# include <cstdlib>
# include <iostream>
# include <iomanip>
# include <cmath>
# include <ctime>
# include <cstring>

using namespace std;

# include "jacobi_eigenvalue.hpp"

//****************************************************************************80

void jacobi_eigenvalue ( int n, double a[], int it_max, double v[], 
  double d[], int &it_num, int &rot_num )

//****************************************************************************80
//
//  Purpose:
//
//    JACOBI_EIGENVALUE carries out the Jacobi eigenvalue iteration.
//
//  Discussion:
//
//    This function computes the eigenvalues and eigenvectors of a
//    real symmetric matrix, using Rutishauser's modfications of the classical
//    Jacobi rotation method with threshold pivoting. 
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    17 September 2013
//
//  Author:
//
//    John Burkardt
//
//  Reference:
//
//    Gene Golub, Charles VanLoan,
//    Matrix Computations,
//    Third Edition,
//    Johns Hopkins, 1996,
//    ISBN: 0-8018-4513-X,
//    LC: QA188.G65.
//
//  Input:
//
//    int N, the order of the matrix.
//
//    double A[N*N], the matrix, which must be square, real,
//    and symmetric.
//
//    int IT_MAX, the maximum number of iterations.
//
//  Output:
//
//    double V[N*N], the matrix of eigenvectors.
//
//    double D[N], the eigenvalues, in descending order.
//
//    int &IT_NUM, the total number of iterations.
//
//    int &ROT_NUM, the total number of rotations.
//
{
  double *bw;
  double c;
  double g;
  double gapq;
  double h;
  int i;
  int j;
  int k;
  int l;
  int m;
  int p;
  int q;
  double s;
  double t;
  double tau;
  double term;
  double termp;
  double termq;
  double theta;
  double thresh;
  double w;
  double *zw;

  r8mat_identity ( n, v );

  r8mat_diag_get_vector ( n, a, d );

  bw = new double[n];
  zw = new double[n];

  for ( i = 0; i < n; i++ )
  {
    bw[i] = d[i];
    zw[i] = 0.0;
  }
  it_num = 0;
  rot_num = 0;

  while ( it_num < it_max )
  {
    it_num = it_num + 1;
//
//  The convergence threshold is based on the size of the elements in
//  the strict upper triangle of the matrix.
//
    thresh = 0.0;
    for ( j = 0; j < n; j++ )
    {
      for ( i = 0; i < j; i++ )
      {
        thresh = thresh + a[i+j*n] * a[i+j*n];
      }
    }

    thresh = sqrt ( thresh ) / ( double ) ( 4 * n );

    if ( thresh == 0.0 )
    {
      break;
    }

    for ( p = 0; p < n; p++ )
    {
      for ( q = p + 1; q < n; q++ )
      {
        gapq = 10.0 * fabs ( a[p+q*n] );
        termp = gapq + fabs ( d[p] );
        termq = gapq + fabs ( d[q] );
//
//  Annihilate tiny offdiagonal elements.
//
        if ( 4 < it_num &&
             termp == fabs ( d[p] ) &&
             termq == fabs ( d[q] ) )
        {
          a[p+q*n] = 0.0;
        }
//
//  Otherwise, apply a rotation.
//
        else if ( thresh <= fabs ( a[p+q*n] ) )
        {
          h = d[q] - d[p];
          term = fabs ( h ) + gapq;

          if ( term == fabs ( h ) )
          {
            t = a[p+q*n] / h;
          }
          else
          {
            theta = 0.5 * h / a[p+q*n];
            t = 1.0 / ( fabs ( theta ) + sqrt ( 1.0 + theta * theta ) );
            if ( theta < 0.0 )
            {
              t = - t;
            }
          }
          c = 1.0 / sqrt ( 1.0 + t * t );
          s = t * c;
          tau = s / ( 1.0 + c );
          h = t * a[p+q*n];
//
//  Accumulate corrections to diagonal elements.
//
          zw[p] = zw[p] - h;                 
          zw[q] = zw[q] + h;
          d[p] = d[p] - h;
          d[q] = d[q] + h;

          a[p+q*n] = 0.0;
//
//  Rotate, using information from the upper triangle of A only.
//
          for ( j = 0; j < p; j++ )
          {
            g = a[j+p*n];
            h = a[j+q*n];
            a[j+p*n] = g - s * ( h + g * tau );
            a[j+q*n] = h + s * ( g - h * tau );
          }

          for ( j = p + 1; j < q; j++ )
          {
            g = a[p+j*n];
            h = a[j+q*n];
            a[p+j*n] = g - s * ( h + g * tau );
            a[j+q*n] = h + s * ( g - h * tau );
          }

          for ( j = q + 1; j < n; j++ )
          {
            g = a[p+j*n];
            h = a[q+j*n];
            a[p+j*n] = g - s * ( h + g * tau );
            a[q+j*n] = h + s * ( g - h * tau );
          }
//
//  Accumulate information in the eigenvector matrix.
//
          for ( j = 0; j < n; j++ )
          {
            g = v[j+p*n];
            h = v[j+q*n];
            v[j+p*n] = g - s * ( h + g * tau );
            v[j+q*n] = h + s * ( g - h * tau );
          }
          rot_num = rot_num + 1;
        }
      }
    }

