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Update to phpunit 8 and bump min php to 7.2 (#367)

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* Update to phpunit 8

* Require at least PHP 7.2
This commit is contained in:
Marcin Michalski 2019-04-10 20:42:59 +02:00 committed by Arkadiusz Kondas
parent cefb4fc7a7
commit db82afa263
43 changed files with 176 additions and 179 deletions
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3
.gitignore vendored
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@ -1,4 +1,5 @@
/vendor/ /vendor/
.php_cs.cache
/build /build
/tests/Performance/Data/*.csv /tests/Performance/Data/*.csv
.php_cs.cache
.phpunit.result.cache

6
.travis.yml
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@ -4,13 +4,9 @@ matrix:
fast_finish: true fast_finish: true
include: include:
- os: linux
php: '7.1'
env: DISABLE_XDEBUG="true" STATIC_ANALYSIS="true"
- os: linux - os: linux
php: '7.2' php: '7.2'
env: PHPUNIT_FLAGS="--coverage-clover build/logs/clover.xml" env: PHPUNIT_FLAGS="--coverage-clover build/logs/clover.xml" DISABLE_XDEBUG="true" STATIC_ANALYSIS="true"
- os: linux - os: linux
php: '7.3' php: '7.3'

4
README.md
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@ -1,6 +1,6 @@
# PHP-ML - Machine Learning library for PHP # PHP-ML - Machine Learning library for PHP
[![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.1-8892BF.svg)](https://php.net/) [![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.2-8892BF.svg)](https://php.net/)
[![Latest Stable Version](https://img.shields.io/packagist/v/php-ai/php-ml.svg)](https://packagist.org/packages/php-ai/php-ml) [![Latest Stable Version](https://img.shields.io/packagist/v/php-ai/php-ml.svg)](https://packagist.org/packages/php-ai/php-ml)
[![Build Status](https://travis-ci.org/php-ai/php-ml.svg?branch=master)](https://travis-ci.org/php-ai/php-ml) [![Build Status](https://travis-ci.org/php-ai/php-ml.svg?branch=master)](https://travis-ci.org/php-ai/php-ml)
[![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/) [![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/)
@ -15,7 +15,7 @@
Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library. Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
PHP-ML requires PHP >= 7.1. PHP-ML requires PHP >= 7.2.
Simple example of classification: Simple example of classification:
```php ```php

4
composer.json
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@ -20,14 +20,14 @@
} }
], ],
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"php": "^7.1" "php": "^7.2"
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}, },

71
composer.lock generated
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@ -4,7 +4,7 @@
"Read more about it at https://getcomposer.org/doc/01-basic-usage.md#installing-dependencies", "Read more about it at https://getcomposer.org/doc/01-basic-usage.md#installing-dependencies",
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@ -1881,40 +1881,40 @@
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}, },
"autoload": { "autoload": {
@ -1940,7 +1940,7 @@
"testing", "testing",
"xunit" "xunit"
], ],
"time": "2018-10-31T16:06:48+00:00" "time": "2019-02-26T07:38:26+00:00"
}, },
{ {
"name": "phpunit/php-file-iterator", "name": "phpunit/php-file-iterator",
@ -2133,16 +2133,16 @@
}, },
{ {
"name": "phpunit/phpunit", "name": "phpunit/phpunit",
"version": "7.5.7", "version": "8.0.5",
"source": { "source": {
"type": "git", "type": "git",
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"shasum": "" "shasum": ""
}, },
"require": { "require": {
@ -2152,27 +2152,25 @@
"ext-libxml": "*", "ext-libxml": "*",
"ext-mbstring": "*", "ext-mbstring": "*",
"ext-xml": "*", "ext-xml": "*",
"ext-xmlwriter": "*",
"myclabs/deep-copy": "^1.7", "myclabs/deep-copy": "^1.7",
"phar-io/manifest": "^1.0.2", "phar-io/manifest": "^1.0.2",
"phar-io/version": "^2.0", "phar-io/version": "^2.0",
"php": "^7.1", "php": "^7.2",
"phpspec/prophecy": "^1.7", "phpspec/prophecy": "^1.7",
"phpunit/php-code-coverage": "^6.0.7", "phpunit/php-code-coverage": "^7.0",
"phpunit/php-file-iterator": "^2.0.1", "phpunit/php-file-iterator": "^2.0.1",
"phpunit/php-text-template": "^1.2.1", "phpunit/php-text-template": "^1.2.1",
"phpunit/php-timer": "^2.1", "phpunit/php-timer": "^2.1",
"sebastian/comparator": "^3.0", "sebastian/comparator": "^3.0",
"sebastian/diff": "^3.0", "sebastian/diff": "^3.0",
"sebastian/environment": "^4.0", "sebastian/environment": "^4.1",
"sebastian/exporter": "^3.1", "sebastian/exporter": "^3.1",
"sebastian/global-state": "^2.0", "sebastian/global-state": "^3.0",
"sebastian/object-enumerator": "^3.0.3", "sebastian/object-enumerator": "^3.0.3",
"sebastian/resource-operations": "^2.0", "sebastian/resource-operations": "^2.0",
"sebastian/version": "^2.0.1" "sebastian/version": "^2.0.1"
}, },
"conflict": {
"phpunit/phpunit-mock-objects": "*"
},
"require-dev": { "require-dev": {
"ext-pdo": "*" "ext-pdo": "*"
}, },
@ -2187,7 +2185,7 @@
"type": "library", "type": "library",
"extra": { "extra": {
"branch-alias": { "branch-alias": {
"dev-master": "7.5-dev" "dev-master": "8.0-dev"
} }
}, },
"autoload": { "autoload": {
@ -2213,7 +2211,7 @@
"testing", "testing",
"xunit" "xunit"
], ],
"time": "2019-03-16T07:31:17+00:00" "time": "2019-03-16T07:33:46+00:00"
}, },
{ {
"name": "psr/cache", "name": "psr/cache",
@ -2692,23 +2690,26 @@
}, },
{ {
"name": "sebastian/global-state", "name": "sebastian/global-state",
"version": "2.0.0", "version": "3.0.0",
"source": { "source": {
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"url": "https://github.com/sebastianbergmann/global-state.git", "url": "https://github.com/sebastianbergmann/global-state.git",
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"shasum": "" "shasum": ""
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"php": "^7.0" "php": "^7.2",
"sebastian/object-reflector": "^1.1.1",
"sebastian/recursion-context": "^3.0"
}, },
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"phpunit/phpunit": "^6.0" "ext-dom": "*",
"phpunit/phpunit": "^8.0"
}, },
"suggest": { "suggest": {
"ext-uopz": "*" "ext-uopz": "*"
@ -2716,7 +2717,7 @@
"type": "library", "type": "library",
"extra": { "extra": {
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"dev-master": "2.0-dev" "dev-master": "3.0-dev"
} }
}, },
"autoload": { "autoload": {
@ -2739,7 +2740,7 @@
"keywords": [ "keywords": [
"global state" "global state"
], ],
"time": "2017-04-27T15:39:26+00:00" "time": "2019-02-01T05:30:01+00:00"
}, },
{ {
"name": "sebastian/object-enumerator", "name": "sebastian/object-enumerator",
@ -4749,7 +4750,7 @@
"prefer-stable": false, "prefer-stable": false,
"prefer-lowest": false, "prefer-lowest": false,
"platform": { "platform": {
"php": "^7.1" "php": "^7.2"
}, },
"platform-dev": [] "platform-dev": []
} }

4
docs/index.md
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@ -1,6 +1,6 @@
# PHP-ML - Machine Learning library for PHP # PHP-ML - Machine Learning library for PHP
[![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.1-8892BF.svg)](https://php.net/) [![Minimum PHP Version](https://img.shields.io/badge/php-%3E%3D%207.2-8892BF.svg)](https://php.net/)
[![Latest Stable Version](https://img.shields.io/packagist/v/php-ai/php-ml.svg)](https://packagist.org/packages/php-ai/php-ml) [![Latest Stable Version](https://img.shields.io/packagist/v/php-ai/php-ml.svg)](https://packagist.org/packages/php-ai/php-ml)
[![Build Status](https://travis-ci.org/php-ai/php-ml.svg?branch=master)](https://travis-ci.org/php-ai/php-ml) [![Build Status](https://travis-ci.org/php-ai/php-ml.svg?branch=master)](https://travis-ci.org/php-ai/php-ml)
[![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/) [![Documentation Status](https://readthedocs.org/projects/php-ml/badge/?version=master)](http://php-ml.readthedocs.org/)
@ -15,7 +15,7 @@
Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library. Fresh approach to Machine Learning in PHP. Algorithms, Cross Validation, Neural Network, Preprocessing, Feature Extraction and much more in one library.
PHP-ML requires PHP >= 7.1. PHP-ML requires PHP >= 7.2.
Simple example of classification: Simple example of classification:
```php ```php

