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<?php
/**
 *      @package JAMA
 *
 *      Class to obtain eigenvalues and eigenvectors of a real matrix.
 *
 *      If A is symmetric, then A = V*D*V' where the eigenvalue matrix D
 *      is diagonal and the eigenvector matrix V is orthogonal (i.e.
 *      A = V.times(D.times(V.transpose())) and V.times(V.transpose())
 *      equals the identity matrix).
 *
 *      If A is not symmetric, then the eigenvalue matrix D is block diagonal
 *      with the real eigenvalues in 1-by-1 blocks and any complex eigenvalues,
 *      lambda + i*mu, in 2-by-2 blocks, [lambda, mu; -mu, lambda].  The
 *      columns of V represent the eigenvectors in the sense that A*V = V*D,
 *      i.e. A.times(V) equals V.times(D).  The matrix V may be badly
 *      conditioned, or even singular, so the validity of the equation
 *      A = V*D*inverse(V) depends upon V.cond().
 *
 *      @author  Paul Meagher
 *      @license PHP v3.0
 *      @version 1.1
 */
class EigenvalueDecomposition {

        /**
         *      Row and column dimension (square matrix).
         *      @var int
         */
        private $n;

        /**
         *      Internal symmetry flag.
         *      @var int
         */
        private $issymmetric;

        /**
         *      Arrays for internal storage of eigenvalues.
         *      @var array
         */
        private $d = array();
        private $e = array();

        /**
         *      Array for internal storage of eigenvectors.
         *      @var array
         */
        private $V = array();

        /**
        *       Array for internal storage of nonsymmetric Hessenberg form.
        *       @var array
        */
        private $H = array();

        /**
        *       Working storage for nonsymmetric algorithm.
        *       @var array
        */
        private $ort;

        /**
        *       Used for complex scalar division.
        *       @var float
        */
        private $cdivr;
        private $cdivi;


        /**
         *      Symmetric Householder reduction to tridiagonal form.
         *
         *      @access private
         */
        private function tred2 () {
                //  This is derived from the Algol procedures tred2 by
                //  Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
                //  Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
                //  Fortran subroutine in EISPACK.
                $this->d = $this->V[$this->n-1];
                // Householder reduction to tridiagonal form.
                for ($i = $this->n-1; $i > 0; --$i) {
                        $i_ = $i -1;
                        // Scale to avoid under/overflow.
                        $h = $scale = 0.0;
                        $scale += array_sum(array_map(abs, $this->d));
                        if ($scale == 0.0) {
                                $this->e[$i] = $this->d[$i_];
                                $this->d = array_slice($this->V[$i_], 0, $i_);
                                for ($j = 0; $j < $i; ++$j) {
                                        $this->V[$j][$i] = $this->V[$i][$j] = 0.0;
                                }
                        } else {
                                // Generate Householder vector.
                                for ($k = 0; $k < $i; ++$k) {
                                        $this->d[$k] /= $scale;
                                        $h += pow($this->d[$k], 2);
                                }
                                $f = $this->d[$i_];
                                $g = sqrt($h);
                                if ($f > 0) {
                                        $g = -$g;
                                }
                                $this->e[$i] = $scale * $g;
                                $h = $h - $f * $g;
                                $this->d[$i_] = $f - $g;
                                for ($j = 0; $j < $i; ++$j) {
                                        $this->e[$j] = 0.0;
                                }
                                // Apply similarity transformation to remaining columns.
                                for ($j = 0; $j < $i; ++$j) {
                                        $f = $this->d[$j];
                                        $this->V[$j][$i] = $f;
                                        $g = $this->e[$j] + $this->V[$j][$j] * $f;
                                        for ($k = $j+1; $k <= $i_; ++$k) {
                                                $g += $this->V[$k][$j] * $this->d[$k];
                                                $this->e[$k] += $this->V[$k][$j] * $f;
                                        }
                                        $this->e[$j] = $g;
                                }
                                $f = 0.0;
                                for ($j = 0; $j < $i; ++$j) {
                                        $this->e[$j] /= $h;
                                        $f += $this->e[$j] * $this->d[$j];
                                }
                                $hh = $f / (2 * $h);
                                for ($j=0; $j < $i; ++$j) {
                                        $this->e[$j] -= $hh * $this->d[$j];
                                }
                                for ($j = 0; $j < $i; ++$j) {
                                        $f = $this->d[$j];
                                        $g = $this->e[$j];
                                        for ($k = $j; $k <= $i_; ++$k) {
                                                $this->V[$k][$j] -= ($f * $this->e[$k] + $g * $this->d[$k]);
                                        }
                                        $this->d[$j] = $this->V[$i-1][$j];
                                        $this->V[$i][$j] = 0.0;
                                }
                        }
                        $this->d[$i] = $h;
                }

