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view libinterp/corefcn/ccolamd.cc @ 31179:f294b800f002
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author | magedrifaat <magedrifaat@gmail.com> |
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date | Wed, 17 Aug 2022 23:27:54 +0200 |
parents | 796f54d4ddbf |
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//////////////////////////////////////////////////////////////////////// // // Copyright (C) 2005-2022 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/>. // //////////////////////////////////////////////////////////////////////// // This is the octave interface to ccolamd, which bore the copyright given // in the help of the functions. #if defined (HAVE_CONFIG_H) # include "config.h" #endif #include <cstdlib> #include "CSparse.h" #include "Sparse.h" #include "dNDArray.h" #include "oct-locbuf.h" #include "oct-sparse.h" #include "defun.h" #include "error.h" #include "errwarn.h" #include "ov.h" #include "pager.h" OCTAVE_NAMESPACE_BEGIN DEFUN (ccolamd, args, nargout, doc: /* -*- texinfo -*- @deftypefn {} {@var{p} =} ccolamd (@var{S}) @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}) @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}, @var{cmember}) @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{}) Constrained column approximate minimum degree permutation. @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum degree permutation vector for the sparse matrix @var{S}. For a non-symmetric matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have sparser LU@tie{}factors than @var{S}. @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be sparser than @code{chol (@var{S}' * @var{S})}. @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column elimination tree post-ordering. @var{knobs} is an optional 1-element to 5-element input vector, with a default value of @code{[0 10 10 1 0]} if not present or empty. Entries not present are set to their defaults. @table @code @item @var{knobs}(1) if nonzero, the ordering is optimized for @code{lu (S(:, p))}. It will be a poor ordering for @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}. This is the most important knob for ccolamd. @item @var{knobs}(2) if @var{S} is m-by-n, rows with more than @code{max (16, @var{knobs}(2) * sqrt (n))} entries are ignored. @item @var{knobs}(3) columns with more than @code{max (16, @var{knobs}(3) * sqrt (min (@var{m}, @var{n})))} entries are ignored and ordered last in the output permutation (subject to the cmember constraints). @item @var{knobs}(4) if nonzero, aggressive absorption is performed. @item @var{knobs}(5) if nonzero, statistics and knobs are printed. @end table @var{cmember} is an optional vector of length @math{n}. It defines the constraints on the column ordering. If @code{@var{cmember}(j) = @var{c}}, then column @var{j} is in constraint set @var{c} (@var{c} must be in the range 1 to n). In the output permutation @var{p}, all columns in set 1 appear first, followed by all columns in set 2, and so on. @code{@var{cmember} = ones (1,n)} if not present or empty. @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n} @code{@var{p} = ccolamd (@var{S})} is about the same as @code{@var{p} = colamd (@var{S})}. @var{knobs} and its default values differ. @code{colamd} always does aggressive absorption, and it finds an ordering suitable for both @code{lu (@var{S}(:, @var{p}))} and @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}; it cannot optimize its ordering for @code{lu (@var{S}(:, @var{p}))} to the extent that @code{ccolamd (@var{S}, 1)} can. @var{stats} is an optional 20-element output vector that provides data about the ordering and the validity of the input matrix @var{S}. Ordering statistics are in @code{@var{stats}(1 : 3)}. @code{@var{stats}(1)} and @code{@var{stats}(2)} are the number of dense or empty rows and columns ignored by @sc{ccolamd} and @code{@var{stats}(3)} is the number of garbage collections performed on the internal data structure used by @sc{ccolamd} (roughly of size @code{2.2 * nnz (@var{S}) + 4 * @var{m} + 7 * @var{n}} integers). @code{@var{stats}(4 : 7)} provide information