10
tests/Classification/Linear/LogisticRegressionTest.php
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@ -171,12 +171,12 @@ class LogisticRegressionTest extends TestCase
$zero = $method->invoke($predictor, [0.1, 0.1], 0); $zero = $method->invoke($predictor, [0.1, 0.1], 0);
$one = $method->invoke($predictor, [0.1, 0.1], 1); $one = $method->invoke($predictor, [0.1, 0.1], 1);
self::assertEquals(1, $zero + $one, '', 1e-6); self::assertEqualsWithDelta(1, $zero + $one, 1e-6);
self::assertTrue($zero > $one); self::assertTrue($zero > $one);
$zero = $method->invoke($predictor, [0.9, 0.9], 0); $zero = $method->invoke($predictor, [0.9, 0.9], 0);
$one = $method->invoke($predictor, [0.9, 0.9], 1); $one = $method->invoke($predictor, [0.9, 0.9], 1);
self::assertEquals(1, $zero + $one, '', 1e-6); self::assertEqualsWithDelta(1, $zero + $one, 1e-6);
self::assertTrue($zero < $one); self::assertTrue($zero < $one);
} }
@ -213,9 +213,9 @@ class LogisticRegressionTest extends TestCase
$two = $method->invoke($predictor, [3.0, 9.5], 2); $two = $method->invoke($predictor, [3.0, 9.5], 2);
$not_two = $method->invoke($predictor, [3.0, 9.5], 'not_2'); $not_two = $method->invoke($predictor, [3.0, 9.5], 'not_2');
self::assertEquals(1, $zero + $not_zero, '', 1e-6); self::assertEqualsWithDelta(1, $zero + $not_zero, 1e-6);
self::assertEquals(1, $one + $not_one, '', 1e-6); self::assertEqualsWithDelta(1, $one + $not_one, 1e-6);
self::assertEquals(1, $two + $not_two, '', 1e-6); self::assertEqualsWithDelta(1, $two + $not_two, 1e-6);
self::assertTrue($zero < $two); self::assertTrue($zero < $two);
self::assertTrue($one < $two); self::assertTrue($one < $two);
} }

6
tests/DimensionReduction/KernelPCATest.php
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@ -33,14 +33,14 @@ class KernelPCATest extends TestCase
[-0.13128352866095], [-0.20865959471756], [-0.17531601535848], [0.4240660966961], [-0.13128352866095], [-0.20865959471756], [-0.17531601535848], [0.4240660966961],
[0.36351946685163], [-0.14334173054136], [0.22454914091011], [0.15035027480881], ]; [0.36351946685163], [-0.14334173054136], [0.22454914091011], [0.15035027480881], ];
$kpca = new KernelPCA(KernelPCA::KERNEL_RBF, null, 1, 15); $kpca = new KernelPCA(KernelPCA::KERNEL_RBF, null, 1, 15.);
$reducedData = $kpca->fit($data); $reducedData = $kpca->fit($data);
// Due to the fact that the sign of values can be flipped // Due to the fact that the sign of values can be flipped
// during the calculation of eigenValues, we have to compare // during the calculation of eigenValues, we have to compare
// absolute value of the values // absolute value of the values
array_map(function ($val1, $val2) use ($epsilon): void { array_map(function ($val1, $val2) use ($epsilon): void {
self::assertEquals(abs($val1), abs($val2), '', $epsilon); self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
}, $transformed, $reducedData); }, $transformed, $reducedData);
// Fitted KernelPCA object can also transform an arbitrary sample of the // Fitted KernelPCA object can also transform an arbitrary sample of the
@ -48,7 +48,7 @@ class KernelPCATest extends TestCase
$newData = [1.25, 2.25]; $newData = [1.25, 2.25];
$newTransformed = [0.18956227539216]; $newTransformed = [0.18956227539216];
$newTransformed2 = $kpca->transform($newData); $newTransformed2 = $kpca->transform($newData);
self::assertEquals(abs($newTransformed[0]), abs($newTransformed2[0]), '', $epsilon); self::assertEqualsWithDelta(abs($newTransformed[0]), abs($newTransformed2[0]), $epsilon);
} }
public function testKernelPCAThrowWhenKernelInvalid(): void public function testKernelPCAThrowWhenKernelInvalid(): void

2
tests/DimensionReduction/LDATest.php
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@ -51,7 +51,7 @@ class LDATest extends TestCase
// absolute value of the values // absolute value of the values
$row1 = array_map('abs', $row1); $row1 = array_map('abs', $row1);
$row2 = array_map('abs', $row2); $row2 = array_map('abs', $row2);
self::assertEquals($row1, $row2, '', $epsilon); self::assertEqualsWithDelta($row1, $row2, $epsilon);
}; };
array_map($check, $control, $transformed2); array_map($check, $control, $transformed2);

4
tests/DimensionReduction/PCATest.php
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@ -42,7 +42,7 @@ class PCATest extends TestCase
// during the calculation of eigenValues, we have to compare // during the calculation of eigenValues, we have to compare
// absolute value of the values // absolute value of the values
array_map(function ($val1, $val2) use ($epsilon): void { array_map(function ($val1, $val2) use ($epsilon): void {
self::assertEquals(abs($val1), abs($val2), '', $epsilon); self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
}, $transformed, $reducedData); }, $transformed, $reducedData);
// Test fitted PCA object to transform an arbitrary sample of the // Test fitted PCA object to transform an arbitrary sample of the
@ -52,7 +52,7 @@ class PCATest extends TestCase
$newRow2 = $pca->transform($row); $newRow2 = $pca->transform($row);
array_map(function ($val1, $val2) use ($epsilon): void { array_map(function ($val1, $val2) use ($epsilon): void {
self::assertEquals(abs($val1), abs($val2), '', $epsilon); self::assertEqualsWithDelta(abs($val1), abs($val2), $epsilon);
}, $newRow, $newRow2); }, $newRow, $newRow2);
} }
} }

2
tests/FeatureExtraction/TfIdfTransformerTest.php
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@ -54,6 +54,6 @@ class TfIdfTransformerTest extends TestCase
$transformer = new TfIdfTransformer($samples); $transformer = new TfIdfTransformer($samples);
$transformer->transform($samples); $transformer->transform($samples);
self::assertEquals($tfIdfSamples, $samples, '', 0.001); self::assertEqualsWithDelta($tfIdfSamples, $samples, 0.001);
} }
} }

3
tests/FeatureSelection/ScoringFunction/ANOVAFValueTest.php
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@ -15,10 +15,9 @@ final class ANOVAFValueTest extends TestCase
$dataset = new IrisDataset(); $dataset = new IrisDataset();
$function = new ANOVAFValue(); $function = new ANOVAFValue();
self::assertEquals( self::assertEqualsWithDelta(
[119.2645, 47.3644, 1179.0343, 959.3244], [119.2645, 47.3644, 1179.0343, 959.3244],
$function->score($dataset->getSamples(), $dataset->getTargets()), $function->score($dataset->getSamples(), $dataset->getTargets()),
'',
0.0001 0.0001
); );
} }

