feat: add ml/strided/dkmeans-init-plus-plus

lib/node_modules/@stdlib/ml/strided/dkmeans-init-plus-plus/benchmark/benchmark.js

@@ -0,0 +1,159 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dkmeansInitPlusPlus = require( './../lib/dkmeans_init_plus_plus.js' );
+
+
+// VARIABLES //
+
+var LAYOUTS = [
+	'row-major',
+	'column-major'
+];
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {string} order - storage layout
+* @param {PositiveInteger} k - number of clusters
+* @param {PositiveInteger} M - number of data points
+* @param {PositiveInteger} N - number of features
+* @param {string} metric - distance metric
+* @param {PositiveInteger} trials - number of potential centroids per iteration (>= 1)
+* @returns {Function} benchmark function
+*/
+function createBenchmark( order, k, M, N, metric, trials ) {
+	var out = new Float64Array( k*N );
+	var x = uniform( M*N, -100.0, 100.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var c;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			c = dkmeansInitPlusPlus( order, k, M, N, out, N, x, N, metric, trials, 44 ); // eslint-disable-line max-len
+			if ( isnan( c[ i%(k*N) ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( c[ 0 ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var metrics;
+	var trials;
+	var min;
+	var max;
+	var M;
+	var N;
+	var k;
+	var t;
+	var m;
+	var i;
+	var j;
+	var f;
+
+	min = 1; // 10^min
+	max = 4; // 10^max
+
+	// Benchmark: vary order with defaults k=2, M=100, N=2, metric=sqeuclidean, trials=1...
+	for ( i = 0; i <= LAYOUTS.length; i++ ) {
+		f = createBenchmark( LAYOUTS[ i ], 2, 100, 2, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_M:order=%s,k=2,M=100,N=2,metric=sqeuclidean,trials=1', pkg, LAYOUTS[ i ] ), f );
+	}
+
+	// Benchmark: vary number of data points (M) with defaults k=2, N=2, metric=sqeuclidean, trials=1...
+	for ( i = min; i <= max; i++ ) {
+		M = pow( 10, i );
+		f = createBenchmark( 'row-major', 2, M, 2, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_M:order=row-major,k=2,M=%d,N=2,metric=sqeuclidean,trials=1', pkg, M ), f );
+	}
+
+	// Benchmark: vary number of features (N) with defaults k=2, M=10, metric=sqeuclidean, trials=1...
+	for ( i = min; i <= max; i++ ) {
+		N = pow( 10, i );
+		f = createBenchmark( 'row-major', 2, 10, N, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_N:order=row-major,k=2,M=1000,N=%d,metric=sqeuclidean,trials=1', pkg, N ), f );
+	}
+
+	// Benchmark: vary number of clusters (k) with defaults M=1000, N=2, metric=sqeuclidean, trials=1...
+	for ( i = 1; i <= 4; i++ ) {
+		k = pow( 2, i );
+		f = createBenchmark( 'row-major', k, 1000, 2, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_k:order=row-major,k=%d,M=1000,N=2,metric=sqeuclidean,trials=1', pkg, k ), f );
+	}
+
+	// Benchmark: vary number of trials with defaults k=2, M=1000, N=2, metric=sqeuclidean...
+	trials = [ 1, 10, 100, 1000 ];
+	for ( j = 0; j < trials.length; j++ ) {
+		t = trials[ j ];
+		f = createBenchmark( 'row-major', 2, 1000, 2, 'sqeuclidean', t );
+		bench( format( '%s::vary_trials:order=row-major,k=2,M=1000,N=2,metric=sqeuclidean,trials=%d', pkg, t ), f );
+	}
+
+	// Benchmark: vary metric with defaults k=2, M=1000, N=2, trials=1...
+	metrics = [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ];
+	for ( j = 0; j < metrics.length; j++ ) {
+		m = metrics[ j ];
+		f = createBenchmark( 'row-major', 2, 1000, 2, m, 1 );
+		bench( format( '%s::vary_metric:order=row-major,k=2,M=1000,N=2,metric=%s,trials=1', pkg, m ), f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/ml/strided/dkmeans-init-plus-plus/benchmark/benchmark.ndarray.js

@@ -0,0 +1,147 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var Float64Array = require( '@stdlib/array/float64' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dkmeansInitPlusPlus = require( './../lib/ndarray.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} k - number of clusters
+* @param {PositiveInteger} M - number of data points
+* @param {PositiveInteger} N - number of features
+* @param {string} metric - distance metric
+* @param {PositiveInteger} trials - number of potential centroids per iteration (>= 1)
+* @returns {Function} benchmark function
+*/
+function createBenchmark( k, M, N, metric, trials ) {
+	var out = new Float64Array( k*N );
+	var x = uniform( M*N, -100.0, 100.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var c;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			c = dkmeansInitPlusPlus( k, M, N, out, N, 1, 0, x, N, 1, 0, metric, trials, 44 ); // eslint-disable-line max-len
+			if ( isnan( c[ i%(k*N) ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( c[ 0 ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var metrics;
+	var trials;
+	var min;
+	var max;
+	var M;
+	var N;
+	var k;
+	var t;
+	var m;
+	var i;
+	var j;
+	var f;
+
+	min = 1; // 10^min
+	max = 4; // 10^max
+
+	// Benchmark: vary number of data points (M) with defaults k=2, N=2, metric=sqeuclidean, trials=1...
+	for ( i = min; i <= max; i++ ) {
+		M = pow( 10, i );
+		f = createBenchmark( 2, M, 2, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_M:k=2,M=%d,N=2,metric=sqeuclidean,trials=1', pkg, M ), f );
+	}
+
+	// Benchmark: vary number of features (N) with defaults k=2, M=10, metric=sqeuclidean, trials=1...
+	for ( i = min; i <= max; i++ ) {
+		N = pow( 10, i );
+		f = createBenchmark( 2, 10, N, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_N:k=2,M=1000,N=%d,metric=sqeuclidean,trials=1', pkg, N ), f );
+	}
+
+	// Benchmark: vary number of clusters (k) with defaults M=1000, N=2, metric=sqeuclidean, trials=1...
+	for ( i = 1; i <= 4; i++ ) {
+		k = pow( 2, i );
+		f = createBenchmark( k, 1000, 2, 'sqeuclidean', 1 );
+		bench( format( '%s::vary_k:k=%d,M=1000,N=2,metric=sqeuclidean,trials=1', pkg, k ), f );
+	}
+
+	// Benchmark: vary number of trials with defaults k=2, M=1000, N=2, metric=sqeuclidean...
+	trials = [ 1, 10, 100 ];
+	for ( j = 0; j < trials.length; j++ ) {
+		t = trials[ j ];
+		f = createBenchmark( 2, 1000, 2, 'sqeuclidean', t );
+		bench( format( '%s::vary_trials:k=2,M=1000,N=2,metric=sqeuclidean,trials=%d', pkg, t ), f );
+	}
+
+	// Benchmark: vary metric with defaults k=2, M=1000, N=2, trials=1...
+	metrics = [ 'sqeuclidean', 'cosine', 'cityblock', 'correlation' ];
+	for ( j = 0; j < metrics.length; j++ ) {
+		m = metrics[ j ];
+		f = createBenchmark( 2, 1000, 2, m, 1 );
+		bench( format( '%s::vary_metric:k=2,M=1000,N=2,metric=%s,trials=1', pkg, m ), f );
+	}
+}
+
+main();