                // Accumulate transformations.
                for ($i = 0; $i < $this->n-1; ++$i) {
                        $this->V[$this->n-1][$i] = $this->V[$i][$i];
                        $this->V[$i][$i] = 1.0;
                        $h = $this->d[$i+1];
                        if ($h != 0.0) {
                                for ($k = 0; $k <= $i; ++$k) {
                                        $this->d[$k] = $this->V[$k][$i+1] / $h;
                                }
                                for ($j = 0; $j <= $i; ++$j) {
                                        $g = 0.0;
                                        for ($k = 0; $k <= $i; ++$k) {
                                                $g += $this->V[$k][$i+1] * $this->V[$k][$j];
                                        }
                                        for ($k = 0; $k <= $i; ++$k) {
                                                $this->V[$k][$j] -= $g * $this->d[$k];
                                        }
                                }
                        }
                        for ($k = 0; $k <= $i; ++$k) {
                                $this->V[$k][$i+1] = 0.0;
                        }
                }

                $this->d = $this->V[$this->n-1];
                $this->V[$this->n-1] = array_fill(0, $j, 0.0);
                $this->V[$this->n-1][$this->n-1] = 1.0;
                $this->e[0] = 0.0;
        }


        /**
         *      Symmetric tridiagonal QL algorithm.
         *
         *      This is derived from the Algol procedures tql2, by
         *      Bowdler, Martin, Reinsch, and Wilkinson, Handbook for
         *      Auto. Comp., Vol.ii-Linear Algebra, and the corresponding
         *      Fortran subroutine in EISPACK.
         *
         *      @access private
         */
        private function tql2() {
                for ($i = 1; $i < $this->n; ++$i) {
                        $this->e[$i-1] = $this->e[$i];
                }
                $this->e[$this->n-1] = 0.0;
                $f = 0.0;
                $tst1 = 0.0;
                $eps  = pow(2.0,-52.0);

                for ($l = 0; $l < $this->n; ++$l) {
                        // Find small subdiagonal element
                        $tst1 = max($tst1, abs($this->d[$l]) + abs($this->e[$l]));
                        $m = $l;
                        while ($m < $this->n) {
                                if (abs($this->e[$m]) <= $eps * $tst1)
                                        break;
                                ++$m;
                        }
                        // If m == l, $this->d[l] is an eigenvalue,
                        // otherwise, iterate.
                        if ($m > $l) {
                                $iter = 0;
                                do {
                                        // Could check iteration count here.
                                        $iter += 1;
                                        // Compute implicit shift
                                        $g = $this->d[$l];
                                        $p = ($this->d[$l+1] - $g) / (2.0 * $this->e[$l]);
                                        $r = hypo($p, 1.0);
                                        if ($p < 0)
                                                $r *= -1;
                                        $this->d[$l] = $this->e[$l] / ($p + $r);
                                        $this->d[$l+1] = $this->e[$l] * ($p + $r);
                                        $dl1 = $this->d[$l+1];
                                        $h = $g - $this->d[$l];
                                        for ($i = $l + 2; $i < $this->n; ++$i)
                                                $this->d[$i] -= $h;
                                        $f += $h;
                                        // Implicit QL transformation.
                                        $p = $this->d[$m];
                                        $c = 1.0;
                                        $c2 = $c3 = $c;
                                        $el1 = $this->e[$l + 1];
                                        $s = $s2 = 0.0;
                                        for ($i = $m-1; $i >= $l; --$i) {
                                                $c3 = $c2;
                                                $c2 = $c;
                                                $s2 = $s;
                                                $g  = $c * $this->e[$i];
                                                $h  = $c * $p;
                                                $r  = hypo($p, $this->e[$i]);
                                                $this->e[$i+1] = $s * $r;
                                                $s = $this->e[$i] / $r;
                                                $c = $p / $r;
                                                $p = $c * $this->d[$i] - $s * $g;
                                                $this->d[$i+1] = $h + $s * ($c * $g + $s * $this->d[$i]);
                                                // Accumulate transformation.
                                                for ($k = 0; $k < $this->n; ++$k) {
                                                        $h = $this->V[$k][$i+1];
                                                        $this->V[$k][$i+1] = $s * $this->V[$k][$i] + $c * $h;
                                                        $this->V[$k][$i] = $c * $this->V[$k][$i] - $s * $h;
                                                }
                                        }
                                        $p = -$s * $s2 * $c3 * $el1 * $this->e[$l] / $dl1;
                                        $this->e[$l] = $s * $p;
                                        $this->d[$l] = $c * $p;
                                // Check for convergence.
                                } while (abs($this->e[$l]) > $eps * $tst1);
                        }
                        $this->d[$l] = $this->d[$l] + $f;
                        $this->e[$l] = 0.0;
                }