4
tests/FeatureSelection/ScoringFunction/UnivariateLinearRegressionTest.php
View File

@ -15,7 +15,7 @@ final class UnivariateLinearRegressionTest extends TestCase
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400]; $targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
$function = new UnivariateLinearRegression(); $function = new UnivariateLinearRegression();
self::assertEquals([6.97286, 6.48558], $function->score($samples, $targets), '', 0.0001); self::assertEqualsWithDelta([6.97286, 6.48558], $function->score($samples, $targets), 0.0001);
} }
public function testRegressionScoreWithoutCenter(): void public function testRegressionScoreWithoutCenter(): void
@ -24,6 +24,6 @@ final class UnivariateLinearRegressionTest extends TestCase
$targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400]; $targets = [2000, 2750, 15500, 960, 4400, 8800, 7100, 2550, 1025, 5900, 4600, 4400];
$function = new UnivariateLinearRegression(false); $function = new UnivariateLinearRegression(false);
self::assertEquals([1.74450, 18.08347], $function->score($samples, $targets), '', 0.0001); self::assertEqualsWithDelta([1.74450, 18.08347], $function->score($samples, $targets), 0.0001);
} }
} }

6
tests/Helper/Optimizer/ConjugateGradientTest.php
View File

@ -33,7 +33,7 @@ class ConjugateGradientTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
} }
public function testRunOptimizationWithCustomInitialTheta(): void public function testRunOptimizationWithCustomInitialTheta(): void
@ -61,7 +61,7 @@ class ConjugateGradientTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1.087708, 2.212034], $theta, '', 0.000001); self::assertEqualsWithDelta([-1.087708, 2.212034], $theta, 0.000001);
} }
public function testRunOptimization2Dim(): void public function testRunOptimization2Dim(): void
@ -89,7 +89,7 @@ class ConjugateGradientTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2, -3], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
} }
public function testThrowExceptionOnInvalidTheta(): void public function testThrowExceptionOnInvalidTheta(): void

4
tests/Helper/Optimizer/GDTest.php
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@ -32,7 +32,7 @@ class GDTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
} }
public function testRunOptimization2Dim(): void public function testRunOptimization2Dim(): void
@ -60,6 +60,6 @@ class GDTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2, -3], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
} }
} }

4
tests/Helper/Optimizer/StochasticGDTest.php
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@ -32,7 +32,7 @@ class StochasticGDTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2], $theta, 0.1);
} }
public function testRunOptimization2Dim(): void public function testRunOptimization2Dim(): void
@ -60,6 +60,6 @@ class StochasticGDTest extends TestCase
$theta = $optimizer->runOptimization($samples, $targets, $callback); $theta = $optimizer->runOptimization($samples, $targets, $callback);
self::assertEquals([-1, 2, -3], $theta, '', 0.1); self::assertEqualsWithDelta([-1, 2, -3], $theta, 0.1);
} }
} }

6
tests/Math/Distance/MinkowskiTest.php
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@ -47,7 +47,7 @@ class MinkowskiTest extends TestCase
$expectedDistance = 2.080; $expectedDistance = 2.080;
$actualDistance = $this->distanceMetric->distance($a, $b); $actualDistance = $this->distanceMetric->distance($a, $b);
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001); self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
} }
public function testCalculateDistanceForThreeDimensions(): void public function testCalculateDistanceForThreeDimensions(): void
@ -58,7 +58,7 @@ class MinkowskiTest extends TestCase
$expectedDistance = 5.819; $expectedDistance = 5.819;
$actualDistance = $this->distanceMetric->distance($a, $b); $actualDistance = $this->distanceMetric->distance($a, $b);
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001); self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
} }
public function testCalculateDistanceForThreeDimensionsWithDifferentLambda(): void public function testCalculateDistanceForThreeDimensionsWithDifferentLambda(): void
@ -71,6 +71,6 @@ class MinkowskiTest extends TestCase
$expectedDistance = 5.300; $expectedDistance = 5.300;
$actualDistance = $distanceMetric->distance($a, $b); $actualDistance = $distanceMetric->distance($a, $b);
self::assertEquals($expectedDistance, $actualDistance, '', $delta = 0.001); self::assertEqualsWithDelta($expectedDistance, $actualDistance, $delta = 0.001);
} }
} }

6
tests/Math/Kernel/RBFTest.php
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@ -15,13 +15,13 @@ class RBFTest extends TestCase
$rbf = new RBF($gamma = 0.001); $rbf = new RBF($gamma = 0.001);
self::assertEquals(1, $rbf->compute([1, 2], [1, 2])); self::assertEquals(1, $rbf->compute([1, 2], [1, 2]));
self::assertEquals(0.97336, $rbf->compute([1, 2, 3], [4, 5, 6]), '', $delta = 0.0001); self::assertEqualsWithDelta(0.97336, $rbf->compute([1, 2, 3], [4, 5, 6]), $delta = 0.0001);
self::assertEquals(0.00011, $rbf->compute([4, 5], [1, 100]), '', $delta = 0.0001); self::assertEqualsWithDelta(0.00011, $rbf->compute([4, 5], [1, 100]), $delta = 0.0001);
$rbf = new RBF($gamma = 0.2); $rbf = new RBF($gamma = 0.2);
self::assertEquals(1, $rbf->compute([1, 2], [1, 2])); self::assertEquals(1, $rbf->compute([1, 2], [1, 2]));
self::assertEquals(0.00451, $rbf->compute([1, 2, 3], [4, 5, 6]), '', $delta = 0.0001); self::assertEqualsWithDelta(0.00451, $rbf->compute([1, 2, 3], [4, 5, 6]), $delta = 0.0001);
self::assertEquals(0, $rbf->compute([4, 5], [1, 100])); self::assertEquals(0, $rbf->compute([4, 5], [1, 100]));
} }

20
tests/Math/LinearAlgebra/EigenvalueDecompositionTest.php
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@ -21,11 +21,11 @@ class EigenvalueDecompositionTest extends TestCase
$decomp = new EigenvalueDecomposition($matrix); $decomp = new EigenvalueDecomposition($matrix);
self::assertEquals([0.0490833989, 1.28402771], $decomp->getRealEigenvalues(), '', 0.001); self::assertEqualsWithDelta([0.0490833989, 1.28402771], $decomp->getRealEigenvalues(), 0.001);
self::assertEquals([ self::assertEqualsWithDelta([
[-0.735178656, 0.677873399], [-0.735178656, 0.677873399],
[-0.677873399, -0.735178656], [-0.677873399, -0.735178656],
], $decomp->getEigenvectors(), '', 0.001); ], $decomp->getEigenvectors(), 0.001);
} }
public function testMatrixWithAllZeroRow(): void public function testMatrixWithAllZeroRow(): void
@ -39,12 +39,12 @@ class EigenvalueDecompositionTest extends TestCase
$decomp = new EigenvalueDecomposition($matrix); $decomp = new EigenvalueDecomposition($matrix);
self::assertEquals([0.0, 6.0, 10.0], $decomp->getRealEigenvalues(), '', 0.0001); self::assertEqualsWithDelta([0.0, 6.0, 10.0], $decomp->getRealEigenvalues(), 0.0001);
self::assertEquals([ self::assertEqualsWithDelta([
[0, 0, 1], [0, 0, 1],
[0, 1, 0], [0, 1, 0],
[1, 0, 0], [1, 0, 0],
], $decomp->getEigenvectors(), '', 0.0001); ], $decomp->getEigenvectors(), 0.0001);
} }
public function testMatrixThatCauseErrorWithStrictComparision(): void public function testMatrixThatCauseErrorWithStrictComparision(): void
@ -58,12 +58,12 @@ class EigenvalueDecompositionTest extends TestCase
$decomp = new EigenvalueDecomposition($matrix); $decomp = new EigenvalueDecomposition($matrix);
self::assertEquals([-5.2620873481, 1.0, 10.2620873481], $decomp->getRealEigenvalues(), '', 0.000001); self::assertEqualsWithDelta([-5.2620873481, 1.0, 10.2620873481], $decomp->getRealEigenvalues(), 0.000001);
self::assertEquals([ self::assertEqualsWithDelta([
[-0.3042688, -0.709960552, 0.63511928], [-0.3042688, -0.709960552, 0.63511928],
[-0.9191450, 0.393919298, 0.0], [-0.9191450, 0.393919298, 0.0],
[0.25018574, 0.5837667, 0.7724140], [0.25018574, 0.5837667, 0.7724140],
], $decomp->getEigenvectors(), '', 0.0001); ], $decomp->getEigenvectors(), 0.0001);
} }
public function testRandomSymmetricMatrixEigenPairs(): void public function testRandomSymmetricMatrixEigenPairs(): void
@ -98,7 +98,7 @@ class EigenvalueDecompositionTest extends TestCase
$leftSide = $m1->multiply($m2)->toArray(); $leftSide = $m1->multiply($m2)->toArray();
$rightSide = $m2->multiplyByScalar($lambda)->toArray(); $rightSide = $m2->multiplyByScalar($lambda)->toArray();
self::assertEquals($leftSide, $rightSide, '', $epsilon); self::assertEqualsWithDelta($leftSide, $rightSide, $epsilon);
} }
} }
} }

