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dMatrix.cc
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1997-07-27
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// Matrix manipulations.
/*
Copyright (C) 1996 John W. Eaton
This file is part of Octave.
Octave is free software; you can redistribute it and/or modify it
under the terms of the GNU General Public License as published by the
Free Software Foundation; either version 2, or (at your option) any
later version.
Octave is distributed in the hope that it will be useful, but WITHOUT
ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
for more details.
You should have received a copy of the GNU General Public License
along with Octave; see the file COPYING. If not, write to the Free
Software Foundation, 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*/
#if defined (__GNUG__)
#pragma implementation
#endif
#ifdef HAVE_CONFIG_H
#include <config.h>
#endif
#include <cfloat>
#include <iostream.h>
#include "byte-swap.h"
#include "dbleAEPBAL.h"
#include "dbleDET.h"
#include "dbleSCHUR.h"
#include "dbleSVD.h"
#include "f77-fcn.h"
#include "lo-error.h"
#include "lo-ieee.h"
#include "lo-mappers.h"
#include "lo-utils.h"
#include "mx-base.h"
#include "mx-inlines.cc"
#include "oct-cmplx.h"
// Fortran functions we call.
extern "C"
{
int F77_FCN (dgemm, DGEMM) (const char*, const char*, const int&,
const int&, const int&, const double&,
const double*, const int&,
const double*, const int&,
const double&, double*, const int&,
long, long);
int F77_FCN (dgeco, DGECO) (double*, const int&, const int&, int*,
double&, double*);
int F77_FCN (dgesl, DGESL) (const double*, const int&, const int&,
const int*, double*, const int&);
int F77_FCN (dgedi, DGEDI) (double*, const int&, const int&,
const int*, double*, double*,
const int&);
int F77_FCN (dgelss, DGELSS) (const int&, const int&, const int&,
double*, const int&, double*,
const int&, double*, double&, int&,
double*, const int&, int&);
// Note that the original complex fft routines were not written for
// double complex arguments. They have been modified by adding an
// implicit double precision (a-h,o-z) statement at the beginning of
// each subroutine.
int F77_FCN (cffti, CFFTI) (const int&, Complex*);
int F77_FCN (cfftf, CFFTF) (const int&, Complex*, Complex*);
int F77_FCN (cfftb, CFFTB) (const int&, Complex*, Complex*);
int F77_FCN (dlartg, DLARTG) (const double&, const double&, double&,
double&, double&);
int F77_FCN (dtrsyl, DTRSYL) (const char*, const char*, const int&,
const int&, const int&, const double*,
const int&, const double*, const int&,
const double*, const int&, double&,
int&, long, long);
double F77_FCN (dlange, DLANGE) (const char*, const int&,
const int&, const double*,
const int&, double*);
int F77_FCN (qzhes, QZHES) (const int&, const int&, double*,
double*, const long&, double*);
int F77_FCN (qzit, QZIT) (const int&, const int&, double*, double*,
const double&, const long&, double*,
int&);
int F77_FCN (qzval, QZVAL) (const int&, const int&, double*,
double*, double*, double*, double*,
const long&, double*);
}
// Matrix class.
Matrix::Matrix (const RowVector& rv)
: MArray2<double> (1, rv.length (), 0.0)
{
for (int i = 0; i < rv.length (); i++)
elem (0, i) = rv.elem (i);
}
Matrix::Matrix (const ColumnVector& cv)
: MArray2<double> (cv.length (), 1, 0.0)
{
for (int i = 0; i < cv.length (); i++)
elem (i, 0) = cv.elem (i);
}
Matrix::Matrix (const DiagMatrix& a)
: MArray2<double> (a.rows (), a.cols (), 0.0)
{
for (int i = 0; i < a.length (); i++)
elem (i, i) = a.elem (i, i);
}
// XXX FIXME XXX -- could we use a templated mixed-type copy function
// here?
Matrix::Matrix (const charMatrix& a)
: MArray2<double> (a.rows (), a.cols ())
{
for (int i = 0; i < a.rows (); i++)
for (int j = 0; j < a.cols (); j++)
elem (i, j) = a.elem (i, j);
}
bool
Matrix::operator == (const Matrix& a) const
{
if (rows () != a.rows () || cols () != a.cols ())
return false;
return equal (data (), a.data (), length ());
}
bool
Matrix::operator != (const Matrix& a) const
{
return !(*this == a);
}
Matrix&
Matrix::insert (const Matrix& a, int r, int c)
{
Array2<double>::insert (a, r, c);
return *this;
}
Matrix&
Matrix::insert (const RowVector& a, int r, int c)
{
int a_len = a.length ();
if (r < 0 || r >= rows () || c < 0 || c + a_len > cols ())
{
(*current_liboctave_error_handler) ("range error for insert");
return *this;
}
for (int i = 0; i < a_len; i++)
elem (r, c+i) = a.elem (i);
return *this;
}
Matrix&
Matrix::insert (const ColumnVector& a, int r, int c)
{
int a_len = a.length ();
if (r < 0 || r + a_len > rows () || c < 0 || c >= cols ())
{
(*current_liboctave_error_handler) ("range error for insert");
return *this;
}
for (int i = 0; i < a_len; i++)
elem (r+i, c) = a.elem (i);
return *this;
}
Matrix&
Matrix::insert (const DiagMatrix& a, int r, int c)
{
int a_nr = a.rows ();
int a_nc = a.cols ();
if (r < 0 || r + a_nr > rows () || c < 0 || c + a_nc > cols ())
{
(*current_liboctave_error_handler) ("range error for insert");
return *this;
}
fill (0.0, r, c, r + a_nr - 1, c + a_nc - 1);
for (int i = 0; i < a.length (); i++)
elem (r+i, c+i) = a.elem (i, i);
return *this;
}
Matrix&
Matrix::fill (double val)
{
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
elem (i, j) = val;
return *this;
}
Matrix&
Matrix::fill (double val, int r1, int c1, int r2, int c2)
{
int nr = rows ();
int nc = cols ();
if (r1 < 0 || r2 < 0 || c1 < 0 || c2 < 0
|| r1 >= nr || r2 >= nr || c1 >= nc || c2 >= nc)
{
(*current_liboctave_error_handler) ("range error for fill");
return *this;
}
if (r1 > r2) { int tmp = r1; r1 = r2; r2 = tmp; }
if (c1 > c2) { int tmp = c1; c1 = c2; c2 = tmp; }
for (int j = c1; j <= c2; j++)
for (int i = r1; i <= r2; i++)
elem (i, j) = val;
return *this;
}
Matrix
