ghostjat /
Np
| Total Complexity | 134 |
| Total Lines | 694 |
| Duplicated Lines | 0 % |
| Changes | 2 | ||
| Bugs | 0 | Features | 0 |
Complex classes like vector often do a lot of different things. To break such a class down, we need to identify a cohesive component within that class. A common approach to find such a component is to look for fields/methods that share the same prefixes, or suffixes.
Once you have determined the fields that belong together, you can apply the Extract Class refactoring. If the component makes sense as a sub-class, Extract Subclass is also a candidate, and is often faster.
While breaking up the class, it is a good idea to analyze how other classes use vector, and based on these observations, apply Extract Interface, too.
| 1 | <?php |
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| 29 | class vector extends nd { |
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| 30 | |||
| 31 | /** |
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| 32 | * Factory method to build a new vector. |
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| 33 | * |
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| 34 | * @param int $col |
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| 35 | * @param int $dtype |
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| 36 | * @return vector |
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| 37 | */ |
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| 38 | public static function factory(int $col, int $dtype = self::FLOAT): vector { |
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| 39 | return new self($col, $dtype); |
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| 40 | } |
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| 41 | |||
| 42 | /** |
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| 43 | * Build a new vector from a php array. |
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| 44 | * |
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| 45 | * @param array $data |
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| 46 | * @param int $dtype |
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| 47 | * @return vector |
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| 48 | */ |
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| 49 | public static function ar(array $data, int $dtype = self::FLOAT): vector { |
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| 50 | if (is_array($data) && !is_array($data[0])) { |
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| 51 | $ar = self::factory(count($data), $dtype); |
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| 52 | $ar->setData($data); |
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| 53 | return $ar; |
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| 54 | } else { |
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| 55 | self::_err('data must be of same dimensions'); |
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| 56 | } |
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| 57 | } |
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| 58 | |||
| 59 | /** |
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| 60 | * Return vector with random values |
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| 61 | * @param int $col |
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| 62 | * @param int $dtype |
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| 63 | * @return vector |
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| 64 | */ |
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| 65 | public static function randn(int $col, int $dtype = self::FLOAT): vector { |
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| 66 | $ar = self::factory($col, $dtype); |
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| 67 | $max = getrandmax(); |
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| 68 | for ($i = 0; $i < $ar->col; ++$i) { |
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| 69 | $ar->data[$i] = rand() / $max; |
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| 70 | } |
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| 71 | return $ar; |
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| 72 | } |
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| 73 | |||
| 74 | /** |
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| 75 | * Return vector with uniform values |
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| 76 | * @param int $col |
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| 77 | * @param int $dtype |
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| 78 | * @return vector |
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| 79 | */ |
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| 80 | public static function uniform(int $col, int $dtype = self::FLOAT): vector { |
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| 81 | $ar = self::factory($col, $dtype); |
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| 82 | $max = getrandmax(); |
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| 83 | for ($i = 0; $i < $col; ++$i) { |
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| 84 | $ar->data[$i] = rand(-$max, $max) / $max; |
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| 85 | } |
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| 86 | return $ar; |
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| 87 | } |
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| 88 | |||
| 89 | /** |
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| 90 | * Build a vector of zeros with n elements. |
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| 91 | * |
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| 92 | * @param int $col |
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| 93 | * @param int $dtype |
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| 94 | * @return vector |
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| 95 | */ |
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| 96 | public static function zeros(int $col, int $dtype = self::FLOAT): vector { |
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| 97 | $ar = self::factory($col, $dtype); |
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| 98 | for ($i = 0; $i < $col; ++$i) { |
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| 99 | $ar->data[$i] = 0; |
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| 100 | } |
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| 101 | return $ar; |
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| 102 | } |
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| 103 | |||
| 104 | /** |
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| 105 | * create one like vector |
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| 106 | * |
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| 107 | * @param int $col |
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| 108 | * @return vector |
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| 109 | */ |
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| 110 | public static function ones(int $col, int $dtype = self::FLOAT): vector { |
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| 111 | $ar = self::factory($col, $dtype); |
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| 112 | for ($i = 0; $i < $col; ++$i) { |
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| 113 | $ar->data[$i] = 1; |
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| 114 | } |
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| 115 | return $ar; |
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| 116 | } |
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| 117 | |||
| 118 | /** |