if CCOLAMD was able to continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if invalid. @code{@var{stats}(5)} is the rightmost column index that is unsorted or contains duplicate entries, or zero if no such column exists. @code{@var{stats}(6)} is the last seen duplicate or out-of-order row index in the column index given by @code{@var{stats}(5)}, or zero if no such row index exists. @code{@var{stats}(7)} is the number of duplicate or out-of-order row indices. @code{@var{stats}(8 : 20)} is always zero in the current version of @sc{ccolamd} (reserved for future use). The authors of the code itself are @nospell{S. Larimore, T. Davis} and @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from @nospell{Sandia} National Lab. See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd, csymamd, amd, colamd, symamd, and other related orderings. @seealso{colamd, csymamd} @end deftypefn */) { #if defined (HAVE_CCOLAMD) int nargin = args.length (); if (nargin < 1 || nargin > 3) print_usage (); octave_value_list retval (nargout == 2 ? 2 : 1); int spumoni = 0; // Get knobs static_assert (CCOLAMD_KNOBS <= 40, "ccolamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org"); double knob_storage[CCOLAMD_KNOBS]; double *knobs = &knob_storage[0]; CCOLAMD_NAME (_set_defaults) (knobs); // Check for user-passed knobs if (nargin > 1) { NDArray User_knobs = args(1).array_value (); int nel_User_knobs = User_knobs.numel (); if (nel_User_knobs > 0) knobs[CCOLAMD_LU] = (User_knobs(0) != 0); if (nel_User_knobs > 1) knobs[CCOLAMD_DENSE_ROW] = User_knobs(1); if (nel_User_knobs > 2) knobs[CCOLAMD_DENSE_COL] = User_knobs(2); if (nel_User_knobs > 3) knobs[CCOLAMD_AGGRESSIVE] = (User_knobs(3) != 0); if (nel_User_knobs > 4) spumoni = (User_knobs(4) != 0); // print knob settings if spumoni is set if (spumoni) { octave_stdout << "\nccolamd version " << CCOLAMD_MAIN_VERSION << '.' << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE << ":\nknobs(1): " << User_knobs(0) << ", order for "; if (knobs[CCOLAMD_LU] != 0) octave_stdout << "lu (A)\n"; else octave_stdout << "chol (A'*A)\n"; if (knobs[CCOLAMD_DENSE_ROW] >= 0) octave_stdout << "knobs(2): " << User_knobs(1) << ", rows with > max (16," << knobs[CCOLAMD_DENSE_ROW] << "*sqrt (columns(A)))" << " entries removed\n"; else octave_stdout << "knobs(2): " << User_knobs(1) << ", no dense rows removed\n"; if (knobs[CCOLAMD_DENSE_COL] >= 0) octave_stdout << "knobs(3): " << User_knobs(2) << ", cols with > max (16," << knobs[CCOLAMD_DENSE_COL] << "*sqrt (size(A)))" << " entries removed\n"; else octave_stdout << "knobs(3): " << User_knobs(2) << ", no dense columns removed\n"; if (knobs[CCOLAMD_AGGRESSIVE] != 0) octave_stdout << "knobs(4): " << User_knobs(3) << ", aggressive absorption: yes"; else octave_stdout << "knobs(4): " << User_knobs(3) << ", aggressive absorption: no"; octave_stdout << "knobs(5): " << User_knobs(4) << ", statistics and knobs printed\n"; } } octave_idx_type n_row, n_col, nnz; octave_idx_type *ridx, *cidx; SparseComplexMatrix scm; SparseMatrix sm; if (args(0).issparse ()) { if (args(0).iscomplex ()) { scm = args(0).sparse_complex_matrix_value (); n_row = scm.rows (); n_col = scm.cols (); nnz = scm.nnz (); ridx = scm.xridx (); cidx = scm.xcidx (); } else { sm = args(0).sparse_matrix_value (); n_row = sm.rows (); n_col = sm.cols (); nnz = sm.nnz (); ridx = sm.xridx (); cidx = sm.xcidx (); } } else { if (args(0).iscomplex ()) sm = SparseMatrix (real (args(0).complex_matrix_value ())); else sm = SparseMatrix (args(0).matrix_value ()); n_row = sm.rows (); n_col = sm.cols (); nnz = sm.nnz (); ridx = sm.xridx (); cidx = sm.xcidx (); } // Allocate workspace for ccolamd OCTAVE_LOCAL_BUFFER (suitesparse_integer, p, n_col+1); for (octave_idx_type i = 0; i < n_col+1; i++) p[i] = cidx[i]; octave_idx_type Alen = CCOLAMD_NAME (_recommended) (nnz, n_row, n_col); OCTAVE_LOCAL_BUFFER (suitesparse_integer, A, Alen); for (octave_idx_type i = 0; i < nnz; i++) A[i] = ridx[i]; static_assert (CCOLAMD_STATS <= 40, "ccolamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org"); suitesparse_integer stats_storage[CCOLAMD_STATS]; suitesparse_integer *stats = &stats_storage[0]; if (nargin > 2) { NDArray in_cmember = args(2).array_value (); octave_idx_type cslen = in_cmember.numel (); OCTAVE_LOCAL_BUFFER (suitesparse_integer, cmember, cslen); for (octave_idx_type i = 0; i < cslen; i++) // convert cmember from 1-based to 0-based cmember[i] = static_cast<suitesparse_integer>(in_cmember(i) - 1); if (cslen != n_col) error ("ccolamd: CMEMBER must be of length equal to #cols of A"); // Order the columns (destroys A) if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, cmember)) { CCOLAMD_NAME (_report) (stats); error ("ccolamd: internal error!"); } } else { // Order the columns (destroys A) if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, nullptr)) { CCOLAMD_NAME (_report) (stats); error ("ccolamd: internal error!"); } } // return the permutation vector NDArray out_perm (dim_vector (1, n_col)); for (octave_idx_type i = 0; i < n_col; i++) out_perm(i) = p[i] + 1; retval(0) = out_perm; // print stats if spumoni > 0 if (spumoni > 0) CCOLAMD_NAME (_report) (stats); // Return the stats vector if (nargout == 2) { NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) out_stats(i) = stats[i]; retval(1) = out_stats; // fix stats (5) and (6), for 1-based information on // jumbled matrix. note that this correction doesn't // occur if symamd returns FALSE out_stats(CCOLAMD_INFO1)++; out_stats(CCOLAMD_INFO2)++; } return retval; #else octave_unused_parameter (args); octave_unused_parameter (nargout); err_disabled_feature ("ccolamd", "CCOLAMD"); #endif } DEFUN (csymamd, args, nargout, doc: /* -*- texinfo -*- @deftypefn {} {@var{p} =} csymamd (@var{S}) @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}) @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}, @var{cmember}) @deftypefnx {} {[@var{p}, @var{stats}] =} csymamd (@dots{}) For a symmetric positive definite matrix @var{S}, return the permutation vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a sparser Cholesky@tie{}factor than @var{S}. Sometimes @code{csymamd} works well for symmetric indefinite matrices too. The matrix @var{S} is assumed to be symmetric; only the strictly lower triangular part is referenced. @var{S} must be square. The ordering is followed by an elimination tree post-ordering. @var{knobs} is an optional 1-element to 3-element input vector, with a default value of @code{[10 1 0]}. Entries not present are set to their defaults. @table @code @item @var{knobs}(1) If @var{S} is n-by-n, then rows and columns with more than @code{max(16,@var{knobs}(1)*sqrt(n))} entries are ignored, and ordered last in the output permutation (subject to the cmember constraints). @item @var{knobs}(2) If nonzero, aggressive absorption is performed. @item @var{knobs}(3) If nonzero, statistics and knobs are printed. @end table @var{cmember} is an optional vector of length n. It defines the constraints on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is in constraint set @var{c} (@var{c} must be in the range 1 to n). In the output permutation @var{p}, rows/columns in set 1 appear first, followed by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)} if not present or empty. @code{csymamd (@var{S},[],1:n)} returns @code{1:n}. @code{@var{p} = csymamd (@var{S})} is about the same as @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values differ. @code{@var{stats}(4:7)} provide information if CCOLAMD was able to continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if invalid. @code{@var{stats}(5)} is the rightmost column index that is unsorted or contains duplicate entries, or zero if no such column exists. @code{@var{stats}(6)} is the last seen duplicate or out-of-order row index in the column index given by @code{@var{stats}(5)}, or zero if no such row index exists. @code{@var{stats}(7)} is the number of duplicate or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in the current version of @sc{ccolamd} (reserved for future use). The authors of the code itself are @nospell{S. Larimore, T. Davis} and @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from @nospell{Sandia} National Lab. See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd, colamd, csymamd, amd, colamd, symamd, and other related orderings. @seealso{symamd, ccolamd} @end deftypefn */) { #if defined (HAVE_CCOLAMD) int nargin = args.length (); if (nargin < 1 || nargin > 3) print_usage (); octave_value_list retval (nargout == 2 ? 