Matrix::append (const Matrix& a) const
{
int nr = rows ();
int nc = cols ();
if (nr != a.rows ())
{
(*current_liboctave_error_handler) ("row dimension mismatch for append");
return Matrix ();
}
int nc_insert = nc;
Matrix retval (nr, nc + a.cols ());
retval.insert (*this, 0, 0);
retval.insert (a, 0, nc_insert);
return retval;
}
Matrix
Matrix::append (const RowVector& a) const
{
int nr = rows ();
int nc = cols ();
if (nr != 1)
{
(*current_liboctave_error_handler) ("row dimension mismatch for append");
return Matrix ();
}
int nc_insert = nc;
Matrix retval (nr, nc + a.length ());
retval.insert (*this, 0, 0);
retval.insert (a, 0, nc_insert);
return retval;
}
Matrix
Matrix::append (const ColumnVector& a) const
{
int nr = rows ();
int nc = cols ();
if (nr != a.length ())
{
(*current_liboctave_error_handler) ("row dimension mismatch for append");
return Matrix ();
}
int nc_insert = nc;
Matrix retval (nr, nc + 1);
retval.insert (*this, 0, 0);
retval.insert (a, 0, nc_insert);
return retval;
}
Matrix
Matrix::append (const DiagMatrix& a) const
{
int nr = rows ();
int nc = cols ();
if (nr != a.rows ())
{
(*current_liboctave_error_handler) ("row dimension mismatch for append");
return *this;
}
int nc_insert = nc;
Matrix retval (nr, nc + a.cols ());
retval.insert (*this, 0, 0);
retval.insert (a, 0, nc_insert);
return retval;
}
Matrix
Matrix::stack (const Matrix& a) const
{
int nr = rows ();
int nc = cols ();
if (nc != a.cols ())
{
(*current_liboctave_error_handler)
("column dimension mismatch for stack");
return Matrix ();
}
int nr_insert = nr;
Matrix retval (nr + a.rows (), nc);
retval.insert (*this, 0, 0);
retval.insert (a, nr_insert, 0);
return retval;
}
Matrix
Matrix::stack (const RowVector& a) const
{
int nr = rows ();
int nc = cols ();
if (nc != a.length ())
{
(*current_liboctave_error_handler)
("column dimension mismatch for stack");
return Matrix ();
}
int nr_insert = nr;
Matrix retval (nr + 1, nc);
retval.insert (*this, 0, 0);
retval.insert (a, nr_insert, 0);
return retval;
}
Matrix
Matrix::stack (const ColumnVector& a) const
{
int nr = rows ();
int nc = cols ();
if (nc != 1)
{
(*current_liboctave_error_handler)
("column dimension mismatch for stack");
return Matrix ();
}
int nr_insert = nr;
Matrix retval (nr + a.length (), nc);
retval.insert (*this, 0, 0);
retval.insert (a, nr_insert, 0);
return retval;
}
Matrix
Matrix::stack (const DiagMatrix& a) const
{
int nr = rows ();
int nc = cols ();
if (nc != a.cols ())
{
(*current_liboctave_error_handler)
("column dimension mismatch for stack");
return Matrix ();
}
int nr_insert = nr;
Matrix retval (nr + a.rows (), nc);
retval.insert (*this, 0, 0);
retval.insert (a, nr_insert, 0);
return retval;
}
Matrix
Matrix::transpose (void) const
{
int nr = rows ();
int nc = cols ();
Matrix result (nc, nr);
if (length () > 0)
{
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
result.elem (j, i) = elem (i, j);
}
return result;
}
Matrix
real (const ComplexMatrix& a)
{
int a_len = a.length ();
Matrix retval;
if (a_len > 0)
retval = Matrix (real_dup (a.data (), a_len), a.rows (), a.cols ());
return retval;
}
Matrix
imag (const ComplexMatrix& a)
{
int a_len = a.length ();
Matrix retval;
if (a_len > 0)
retval = Matrix (imag_dup (a.data (), a_len), a.rows (), a.cols ());
return retval;
}
Matrix
Matrix::extract (int r1, int c1, int r2, int c2) const
{
if (r1 > r2) { int tmp = r1; r1 = r2; r2 = tmp; }
if (c1 > c2) { int tmp = c1; c1 = c2; c2 = tmp; }
int new_r = r2 - r1 + 1;
int new_c = c2 - c1 + 1;
Matrix result (new_r, new_c);
for (int j = 0; j < new_c; j++)
for (int i = 0; i < new_r; i++)
result.elem (i, j) = elem (r1+i, c1+j);
return result;
}
// extract row or column i.
RowVector
Matrix::row (int i) const
{
int nc = cols ();
if (i < 0 || i >= rows ())
{
(*current_liboctave_error_handler) ("invalid row selection");
return RowVector ();
}
RowVector retval (nc);
for (int j = 0; j < nc; j++)
retval.elem (j) = elem (i, j);
return retval;
}
RowVector
Matrix::row (char *s) const
{
if (! s)
{
(*current_liboctave_error_handler) ("invalid row selection");
return RowVector ();
}
char c = *s;
if (c == 'f' || c == 'F')
return row (0);
else if (c == 'l' || c == 'L')
return row (rows () - 1);
else
{
(*current_liboctave_error_handler) ("invalid row selection");
return RowVector ();
}
}
ColumnVector
Matrix::column (int i) const
{
int nr = rows ();
if (i < 0 || i >= cols ())
{
(*current_liboctave_error_handler) ("invalid column selection");
return ColumnVector ();
}
ColumnVector retval (nr);
for (int j = 0; j < nr; j++)
retval.elem (j) = elem (j, i);
return retval;
}
ColumnVector
Matrix::column (char *s) const
{
if (! s)
{
(*current_liboctave_error_handler) ("invalid column selection");
return ColumnVector ();
}
char c = *s;
if (c == 'f' || c == 'F')
return column (0);
else if (c == 'l' || c == 'L')
return column (cols () - 1);
else
{
(*current_liboctave_error_handler) ("invalid column selection");
return ColumnVector ();
}
}
Matrix
Matrix::inverse (void) const
{
int info;
double rcond;
return inverse (info, rcond);
}
Matrix
Matrix::inverse (int& info) const
{
double rcond;
return inverse (info, rcond);
}
Matrix
Matrix::inverse (int& info, double& rcond, int force) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr != nc || nr == 0 || nc == 0)
(*current_liboctave_error_handler) ("inverse requires square matrix");
else
{
info = 0;
Array<int> ipvt (nr);
int *pipvt = ipvt.fortran_vec ();
Array<double> z (nr);
double *pz = z.fortran_vec ();
retval = *this;
double *tmp_data = retval.fortran_vec ();
F77_XFCN (dgeco, DGECO, (tmp_data, nr, nc, pipvt, rcond, pz));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dgeco");
else
{
volatile double rcond_plus_one = rcond + 1.0;
if (rcond_plus_one == 1.0)
info = -1;
if (info == -1 && ! force)
retval = *this; // Restore matrix contents.
