Mercurial > octave-antonio
annotate libinterp/dldfcn/ccolamd.cc @ 20163:075a5e2e1ba5 stable
doc: Update more docstrings to have one sentence summary as first line.
Reviewed build-aux, libinterp/dldfcn, libinterp/octave-value,
libinterp/parse-tree directories.
* build-aux/mk-opts.pl, libinterp/dldfcn/__magick_read__.cc,
libinterp/dldfcn/amd.cc, libinterp/dldfcn/audiodevinfo.cc,
libinterp/dldfcn/audioread.cc, libinterp/dldfcn/ccolamd.cc,
libinterp/dldfcn/chol.cc, libinterp/dldfcn/colamd.cc,
libinterp/dldfcn/convhulln.cc, libinterp/dldfcn/dmperm.cc,
libinterp/dldfcn/fftw.cc, libinterp/dldfcn/qr.cc, libinterp/dldfcn/symbfact.cc,
libinterp/dldfcn/symrcm.cc, libinterp/octave-value/ov-base.cc,
libinterp/octave-value/ov-bool-mat.cc, libinterp/octave-value/ov-cell.cc,
libinterp/octave-value/ov-class.cc, libinterp/octave-value/ov-fcn-handle.cc,
libinterp/octave-value/ov-fcn-inline.cc, libinterp/octave-value/ov-java.cc,
libinterp/octave-value/ov-null-mat.cc, libinterp/octave-value/ov-oncleanup.cc,
libinterp/octave-value/ov-range.cc, libinterp/octave-value/ov-struct.cc,
libinterp/octave-value/ov-typeinfo.cc, libinterp/octave-value/ov-usr-fcn.cc,
libinterp/octave-value/ov.cc, libinterp/parse-tree/lex.ll,
libinterp/parse-tree/oct-parse.in.yy, libinterp/parse-tree/pt-binop.cc,
libinterp/parse-tree/pt-eval.cc, libinterp/parse-tree/pt-mat.cc:
doc: Update more docstrings to have one sentence summary as first line.
author | Rik <rik@octave.org> |
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date | Sun, 03 May 2015 21:52:42 -0700 |
parents | 4197fc428c7d |
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rev | line source |
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5451 | 1 /* |
2 | |
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3 Copyright (C) 2005-2015 David Bateman |
5451 | 4 |
7016 | 5 This file is part of Octave. |
6 | |
5451 | 7 Octave is free software; you can redistribute it and/or modify it |
8 under the terms of the GNU General Public License as published by the | |
7016 | 9 Free Software Foundation; either version 3 of the License, or (at your |
10 option) any later version. | |
5451 | 11 |
12 Octave is distributed in the hope that it will be useful, but WITHOUT | |
13 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
14 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
15 for more details. | |
16 | |
17 You should have received a copy of the GNU General Public License | |
7016 | 18 along with Octave; see the file COPYING. If not, see |
19 <http://www.gnu.org/licenses/>. | |
5451 | 20 |
21 */ | |
22 | |
23 // This is the octave interface to ccolamd, which bore the copyright given | |
24 // in the help of the functions. | |
25 | |
26 #ifdef HAVE_CONFIG_H | |
27 #include <config.h> | |
28 #endif | |
29 | |
30 #include <cstdlib> | |
31 | |
32 #include <string> | |
33 #include <vector> | |
34 | |
35 #include "ov.h" | |
36 #include "defun-dld.h" | |
37 #include "pager.h" | |
38 #include "ov-re-mat.h" | |
39 | |
40 #include "ov-re-sparse.h" | |
41 #include "ov-cx-sparse.h" | |
42 | |
43 #include "oct-sparse.h" | |
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44 #include "oct-locbuf.h" |
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46 #ifdef USE_64_BIT_IDX_T |
5451 | 47 #define CCOLAMD_NAME(name) ccolamd_l ## name |
48 #define CSYMAMD_NAME(name) csymamd_l ## name | |
49 #else | |
50 #define CCOLAMD_NAME(name) ccolamd ## name | |
51 #define CSYMAMD_NAME(name) csymamd ## name | |
52 #endif | |
53 | |
54 DEFUN_DLD (ccolamd, args, nargout, | |
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55 "-*- texinfo -*-\n\ |
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56 @deftypefn {Loadable Function} {@var{p} =} ccolamd (@var{S})\n\ |
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57 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{S}, @var{knobs})\n\ |
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58 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{S}, @var{knobs}, @var{cmember})\n\ |
5451 | 59 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\ |
60 \n\ | |
10840 | 61 Constrained column approximate minimum degree permutation.\n\ |
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62 \n\ |
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63 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum\n\ |
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64 degree permutation vector for the sparse matrix @var{S}. For a non-symmetric\n\ |
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65 matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have sparser\n\ |
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66 LU@tie{}factors than @var{S}.\n\ |
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67 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be\n\ |
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68 sparser than @code{chol (@var{S}' * @var{S})}.\n\ |
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69 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for\n\ |
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70 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column\n\ |
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71 elimination tree post-ordering.\n\ |
5451 | 72 \n\ |
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73 @var{knobs} is an optional 1-element to 5-element input vector, with a\n\ |
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74 default value of @code{[0 10 10 1 0]} if not present or empty. Entries not\n\ |
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75 present are set to their defaults.\n\ |
5451 | 76 \n\ |
77 @table @code\n\ | |
78 @item @var{knobs}(1)\n\ | |
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79 if nonzero, the ordering is optimized for @code{lu (S(:, p))}. It will be a\n\ |
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80 poor ordering for @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}.\n\ |
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81 This is the most important knob for ccolamd.\n\ |
5451 | 82 \n\ |
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83 @item @var{knobs}(2)\n\ |
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84 if @var{S} is m-by-n, rows with more than\n\ |
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85 @code{max (16, @var{knobs}(2) * sqrt (n))} entries are ignored.\n\ |
