tnt/tnt_linalg.h

#ifndef TNT_LINALG_H_
#define TNT_LINALG_H_

#include <algorithm>
// for min(), max() below

#include <cmath>
// for abs(), sqrt()  below


namespace TNT {
namespace Linear_Algebra {

        using namespace std;

template <class Real>
class Cholesky
{
        Matrix<Real> L_;                // lower triangular factor
        int isspd;                              // 1 if matrix to be factored was SPD

public:

        Cholesky();
        Cholesky(const Matrix<Real> &A);
        Matrix<Real> getL() const;
        Vector<Real> solve(const Vector<Real> &B);
        Matrix<Real> solve(const Matrix<Real> &B);
        int is_spd() const;

};

template <class Real>
Cholesky<Real>::Cholesky() : L_(Real(0.0)), isspd(0) {}

template <class Real>
int Cholesky<Real>::is_spd() const
{
        return isspd;
}

template <class Real>
Matrix<Real> Cholesky<Real>::getL() const
{
        return L_;
}

template <class Real>
Cholesky<Real>::Cholesky(const Matrix<Real> &A)
{


        int m = A.num_rows();
        int n = A.num_cols();
        
        isspd = (m == n);

        if (m != n)
        {
                L_ = Matrix<Real>(Real(0.0));
                return;
        }

        L_ = Matrix<Real>(n,n);


      // Main loop.
     for (int j = 0; j < n; j++) 
         {
        Real d = Real(0.0);
        for (int k = 0; k < j; k++) 
                {
            Real s = Real(0.0);
            for (int i = 0; i < k; i++) 
                        {
               s += L_[k][i]*L_[j][i];
            }
            L_[j][k] = s = (A[j][k] - s)/L_[k][k];
            d = d + s*s;
            isspd = isspd && (A[k][j] == A[j][k]); 
         }
         d = A[j][j] - d;
         isspd = isspd && (d > Real(0.0));
         L_[j][j] = sqrt(d > Real(0.0) ? d : Real(0.0));
         for (int k = j+1; k < n; k++) 
                 {
            L_[j][k] = Real(0.0);
         }
        }
}

template <class Real>
Vector<Real> Cholesky<Real>::solve(const Vector<Real> &b)
{
        int n = L_.num_rows();
        if (b.dim() != n)
                return Vector<Real>();


        Vector<Real> x = b;


      // Solve L*y = b;
      for (int k = 0; k < n; k++) 
          {
         for (int i = 0; i < k; i++) 
               x[k] -= x[i]*L_[k][i];
                 x[k] /= L_[k][k];
                
      }

      // Solve L'*X = Y;
      for (int k = n-1; k >= 0; k--) 
          {
         for (int i = k+1; i < n; i++) 
               x[k] -= x[i]*L_[i][k];
         x[k] /= L_[k][k];
      }

        return x;
}


template <class Real>
Matrix<Real> Cholesky<Real>::solve(const Matrix<Real> &B)
{
        int n = L_.num_rows();
        if (B.num_rows() != n)
                return Matrix<Real>();


        Matrix<Real> X = B;
        int nx = B.num_cols();

      // Solve L*y = b;
          for (int j=0; j< nx; j++)
          {
        for (int k = 0; k < n; k++) 
                {
                        for (int i = 0; i < k; i++) 
               X[k][j] -= X[i][j]*L_[k][i];
                    X[k][j] /= L_[k][k];
                 }
      }

      // Solve L'*X = Y;
     for (int j=0; j<nx; j++)
         {
        for (int k = n-1; k >= 0; k--) 
                {
                for (int i = k+1; i < n; i++) 
               X[k][j] -= X[i][j]*L_[i][k];
                X[k][j] /= L_[k][k];
                }
      }



        return X;
}




template <class Real>
class Eigenvalue
{


    int n;

   int issymmetric; /* boolean*/

   Vector<Real> d;         /* real part */
   Vector<Real> e;         /* img part */

   Matrix<Real> V;

   /* Array for internal storage of nonsymmetric Hessenberg form.
   @serial internal storage of nonsymmetric Hessenberg form.
   */
   Matrix<Real> H;
   

   /* Working storage for nonsymmetric algorithm.
   @serial working storage for nonsymmetric algorithm.
   */
   Vector<Real> ort;


   // Symmetric Householder reduction to tridiagonal form.

   void 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.

      for (int j = 0; j < n; j++) {
         d[j] = V[n-1][j];
      }

      // Householder reduction to tridiagonal form.
   
      for (int i = n-1; i > 0; i--) {
   
         // Scale to avoid under/overflow.
   
         Real scale = Real(0.0);
         Real h = Real(0.0);
         for (int k = 0; k < i; k++) {
            scale = scale + abs(d[k]);
         }
         if (scale == Real(0.0)) {
            e[i] = d[i-1];
            for (int j = 0; j < i; j++) {
               d[j] = V[i-1][j];
               V[i][j] = Real(0.0);
               V[j][i] = Real(0.0);
            }
         } else {
   
            // Generate Householder vector.
   
            for (int k = 0; k < i; k++) {
               d[k] /= scale;
               h += d[k] * d[k];
            }
            Real f = d[i-1];
            Real g = sqrt(h);
            if (f > 0) {
               g = -g;
            }
            e[i] = scale * g;
            h = h - f * g;
            d[i-1] = f - g;
            for (int j = 0; j < i; j++) {
               e[j] = Real(0.0);
            }
   
            // Apply similarity transformation to remaining columns.
   
            for (int j = 0; j < i; j++) {
               f = d[j];
               V[j][i] = f;
               g = e[j] + V[j][j] * f;
               for (int k = j+1; k <= i-1; k++) {
                  g += V[k][j] * d[k];
                  e[k] += V[k][j] * f;
               }
               e[j] = g;
            }
            f = Real(0.0);
            for (int j = 0; j < i; j++) {
               e[j] /= h;
               f += e[j] * d[j];
            }
            Real hh = f / (h + h);
            for (int j = 0; j < i; j++) {
               e[j] -= hh * d[j];
            }
            for (int j = 0; j < i; j++) {
               f = d[j];
               g = e[j];
               for (int k = j; k <= i-1; k++) {
                  V[k][j] -= (f * e[k] + g * d[k]);
               }
               d[j] = V[i-1][j];
               V[i][j] = Real(0.0);
            }
         }
         d[i] = h;
      }
   