                // Sort eigenvalues and corresponding vectors.
                for ($i = 0; $i < $this->n - 1; ++$i) {
                        $k = $i;
                        $p = $this->d[$i];
                        for ($j = $i+1; $j < $this->n; ++$j) {
                                if ($this->d[$j] < $p) {
                                        $k = $j;
                                        $p = $this->d[$j];
                                }
                        }
                        if ($k != $i) {
                                $this->d[$k] = $this->d[$i];
                                $this->d[$i] = $p;
                                for ($j = 0; $j < $this->n; ++$j) {
                                        $p = $this->V[$j][$i];
                                        $this->V[$j][$i] = $this->V[$j][$k];
                                        $this->V[$j][$k] = $p;
                                }
                        }
                }
        }


        /**
         *      Nonsymmetric reduction to Hessenberg form.
         *
         *      This is derived from the Algol procedures orthes and ortran,
         *      by Martin and Wilkinson, Handbook for Auto. Comp.,
         *      Vol.ii-Linear Algebra, and the corresponding
         *      Fortran subroutines in EISPACK.
         *
         *      @access private
         */
        private function orthes () {
                $low  = 0;
                $high = $this->n-1;

                for ($m = $low+1; $m <= $high-1; ++$m) {
                        // Scale column.
                        $scale = 0.0;
                        for ($i = $m; $i <= $high; ++$i) {
                                $scale = $scale + abs($this->H[$i][$m-1]);
                        }
                        if ($scale != 0.0) {
                                // Compute Householder transformation.
                                $h = 0.0;
                                for ($i = $high; $i >= $m; --$i) {
                                        $this->ort[$i] = $this->H[$i][$m-1] / $scale;
                                        $h += $this->ort[$i] * $this->ort[$i];
                                }
                                $g = sqrt($h);
                                if ($this->ort[$m] > 0) {
                                        $g *= -1;
                                }
                                $h -= $this->ort[$m] * $g;
                                $this->ort[$m] -= $g;
                                // Apply Householder similarity transformation
                                // H = (I -u * u' / h) * H * (I -u * u') / h)
                                for ($j = $m; $j < $this->n; ++$j) {
                                        $f = 0.0;
                                        for ($i = $high; $i >= $m; --$i) {
                                                $f += $this->ort[$i] * $this->H[$i][$j];
                                        }
                                        $f /= $h;
                                        for ($i = $m; $i <= $high; ++$i) {
                                                $this->H[$i][$j] -= $f * $this->ort[$i];
                                        }
                                }
                                for ($i = 0; $i <= $high; ++$i) {
                                        $f = 0.0;
                                        for ($j = $high; $j >= $m; --$j) {
                                                $f += $this->ort[$j] * $this->H[$i][$j];
                                        }
                                        $f = $f / $h;
                                        for ($j = $m; $j <= $high; ++$j) {
                                                $this->H[$i][$j] -= $f * $this->ort[$j];
                                        }
                                }
                                $this->ort[$m] = $scale * $this->ort[$m];
                                $this->H[$m][$m-1] = $scale * $g;
                        }
                }

