Total Complexity | 50 |
Total Lines | 315 |
Duplicated Lines | 0 % |
Changes | 1 | ||
Bugs | 0 | Features | 0 |
Complex classes like Matrix 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 Matrix, and based on these observations, apply Extract Interface, too.
1 | <?php |
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11 | class Matrix |
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12 | { |
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13 | /** |
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14 | * @var array |
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15 | */ |
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16 | private $matrix = []; |
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17 | |||
18 | /** |
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19 | * @var int |
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20 | */ |
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21 | private $rows; |
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22 | |||
23 | /** |
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24 | * @var int |
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25 | */ |
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26 | private $columns; |
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27 | |||
28 | /** |
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29 | * @var float |
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30 | */ |
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31 | private $determinant; |
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32 | |||
33 | /** |
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34 | * @throws InvalidArgumentException |
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35 | */ |
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36 | public function __construct(array $matrix, bool $validate = true) |
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37 | { |
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38 | // When a row vector is given |
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39 | if (!is_array($matrix[0])) { |
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40 | $this->rows = 1; |
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41 | $this->columns = count($matrix); |
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42 | $matrix = [$matrix]; |
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43 | } else { |
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44 | $this->rows = count($matrix); |
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45 | $this->columns = count($matrix[0]); |
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46 | } |
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47 | |||
48 | if ($validate) { |
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49 | for ($i = 0; $i < $this->rows; ++$i) { |
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50 | if (count($matrix[$i]) !== $this->columns) { |
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51 | throw new InvalidArgumentException('Matrix dimensions did not match'); |
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52 | } |
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53 | } |
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54 | } |
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55 | |||
56 | $this->matrix = $matrix; |
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57 | } |
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58 | |||
59 | public static function fromFlatArray(array $array): self |
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60 | { |
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61 | $matrix = []; |
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62 | foreach ($array as $value) { |
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63 | $matrix[] = [$value]; |
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64 | } |
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65 | |||
66 | return new self($matrix); |
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67 | } |
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68 | |||
69 | public function toArray(): array |
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70 | { |
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71 | return $this->matrix; |
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72 | } |
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73 | |||
74 | public function toScalar(): float |
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75 | { |
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76 | return $this->matrix[0][0]; |
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77 | } |
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78 | |||
79 | public function getRows(): int |
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80 | { |
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81 | return $this->rows; |
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82 | } |
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83 | |||
84 | public function getColumns(): int |
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85 | { |
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86 | return $this->columns; |
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87 | } |
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88 | |||
89 | /** |
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90 | * @throws MatrixException |
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91 | */ |
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92 | public function getColumnValues(int $column): array |
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93 | { |
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94 | if ($column >= $this->columns) { |
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95 | throw new MatrixException('Column out of range'); |
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96 | } |
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97 | |||
98 | return array_column($this->matrix, $column); |
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99 | } |
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100 | |||
101 | /** |
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102 | * @return float|int |
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103 | * |
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104 | * @throws MatrixException |
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105 | */ |
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106 | public function getDeterminant() |
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107 | { |
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108 | if ($this->determinant !== null) { |
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109 | return $this->determinant; |
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110 | } |
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111 | |||
112 | if (!$this->isSquare()) { |
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113 | throw new MatrixException('Matrix is not square matrix'); |
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114 | } |
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115 | |||
116 | $lu = new LUDecomposition($this); |
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117 | |||
118 | return $this->determinant = $lu->det(); |
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119 | } |
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120 | |||
121 | public function isSquare(): bool |
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122 | { |
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123 | return $this->columns === $this->rows; |
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124 | } |
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125 | |||
126 | public function transpose(): self |
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127 | { |
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128 | if ($this->rows === 1) { |
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129 | $matrix = array_map(function ($el) { |
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130 | return [$el]; |
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131 | }, $this->matrix[0]); |
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132 | } else { |
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133 | $matrix = array_map(null, ...$this->matrix); |
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134 | } |
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135 | |||
136 | return new self($matrix, false); |
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137 | } |
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138 | |||
139 | public function multiply(self $matrix): self |
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140 | { |
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141 | if ($this->columns !== $matrix->getRows()) { |
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142 | throw new InvalidArgumentException('Inconsistent matrix supplied'); |
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143 | } |
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144 | |||
145 | $array1 = $this->toArray(); |
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146 | $array2 = $matrix->toArray(); |
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147 | $colCount = $matrix->columns; |
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148 | |||
149 | /* |
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150 | - To speed-up multiplication, we need to avoid use of array index operator [ ] as much as possible( See #255 for details) |
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151 | - A combination of "foreach" and "array_column" works much faster then accessing the array via index operator |
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152 | */ |
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153 | $product = []; |
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154 | foreach ($array1 as $row => $rowData) { |