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| 119 | * create a null like vector |
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| 120 | * @param int $col |
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| 121 | * @return vector |
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| 122 | */ |
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| 123 | public static function null(int $col, int $dtype = self::FLOAT): vector { |
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| 124 | $ar = self::factory($col, $dtype); |
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| 125 | for ($i = 0; $i < $col; ++$i) { |
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| 126 | $ar->data[$i] = null; |
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| 127 | } |
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| 128 | return $ar; |
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| 129 | } |
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| 130 | |||
| 131 | /** |
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| 132 | * create a vector with given scalar value |
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| 133 | * @param int $col |
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| 134 | * @param int|float|double $val |
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| 135 | * @param int $dtype |
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| 136 | * @return vector |
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| 137 | */ |
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| 138 | public static function full(int $col, int|float $val, int $dtype = self::FLOAT): vector { |
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| 139 | $ar = self::factory($col, $dtype); |
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| 140 | for ($i = 0; $i < $col; ++$i) { |
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| 141 | $ar->data[$i] = $val; |
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| 142 | } |
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| 143 | return $ar; |
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| 144 | } |
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| 145 | |||
| 146 | /** |
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| 147 | * Return evenly spaced values within a given interval. |
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| 148 | * |
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| 149 | * @param int|float $start |
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| 150 | * @param int|float $end |
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| 151 | * @param int|float $interval |
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| 152 | * @param int $dtype |
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| 153 | * @return vector |
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| 154 | */ |
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| 155 | public static function range(int|float $start, int|float $end, int|float $interval = 1, int $dtype = self::FLOAT): vector { |
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| 156 | return self::ar(range($start, $end, $interval)); |
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| 157 | } |
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| 158 | |||
| 159 | /** |
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| 160 | * Return a Gaussian random vector with mean 0 |
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| 161 | * and unit variance. |
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| 162 | * |
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| 163 | * @param int $n |
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| 164 | * @param int $dtype |
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| 165 | * @return self |
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| 166 | */ |
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| 167 | public static function gaussian(int $n, int $dtype = self::FLOAT): vector { |
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| 168 | $max = getrandmax(); |
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| 169 | $a = new self($n, $dtype); |
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| 170 | while (count($a) < $n) { |
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| 171 | $r = sqrt(-2.0 * log(rand() / $max)); |
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| 172 | $phi = rand() / $max * (2. * M_PI); |
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| 173 | $a[] = $r * sin($phi); |
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| 174 | $a[] = $r * cos($phi); |
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| 175 | } |
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| 176 | if (count($a) > $n) { |
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| 177 | $a = array_slice($a, 0, $n); |
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| 178 | } |
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| 179 | return self::ar($a, $dtype); |
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| 180 | } |
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| 181 | |||
| 182 | /** |
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| 183 | * Generate a vector with n elements from a Poisson distribution. |
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| 184 | * |
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| 185 | * @param int $n |
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| 186 | * @param float $lambda |
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| 187 | * @param int $dtype |
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| 188 | * @return vector |
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| 189 | */ |
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| 190 | public static function poisson(int $n, float $lambda = 1.0, int $dtype = self::FLOAT): vector { |
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| 191 | $max = getrandmax(); |
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| 192 | $l = exp(-$lambda); |
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| 193 | $a = new self($n, $dtype); |
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| 194 | for ($i = 0; $i < $n; ++$i) { |
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| 195 | $k = 0; |
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| 196 | $p = 1.0; |
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| 197 | while ($p > $l) { |
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| 198 | ++$k; |
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| 199 | $p *= rand() / $max; |
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| 200 | } |
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| 201 | $a->data[$i] = $k - 1; |
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| 202 | } |
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| 203 | return $a; |
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| 204 | } |
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| 205 | |||
| 206 | /** |
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| 207 | * Return a vector of n evenly spaced numbers between minimum and maximum. |
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| 208 | * |
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| 209 | * @param float $min |
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| 210 | * @param float $max |
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| 211 | * @param int $n |
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| 212 | * @param int $dtype |
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| 213 | * @throws invalidArgumentException |
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| 214 | * @return vector |
