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Update phpstan & easy coding standard (#366)

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This commit is contained in:
Marcin Michalski 2019-03-25 14:55:14 +01:00 committed by Arkadiusz Kondas
parent 5e02b893e9
commit d3888efa7a
16 changed files with 652 additions and 495 deletions
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6
composer.json
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@ -24,9 +24,9 @@
},
"require-dev": {
"phpbench/phpbench": "^0.14.0",
"phpstan/phpstan-phpunit": "^0.10",
"phpstan/phpstan-shim": "^0.10",
"phpstan/phpstan-strict-rules": "^0.10",
"phpstan/phpstan-phpunit": "^0.11",
"phpstan/phpstan-shim": "^0.11",
"phpstan/phpstan-strict-rules": "^0.11",
"phpunit/phpunit": "^7.0.0",
"symplify/coding-standard": "^5.1",
"symplify/easy-coding-standard": "^5.1"

1048
composer.lock generated
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File diff suppressed because it is too large Load Diff

16
ecs.yml
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@ -30,14 +30,14 @@ services:
Symplify\CodingStandard\Fixer\ArrayNotation\StandaloneLineInMultilineArrayFixer: ~
parameters:
exclude_checkers:
# from strict.neon
- 'PhpCsFixer\Fixer\PhpUnit\PhpUnitStrictFixer'
- 'PhpCsFixer\Fixer\Strict\StrictComparisonFixer'
# personal prefference
- 'PhpCsFixer\Fixer\Operator\NotOperatorWithSuccessorSpaceFixer'
skip:
# from strict.neon
PhpCsFixer\Fixer\PhpUnit\PhpUnitStrictFixer: ~
PhpCsFixer\Fixer\Strict\StrictComparisonFixer: ~
# personal prefference
PhpCsFixer\Fixer\Operator\NotOperatorWithSuccessorSpaceFixer: ~
PhpCsFixer\Fixer\Alias\RandomApiMigrationFixer:
# random_int() breaks code
- 'src/CrossValidation/RandomSplit.php'
@ -65,4 +65,4 @@ parameters:
SlevomatCodingStandard\Sniffs\TypeHints\TypeHintDeclarationSniff.MissingTraversablePropertyTypeHintSpecification: ~
# assignment in "while ($var = ...)" are ok
PHP_CodeSniffer\Standards\Generic\Sniffs\CodeAnalysis\AssignmentInConditionSniff.FoundInWhileCondition:
PHP_CodeSniffer\Standards\Generic\Sniffs\CodeAnalysis\AssignmentInConditionSniff.FoundInWhileCondition:

5
phpstan.neon
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@ -7,9 +7,8 @@ parameters:
ignoreErrors:
- '#Property Phpml\\Clustering\\KMeans\\Cluster\:\:\$points \(iterable\<Phpml\\Clustering\\KMeans\\Point\>\&SplObjectStorage\) does not accept SplObjectStorage#'
- '#Phpml\\Dataset\\(.*)Dataset::__construct\(\) does not call parent constructor from Phpml\\Dataset\\ArrayDataset#'
# wide range cases
- '#Parameter \#1 \$coordinates of class Phpml\\Clustering\\KMeans\\Point constructor expects array, array<int>\|Phpml\\Clustering\\KMeans\\Point given#'
- '#Variable property access on .+#'
- '#Variable method call on .+#'
# probably known value
- '#Method Phpml\\Classification\\DecisionTree::getBestSplit\(\) should return Phpml\\Classification\\DecisionTree\\DecisionTreeLeaf but returns Phpml\\Classification\\DecisionTree\\DecisionTreeLeaf\|null#'

14
src/Classification/Ensemble/RandomForest.php
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@ -41,7 +41,7 @@ class RandomForest extends Bagging
* Default value for the ratio is 'log' which results in log(numFeatures, 2) + 1
* features to be taken into consideration while selecting subspace of features
*
* @param string|float $ratio
* @param mixed $ratio
*/
public function setFeatureSubsetRatio($ratio): self
{
@ -73,7 +73,9 @@ class RandomForest extends Bagging
throw new InvalidArgumentException('RandomForest can only use DecisionTree as base classifier');
}
return parent::setClassifer($classifier, $classifierOptions);
parent::setClassifer($classifier, $classifierOptions);
return $this;
}
/**
@ -122,12 +124,16 @@ class RandomForest extends Bagging
}
/**
* @param DecisionTree $classifier
*
* @return DecisionTree
*/
protected function initSingleClassifier(Classifier $classifier): Classifier
{
if (!$classifier instanceof DecisionTree) {
throw new InvalidArgumentException(
sprintf('Classifier %s expected, got %s', DecisionTree::class, get_class($classifier))
);
}
if (is_float($this->featureSubsetRatio)) {
$featureCount = (int) ($this->featureSubsetRatio * $this->featureCount);
} elseif ($this->featureSubsetRatio === 'sqrt') {

2
src/Classification/Linear/LogisticRegression.php
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@ -226,7 +226,7 @@ class LogisticRegression extends Adaline
$y = $y < 0 ? 0 : 1;
$error = ($y - $hX) ** 2;
$error = (($y - $hX) ** 2);
$gradient = -($y - $hX) * $hX * (1 - $hX);
return [$error, $gradient, $penalty];

5
src/Clustering/FuzzyCMeans.php
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@ -77,9 +77,6 @@ class FuzzyCMeans implements Clusterer
return $this->membership;
}
/**
* @param Point[]|int[][] $samples
*/
public function cluster(array $samples): array
{
// Initialize variables, clusters and membership matrix
@ -210,7 +207,7 @@ class FuzzyCMeans implements Clusterer
$this->samples[$col]
);
$val = ($dist1 / $dist2) ** 2.0 / ($this->fuzziness - 1);
$val = (($dist1 / $dist2) ** 2.0) / ($this->fuzziness - 1);
$sum += $val;
}