      // Accumulate transformations.
   
      for (int i = 0; i < n-1; i++) {
         V[n-1][i] = V[i][i];
         V[i][i] = Real(1.0);
         Real h = d[i+1];
         if (h != Real(0.0)) {
            for (int k = 0; k <= i; k++) {
               d[k] = V[k][i+1] / h;
            }
            for (int j = 0; j <= i; j++) {
               Real g = Real(0.0);
               for (int k = 0; k <= i; k++) {
                  g += V[k][i+1] * V[k][j];
               }
               for (int k = 0; k <= i; k++) {
                  V[k][j] -= g * d[k];
               }
            }
         }
         for (int k = 0; k <= i; k++) {
            V[k][i+1] = Real(0.0);
         }
      }
      for (int j = 0; j < n; j++) {
         d[j] = V[n-1][j];
         V[n-1][j] = Real(0.0);
      }
      V[n-1][n-1] = Real(1.0);
      e[0] = Real(0.0);
   } 

   // Symmetric tridiagonal QL algorithm.
   
   void tql2 () {

   //  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.
   
      for (int i = 1; i < n; i++) {
         e[i-1] = e[i];
      }
      e[n-1] = Real(0.0);
   
      Real f = Real(0.0);
      Real tst1 = Real(0.0);
      Real eps = pow(2.0,-52.0);
      for (int l = 0; l < n; l++) {

         // Find small subdiagonal element
   
         tst1 = max(tst1,abs(d[l]) + abs(e[l]));
         int m = l;

        // Original while-loop from Java code
         while (m < n) {
            if (abs(e[m]) <= eps*tst1) {
               break;
            }
            m++;
         }

   
         // If m == l, d[l] is an eigenvalue,
         // otherwise, iterate.
   
         if (m > l) {
            int iter = 0;
            do {
               iter = iter + 1;  // (Could check iteration count here.)
   
               // Compute implicit shift
   
               Real g = d[l];
               Real p = (d[l+1] - g) / (2.0 * e[l]);
               Real r = hypot(p, static_cast<Real>(Real(1.0)));
               if (p < 0) {
                  r = -r;
               }
               d[l] = e[l] / (p + r);
               d[l+1] = e[l] * (p + r);
               Real dl1 = d[l+1];
               Real h = g - d[l];
               for (int i = l+2; i < n; i++) {
                  d[i] -= h;
               }
               f = f + h;
   
               // Implicit QL transformation.
   
               p = d[m];
               Real c = Real(1.0);
               Real c2 = c;
               Real c3 = c;
               Real el1 = e[l+1];
               Real s = Real(0.0);
               Real s2 = Real(0.0);
               for (int i = m-1; i >= l; i--) {
                  c3 = c2;
                  c2 = c;
                  s2 = s;
                  g = c * e[i];
                  h = c * p;
                  r = hypot(p,e[i]);
                  e[i+1] = s * r;
                  s = e[i] / r;
                  c = p / r;
                  p = c * d[i] - s * g;
                  d[i+1] = h + s * (c * g + s * d[i]);
   
                  // Accumulate transformation.
   
                  for (int k = 0; k < n; k++) {
                     h = V[k][i+1];
                     V[k][i+1] = s * V[k][i] + c * h;
                     V[k][i] = c * V[k][i] - s * h;
                  }
               }
               p = -s * s2 * c3 * el1 * e[l] / dl1;
               e[l] = s * p;
               d[l] = c * p;
   
               // Check for convergence.
   
            } while (abs(e[l]) > eps*tst1);
         }
         d[l] = d[l] + f;
         e[l] = Real(0.0);
      }
     
      // Sort eigenvalues and corresponding vectors.
   
      for (int i = 0; i < n-1; i++) {
         int k = i;
         Real p = d[i];
         for (int j = i+1; j < n; j++) {
            if (d[j] < p) {
               k = j;
               p = d[j];
            }
         }
         if (k != i) {
            d[k] = d[i];
            d[i] = p;
            for (int j = 0; j < n; j++) {
               p = V[j][i];
               V[j][i] = V[j][k];
               V[j][k] = p;
            }
         }
      }
   }

   // Nonsymmetric reduction to Hessenberg form.

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

      for (int i = 0; i < n; i++) {
         for (int j = 0; j < n; j++) {
            V[i][j] = (i == j ? Real(1.0) : Real(0.0));
         }
      }

      for (int m = high-1; m >= low+1; m--) {
         if (H[m][m-1] != Real(0.0)) {
            for (int i = m+1; i <= high; i++) {
               ort[i] = H[i][m-1];
            }
            for (int j = m; j <= high; j++) {
               Real g = Real(0.0);
               for (int i = m; i <= high; i++) {
                  g += ort[i] * V[i][j];
               }
               // Double division avoids possible underflow
               g = (g / ort[m]) / H[m][m-1];
               for (int i = m; i <= high; i++) {
                  V[i][j] += g * ort[i];
               }
            }
         }
      }
   }


   // Complex scalar division.

   Real cdivr, cdivi;
   void cdiv(Real xr, Real xi, Real yr, Real yi) {
      Real r,d;
      if (abs(yr) > abs(yi)) {
         r = yi/yr;
         d = yr + r*yi;
         cdivr = (xr + r*xi)/d;
         cdivi = (xi - r*xr)/d;
      } else {
         r = yr/yi;
         d = yi + r*yr;
         cdivr = (r*xr + xi)/d;
         cdivi = (r*xi - xr)/d;
      }
   }


   // Nonsymmetric reduction from Hessenberg to real Schur form.

   void hqr2 () {
   
      //  This 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.
   
