@@ -1,6 +1,6 @@ |
||
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 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\NeuralNetwork\ActivationFunction; |
6 | 6 |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\Math; |
6 | 6 |
@@ -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 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | /** |
6 | 6 | * @package JAMA |
@@ -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 | /** |
6 | 6 | * Class to obtain eigenvalues and eigenvectors of a real matrix. |
@@ -128,7 +128,7 @@ discard block |
||
128 | 128 | |
129 | 129 | // Always return the eigenvectors of length 1.0 |
130 | 130 | $vectors = new Matrix($vectors); |
131 | - $vectors = array_map(function ($vect) { |
|
131 | + $vectors = array_map(function($vect) { |
|
132 | 132 | $sum = 0; |
133 | 133 | for ($i = 0; $i < count($vect); ++$i) { |
134 | 134 | $sum += $vect[$i] ** 2; |
@@ -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\Distance; |
6 | 6 | |
@@ -18,7 +18,7 @@ discard block |
||
18 | 18 | throw InvalidArgumentException::arraySizeNotMatch(); |
19 | 19 | } |
20 | 20 | |
21 | - return array_sum(array_map(function ($m, $n) { |
|
21 | + return array_sum(array_map(function($m, $n) { |
|
22 | 22 | return abs($m - $n); |
23 | 23 | }, $a, $b)); |
24 | 24 | } |
@@ -1,6 +1,6 @@ |
||
1 | 1 | <?php |
2 | 2 | |
3 | -declare(strict_types=1); |
|
3 | +declare(strict_types = 1); |
|
4 | 4 | |
5 | 5 | namespace Phpml\FeatureExtraction; |
6 | 6 |