else
{
double *dummy = 0;
F77_XFCN (dgedi, DGEDI, (tmp_data, nr, nc, pipvt, dummy,
pz, 1));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgedi");
}
}
}
return retval;
}
Matrix
Matrix::pseudo_inverse (double tol)
{
SVD result (*this);
DiagMatrix S = result.singular_values ();
Matrix U = result.left_singular_matrix ();
Matrix V = result.right_singular_matrix ();
ColumnVector sigma = S.diag ();
int r = sigma.length () - 1;
int nr = rows ();
int nc = cols ();
if (tol <= 0.0)
{
if (nr > nc)
tol = nr * sigma.elem (0) * DBL_EPSILON;
else
tol = nc * sigma.elem (0) * DBL_EPSILON;
}
while (r >= 0 && sigma.elem (r) < tol)
r--;
if (r < 0)
return Matrix (nc, nr, 0.0);
else
{
Matrix Ur = U.extract (0, 0, nr-1, r);
DiagMatrix D = DiagMatrix (sigma.extract (0, r)) . inverse ();
Matrix Vr = V.extract (0, 0, nc-1, r);
return Vr * D * Ur.transpose ();
}
}
ComplexMatrix
Matrix::fourier (void) const
{
ComplexMatrix retval;
int nr = rows ();
int nc = cols ();
int npts, nsamples;
if (nr == 1 || nc == 1)
{
npts = nr > nc ? nr : nc;
nsamples = 1;
}
else
{
npts = nr;
nsamples = nc;
}
int nn = 4*npts+15;
Array<Complex> wsave (nn);
Complex *pwsave = wsave.fortran_vec ();
retval = *this;
Complex *tmp_data = retval.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
F77_FCN (cfftf, CFFTF) (npts, &tmp_data[npts*j], pwsave);
return retval;
}
ComplexMatrix
Matrix::ifourier (void) const
{
ComplexMatrix retval;
int nr = rows ();
int nc = cols ();
int npts, nsamples;
if (nr == 1 || nc == 1)
{
npts = nr > nc ? nr : nc;
nsamples = 1;
}
else
{
npts = nr;
nsamples = nc;
}
int nn = 4*npts+15;
Array<Complex> wsave (nn);
Complex *pwsave = wsave.fortran_vec ();
retval = *this;
Complex *tmp_data = retval.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
F77_FCN (cfftb, CFFTB) (npts, &tmp_data[npts*j], pwsave);
for (int j = 0; j < npts*nsamples; j++)
tmp_data[j] = tmp_data[j] / (double) npts;
return retval;
}
ComplexMatrix
Matrix::fourier2d (void) const
{
ComplexMatrix retval;
int nr = rows ();
int nc = cols ();
int npts, nsamples;
if (nr == 1 || nc == 1)
{
npts = nr > nc ? nr : nc;
nsamples = 1;
}
else
{
npts = nr;
nsamples = nc;
}
int nn = 4*npts+15;
Array<Complex> wsave (nn);
Complex *pwsave = wsave.fortran_vec ();
retval = *this;
Complex *tmp_data = retval.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
F77_FCN (cfftf, CFFTF) (npts, &tmp_data[npts*j], pwsave);
npts = nc;
nsamples = nr;
nn = 4*npts+15;
wsave.resize (nn);
pwsave = wsave.fortran_vec ();
Array<Complex> row (npts);
Complex *prow = row.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
{
for (int i = 0; i < npts; i++)
prow[i] = tmp_data[i*nr + j];
F77_FCN (cfftf, CFFTF) (npts, prow, pwsave);
for (int i = 0; i < npts; i++)
tmp_data[i*nr + j] = prow[i];
}
return retval;
}
ComplexMatrix
Matrix::ifourier2d (void) const
{
ComplexMatrix retval;
int nr = rows ();
int nc = cols ();
int npts, nsamples;
if (nr == 1 || nc == 1)
{
npts = nr > nc ? nr : nc;
nsamples = 1;
}
else
{
npts = nr;
nsamples = nc;
}
int nn = 4*npts+15;
Array<Complex> wsave (nn);
Complex *pwsave = wsave.fortran_vec ();
retval = *this;
Complex *tmp_data = retval.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
F77_FCN (cfftb, CFFTB) (npts, &tmp_data[npts*j], pwsave);
for (int j = 0; j < npts*nsamples; j++)
tmp_data[j] = tmp_data[j] / (double) npts;
npts = nc;
nsamples = nr;
nn = 4*npts+15;
wsave.resize (nn);
pwsave = wsave.fortran_vec ();
Array<Complex> row (npts);
Complex *prow = row.fortran_vec ();
F77_FCN (cffti, CFFTI) (npts, pwsave);
for (int j = 0; j < nsamples; j++)
{
for (int i = 0; i < npts; i++)
prow[i] = tmp_data[i*nr + j];
F77_FCN (cfftb, CFFTB) (npts, prow, pwsave);
for (int i = 0; i < npts; i++)
tmp_data[i*nr + j] = prow[i] / (double) npts;
}
return retval;
}
DET
Matrix::determinant (void) const
{
int info;
double rcond;
return determinant (info, rcond);
}
DET
Matrix::determinant (int& info) const
{
double rcond;
return determinant (info, rcond);
}
DET
Matrix::determinant (int& info, double& rcond) const
{
DET retval;
int nr = rows ();
int nc = cols ();
if (nr == 0 || nc == 0)
{
double d[2];
d[0] = 1.0;
d[1] = 0.0;
retval = DET (d);
}
else
{
info = 0;
Array<int> ipvt (nr);
int *pipvt = ipvt.fortran_vec ();
Array<double> z (nr);
double *pz = z.fortran_vec ();
Matrix atmp = *this;
double *tmp_data = atmp.fortran_vec ();
F77_XFCN (dgeco, DGECO, (tmp_data, nr, nr, pipvt, rcond, pz));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dgeco");
else
{
volatile double rcond_plus_one = rcond + 1.0;
if (rcond_plus_one == 1.0)
{
info = -1;
retval = DET ();
}
else
{
double d[2];
F77_XFCN (dgedi, DGEDI, (tmp_data, nr, nr, pipvt, d, pz, 10));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgedi");
else
retval = DET (d);
}
}
}
return retval;
}
Matrix
Matrix::solve (const Matrix& b) const
{
int info;
double rcond;
return solve (b, info, rcond);
}
Matrix
Matrix::solve (const Matrix& b, int& info) const
{
double rcond;
return solve (b, info, rcond);
}
Matrix
Matrix::solve (const Matrix& b, int& info, double& rcond) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 0 || nc == 0 || nr != nc || nr != b.rows ())
(*current_liboctave_error_handler)
("matrix dimension mismatch solution of linear equations");
else
{
info = 0;
Array<int> ipvt (nr);
int *pipvt = ipvt.fortran_vec ();
Array<double> z (nr);
double *pz = z.fortran_vec ();
Matrix atmp = *this;
double *tmp_data = atmp.fortran_vec ();
F77_XFCN (dgeco, DGECO, (tmp_data, nr, nr, pipvt, rcond, pz));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dgeco");
else
{
volatile double rcond_plus_one = rcond + 1.0;
if (rcond_plus_one == 1.0)
{
info = -2;
}
else
{
retval = b;
double *result = retval.fortran_vec ();
int b_nc = b.cols ();
for (volatile int j = 0; j < b_nc; j++)
{
F77_XFCN (dgesl, DGESL, (tmp_data, nr, nr, pipvt,
&result[nr*j], 0));
if (f77_exception_encountered)
{
(*current_liboctave_error_handler)
("unrecoverable error in dgesl");
break;
}
}
}
}
}
return retval;
}
ComplexMatrix
Matrix::solve (const ComplexMatrix& b) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b);
}
ComplexMatrix
Matrix::solve (const ComplexMatrix& b, int& info) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b, info);
}
ComplexMatrix
Matrix::solve (const ComplexMatrix& b, int& info, double& rcond) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b, info, rcond);
}
ColumnVector
Matrix::solve (const ColumnVector& b) const
{
int info; double rcond;
return solve (b, info, rcond);
}
ColumnVector
Matrix::solve (const ColumnVector& b, int& info) const
{
double rcond;
return solve (b, info, rcond);
}
ColumnVector
Matrix::solve (const ColumnVector& b, int& info, double& rcond) const
{
ColumnVector retval;
int nr = rows ();
int nc = cols ();
if (nr == 0 || nc == 0 || nr != nc || nr != b.length ())
(*current_liboctave_error_handler)
("matrix dimension mismatch solution of linear equations");
else
{
info = 0;
Array<int> ipvt (nr);
int *pipvt = ipvt.fortran_vec ();
Array<double> z (nr);
double *pz = z.fortran_vec ();
Matrix atmp = *this;
double *tmp_data = atmp.fortran_vec ();
