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////////////////////////////////////////////////////////////////////////
//
// Copyright (C) 1998-2021 The Octave Project Developers
//
// See the file COPYRIGHT.md in the top-level directory of this
// distribution or <https://octave.org/copyright/>.
//
// 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 3 of the License, 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, see
// <https://www.gnu.org/licenses/>.
//
////////////////////////////////////////////////////////////////////////
#if defined (HAVE_CONFIG_H)
# include "config.h"
#endif
#include <cmath>
#include <algorithm>
#include <string>
#include "CSparse.h"
#include "boolSparse.h"
#include "dColVector.h"
#include "dSparse.h"
#include "oct-locbuf.h"
#include "oct-sparse.h"
#include "oct-spparms.h"
#include "sparse-util.h"
#include "defun.h"
#include "error.h"
#include "errwarn.h"
#include "ovl.h"
#include "parse.h"
#include "utils.h"
DEFUN (symbfact, args, nargout,
doc: /* -*- texinfo -*-
@deftypefn {} {[@var{count}, @var{h}, @var{parent}, @var{post}, @var{R}] =} symbfact (@var{S})
@deftypefnx {} {[@dots{}] =} symbfact (@var{S}, @var{typ})
@deftypefnx {} {[@dots{}] =} symbfact (@var{S}, @var{typ}, @var{mode})
Perform a symbolic factorization analysis of the sparse matrix @var{S}.
The input variables are
@table @var
@item S
@var{S} is a real or complex sparse matrix.
@item typ
Is the type of the factorization and can be one of
@table @asis
@item @qcode{"sym"} (default)
Factorize @var{S}. Assumes @var{S} is symmetric and uses the upper
triangular portion of the matrix.
@item @qcode{"col"}
Factorize @tcode{@var{S}' * @var{S}}.
@item @qcode{"row"}
Factorize @tcode{@var{S} * @var{S}'}.
@item @qcode{"lo"}
Factorize @tcode{@var{S}'}. Assumes @var{S} is symmetric and uses the lower
triangular portion of the matrix.
@end table
@item mode
When @var{mode} is unspecified return the Cholesky@tie{}factorization for
@var{R}. If @var{mode} is @qcode{"lower"} or @qcode{"L"} then return
the conjugate transpose @tcode{@var{R}'} which is a lower triangular factor.
The conjugate transpose version is faster and uses less memory, but still
returns the same values for all other outputs: @var{count}, @var{h},
@var{parent}, and @var{post}.
@end table
The output variables are:
@table @var
@item count
The row counts of the Cholesky@tie{}factorization as determined by
@var{typ}. The computational difficulty of performing the true
factorization using @code{chol} is @code{sum (@var{count} .^ 2)}.
@item h
The height of the elimination tree.
@item parent
The elimination tree itself.
@item post
A sparse boolean matrix whose structure is that of the
Cholesky@tie{}factorization as determined by @var{typ}.