6
tests/Math/MatrixTest.php
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@ -60,7 +60,7 @@ class MatrixTest extends TestCase
[1 / 4, 4, 1, 0, 2, 3 / 7], [1 / 4, 4, 1, 0, 2, 3 / 7],
[1, 8, 7, 5, 4, 4 / 5], [1, 8, 7, 5, 4, 4 / 5],
]); ]);
self::assertEquals(1116.5035, $matrix->getDeterminant(), '', $delta = 0.0001); self::assertEqualsWithDelta(1116.5035, $matrix->getDeterminant(), $delta = 0.0001);
} }
public function testMatrixTranspose(): void public function testMatrixTranspose(): void
@ -157,7 +157,7 @@ class MatrixTest extends TestCase
[-1 / 2, 1 / 2, -1 / 2], [-1 / 2, 1 / 2, -1 / 2],
]; ];
self::assertEquals($inverseMatrix, $matrix->inverse()->toArray(), '', $delta = 0.0001); self::assertEqualsWithDelta($inverseMatrix, $matrix->inverse()->toArray(), $delta = 0.0001);
} }
public function testCrossOutMatrix(): void public function testCrossOutMatrix(): void
@ -256,7 +256,7 @@ class MatrixTest extends TestCase
*/ */
public function testFrobeniusNorm(array $matrix, float $norm): void public function testFrobeniusNorm(array $matrix, float $norm): void
{ {
self::assertEquals($norm, (new Matrix($matrix))->frobeniusNorm(), '', 0.0001); self::assertEqualsWithDelta($norm, (new Matrix($matrix))->frobeniusNorm(), 0.0001);
} }
public function dataProviderForFrobeniusNorm(): array public function dataProviderForFrobeniusNorm(): array

4
tests/Math/Statistic/ANOVATest.php
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@ -19,7 +19,7 @@ final class ANOVATest extends TestCase
$f = [1.47058824, 4.0, 3.0]; $f = [1.47058824, 4.0, 3.0];
self::assertEquals($f, ANOVA::oneWayF($samples), '', 0.00000001); self::assertEqualsWithDelta($f, ANOVA::oneWayF($samples), 0.00000001);
} }
public function testOneWayFWithDifferingSizes(): void public function testOneWayFWithDifferingSizes(): void
@ -29,7 +29,7 @@ final class ANOVATest extends TestCase
[[1, 3, 3], [1, 3, 4]], [[1, 3, 3], [1, 3, 4]],
]; ];
self::assertEquals([0.6, 2.4, 1.24615385], ANOVA::oneWayF($samples), '', 0.00000001); self::assertEqualsWithDelta([0.6, 2.4, 1.24615385], ANOVA::oneWayF($samples), 0.00000001);
} }
public function testThrowExceptionOnTooSmallSamples(): void public function testThrowExceptionOnTooSmallSamples(): void

6
tests/Math/Statistic/CorrelationTest.php
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@ -16,18 +16,18 @@ class CorrelationTest extends TestCase
$delta = 0.001; $delta = 0.001;
$x = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260]; $x = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260];
$y = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025]; $y = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
self::assertEquals(-0.641, Correlation::pearson($x, $y), '', $delta); self::assertEqualsWithDelta(-0.641, Correlation::pearson($x, $y), $delta);
//http://www.statisticshowto.com/how-to-compute-pearsons-correlation-coefficients/ //http://www.statisticshowto.com/how-to-compute-pearsons-correlation-coefficients/
$delta = 0.001; $delta = 0.001;
$x = [43, 21, 25, 42, 57, 59]; $x = [43, 21, 25, 42, 57, 59];
$y = [99, 65, 79, 75, 87, 82]; $y = [99, 65, 79, 75, 87, 82];
self::assertEquals(0.549, Correlation::pearson($x, $y), '', $delta); self::assertEqualsWithDelta(0.549, Correlation::pearson($x, $y), $delta);
$delta = 0.001; $delta = 0.001;
$x = [60, 61, 62, 63, 65]; $x = [60, 61, 62, 63, 65];
$y = [3.1, 3.6, 3.8, 4, 4.1]; $y = [3.1, 3.6, 3.8, 4, 4.1];
self::assertEquals(0.911, Correlation::pearson($x, $y), '', $delta); self::assertEqualsWithDelta(0.911, Correlation::pearson($x, $y), $delta);
} }
public function testThrowExceptionOnInvalidArgumentsForPearsonCorrelation(): void public function testThrowExceptionOnInvalidArgumentsForPearsonCorrelation(): void

12
tests/Math/Statistic/CovarianceTest.php
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@ -38,18 +38,18 @@ class CovarianceTest extends TestCase
// Calculate only one covariance value: Cov(x, y) // Calculate only one covariance value: Cov(x, y)
$cov1 = Covariance::fromDataset($matrix, 0, 0); $cov1 = Covariance::fromDataset($matrix, 0, 0);
self::assertEquals($cov1, $knownCovariance[0][0], '', $epsilon); self::assertEqualsWithDelta($cov1, $knownCovariance[0][0], $epsilon);
$cov1 = Covariance::fromXYArrays($x, $x); $cov1 = Covariance::fromXYArrays($x, $x);
self::assertEquals($cov1, $knownCovariance[0][0], '', $epsilon); self::assertEqualsWithDelta($cov1, $knownCovariance[0][0], $epsilon);
$cov2 = Covariance::fromDataset($matrix, 0, 1); $cov2 = Covariance::fromDataset($matrix, 0, 1);
self::assertEquals($cov2, $knownCovariance[0][1], '', $epsilon); self::assertEqualsWithDelta($cov2, $knownCovariance[0][1], $epsilon);
$cov2 = Covariance::fromXYArrays($x, $y); $cov2 = Covariance::fromXYArrays($x, $y);
self::assertEquals($cov2, $knownCovariance[0][1], '', $epsilon); self::assertEqualsWithDelta($cov2, $knownCovariance[0][1], $epsilon);
// Second: calculation cov matrix with automatic means for each column // Second: calculation cov matrix with automatic means for each column
$covariance = Covariance::covarianceMatrix($matrix); $covariance = Covariance::covarianceMatrix($matrix);
self::assertEquals($knownCovariance, $covariance, '', $epsilon); self::assertEqualsWithDelta($knownCovariance, $covariance, $epsilon);
// Thirdly, CovMatrix: Means are precalculated and given to the method // Thirdly, CovMatrix: Means are precalculated and given to the method
$x = array_column($matrix, 0); $x = array_column($matrix, 0);
@ -58,7 +58,7 @@ class CovarianceTest extends TestCase
$meanY = Mean::arithmetic($y); $meanY = Mean::arithmetic($y);
$covariance = Covariance::covarianceMatrix($matrix, [$meanX, $meanY]); $covariance = Covariance::covarianceMatrix($matrix, [$meanX, $meanY]);
self::assertEquals($knownCovariance, $covariance, '', $epsilon); self::assertEqualsWithDelta($knownCovariance, $covariance, $epsilon);
} }
public function testThrowExceptionOnEmptyX(): void public function testThrowExceptionOnEmptyX(): void

