ghostjat /
Np
| Total Complexity | 137 |
| Total Lines | 772 |
| Duplicated Lines | 0 % |
| Changes | 13 | ||
| Bugs | 5 | 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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| 20 | class vector extends nd { |
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| 21 | use ops,linAlgb\linAlg; |
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| 22 | |||
| 23 | /** |
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| 24 | * Factory method to build a new vector. |
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| 25 | * |
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| 26 | * @param int $col |
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| 27 | * @param int $dtype |
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| 28 | * @return vector |
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| 29 | */ |
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| 30 | public static function factory(int $col, int $dtype = self::DOUBLE): vector { |
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| 31 | return new self($col, $dtype); |
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| 32 | } |
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| 33 | |||
| 34 | /** |
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| 35 | * Build a new vector from a php array. |
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| 36 | * |
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| 37 | * @param array $data |
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| 38 | * @return vector |
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| 39 | */ |
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| 40 | public static function ar(array $data): vector { |
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| 41 | if (is_array($data) && !is_array($data[0])) { |
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| 42 | $ar = self::factory(count($data)); |
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| 43 | $ar->setData($data); |
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| 44 | return $ar; |
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| 45 | } else { |
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| 46 | self::_err('data must be of same dimensions'); |
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| 47 | } |
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| 48 | } |
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| 49 | |||
| 50 | /** |
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| 51 | * Return vector with random values |
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| 52 | * @param int $col |
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| 53 | * @return vector |
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| 54 | */ |
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| 55 | public static function randn(int $col): vector { |
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| 56 | $ar = self::factory($col); |
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| 57 | $max = getrandmax(); |
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| 58 | for ($i = 0; $i < $ar->col; ++$i) { |
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| 59 | $ar->data[$i] = rand() / $max; |
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| 60 | } |
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| 61 | return $ar; |
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| 62 | } |
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| 63 | |||
| 64 | /** |
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| 65 | * Return vector with uniform values |
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| 66 | * @param int $col |
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| 67 | * @return vector |
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| 68 | */ |
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| 69 | public static function uniform(int $col): vector { |
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| 70 | $ar = self::factory($col); |
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| 71 | $max = getrandmax(); |
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| 72 | for ($i = 0; $i < $col; ++$i) { |
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| 73 | $ar->data[$i] = rand(-$max, $max) / $max; |
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| 74 | } |
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| 75 | return $ar; |
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| 76 | } |
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| 77 | |||
| 78 | /** |
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| 79 | * Build a vector of zeros with n elements. |
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| 80 | * |
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| 81 | * @param int $col |
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| 82 | * @return vector |
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| 83 | */ |
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| 84 | public static function zeros(int $col): vector { |
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| 85 | $ar = self::factory($col); |
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| 86 | for ($i = 0; $i < $col; ++$i) { |
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| 87 | $ar->data[$i] = 0; |
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| 88 | } |
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| 89 | return $ar; |
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| 90 | } |
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| 91 | |||
| 92 | /** |
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| 93 | * create one like vector |
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| 94 | * |
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| 95 | * @param int $col |
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| 96 | * @return vector |
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| 97 | */ |
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| 98 | public static function ones(int $col): vector { |
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| 99 | $ar = self::factory($col); |
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| 100 | for ($i = 0; $i < $col; ++$i) { |
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| 101 | $ar->data[$i] = 1; |
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| 102 | } |
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| 103 | return $ar; |
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| 104 | } |
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| 105 | |||
| 106 | /** |
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| 107 | * create a null like vector |
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| 108 | * @param int $col |
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| 109 | * @return vector |