2
src/Dataset/SvmDataset.php
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@ -24,7 +24,7 @@ class SvmDataset extends ArrayDataset
$targets = [];
$maxIndex = 0;
while (false !== $line = fgets($handle)) {
[$sample, $target, $maxIndex] = self::processLine((string) $line, $maxIndex);
[$sample, $target, $maxIndex] = self::processLine($line, $maxIndex);
$samples[] = $sample;
$targets[] = $target;
}

2
src/FeatureSelection/ScoringFunction/UnivariateLinearRegression.php
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@ -46,7 +46,7 @@ final class UnivariateLinearRegression implements ScoringFunction
foreach (array_keys($samples[0]) as $index) {
$featureColumn = array_column($samples, $index);
$correlations[$index] =
(Matrix::dot($targets, $featureColumn)[0] / (new Matrix($featureColumn, false))->transpose()->frobeniusNorm())
Matrix::dot($targets, $featureColumn)[0] / (new Matrix($featureColumn, false))->transpose()->frobeniusNorm()
/ (new Matrix($targets, false))->frobeniusNorm();
}

9
src/Math/Kernel/RBF.php
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@ -4,6 +4,7 @@ declare(strict_types=1);
namespace Phpml\Math\Kernel;
use Phpml\Exception\InvalidArgumentException;
use Phpml\Math\Kernel;
use Phpml\Math\Product;
@ -19,12 +20,12 @@ class RBF implements Kernel
$this->gamma = $gamma;
}
/**
* @param array $a
* @param array $b
*/
public function compute($a, $b): float
{
if (!is_array($a) || !is_array($b)) {
throw new InvalidArgumentException(sprintf('Arguments of %s must be arrays', __METHOD__));
}
$score = 2 * Product::scalar($a, $b);
$squares = Product::scalar($a, $a) + Product::scalar($b, $b);

5
src/Math/LinearAlgebra/EigenvalueDecomposition.php
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@ -502,7 +502,8 @@ class EigenvalueDecomposition
}
// Double division avoids possible underflow
$g = ($g / $this->ort[$m]) / $this->H[$m][$m - 1];
$g /= $this->ort[$m];
$g /= $this->H[$m][$m - 1];
for ($i = $m; $i <= $high; ++$i) {
$this->V[$i][$j] += $g * $this->ort[$i];
}
@ -734,7 +735,7 @@ class EigenvalueDecomposition
// Double QR step involving rows l:n and columns m:n
for ($k = $m; $k <= $n - 1; ++$k) {
$notlast = ($k != $n - 1);
$notlast = $k != $n - 1;
if ($k != $m) {
$p = $this->H[$k][$k - 1];
$q = $this->H[$k + 1][$k - 1];

10
src/NeuralNetwork/Network/MultilayerPerceptron.php
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@ -59,8 +59,14 @@ abstract class MultilayerPerceptron extends LayeredNetwork implements Estimator,
/**
* @throws InvalidArgumentException
*/
public function __construct(int $inputLayerFeatures, array $hiddenLayers, array $classes, int $iterations = 10000, ?ActivationFunction $activationFunction = null, float $learningRate = 1)
{
public function __construct(
int $inputLayerFeatures,
array $hiddenLayers,
array $classes,
int $iterations = 10000,
?ActivationFunction $activationFunction = null,
float $learningRate = 1.
) {
if (count($hiddenLayers) === 0) {
throw new InvalidArgumentException('Provide at least 1 hidden layer');
}

6
tests/Helper/Optimizer/ConjugateGradientTest.php
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@ -23,7 +23,7 @@ class ConjugateGradientTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];
@ -49,7 +49,7 @@ class ConjugateGradientTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];
@ -78,7 +78,7 @@ class ConjugateGradientTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0] + $theta[2] * $sample[1];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];

4
tests/Helper/Optimizer/GDTest.php
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@ -22,7 +22,7 @@ class GDTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];
@ -49,7 +49,7 @@ class GDTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0] + $theta[2] * $sample[1];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];

4
tests/Helper/Optimizer/StochasticGDTest.php
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@ -22,7 +22,7 @@ class StochasticGDTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];
@ -49,7 +49,7 @@ class StochasticGDTest extends TestCase
$callback = function ($theta, $sample, $target) {
$y = $theta[0] + $theta[1] * $sample[0] + $theta[2] * $sample[1];
$cost = ($y - $target) ** 2 / 2;
$cost = (($y - $target) ** 2) / 2;
$grad = $y - $target;
return [$cost, $grad];

9
tests/Math/Kernel/RBFTest.php
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@ -4,6 +4,7 @@ declare(strict_types=1);
namespace Phpml\Tests\Math\Kernel;
use Phpml\Exception\InvalidArgumentException;
use Phpml\Math\Kernel\RBF;
use PHPUnit\Framework\TestCase;
@ -23,4 +24,12 @@ class RBFTest extends TestCase
self::assertEquals(0.00451, $rbf->compute([1, 2, 3], [4, 5, 6]), '', $delta = 0.0001);
self::assertEquals(0, $rbf->compute([4, 5], [1, 100]));
}
public function testThrowExceptionWhenComputeArgumentIsNotAnArray(): void
{
$this->expectException(InvalidArgumentException::class);
$this->expectExceptionMessage('Arguments of Phpml\\Math\\Kernel\\RBF::compute must be arrays');
(new RBF(0.1))->compute([0], 1.0);
}
}