F77_XFCN (dgeco, DGECO, (tmp_data, nr, nr, pipvt, rcond, pz));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgeco");
else
{
volatile double rcond_plus_one = rcond + 1.0;
if (rcond_plus_one == 1.0)
{
info = -2;
}
else
{
retval = b;
double *result = retval.fortran_vec ();
F77_XFCN (dgesl, DGESL, (tmp_data, nr, nr, pipvt, result, 0));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgesl");
}
}
}
return retval;
}
ComplexColumnVector
Matrix::solve (const ComplexColumnVector& b) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b);
}
ComplexColumnVector
Matrix::solve (const ComplexColumnVector& b, int& info) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b, info);
}
ComplexColumnVector
Matrix::solve (const ComplexColumnVector& b, int& info, double& rcond) const
{
ComplexMatrix tmp (*this);
return tmp.solve (b, info, rcond);
}
Matrix
Matrix::lssolve (const Matrix& b) const
{
int info;
int rank;
return lssolve (b, info, rank);
}
Matrix
Matrix::lssolve (const Matrix& b, int& info) const
{
int rank;
return lssolve (b, info, rank);
}
Matrix
Matrix::lssolve (const Matrix& b, int& info, int& rank) const
{
Matrix retval;
int nrhs = b.cols ();
int m = rows ();
int n = cols ();
if (m == 0 || n == 0 || m != b.rows ())
(*current_liboctave_error_handler)
("matrix dimension mismatch in solution of least squares problem");
else
{
Matrix atmp = *this;
double *tmp_data = atmp.fortran_vec ();
int nrr = m > n ? m : n;
Matrix result (nrr, nrhs);
for (int j = 0; j < nrhs; j++)
for (int i = 0; i < m; i++)
result.elem (i, j) = b.elem (i, j);
double *presult = result.fortran_vec ();
int len_s = m < n ? m : n;
Array<double> s (len_s);
double *ps = s.fortran_vec ();
double rcond = -1.0;
int lwork;
if (m < n)
lwork = 3*m + (2*m > nrhs
? (2*m > n ? 2*m : n)
: (nrhs > n ? nrhs : n));
else
lwork = 3*n + (2*n > nrhs
? (2*n > m ? 2*n : m)
: (nrhs > m ? nrhs : m));
lwork *= 16;
Array<double> work (lwork);
double *pwork = work.fortran_vec ();
F77_XFCN (dgelss, DGELSS, (m, n, nrhs, tmp_data, m, presult, nrr, ps,
rcond, rank, pwork, lwork, info));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dgelss");
else
{
retval.resize (n, nrhs);
for (int j = 0; j < nrhs; j++)
for (int i = 0; i < n; i++)
retval.elem (i, j) = result.elem (i, j);
}
}
return retval;
}
ComplexMatrix
Matrix::lssolve (const ComplexMatrix& b) const
{
ComplexMatrix tmp (*this);
int info;
int rank;
return tmp.lssolve (b, info, rank);
}
ComplexMatrix
Matrix::lssolve (const ComplexMatrix& b, int& info) const
{
ComplexMatrix tmp (*this);
int rank;
return tmp.lssolve (b, info, rank);
}
ComplexMatrix
Matrix::lssolve (const ComplexMatrix& b, int& info, int& rank) const
{
ComplexMatrix tmp (*this);
return tmp.lssolve (b, info, rank);
}
ColumnVector
Matrix::lssolve (const ColumnVector& b) const
{
int info;
int rank;
return lssolve (b, info, rank);
}
ColumnVector
Matrix::lssolve (const ColumnVector& b, int& info) const
{
int rank;
return lssolve (b, info, rank);
}
ColumnVector
Matrix::lssolve (const ColumnVector& b, int& info, int& rank) const
{
ColumnVector retval;
int nrhs = 1;
int m = rows ();
int n = cols ();
if (m == 0 || n == 0 || m != b.length ())
(*current_liboctave_error_handler)
("matrix dimension mismatch in solution of least squares problem");
else
{
Matrix atmp = *this;
double *tmp_data = atmp.fortran_vec ();
int nrr = m > n ? m : n;
ColumnVector result (nrr);
for (int i = 0; i < m; i++)
result.elem (i) = b.elem (i);
double *presult = result.fortran_vec ();
int len_s = m < n ? m : n;
Array<double> s (len_s);
double *ps = s.fortran_vec ();
double rcond = -1.0;
int lwork;
if (m < n)
lwork = 3*m + (2*m > nrhs
? (2*m > n ? 2*m : n)
: (nrhs > n ? nrhs : n));
else
lwork = 3*n + (2*n > nrhs
? (2*n > m ? 2*n : m)
: (nrhs > m ? nrhs : m));
lwork *= 16;
Array<double> work (lwork);
double *pwork = work.fortran_vec ();
F77_XFCN (dgelss, DGELSS, (m, n, nrhs, tmp_data, m, presult, nrr,
ps, rcond, rank, pwork, lwork, info));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dgelss");
else
{
retval.resize (n);
for (int i = 0; i < n; i++)
retval.elem (i) = result.elem (i);
}
}
return retval;
}
ComplexColumnVector
Matrix::lssolve (const ComplexColumnVector& b) const
{
ComplexMatrix tmp (*this);
return tmp.lssolve (b);
}
ComplexColumnVector
Matrix::lssolve (const ComplexColumnVector& b, int& info) const
{
ComplexMatrix tmp (*this);
return tmp.lssolve (b, info);
}
ComplexColumnVector
Matrix::lssolve (const ComplexColumnVector& b, int& info, int& rank) const
{
ComplexMatrix tmp (*this);
return tmp.lssolve (b, info, rank);
}
// Constants for matrix exponential calculation.
static double padec [] =
{
5.0000000000000000e-1,
1.1666666666666667e-1,
1.6666666666666667e-2,
1.6025641025641026e-3,
1.0683760683760684e-4,
4.8562548562548563e-6,
1.3875013875013875e-7,
1.9270852604185938e-9,
};
Matrix
Matrix::expm (void) const
{
Matrix retval;
Matrix m = *this;
int nc = columns ();
// trace shift value
double trshift = 0;
// Preconditioning step 1: trace normalization.
for (int i = 0; i < nc; i++)
trshift += m.elem (i, i);
trshift /= nc;
for (int i = 0; i < nc; i++)
m.elem (i, i) -= trshift;
// Preconditioning step 2: balancing.
AEPBALANCE mbal (m, "B");
m = mbal.balanced_matrix ();
Matrix d = mbal.balancing_matrix ();
// Preconditioning step 3: scaling.
ColumnVector work(nc);
double inf_norm
= F77_FCN (dlange, DLANGE) ("I", nc, nc, m.fortran_vec (),nc,
work.fortran_vec ());
int sqpow = (int) (inf_norm > 0.0
? (1.0 + log (inf_norm) / log (2.0))
: 0.0);
// Check whether we need to square at all.
if (sqpow < 0)
sqpow = 0;
if (sqpow > 0)
{
double scale_factor = 1.0;
for (int i = 0; i < sqpow; i++)
scale_factor *= 2.0;
m = m / scale_factor;
}
// npp, dpp: pade' approx polynomial matrices.
Matrix npp (nc, nc, 0.0);
Matrix dpp = npp;
// Now powers a^8 ... a^1.
int minus_one_j = -1;
for (int j = 7; j >= 0; j--)
{
npp = m * npp + m * padec[j];
dpp = m * dpp + m * (minus_one_j * padec[j]);
minus_one_j *= -1;
}
// Zero power.
dpp = -dpp;
for(int j = 0; j < nc; j++)
{
npp.elem (j, j) += 1.0;
dpp.elem (j, j) += 1.0;
}
// Compute pade approximation = inverse (dpp) * npp.
retval = dpp.solve (npp);
// Reverse preconditioning step 3: repeated squaring.
while (sqpow)
{
retval = retval * retval;
sqpow--;
}
// Reverse preconditioning step 2: inverse balancing.
retval = retval.transpose();
d = d.transpose ();
retval = retval * d;
retval = d.solve (retval);
retval = retval.transpose ();
// Reverse preconditioning step 1: fix trace normalization.
return retval * exp (trshift);
}
Matrix&
Matrix::operator += (const Matrix& a)
{
int nr = rows ();
int nc = cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator +=", nr, nc, a_nr, a_nc);
return *this;
}
if (nr == 0 || nc == 0)
return *this;
double *d = fortran_vec (); // Ensures only one reference to my privates!
add2 (d, a.data (), length ());
return *this;
}
Matrix&
Matrix::operator -= (const Matrix& a)
{
int nr = rows ();
int nc = cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator -=", nr, nc, a_nr, a_nc);
return *this;
}
if (nr == 0 || nc == 0)
return *this;
double *d = fortran_vec (); // Ensures only one reference to my privates!