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| 110 | */ |
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| 111 | public static function null(int $col): vector { |
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| 112 | $ar = self::factory($col); |
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| 113 | for ($i = 0; $i < $col; ++$i) { |
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| 114 | $ar->data[$i] = null; |
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| 115 | } |
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| 116 | return $ar; |
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| 117 | } |
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| 118 | |||
| 119 | /** |
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| 120 | * create a vector with given scalar value |
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| 121 | * @param int $col |
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| 122 | * @param int|float|double $val |
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| 123 | * @return vector |
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| 124 | */ |
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| 125 | public static function full(int $col, int|float $val): vector { |
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| 126 | $ar = self::factory($col); |
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| 127 | for ($i = 0; $i < $col; ++$i) { |
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| 128 | $ar->data[$i] = $val; |
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| 129 | } |
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| 130 | return $ar; |
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| 131 | } |
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| 132 | |||
| 133 | /** |
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| 134 | * Return evenly spaced values within a given interval. |
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| 135 | * |
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| 136 | * @param int|float $start |
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| 137 | * @param int|float $end |
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| 138 | * @param int|float $interval |
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| 139 | * @return vector |
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| 140 | */ |
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| 141 | public static function range(int|float $start, int|float $end, int|float $interval = 1): vector { |
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| 142 | return self::ar(range($start, $end, $interval)); |
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| 143 | } |
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| 144 | |||
| 145 | /** |
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| 146 | * Return a Gaussian random vector with mean 0 |
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| 147 | * and unit variance. |
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| 148 | * |
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| 149 | * @param int $n |
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| 150 | * @return self |
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| 151 | */ |
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| 152 | public static function gaussian(int $n): vector { |
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| 153 | $max = getrandmax(); |
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| 154 | $a = []; |
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| 155 | while (count($a) < $n) { |
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| 156 | $r = sqrt(-2.0 * log(rand() / $max)); |
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| 157 | $phi = rand() / $max * (2. * M_PI); |
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| 158 | $a[] = $r * sin($phi); |
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| 159 | $a[] = $r * cos($phi); |
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| 160 | } |
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| 161 | if (count($a) > $n) { |
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| 162 | $a = array_slice($a, 0, $n); |
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| 163 | } |
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| 164 | return self::ar($a); |
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| 165 | } |
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| 166 | |||
| 167 | /** |
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| 168 | * Generate a vector with n elements from a Poisson distribution. |
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| 169 | * |
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| 170 | * @param int $n |
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| 171 | * @param float $lambda |
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| 172 | * @return vector |
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| 173 | */ |
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| 174 | public static function poisson(int $n, float $lambda = 1.0): vector { |
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| 175 | $max = getrandmax(); |
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| 176 | $l = exp(-$lambda); |
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| 177 | $a = new self($n); |
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| 178 | for ($i = 0; $i < $n; ++$i) { |
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| 179 | $k = 0; |
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| 180 | $p = 1.0; |
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| 181 | while ($p > $l) { |
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| 182 | ++$k; |
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| 183 | $p *= rand() / $max; |
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| 184 | } |
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| 185 | $a->data[$i] = $k - 1; |
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| 186 | } |
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| 187 | return $a; |
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| 188 | } |
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| 189 | |||
| 190 | /** |
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| 191 | * Return a vector of n evenly spaced numbers between minimum and maximum. |
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| 192 | * |
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| 193 | * @param float $min |
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| 194 | * @param float $max |
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| 195 | * @param int $n |
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| 196 | * @throws invalidArgumentException |
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| 197 | * @return vector |