      // Initialize
   
      int nn = this->n;
      int n = nn-1;
      int low = 0;
      int high = nn-1;
      Real eps = pow(2.0,-52.0);
      Real exshift = Real(0.0);
      Real p=0,q=0,r=0,s=0,z=0,t,w,x,y;
   
      // Store roots isolated by balanc and compute matrix norm
   
      Real norm = Real(0.0);
      for (int i = 0; i < nn; i++) {
         if ((i < low) || (i > high)) {
            d[i] = H[i][i];
            e[i] = Real(0.0);
         }
         for (int j = max(i-Real(1.0)); j < nn; j++) {
            norm = norm + abs(H[i][j]);
         }
      }
   
      // Outer loop over eigenvalue index
   
      int iter = 0;
      while (n >= low) {
   
         // Look for single small sub-diagonal element
   
         int l = n;
         while (l > low) {
            s = abs(H[l-1][l-1]) + abs(H[l][l]);
            if (s == Real(0.0)) {
               s = norm;
            }
            if (abs(H[l][l-1]) < eps * s) {
               break;
            }
            l--;
         }
       
         // Check for convergence
         // One root found
   
         if (l == n) {
            H[n][n] = H[n][n] + exshift;
            d[n] = H[n][n];
            e[n] = Real(0.0);
            n--;
            iter = 0;
   
         // Two roots found
   
         } else if (l == n-1) {
            w = H[n][n-1] * H[n-1][n];
            p = (H[n-1][n-1] - H[n][n]) / 2.0;
            q = p * p + w;
            z = sqrt(abs(q));
            H[n][n] = H[n][n] + exshift;
            H[n-1][n-1] = H[n-1][n-1] + exshift;
            x = H[n][n];
   
            // Real pair
   
            if (q >= 0) {
               if (p >= 0) {
                  z = p + z;
               } else {
                  z = p - z;
               }
               d[n-1] = x + z;
               d[n] = d[n-1];
               if (z != Real(0.0)) {
                  d[n] = x - w / z;
               }
               e[n-1] = Real(0.0);
               e[n] = Real(0.0);
               x = 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 (int j = n-1; j < nn; j++) {
                  z = H[n-1][j];
                  H[n-1][j] = q * z + p * H[n][j];
                  H[n][j] = q * H[n][j] - p * z;
               }
   
               // Column modification
   
               for (int i = 0; i <= n; i++) {
                  z = H[i][n-1];
                  H[i][n-1] = q * z + p * H[i][n];
                  H[i][n] = q * H[i][n] - p * z;
               }
   
               // Accumulate transformations
   
               for (int i = low; i <= high; i++) {
                  z = V[i][n-1];
                  V[i][n-1] = q * z + p * V[i][n];
                  V[i][n] = q * V[i][n] - p * z;
               }
   
            // Complex pair
   
            } else {
               d[n-1] = x + p;
               d[n] = x + p;
               e[n-1] = z;
               e[n] = -z;
            }
            n = n - 2;
            iter = 0;
   
         // No convergence yet
   
         } else {
   
            // Form shift
   
            x = H[n][n];
            y = Real(0.0);
            w = Real(0.0);
            if (l < n) {
               y = H[n-1][n-1];
               w = H[n][n-1] * H[n-1][n];
            }
   
            // Wilkinson's original ad hoc shift
   
            if (iter == 10) {
               exshift += x;
               for (int i = low; i <= n; i++) {
                  H[i][i] -= x;
               }
               s = abs(H[n][n-1]) + abs(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 (int i = low; i <= n; i++) {
                       H[i][i] -= s;
                    }
                    exshift += s;
                    x = y = w = 0.964;
                }
            }
   
            iter = iter + 1;   // (Could check iteration count here.)
   
            // Look for two consecutive small sub-diagonal elements
   
            int m = n-2;
            while (m >= l) {
               z = H[m][m];
               r = x - z;
               s = y - z;
               p = (r * s - w) / H[m+1][m] + H[m][m+1];
               q = H[m+1][m+1] - z - r - s;
               r = 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(H[m][m-1]) * (abs(q) + abs(r)) <
                  eps * (abs(p) * (abs(H[m-1][m-1]) + abs(z) +
                  abs(H[m+1][m+1])))) {
                     break;
               }
               m--;
            }
   
            for (int i = m+2; i <= n; i++) {
               H[i][i-2] = Real(0.0);
               if (i > m+2) {
                  H[i][i-3] = Real(0.0);
               }
            }
   
            // Double QR step involving rows l:n and columns m:n
   
            for (int k = m; k <= n-1; k++) {
               int notlast = (k != n-1);
               if (k != m) {
                  p = H[k][k-1];
                  q = H[k+1][k-1];
                  r = (notlast ? H[k+2][k-1] : Real(0.0));
                  x = abs(p) + abs(q) + abs(r);
                  if (x != Real(0.0)) {
                     p = p / x;
                     q = q / x;
                     r = r / x;
                  }
               }
               if (x == Real(0.0)) {
                  break;
               }
               s = sqrt(p * p + q * q + r * r);
               if (p < 0) {
                  s = -s;
               }
               if (s != 0) {
                  if (k != m) {
                     H[k][k-1] = -s * x;
                  } else if (l != m) {
                     H[k][k-1] = -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 (int j = k; j < nn; j++) {
                     p = H[k][j] + q * H[k+1][j];
                     if (notlast) {
                        p = p + r * H[k+2][j];
                        H[k+2][j] = H[k+2][j] - p * z;
                     }
                     H[k][j] = H[k][j] - p * x;
                     H[k+1][j] = H[k+1][j] - p * y;
                  }
   
                  // Column modification
   
                  for (int i = 0; i <= min(n,k+3); i++) {
                     p = x * H[i][k] + y * H[i][k+1];
                     if (notlast) {
                        p = p + z * H[i][k+2];
                        H[i][k+2] = H[i][k+2] - p * r;
                     }
                     H[i][k] = H[i][k] - p;
                     H[i][k+1] = H[i][k+1] - p * q;
                  }
   
                  // Accumulate transformations
   
                  for (int i = low; i <= high; i++) {
                     p = x * V[i][k] + y * V[i][k+1];
                     if (notlast) {
                        p = p + z * V[i][k+2];
                        V[i][k+2] = V[i][k+2] - p * r;
                     }
                     V[i][k] = V[i][k] - p;
                     V[i][k+1] = 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 == Real(0.0)) {
         return;
      }
   
      for (n = nn-1; n >= 0; n--) {
         p = d[n];
         q = e[n];
   