4
tests/Math/Statistic/GaussianTest.php
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@ -20,9 +20,9 @@ class GaussianTest extends TestCase
$x = [0, 0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0]; $x = [0, 0.1, 0.5, 1.0, 1.5, 2.0, 2.5, 3.0];
$pdf = [0.3989, 0.3969, 0.3520, 0.2419, 0.1295, 0.0539, 0.0175, 0.0044]; $pdf = [0.3989, 0.3969, 0.3520, 0.2419, 0.1295, 0.0539, 0.0175, 0.0044];
foreach ($x as $i => $v) { foreach ($x as $i => $v) {
self::assertEquals($pdf[$i], $g->pdf($v), '', $delta); self::assertEqualsWithDelta($pdf[$i], $g->pdf($v), $delta);
self::assertEquals($pdf[$i], Gaussian::distributionPdf($mean, $std, $v), '', $delta); self::assertEqualsWithDelta($pdf[$i], Gaussian::distributionPdf($mean, $std, $v), $delta);
} }
} }
} }

6
tests/Math/Statistic/MeanTest.php
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@ -19,9 +19,9 @@ class MeanTest extends TestCase
public function testArithmeticMean(): void public function testArithmeticMean(): void
{ {
$delta = 0.01; $delta = 0.01;
self::assertEquals(3.5, Mean::arithmetic([2, 5]), '', $delta); self::assertEqualsWithDelta(3.5, Mean::arithmetic([2, 5]), $delta);
self::assertEquals(41.16, Mean::arithmetic([43, 21, 25, 42, 57, 59]), '', $delta); self::assertEqualsWithDelta(41.16, Mean::arithmetic([43, 21, 25, 42, 57, 59]), $delta);
self::assertEquals(1.7, Mean::arithmetic([0.5, 0.5, 1.5, 2.5, 3.5]), '', $delta); self::assertEqualsWithDelta(1.7, Mean::arithmetic([0.5, 0.5, 1.5, 2.5, 3.5]), $delta);
} }
public function testMedianThrowExceptionOnEmptyArray(): void public function testMedianThrowExceptionOnEmptyArray(): void

8
tests/Math/Statistic/StandardDeviationTest.php
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@ -15,15 +15,15 @@ class StandardDeviationTest extends TestCase
//https://pl.wikipedia.org/wiki/Odchylenie_standardowe //https://pl.wikipedia.org/wiki/Odchylenie_standardowe
$delta = 0.001; $delta = 0.001;
$population = [5, 6, 8, 9]; $population = [5, 6, 8, 9];
self::assertEquals(1.825, StandardDeviation::population($population), '', $delta); self::assertEqualsWithDelta(1.825, StandardDeviation::population($population), $delta);
//http://www.stat.wmich.edu/s216/book/node126.html //http://www.stat.wmich.edu/s216/book/node126.html
$delta = 0.5; $delta = 0.5;
$population = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025]; $population = [7100, 15500, 4400, 4400, 5900, 4600, 8800, 2000, 2750, 2550, 960, 1025];
self::assertEquals(4079, StandardDeviation::population($population), '', $delta); self::assertEqualsWithDelta(4079, StandardDeviation::population($population), $delta);
$population = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260]; $population = [9300, 10565, 15000, 15000, 17764, 57000, 65940, 73676, 77006, 93739, 146088, 153260];
self::assertEquals(50989, StandardDeviation::population($population), '', $delta); self::assertEqualsWithDelta(50989, StandardDeviation::population($population), $delta);
} }
public function testThrowExceptionOnEmptyArrayIfNotSample(): void public function testThrowExceptionOnEmptyArrayIfNotSample(): void
@ -43,7 +43,7 @@ class StandardDeviationTest extends TestCase
*/ */
public function testSumOfSquares(array $numbers, float $sum): void public function testSumOfSquares(array $numbers, float $sum): void
{ {
self::assertEquals($sum, StandardDeviation::sumOfSquares($numbers), '', 0.0001); self::assertEqualsWithDelta($sum, StandardDeviation::sumOfSquares($numbers), 0.0001);
} }
public function dataProviderForSumOfSquaresDeviations(): array public function dataProviderForSumOfSquaresDeviations(): array

2
tests/Math/Statistic/VarianceTest.php
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@ -14,7 +14,7 @@ final class VarianceTest extends TestCase
*/ */
public function testVarianceFromInt(array $numbers, float $variance): void public function testVarianceFromInt(array $numbers, float $variance): void
{ {
self::assertEquals($variance, Variance::population($numbers), '', 0.001); self::assertEqualsWithDelta($variance, Variance::population($numbers), 0.001);
} }
public function dataProviderForPopulationVariance(): array public function dataProviderForPopulationVariance(): array

2
tests/Metric/AccuracyTest.php
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@ -51,6 +51,6 @@ class AccuracyTest extends TestCase
$expected = PHP_VERSION_ID >= 70100 ? 1 : 0.959; $expected = PHP_VERSION_ID >= 70100 ? 1 : 0.959;
self::assertEquals($expected, $accuracy, '', 0.01); self::assertEqualsWithDelta($expected, $accuracy, 0.01);
} }
} }