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| 198 | */ |
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| 199 | public static function linspace(float $min, float $max, int $n): vector { |
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| 200 | if ($min > $max) { |
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| 201 | throw new invalidArgumentException('Minimum must be less than maximum.'); |
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| 202 | } |
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| 203 | if ($n < 2) { |
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| 204 | throw new invalidArgumentException('Number of elements must be greater than 1.'); |
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| 205 | } |
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| 206 | $k = $n - 1; |
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| 207 | $interval = abs($max - $min) / $k; |
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| 208 | $a = [$min]; |
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| 209 | while (count($a) < $k) { |
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| 210 | $a[] = end($a) + $interval; |
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| 211 | } |
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| 212 | $a[] = $max; |
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| 213 | return self::ar($a); |
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| 214 | } |
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| 215 | |||
| 216 | /** |
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| 217 | * Return the index of the minimum element in the vector. |
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| 218 | * |
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| 219 | * @return int |
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| 220 | */ |
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| 221 | public function argMin(): int { |
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| 222 | return blas::min($this); |
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| 223 | } |
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| 224 | |||
| 225 | /** |
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| 226 | * Return the index of the maximum element in the vector. |
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| 227 | * |
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| 228 | * @return int |
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| 229 | */ |
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| 230 | public function argMax(): int { |
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| 232 | } |
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| 233 | |||
| 234 | /** |
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| 235 | * The sum of the vector. |
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| 236 | * @return float |
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| 237 | */ |
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| 238 | public function sum(): float { |
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| 239 | return blas::asum($this); |
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| 240 | } |
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| 241 | |||
| 242 | /** |
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| 243 | * Return the product of the vector. |
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| 244 | * @return int|float |
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| 245 | */ |
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| 246 | public function product(): float { |
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| 247 | $r = 1.0; |
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| 248 | for ($i = 0; $i < $this->col; ++$i) { |
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| 249 | $r *= $this->data[$i]; |
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| 250 | } |
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| 251 | return $r; |
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| 252 | } |
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| 253 | |||
| 254 | /** |
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| 255 | * Compute the vector-matrix dot product of this vector and matrix . |
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| 256 | * @param \Np\matrix $m |
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| 257 | * @return vector |
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| 258 | */ |
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| 259 | public function dotMatrix(\Np\matrix $m): vector { |
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| 260 | if ($this->checkDtype($this, $m)) { |
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| 261 | $mvr = self::factory($this->col); |
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| 262 | core\blas::gemv($m, $this, $mvr); |
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| 263 | return $mvr; |
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| 264 | } |
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| 265 | } |
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| 266 | |||
| 267 | /** |
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| 268 | * |
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| 269 | * @param int|float|matrix|vector $d |
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| 270 | * @return matrix|vector |
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| 271 | */ |
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| 272 | public function divide(int|float|matrix|vector $d): matrix|vector { |
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| 273 | if ($d instanceof matrix) { |
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| 274 | return $this->divideMatrix($d); |
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| 275 | } |
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| 276 | if ($d instanceof self) { |
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| 277 | return $this->divideVector($d); |
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| 278 | } |
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| 279 | return $this->divideScalar($d); |
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| 280 | } |
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| 281 | |||
| 282 | /** |
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| 283 | * |
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| 284 | * @param \Np\matrix $m |
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| 285 | * @return matrix |
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| 286 | */ |
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| 287 | protected function divideMatrix(\Np\matrix $m): matrix { |
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| 288 | if ($this->checkShape($this, $m)) { |