         // Real vector
   
         if (q == 0) {
            int l = n;
            H[n][n] = Real(1.0);
            for (int i = n-1; i >= 0; i--) {
               w = H[i][i] - p;
               r = Real(0.0);
               for (int j = l; j <= n; j++) {
                  r = r + H[i][j] * H[j][n];
               }
               if (e[i] < Real(0.0)) {
                  z = w;
                  s = r;
               } else {
                  l = i;
                  if (e[i] == Real(0.0)) {
                     if (w != Real(0.0)) {
                        H[i][n] = -r / w;
                     } else {
                        H[i][n] = -r / (eps * norm);
                     }
   
                  // Solve real equations
   
                  } else {
                     x = H[i][i+1];
                     y = H[i+1][i];
                     q = (d[i] - p) * (d[i] - p) + e[i] * e[i];
                     t = (x * s - z * r) / q;
                     H[i][n] = t;
                     if (abs(x) > abs(z)) {
                        H[i+1][n] = (-r - w * t) / x;
                     } else {
                        H[i+1][n] = (-s - y * t) / z;
                     }
                  }
   
                  // Overflow control
   
                  t = abs(H[i][n]);
                  if ((eps * t) * t > 1) {
                     for (int j = i; j <= n; j++) {
                        H[j][n] = H[j][n] / t;
                     }
                  }
               }
            }
   
         // Complex vector
   
         } else if (q < 0) {
            int l = n-1;

            // Last vector component imaginary so matrix is triangular
   
            if (abs(H[n][n-1]) > abs(H[n-1][n])) {
               H[n-1][n-1] = q / H[n][n-1];
               H[n-1][n] = -(H[n][n] - p) / H[n][n-1];
            } else {
               cdiv(Real(0.0),-H[n-1][n],H[n-1][n-1]-p,q);
               H[n-1][n-1] = cdivr;
               H[n-1][n] = cdivi;
            }
            H[n][n-1] = Real(0.0);
            H[n][n] = Real(1.0);
            for (int i = n-2; i >= 0; i--) {
               Real ra,sa,vr,vi;
               ra = Real(0.0);
               sa = Real(0.0);
               for (int j = l; j <= n; j++) {
                  ra = ra + H[i][j] * H[j][n-1];
                  sa = sa + H[i][j] * H[j][n];
               }
               w = H[i][i] - p;
   
               if (e[i] < Real(0.0)) {
                  z = w;
                  r = ra;
                  s = sa;
               } else {
                  l = i;
                  if (e[i] == 0) {
                     cdiv(-ra,-sa,w,q);
                     H[i][n-1] = cdivr;
                     H[i][n] = cdivi;
                  } else {
   
                     // Solve complex equations
   
                     x = H[i][i+1];
                     y = H[i+1][i];
                     vr = (d[i] - p) * (d[i] - p) + e[i] * e[i] - q * q;
                     vi = (d[i] - p) * 2.0 * q;
                     if ((vr == Real(0.0)) && (vi == Real(0.0))) {
                        vr = eps * norm * (abs(w) + abs(q) +
                        abs(x) + abs(y) + abs(z));
                     }
                     cdiv(x*r-z*ra+q*sa,x*s-z*sa-q*ra,vr,vi);
                     H[i][n-1] = cdivr;
                     H[i][n] = cdivi;
                     if (abs(x) > (abs(z) + abs(q))) {
                        H[i+1][n-1] = (-ra - w * H[i][n-1] + q * H[i][n]) / x;
                        H[i+1][n] = (-sa - w * H[i][n] - q * H[i][n-1]) / x;
                     } else {
                        cdiv(-r-y*H[i][n-1],-s-y*H[i][n],z,q);
                        H[i+1][n-1] = cdivr;
                        H[i+1][n] = cdivi;
                     }
                  }
   
                  // Overflow control

                  t = max(abs(H[i][n-1]),abs(H[i][n]));
                  if ((eps * t) * t > 1) {
                     for (int j = i; j <= n; j++) {
                        H[j][n-1] = H[j][n-1] / t;
                        H[j][n] = H[j][n] / t;
                     }
                  }
               }
            }
         }
      }
   
      // Vectors of isolated roots
   
      for (int i = 0; i < nn; i++) {
         if (i < low || i > high) {
            for (int j = i; j < nn; j++) {
               V[i][j] = H[i][j];
            }
         }
      }
   
      // Back transformation to get eigenvectors of original matrix
   
      for (int j = nn-1; j >= low; j--) {
         for (int i = low; i <= high; i++) {
            z = Real(0.0);
            for (int k = low; k <= min(j,high); k++) {
               z = z + V[i][k] * H[k][j];
            }
            V[i][j] = z;
         }
      }
   }

public:


   Eigenvalue(const Matrix<Real> &A) {
      n = A.num_cols();
      V = Matrix<Real>(n,n);
      d = Vector<Real>(n);
      e = Vector<Real>(n);

      issymmetric = 1;
      for (int j = 0; (j < n) && issymmetric; j++) {
         for (int i = 0; (i < n) && issymmetric; i++) {
            issymmetric = (A[i][j] == A[j][i]);
         }
      }

      if (issymmetric) {
         for (int i = 0; i < n; i++) {
            for (int j = 0; j < n; j++) {
               V[i][j] = A[i][j];
            }
         }
   
         // Tridiagonalize.
         tred2();
   
         // Diagonalize.
         tql2();

      } else {
         H = Matrix<Real>(n,n);
         ort = Vector<Real>(n);
         
         for (int j = 0; j < n; j++) {
            for (int i = 0; i < n; i++) {
               H[i][j] = A[i][j];
            }
         }
   
         // Reduce to Hessenberg form.
         orthes();
   
         // Reduce Hessenberg to real Schur form.
         hqr2();
      }
   }


   void getV (Matrix<Real> &V_) {
      V_ = V;
      return;
   }

   void getRealEigenvalues (Vector<Real> &d_) {
      d_ = d;
      return ;
   }

   void getImagEigenvalues (Vector<Real> &e_) {
      e_ = e;
      return;
   }

   
   void getD (Matrix<Real> &D) {
      D = Matrix<Real>(n,n);
      for (int i = 0; i < n; i++) {
         for (int j = 0; j < n; j++) {
            D[i][j] = Real(0.0);
         }
         D[i][i] = d[i];
         if (e[i] > 0) {
            D[i][i+1] = e[i];
         } else if (e[i] < 0) {
            D[i][i-1] = e[i];
         }
      }
   }
};


template <class Real>
class LU
{

        private:

   /* Array for internal storage of decomposition.  */
   Matrix<Real>  LU_;
   int m, n, pivsign; 
   Vector<int> piv;


   Matrix<Real> permute_copy( const Matrix<Real> &A, 
                        const Vector<int> &piv, int j0, int j1)
        {
                int piv_length = piv.dim();

                Matrix<Real> X(piv_length, j1-j0+1);


         for (int i = 0; i < piv_length; i++) 
            for (int j = j0; j <= j1; j++) 
               X[i][j-j0] = A[piv[i]][j];

                return X;
        }

   Vector<Real> permute_copy( const Vector<Real> &A, 
                const Vector<int> &piv)
        {
                int piv_length = piv.dim();
                if (piv_length != A.dim())
                        return Vector<Real>();

                Vector<Real> x(piv_length);


         for (int i = 0; i < piv_length; i++) 
               x[i] = A[piv[i]];

                return x;
        }


        public :

    LU (const Matrix<Real> &A) : LU_(A), m(A.num_rows()), n(A.num_cols()), 
                piv(A.num_rows())
        
        {

   // Use a "left-looking", dot-product, Crout/Doolittle algorithm.


      for (int i = 0; i < m; i++) {
         piv[i] = i;
      }
      pivsign = 1;
      Real *LUrowi = 0;;
      Vector<Real> LUcolj(m);

      // Outer loop.

      for (int j = 0; j < n; j++) {

         // Make a copy of the j-th column to localize references.

         for (int i = 0; i < m; i++) {
            LUcolj[i] = LU_[i][j];
         }

         // Apply previous transformations.

         for (int i = 0; i < m; i++) {
            LUrowi = LU_[i];

            // Most of the time is spent in the following dot product.

            int kmax = min(i,j);
            double s = Real(0.0);
            for (int k = 0; k < kmax; k++) {
               s += LUrowi[k]*LUcolj[k];
            }

            LUrowi[j] = LUcolj[i] -= s;
         }
   
         // Find pivot and exchange if necessary.

         int p = j;
         for (int i = j+1; i < m; i++) {
            if (abs(LUcolj[i]) > abs(LUcolj[p])) {
               p = i;
            }
         }
         if (p != j) {
                    int k=0;
            for (k = 0; k < n; k++) {
               double t = LU_[p][k]; 
                           LU_[p][k] = LU_[j][k]; 
                           LU_[j][k] = t;
            }
            k = piv[p]; 
                        piv[p] = piv[j]; 
                        piv[j] = k;
            pivsign = -pivsign;
         }

         // Compute multipliers.
         
         if ((j < m) && (LU_[j][j] != Real(0.0))) {
            for (int i = j+1; i < m; i++) {
               LU_[i][j] /= LU_[j][j];
            }
         }
      }
   }


   int isNonsingular () {
      for (int j = 0; j < n; j++) {
         if (LU_[j][j] == 0)
            return 0;
      }
      return 1;
   }

   Matrix<Real> getL () {
      Matrix<Real> L_(m,n);
      for (int i = 0; i < m; i++) {
         for (int j = 0; j < n; j++) {
            if (i > j) {
               L_[i][j] = LU_[i][j];
            } else if (i == j) {
               L_[i][j] = Real(1.0);
            } else {
               L_[i][j] = Real(0.0);
            }
         }
      }
      return L_;
   }

   Matrix<Real> getU () {
          Matrix<Real> U_(n,n);
      for (int i = 0; i < n; i++) {
         for (int j = 0; j < n; j++) {
            if (i <= j) {
               U_[i][j] = LU_[i][j];
            } else {
               U_[i][j] = Real(0.0);
            }
         }
      }
      return U_;
   }

   Vector<int> getPivot () {
      return piv;
   }


   Real det () {
      if (m != n) {
         return Real(0);
      }
      Real d = Real(pivsign);
      for (int j = 0; j < n; j++) {
         d *= LU_[j][j];
      }
      return d;
   }

   Matrix<Real> solve (const Matrix<Real> &B) 
   {

          /* Dimensions: A is mxn, X is nxk, B is mxk */
      
      if (B.num_rows() != m) {
                return Matrix<Real>(Real(0.0));
      }
      if (!isNonsingular()) {
        return Matrix<Real>(Real(0.0));
      }

      // Copy right hand side with pivoting
      int nx = B.num_cols();


          Matrix<Real> X = permute_copy(B, piv, 0, nx-1);

      // Solve L*Y = B(piv,:)
      for (int k = 0; k < n; k++) {
         for (int i = k+1; i < n; i++) {
            for (int j = 0; j < nx; j++) {
               X[i][j] -= X[k][j]*LU_[i][k];
            }
         }
      }
      // Solve U*X = Y;
      for (int k = n-1; k >= 0; k--) {
         for (int j = 0; j < nx; j++) {
            X[k][j] /= LU_[k][k];
         }
         for (int i = 0; i < k; i++) {
            for (int j = 0; j < nx; j++) {
               X[i][j] -= X[k][j]*LU_[i][k];
            }
         }
      }
      return X;
   }


   Vector<Real> solve (const Vector<Real> &b) 
   {

          /* Dimensions: A is mxn, X is nxk, B is mxk */
      
      if (b.dim() != m) {
                return Vector<Real>();
      }
      if (!isNonsingular()) {
        return Vector<Real>();
      }


          Vector<Real> x = permute_copy(b, piv);

      // Solve L*Y = B(piv)
      for (int k = 0; k < n; k++) {
         for (int i = k+1; i < n; i++) {
               x[i] -= x[k]*LU_[i][k];
            }
         }
      
          // Solve U*X = Y;
      for (int k = n-1; k >= 0; k--) {
            x[k] /= LU_[k][k];
                for (int i = 0; i < k; i++) 
                x[i] -= x[k]*LU_[i][k];
      }
     

      return x;
   }

}; /* class LU */


template <class Real>
class QR {


   /* Array for internal storage of decomposition.
   @serial internal array storage.
   */
   
   Matrix<Real> QR_;

   /* Row and column dimensions.
   @serial column dimension.
   @serial row dimension.
   */
   int m, n;

   /* Array for internal storage of diagonal of R.
   @serial diagonal of R.
   */
   Vector<Real> Rdiag;


public:
        