2 : 1); int spumoni = 0; // Get knobs static_assert (CCOLAMD_KNOBS <= 40, "csymamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org"); double knob_storage[CCOLAMD_KNOBS]; double *knobs = &knob_storage[0]; CCOLAMD_NAME (_set_defaults) (knobs); // Check for user-passed knobs if (nargin > 1) { NDArray User_knobs = args(1).array_value (); int nel_User_knobs = User_knobs.numel (); if (nel_User_knobs > 0) knobs[CCOLAMD_DENSE_ROW] = User_knobs(0); if (nel_User_knobs > 1) knobs[CCOLAMD_AGGRESSIVE] = User_knobs(1); if (nel_User_knobs > 2) spumoni = static_cast<int> (User_knobs(2)); // print knob settings if spumoni is set if (spumoni) { octave_stdout << "\ncsymamd version " << CCOLAMD_MAIN_VERSION << '.' << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE << "\n"; if (knobs[CCOLAMD_DENSE_ROW] >= 0) octave_stdout << "knobs(1): " << User_knobs(0) << ", rows/cols with > max (16," << knobs[CCOLAMD_DENSE_ROW] << "*sqrt (columns(A)))" << " entries removed\n"; else octave_stdout << "knobs(1): " << User_knobs(0) << ", no dense rows/cols removed\n"; if (knobs[CCOLAMD_AGGRESSIVE] != 0) octave_stdout << "knobs(2): " << User_knobs(1) << ", aggressive absorption: yes"; else octave_stdout << "knobs(2): " << User_knobs(1) << ", aggressive absorption: no"; octave_stdout << "knobs(3): " << User_knobs(2) << ", statistics and knobs printed\n"; } } octave_idx_type n_row, n_col; octave_idx_type *ridx, *cidx; SparseMatrix sm; SparseComplexMatrix scm; if (args(0).issparse ()) { if (args(0).iscomplex ()) { scm = args(0).sparse_complex_matrix_value (); n_row = scm.rows (); n_col = scm.cols (); ridx = scm.xridx (); cidx = scm.xcidx (); } else { sm = args(0).sparse_matrix_value (); n_row = sm.rows (); n_col = sm.cols (); ridx = sm.xridx (); cidx = sm.xcidx (); } } else { if (args(0).iscomplex ()) sm = SparseMatrix (real (args(0).complex_matrix_value ())); else sm = SparseMatrix (args(0).matrix_value ()); n_row = sm.rows (); n_col = sm.cols (); ridx = sm.xridx (); cidx = sm.xcidx (); } if (n_row != n_col) err_square_matrix_required ("csymamd", "S"); // Allocate workspace for symamd OCTAVE_LOCAL_BUFFER (suitesparse_integer, perm, n_col+1); static_assert (CCOLAMD_STATS <= 40, "csymamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org"); suitesparse_integer stats_storage[CCOLAMD_STATS]; suitesparse_integer *stats = &stats_storage[0]; if (nargin > 2) { NDArray in_cmember = args(2).array_value (); octave_idx_type cslen = in_cmember.numel (); OCTAVE_LOCAL_BUFFER (suitesparse_integer, cmember, cslen); for (octave_idx_type i = 0; i < cslen; i++) // convert cmember from 1-based to 0-based cmember[i] = static_cast<octave_idx_type> (in_cmember(i) - 1); if (cslen != n_col) error ("csymamd: CMEMBER must be of length equal to #cols of A"); if (! CSYMAMD_NAME () (n_col, to_suitesparse_intptr (ridx), to_suitesparse_intptr (cidx), perm, knobs, stats, &calloc, &free, cmember, -1)) { CSYMAMD_NAME (_report)(stats); error ("csymamd: internal error!"); } } else { if (! CSYMAMD_NAME () (n_col, to_suitesparse_intptr (ridx), to_suitesparse_intptr (cidx), perm, knobs, stats, &calloc, &free, nullptr, -1)) { CSYMAMD_NAME (_report)(stats); error ("csymamd: internal error!"); } } // return the permutation vector NDArray out_perm (dim_vector (1, n_col)); for (octave_idx_type i = 0; i < n_col; i++) out_perm(i) = perm[i] + 1; retval(0) = out_perm; // print stats if spumoni > 0 if (spumoni > 0) CSYMAMD_NAME (_report)(stats); // Return the stats vector if (nargout == 2) { NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) out_stats(i) = stats[i]; retval(1) = out_stats; // fix stats (5) and (6), for 1-based information on // jumbled matrix. note that this correction doesn't // occur if symamd returns FALSE out_stats(CCOLAMD_INFO1)++; out_stats(CCOLAMD_INFO2)++; } return retval; #else octave_unused_parameter (args); octave_unused_parameter (nargout); err_disabled_feature ("csymamd", "CCOLAMD"); #endif } OCTAVE_NAMESPACE_END