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| 289 | $vr = matrix::factory($m->row, $m->col); |
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| 290 | for ($i = 0; $i < $m->row; ++$i) { |
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| 291 | for ($j = 0; $j < $m->col; ++$j) { |
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| 292 | $vr->data[$i * $m->col + $j] = $this->data[$j] / $m->data[$i * $m->col + $j]; |
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| 293 | } |
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| 294 | } |
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| 295 | return $vr; |
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| 296 | } |
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| 297 | } |
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| 298 | |||
| 299 | /** |
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| 300 | * |
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| 301 | * @param vector $v |
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| 302 | * @return vector |
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| 303 | */ |
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| 304 | protected function divideVector(vector $v): vector { |
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| 305 | if ($this->checkShape($this, $v)) { |
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| 306 | $vr = self::factory($this->col); |
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| 307 | for ($i = 0; $i < $this->col; ++$i) { |
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| 308 | $vr->data[$i] = $this->data[$i] / $v->data[$i]; |
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| 309 | } |
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| 310 | return $vr; |
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| 311 | } |
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| 312 | } |
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| 313 | |||
| 314 | /** |
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| 315 | * |
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| 316 | * @param int|float $s |
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| 317 | * @return vector |
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| 318 | */ |
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| 319 | protected function divideScalar(int|float $s): vector { |
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| 320 | $vr = self::factory($this->col); |
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| 321 | for ($i = 0; $i < $this->col; ++$i) { |
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| 322 | $vr->data[$i] = $this->data[$i] / $s; |
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| 323 | } |
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| 324 | return $vr; |
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| 325 | } |
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| 326 | |||
| 327 | /** |
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| 328 | * |
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| 329 | * @param int|float|matrix|vector $d |
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| 330 | * @return matrix|vector |
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| 331 | */ |
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| 332 | public function multiply(int|float|matrix|vector $d): matrix|vector { |
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| 333 | if ($d instanceof matrix) { |
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| 334 | return $this->multiplyMatrix($d); |
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| 335 | } |
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| 336 | if ($d instanceof self) { |
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| 337 | return $this->multiplyVector($d); |
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| 338 | } |
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| 339 | return $this->multiplyScalar($d); |
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| 340 | } |
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| 341 | |||
| 342 | /** |
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| 343 | * |
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| 344 | * @param \Np\matrix $m |
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| 345 | * @return matrix |
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| 346 | */ |
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| 347 | protected function multiplyMatrix(\Np\matrix $m): matrix { |
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| 348 | if ($this->checkShape($this, $m)) { |
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| 349 | $vr = matrix::factory($m->row, $m->col); |
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| 350 | for ($i = 0; $i < $m->row; ++$i) { |
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| 351 | for ($j = 0; $j < $m->col; ++$j) { |
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| 352 | $vr->data[$i * $m->col + $j] = $this->data[$j] * $m->data[$i * $m->col + $j]; |
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| 353 | } |
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| 354 | } |
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| 355 | return $vr; |
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| 356 | } |
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| 357 | } |
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| 358 | |||
| 359 | /** |
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| 360 | * |
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| 361 | * @param \Np\vector $vector |
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| 362 | * @return vector |
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| 363 | */ |
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| 364 | protected function multiplyVector(\Np\vector $vector): vector { |
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| 365 | if ($this->checkShape($this, $vector)) { |
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| 366 | $vr = self::factory($this->col); |
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| 367 | for ($i = 0; $i < $this->col; ++$i) { |
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| 368 | $vr->data[$i] = $this->data[$i] * $vector->data[$i]; |
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| 369 | } |
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| 370 | return $vr; |
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| 371 | } |
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| 372 | } |
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| 373 | |||
| 374 | /** |
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| 375 | * |
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| 376 | * @param int|float $s |
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| 377 | * @return vector |
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| 378 | */ |