42
tests/Metric/ClassificationReportTest.php
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@ -45,11 +45,11 @@ class ClassificationReportTest extends TestCase
'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45 'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45
]; ];
self::assertEquals($precision, $report->getPrecision(), '', 0.01); self::assertEqualsWithDelta($precision, $report->getPrecision(), 0.01);
self::assertEquals($recall, $report->getRecall(), '', 0.01); self::assertEqualsWithDelta($recall, $report->getRecall(), 0.01);
self::assertEquals($f1score, $report->getF1score(), '', 0.01); self::assertEqualsWithDelta($f1score, $report->getF1score(), 0.01);
self::assertEquals($support, $report->getSupport(), '', 0.01); self::assertEqualsWithDelta($support, $report->getSupport(), 0.01);
self::assertEquals($average, $report->getAverage(), '', 0.01); self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
} }
public function testClassificationReportGenerateWithNumericLabels(): void public function testClassificationReportGenerateWithNumericLabels(): void
@ -85,11 +85,11 @@ class ClassificationReportTest extends TestCase
'f1score' => 0.49, 'f1score' => 0.49,
]; ];
self::assertEquals($precision, $report->getPrecision(), '', 0.01); self::assertEqualsWithDelta($precision, $report->getPrecision(), 0.01);
self::assertEquals($recall, $report->getRecall(), '', 0.01); self::assertEqualsWithDelta($recall, $report->getRecall(), 0.01);
self::assertEquals($f1score, $report->getF1score(), '', 0.01); self::assertEqualsWithDelta($f1score, $report->getF1score(), 0.01);
self::assertEquals($support, $report->getSupport(), '', 0.01); self::assertEqualsWithDelta($support, $report->getSupport(), 0.01);
self::assertEquals($average, $report->getAverage(), '', 0.01); self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
} }
public function testClassificationReportAverageOutOfRange(): void public function testClassificationReportAverageOutOfRange(): void
@ -114,7 +114,7 @@ class ClassificationReportTest extends TestCase
'f1score' => 0.6, // Harmonic mean of precision and recall 'f1score' => 0.6, // Harmonic mean of precision and recall
]; ];
self::assertEquals($average, $report->getAverage(), '', 0.01); self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
} }
public function testClassificationReportMacroAverage(): void public function testClassificationReportMacroAverage(): void
@ -130,7 +130,7 @@ class ClassificationReportTest extends TestCase
'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45 'f1score' => 0.49, // (2/3 + 0 + 4/5) / 3 = 22/45
]; ];
self::assertEquals($average, $report->getAverage(), '', 0.01); self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
} }
public function testClassificationReportWeightedAverage(): void public function testClassificationReportWeightedAverage(): void
@ -146,7 +146,7 @@ class ClassificationReportTest extends TestCase
'f1score' => 0.61, // (2/3 * 1 + 0 * 1 + 4/5 * 3) / 5 = 46/75 'f1score' => 0.61, // (2/3 * 1 + 0 * 1 + 4/5 * 3) / 5 = 46/75
]; ];
self::assertEquals($average, $report->getAverage(), '', 0.01); self::assertEqualsWithDelta($average, $report->getAverage(), 0.01);
} }
public function testPreventDivideByZeroWhenTruePositiveAndFalsePositiveSumEqualsZero(): void public function testPreventDivideByZeroWhenTruePositiveAndFalsePositiveSumEqualsZero(): void
@ -156,10 +156,10 @@ class ClassificationReportTest extends TestCase
$report = new ClassificationReport($labels, $predicted); $report = new ClassificationReport($labels, $predicted);
self::assertEquals([ self::assertEqualsWithDelta([
1 => 0.0, 1 => 0.0,
2 => 0.5, 2 => 0.5,
], $report->getPrecision(), '', 0.01); ], $report->getPrecision(), 0.01);
} }
public function testPreventDivideByZeroWhenTruePositiveAndFalseNegativeSumEqualsZero(): void public function testPreventDivideByZeroWhenTruePositiveAndFalseNegativeSumEqualsZero(): void
@ -169,11 +169,11 @@ class ClassificationReportTest extends TestCase
$report = new ClassificationReport($labels, $predicted); $report = new ClassificationReport($labels, $predicted);
self::assertEquals([ self::assertEqualsWithDelta([
1 => 0.0, 1 => 0.0,
2 => 1, 2 => 1,
3 => 0, 3 => 0,
], $report->getPrecision(), '', 0.01); ], $report->getPrecision(), 0.01);
} }
public function testPreventDividedByZeroWhenPredictedLabelsAllNotMatch(): void public function testPreventDividedByZeroWhenPredictedLabelsAllNotMatch(): void
@ -183,11 +183,11 @@ class ClassificationReportTest extends TestCase
$report = new ClassificationReport($labels, $predicted); $report = new ClassificationReport($labels, $predicted);
self::assertEquals([ self::assertEqualsWithDelta([
'precision' => 0, 'precision' => 0,
'recall' => 0, 'recall' => 0,
'f1score' => 0, 'f1score' => 0,
], $report->getAverage(), '', 0.01); ], $report->getAverage(), 0.01);
} }
public function testPreventDividedByZeroWhenLabelsAreEmpty(): void public function testPreventDividedByZeroWhenLabelsAreEmpty(): void
@ -197,10 +197,10 @@ class ClassificationReportTest extends TestCase
$report = new ClassificationReport($labels, $predicted); $report = new ClassificationReport($labels, $predicted);
self::assertEquals([ self::assertEqualsWithDelta([
'precision' => 0, 'precision' => 0,
'recall' => 0, 'recall' => 0,
'f1score' => 0, 'f1score' => 0,
], $report->getAverage(), '', 0.01); ], $report->getAverage(), 0.01);
} }
} }

4
tests/NeuralNetwork/ActivationFunction/GaussianTest.php
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@ -18,7 +18,7 @@ class GaussianTest extends TestCase
{ {
$gaussian = new Gaussian(); $gaussian = new Gaussian();
self::assertEquals($expected, $gaussian->compute($value), '', 0.001); self::assertEqualsWithDelta($expected, $gaussian->compute($value), 0.001);
} }
public function gaussianProvider(): array public function gaussianProvider(): array
@ -41,7 +41,7 @@ class GaussianTest extends TestCase
{ {
$gaussian = new Gaussian(); $gaussian = new Gaussian();
$activatedValue = $gaussian->compute($value); $activatedValue = $gaussian->compute($value);
self::assertEquals($expected, $gaussian->differentiate($value, $activatedValue), '', 0.001); self::assertEqualsWithDelta($expected, $gaussian->differentiate($value, $activatedValue), 0.001);
} }
public function gaussianDerivativeProvider(): array public function gaussianDerivativeProvider(): array

4
tests/NeuralNetwork/ActivationFunction/HyperboliTangentTest.php
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@ -18,7 +18,7 @@ class HyperboliTangentTest extends TestCase
{ {
$tanh = new HyperbolicTangent($beta); $tanh = new HyperbolicTangent($beta);
self::assertEquals($expected, $tanh->compute($value), '', 0.001); self::assertEqualsWithDelta($expected, $tanh->compute($value), 0.001);
} }
public function tanhProvider(): array public function tanhProvider(): array
@ -42,7 +42,7 @@ class HyperboliTangentTest extends TestCase
{ {
$tanh = new HyperbolicTangent($beta); $tanh = new HyperbolicTangent($beta);
$activatedValue = $tanh->compute($value); $activatedValue = $tanh->compute($value);
self::assertEquals($expected, $tanh->differentiate($value, $activatedValue), '', 0.001); self::assertEqualsWithDelta($expected, $tanh->differentiate($value, $activatedValue), 0.001);
} }
public function tanhDerivativeProvider(): array public function tanhDerivativeProvider(): array

2
tests/NeuralNetwork/ActivationFunction/PReLUTest.php
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@ -18,7 +18,7 @@ class PReLUTest extends TestCase
{ {
$prelu = new PReLU($beta); $prelu = new PReLU($beta);
self::assertEquals($expected, $prelu->compute($value), '', 0.001); self::assertEqualsWithDelta($expected, $prelu->compute($value), 0.001);
} }
public function preluProvider(): array public function preluProvider(): array

4
tests/NeuralNetwork/ActivationFunction/SigmoidTest.php
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@ -18,7 +18,7 @@ class SigmoidTest extends TestCase
{ {
$sigmoid = new Sigmoid($beta); $sigmoid = new Sigmoid($beta);
self::assertEquals($expected, $sigmoid->compute($value), '', 0.001); self::assertEqualsWithDelta($expected, $sigmoid->compute($value), 0.001);
} }
public function sigmoidProvider(): array public function sigmoidProvider(): array
@ -42,7 +42,7 @@ class SigmoidTest extends TestCase
{ {
$sigmoid = new Sigmoid($beta); $sigmoid = new Sigmoid($beta);
$activatedValue = $sigmoid->compute($value); $activatedValue = $sigmoid->compute($value);
self::assertEquals($expected, $sigmoid->differentiate($value, $activatedValue), '', 0.001); self::assertEqualsWithDelta($expected, $sigmoid->differentiate($value, $activatedValue), 0.001);
} }
public function sigmoidDerivativeProvider(): array public function sigmoidDerivativeProvider(): array

