private function EigenvalueDecomposition::hqr2 in Loft Data Grids 6.2
Same name and namespace in other branches
- 7.2 vendor/phpoffice/phpexcel/Classes/PHPExcel/Shared/JAMA/EigenvalueDecomposition.php \EigenvalueDecomposition::hqr2()
* Nonsymmetric reduction from Hessenberg to real Schur form. * * Code is derived from the Algol procedure hqr2, * by Martin and Wilkinson, Handbook for Auto. Comp., * Vol.ii-Linear Algebra, and the corresponding * Fortran subroutine in EISPACK. * * @access private
1 call to EigenvalueDecomposition::hqr2()
- EigenvalueDecomposition::__construct in vendor/
phpoffice/ phpexcel/ Classes/ PHPExcel/ Shared/ JAMA/ EigenvalueDecomposition.php - * Constructor: Check for symmetry, then construct the eigenvalue decomposition * * @access public *
File
- vendor/
phpoffice/ phpexcel/ Classes/ PHPExcel/ Shared/ JAMA/ EigenvalueDecomposition.php, line 398
Class
- EigenvalueDecomposition
- @package JAMA
Code
private function hqr2() {
// Initialize
$nn = $this->n;
$n = $nn - 1;
$low = 0;
$high = $nn - 1;
$eps = pow(2.0, -52.0);
$exshift = 0.0;
$p = $q = $r = $s = $z = 0;
// Store roots isolated by balanc and compute matrix norm
$norm = 0.0;
for ($i = 0; $i < $nn; ++$i) {
if ($i < $low or $i > $high) {
$this->d[$i] = $this->H[$i][$i];
$this->e[$i] = 0.0;
}
for ($j = max($i - 1, 0); $j < $nn; ++$j) {
$norm = $norm + abs($this->H[$i][$j]);
}
}
// Outer loop over eigenvalue index
$iter = 0;
while ($n >= $low) {
// Look for single small sub-diagonal element
$l = $n;
while ($l > $low) {
$s = abs($this->H[$l - 1][$l - 1]) + abs($this->H[$l][$l]);
if ($s == 0.0) {
$s = $norm;
}
if (abs($this->H[$l][$l - 1]) < $eps * $s) {
break;
}
--$l;
}
// Check for convergence
// One root found
if ($l == $n) {
$this->H[$n][$n] = $this->H[$n][$n] + $exshift;
$this->d[$n] = $this->H[$n][$n];
$this->e[$n] = 0.0;
--$n;
$iter = 0;
// Two roots found
}
else {
if ($l == $n - 1) {
$w = $this->H[$n][$n - 1] * $this->H[$n - 1][$n];
$p = ($this->H[$n - 1][$n - 1] - $this->H[$n][$n]) / 2.0;
$q = $p * $p + $w;
$z = sqrt(abs($q));
$this->H[$n][$n] = $this->H[$n][$n] + $exshift;
$this->H[$n - 1][$n - 1] = $this->H[$n - 1][$n - 1] + $exshift;
$x = $this->H[$n][$n];
// Real pair
if ($q >= 0) {
if ($p >= 0) {
$z = $p + $z;
}
else {
$z = $p - $z;
}
$this->d[$n - 1] = $x + $z;
$this->d[$n] = $this->d[$n - 1];
if ($z != 0.0) {
$this->d[$n] = $x - $w / $z;
}
$this->e[$n - 1] = 0.0;
$this->e[$n] = 0.0;
$x = $this->H[$n][$n - 1];
$s = abs($x) + abs($z);
$p = $x / $s;
$q = $z / $s;
$r = sqrt($p * $p + $q * $q);
