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feat: add tests
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‎lib/node_modules/@stdlib/stats/strided/dztest2/test/test.dztest2.js‎

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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'use strict';
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// MODULES //
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var tape = require( 'tape' );
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var Float64Results = require( '@stdlib/stats/base/ztest/two-sample/results/float64' );
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var isfinite = require( '@stdlib/math/base/assert/is-finite' );
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var isnan = require( '@stdlib/math/base/assert/is-nan' );
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var dfill = require( '@stdlib/blas/ext/base/dfill' ).ndarray;
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var normalFactory = require( '@stdlib/random/array/normal' ).factory;
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var PINF = require( '@stdlib/constants/float64/pinf' );
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var NINF = require( '@stdlib/constants/float64/ninf' );
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var dztest2 = require( './../lib/dztest2.js' );
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// VARIABLES //
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var normal = normalFactory({
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'seed': 12345
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});
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// TESTS //
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tape( 'main export is a function', function test( t ) {
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t.ok( true, __filename );
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t.strictEqual( typeof dztest2, 'function', 'main export is a function' );
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t.end();
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});
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tape( 'the function performs a two-sample Z-test over strided arrays (alternative=two-sided)', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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results = new Float64Results();
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'two-sided', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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out = dztest2( x.length, y.length, 'two-sided', 0.1, 100.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 4.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 2.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'two-sided', 0.1, 2.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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t.end();
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});
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tape( 'the function performs a two-sample Z-test over strided arrays (alternative=greater)', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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results = new Float64Results();
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 2.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'greater', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'greater', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( out.ci[ 1 ], PINF, 'returns expected value' );
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'greater', 0.1, -1.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'greater', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( out.ci[ 1 ], PINF, 'returns expected value' );
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t.end();
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});
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tape( 'the function performs a two-sample Z-test over strided arrays (alternative=less)', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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results = new Float64Results();
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 2.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'less', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'less', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( out.ci[ 0 ], NINF, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10000, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( x.length, y.length, 'less', 0.1, 1.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'less', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( out.ci[ 0 ], NINF, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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t.end();
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});
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tape( 'if provided an `NX` or `NY` parameter less than or equal to `0`, the function returns `NaN` results', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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results = new Float64Results();
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x = normal( 10, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( 10, 0.0, 1.0, {
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'dtype': 'float64'
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});
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out = dztest2( 0, y.length, 'two-sided', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), true, 'returns expected value' );
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out = dztest2( -1, y.length, 'two-sided', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), true, 'returns expected value' );
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out = dztest2( x.length, 0, 'two-sided', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), true, 'returns expected value' );
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out = dztest2( x.length, -1, 'two-sided', 0.1, 0.0, 1.0, x, 1, 1.0, y, 1, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), true, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), true, 'returns expected value' );
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t.end();
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});
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tape( 'the function supports a stride parameter', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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var N;
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N = 10000;
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results = new Float64Results();
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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dfill( N, NaN, y, 2, 1 );
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out = dztest2( N, N, 'two-sided', 0.1, 0.0, 1.0, x, 2, 1.0, y, 2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 4.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( N*2, 2.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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dfill( N, NaN, y, 2, 1 );
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out = dztest2( N, N, 'two-sided', 0.1, 10.0, 1.0, x, 2, 1.0, y, 2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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t.end();
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});
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tape( 'the function supports a negative stride parameter', function test( t ) {
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var results;
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var out;
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var x;
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var y;
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var N;
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N = 10000;
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results = new Float64Results();
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( N*2, 0.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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dfill( N, NaN, y, 2, 1 );
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out = dztest2( N, N, 'two-sided', 0.1, 0.0, 1.0, x, -2, 1.0, y, -2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, false, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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// Generate arrays with a sufficiently large sample size to effectively guarantee expected results:
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x = normal( N*2, 100.0, 1.0, {
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'dtype': 'float64'
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});
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y = normal( N*2, 100.0, 1.0, {
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'dtype': 'float64'
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});
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dfill( N, NaN, x, 2, 1 );
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dfill( N, NaN, y, 2, 1 );
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out = dztest2( N, N, 'two-sided', 0.1, 0.0, 1.0, x, -2, 1.0, y, -2, results );
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t.strictEqual( out, results, 'returns expected value' );
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t.strictEqual( out.rejected, true, 'returns expected value' );
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t.strictEqual( out.alternative, 'two-sided', 'returns expected value' );
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t.strictEqual( isnan( out.statistic ), false, 'returns expected value' );
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t.strictEqual( isnan( out.pValue ), false, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 0 ] ), true, 'returns expected value' );
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t.strictEqual( isfinite( out.ci[ 1 ] ), true, 'returns expected value' );
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t.end();
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});

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