subtract2 (d, a.data (), length ());
return *this;
}
Matrix&
Matrix::operator += (const DiagMatrix& a)
{
int nr = rows ();
int nc = cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator +=", nr, nc, a_nr, a_nc);
return *this;
}
for (int i = 0; i < a.length (); i++)
elem (i, i) += a.elem (i, i);
return *this;
}
Matrix&
Matrix::operator -= (const DiagMatrix& a)
{
int nr = rows ();
int nc = cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator -=", nr, nc, a_nr, a_nc);
return *this;
}
for (int i = 0; i < a.length (); i++)
elem (i, i) -= a.elem (i, i);
return *this;
}
// unary operations
Matrix
Matrix::operator ! (void) const
{
int nr = rows ();
int nc = cols ();
Matrix b (nr, nc);
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
b.elem (i, j) = ! elem (i, j);
return b;
}
// column vector by row vector -> matrix operations
Matrix
operator * (const ColumnVector& v, const RowVector& a)
{
Matrix retval;
int len = v.length ();
int a_len = a.length ();
if (len != a_len)
gripe_nonconformant ("operator *", len, 1, 1, a_len);
else
{
if (len != 0)
{
retval.resize (len, a_len);
double *c = retval.fortran_vec ();
F77_XFCN (dgemm, DGEMM, ("N", "N", len, a_len, 1, 1.0,
v.data (), len, a.data (), 1, 0.0,
c, len, 1L, 1L));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgemm");
}
}
return retval;
}
// diagonal matrix by scalar -> matrix operations
Matrix
operator + (const DiagMatrix& a, double s)
{
Matrix tmp (a.rows (), a.cols (), s);
return a + tmp;
}
Matrix
operator - (const DiagMatrix& a, double s)
{
Matrix tmp (a.rows (), a.cols (), -s);
return a + tmp;
}
// scalar by diagonal matrix -> matrix operations
Matrix
operator + (double s, const DiagMatrix& a)
{
Matrix tmp (a.rows (), a.cols (), s);
return tmp + a;
}
Matrix
operator - (double s, const DiagMatrix& a)
{
Matrix tmp (a.rows (), a.cols (), s);
return tmp - a;
}
// matrix by diagonal matrix -> matrix operations
Matrix
operator + (const Matrix& m, const DiagMatrix& a)
{
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator +", nr, nc, a_nr, a_nc);
return Matrix ();
}
if (nr == 0 || nc == 0)
return Matrix (nr, nc);
Matrix result (m);
int a_len = a.length ();
for (int i = 0; i < a_len; i++)
result.elem (i, i) += a.elem (i, i);
return result;
}
Matrix
operator - (const Matrix& m, const DiagMatrix& a)
{
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator -", nr, nc, a_nr, a_nc);
return Matrix ();
}
if (nr == 0 || nc == 0)
return Matrix (nr, nc);
Matrix result (m);
int a_len = a.length ();
for (int i = 0; i < a_len; i++)
result.elem (i, i) -= a.elem (i, i);
return result;
}
Matrix
operator * (const Matrix& m, const DiagMatrix& a)
{
Matrix retval;
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nc != a_nr)
gripe_nonconformant ("operator *", nr, nc, a_nr, a_nc);
else
{
if (nr == 0 || nc == 0 || a_nc == 0)
retval.resize (nr, a_nc, 0.0);
else
{
retval.resize (nr, a_nc);
double *c = retval.fortran_vec ();
double *ctmp = 0;
int a_len = a.length ();
for (int j = 0; j < a_len; j++)
{
int idx = j * nr;
ctmp = c + idx;
if (a.elem (j, j) == 1.0)
{
for (int i = 0; i < nr; i++)
ctmp[i] = m.elem (i, j);
}
else if (a.elem (j, j) == 0.0)
{
for (int i = 0; i < nr; i++)
ctmp[i] = 0.0;
}
else
{
for (int i = 0; i < nr; i++)
ctmp[i] = a.elem (j, j) * m.elem (i, j);
}
}
if (a_nr < a_nc)
{
for (int i = nr * nc; i < nr * a_nc; i++)
ctmp[i] = 0.0;
}
}
}
return retval;
}
// diagonal matrix by matrix -> matrix operations
Matrix
operator + (const DiagMatrix& m, const Matrix& a)
{
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator +", nr, nc, a_nr, a_nc);
return Matrix ();
}
if (nr == 0 || nc == 0)
return Matrix (nr, nc);
Matrix result (a);
for (int i = 0; i < m.length (); i++)
result.elem (i, i) += m.elem (i, i);
return result;
}
Matrix
operator - (const DiagMatrix& m, const Matrix& a)
{
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nr != a_nr || nc != a_nc)
{
gripe_nonconformant ("operator -", nr, nc, a_nr, a_nc);
return Matrix ();
}
if (nr == 0 || nc == 0)
return Matrix (nr, nc);
Matrix result (-a);
for (int i = 0; i < m.length (); i++)
result.elem (i, i) += m.elem (i, i);
return result;
}
Matrix
operator * (const DiagMatrix& m, const Matrix& a)
{
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nc != a_nr)
{
gripe_nonconformant ("operator *", nr, nc, a_nr, a_nc);
return Matrix ();
}
if (nr == 0 || nc == 0 || a_nc == 0)
return Matrix (nr, a_nc, 0.0);
Matrix c (nr, a_nc);
for (int i = 0; i < m.length (); i++)
{
if (m.elem (i, i) == 1.0)
{
for (int j = 0; j < a_nc; j++)
c.elem (i, j) = a.elem (i, j);
}
else if (m.elem (i, i) == 0.0)
{
for (int j = 0; j < a_nc; j++)
c.elem (i, j) = 0.0;
}
else
{
for (int j = 0; j < a_nc; j++)
c.elem (i, j) = m.elem (i, i) * a.elem (i, j);
}
}
if (nr > nc)
{
for (int j = 0; j < a_nc; j++)
for (int i = a_nr; i < nr; i++)
c.elem (i, j) = 0.0;
}
return c;
}
// matrix by matrix -> matrix operations
Matrix
operator * (const Matrix& m, const Matrix& a)
{
Matrix retval;
int nr = m.rows ();
int nc = m.cols ();
int a_nr = a.rows ();
int a_nc = a.cols ();
if (nc != a_nr)
gripe_nonconformant ("operator *", nr, nc, a_nr, a_nc);
else
{
if (nr == 0 || nc == 0 || a_nc == 0)
retval.resize (nr, a_nc, 0.0);
else
{
int ld = nr;
int lda = a_nr;
retval.resize (nr, a_nc);
double *c = retval.fortran_vec ();
F77_XFCN (dgemm, DGEMM, ("N", "N", nr, a_nc, nc, 1.0,
m.data (), ld, a.data (), lda, 0.0,
c, nr, 1L, 1L));
if (f77_exception_encountered)
(*current_liboctave_error_handler)
("unrecoverable error in dgemm");
}
}
return retval;
}
// other operations.