$p = $p / $r;
$q = $q / $r;
// Row modification
for ($j = $n - 1; $j < $nn; ++$j) {
$z = $this->H[$n - 1][$j];
$this->H[$n - 1][$j] = $q * $z + $p * $this->H[$n][$j];
$this->H[$n][$j] = $q * $this->H[$n][$j] - $p * $z;
}
// Column modification
for ($i = 0; $i <= n; ++$i) {
$z = $this->H[$i][$n - 1];
$this->H[$i][$n - 1] = $q * $z + $p * $this->H[$i][$n];
$this->H[$i][$n] = $q * $this->H[$i][$n] - $p * $z;
}
// Accumulate transformations
for ($i = $low; $i <= $high; ++$i) {
$z = $this->V[$i][$n - 1];
$this->V[$i][$n - 1] = $q * $z + $p * $this->V[$i][$n];
$this->V[$i][$n] = $q * $this->V[$i][$n] - $p * $z;
}
// Complex pair
}
else {
$this->d[$n - 1] = $x + $p;
$this->d[$n] = $x + $p;
$this->e[$n - 1] = $z;
$this->e[$n] = -$z;
}
$n = $n - 2;
$iter = 0;
// No convergence yet
}
else {
// Form shift
$x = $this->H[$n][$n];
$y = 0.0;
$w = 0.0;
if ($l < $n) {
$y = $this->H[$n - 1][$n - 1];
$w = $this->H[$n][$n - 1] * $this->H[$n - 1][$n];
}
// Wilkinson's original ad hoc shift
if ($iter == 10) {
$exshift += $x;
for ($i = $low; $i <= $n; ++$i) {
$this->H[$i][$i] -= $x;
}
$s = abs($this->H[$n][$n - 1]) + abs($this->H[$n - 1][$n - 2]);
$x = $y = 0.75 * $s;
$w = -0.4375 * $s * $s;
}
// MATLAB's new ad hoc shift
if ($iter == 30) {
$s = ($y - $x) / 2.0;
$s = $s * $s + $w;
if ($s > 0) {
$s = sqrt($s);
if ($y < $x) {
$s = -$s;
}
$s = $x - $w / (($y - $x) / 2.0 + $s);
for ($i = $low; $i <= $n; ++$i) {
$this->H[$i][$i] -= $s;
}
$exshift += $s;
$x = $y = $w = 0.964;
}
}
// Could check iteration count here.
$iter = $iter + 1;
// Look for two consecutive small sub-diagonal elements
$m = $n - 2;
while ($m >= $l) {
$z = $this->H[$m][$m];
$r = $x - $z;
$s = $y - $z;
$p = ($r * $s - $w) / $this->H[$m + 1][$m] + $this->H[$m][$m + 1];
$q = $this->H[$m + 1][$m + 1] - $z - $r - $s;
$r = $this->H[$m + 2][$m + 1];
$s = abs($p) + abs($q) + abs($r);
$p = $p / $s;
$q = $q / $s;
$r = $r / $s;
if ($m == $l) {
break;
}
if (abs($this->H[$m][$m - 1]) * (abs($q) + abs($r)) < $eps * (abs($p) * (abs($this->H[$m - 1][$m - 1]) + abs($z) + abs($this->H[$m + 1][$m + 1])))) {
break;
}
--$m;
}
for ($i = $m + 2; $i <= $n; ++$i) {
$this->H[$i][$i - 2] = 0.0;
if ($i > $m + 2) {
$this->H[$i][$i - 3] = 0.0;
}
}
// Double QR step involving rows l:n and columns m:n
for ($k = $m; $k <= $n - 1; ++$k) {
$notlast = $k != $n - 1;
if ($k != $m) {
$p = $this->H[$k][$k - 1];
$q = $this->H[$k + 1][$k - 1];
$r = $notlast ? $this->H[$k + 2][$k - 1] : 0.0;
$x = abs($p) + abs($q) + abs($r);
if ($x != 0.0) {
$p = $p / $x;
$q = $q / $x;
