@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\DimensionReduction; |
6 | 6 | |
@@ -161,20 +161,20 @@ discard block |
||
161 | 161 | switch ($this->kernel) { |
162 | 162 | case self::KERNEL_LINEAR: |
163 | 163 | // k(x,y) = xT.y |
164 | - return function ($x, $y) { |
|
164 | + return function($x, $y) { |
|
165 | 165 | return Matrix::dot($x, $y)[0]; |
166 | 166 | }; |
167 | 167 | case self::KERNEL_RBF: |
168 | 168 | // k(x,y)=exp(-γ.|x-y|) where |..| is Euclidean distance |
169 | 169 | $dist = new Euclidean(); |
170 | 170 | |
171 | - return function ($x, $y) use ($dist) { |
|
171 | + return function($x, $y) use ($dist) { |
|
172 | 172 | return exp(-$this->gamma * $dist->sqDistance($x, $y)); |
173 | 173 | }; |
174 | 174 | |
175 | 175 | case self::KERNEL_SIGMOID: |
176 | 176 | // k(x,y)=tanh(γ.xT.y+c0) where c0=1 |
177 | - return function ($x, $y) { |
|
177 | + return function($x, $y) { |
|
178 | 178 | $res = Matrix::dot($x, $y)[0] + 1.0; |
179 | 179 | |
180 | 180 | return tanh($this->gamma * $res); |
@@ -184,7 +184,7 @@ discard block |
||
184 | 184 | // k(x,y)=exp(-γ.|x-y|) where |..| is Manhattan distance |
185 | 185 | $dist = new Manhattan(); |
186 | 186 | |
187 | - return function ($x, $y) use ($dist) { |
|
187 | + return function($x, $y) use ($dist) { |
|
188 | 188 | return exp(-$this->gamma * $dist->distance($x, $y)); |
189 | 189 | }; |
190 | 190 | |
@@ -218,7 +218,7 @@ discard block |
||
218 | 218 | protected function projectSample(array $pairs): array |
219 | 219 | { |
220 | 220 | // Normalize eigenvectors by eig = eigVectors / eigValues |
221 | - $func = function ($eigVal, $eigVect) { |
|
221 | + $func = function($eigVal, $eigVect) { |
|
222 | 222 | $m = new Matrix($eigVect, false); |
223 | 223 | $a = $m->divideByScalar($eigVal)->toArray(); |
224 | 224 |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\CrossValidation; |
6 | 6 | |
@@ -62,7 +62,7 @@ discard block |
||
62 | 62 | |
63 | 63 | abstract protected function splitDataset(Dataset $dataset, float $testSize); |
64 | 64 | |
65 | - protected function seedGenerator(?int $seed = null): void |
|
65 | + protected function seedGenerator(?int $seed = null) : void |
|
66 | 66 | { |
67 | 67 | if ($seed === null) { |
68 | 68 | mt_srand(); |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\FeatureExtraction; |
6 | 6 | |
@@ -13,7 +13,7 @@ discard block |
||
13 | 13 | */ |
14 | 14 | private $idf = []; |
15 | 15 | |
16 | - public function __construct(?array $samples = null) |
|
16 | + public function __construct(? array $samples = null) |
|
17 | 17 | { |
18 | 18 | if ($samples) { |
19 | 19 | $this->fit($samples); |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\NeuralNetwork; |
6 | 6 | |
@@ -44,7 +44,7 @@ discard block |
||
44 | 44 | /** |
45 | 45 | * @return Neuron |
46 | 46 | */ |
47 | - private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null): Node |
|
47 | + private function createNode(string $nodeClass, ?ActivationFunction $activationFunction = null) : Node |
|
48 | 48 | { |
49 | 49 | if ($nodeClass == Neuron::class) { |
50 | 50 | return new Neuron($activationFunction); |
@@ -1,12 +1,12 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Metric; |
6 | 6 | |
7 | 7 | class ConfusionMatrix |
8 | 8 | { |
9 | - public static function compute(array $actualLabels, array $predictedLabels, ?array $labels = null): array |
|
9 | + public static function compute(array $actualLabels, array $predictedLabels, ? array $labels = null) : array |
|
10 | 10 | { |
11 | 11 | $labels = $labels ? array_flip($labels) : self::getUniqueLabels($actualLabels); |
12 | 12 | $matrix = self::generateMatrixWithZeros($labels); |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Association; |
6 | 6 | |
@@ -104,11 +104,11 @@ discard block |
||
104 | 104 | */ |
105 | 105 | protected function predictSample(array $sample): array |
106 | 106 | { |
107 | - $predicts = array_values(array_filter($this->getRules(), function ($rule) use ($sample) { |
|
107 | + $predicts = array_values(array_filter($this->getRules(), function($rule) use ($sample) { |
|
108 | 108 | return $this->equals($rule[self::ARRAY_KEY_ANTECEDENT], $sample); |
