57 $this->QR = $A->getArrayCopy();
58 $this->m = $A->getRowDimension();
59 $this->
n = $A->getColumnDimension();
65 $nrm =
hypo($nrm, $this->QR[
$i][$k]);
69 if ($this->QR[$k][$k] < 0) {
73 $this->QR[
$i][$k] /= $nrm;
75 $this->QR[$k][$k] += 1.0;
77 for ($j = $k+1; $j <
$this->n; ++$j) {
80 $s += $this->QR[
$i][$k] * $this->QR[
$i][$j];
82 $s = -
$s/$this->QR[$k][$k];
84 $this->QR[
$i][$j] +=
$s * $this->QR[
$i][$k];
88 $this->Rdiag[$k] = -$nrm;
103 if ($this->Rdiag[$j] == 0) {
120 $H[
$i][$j] = $this->QR[
$i][$j];
139 $R[
$i][$j] = $this->QR[
$i][$j];
140 } elseif (
$i == $j) {
141 $R[
$i][$j] = $this->Rdiag[
$i];
157 for ($k = $this->
n-1; $k >= 0; --$k) {
162 for ($j = $k; $j <
$this->n; ++$j) {
163 if ($this->QR[$k][$k] != 0) {
166 $s += $this->QR[
$i][$k] * $Q[
$i][$j];
168 $s = -
$s/$this->QR[$k][$k];
170 $Q[
$i][$j] +=
$s * $this->QR[
$i][$k];
195 if ($B->getRowDimension() ==
$this->m) {
198 $nx = $B->getColumnDimension();
199 $X = $B->getArrayCopy();
202 for ($j = 0; $j < $nx; ++$j) {
205 $s += $this->QR[
$i][$k] * $X[
$i][$j];
207 $s = -
$s/$this->QR[$k][$k];
209 $X[
$i][$j] +=
$s * $this->QR[
$i][$k];
214 for ($k = $this->n-1; $k >= 0; --$k) {
215 for ($j = 0; $j < $nx; ++$j) {
216 $X[$k][$j] /= $this->Rdiag[$k];
218 for (
$i = 0;
$i < $k; ++
$i) {
219 for ($j = 0; $j < $nx; ++$j) {
220 $X[
$i][$j] -= $X[$k][$j]* $this->QR[
$i][$k];
225 return ($X->getMatrix(0, $this->n-1, 0, $nx));
const ArgumentTypeException
__construct($A)
QR Decomposition computed by Householder reflections.
const MatrixDimensionException
if(! $in) print Initializing normalization quick check tables n
isFullRank()
Is the matrix full rank?
const MatrixRankException
Create styles array
The data for the language used.
getQ()
Generate and return the (economy-sized) orthogonal factor.
getR()
Return the upper triangular factor.
const MatrixRankException
getH()
Return the Householder vectors.
solve($B)
Least squares solution of A*X = B.