$r = $r / $x;
}
}
if ($x == 0.0) {
break;
}
$s = sqrt($p * $p + $q * $q + $r * $r);
if ($p < 0) {
$s = -$s;
}
if ($s != 0) {
if ($k != $m) {
$this->H[$k][$k - 1] = -$s * $x;
}
elseif ($l != $m) {
$this->H[$k][$k - 1] = -$this->H[$k][$k - 1];
}
$p = $p + $s;
$x = $p / $s;
$y = $q / $s;
$z = $r / $s;
$q = $q / $p;
$r = $r / $p;
// Row modification
for ($j = $k; $j < $nn; ++$j) {
$p = $this->H[$k][$j] + $q * $this->H[$k + 1][$j];
if ($notlast) {
$p = $p + $r * $this->H[$k + 2][$j];
$this->H[$k + 2][$j] = $this->H[$k + 2][$j] - $p * $z;
}
$this->H[$k][$j] = $this->H[$k][$j] - $p * $x;
$this->H[$k + 1][$j] = $this->H[$k + 1][$j] - $p * $y;
}
// Column modification
for ($i = 0; $i <= min($n, $k + 3); ++$i) {
$p = $x * $this->H[$i][$k] + $y * $this->H[$i][$k + 1];
if ($notlast) {
$p = $p + $z * $this->H[$i][$k + 2];
$this->H[$i][$k + 2] = $this->H[$i][$k + 2] - $p * $r;
}
$this->H[$i][$k] = $this->H[$i][$k] - $p;
$this->H[$i][$k + 1] = $this->H[$i][$k + 1] - $p * $q;
}
// Accumulate transformations
for ($i = $low; $i <= $high; ++$i) {
$p = $x * $this->V[$i][$k] + $y * $this->V[$i][$k + 1];
if ($notlast) {
$p = $p + $z * $this->V[$i][$k + 2];
$this->V[$i][$k + 2] = $this->V[$i][$k + 2] - $p * $r;
}
$this->V[$i][$k] = $this->V[$i][$k] - $p;
$this->V[$i][$k + 1] = $this->V[$i][$k + 1] - $p * $q;
}
}
// ($s != 0)
}
// k loop
}
}
// check convergence
}
// while ($n >= $low)
// Backsubstitute to find vectors of upper triangular form
if ($norm == 0.0) {
return;
}
for ($n = $nn - 1; $n >= 0; --$n) {
$p = $this->d[$n];
$q = $this->e[$n];
// Real vector
if ($q == 0) {
$l = $n;
$this->H[$n][$n] = 1.0;
for ($i = $n - 1; $i >= 0; --$i) {
$w = $this->H[$i][$i] - $p;
$r = 0.0;
for ($j = $l; $j <= $n; ++$j) {
$r = $r + $this->H[$i][$j] * $this->H[$j][$n];
}
if ($this->e[$i] < 0.0) {
$z = $w;
$s = $r;
}
else {
$l = $i;
if ($this->e[$i] == 0.0) {
if ($w != 0.0) {
$this->H[$i][$n] = -$r / $w;
}
else {
$this->H[$i][$n] = -$r / ($eps * $norm);
}
// Solve real equations
}
else {
$x = $this->H[$i][$i + 1];
$y = $this->H[$i + 1][$i];
$q = ($this->d[$i] - $p) * ($this->d[$i] - $p) + $this->e[$i] * $this->e[$i];
$t = ($x * $s - $z * $r) / $q;
$this->H[$i][$n] = $t;
if (abs($x) > abs($z)) {
$this->H[$i + 1][$n] = (-$r - $w * $t) / $x;
}
else {
$this->H[$i + 1][$n] = (-$s - $y * $t) / $z;
}
}
// Overflow control
$t = abs($this->H[$i][$n]);
if ($eps * $t * $t > 1) {
for ($j = $i; $j <= $n; ++$j) {
$this->H[$j][$n] = $this->H[$j][$n] / $t;
}
}
}
}
// Complex vector
}
else {
if ($q < 0) {
$l = $n - 1;