Matrix
Matrix::map (d_d_Mapper f) const
{
Matrix b (*this);
return b.apply (f);
}
Matrix&
Matrix::apply (d_d_Mapper f)
{
double *d = fortran_vec (); // Ensures only one reference to my privates!
for (int i = 0; i < length (); i++)
d[i] = f (d[i]);
return *this;
}
bool
Matrix::any_element_is_negative (void) const
{
int nr = rows ();
int nc = cols ();
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
if (elem (i, j) < 0.0)
return true;
return false;
}
bool
Matrix::any_element_is_inf_or_nan (void) const
{
int nr = rows ();
int nc = cols ();
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
{
double val = elem (i, j);
if (xisinf (val) || xisnan (val))
return 1;
}
return 0;
}
bool
Matrix::all_elements_are_int_or_inf_or_nan (void) const
{
int nr = rows ();
int nc = cols ();
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
{
double val = elem (i, j);
if (xisnan (val) || D_NINT (val) == val)
continue;
else
return false;
}
return true;
}
// Return nonzero if any element of M is not an integer. Also extract
// the largest and smallest values and return them in MAX_VAL and MIN_VAL.
bool
Matrix::all_integers (double& max_val, double& min_val) const
{
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
{
max_val = elem (0, 0);
min_val = elem (0, 0);
}
else
return false;
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
{
double val = elem (i, j);
if (val > max_val)
max_val = val;
if (val < min_val)
min_val = val;
if (D_NINT (val) != val)
return false;
}
return true;
}
bool
Matrix::too_large_for_float (void) const
{
int nr = rows ();
int nc = cols ();
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
{
double val = elem (i, j);
if (val > FLT_MAX || val < FLT_MIN)
return true;
}
return false;
}
// XXX FIXME XXX Do these really belong here? They should maybe be
// cleaned up a bit, no? What about corresponding functions for the
// Vectors?
Matrix
Matrix::all (void) const
{
int nr = rows ();
int nc = cols ();
Matrix retval;
if (nr > 0 && nc > 0)
{
if (nr == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 1.0;
for (int j = 0; j < nc; j++)
{
if (elem (0, j) == 0.0)
{
retval.elem (0, 0) = 0.0;
break;
}
}
}
else if (nc == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 1.0;
for (int i = 0; i < nr; i++)
{
if (elem (i, 0) == 0.0)
{
retval.elem (0, 0) = 0.0;
break;
}
}
}
else
{
retval.resize (1, nc);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = 1.0;
for (int i = 0; i < nr; i++)
{
if (elem (i, j) == 0.0)
{
retval.elem (0, j) = 0.0;
break;
}
}
}
}
}
return retval;
}
Matrix
Matrix::any (void) const
{
int nr = rows ();
int nc = cols ();
Matrix retval;
if (nr > 0 && nc > 0)
{
if (nr == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int j = 0; j < nc; j++)
{
if (elem (0, j) != 0.0)
{
retval.elem (0, 0) = 1.0;
break;
}
}
}
else if (nc == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int i = 0; i < nr; i++)
{
if (elem (i, 0) != 0.0)
{
retval.elem (0, 0) = 1.0;
break;
}
}
}
else
{
retval.resize (1, nc);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = 0.0;
for (int i = 0; i < nr; i++)
{
if (elem (i, j) != 0.0)
{
retval.elem (0, j) = 1.0;
break;
}
}
}
}
}
return retval;
}
Matrix
Matrix::cumprod (void) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 1)
{
retval.resize (1, nc);
if (nc > 0)
{
double prod = elem (0, 0);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = prod;
if (j < nc - 1)
prod *= elem (0, j+1);
}
}
}
else if (nc == 1)
{
retval.resize (nr, 1);
if (nr > 0)
{
double prod = elem (0, 0);
for (int i = 0; i < nr; i++)
{
retval.elem (i, 0) = prod;
if (i < nr - 1)
prod *= elem (i+1, 0);
}
}
}
else
{
retval.resize (nr, nc);
if (nr > 0 && nc > 0)
{
for (int j = 0; j < nc; j++)
{
double prod = elem (0, j);
for (int i = 0; i < nr; i++)
{
retval.elem (i, j) = prod;
if (i < nr - 1)
prod *= elem (i+1, j);
}
}
}
}
return retval;
}
Matrix
Matrix::cumsum (void) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 1)
{
retval.resize (1, nc);
if (nc > 0)
{
double sum = elem (0, 0);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = sum;
if (j < nc - 1)
sum += elem (0, j+1);
}
}
}
else if (nc == 1)
{
retval.resize (nr, 1);
if (nr > 0)
{
double sum = elem (0, 0);
for (int i = 0; i < nr; i++)
{
retval.elem (i, 0) = sum;
if (i < nr - 1)
sum += elem (i+1, 0);
}
}
}
else
{
retval.resize (nr, nc);
if (nr > 0 && nc > 0)
{
for (int j = 0; j < nc; j++)
{
double sum = elem (0, j);
for (int i = 0; i < nr; i++)
{
retval.elem (i, j) = sum;
if (i < nr - 1)
sum += elem (i+1, j);
}
}
}
}
return retval;
}
Matrix
Matrix::prod (void) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 1.0;
for (int j = 0; j < nc; j++)
retval.elem (0, 0) *= elem (0, j);
}
else if (nc == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 1.0;
for (int i = 0; i < nr; i++)
retval.elem (0, 0) *= elem (i, 0);
}
else
{
if (nc == 0)
{
retval.resize (1, 1);
retval.elem (0, 0) = 1.0;
}
else
retval.resize (1, nc);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = 1.0;
for (int i = 0; i < nr; i++)
retval.elem (0, j) *= elem (i, j);
}
}
return retval;
}
Matrix
Matrix::sum (void) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int j = 0; j < nc; j++)
retval.elem (0, 0) += elem (0, j);
}
else if (nc == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int i = 0; i < nr; i++)
retval.elem (0, 0) += elem (i, 0);
}
else
{
if (nc == 0)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
}
else
retval.resize (1, nc);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = 0.0;
for (int i = 0; i < nr; i++)
retval.elem (0, j) += elem (i, j);
}
}
return retval;
}
Matrix
Matrix::sumsq (void) const
{
Matrix retval;
int nr = rows ();
int nc = cols ();
if (nr == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int j = 0; j < nc; j++)
{
double d = elem (0, j);
retval.elem (0, 0) += d * d;
}
}
else if (nc == 1)
{
retval.resize (1, 1);
retval.elem (0, 0) = 0.0;
for (int i = 0; i < nr; i++)
{
double d = elem (i, 0);
retval.elem (0, 0) += d * d;
}
}
else
{
retval.resize (1, nc);
for (int j = 0; j < nc; j++)
{
retval.elem (0, j) = 0.0;
for (int i = 0; i < nr; i++)
{
double d = elem (i, j);
retval.elem (0, j) += d * d;
}
}
}
return retval;
}
Matrix
Matrix::abs (void) const
{
int nr = rows ();
int nc = cols ();
Matrix retval (nr, nc);
for (int j = 0; j < nc; j++)
for (int i = 0; i < nr; i++)
retval (i, j) = fabs (elem (i, j));
return retval;
}
ColumnVector
Matrix::diag (void) const
{
return diag (0);
}
ColumnVector
Matrix::diag (int k) const
{
int nnr = rows ();
int nnc = cols ();
if (k > 0)
nnc -= k;
else if (k < 0)
nnr += k;
ColumnVector d;
if (nnr > 0 && nnc > 0)
{