5451 | 86 \n\ |
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87 @item @var{knobs}(3)\n\ |
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88 columns with more than\n\ |
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89 @code{max (16, @var{knobs}(3) * sqrt (min (@var{m}, @var{n})))} entries are\n\ |
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90 ignored and ordered last in the output permutation\n\ |
7107 | 91 (subject to the cmember constraints).\n\ |
5451 | 92 \n\ |
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93 @item @var{knobs}(4)\n\ |
5451 | 94 if nonzero, aggressive absorption is performed.\n\ |
95 \n\ | |
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96 @item @var{knobs}(5)\n\ |
5451 | 97 if nonzero, statistics and knobs are printed.\n\ |
98 \n\ | |
99 @end table\n\ | |
100 \n\ | |
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101 @var{cmember} is an optional vector of length @math{n}. It defines the\n\ |
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102 constraints on the column ordering. If @code{@var{cmember}(j) = @var{c}},\n\ |
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103 then column @var{j} is in constraint set @var{c} (@var{c} must be in the\n\ |
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104 range 1 to n). In the output permutation @var{p}, all columns in set 1\n\ |
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105 appear first, followed by all columns in set 2, and so on.\n\ |
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106 @code{@var{cmember} = ones (1,n)} if not present or empty.\n\ |
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107 @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n}\n\ |
5451 | 108 \n\ |
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109 @code{@var{p} = ccolamd (@var{S})} is about the same as\n\ |
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110 @code{@var{p} = colamd (@var{S})}. @var{knobs} and its default values\n\ |
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111 differ. @code{colamd} always does aggressive absorption, and it finds an\n\ |
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112 ordering suitable for both @code{lu (@var{S}(:, @var{p}))} and @code{chol\n\ |
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113 (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}; it cannot optimize its\n\ |
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114 ordering for @code{lu (@var{S}(:, @var{p}))} to the extent that\n\ |
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115 @code{ccolamd (@var{S}, 1)} can.\n\ |
5451 | 116 \n\ |
117 @var{stats} is an optional 20-element output vector that provides data\n\ | |
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118 about the ordering and the validity of the input matrix @var{S}. Ordering\n\ |
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119 statistics are in @code{@var{stats}(1 : 3)}. @code{@var{stats}(1)} and\n\ |
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120 @code{@var{stats}(2)} are the number of dense or empty rows and columns\n\ |
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121 ignored by @sc{ccolamd} and @code{@var{stats}(3)} is the number of garbage\n\ |
10840 | 122 collections performed on the internal data structure used by @sc{ccolamd}\n\ |
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123 (roughly of size @code{2.2 * nnz (@var{S}) + 4 * @var{m} + 7 * @var{n}}\n\ |
5451 | 124 integers).\n\ |
125 \n\ | |
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126 @code{@var{stats}(4 : 7)} provide information if CCOLAMD was able to\n\ |
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127 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if\n\ |
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128 invalid. @code{@var{stats}(5)} is the rightmost column index that is\n\ |
5451 | 129 unsorted or contains duplicate entries, or zero if no such column exists.\n\ |
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130 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row\n\ |
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131 index in the column index given by @code{@var{stats}(5)}, or zero if no\n\ |
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132 such row index exists. @code{@var{stats}(7)} is the number of duplicate\n\ |
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133 or out-of-order row indices. @code{@var{stats}(8 : 20)} is always zero in\n\ |
10840 | 134 the current version of @sc{ccolamd} (reserved for future use).\n\ |
5451 | 135 \n\ |
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136 The authors of the code itself are @nospell{S. Larimore, T. Davis}\n\ |
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137 (Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with\n\ |
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138 @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation\n\ |
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139 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from\n\ |
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140 @nospell{Sandia} National Lab.\n\ |
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141 See @url{http://www.cise.ufl.edu/research/sparse} for\n\ |
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142 ccolamd, csymamd, amd, colamd, symamd, and other related orderings.\n\ |
5642 | 143 @seealso{colamd, csymamd}\n\ |
144 @end deftypefn") | |
5451 | 145 { |
5771 | 146 octave_value_list retval; |
147 | |
5451 | 148 #ifdef HAVE_CCOLAMD |
5771 | 149 |
5451 | 150 int nargin = args.length (); |
151 int spumoni = 0; | |
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152 |
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153 if (nargout > 2 || nargin < 1 || nargin > 3) |
5451 | 154 usage ("ccolamd: incorrect number of input and/or output arguments"); |
155 else | |
156 { | |
157 // Get knobs | |
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158 OCTAVE_LOCAL_BUFFER (double, knobs, CCOLAMD_KNOBS); |
5451 | 159 CCOLAMD_NAME (_set_defaults) (knobs); |
160 | |
161 // Check for user-passed knobs | |
162 if (nargin > 1) | |
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163 { |
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164 NDArray User_knobs = args(1).array_value (); |