    for ( i = 0; i < n; i++ )
    {
      bw[i] = bw[i] + zw[i];
      d[i] = bw[i];
      zw[i] = 0.0;
    }
  }
//
//  Restore upper triangle of input matrix.
//
  for ( j = 0; j < n; j++ )
  {
    for ( i = 0; i < j; i++ )
    {
      a[i+j*n] = a[j+i*n];
    }
  }
//
//  Ascending sort the eigenvalues and eigenvectors.
//
  for ( k = 0; k < n - 1; k++ )
  {
    m = k;
    for ( l = k + 1; l < n; l++ )
    {
      if ( d[l] < d[m] )
      {
        m = l;
      }
    }

    if ( m != k )
    {
      t    = d[m];
      d[m] = d[k];
      d[k] = t;
      for ( i = 0; i < n; i++ )
      {
        w        = v[i+m*n];
        v[i+m*n] = v[i+k*n];
        v[i+k*n] = w;
      }
    }
  }

  delete [] bw;
  delete [] zw;

  return;
}
//****************************************************************************80

void r8mat_diag_get_vector ( int n, double a[], double v[] )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_DIAG_GET_VECTOR gets the value of the diagonal of an R8MAT.
//
//  Discussion:
//
//    An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
//    in column-major order.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    15 July 2013
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int N, the number of rows and columns of the matrix.
//
//    double A[N*N], the N by N matrix.
//
//  Output:
//
//    double V[N], the diagonal entries
//    of the matrix.
//
{
  int i;

  for ( i = 0; i < n; i++ )
  {
    v[i] = a[i+i*n];
  }

  return;
}
//****************************************************************************80

void r8mat_identity ( int n, double a[] )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_IDENTITY sets the square matrix A to the identity.
//
//  Discussion:
//
//    An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
//    in column-major order.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    01 December 2011
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int N, the order of A.
//
//  Output:
//
//    double A[N*N], the N by N identity matrix.
//
{
  int i;
  int j;
  int k;

  k = 0;
  for ( j = 0; j < n; j++ )
  {
    for ( i = 0; i < n; i++ )
    {
      if ( i == j )
      {
        a[k] = 1.0;
      }
      else
      {
        a[k] = 0.0;
      }
      k = k + 1;
    }
  }

  return;
}
//****************************************************************************80

double r8mat_is_eigen_right ( int n, int k, double a[], double x[],
  double lambda[] )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_IS_EIGEN_RIGHT determines the error in a (right) eigensystem.
//
//  Discussion:
//
//    An R8MAT is a matrix of doubles.
//
//    This routine computes the Frobenius norm of
//
//      A * X - X * LAMBDA
//
//    where
//
//      A is an N by N matrix,
//      X is an N by K matrix (each of K columns is an eigenvector)
//      LAMBDA is a K by K diagonal matrix of eigenvalues.
//
//    This routine assumes that A, X and LAMBDA are all real.
//
//  Licensing:
//
//    This code is distributed under the MIT license. 
//
//  Modified:
//
//    07 October 2010
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int N, the order of the matrix.
//
//    int K, the number of eigenvectors.
//    K is usually 1 or N.
//
//    double A[N*N], the matrix.
//
//    double X[N*K], the K eigenvectors.
//
//    double LAMBDA[K], the K eigenvalues.
//
//  Output:
//
//    double R8MAT_IS_EIGEN_RIGHT, the Frobenius norm
//    of the difference matrix A * X - X * LAMBDA, which would be exactly zero
//    if X and LAMBDA were exact eigenvectors and eigenvalues of A.
//
{
  double *c;
  double error_frobenius;
  int i;
  int j;
  int l;

  c = new double[n*k];

  for ( j = 0; j < k; j++ )
  {
    for ( i = 0; i < n; i++ )
    {
      c[i+j*n] = 0.0;
      for ( l = 0; l < n; l++ )
      {
        c[i+j*n] = c[i+j*n] + a[i+l*n] * x[l+j*n];
      }
    }
  }

  for ( j = 0; j < k; j++ )
  {
    for ( i = 0; i < n; i++ )
    {
      c[i+j*n] = c[i+j*n] - lambda[j] * x[i+j*n];
    }
  }

  error_frobenius = r8mat_norm_fro ( n, k, c );

  delete [] c;

  return error_frobenius;
}
//****************************************************************************80

double r8mat_norm_fro ( int m, int n, double a[] )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_NORM_FRO returns the Frobenius norm of an R8MAT.
//
//  Discussion:
//
//    An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
//    in column-major order.
//
//    The Frobenius norm is defined as
//
//      R8MAT_NORM_FRO = sqrt (
//        sum ( 1 <= I <= M ) sum ( 1 <= j <= N ) A(I,J)^2 )
//    The matrix Frobenius norm is not derived from a vector norm, but
//    is compatible with the vector L2 norm, so that:
//
//      r8vec_norm_l2 ( A * x ) <= r8mat_norm_fro ( A ) * r8vec_norm_l2 ( x ).
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    10 October 2005
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int M, the number of rows in A.
//
//    int N, the number of columns in A.
//
//    double A[M*N], the matrix whose Frobenius
//    norm is desired.
//
//  Output:
//
//    double R8MAT_NORM_FRO, the Frobenius norm of A.
//
{
  int i;
  int j;
  double value;