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| 379 | protected function multiplyScalar(int|float $s): vector { |
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| 380 | $vr = $this->copy(); |
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| 381 | blas::scale($s, $vr); |
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| 382 | return $vr; |
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| 383 | } |
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| 384 | |||
| 385 | /** |
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| 386 | * |
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| 387 | * @param int|float|matrix|vector $d |
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| 388 | * @return matrix|vector |
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| 389 | */ |
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| 390 | public function add(int|float|matrix|vector $d): matrix|vector { |
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| 391 | if ($d instanceof matrix) { |
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| 392 | return $this->addMatrix($d); |
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| 393 | } |
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| 394 | if ($d instanceof self) { |
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| 395 | return $this->addVector($d); |
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| 396 | } |
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| 397 | return $this->addScalar($d); |
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| 398 | } |
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| 399 | |||
| 400 | /** |
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| 401 | * |
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| 402 | * @param \Np\matrix $m |
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| 403 | * @return matrix |
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| 404 | */ |
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| 405 | protected function addMatrix(\Np\matrix $m): matrix { |
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| 406 | if ($this->checkShape($this, $m)) { |
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| 407 | $vr = matrix::factory($m->row, $m->col); |
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| 408 | for ($i = 0; $i < $m->row; ++$i) { |
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| 409 | for ($j = 0; $j < $m->col; ++$j) { |
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| 410 | $vr->data[$i * $m->col + $j] = $this->data[$j] + $m->data[$i * $m->col + $j]; |
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| 411 | } |
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| 412 | } |
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| 413 | return $vr; |
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| 414 | } |
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| 415 | } |
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| 416 | |||
| 417 | /** |
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| 418 | * |
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| 419 | * @param \Np\vector $vector |
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| 420 | * @return vector |
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| 421 | */ |
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| 422 | protected function addVector(\Np\vector $vector): vector { |
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| 423 | if ($this->checkShape($this, $vector)) { |
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| 424 | $vr = self::factory($this->col); |
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| 425 | for ($i = 0; $i < $this->col; ++$i) { |
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| 426 | $vr->data[$i] = $this->data[$i] + $vector->data[$i]; |
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| 427 | } |
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| 428 | return $vr; |
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| 429 | } |
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| 430 | } |
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| 431 | |||
| 432 | /** |
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| 433 | * |
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| 434 | * @param int|float $s |
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| 435 | * @return vector |
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| 436 | */ |
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| 437 | protected function addScalar(int|float $s): vector { |
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| 438 | $vr = $this->copy(); |
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| 439 | for ($i = 0; $i < $this->col; ++$i) { |
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| 440 | $vr->data[$i] += $s; |
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| 441 | } |
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| 442 | return $vr; |
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| 443 | } |
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| 444 | |||
| 445 | /** |
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| 446 | * |
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| 447 | * @param int|float|\Np\matrix|\Np\vector $d |
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| 448 | * @return matrix|vector |
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| 449 | */ |
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| 450 | public function pow(int|float|\Np\matrix|\Np\vector $d): matrix|vector { |
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| 451 | if ($d instanceof matrix) { |
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| 452 | return $this->powMatrix($d); |
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| 453 | } |
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| 454 | if ($d instanceof vector) { |
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| 455 | return $this->powVector($d); |
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| 456 | } |
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| 457 | return $this->powScalar($d); |
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| 458 | |||
| 459 | } |
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| 460 | |||
| 461 | /** |
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| 462 | * |
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| 463 | * @param \Np\matrix $m |
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| 464 | * @return matrix |
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| 465 | */ |
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| 466 | protected function powMatrix(\Np\matrix $m): matrix { |
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| 467 | if ($this->checkDimensions($this, $m)) { |
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| 468 | $ar = matrix::factory($m->row, $m->col); |