        QR(const Matrix<Real> &A)               /* constructor */
        {
      QR_ = A;
      m = A.num_rows();
      n = A.num_cols();
      Rdiag = Vector<Real>(n);
                int i=0, j=0, k=0;

      // Main loop.
      for (k = 0; k < n; k++) {
         // Compute 2-norm of k-th column without under/overflow.
         Real nrm = 0;
         for (i = k; i < m; i++) {
            nrm = hypot(nrm,QR_[i][k]);
         }

         if (nrm != Real(0.0)) {
            // Form k-th Householder vector.
            if (QR_[k][k] < 0) {
               nrm = -nrm;
            }
            for (i = k; i < m; i++) {
               QR_[i][k] /= nrm;
            }
            QR_[k][k] += Real(1.0);

            // Apply transformation to remaining columns.
            for (j = k+1; j < n; j++) {
               Real s = Real(0.0); 
               for (i = k; i < m; i++) {
                  s += QR_[i][k]*QR_[i][j];
               }
               s = -s/QR_[k][k];
               for (i = k; i < m; i++) {
                  QR_[i][j] += s*QR_[i][k];
               }
            }
         }
         Rdiag[k] = -nrm;
      }
   }


        int isFullRank() const          
        {
      for (int j = 0; j < n; j++) 
          {
         if (Rdiag[j] == 0)
            return 0;
      }
      return 1;
        }
        
        


   Matrix<Real> getHouseholder (void)  const
   {
          Matrix<Real> H(m,n);

          /* note: H is completely filled in by algorithm, so
             initializaiton of H is not necessary.
          */
      for (int i = 0; i < m; i++) 
          {
         for (int j = 0; j < n; j++) 
                 {
            if (i >= j) {
               H[i][j] = QR_[i][j];
            } else {
               H[i][j] = Real(0.0);
            }
         }
      }
          return H;
   }



        Matrix<Real> getR() const
        {
      Matrix<Real> R(n,n);
      for (int i = 0; i < n; i++) {
         for (int j = 0; j < n; j++) {
            if (i < j) {
               R[i][j] = QR_[i][j];
            } else if (i == j) {
               R[i][j] = Rdiag[i];
            } else {
               R[i][j] = Real(0.0);
            }
         }
      }
          return R;
   }
        
        



        Matrix<Real> getQ() const
        {
          int i=0, j=0, k=0;

          Matrix<Real> Q(m,n);
      for (k = n-1; k >= 0; k--) {
         for (i = 0; i < m; i++) {
            Q[i][k] = Real(0.0);
         }
         Q[k][k] = Real(1.0);
         for (j = k; j < n; j++) {
            if (QR_[k][k] != 0) {
               Real s = Real(0.0);
               for (i = k; i < m; i++) {
                  s += QR_[i][k]*Q[i][j];
               }
               s = -s/QR_[k][k];
               for (i = k; i < m; i++) {
                  Q[i][j] += s*QR_[i][k];
               }
            }
         }
      }
          return Q;
   }


   Vector<Real> solve(const Vector<Real> &b) const
   {
          if (b.dim() != m)             /* arrays must be conformant */
                return Vector<Real>();

          if ( !isFullRank() )          /* matrix is rank deficient */
          {
                return Vector<Real>();
          }

          Vector<Real> x = b;

      // Compute Y = transpose(Q)*b
      for (int k = 0; k < n; k++) 
          {
            Real s = Real(0.0); 
            for (int i = k; i < m; i++) 
                        {
               s += QR_[i][k]*x[i];
            }
            s = -s/QR_[k][k];
            for (int i = k; i < m; i++) 
                        {
               x[i] += s*QR_[i][k];
            }
      }
      // Solve R*X = Y;
      for (int k = n-1; k >= 0; k--) 
          {
         x[k] /= Rdiag[k];
         for (int i = 0; i < k; i++) {
               x[i] -= x[k]*QR_[i][k];
         }
      }


          /* return n x nx portion of X */
          Vector<Real> x_(n);
          for (int i=0; i<n; i++)
                        x_[i] = x[i];

          return x_;
   }

   Matrix<Real> solve(const Matrix<Real> &B) const
   {
          if (B.num_rows() != m)                /* arrays must be conformant */
                return Matrix<Real>(Real(0.0));

          if ( !isFullRank() )          /* matrix is rank deficient */
          {
                return Matrix<Real>(Real(0.0));
          }

      int nx = B.num_cols(); 
          Matrix<Real> X = B;
          int i=0, j=0, k=0;

      // Compute Y = transpose(Q)*B
      for (k = 0; k < n; k++) {
         for (j = 0; j < nx; j++) {
            Real s = Real(0.0); 
            for (i = k; i < m; i++) {
               s += QR_[i][k]*X[i][j];
            }
            s = -s/QR_[k][k];
            for (i = k; i < m; i++) {
               X[i][j] += s*QR_[i][k];
            }
         }
      }
      // Solve R*X = Y;
      for (k = n-1; k >= 0; k--) {
         for (j = 0; j < nx; j++) {
            X[k][j] /= Rdiag[k];
         }
         for (i = 0; i < k; i++) {
            for (j = 0; j < nx; j++) {
               X[i][j] -= X[k][j]*QR_[i][k];
            }
         }
      }


          /* return n x nx portion of X */
          Matrix<Real> X_(n,nx);
          for (i=0; i<n; i++)
                for (j=0; j<nx; j++)
                        X_[i][j] = X[i][j];

          return X_;
   }


};


template <class Real>
class SVD 
{


        Matrix<Real> U, V;
        Vector<Real> s;
        int m, n;

  public:


   SVD (const Matrix<Real> &Arg) {


      m = Arg.num_rows();
      n = Arg.num_cols();
      int nu = min(m,n);
      s = Vector<Real>(min(m+1,n)); 
      U = Matrix<Real>(m, nu, Real(0));
      V = Matrix<Real>(n,n);
      Vector<Real> e(n);
      Vector<Real> work(m);
            Matrix<Real> A(Arg);
      int wantu = 1;                                    /* boolean */
      int wantv = 1;                                    /* boolean */
          int i=0, j=0, k=0;

      // Reduce A to bidiagonal form, storing the diagonal elements
      // in s and the super-diagonal elements in e.