// Last vector component imaginary so matrix is triangular
if (abs($this->H[$n][$n - 1]) > abs($this->H[$n - 1][$n])) {
$this->H[$n - 1][$n - 1] = $q / $this->H[$n][$n - 1];
$this->H[$n - 1][$n] = -($this->H[$n][$n] - $p) / $this->H[$n][$n - 1];
}
else {
$this
->cdiv(0.0, -$this->H[$n - 1][$n], $this->H[$n - 1][$n - 1] - $p, $q);
$this->H[$n - 1][$n - 1] = $this->cdivr;
$this->H[$n - 1][$n] = $this->cdivi;
}
$this->H[$n][$n - 1] = 0.0;
$this->H[$n][$n] = 1.0;
for ($i = $n - 2; $i >= 0; --$i) {
// double ra,sa,vr,vi;
$ra = 0.0;
$sa = 0.0;
for ($j = $l; $j <= $n; ++$j) {
$ra = $ra + $this->H[$i][$j] * $this->H[$j][$n - 1];
$sa = $sa + $this->H[$i][$j] * $this->H[$j][$n];
}
$w = $this->H[$i][$i] - $p;
if ($this->e[$i] < 0.0) {
$z = $w;
$r = $ra;
$s = $sa;
}
else {
$l = $i;
if ($this->e[$i] == 0) {
$this
->cdiv(-$ra, -$sa, $w, $q);
$this->H[$i][$n - 1] = $this->cdivr;
$this->H[$i][$n] = $this->cdivi;
}
else {
// Solve complex equations
$x = $this->H[$i][$i + 1];
$y = $this->H[$i + 1][$i];
$vr = ($this->d[$i] - $p) * ($this->d[$i] - $p) + $this->e[$i] * $this->e[$i] - $q * $q;
$vi = ($this->d[$i] - $p) * 2.0 * $q;
if ($vr == 0.0 & $vi == 0.0) {
$vr = $eps * $norm * (abs($w) + abs($q) + abs($x) + abs($y) + abs($z));
}
$this
->cdiv($x * $r - $z * $ra + $q * $sa, $x * $s - $z * $sa - $q * $ra, $vr, $vi);
$this->H[$i][$n - 1] = $this->cdivr;
$this->H[$i][$n] = $this->cdivi;
if (abs($x) > abs($z) + abs($q)) {
$this->H[$i + 1][$n - 1] = (-$ra - $w * $this->H[$i][$n - 1] + $q * $this->H[$i][$n]) / $x;
$this->H[$i + 1][$n] = (-$sa - $w * $this->H[$i][$n] - $q * $this->H[$i][$n - 1]) / $x;
}
else {
$this
->cdiv(-$r - $y * $this->H[$i][$n - 1], -$s - $y * $this->H[$i][$n], $z, $q);
$this->H[$i + 1][$n - 1] = $this->cdivr;
$this->H[$i + 1][$n] = $this->cdivi;
}
}
// Overflow control
$t = max(abs($this->H[$i][$n - 1]), abs($this->H[$i][$n]));
if ($eps * $t * $t > 1) {
for ($j = $i; $j <= $n; ++$j) {
$this->H[$j][$n - 1] = $this->H[$j][$n - 1] / $t;
$this->H[$j][$n] = $this->H[$j][$n] / $t;
}
}
}
// end else
}
// end for
}
}
// end else for complex case
}
// end for
// Vectors of isolated roots
for ($i = 0; $i < $nn; ++$i) {
if ($i < $low | $i > $high) {
for ($j = $i; $j < $nn; ++$j) {
$this->V[$i][$j] = $this->H[$i][$j];
}
}
}
// Back transformation to get eigenvectors of original matrix
for ($j = $nn - 1; $j >= $low; --$j) {
for ($i = $low; $i <= $high; ++$i) {
$z = 0.0;
for ($k = $low; $k <= min($j, $high); ++$k) {
$z = $z + $this->V[$i][$k] * $this->H[$k][$j];
}
$this->V[$i][$j] = $z;
}
}
}