6
tests/NeuralNetwork/Network/LayeredNetworkTest.php
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@ -8,8 +8,8 @@ use Phpml\NeuralNetwork\ActivationFunction;
use Phpml\NeuralNetwork\Layer; use Phpml\NeuralNetwork\Layer;
use Phpml\NeuralNetwork\Network\LayeredNetwork; use Phpml\NeuralNetwork\Network\LayeredNetwork;
use Phpml\NeuralNetwork\Node\Input; use Phpml\NeuralNetwork\Node\Input;
use PHPUnit\Framework\MockObject\MockObject;
use PHPUnit\Framework\TestCase; use PHPUnit\Framework\TestCase;
use PHPUnit_Framework_MockObject_MockObject;
class LayeredNetworkTest extends TestCase class LayeredNetworkTest extends TestCase
{ {
@ -56,7 +56,7 @@ class LayeredNetworkTest extends TestCase
} }
/** /**
* @return LayeredNetwork|PHPUnit_Framework_MockObject_MockObject * @return LayeredNetwork|MockObject
*/ */
private function getLayeredNetworkMock() private function getLayeredNetworkMock()
{ {
@ -64,7 +64,7 @@ class LayeredNetworkTest extends TestCase
} }
/** /**
* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject * @return ActivationFunction|MockObject
*/ */
private function getActivationFunctionMock() private function getActivationFunctionMock()
{ {

4
tests/NeuralNetwork/Network/MultilayerPerceptronTest.php
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@ -9,8 +9,8 @@ use Phpml\NeuralNetwork\ActivationFunction;
use Phpml\NeuralNetwork\Layer; use Phpml\NeuralNetwork\Layer;
use Phpml\NeuralNetwork\Network\MultilayerPerceptron; use Phpml\NeuralNetwork\Network\MultilayerPerceptron;
use Phpml\NeuralNetwork\Node\Neuron; use Phpml\NeuralNetwork\Node\Neuron;
use PHPUnit\Framework\MockObject\MockObject;
use PHPUnit\Framework\TestCase; use PHPUnit\Framework\TestCase;
use PHPUnit_Framework_MockObject_MockObject;
class MultilayerPerceptronTest extends TestCase class MultilayerPerceptronTest extends TestCase
{ {
@ -106,7 +106,7 @@ class MultilayerPerceptronTest extends TestCase
} }
/** /**
* @return ActivationFunction|PHPUnit_Framework_MockObject_MockObject * @return ActivationFunction|MockObject
*/ */
private function getActivationFunctionMock() private function getActivationFunctionMock()
{ {

4
tests/NeuralNetwork/Node/Neuron/SynapseTest.php
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@ -6,8 +6,8 @@ namespace Phpml\Tests\NeuralNetwork\Node\Neuron;
use Phpml\NeuralNetwork\Node\Neuron; use Phpml\NeuralNetwork\Node\Neuron;
use Phpml\NeuralNetwork\Node\Neuron\Synapse; use Phpml\NeuralNetwork\Node\Neuron\Synapse;
use PHPUnit\Framework\MockObject\MockObject;
use PHPUnit\Framework\TestCase; use PHPUnit\Framework\TestCase;
use PHPUnit_Framework_MockObject_MockObject;
class SynapseTest extends TestCase class SynapseTest extends TestCase
{ {
@ -43,7 +43,7 @@ class SynapseTest extends TestCase
/** /**
* @param int|float $output * @param int|float $output
* *
* @return Neuron|PHPUnit_Framework_MockObject_MockObject * @return Neuron|MockObject
*/ */
private function getNodeMock($output = 1) private function getNodeMock($output = 1)
{ {

12
tests/NeuralNetwork/Node/NeuronTest.php
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@ -7,8 +7,8 @@ namespace Phpml\Tests\NeuralNetwork\Node;
use Phpml\NeuralNetwork\ActivationFunction\BinaryStep; use Phpml\NeuralNetwork\ActivationFunction\BinaryStep;
use Phpml\NeuralNetwork\Node\Neuron; use Phpml\NeuralNetwork\Node\Neuron;
use Phpml\NeuralNetwork\Node\Neuron\Synapse; use Phpml\NeuralNetwork\Node\Neuron\Synapse;
use PHPUnit\Framework\MockObject\MockObject;
use PHPUnit\Framework\TestCase; use PHPUnit\Framework\TestCase;
use PHPUnit_Framework_MockObject_MockObject;
class NeuronTest extends TestCase class NeuronTest extends TestCase
{ {
@ -22,7 +22,7 @@ class NeuronTest extends TestCase
public function testNeuronActivationFunction(): void public function testNeuronActivationFunction(): void
{ {
/** @var BinaryStep|PHPUnit_Framework_MockObject_MockObject $activationFunction */ /** @var BinaryStep|MockObject $activationFunction */
$activationFunction = $this->getMockBuilder(BinaryStep::class)->getMock(); $activationFunction = $this->getMockBuilder(BinaryStep::class)->getMock();
$activationFunction->method('compute')->with(0)->willReturn($output = 0.69); $activationFunction->method('compute')->with(0)->willReturn($output = 0.69);
@ -37,7 +37,7 @@ class NeuronTest extends TestCase
$neuron->addSynapse($synapse = $this->getSynapseMock()); $neuron->addSynapse($synapse = $this->getSynapseMock());
self::assertEquals([$synapse], $neuron->getSynapses()); self::assertEquals([$synapse], $neuron->getSynapses());
self::assertEquals(0.88, $neuron->getOutput(), '', 0.01); self::assertEqualsWithDelta(0.88, $neuron->getOutput(), 0.01);
} }
public function testNeuronRefresh(): void public function testNeuronRefresh(): void
@ -46,15 +46,15 @@ class NeuronTest extends TestCase
$neuron->getOutput(); $neuron->getOutput();
$neuron->addSynapse($this->getSynapseMock()); $neuron->addSynapse($this->getSynapseMock());
self::assertEquals(0.5, $neuron->getOutput(), '', 0.01); self::assertEqualsWithDelta(0.5, $neuron->getOutput(), 0.01);
$neuron->reset(); $neuron->reset();
self::assertEquals(0.88, $neuron->getOutput(), '', 0.01); self::assertEqualsWithDelta(0.88, $neuron->getOutput(), 0.01);
} }
/** /**
* @return Synapse|PHPUnit_Framework_MockObject_MockObject * @return Synapse|MockObject
*/ */
private function getSynapseMock(int $output = 2) private function getSynapseMock(int $output = 2)
{ {

2
tests/PipelineTest.php
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@ -115,7 +115,7 @@ class PipelineTest extends TestCase
$pipeline = new Pipeline([$selector = new SelectKBest(2)], new SVC()); $pipeline = new Pipeline([$selector = new SelectKBest(2)], new SVC());
$pipeline->train($samples, $targets); $pipeline->train($samples, $targets);
self::assertEquals([1.47058823, 4.0, 3.0], $selector->scores(), '', 0.00000001); self::assertEqualsWithDelta([1.47058823, 4.0, 3.0], $selector->scores(), 0.00000001);
self::assertEquals(['b'], $pipeline->predict([[1, 3, 5]])); self::assertEquals(['b'], $pipeline->predict([[1, 3, 5]]));
} }