int ndiag = (nnr < nnc) ? nnr : nnc;
d.resize (ndiag);
if (k > 0)
{
for (int i = 0; i < ndiag; i++)
d.elem (i) = elem (i, i+k);
}
else if ( k < 0)
{
for (int i = 0; i < ndiag; i++)
d.elem (i) = elem (i-k, i);
}
else
{
for (int i = 0; i < ndiag; i++)
d.elem (i) = elem (i, i);
}
}
else
cerr << "diag: requested diagonal out of range\n";
return d;
}
ColumnVector
Matrix::row_min (void) const
{
Array<int> index;
return row_min (index);
}
ColumnVector
Matrix::row_min (Array<int>& index) const
{
ColumnVector result;
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
{
result.resize (nr);
index.resize (nr);
for (int i = 0; i < nr; i++)
{
int idx = 0;
double tmp_min = elem (i, idx);
if (xisnan (tmp_min))
idx = -1;
else
{
for (int j = 1; j < nc; j++)
{
double tmp = elem (i, j);
if (xisnan (tmp))
{
idx = -1;
break;
}
else if (tmp < tmp_min)
{
idx = j;
tmp_min = tmp;
}
}
}
result.elem (i) = (idx < 0) ? octave_NaN : tmp_min;
index.elem (i) = idx;
}
}
return result;
}
ColumnVector
Matrix::row_max (void) const
{
Array<int> index;
return row_max (index);
}
ColumnVector
Matrix::row_max (Array<int>& index) const
{
ColumnVector result;
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
{
result.resize (nr);
index.resize (nr);
for (int i = 0; i < nr; i++)
{
int idx = 0;
double tmp_max = elem (i, idx);
if (xisnan (tmp_max))
idx = -1;
else
{
for (int j = 1; j < nc; j++)
{
double tmp = elem (i, j);
if (xisnan (tmp))
{
idx = -1;
break;
}
else if (tmp > tmp_max)
{
idx = j;
tmp_max = tmp;
}
}
}
result.elem (i) = (idx < 0) ? octave_NaN : tmp_max;
index.elem (i) = idx;
}
}
return result;
}
RowVector
Matrix::column_min (void) const
{
Array<int> index;
return column_min (index);
}
RowVector
Matrix::column_min (Array<int>& index) const
{
RowVector result;
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
{
result.resize (nc);
index.resize (nc);
for (int j = 0; j < nc; j++)
{
int idx = 0;
double tmp_min = elem (idx, j);
if (xisnan (tmp_min))
idx = -1;
else
{
for (int i = 1; i < nr; i++)
{
double tmp = elem (i, j);
if (xisnan (tmp))
{
idx = -1;
break;
}
else if (tmp < tmp_min)
{
idx = i;
tmp_min = tmp;
}
}
}
result.elem (j) = (idx < 0) ? octave_NaN : tmp_min;
index.elem (j) = idx;
}
}
return result;
}
RowVector
Matrix::column_max (void) const
{
Array<int> index;
return column_max (index);
}
RowVector
Matrix::column_max (Array<int>& index) const
{
RowVector result;
int nr = rows ();
int nc = cols ();
if (nr > 0 && nc > 0)
{
result.resize (nc);
index.resize (nc);
for (int j = 0; j < nc; j++)
{
int idx = 0;
double tmp_max = elem (idx, j);
if (xisnan (tmp_max))
idx = -1;
else
{
for (int i = 1; i < nr; i++)
{
double tmp = elem (i, j);
if (xisnan (tmp))
{
idx = -1;
break;
}
else if (tmp > tmp_max)
{
idx = i;
tmp_max = tmp;
}
}
}
result.elem (j) = (idx < 0) ? octave_NaN : tmp_max;
index.elem (j) = idx;
}
}
return result;
}
ostream&
operator << (ostream& os, const Matrix& a)
{
// int field_width = os.precision () + 7;
for (int i = 0; i < a.rows (); i++)
{
for (int j = 0; j < a.cols (); j++)
os << " " /* setw (field_width) */ << a.elem (i, j);
os << "\n";
}
return os;
}
istream&
operator >> (istream& is, Matrix& a)
{
int nr = a.rows ();
int nc = a.cols ();
if (nr < 1 || nc < 1)
is.clear (ios::badbit);
else
{
double tmp;
for (int i = 0; i < nr; i++)
for (int j = 0; j < nc; j++)
{
is >> tmp;
if (is)
a.elem (i, j) = tmp;
else
goto done;
}
}
done:
return is;
}
template <class T>
static void
read_int (istream& is, bool swap_bytes, T& val)
{
is.read ((char *) &val, sizeof (T));
if (swap_bytes)
{
switch (sizeof (T))
{
case 1:
break;
case 2:
swap_2_bytes ((char *) &val);
break;
case 4:
swap_4_bytes ((char *) &val);
break;
case 8:
swap_8_bytes ((char *) &val);
break;
default:
(*current_liboctave_error_handler)
("read_int: unrecognized data format!");
}
}
}
template void read_int (istream&, bool, char&);
template void read_int (istream&, bool, signed char&);
template void read_int (istream&, bool, unsigned char&);
template void read_int (istream&, bool, short&);
template void read_int (istream&, bool, unsigned short&);
template void read_int (istream&, bool, int&);
template void read_int (istream&, bool, unsigned int&);
template void read_int (istream&, bool, long&);
template void read_int (istream&, bool, unsigned long&);
static inline bool
do_read (istream& is, oct_data_conv::data_type dt,
oct_mach_info::float_format flt_fmt, bool swap_bytes,
bool do_float_conversion, double& val)
{
bool retval = true;
switch (dt)
{
case oct_data_conv::dt_char:
{
char tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_schar:
{
signed char tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_uchar:
{
unsigned char tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_short:
{
short tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_ushort:
{
unsigned short tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_int:
{
int tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_uint:
{
unsigned int tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_long:
{
long tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_ulong:
{
unsigned long tmp;
read_int (is, swap_bytes, tmp);
val = tmp;
}
break;
case oct_data_conv::dt_float:
{
float f;
is.read ((char *) &f, sizeof (float));
if (do_float_conversion)
do_float_format_conversion (&f, 1, flt_fmt);
val = f;
}
break;
case oct_data_conv::dt_double:
{
is.read ((char *) &val, sizeof (double));
if (do_float_conversion)
do_double_format_conversion (&val, 1, flt_fmt);
}
break;
default:
retval = false;
(*current_liboctave_error_handler)
("read: invalid type specification");
break;
}
return retval;
}
int
Matrix::read (istream& is, int nr, int nc,
oct_data_conv::data_type dt, int skip,
oct_mach_info::float_format flt_fmt)
{
int retval = -1;
bool ok = true;
int count = 0;
double *data = 0;
int max_size = 0;
int final_nr = 0;
int final_nc = 0;
if (nr > 0)
{
if (nc > 0)
{
resize (nr, nc, 0.0);
data = fortran_vec ();
max_size = nr * nc;
}
else
{
resize (nr, 32, 0.0);
data = fortran_vec ();
max_size = nr * 32;
}
}
else
{
resize (32, 1, 0.0);
data = fortran_vec ();
max_size = 32;
}
oct_mach_info::float_format native_flt_fmt
= oct_mach_info::float_format ();
bool do_float_conversion = (flt_fmt != native_flt_fmt);
// XXX FIXME XXX -- byte order for Cray?
bool swap_bytes = false;
if (oct_mach_info::words_big_endian ())
swap_bytes = (flt_fmt == oct_mach_info::ieee_little_endian
|| flt_fmt == oct_mach_info::vax_g
|| flt_fmt == oct_mach_info::vax_g);
else
swap_bytes = (flt_fmt == oct_mach_info::ieee_big_endian);
for (;;)
{
// XXX FIXME XXX -- maybe there should be a special case for
// skip == 0.