@end table
@seealso{chol, etree, treelayout}
@end deftypefn */)
{
#if defined (HAVE_CHOLMOD)
int nargin = args.length ();
if (nargin < 1 || nargin > 3)
print_usage ();
octave_value_list retval;
double dummy;
cholmod_sparse Astore;
cholmod_sparse *A = &Astore;
A->packed = true;
A->sorted = true;
A->nz = nullptr;
#if defined (OCTAVE_ENABLE_64)
A->itype = CHOLMOD_LONG;
#else
A->itype = CHOLMOD_INT;
#endif
A->dtype = CHOLMOD_DOUBLE;
A->stype = 1;
A->x = &dummy;
if (args(0).isreal ())
{
const SparseMatrix a = args(0).sparse_matrix_value ();
A->nrow = a.rows ();
A->ncol = a.cols ();
A->p = a.cidx ();
A->i = a.ridx ();
A->nzmax = a.nnz ();
A->xtype = CHOLMOD_REAL;
if (a.rows () > 0 && a.cols () > 0)
A->x = a.data ();
}
else if (args(0).iscomplex ())
{
const SparseComplexMatrix a = args(0).sparse_complex_matrix_value ();
A->nrow = a.rows ();
A->ncol = a.cols ();
A->p = a.cidx ();
A->i = a.ridx ();
A->nzmax = a.nnz ();
A->xtype = CHOLMOD_COMPLEX;
if (a.rows () > 0 && a.cols () > 0)
A->x = a.data ();
}
else
err_wrong_type_arg ("symbfact", args(0));
bool coletree = false;
octave_idx_type n = A->nrow;
if (nargin > 1)
{
std::string str = args(1).xstring_value ("TYP must be a string");
// FIXME: The input validation could be improved to use strncmp
char ch;
ch = tolower (str[0]);
if (ch == 'r') // 'row'
A->stype = 0;
else if (ch == 'c') // 'col'
{
n = A->ncol;
coletree = true;
A->stype = 0;
}
else if (ch == 's') // 'sym' (default)
A->stype = 1;
else if (ch == 'l') // 'lo'
A->stype = -1;
else
error (R"(symbfact: unrecognized TYP "%s")", str.c_str ());
}
if (nargin == 3)
{
std::string str = args(2).xstring_value ("MODE must be a string");
// FIXME: The input validation could be improved to use strncmp
char ch;
ch = toupper (str[0]);
if (ch != 'L')
error (R"(symbfact: unrecognized MODE "%s")", str.c_str ());
}
if (A->stype && A->nrow != A->ncol)
err_square_matrix_required ("symbfact", "S");
OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, Parent, n);
OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, Post, n);
OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, ColCount, n);
OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, First, n);
OCTAVE_LOCAL_BUFFER (octave_idx_type, Level, n);
cholmod_common Common;
cholmod_common *cm = &Common;
CHOLMOD_NAME(start) (cm);
double spu = octave_sparse_params::get_key ("spumoni");
if (spu == 0.0)
{
cm->print = -1;
SUITESPARSE_ASSIGN_FPTR (printf_func, cm->print_function, nullptr);
}
else
{
cm->print = static_cast<int> (spu) + 2;
SUITESPARSE_ASSIGN_FPTR (printf_func, cm->print_function, &SparseCholPrint);
}
cm->error_handler = &SparseCholError;
SUITESPARSE_ASSIGN_FPTR2 (divcomplex_func, cm->complex_divide, divcomplex);
SUITESPARSE_ASSIGN_FPTR2 (hypot_func, cm->hypotenuse, hypot);
cholmod_sparse *F = CHOLMOD_NAME(transpose) (A, 0, cm);
cholmod_sparse *Aup, *Alo;
if (A->stype == 1 || coletree)
{
Aup = A;
Alo = F;
}
else
{
Aup = F;
Alo = A;
}
CHOLMOD_NAME(etree) (Aup, Parent, cm);
ColumnVector tmp (n); // Declaration must precede any goto cleanup.
std::string err_msg;
if (cm->status < CHOLMOD_OK)
{
err_msg = "symbfact: matrix corrupted";
goto cleanup;
}
if (CHOLMOD_NAME(postorder) (Parent, n, nullptr, Post, cm) != n)
{
err_msg = "symbfact: postorder failed";
goto cleanup;
}
CHOLMOD_NAME(rowcolcounts) (Alo, nullptr, 0, Parent, Post, nullptr, ColCount,
First, octave::to_suitesparse_intptr (Level), cm);
if (cm->status < CHOLMOD_OK)