10
tests/Preprocessing/ImputerTest.php
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@ -32,7 +32,7 @@ class ImputerTest extends TestCase
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $data); $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $data);
$imputer->transform($data); $imputer->transform($data);
self::assertEquals($imputeData, $data, '', $delta = 0.01); self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
} }
public function testComplementsMissingValuesWithMeanStrategyOnRowAxis(): void public function testComplementsMissingValuesWithMeanStrategyOnRowAxis(): void
@ -54,7 +54,7 @@ class ImputerTest extends TestCase
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_ROW, $data); $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_ROW, $data);
$imputer->transform($data); $imputer->transform($data);
self::assertEquals($imputeData, $data, '', $delta = 0.01); self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
} }
public function testComplementsMissingValuesWithMediaStrategyOnColumnAxis(): void public function testComplementsMissingValuesWithMediaStrategyOnColumnAxis(): void
@ -76,7 +76,7 @@ class ImputerTest extends TestCase
$imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_COLUMN, $data); $imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_COLUMN, $data);
$imputer->transform($data); $imputer->transform($data);
self::assertEquals($imputeData, $data, '', $delta = 0.01); self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
} }
public function testComplementsMissingValuesWithMediaStrategyOnRowAxis(): void public function testComplementsMissingValuesWithMediaStrategyOnRowAxis(): void
@ -98,7 +98,7 @@ class ImputerTest extends TestCase
$imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_ROW, $data); $imputer = new Imputer(null, new MedianStrategy(), Imputer::AXIS_ROW, $data);
$imputer->transform($data); $imputer->transform($data);
self::assertEquals($imputeData, $data, '', $delta = 0.01); self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
} }
public function testComplementsMissingValuesWithMostFrequentStrategyOnColumnAxis(): void public function testComplementsMissingValuesWithMostFrequentStrategyOnColumnAxis(): void
@ -172,7 +172,7 @@ class ImputerTest extends TestCase
$imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $trainData); $imputer = new Imputer(null, new MeanStrategy(), Imputer::AXIS_COLUMN, $trainData);
$imputer->transform($data); $imputer->transform($data);
self::assertEquals($imputeData, $data, '', $delta = 0.01); self::assertEqualsWithDelta($imputeData, $data, $delta = 0.01);
} }
public function testThrowExceptionWhenTryingToTransformWithoutTrainSamples(): void public function testThrowExceptionWhenTryingToTransformWithoutTrainSamples(): void

10
tests/Preprocessing/NormalizerTest.php
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@ -33,7 +33,7 @@ class NormalizerTest extends TestCase
$normalizer = new Normalizer(); $normalizer = new Normalizer();
$normalizer->transform($samples); $normalizer->transform($samples);
self::assertEquals($normalized, $samples, '', $delta = 0.01); self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
} }
public function testNormalizeSamplesWithL1Norm(): void public function testNormalizeSamplesWithL1Norm(): void
@ -53,7 +53,7 @@ class NormalizerTest extends TestCase
$normalizer = new Normalizer(Normalizer::NORM_L1); $normalizer = new Normalizer(Normalizer::NORM_L1);
$normalizer->transform($samples); $normalizer->transform($samples);
self::assertEquals($normalized, $samples, '', $delta = 0.01); self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
} }
public function testFitNotChangeNormalizerBehavior(): void public function testFitNotChangeNormalizerBehavior(): void
@ -73,11 +73,11 @@ class NormalizerTest extends TestCase
$normalizer = new Normalizer(); $normalizer = new Normalizer();
$normalizer->transform($samples); $normalizer->transform($samples);
self::assertEquals($normalized, $samples, '', $delta = 0.01); self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
$normalizer->fit($samples); $normalizer->fit($samples);
self::assertEquals($normalized, $samples, '', $delta = 0.01); self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
} }
public function testL1NormWithZeroSumCondition(): void public function testL1NormWithZeroSumCondition(): void
@ -97,7 +97,7 @@ class NormalizerTest extends TestCase
$normalizer = new Normalizer(Normalizer::NORM_L1); $normalizer = new Normalizer(Normalizer::NORM_L1);
$normalizer->transform($samples); $normalizer->transform($samples);
self::assertEquals($normalized, $samples, '', $delta = 0.01); self::assertEqualsWithDelta($normalized, $samples, $delta = 0.01);
} }
public function testStandardNorm(): void public function testStandardNorm(): void

22
tests/Regression/LeastSquaresTest.php
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@ -21,7 +21,7 @@ class LeastSquaresTest extends TestCase
$regression = new LeastSquares(); $regression = new LeastSquares();
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals(4.06, $regression->predict([64]), '', $delta); self::assertEqualsWithDelta(4.06, $regression->predict([64]), $delta);
//http://www.stat.wmich.edu/s216/book/node127.html //http://www.stat.wmich.edu/s216/book/node127.html
$samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]]; $samples = [[9300], [10565], [15000], [15000], [17764], [57000], [65940], [73676], [77006], [93739], [146088], [153260]];
@ -30,11 +30,11 @@ class LeastSquaresTest extends TestCase
$regression = new LeastSquares(); $regression = new LeastSquares();
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals(7659.35, $regression->predict([9300]), '', $delta); self::assertEqualsWithDelta(7659.35, $regression->predict([9300]), $delta);
self::assertEquals(5213.81, $regression->predict([57000]), '', $delta); self::assertEqualsWithDelta(5213.81, $regression->predict([57000]), $delta);
self::assertEquals(4188.13, $regression->predict([77006]), '', $delta); self::assertEqualsWithDelta(4188.13, $regression->predict([77006]), $delta);
self::assertEquals(7659.35, $regression->predict([9300]), '', $delta); self::assertEqualsWithDelta(7659.35, $regression->predict([9300]), $delta);
self::assertEquals(278.66, $regression->predict([153260]), '', $delta); self::assertEqualsWithDelta(278.66, $regression->predict([153260]), $delta);
} }
public function testPredictSingleFeatureSamplesWithMatrixTargets(): void public function testPredictSingleFeatureSamplesWithMatrixTargets(): void
@ -48,7 +48,7 @@ class LeastSquaresTest extends TestCase
$regression = new LeastSquares(); $regression = new LeastSquares();
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals(4.06, $regression->predict([64]), '', $delta); self::assertEqualsWithDelta(4.06, $regression->predict([64]), $delta);
} }
public function testPredictMultiFeaturesSamples(): void public function testPredictMultiFeaturesSamples(): void
@ -62,10 +62,10 @@ class LeastSquaresTest extends TestCase
$regression = new LeastSquares(); $regression = new LeastSquares();
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals(-800614.957, $regression->getIntercept(), '', $delta); self::assertEqualsWithDelta(-800614.957, $regression->getIntercept(), $delta);
self::assertEquals([-0.0327, 404.14], $regression->getCoefficients(), '', $delta); self::assertEqualsWithDelta([-0.0327, 404.14], $regression->getCoefficients(), $delta);
self::assertEquals(4094.82, $regression->predict([60000, 1996]), '', $delta); self::assertEqualsWithDelta(4094.82, $regression->predict([60000, 1996]), $delta);
self::assertEquals(5711.40, $regression->predict([60000, 2000]), '', $delta); self::assertEqualsWithDelta(5711.40, $regression->predict([60000, 2000]), $delta);
} }
public function testSaveAndRestore(): void public function testSaveAndRestore(): void

4
tests/Regression/SVRTest.php
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@ -21,7 +21,7 @@ class SVRTest extends TestCase
$regression = new SVR(Kernel::LINEAR); $regression = new SVR(Kernel::LINEAR);
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals(4.03, $regression->predict([64]), '', $delta); self::assertEqualsWithDelta(4.03, $regression->predict([64]), $delta);
} }
public function testPredictMultiFeaturesSamples(): void public function testPredictMultiFeaturesSamples(): void
@ -34,7 +34,7 @@ class SVRTest extends TestCase
$regression = new SVR(Kernel::LINEAR); $regression = new SVR(Kernel::LINEAR);
$regression->train($samples, $targets); $regression->train($samples, $targets);
self::assertEquals([4109.82, 4112.28], $regression->predict([[60000, 1996], [60000, 2000]]), '', $delta); self::assertEqualsWithDelta([4109.82, 4112.28], $regression->predict([[60000, 1996], [60000, 2000]]), $delta);
} }
public function testSaveAndRestore(): void public function testSaveAndRestore(): void

4
tests/SupportVectorMachine/SupportVectorMachineTest.php
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@ -59,8 +59,8 @@ SV
); );
$svm->train($samples, $labels); $svm->train($samples, $labels);
self::assertContains(PHP_EOL.'probA ', $svm->getModel()); self::assertStringContainsString(PHP_EOL.'probA ', $svm->getModel());
self::assertContains(PHP_EOL.'probB ', $svm->getModel()); self::assertStringContainsString(PHP_EOL.'probB ', $svm->getModel());
} }
public function testPredictSampleWithLinearKernel(): void public function testPredictSampleWithLinearKernel(): void