if (is)
{
if (nr > 0 && nc > 0 && count == max_size)
{
final_nr = nr;
final_nc = nc;
break;
}
if (skip != 0)
is.seekg (skip, ios::cur);
if (is)
{
double tmp = 0.0;
ok = do_read (is, dt, flt_fmt, swap_bytes,
do_float_conversion, tmp);
if (ok)
{
if (is)
{
if (count == max_size)
{
max_size *= 2;
if (nr > 0)
resize (nr, max_size / nr, 0.0);
else
resize (max_size, 1, 0.0);
data = fortran_vec ();
}
data[count++] = tmp;
}
else
{
if (is.eof ())
{
if (nr > 0)
{
if (count > nr)
{
final_nr = nr;
final_nc = (count - 1) / nr + 1;
}
else
{
final_nr = count;
final_nc = 1;
}
}
else
{
final_nr = count;
final_nc = 1;
}
}
break;
}
}
else
break;
}
else
{
ok = false;
break;
}
}
else
{
ok = false;
break;
}
}
if (ok)
{
resize (final_nr, final_nc, 0.0);
retval = count;
}
return retval;
}
template <class T>
static void
write_int (ostream& os, bool swap_bytes, T val)
{
if (swap_bytes)
{
switch (sizeof (T))
{
case 1:
break;
case 2:
swap_2_bytes ((char *) &val);
break;
case 4:
swap_4_bytes ((char *) &val);
break;
case 8:
swap_8_bytes ((char *) &val);
break;
default:
(*current_liboctave_error_handler)
("write_int: unrecognized data format!");
}
}
os.write ((char *) &val, sizeof (T));
}
template void write_int (ostream&, bool, char);
template void write_int (ostream&, bool, signed char);
template void write_int (ostream&, bool, unsigned char);
template void write_int (ostream&, bool, short);
template void write_int (ostream&, bool, unsigned short);
template void write_int (ostream&, bool, int);
template void write_int (ostream&, bool, unsigned int);
template void write_int (ostream&, bool, long);
template void write_int (ostream&, bool, unsigned long);
static inline bool
do_write (ostream& os, double d, oct_data_conv::data_type dt,
oct_mach_info::float_format flt_fmt, bool swap_bytes,
bool do_float_conversion)
{
bool retval = true;
switch (dt)
{
case oct_data_conv::dt_char:
write_int (os, swap_bytes, (char) d);
break;
case oct_data_conv::dt_schar:
write_int (os, swap_bytes, (signed char) d);
break;
case oct_data_conv::dt_uchar:
write_int (os, swap_bytes, (unsigned char) d);
break;
case oct_data_conv::dt_short:
write_int (os, swap_bytes, (short) d);
break;
case oct_data_conv::dt_ushort:
write_int (os, swap_bytes, (unsigned short) d);
break;
case oct_data_conv::dt_int:
write_int (os, swap_bytes, (int) d);
break;
case oct_data_conv::dt_uint:
write_int (os, swap_bytes, (unsigned int) d);
break;
case oct_data_conv::dt_long:
write_int (os, swap_bytes, (long) d);
break;
case oct_data_conv::dt_ulong:
write_int (os, swap_bytes, (unsigned long) d);
break;
case oct_data_conv::dt_float:
{
float f = (float) d;
if (do_float_conversion)
do_float_format_conversion (&f, 1, flt_fmt);
os.write ((char *) &f, sizeof (float));
}
break;
case oct_data_conv::dt_double:
{
if (do_float_conversion)
do_double_format_conversion (&d, 1, flt_fmt);
os.write ((char *) &d, sizeof (double));
}
break;
default:
retval = false;
(*current_liboctave_error_handler)
("write: invalid type specification");
break;
}
return retval;
}
int
Matrix::write (ostream& os, oct_data_conv::data_type dt, int skip,
oct_mach_info::float_format flt_fmt)
{
int retval = -1;
bool ok = true;
int count = 0;
const double *d = data ();
int n = length ();
oct_mach_info::float_format native_flt_fmt
= oct_mach_info::float_format ();
bool do_float_conversion = (flt_fmt != native_flt_fmt);
// XXX FIXME XXX -- byte order for Cray?
bool swap_bytes = false;
if (oct_mach_info::words_big_endian ())
swap_bytes = (flt_fmt == oct_mach_info::ieee_little_endian
|| flt_fmt == oct_mach_info::vax_g
|| flt_fmt == oct_mach_info::vax_g);
else
swap_bytes = (flt_fmt == oct_mach_info::ieee_big_endian);
for (int i = 0; i < n; i++)
{
if (os)
{
if (skip != 0)
os.seekp (skip, ios::cur);
if (os)
{
ok = do_write (os, d[i], dt, flt_fmt, swap_bytes,
do_float_conversion);
if (os && ok)
count++;
else
break;
}
else
{
ok = false;
break;
}
}
else
{
ok = false;
break;
}
}
if (ok)
retval = count;
return retval;
}
Matrix
Givens (double x, double y)
{
double cc, s, temp_r;
F77_FCN (dlartg, DLARTG) (x, y, cc, s, temp_r);
Matrix g (2, 2);
g.elem (0, 0) = cc;
g.elem (1, 1) = cc;
g.elem (0, 1) = s;
g.elem (1, 0) = -s;
return g;
}
Matrix
Sylvester (const Matrix& a, const Matrix& b, const Matrix& c)
{
Matrix retval;
// XXX FIXME XXX -- need to check that a, b, and c are all the same
// size.
// Compute Schur decompositions.
SCHUR as (a, "U");
SCHUR bs (b, "U");
// Transform c to new coordinates.
Matrix ua = as.unitary_matrix ();
Matrix sch_a = as.schur_matrix ();
Matrix ub = bs.unitary_matrix ();
Matrix sch_b = bs.schur_matrix ();
Matrix cx = ua.transpose () * c * ub;
// Solve the sylvester equation, back-transform, and return the
// solution.
int a_nr = a.rows ();
int b_nr = b.rows ();
double scale;
int info;
double *pa = sch_a.fortran_vec ();
double *pb = sch_b.fortran_vec ();
double *px = cx.fortran_vec ();
F77_XFCN (dtrsyl, DTRSYL, ("N", "N", 1, a_nr, b_nr, pa, a_nr, pb,
b_nr, px, a_nr, scale, info, 1L, 1L));
if (f77_exception_encountered)
(*current_liboctave_error_handler) ("unrecoverable error in dtrsyl");
else
{
// XXX FIXME XXX -- check info?
retval = -ua*cx*ub.transpose ();
}
return retval;
}
ComplexColumnVector
Qzval (const Matrix& a, const Matrix& b)
{
ComplexColumnVector retval;
int a_nr = a.rows();
int a_nc = a.cols();
int b_nr = b.rows();
int b_nc = b.cols();
if (a_nr == a_nc)
{
if (a_nr == b_nr && a_nc == b_nc)
{
if (a_nr != 0)
{
Matrix jnk (a_nr, a_nr, 0.0);
double *pjnk = jnk.fortran_vec ();
ColumnVector alfr (a_nr);
double *palfr = alfr.fortran_vec ();
ColumnVector alfi (a_nr);
double *palfi = alfi.fortran_vec ();
ColumnVector beta (a_nr);
double *pbeta = beta.fortran_vec ();
Matrix atmp = a;
double *pa = atmp.fortran_vec ();
Matrix btmp = b;
double *pb = btmp.fortran_vec ();
long matz = 0;
int info;
// XXX FIXME ??? XXX
double eps = DBL_EPSILON;
F77_FCN (qzhes, QZHES) (a_nr, a_nr, pa, pb, matz, pjnk);
F77_FCN (qzit, QZIT) (a_nr, a_nr, pa, pb, eps, matz, pjnk, info);
if (! info)
{
F77_FCN (qzval, QZVAL) (a_nr, a_nr, pa, pb, palfr,
palfi, pbeta, matz, pjnk);
// Count and extract finite generalized eigenvalues.
int cnt = 0;
for (int i = 0; i < a_nr; i++)
if (beta(i) != 0)
cnt++;
ComplexColumnVector cx (cnt);
cnt = 0;
for (int i = 0; i < a_nr; i++)
{
if (beta(i) != 0)
{
// Finite generalized eigenvalue.
cx(cnt++) = Complex (alfr(i), alfi(i)) / beta(i);
}
}
retval = cx;
}
else
(*current_liboctave_error_handler)
("qzval: trouble in qzit, info = %d", info);
}
}
else
gripe_nonconformant ("qzval", a_nr, a_nc, b_nr, b_nc);
}
else
(*current_liboctave_error_handler) ("qzval: square matrices required");
return retval;
}
/*
;;; Local Variables: ***
;;; mode: C++ ***
;;; End: ***
*/