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| 469 | for ($i = 0; $i < $m->row; ++$i) { |
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| 470 | for ($j = 0; $j < $m->col; ++$j) { |
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| 471 | $ar->data[$i * $m->col + $j] = $m->data[$i * $m->col + $j] ** $this->data[$j]; |
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| 472 | } |
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| 473 | } |
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| 474 | return $ar; |
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| 475 | } |
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| 476 | } |
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| 477 | |||
| 478 | /** |
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| 479 | * |
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| 480 | * @param \Np\vector $vector |
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| 481 | * @return vector |
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| 482 | */ |
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| 483 | protected function powVector(\Np\vector $vector): vector { |
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| 490 | } |
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| 491 | } |
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| 492 | |||
| 493 | /** |
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| 494 | * |
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| 495 | * @param int|float $s |
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| 496 | * @return vector |
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| 497 | */ |
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| 498 | protected function powScalar(int|float $s): vector { |
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| 499 | $v = $this->copy(); |
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| 500 | for ($i = 0; $i < $this->col; ++$i) { |
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| 501 | $v->data[$i] = $v->data[$i] ** $s; |
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| 502 | } |
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| 503 | return $v; |
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| 504 | } |
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| 505 | |||
| 506 | /** |
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| 507 | * |
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| 508 | * @param int|float|\Np\matrix|\Np\vector $d |
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| 509 | * @return matrix|vector |
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| 510 | */ |
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| 511 | public function mod(int|float|\Np\matrix|\Np\vector $d): matrix|vector { |
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| 512 | if ($d instanceof matrix) { |
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| 513 | return $this->powMatrix($d); |
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| 514 | } |
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| 515 | if ($d instanceof vector) { |
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| 516 | return $this->powVector($d); |
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| 517 | } |
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| 518 | return $this->powScalar($d); |
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| 519 | } |
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| 520 | |||
| 521 | /** |
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| 522 | * |
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| 523 | * @param \Np\matrix $m |
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| 524 | * @return matrix |
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| 525 | */ |
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| 526 | protected function modMatrix(\Np\matrix $m): matrix { |
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| 527 | if ($this->checkDimensions($this, $m)) { |
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| 528 | $ar = matrix::factory($m->row, $m->col); |
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| 529 | for ($i = 0; $i < $m->row; ++$i) { |
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| 530 | for ($j = 0; $j < $m->col; ++$j) { |
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| 531 | $ar->data[$i * $m->col + $j] = $m->data[$i * $m->col + $j] % $this->data[$j]; |
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| 532 | } |
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| 533 | } |
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| 534 | return $ar; |
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| 535 | } |
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| 536 | } |
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| 537 | |||
| 538 | /** |
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| 539 | * |
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| 540 | * @param \Np\vector $vector |
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| 541 | * @return vector |
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| 542 | */ |
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| 543 | protected function modVector(\Np\vector $vector): vector { |
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| 544 | if ($this->checkShape($this, $vector)) { |
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| 545 | $vr = self::factory($this->col); |
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| 546 | for ($i = 0; $i < $this->col; ++$i) { |
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| 547 | $vr->data[$i] = $this->data[$i] % $vector->data[$i]; |
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| 548 | } |
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| 549 | return $vr; |
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| 550 | } |
||
| 551 | } |
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| 552 | |||
| 553 | /** |
||
| 554 | * |
||
| 555 | * @param int|float $s |
||
| 556 | */ |
||
| 557 | protected function modScalar(int|float $s) { |
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| 558 | $v = $this->copy(); |
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| 559 | for ($i = 0; $i < $this->col; ++$i) { |
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| 560 | $v->data[$i] = $v->data[$i] % $s; |
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| 561 | } |
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| 562 | } |
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| 563 | |||
| 564 | /** |
||
| 565 | * |
||
| 566 | * @param int|float|matrix|vector $d |
||
| 567 | * @return matrix|vector |
||
| 568 | */ |
||
| 569 | public function subtract(int|float|matrix|vector $d): matrix|vector { |
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| 570 | if ($d instanceof matrix) { |
