( isAlmostSameValue( z, 147.0, 1 ), true, 'returns expected value' ); @@ -212,7 +212,7 @@ tape( 'the function supports offset parameters', opts, function test( t ) { 4.0 ]); - z = dkmeansDistance( 4, 'sqeuclidean', x, 2, 1, y, 2, 1 ); + z = dkmeansDistance( 4, 'squared-euclidean', x, 2, 1, y, 2, 1 ); // 9+0+16+25 = 50 t.strictEqual( isAlmostSameValue( z, 50.0, 1 ), true, 'returns expected value' );