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| 215 | */ |
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| 216 | public static function linspace(float $min, float $max, int $n, int $dtype = self::FLOAT): vector { |
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| 217 | if ($min > $max) { |
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| 218 | throw new invalidArgumentException('Minimum must be less than maximum.'); |
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| 219 | } |
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| 220 | if ($n < 2) { |
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| 221 | throw new invalidArgumentException('Number of elements must be greater than 1.'); |
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| 222 | } |
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| 223 | $k = $n - 1; |
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| 224 | $interval = abs($max - $min) / $k; |
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| 225 | $a = [$min]; |
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| 226 | while (count($a) < $k) { |
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| 227 | $a[] = end($a) + $interval; |
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| 228 | } |
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| 229 | $a[] = $max; |
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| 230 | return self::ar($a); |
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| 231 | } |
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| 232 | |||
| 233 | /** |
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| 234 | * make a copy of vector |
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| 235 | * @return vector |
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| 236 | */ |
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| 237 | public function copyVector(): vector { |
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| 238 | return clone $this; |
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| 239 | } |
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| 240 | |||
| 241 | /** |
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| 242 | * Return the element-wise maximum of given vector with current vector |
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| 243 | * |
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| 244 | * @param \Np\vector $vector |
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| 245 | * @return vector |
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| 246 | */ |
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| 247 | public function maximum(\Np\vector $vector): vector { |
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| 248 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 249 | $v = new self($this->ndim, $this->dtype); |
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| 250 | for($i = 0; $i<$v->ndim; ++$i) { |
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| 251 | $v->data[$i] = max($this->data[$i],$vector->data[$i]); |
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| 252 | } |
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| 253 | return $v; |
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| 254 | } |
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| 255 | } |
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| 256 | |||
| 257 | /** |
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| 258 | * Return the element-wise minium of given vector with current vector |
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| 259 | * |
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| 260 | * @param \Np\vector $vector |
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| 261 | * @return vector |
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| 262 | */ |
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| 263 | public function minium(\Np\vector $vector): vector { |
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| 264 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 265 | $v = new self($this->ndim, $this->dtype); |
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| 266 | for($i = 0; $i<$v->ndim; ++$i) { |
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| 267 | $v->data[$i] = min($this->data[$i],$vector->data[$i]); |
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| 268 | } |
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| 269 | return $v; |
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| 270 | } |
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| 271 | } |
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| 272 | |||
| 273 | /** |
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| 274 | * Return the index of the minimum element in the vector. |
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| 275 | * |
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| 276 | * @return int |
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| 277 | */ |
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| 278 | public function argMin():int { |
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| 279 | return blas::min($this); |
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| 280 | } |
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| 281 | |||
| 282 | /** |
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| 283 | * Return the index of the maximum element in the vector. |
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| 284 | * |
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| 285 | * @return int |
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| 286 | */ |
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| 287 | public function argMx():int { |
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| 288 | return blas::max($this); |
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| 289 | } |
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| 290 | |||
| 291 | /** |
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| 292 | * vector-vector dot product |
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| 293 | * @param \Np\vector $vector |
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| 294 | * @param int $incX |
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| 295 | * @param int $incY |
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| 296 | * @return vector |
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| 297 | */ |
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| 298 | public function dotVector(\Np\vector $v) { |
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| 299 | if ($this->checkDtype($v)) { |
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| 300 | return blas::dot($this, $v); |
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| 301 | } |
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| 302 | } |
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| 303 | |||
| 304 | /** |
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| 305 | * |
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| 306 | * @return float |
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| 307 | */ |
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| 308 | public function sum(): float { |
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| 309 | return blas::asum($this); |
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| 310 | } |
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| 311 | |||
| 312 | /** |
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| 313 | * Return the product of the vector. |
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| 314 | * @return int|float |
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| 315 | */ |