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155 | for ($col = 0; $col < $colCount; ++$col) { |
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156 | $columnData = array_column($array2, $col); |
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157 | $sum = 0; |
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158 | foreach ($rowData as $key => $valueData) { |
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159 | $sum += $valueData * $columnData[$key]; |
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160 | } |
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161 | |||
162 | $product[$row][$col] = $sum; |
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163 | } |
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164 | } |
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165 | |||
166 | return new self($product, false); |
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167 | } |
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168 | |||
169 | /** |
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170 | * @param float|int $value |
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171 | */ |
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172 | public function divideByScalar($value): self |
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173 | { |
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174 | $newMatrix = []; |
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175 | for ($i = 0; $i < $this->rows; ++$i) { |
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176 | for ($j = 0; $j < $this->columns; ++$j) { |
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177 | $newMatrix[$i][$j] = $this->matrix[$i][$j] / $value; |
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178 | } |
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179 | } |
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180 | |||
181 | return new self($newMatrix, false); |
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182 | } |
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183 | |||
184 | /** |
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185 | * @param float|int $value |
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186 | */ |
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187 | public function multiplyByScalar($value): self |
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197 | } |
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198 | |||
199 | /** |
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200 | * Element-wise addition of the matrix with another one |
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201 | */ |
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202 | public function add(self $other): self |
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203 | { |
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204 | return $this->sum($other); |
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205 | } |
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206 | |||
207 | /** |
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208 | * Element-wise subtracting of another matrix from this one |
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209 | */ |
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210 | public function subtract(self $other): self |
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211 | { |
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212 | return $this->sum($other, -1); |
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213 | } |
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214 | |||
215 | public function inverse(): self |
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216 | { |
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217 | if (!$this->isSquare()) { |
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218 | throw new MatrixException('Matrix is not square matrix'); |
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219 | } |
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220 | |||
221 | $LU = new LUDecomposition($this); |
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222 | $identity = $this->getIdentity(); |
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223 | $inverse = $LU->solve($identity); |
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224 | |||
225 | return new self($inverse, false); |
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226 | } |
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227 | |||
228 | public function crossOut(int $row, int $column): self |
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229 | { |
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230 | $newMatrix = []; |
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231 | $r = 0; |
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232 | for ($i = 0; $i < $this->rows; ++$i) { |
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233 | $c = 0; |
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234 | if ($row != $i) { |
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235 | for ($j = 0; $j < $this->columns; ++$j) { |
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236 | if ($column != $j) { |
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237 | $newMatrix[$r][$c] = $this->matrix[$i][$j]; |
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238 | ++$c; |
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239 | } |
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240 | } |
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241 | |||
242 | ++$r; |
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243 | } |
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244 | } |
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245 | |||
246 | return new self($newMatrix, false); |
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247 | } |
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248 | |||
249 | public function isSingular(): bool |
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250 | { |
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251 | return $this->getDeterminant() == 0; |
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252 | } |
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253 | |||
254 | /** |
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255 | * Frobenius norm (Hilbert–Schmidt norm, Euclidean norm) (‖A‖F) |
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256 | * Square root of the sum of the square of all elements. |
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257 | * |
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258 | * https://en.wikipedia.org/wiki/Matrix_norm#Frobenius_norm |
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259 | * |
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260 | * _____________ |
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261 | * /ᵐ ⁿ |
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262 | * ‖A‖F = √ Σ Σ |aᵢⱼ|² |
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263 | * ᵢ₌₁ ᵢ₌₁ |
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264 | */ |
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265 | public function frobeniusNorm(): float |
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275 | } |
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276 | |||
277 | /** |
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278 | * Returns the transpose of given array |
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279 | */ |
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280 | public static function transposeArray(array $array): array |
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283 | } |
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284 | |||
285 | /** |
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286 | * Returns the dot product of two arrays<br> |
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287 | * Matrix::dot(x, y) ==> x.y' |
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288 | */ |
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289 | public static function dot(array $array1, array $array2): array |
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295 | } |
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296 | |||
297 | /** |
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298 | * Element-wise addition or substraction depending on the given sign parameter |
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299 | */ |
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300 | private function sum(self $other, int $sign = 1): self |
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301 | { |
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302 | $a1 = $this->toArray(); |
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303 | $a2 = $other->toArray(); |
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304 | |||
305 | $newMatrix = []; |
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306 | for ($i = 0; $i < $this->rows; ++$i) { |
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307 | for ($k = 0; $k < $this->columns; ++$k) { |
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308 | $newMatrix[$i][$k] = $a1[$i][$k] + $sign * $a2[$i][$k]; |
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309 | } |
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310 | } |
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311 | |||
312 | return new self($newMatrix, false); |
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313 | } |
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314 | |||
315 | /** |
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316 | * Returns diagonal identity matrix of the same size of this matrix |
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317 | */ |
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318 | private function getIdentity(): self |
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326 | } |
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327 | } |
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328 |