{
err_msg = "symbfact: matrix corrupted";
goto cleanup;
}
if (nargout > 4)
{
cholmod_sparse *A1, *A2;
if (A->stype == 1)
{
A1 = A;
A2 = nullptr;
}
else if (A->stype == -1)
{
A1 = F;
A2 = nullptr;
}
else if (coletree)
{
A1 = F;
A2 = A;
}
else
{
A1 = A;
A2 = F;
}
// count the total number of entries in L
octave_idx_type lnz = 0;
for (octave_idx_type j = 0 ; j < n ; j++)
lnz += ColCount[j];
// allocate the output matrix L (pattern-only)
SparseBoolMatrix L (dim_vector (n, n), lnz);
// initialize column pointers
lnz = 0;
for (octave_idx_type j = 0 ; j < n ; j++)
{
L.xcidx(j) = lnz;
lnz += ColCount[j];
}
L.xcidx(n) = lnz;
// create a copy of the column pointers
octave::suitesparse_integer *W = First;
for (octave_idx_type j = 0 ; j < n ; j++)
W[j] = L.xcidx (j);
// get workspace for computing one row of L
cholmod_sparse *R
= CHOLMOD_NAME(allocate_sparse) (n, 1, n, false, true,
0, CHOLMOD_PATTERN, cm);
octave_idx_type *Rp = static_cast<octave_idx_type *> (R->p);
octave_idx_type *Ri = static_cast<octave_idx_type *> (R->i);
// compute L one row at a time
for (octave_idx_type k = 0 ; k < n ; k++)
{
// get the kth row of L and store in the columns of L
CHOLMOD_NAME(row_subtree) (A1, A2, k, Parent, R, cm);
for (octave_idx_type p = 0 ; p < Rp[1] ; p++)
L.xridx (W[Ri[p]]++) = k;
// add the diagonal entry
L.xridx (W[k]++) = k;
}
// free workspace
CHOLMOD_NAME(free_sparse) (&R, cm);
// fill L with one's
std::fill_n (L.xdata (), lnz, true);
// transpose L to get R, or leave as is
if (nargin < 3)
L = L.transpose ();
retval(4) = L;
}
if (nargout > 3)
{
for (octave_idx_type i = 0; i < n; i++)
tmp(i) = Post[i] + 1;
retval(3) = tmp;
}
if (nargout > 2)
{
for (octave_idx_type i = 0; i < n; i++)
tmp(i) = Parent[i] + 1;
retval(2) = tmp;
}
if (nargout > 1)
{
// compute the elimination tree height
octave_idx_type height = 0;
for (int i = 0 ; i < n ; i++)
height = std::max (height, Level[i]);
height++;
retval(1) = static_cast<double> (height);
}
for (octave_idx_type i = 0; i < n; i++)
tmp(i) = ColCount[i];
retval(0) = tmp;
cleanup:
CHOLMOD_NAME(free_sparse) (&F, cm);
CHOLMOD_NAME(finish) (cm);
if (! err_msg.empty ())
error ("%s", err_msg.c_str ());
return retval;
#else
octave_unused_parameter (args);
octave_unused_parameter (nargout);
err_disabled_feature ("symbfact", "CHOLMOD");
#endif
}
/*
%!testif HAVE_CHOLMOD
%! A = sparse (magic (3));
%! [count, h, parent, post, r] = symbfact (A);
%! assert (count, [3; 2; 1]);
%! assert (h, 3);
%! assert (parent, [2; 3; 0]);
%! assert (r, sparse (triu (true (3))));
%!testif HAVE_CHOLMOD
%! ## Test MODE "lower"
%! A = sparse (magic (3));
%! [~, ~, ~, ~, l] = symbfact (A, "sym", "lower");
%! assert (l, sparse (tril (true (3))));
%!testif HAVE_CHOLMOD <*42587>
%! ## singular matrix
%! A = sparse ([1 0 8;0 1 8;8 8 1]);
%! [count, h, parent, post, r] = symbfact (A);
## Test input validation
%!testif HAVE_CHOLMOD
%! fail ("symbfact ()");
%! fail ("symbfact (1,2,3,4)");
%! fail ("symbfact ({1})", "wrong type argument 'cell'");
%! fail ("symbfact (sparse (1), {1})", "TYP must be a string");
%! fail ("symbfact (sparse (1), 'foobar')", 'unrecognized TYP "foobar"');
%! fail ("symbfact (sparse (1), 'sym', {'L'})", "MODE must be a string");
%! fail ('symbfact (sparse (1), "sym", "foobar")', 'unrecognized MODE "foobar"');
%! fail ("symbfact (sparse ([1, 2; 3, 4; 5, 6]))", "S must be a square matrix");
*/
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