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| 316 | public function product(): float { |
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| 317 | $r = 1.0; |
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| 318 | for ($i = 0; $i < $this->col; ++$i) { |
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| 319 | $r *= $this->data[$i]; |
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| 320 | } |
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| 321 | return $r; |
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| 322 | } |
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| 323 | |||
| 324 | /** |
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| 325 | * Compute the vector-matrix dot product of this vector and matrix . |
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| 326 | * @param \Np\matrix $m |
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| 327 | * @return vector |
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| 328 | */ |
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| 329 | public function dotMatrix(\Np\matrix $m): vector { |
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| 330 | if ($this->dtype != $m->dtype) { |
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| 331 | self::_err('Mismatch Dtype of given matrix'); |
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| 332 | } |
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| 333 | $mvr = self::factory($this->col, $this->dtype); |
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| 334 | core\blas::gemv($m, $this, $mvr); |
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| 335 | return $mvr; |
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| 336 | } |
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| 337 | |||
| 338 | /** |
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| 339 | * |
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| 340 | * @param int|float|matrix|vector $d |
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| 341 | * @return matrix|vector |
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| 342 | */ |
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| 343 | public function divide(int|float|matrix|vector $d): matrix|vector { |
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| 344 | if ($d instanceof matrix) { |
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| 345 | return $this->divideMatrix($d); |
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| 346 | } elseif ($d instanceof self) { |
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| 347 | return $this->divideVector($d); |
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| 348 | } else { |
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| 349 | return $this->divideScalar($d); |
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| 350 | } |
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| 351 | } |
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| 352 | |||
| 353 | /** |
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| 354 | * |
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| 355 | * @param \Np\matrix $m |
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| 356 | * @return matrix |
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| 357 | */ |
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| 358 | protected function divideMatrix(\Np\matrix $m): matrix { |
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| 359 | if ($this->col == $m->col && $this->dtype == $m->dtype) { |
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| 360 | $vr = matrix::factory($m->row, $m->col, $m->dtype); |
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| 361 | for ($i = 0; $i < $m->row; ++$i) { |
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| 362 | for ($j = 0; $j < $m->col; ++$j) { |
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| 363 | $vr->data[$i * $m->col + $j] = $this->data[$j] / $m->data[$i * $m->col + $j]; |
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| 364 | } |
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| 365 | } |
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| 366 | return $vr; |
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| 367 | } |
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| 368 | } |
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| 369 | |||
| 370 | /** |
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| 371 | * |
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| 372 | * @param vector $v |
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| 373 | * @return vector |
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| 374 | */ |
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| 375 | protected function divideVector(vector $v): vector { |
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| 376 | if ($this->checkDimensions($v) && $this->checkDtype($v)) { |
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| 377 | $vr = self::factory($this->col, $this->dtype); |
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| 378 | for ($i = 0; $i < $this->col; ++$i) { |
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| 379 | $vr->data[$i] = $this->data[$i] / $v->data[$i]; |
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| 380 | } |
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| 381 | return $vr; |
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| 382 | } |
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| 383 | } |
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| 384 | |||
| 385 | /** |
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| 386 | * |
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| 387 | * @param int|float $s |
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| 388 | * @return vector |
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| 389 | */ |
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| 390 | protected function divideScalar(int|float $s): vector { |
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| 391 | $vr = self::factory($this->col, $this->dtype); |
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| 392 | for ($i = 0; $i < $this->col; ++$i) { |
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| 393 | $vr->data[$i] = $this->data[$i] / $s; |
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| 394 | } |
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| 395 | return $vr; |
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| 396 | } |
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| 397 | |||
| 398 | /** |
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| 399 | * |
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| 400 | * @param int|float|matrix|vector $d |
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| 401 | * @return matrix|vector |
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| 402 | */ |
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| 403 | public function multiply(int|float|matrix|vector $d): matrix|vector { |
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| 404 | if ($d instanceof matrix) { |
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| 405 | return $this->multiplyMatrix($d); |
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| 406 | } elseif ($d instanceof self) { |
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| 407 | return $this->multiplyVector($d); |
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| 408 | } else { |
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| 409 | return $this->multiplyScalar($d); |
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| 410 | } |
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| 411 | } |
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| 412 | |||
| 413 | /** |
