# include # include # include # include # include # include 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 GNU LGPL license. // // Modified: // // 17 September 2013 // // Author: // // C++ version by John Burkardt // // Parameters: // // Input, int N, the order of the matrix. // // Input, double A[N*N], the matrix, which must be square, real, // and symmetric. // // Input, int IT_MAX, the maximum number of iterations. // // Output, double V[N*N], the matrix of eigenvectors. // // Output, double D[N], the eigenvalues, in descending order. // // Output, int &IT_NUM, the total number of iterations. // // Output, 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 GNU LGPL license. // // Modified: // // 15 July 2013 // // Author: // // John Burkardt // // Parameters: // // Input, int N, the number of rows and columns of the matrix. // // Input, 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 GNU LGPL license. // // Modified: // // 01 December 2011 // // Author: // // John Burkardt // // Parameters: // // 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 GNU LGPL license. // // Modified: // // 07 October 2010 // // Author: // // John Burkardt // // Parameters: // // Input, int N, the order of the matrix. // // Input, int K, the number of eigenvectors. // K is usually 1 or N. // // Input, double A[N*N], the matrix. // // Input, double X[N*K], the K eigenvectors. // // Input, 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 GNU LGPL license. // // Modified: // // 10 October 2005 // // Author: // // John Burkardt // // Parameters: // // Input, int M, the number of rows in A. // // Input, int N, the number of columns in A. // // Input, 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 GNU LGPL license. // // Modified: // // 10 September 2009 // // Author: // // John Burkardt // // Parameters: // // Input, int M, the number of rows in A. // // Input, int N, the number of columns in A. // // Input, double A[M*N], the M by N matrix. // // Input, 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 GNU LGPL license. // // Modified: // // 26 June 2013 // // Author: // // John Burkardt // // Parameters: // // Input, int M, the number of rows of the matrix. // M must be positive. // // Input, int N, the number of columns of the matrix. // N must be positive. // // Input, double A[M*N], the matrix. // // Input, int ILO, JLO, IHI, JHI, designate the first row and // column, and the last row and column to be printed. // // Input, 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 GNU LGPL license. // // Modified: // // 16 August 2004 // // Author: // // John Burkardt // // Parameters: // // Input, int N, the number of components of the vector. // // Input, double A[N], the vector to be printed. // // Input, 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 GNU LGPL license. // // Modified: // // 08 July 2009 // // Author: // // John Burkardt // // Parameters: // // None // { # define TIME_SIZE 40 static char time_buffer[TIME_SIZE]; const struct std::tm *tm_ptr; size_t len; std::time_t now; now = std::time ( NULL ); tm_ptr = std::localtime ( &now ); len = std::strftime ( time_buffer, TIME_SIZE, "%d %B %Y %I:%M:%S %p", tm_ptr ); std::cout << time_buffer << "\n"; return; # undef TIME_SIZE }