  value = 0.0;
  for ( j = 0; j < n; j++ )
  {
    for ( i = 0; i < m; i++ )
    {
      value = value + pow ( a[i+j*m], 2 );
    }
  }
  value = sqrt ( value );

  return value;
}
//****************************************************************************80

void r8mat_print ( int m, int n, double a[], string title )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_PRINT prints an R8MAT.
//
//  Discussion:
//
//    An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
//    in column-major order.
//
//    Entry A(I,J) is stored as A[I+J*M]
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    10 September 2009
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int M, the number of rows in A.
//
//    int N, the number of columns in A.
//
//    double A[M*N], the M by N matrix.
//
//    string TITLE, a title.
//
{
  r8mat_print_some ( m, n, a, 1, 1, m, n, title );

  return;
}
//****************************************************************************80

void r8mat_print_some ( int m, int n, double a[], int ilo, int jlo, int ihi,
  int jhi, string title )

//****************************************************************************80
//
//  Purpose:
//
//    R8MAT_PRINT_SOME prints some of an R8MAT.
//
//  Discussion:
//
//    An R8MAT is a doubly dimensioned array of R8 values, stored as a vector
//    in column-major order.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    26 June 2013
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int M, the number of rows of the matrix.
//    M must be positive.
//
//    int N, the number of columns of the matrix.
//    N must be positive.
//
//    double A[M*N], the matrix.
//
//    int ILO, JLO, IHI, JHI, designate the first row and
//    column, and the last row and column to be printed.
//
//    string TITLE, a title.
//
{
# define INCX 5

  int i;
  int i2hi;
  int i2lo;
  int j;
  int j2hi;
  int j2lo;

  cout << "\n";
  cout << title << "\n";

  if ( m <= 0 || n <= 0 )
  {
    cout << "\n";
    cout << "  (None)\n";
    return;
  }
//
//  Print the columns of the matrix, in strips of 5.
//
  for ( j2lo = jlo; j2lo <= jhi; j2lo = j2lo + INCX )
  {
    j2hi = j2lo + INCX - 1;
    if ( n < j2hi )
    {
      j2hi = n;
    }
    if ( jhi < j2hi )
    {
      j2hi = jhi;
    }
    cout << "\n";
//
//  For each column J in the current range...
//
//  Write the header.
//
    cout << "  Col:    ";
    for ( j = j2lo; j <= j2hi; j++ )
    {
      cout << setw(7) << j - 1 << "       ";
    }
    cout << "\n";
    cout << "  Row\n";
    cout << "\n";
//
//  Determine the range of the rows in this strip.
//
    if ( 1 < ilo )
    {
      i2lo = ilo;
    }
    else
    {
      i2lo = 1;
    }
    if ( ihi < m )
    {
      i2hi = ihi;
    }
    else
    {
      i2hi = m;
    }

    for ( i = i2lo; i <= i2hi; i++ )
    {
//
//  Print out (up to) 5 entries in row I, that lie in the current strip.
//
      cout << setw(5) << i - 1 << ": ";
      for ( j = j2lo; j <= j2hi; j++ )
      {
        cout << setw(12) << a[i-1+(j-1)*m] << "  ";
      }
      cout << "\n";
    }
  }

  return;
# undef INCX
}
//****************************************************************************80

void r8vec_print ( int n, double a[], string title )

//****************************************************************************80
//
//  Purpose:
//
//    R8VEC_PRINT prints an R8VEC.
//
//  Discussion:
//
//    An R8VEC is a vector of R8's.
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    16 August 2004
//
//  Author:
//
//    John Burkardt
//
//  Input:
//
//    int N, the number of components of the vector.
//
//    double A[N], the vector to be printed.
//
//    string TITLE, a title.
//
{
  int i;

  cout << "\n";
  cout << title << "\n";
  cout << "\n";
  for ( i = 0; i < n; i++ )
  {
    cout << "  " << setw(8)  << i
         << ": " << setw(14) << a[i]  << "\n";
  }

  return;
}
//****************************************************************************80

void timestamp ( )

//****************************************************************************80
//
//  Purpose:
//
//    TIMESTAMP prints the current YMDHMS date as a time stamp.
//
//  Example:
//
//    31 May 2001 09:45:54 AM
//
//  Licensing:
//
//    This code is distributed under the MIT license.
//
//  Modified:
//
//    08 July 2009
//
//  Author:
//
//    John Burkardt
//
{
# define TIME_SIZE 40

  static char time_buffer[TIME_SIZE];
  const struct std::tm *tm_ptr;
  std::time_t now;

  now = std::time ( NULL );
  tm_ptr = std::localtime ( &now );

  std::strftime ( time_buffer, TIME_SIZE, "%d %B %Y %I:%M:%S %p", tm_ptr );

  std::cout << time_buffer << "\n";

  return;
# undef TIME_SIZE
}