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| 414 | * |
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| 415 | * @param \Np\matrix $m |
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| 416 | * @return matrix |
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| 417 | */ |
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| 418 | protected function multiplyMatrix(\Np\matrix $m): matrix { |
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| 419 | if ($this->col == $m->col && $this->dtype == $m->dtype) { |
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| 420 | $vr = matrix::factory($m->row, $m->col, $m->dtype); |
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| 421 | for ($i = 0; $i < $m->row; ++$i) { |
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| 422 | for ($j = 0; $j < $m->col; ++$j) { |
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| 423 | $vr->data[$i * $m->col + $j] = $this->data[$j] * $m->data[$i * $m->col + $j]; |
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| 424 | } |
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| 425 | } |
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| 426 | return $vr; |
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| 427 | } |
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| 428 | } |
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| 429 | |||
| 430 | /** |
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| 431 | * |
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| 432 | * @param \Np\vector $vector |
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| 433 | * @return vector |
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| 434 | */ |
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| 435 | protected function multiplyVector(\Np\vector $vector): vector { |
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| 436 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 437 | $vr = self::factory($this->col, $this->dtype); |
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| 438 | for ($i = 0; $i < $this->col; ++$i) { |
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| 439 | $vr->data[$i] = $this->data[$i] * $vector->data[$i]; |
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| 440 | } |
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| 441 | return $vr; |
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| 442 | } |
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| 443 | } |
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| 444 | |||
| 445 | /** |
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| 446 | * |
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| 447 | * @param int|float $s |
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| 448 | * @return vector |
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| 449 | */ |
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| 450 | protected function multiplyScalar(int|float $s): vector { |
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| 451 | $vr = $this->copyVector(); |
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| 452 | blas::scale($s, $vr); |
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| 453 | return $vr; |
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| 454 | } |
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| 455 | |||
| 456 | /** |
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| 457 | * |
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| 458 | * @param int|float|matrix|vector $d |
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| 459 | * @return matrix|vector |
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| 460 | */ |
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| 461 | public function add(int|float|matrix|vector $d): matrix|vector { |
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| 462 | if ($d instanceof matrix) { |
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| 463 | return $this->addMatrix($d); |
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| 464 | } elseif ($d instanceof self) { |
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| 465 | return $this->addVector($d); |
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| 466 | } else { |
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| 467 | return $this->addScalar($d); |
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| 468 | } |
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| 469 | } |
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| 470 | |||
| 471 | /** |
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| 472 | * |
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| 473 | * @param \Np\matrix $m |
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| 474 | * @return matrix |
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| 475 | */ |
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| 476 | protected function addMatrix(\Np\matrix $m): matrix { |
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| 477 | if ($this->col == $m->col && $this->dtype == $m->dtype) { |
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| 478 | $vr = matrix::factory($m->row, $m->col, $m->dtype); |
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| 479 | for ($i = 0; $i < $m->row; ++$i) { |
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| 480 | for ($j = 0; $j < $m->col; ++$j) { |
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| 481 | $vr->data[$i * $m->col + $j] = $this->data[$j] + $m->data[$i * $m->col + $j]; |
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| 482 | } |
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| 483 | } |
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| 484 | return $vr; |
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| 485 | } |
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| 486 | self::_invalidArgument(''); |
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| 487 | } |
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| 488 | |||
| 489 | /** |
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| 490 | * |
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| 491 | * @param \Np\vector $vector |
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| 492 | * @return vector |
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| 493 | */ |
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| 494 | protected function addVector(\Np\vector $vector): vector { |
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| 495 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 496 | $vr = self::factory($this->col, $this->dtype); |
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| 497 | for ($i = 0; $i < $this->col; ++$i) { |
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| 498 | $vr->data[$i] = $this->data[$i] + $vector->data[$i]; |
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| 499 | } |
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| 500 | return $vr; |
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| 501 | } |
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| 502 | } |
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| 503 | |||
| 504 | /** |
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| 505 | * |
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| 506 | * @param int|float $s |
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| 507 | * @return vector |
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| 508 | */ |
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| 509 | protected function addScalar(int|float $s): vector { |
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| 510 | $vr = $this->copyVector(); |
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| 511 | for ($i = 0; $i < $this->col; ++$i) { |
