Use factory instead of instantiating individual Matrix classes.
public function evaluate(array $params)
{
$m = $this->m;
$n = $this->n;
$R = [];
for ($i = 0; $i < $m; $i++) {
for ($j = 0; $j < $n; $j++) {
$func = $this->A[$i][$j];
$R[$i][$j] = $func($params);
}
}
return MatrixFactory::create($R);
}
/**
* Pivotize creates the permutation matrix P for the LU decomposition.
* The permutation matrix is an identity matrix with rows possibly interchanged.
*
* The product PA results in a new matrix whose rows consist of the rows of A
* but no rearranged in the order specified by the permutation matrix P.
*
* Example:
*
* [α₁₁ α₁₂ α₁₃]
* A = [α₂₁ α₂₂ α₂₃]
* [α₃₁ α₃₂ α₃₃]
*
* [0 1 0]
* P = [1 0 0]
* [0 0 1]
*
* [α₂₁ α₂₂ α₂₃] \ rows
* PA = [α₁₁ α₁₂ α₁₃] / interchanged
* [α₃₁ α₃₂ α₃₃]
*
* @return Matrix
*/
protected function pivotize() : Matrix
{
$n = $this->n;
$P = MatrixFactory::identity($n);
$A = $this->A;
// Set initial column max to diagonal element Aᵢᵢ
for ($i = 0; $i < $n; $i++) {
$max = $A[$i][$i];
$row = $i;
// Check for column element below Aᵢᵢ that is bigger
for ($j = $i; $j < $n; $j++) {
if ($A[$j][$i] > $max) {
$max = $A[$j][$i];
$row = $j;
}
}
// Swap rows if a larger column element below Aᵢᵢ was found
if ($i != $row) {
$P = $P->rowInterchange($i, $row);
}
}
return $P;
}
/**
* Outer product (A⨂B)
* https://en.wikipedia.org/wiki/Outer_product
*
* @param Vector $B
*
* @return Matrix
*/
public function outerProduct(Vector $B) : Matrix
{
$m = $this->n;
$n = $B->getN();
$R = [];
for ($i = 0; $i < $m; $i++) {
for ($j = 0; $j < $n; $j++) {
$R[$i][$j] = $this->A[$i] * $B[$j];
}
}
return MatrixFactory::create($R);
}