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165 int nel_User_knobs = User_knobs.length (); |
5451 | 166 |
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167 if (nel_User_knobs > 0) |
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168 knobs[CCOLAMD_LU] = (User_knobs(0) != 0); |
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169 if (nel_User_knobs > 1) |
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170 knobs[CCOLAMD_DENSE_ROW] = User_knobs(1); |
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171 if (nel_User_knobs > 2) |
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172 knobs[CCOLAMD_DENSE_COL] = User_knobs(2); |
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173 if (nel_User_knobs > 3) |
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174 knobs[CCOLAMD_AGGRESSIVE] = (User_knobs(3) != 0); |
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175 if (nel_User_knobs > 4) |
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176 spumoni = (User_knobs(4) != 0); |
5451 | 177 |
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178 // print knob settings if spumoni is set |
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179 if (spumoni) |
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180 { |
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181 octave_stdout << "\nccolamd version " << CCOLAMD_MAIN_VERSION << "." |
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182 << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE |
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183 << ":\nknobs(1): " << User_knobs(0) << ", order for "; |
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184 if (knobs[CCOLAMD_LU] != 0) |
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185 octave_stdout << "lu (A)\n"; |
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186 else |
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187 octave_stdout << "chol (A'*A)\n"; |
5451 | 188 |
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189 if (knobs[CCOLAMD_DENSE_ROW] >= 0) |
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190 octave_stdout << "knobs(2): " << User_knobs(1) |
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191 << ", rows with > max (16," |
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192 << knobs[CCOLAMD_DENSE_ROW] |
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193 << "*sqrt (size(A,2)))" |
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194 << " entries removed\n"; |
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195 else |
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196 octave_stdout << "knobs(2): " << User_knobs(1) |
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197 << ", no dense rows removed\n"; |
5451 | 198 |
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199 if (knobs[CCOLAMD_DENSE_COL] >= 0) |
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200 octave_stdout << "knobs(3): " << User_knobs(2) |
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201 << ", cols with > max (16," |
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202 << knobs[CCOLAMD_DENSE_COL] << "*sqrt (size(A)))" |
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203 << " entries removed\n"; |
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204 else |
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205 octave_stdout << "knobs(3): " << User_knobs(2) |
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206 << ", no dense columns removed\n"; |
5451 | 207 |
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208 if (knobs[CCOLAMD_AGGRESSIVE] != 0) |
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209 octave_stdout << "knobs(4): " << User_knobs(3) |
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210 << ", aggressive absorption: yes"; |
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211 else |
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212 octave_stdout << "knobs(4): " << User_knobs(3) |
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213 << ", aggressive absorption: no"; |
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214 |
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215 octave_stdout << "knobs(5): " << User_knobs(4) |
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216 << ", statistics and knobs printed\n"; |
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217 } |
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218 } |
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219 |
5451 | 220 octave_idx_type n_row, n_col, nnz; |
221 octave_idx_type *ridx, *cidx; | |
222 SparseComplexMatrix scm; | |
223 SparseMatrix sm; | |
224 | |
5631 | 225 if (args(0).is_sparse_type ()) |
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226 { |
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227 if (args(0).is_complex_type ()) |
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228 { |
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229 scm = args(0). sparse_complex_matrix_value (); |
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230 n_row = scm.rows (); |
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231 n_col = scm.cols (); |
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232 nnz = scm.nnz (); |
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233 ridx = scm.xridx (); |
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234 cidx = scm.xcidx (); |
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235 } |
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236 else |
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237 { |
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238 sm = args(0).sparse_matrix_value (); |
5451 | 239 |
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240 n_row = sm.rows (); |
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241 n_col = sm.cols (); |
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242 nnz = sm.nnz (); |
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243 ridx = sm.xridx (); |
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244 cidx = sm.xcidx (); |
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245 } |
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246 } |
5451 | 247 else |
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248 { |