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| 512 | $vr->data[$i] += $s; |
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| 513 | } |
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| 514 | return $vr; |
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| 515 | } |
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| 516 | |||
| 517 | /** |
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| 518 | * |
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| 519 | * @param \Np\vector $vector |
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| 520 | * @return vector |
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| 521 | */ |
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| 522 | public function powVector(\Np\vector $vector): vector { |
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| 529 | } |
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| 530 | } |
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| 531 | |||
| 532 | /** |
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| 533 | * |
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| 534 | * @param \Np\vector $vector |
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| 535 | * @return vector |
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| 536 | */ |
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| 537 | public function modVector(\Np\vector $vector): vector { |
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| 538 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 539 | $vr = self::factory($this->col, $this->dtype); |
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| 540 | for ($i = 0; $i < $this->col; ++$i) { |
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| 541 | $vr->data[$i] = $this->data[$i] % $vector->data[$i]; |
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| 542 | } |
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| 543 | return $vr; |
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| 544 | } |
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| 545 | } |
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| 546 | |||
| 547 | /** |
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| 548 | * |
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| 549 | * @param int|float|matrix|vector $d |
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| 550 | * @return matrix|vector |
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| 551 | */ |
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| 552 | public function subtract(int|float|matrix|vector $d): matrix|vector { |
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| 553 | if ($d instanceof matrix) { |
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| 554 | return $this->subtractMatrix($d); |
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| 555 | } elseif ($d instanceof self) { |
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| 556 | return $this->subtractVector($d); |
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| 557 | } else { |
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| 558 | return $this->substractScalar($d); |
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| 559 | } |
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| 560 | } |
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| 561 | |||
| 562 | /** |
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| 563 | * |
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| 564 | * @param \Np\matrix $m |
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| 565 | * @return matrix |
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| 566 | */ |
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| 567 | protected function subtractMatrix(\Np\matrix $m): matrix { |
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| 568 | if ($this->col == $m->col && $this->dtype == $m->dtype) { |
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| 569 | $vr = matrix::factory($m->row, $m->col, $m->dtype); |
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| 570 | for ($i = 0; $i < $m->row; ++$i) { |
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| 571 | for ($j = 0; $j < $m->col; ++$j) { |
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| 572 | $vr->data[$i * $m->col + $j] = $this->data[$j] - $m->data[$i * $m->col + $j]; |
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| 573 | } |
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| 574 | } |
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| 575 | return $vr; |
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| 576 | } |
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| 577 | self::_invalidArgument(''); |
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| 578 | } |
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| 579 | |||
| 580 | /** |
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| 581 | * |
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| 582 | * @param \Np\vector $vector |
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| 583 | * @return vector |
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| 584 | */ |
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| 585 | protected function subtractVector(\Np\vector $vector): vector { |
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| 586 | if ($this->checkDimensions($vector) && $this->checkDtype($vector)) { |
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| 587 | $vr = self::factory($this->col, $this->dtype); |
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| 588 | for ($i = 0; $i < $this->col; ++$i) { |
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| 589 | $vr->data[$i] = $this->data[$i] - $vector->data[$i]; |
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| 590 | } |
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| 591 | return $vr; |
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| 592 | } |
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| 593 | } |
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| 594 | |||
| 595 | /** |
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| 596 | * |
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| 597 | * @param \Np\vector $scalar |
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| 598 | * @return \Np\vector |
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| 599 | */ |
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| 600 | protected function substractScalar(int|float $scalar): vector { |
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| 601 | $vr = self::factory($this->col, $this->dtype); |
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| 602 | for ($i = 0; $i < $this->col; ++$i) { |
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| 603 | $vr->data[$i] = $this->data[$i] - $scalar; |
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| 604 | } |
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| 605 | return $vr; |
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| 606 | } |
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| 607 | |||
| 608 | /** |
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| 609 | * |
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| 610 | * @param \Np\vector $v |
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| 611 | * @param int $stride |
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| 612 | * @return vector |
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| 613 | */ |
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| 614 | public function convolve(\Np\vector $v, int $stride = 1): vector { |
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| 616 | } |
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| 617 | |||
| 618 | /** |