109 | 109 | })); |
110 | 110 | |
111 | - return array_map(function ($rule) { |
|
111 | + return array_map(function($rule) { |
|
112 | 112 | return $rule[self::ARRAY_KEY_CONSEQUENT]; |
113 | 113 | }, $predicts); |
114 | 114 | } |
@@ -177,7 +177,7 @@ discard block |
||
177 | 177 | $cardinality = count($sample); |
178 | 178 | $antecedents = $this->powerSet($sample); |
179 | 179 | |
180 | - return array_filter($antecedents, function ($antecedent) use ($cardinality) { |
|
180 | + return array_filter($antecedents, function($antecedent) use ($cardinality) { |
|
181 | 181 | return (count($antecedent) != $cardinality) && ($antecedent != []); |
182 | 182 | }); |
183 | 183 | } |
@@ -199,7 +199,7 @@ discard block |
||
199 | 199 | } |
200 | 200 | } |
201 | 201 | |
202 | - return array_map(function ($entry) { |
|
202 | + return array_map(function($entry) { |
|
203 | 203 | return [$entry]; |
204 | 204 | }, $items); |
205 | 205 | } |
@@ -213,7 +213,7 @@ discard block |
||
213 | 213 | */ |
214 | 214 | private function frequent(array $samples): array |
215 | 215 | { |
216 | - return array_filter($samples, function ($entry) { |
|
216 | + return array_filter($samples, function($entry) { |
|
217 | 217 | return $this->support($entry) >= $this->support; |
218 | 218 | }); |
219 | 219 | } |
@@ -287,7 +287,7 @@ discard block |
||
287 | 287 | */ |
288 | 288 | private function frequency(array $sample): int |
289 | 289 | { |
290 | - return count(array_filter($this->samples, function ($entry) use ($sample) { |
|
290 | + return count(array_filter($this->samples, function($entry) use ($sample) { |
|
291 | 291 | return $this->subset($entry, $sample); |
292 | 292 | })); |
293 | 293 | } |
@@ -302,7 +302,7 @@ discard block |
||
302 | 302 | */ |
303 | 303 | private function contains(array $system, array $set): bool |
304 | 304 | { |
305 | - return (bool) array_filter($system, function ($entry) use ($set) { |
|
305 | + return (bool) array_filter($system, function($entry) use ($set) { |
|
306 | 306 | return $this->equals($entry, $set); |
307 | 307 | }); |
308 | 308 | } |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Math; |
6 | 6 | |
@@ -126,7 +126,7 @@ discard block |
||
126 | 126 | public function transpose(): self |
127 | 127 | { |
128 | 128 | if ($this->rows == 1) { |
129 | - $matrix = array_map(function ($el) { |
|
129 | + $matrix = array_map(function($el) { |
|
130 | 130 | return [$el]; |
131 | 131 | }, $this->matrix[0]); |
132 | 132 | } else { |
@@ -1,6 +1,6 @@ discard block |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Math\Statistic; |
6 | 6 | |
@@ -14,7 +14,7 @@ discard block |
||
14 | 14 | * |
15 | 15 | * @throws InvalidArgumentException |
16 | 16 | */ |
17 | - public static function fromXYArrays(array $x, array $y, bool $sample = true, ?float $meanX = null, ?float $meanY = null): float |
|
17 | + public static function fromXYArrays(array $x, array $y, bool $sample = true, ?float $meanX = null, ?float $meanY = null) : float |
|
18 | 18 | { |
19 | 19 | if (empty($x) || empty($y)) { |
20 | 20 | throw InvalidArgumentException::arrayCantBeEmpty(); |
@@ -52,7 +52,7 @@ discard block |
||
52 | 52 | * @throws InvalidArgumentException |
53 | 53 | * @throws \Exception |
54 | 54 | */ |
55 | - public static function fromDataset(array $data, int $i, int $k, bool $sample = true, ?float $meanX = null, ?float $meanY = null): float |
|
55 | + public static function fromDataset(array $data, int $i, int $k, bool $sample = true, ?float $meanX = null, ?float $meanY = null) : float |
|
56 | 56 | { |
57 | 57 | if (empty($data)) { |
58 | 58 | throw InvalidArgumentException::arrayCantBeEmpty(); |
@@ -115,7 +115,7 @@ discard block |
||
115 | 115 | * |
116 | 116 | * @param array|null $means |
117 | 117 | */ |
118 | - public static function covarianceMatrix(array $data, ?array $means = null): array |
|
118 | + public static function covarianceMatrix(array $data, ? array $means = null) : array |
|
119 | 119 | { |
120 | 120 | $n = count($data[0]); |
121 | 121 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | /** |
6 | 6 | * @package JAMA |