      int nct = min(m-1,n);
      int nrt = max(0,min(n-2,m));
      for (k = 0; k < max(nct,nrt); k++) {
         if (k < nct) {

            // Compute the transformation for the k-th column and
            // place the k-th diagonal in s[k].
            // Compute 2-norm of k-th column without under/overflow.
            s[k] = 0;
            for (i = k; i < m; i++) {
               s[k] = hypot(s[k],A[i][k]);
            }
            if (s[k] != Real(0.0)) {
               if (A[k][k] < Real(0.0)) {
                  s[k] = -s[k];
               }
               for (i = k; i < m; i++) {
                  A[i][k] /= s[k];
               }
               A[k][k] += Real(1.0);
            }
            s[k] = -s[k];
         }
         for (j = k+1; j < n; j++) {
            if ((k < nct) && (s[k] != Real(0.0)))  {

            // Apply the transformation.

               double t = 0;
               for (i = k; i < m; i++) {
                  t += A[i][k]*A[i][j];
               }
               t = -t/A[k][k];
               for (i = k; i < m; i++) {
                  A[i][j] += t*A[i][k];
               }
            }

            // Place the k-th row of A into e for the
            // subsequent calculation of the row transformation.

            e[j] = A[k][j];
         }
         if (wantu & (k < nct)) {

            // Place the transformation in U for subsequent back
            // multiplication.

            for (i = k; i < m; i++) {
               U[i][k] = A[i][k];
            }
         }
         if (k < nrt) {

            // Compute the k-th row transformation and place the
            // k-th super-diagonal in e[k].
            // Compute 2-norm without under/overflow.
            e[k] = 0;
            for (i = k+1; i < n; i++) {
               e[k] = hypot(e[k],e[i]);
            }
            if (e[k] != Real(0.0)) {
               if (e[k+1] < Real(0.0)) {
                  e[k] = -e[k];
               }
               for (i = k+1; i < n; i++) {
                  e[i] /= e[k];
               }
               e[k+1] += Real(1.0);
            }
            e[k] = -e[k];
            if ((k+1 < m) & (e[k] != Real(0.0))) {

            // Apply the transformation.

               for (i = k+1; i < m; i++) {
                  work[i] = Real(0.0);
               }
               for (j = k+1; j < n; j++) {
                  for (i = k+1; i < m; i++) {
                     work[i] += e[j]*A[i][j];
                  }
               }
               for (j = k+1; j < n; j++) {
                  double t = -e[j]/e[k+1];
                  for (i = k+1; i < m; i++) {
                     A[i][j] += t*work[i];
                  }
               }
            }
            if (wantv) {

            // Place the transformation in V for subsequent
            // back multiplication.

               for (i = k+1; i < n; i++) {
                  V[i][k] = e[i];
               }
            }
         }
      }

      // Set up the final bidiagonal matrix or order p.

      int p = min(n,m+1);
      if (nct < n) {
         s[nct] = A[nct][nct];
      }
      if (m < p) {
         s[p-1] = Real(0.0);
      }
      if (nrt+1 < p) {
         e[nrt] = A[nrt][p-1];
      }
      e[p-1] = Real(0.0);

      // If required, generate U.

      if (wantu) {
         for (j = nct; j < nu; j++) {
            for (i = 0; i < m; i++) {
               U[i][j] = Real(0.0);
            }
            U[j][j] = Real(1.0);
         }
         for (k = nct-1; k >= 0; k--) {
            if (s[k] != Real(0.0)) {
               for (j = k+1; j < nu; j++) {
                  double t = 0;
                  for (i = k; i < m; i++) {
                     t += U[i][k]*U[i][j];
                  }
                  t = -t/U[k][k];
                  for (i = k; i < m; i++) {
                     U[i][j] += t*U[i][k];
                  }
               }
               for (i = k; i < m; i++ ) {
                  U[i][k] = -U[i][k];
               }
               U[k][k] = Real(1.0) + U[k][k];
               for (i = 0; i < k-1; i++) {
                  U[i][k] = Real(0.0);
               }
            } else {
               for (i = 0; i < m; i++) {
                  U[i][k] = Real(0.0);
               }
               U[k][k] = Real(1.0);
            }
         }
      }

      // If required, generate V.

      if (wantv) {
         for (k = n-1; k >= 0; k--) {
            if ((k < nrt) & (e[k] != Real(0.0))) {
               for (j = k+1; j < nu; j++) {
                  double t = 0;
                  for (i = k+1; i < n; i++) {
                     t += V[i][k]*V[i][j];
                  }
                  t = -t/V[k+1][k];
                  for (i = k+1; i < n; i++) {
                     V[i][j] += t*V[i][k];
                  }
               }
            }
            for (i = 0; i < n; i++) {
               V[i][k] = Real(0.0);
            }
            V[k][k] = Real(1.0);
         }
      }

      // Main iteration loop for the singular values.

      int pp = p-1;
      int iter = 0;
      double eps = pow(2.0,-52.0);
      while (p > 0) {
         int k=0;
                 int kase=0;

         // Here is where a test for too many iterations would go.

         // This section of the program inspects for
         // negligible elements in the s and e arrays.  On
         // completion the variables kase and k are set as follows.

         // kase = 1     if s(p) and e[k-1] are negligible and k<p
         // kase = 2     if s(k) is negligible and k<p
         // kase = 3     if e[k-1] is negligible, k<p, and
         //              s(k), ..., s(p) are not negligible (qr step).
         // kase = 4     if e(p-1) is negligible (convergence).

         for (k = p-2; k >= -1; k--) {
            if (k == -1) {
               break;
            }
            if (abs(e[k]) <= eps*(abs(s[k]) + abs(s[k+1]))) {
               e[k] = Real(0.0);
               break;
            }
         }
         if (k == p-2) {
            kase = 4;
         } else {
            int ks;
            for (ks = p-1; ks >= k; ks--) {
               if (ks == k) {
                  break;
               }
               double t = (ks != p ? abs(e[ks]) : 0.) + 
                          (ks != k+1 ? abs(e[ks-1]) : 0.);
               if (abs(s[ks]) <= eps*t)  {
                  s[ks] = Real(0.0);
                  break;
               }
            }
            if (ks == k) {
               kase = 3;
            } else if (ks == p-1) {
               kase = 1;
            } else {
               kase = 2;
               k = ks;
            }
         }
         k++;