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| 619 | * Return the inner product of two vectors. |
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| 620 | * |
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| 621 | * @param \Np\vector $vector |
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| 622 | * @return float |
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| 623 | */ |
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| 624 | public function inner(\Np\vector $vector) { |
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| 625 | return $this->dotVector($vector); |
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| 626 | } |
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| 627 | |||
| 628 | public function l1_norm() { |
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| 629 | |||
| 630 | } |
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| 631 | |||
| 632 | public function l2_norm() { |
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| 633 | |||
| 634 | } |
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| 635 | |||
| 636 | /** |
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| 637 | * sort the vector |
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| 638 | * @param string $type i or d |
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| 639 | * |
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| 640 | */ |
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| 641 | public function sort($type = 'i') { |
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| 642 | lapack::sort($this, $type); |
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| 643 | return $this; |
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| 644 | } |
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| 645 | |||
| 646 | /** |
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| 647 | * set data to vector |
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| 648 | * @param int|float|array $data |
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| 649 | */ |
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| 650 | public function setData(int|float|array $data) { |
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| 651 | if (is_array($data) && !is_array($data[0])) { |
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| 652 | for ($i = 0; $i < $this->col; ++$i) { |
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| 653 | $this->data[$i] = $data[$i]; |
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| 654 | } |
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| 655 | } elseif (is_numeric($data)) { |
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| 656 | for ($i = 0; $i < $this->col; ++$i) { |
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| 657 | $this->data[$i] = $data; |
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| 658 | } |
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| 659 | } |
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| 660 | } |
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| 661 | |||
| 662 | public function asMatrix(): matrix { |
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| 663 | $size = (int) sqrt($this->col); |
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| 664 | $ar = matrix::factory($size, $size, $this->dtype); |
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| 665 | for ($i = 0; $i < $ar->ndim; ++$i) { |
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| 666 | $ar->data[$i] = $this->data[$i]; |
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| 667 | } |
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| 668 | return $ar; |
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| 669 | } |
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| 670 | |||
| 671 | /** |
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| 672 | * get the shape of matrix |
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| 673 | * @return int |
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| 674 | */ |
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| 675 | public function getShape(): int { |
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| 676 | return $this->col; |
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| 677 | } |
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| 678 | |||
| 679 | public function getDtype() { |
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| 680 | return $this->dtype; |
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| 681 | } |
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| 682 | |||
| 683 | public function asArray() { |
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| 684 | $ar = array_fill(0, $this->col, null); |
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| 685 | for ($i = 0; $i < $this->col; ++$i) { |
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| 686 | $ar[$i] = $this->data[$i]; |
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| 687 | } |
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| 688 | return $ar; |
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| 689 | } |
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| 690 | |||
| 691 | public function printVector() { |
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| 692 | for ($j = 0; $j < $this->col; ++$j) { |
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| 693 | printf('%lf ', $this->data[$j]); |
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| 694 | } |
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| 695 | echo PHP_EOL; |
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| 696 | } |
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| 697 | |||
| 698 | public function __toString() { |
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| 699 | return (string) $this->printVector(); |
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| 700 | } |
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| 701 | |||
| 702 | protected function checkDimensions(vector $vector) { |
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| 707 | } |
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| 708 | |||
| 709 | protected function checkDtype(vector $vector) { |
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| 710 | if ($this->dtype != $vector->dtype) { |
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| 711 | throw new dtypeException('Mismatch dtype of given vector'); |
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| 712 | } |
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| 713 | return true; |
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| 714 | } |
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| 715 | |||
| 716 | protected function __construct(int $col, int $dtype = self::FLOAT) { |
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| 717 | if ($col < 1) { |
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| 718 | throw new invalidArgumentException('* To create Numphp/Vector col must be greater than 0!, Op Failed! * '); |
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| 719 | } |
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| 720 | parent::__construct($col, $dtype); |
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| 721 | $this->col = $col; |
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| 722 | return $this; |
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| 723 | } |
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| 724 | |||
| 725 | } |
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| 726 |
Loading history...
For hinted functions/methods where all return statements with the correct type are only reachable via conditions, ?null? gets implicitly returned which may be incompatible with the hinted type. Let?s take a look at an example: