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Direktori : /home/silvzytp/crm-ind-code/vendor/markbaker/matrix/classes/src/Decomposition/ |
Current File : //home/silvzytp/crm-ind-code/vendor/markbaker/matrix/classes/src/Decomposition/LU.php |
<?php namespace Matrix\Decomposition; use Matrix\Exception; use Matrix\Matrix; class LU { private $luMatrix; private $rows; private $columns; private $pivot = []; public function __construct(Matrix $matrix) { $this->luMatrix = $matrix->toArray(); $this->rows = $matrix->rows; $this->columns = $matrix->columns; $this->buildPivot(); } /** * Get lower triangular factor. * * @return Matrix Lower triangular factor */ public function getL(): Matrix { $lower = []; $columns = min($this->rows, $this->columns); for ($row = 0; $row < $this->rows; ++$row) { for ($column = 0; $column < $columns; ++$column) { if ($row > $column) { $lower[$row][$column] = $this->luMatrix[$row][$column]; } elseif ($row === $column) { $lower[$row][$column] = 1.0; } else { $lower[$row][$column] = 0.0; } } } return new Matrix($lower); } /** * Get upper triangular factor. * * @return Matrix Upper triangular factor */ public function getU(): Matrix { $upper = []; $rows = min($this->rows, $this->columns); for ($row = 0; $row < $rows; ++$row) { for ($column = 0; $column < $this->columns; ++$column) { if ($row <= $column) { $upper[$row][$column] = $this->luMatrix[$row][$column]; } else { $upper[$row][$column] = 0.0; } } } return new Matrix($upper); } /** * Return pivot permutation vector. * * @return Matrix Pivot matrix */ public function getP(): Matrix { $pMatrix = []; $pivots = $this->pivot; $pivotCount = count($pivots); foreach ($pivots as $row => $pivot) { $pMatrix[$row] = array_fill(0, $pivotCount, 0); $pMatrix[$row][$pivot] = 1; } return new Matrix($pMatrix); } /** * Return pivot permutation vector. * * @return array Pivot vector */ public function getPivot(): array { return $this->pivot; } /** * Is the matrix nonsingular? * * @return bool true if U, and hence A, is nonsingular */ public function isNonsingular(): bool { for ($diagonal = 0; $diagonal < $this->columns; ++$diagonal) { if ($this->luMatrix[$diagonal][$diagonal] === 0.0) { return false; } } return true; } private function buildPivot(): void { for ($row = 0; $row < $this->rows; ++$row) { $this->pivot[$row] = $row; } for ($column = 0; $column < $this->columns; ++$column) { $luColumn = $this->localisedReferenceColumn($column); $this->applyTransformations($column, $luColumn); $pivot = $this->findPivot($column, $luColumn); if ($pivot !== $column) { $this->pivotExchange($pivot, $column); } $this->computeMultipliers($column); unset($luColumn); } } private function localisedReferenceColumn($column): array { $luColumn = []; for ($row = 0; $row < $this->rows; ++$row) { $luColumn[$row] = &$this->luMatrix[$row][$column]; } return $luColumn; } private function applyTransformations($column, array $luColumn): void { for ($row = 0; $row < $this->rows; ++$row) { $luRow = $this->luMatrix[$row]; // Most of the time is spent in the following dot product. $kmax = min($row, $column); $sValue = 0.0; for ($kValue = 0; $kValue < $kmax; ++$kValue) { $sValue += $luRow[$kValue] * $luColumn[$kValue]; } $luRow[$column] = $luColumn[$row] -= $sValue; } } private function findPivot($column, array $luColumn): int { $pivot = $column; for ($row = $column + 1; $row < $this->rows; ++$row) { if (abs($luColumn[$row]) > abs($luColumn[$pivot])) { $pivot = $row; } } return $pivot; } private function pivotExchange($pivot, $column): void { for ($kValue = 0; $kValue < $this->columns; ++$kValue) { $tValue = $this->luMatrix[$pivot][$kValue]; $this->luMatrix[$pivot][$kValue] = $this->luMatrix[$column][$kValue]; $this->luMatrix[$column][$kValue] = $tValue; } $lValue = $this->pivot[$pivot]; $this->pivot[$pivot] = $this->pivot[$column]; $this->pivot[$column] = $lValue; } private function computeMultipliers($diagonal): void { if (($diagonal < $this->rows) && ($this->luMatrix[$diagonal][$diagonal] != 0.0)) { for ($row = $diagonal + 1; $row < $this->rows; ++$row) { $this->luMatrix[$row][$diagonal] /= $this->luMatrix[$diagonal][$diagonal]; } } } private function pivotB(Matrix $B): array { $X = []; foreach ($this->pivot as $rowId) { $row = $B->getRows($rowId + 1)->toArray(); $X[] = array_pop($row); } return $X; } /** * Solve A*X = B. * * @param Matrix $B a Matrix with as many rows as A and any number of columns * * @throws Exception * * @return Matrix X so that L*U*X = B(piv,:) */ public function solve(Matrix $B): Matrix { if ($B->rows !== $this->rows) { throw new Exception('Matrix row dimensions are not equal'); } if ($this->rows !== $this->columns) { throw new Exception('LU solve() only works on square matrices'); } if (!$this->isNonsingular()) { throw new Exception('Can only perform operation on singular matrix'); } // Copy right hand side with pivoting $nx = $B->columns; $X = $this->pivotB($B); // Solve L*Y = B(piv,:) for ($k = 0; $k < $this->columns; ++$k) { for ($i = $k + 1; $i < $this->columns; ++$i) { for ($j = 0; $j < $nx; ++$j) { $X[$i][$j] -= $X[$k][$j] * $this->luMatrix[$i][$k]; } } } // Solve U*X = Y; for ($k = $this->columns - 1; $k >= 0; --$k) { for ($j = 0; $j < $nx; ++$j) { $X[$k][$j] /= $this->luMatrix[$k][$k]; } for ($i = 0; $i < $k; ++$i) { for ($j = 0; $j < $nx; ++$j) { $X[$i][$j] -= $X[$k][$j] * $this->luMatrix[$i][$k]; } } } return new Matrix($X); } }