         // Perform the task indicated by kase.

         switch (kase) {

            // Deflate negligible s(p).

            case 1: {
               double f = e[p-2];
               e[p-2] = Real(0.0);
               for (j = p-2; j >= k; j--) {
                  double t = hypot(s[j],f);
                  double cs = s[j]/t;
                  double sn = f/t;
                  s[j] = t;
                  if (j != k) {
                     f = -sn*e[j-1];
                     e[j-1] = cs*e[j-1];
                  }
                  if (wantv) {
                     for (i = 0; i < n; i++) {
                        t = cs*V[i][j] + sn*V[i][p-1];
                        V[i][p-1] = -sn*V[i][j] + cs*V[i][p-1];
                        V[i][j] = t;
                     }
                  }
               }
            }
            break;

            // Split at negligible s(k).

            case 2: {
               double f = e[k-1];
               e[k-1] = Real(0.0);
               for (j = k; j < p; j++) {
                  double t = hypot(s[j],f);
                  double cs = s[j]/t;
                  double sn = f/t;
                  s[j] = t;
                  f = -sn*e[j];
                  e[j] = cs*e[j];
                  if (wantu) {
                     for (i = 0; i < m; i++) {
                        t = cs*U[i][j] + sn*U[i][k-1];
                        U[i][k-1] = -sn*U[i][j] + cs*U[i][k-1];
                        U[i][j] = t;
                     }
                  }
               }
            }
            break;

            // Perform one qr step.

            case 3: {

               // Calculate the shift.
   
               double scale = max(max(max(max(
                       abs(s[p-1]),abs(s[p-2])),abs(e[p-2])), 
                       abs(s[k])),abs(e[k]));
               double sp = s[p-1]/scale;
               double spm1 = s[p-2]/scale;
               double epm1 = e[p-2]/scale;
               double sk = s[k]/scale;
               double ek = e[k]/scale;
               double b = ((spm1 + sp)*(spm1 - sp) + epm1*epm1)/2.0;
               double c = (sp*epm1)*(sp*epm1);
               double shift = Real(0.0);
               if ((b != Real(0.0)) || (c != Real(0.0))) {
                  shift = sqrt(b*b + c);
                  if (b < Real(0.0)) {
                     shift = -shift;
                  }
                  shift = c/(b + shift);
               }
               double f = (sk + sp)*(sk - sp) + shift;
               double g = sk*ek;
   
               // Chase zeros.
   
               for (j = k; j < p-1; j++) {
                  double t = hypot(f,g);
                  double cs = f/t;
                  double sn = g/t;
                  if (j != k) {
                     e[j-1] = t;
                  }
                  f = cs*s[j] + sn*e[j];
                  e[j] = cs*e[j] - sn*s[j];
                  g = sn*s[j+1];
                  s[j+1] = cs*s[j+1];
                  if (wantv) {
                     for (i = 0; i < n; i++) {
                        t = cs*V[i][j] + sn*V[i][j+1];
                        V[i][j+1] = -sn*V[i][j] + cs*V[i][j+1];
                        V[i][j] = t;
                     }
                  }
                  t = hypot(f,g);
                  cs = f/t;
                  sn = g/t;
                  s[j] = t;
                  f = cs*e[j] + sn*s[j+1];
                  s[j+1] = -sn*e[j] + cs*s[j+1];
                  g = sn*e[j+1];
                  e[j+1] = cs*e[j+1];
                  if (wantu && (j < m-1)) {
                     for (i = 0; i < m; i++) {
                        t = cs*U[i][j] + sn*U[i][j+1];
                        U[i][j+1] = -sn*U[i][j] + cs*U[i][j+1];
                        U[i][j] = t;
                     }
                  }
               }
               e[p-2] = f;
               iter = iter + 1;
            }
            break;

            // Convergence.

            case 4: {

               // Make the singular values positive.
   
               if (s[k] <= Real(0.0)) {
                  s[k] = (s[k] < Real(0.0) ? -s[k] : Real(0.0));
                  if (wantv) {
                     for (i = 0; i <= pp; i++) {
                        V[i][k] = -V[i][k];
                     }
                  }
               }
   
               // Order the singular values.
   
               while (k < pp) {
                  if (s[k] >= s[k+1]) {
                     break;
                  }
                  double t = s[k];
                  s[k] = s[k+1];
                  s[k+1] = t;
                  if (wantv && (k < n-1)) {
                     for (i = 0; i < n; i++) {
                        t = V[i][k+1]; V[i][k+1] = V[i][k]; V[i][k] = t;
                     }
                  }
                  if (wantu && (k < m-1)) {
                     for (i = 0; i < m; i++) {
                        t = U[i][k+1]; U[i][k+1] = U[i][k]; U[i][k] = t;
                     }
                  }
                  k++;
               }
               iter = 0;
               p--;
            }
            break;
         }
      }
   }


   void getU (Matrix<Real> &A) 
   {
          int minm = min(m+1,n);

          A = Matrix<Real>(m, minm);

          for (int i=0; i<m; i++)
                for (int j=0; j<minm; j++)
                        A[i][j] = U[i][j];
        
   }

   /* Return the right singular vectors */

   void getV (Matrix<Real> &A) 
   {
          A = V;
   }

   void getSingularValues (Vector<Real> &x) 
   {
      x = s;
   }

   void getS (Matrix<Real> &A) {
          A = Matrix<Real>(n,n);
      for (int i = 0; i < n; i++) {
         for (int j = 0; j < n; j++) {
            A[i][j] = Real(0.0);
         }
         A[i][i] = s[i];
      }
   }

   double norm2 () {
      return s[0];
   }

   double cond () {
      return s[0]/s[min(m,n)-1];
   }

   int rank () 
   {
      double eps = pow(2.0,-52.0);
      double tol = max(m,n)*s[0]*eps;
      int r = 0;
      for (int i = 0; i < s.dim(); i++) {
         if (s[i] > tol) {
            r++;
         }
      }
      return r;
   }
};

}  /* namespace Linear_Algebra */
}  /* namespace TNT */

#endif
// TNT_LINALG_H_

---