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| 571 | return $this->subtractMatrix($d); |
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| 572 | } |
||
| 573 | if ($d instanceof self) { |
||
| 574 | return $this->subtractVector($d); |
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| 575 | } |
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| 576 | return $this->substractScalar($d); |
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| 577 | } |
||
| 578 | |||
| 579 | /** |
||
| 580 | * |
||
| 581 | * @param \Np\matrix $m |
||
| 582 | * @return matrix |
||
| 583 | */ |
||
| 584 | protected function subtractMatrix(\Np\matrix $m): matrix { |
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| 585 | if ($this->checkShape($this, $m)) { |
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| 586 | $vr = matrix::factory($m->row, $m->col); |
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| 587 | for ($i = 0; $i < $m->row; ++$i) { |
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| 588 | for ($j = 0; $j < $m->col; ++$j) { |
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| 589 | $vr->data[$i * $m->col + $j] = $this->data[$j] - $m->data[$i * $m->col + $j]; |
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| 590 | } |
||
| 591 | } |
||
| 592 | return $vr; |
||
| 593 | } |
||
| 594 | } |
||
| 595 | |||
| 596 | /** |
||
| 597 | * |
||
| 598 | * @param \Np\vector $vector |
||
| 599 | * @return vector |
||
| 600 | */ |
||
| 601 | protected function subtractVector(\Np\vector $vector): vector { |
||
| 602 | if ($this->checkShape($this, $vector) ) { |
||
| 603 | $vr = self::factory($this->col); |
||
| 604 | for ($i = 0; $i < $this->col; ++$i) { |
||
| 605 | $vr->data[$i] = $this->data[$i] - $vector->data[$i]; |
||
| 606 | } |
||
| 607 | return $vr; |
||
| 608 | } |
||
| 609 | } |
||
| 610 | |||
| 611 | /** |
||
| 612 | * |
||
| 613 | * @param \Np\vector $scalar |
||
| 614 | * @return \Np\vector |
||
| 615 | */ |
||
| 616 | protected function substractScalar(int|float $scalar): vector { |
||
| 617 | $vr = self::factory($this->col); |
||
| 618 | for ($i = 0; $i < $this->col; ++$i) { |
||
| 619 | $vr->data[$i] = $this->data[$i] - $scalar; |
||
| 620 | } |
||
| 621 | return $vr; |
||
| 622 | } |
||
| 623 | |||
| 624 | /** |
||
| 625 | * |
||
| 626 | * @param \Np\vector $v |
||
| 627 | * @param int $stride |
||
| 628 | * @return vector |
||
| 629 | */ |
||
| 630 | public function convolve(\Np\vector $v, int $stride = 1): vector { |
||
| 632 | } |
||
| 633 | |||
| 634 | public function max() { |
||
| 636 | } |
||
| 637 | |||
| 638 | public function min() { |
||
| 639 | $this->data[blas::min($this)]; |
||
| 640 | } |
||
| 641 | |||
| 642 | /** |
||
| 643 | * Return the inner product of two vectors. |
||
| 644 | * |
||
| 645 | * @param \Np\vector $vector |
||
| 646 | * |
||
| 647 | */ |
||
| 648 | public function inner(\Np\vector $vector) { |
||
| 649 | return $this->dotVector($vector); |
||
| 650 | } |
||
| 651 | |||
| 652 | /** |
||
| 653 | * Calculate the L1 norm of the vector. |
||
| 654 | * @return float |
||
| 655 | */ |
||
| 656 | public function normL1(): float { |
||
| 657 | return $this->abs()->sum(); |
||
| 658 | } |
||
| 659 | |||
| 660 | public function normL2() { |
||
| 661 | return sqrt($this->square()->sum()); |
||
| 662 | } |
||
| 663 | |||
| 664 | public function normMax() { |
||
| 665 | return $this->abs()->max(); |
||
| 666 | } |
||
| 667 | |||
| 668 | public function normP(float $p = 2.5) { |
||
| 669 | if ($p <= 0.0) { |
||
| 670 | self::_invalidArgument('P must be greater than 0.0 !'); |
||
| 671 | } |
||
| 672 | return $this->abs()->powScalar($p)->sum() ** (1.0 / $p); |
||
| 673 | } |
||
| 674 | |||
| 675 | /** |
||
| 676 | * Return the reciprocal of the vector element-wise. |
||
| 677 | * |
||
| 678 | * @return self |
||
| 679 | */ |
||
| 680 | public function reciprocal(): vector { |
||
| 681 | return self::ones($this->col)->divideVector($this); |
||
| 682 | } |
||
| 683 | |||
| 684 | /** |
||
| 685 | * |
||
| 686 | * @return int|float |
||
| 687 | */ |
||
| 688 | public function mean():int|float { |
||
| 689 | return $this->sum()/ $this->col; |
||
| 690 | } |
||
| 691 | |||
| 692 | /** |
||
| 693 | * |
||
| 694 | * @return int|float |
||
| 695 | */ |
||
| 696 | public function median():int|float { |
||
| 697 | $mid = intdiv($this->col, 2); |
||
| 698 | |||
| 699 | $a = $this->copy()->sort(); |
||
| 700 | if ($this->col % 2 === 1) { |
||
| 701 | $median = $a->data[$mid]; |
||
| 702 | } else { |
||
| 703 | $median = ($a->data[$mid - 1] + $a->data[$mid]) / 2.; |
||
| 704 | } |
||
| 705 | return $median; |
||
| 706 | } |
||
| 707 | |||
| 708 | public function variance($mean = null) |
||
| 709 | { |
||
| 710 | if (is_null($mean)) { |
||
| 711 | $mean = $this->mean(); |
||
| 712 | } |
||
| 713 | |||
| 714 | $sd = $this->substractScalar($mean)->square()->sum(); |
||
| 715 | |||
| 716 | return $sd / $this->col; |
||
| 717 | } |
||
| 718 | |||
| 719 | /** |
||
| 720 | * |
||
| 721 | * @return vector |
||
| 722 | */ |
||
| 723 | public function square(): vector { |
||
| 724 | return $this->multiplyVector($this); |
||
| 725 | } |
||
| 726 | |||
| 727 | /** |
||
| 728 | * sort the vector |
||
| 729 | * @param string $type i or d |
||
| 730 | * |
||
| 731 | */ |
||
| 732 | public function sort($type = 'i') { |
||
| 735 | } |
||
| 736 | |||
| 737 | /** |
||
| 738 | * set data to vector |
||
| 739 | * @param int|float|array $data |
||
| 740 | */ |
||
| 741 | public function setData(int|float|array $data) { |
||
| 742 | if (is_array($data) && !is_array($data[0])) { |
||
| 743 | for ($i = 0; $i < $this->col; ++$i) { |
||
| 744 | $this->data[$i] = $data[$i]; |
||
| 745 | } |
||
| 746 | } |
||
| 747 | if (is_numeric($data)) { |
||
| 748 | for ($i = 0; $i < $this->col; ++$i) { |
||
| 749 | $this->data[$i] = $data; |
||
| 750 | } |
||
| 751 | } |
||
| 752 | } |
||
| 753 | |||
| 754 | /** |
||
| 755 | * get the size of vector |
||
| 756 | * @return int |
||
| 757 | */ |
||
| 758 | public function getSize(): int { |
||
| 759 | return $this->col; |
||
| 760 | } |
||
| 761 | |||
| 762 | public function getDtype() { |
||
| 763 | return $this->dtype; |
||
| 764 | } |
||
| 765 | |||
| 766 | public function asArray() { |
||
| 772 | } |
||
| 773 | |||
| 774 | public function printVector() { |
||
| 775 | echo __CLASS__ . PHP_EOL; |
||
| 776 | for ($j = 0; $j < $this->col; ++$j) { |
||
| 777 | printf('%lf ', $this->data[$j]); |
||
| 778 | } |
||
| 779 | echo PHP_EOL; |
||
| 780 | } |
||
| 781 | |||
| 782 | public function __toString() { |
||
| 783 | return (string) $this->printVector(); |
||
| 784 | } |
||
| 785 | |||
| 786 | protected function __construct(public int $col, int $dtype = self::DOUBLE) { |
||
| 787 | if ($this->col < 1) { |
||
| 788 | throw new invalidArgumentException('* To create Numphp/Vector col must be greater than 0!, Op Failed! * '); |
||
| 789 | } |
||
| 790 | parent::__construct($this->col, $dtype); |
||
| 791 | return $this; |
||
| 792 | } |
||
| 793 | |||
| 794 | } |
||
| 795 |