                // Accumulate transformations (Algol's ortran).
                for ($i = 0; $i < $this->n; ++$i) {
                        for ($j = 0; $j < $this->n; ++$j) {
                                $this->V[$i][$j] = ($i == $j ? 1.0 : 0.0);
                        }
                }
                for ($m = $high-1; $m >= $low+1; --$m) {
                        if ($this->H[$m][$m-1] != 0.0) {
                                for ($i = $m+1; $i <= $high; ++$i) {
                                        $this->ort[$i] = $this->H[$i][$m-1];
                                }
                                for ($j = $m; $j <= $high; ++$j) {
                                        $g = 0.0;
                                        for ($i = $m; $i <= $high; ++$i) {
                                                $g += $this->ort[$i] * $this->V[$i][$j];
                                        }
                                        // Double division avoids possible underflow
                                        $g = ($g / $this->ort[$m]) / $this->H[$m][$m-1];
                                        for ($i = $m; $i <= $high; ++$i) {
                                                $this->V[$i][$j] += $g * $this->ort[$i];
                                        }
                                }
                        }
                }
        }


        /**
         *      Performs complex division.
         *
         *      @access private
         */
        private function cdiv($xr, $xi, $yr, $yi) {
                if (abs($yr) > abs($yi)) {
                        $r = $yi / $yr;
                        $d = $yr + $r * $yi;
                        $this->cdivr = ($xr + $r * $xi) / $d;
                        $this->cdivi = ($xi - $r * $xr) / $d;
                } else {
                        $r = $yr / $yi;
                        $d = $yi + $r * $yr;
                        $this->cdivr = ($r * $xr + $xi) / $d;
                        $this->cdivi = ($r * $xi - $xr) / $d;
                }
        }


        /**
         *      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
         */
        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;
                        }
                }
        } // end hqr2


        /**
         *      Constructor: Check for symmetry, then construct the eigenvalue decomposition
         *
         *      @access public
         *      @param A  Square matrix
         *      @return Structure to access D and V.
         */
        public function __construct($Arg) {
                $this->A = $Arg->getArray();
                $this->n = $Arg->getColumnDimension();

                $issymmetric = true;
                for ($j = 0; ($j < $this->n) & $issymmetric; ++$j) {
                        for ($i = 0; ($i < $this->n) & $issymmetric; ++$i) {
                                $issymmetric = ($this->A[$i][$j] == $this->A[$j][$i]);
                        }
                }

                if ($issymmetric) {
                        $this->V = $this->A;
                        // Tridiagonalize.
                        $this->tred2();
                        // Diagonalize.
                        $this->tql2();
                } else {
                        $this->H = $this->A;
                        $this->ort = array();
                        // Reduce to Hessenberg form.
                        $this->orthes();
                        // Reduce Hessenberg to real Schur form.
                        $this->hqr2();
                }
        }


        /**
         *      Return the eigenvector matrix
         *
         *      @access public
         *      @return V
         */
        public function getV() {
                return new Matrix($this->V, $this->n, $this->n);
        }


        /**
         *      Return the real parts of the eigenvalues
         *
         *      @access public
         *      @return real(diag(D))
         */
        public function getRealEigenvalues() {
                return $this->d;
        }


        /**
         *      Return the imaginary parts of the eigenvalues
         *
         *      @access public
         *      @return imag(diag(D))
         */
        public function getImagEigenvalues() {
                return $this->e;
        }


        /**
         *      Return the block diagonal eigenvalue matrix
         *
         *      @access public
         *      @return D
         */
        public function getD() {
                for ($i = 0; $i < $this->n; ++$i) {
                        $D[$i] = array_fill(0, $this->n, 0.0);
                        $D[$i][$i] = $this->d[$i];
                        if ($this->e[$i] == 0) {
                                continue;
                        }
                        $o = ($this->e[$i] > 0) ? $i + 1 : $i - 1;
                        $D[$i][$o] = $this->e[$i];
                }
                return new Matrix($D);
        }

}       //      class EigenvalueDecomposition