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249 if (args(0).is_complex_type ()) |
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250 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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251 else |
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252 sm = SparseMatrix (args(0).matrix_value ()); |
5451 | 253 |
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254 n_row = sm.rows (); |
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255 n_col = sm.cols (); |
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256 nnz = sm.nnz (); |
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257 ridx = sm.xridx (); |
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258 cidx = sm.xcidx (); |
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259 } |
5451 | 260 |
261 // Allocate workspace for ccolamd | |
262 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, n_col+1); | |
263 for (octave_idx_type i = 0; i < n_col+1; i++) | |
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264 p[i] = cidx[i]; |
5451 | 265 |
266 octave_idx_type Alen = CCOLAMD_NAME (_recommended) (nnz, n_row, n_col); | |
267 OCTAVE_LOCAL_BUFFER (octave_idx_type, A, Alen); | |
268 for (octave_idx_type i = 0; i < nnz; i++) | |
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269 A[i] = ridx[i]; |
5451 | 270 |
271 OCTAVE_LOCAL_BUFFER (octave_idx_type, stats, CCOLAMD_STATS); | |
272 | |
273 if (nargin > 2) | |
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274 { |
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275 NDArray in_cmember = args(2).array_value (); |
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276 octave_idx_type cslen = in_cmember.length (); |
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277 OCTAVE_LOCAL_BUFFER (octave_idx_type, cmember, cslen); |
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278 for (octave_idx_type i = 0; i < cslen; i++) |
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279 // convert cmember from 1-based to 0-based |
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280 cmember[i] = static_cast<octave_idx_type>(in_cmember(i) - 1); |
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281 |
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282 if (cslen != n_col) |
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283 error ("ccolamd: CMEMBER must be of length equal to #cols of A"); |
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284 else |
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285 // Order the columns (destroys A) |
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286 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, |
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287 knobs, stats, cmember)) |
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288 { |
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289 CCOLAMD_NAME (_report) (stats) ; |
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290 error ("ccolamd: internal error!"); |
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291 return retval; |
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292 } |
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293 } |
5451 | 294 else |
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295 { |
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296 // Order the columns (destroys A) |
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297 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, 0)) |
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298 { |
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299 CCOLAMD_NAME (_report) (stats) ; |
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300 error ("ccolamd: internal error!"); |
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301 return retval; |
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302 } |
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303 } |
5451 | 304 |
305 // return the permutation vector | |
306 NDArray out_perm (dim_vector (1, n_col)); | |
307 for (octave_idx_type i = 0; i < n_col; i++) | |
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308 out_perm(i) = p[i] + 1; |
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310 retval(0) = out_perm; |
5451 | 311 |
312 // print stats if spumoni > 0 | |
313 if (spumoni > 0) | |
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314 CCOLAMD_NAME (_report) (stats) ; |
5451 | 315 |
316 // Return the stats vector | |
317 if (nargout == 2) | |
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318 { |
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319 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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320 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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321 out_stats(i) = stats[i] ; |
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322 retval(1) = out_stats; |
5451 | 323 |
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324 // fix stats (5) and (6), for 1-based information on |
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325 // jumbled matrix. note that this correction doesn't |
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326 // occur if symamd returns FALSE |
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327 out_stats (CCOLAMD_INFO1) ++ ; |
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328 out_stats (CCOLAMD_INFO2) ++ ; |
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329 } |
5451 | 330 } |
331 | |
332 #else | |
333 | |
334 error ("ccolamd: not available in this version of Octave"); | |
335 | |
336 #endif | |
5771 | 337 |
338 return retval; | |
5451 | 339 } |
340 | |
341 DEFUN_DLD (csymamd, args, nargout, | |
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342 "-*- texinfo -*-\n\ |
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343 @deftypefn {Loadable Function} {@var{p} =} csymamd (@var{S})\n\ |
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344 @deftypefnx {Loadable Function} {@var{p} =} csymamd (@var{S}, @var{knobs})\n\ |
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345 @deftypefnx {Loadable Function} {@var{p} =} csymamd (@var{S}, @var{knobs}, @var{cmember})\n\ |
5451 | 346 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} csymamd (@dots{})\n\ |
347 \n\ | |
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348 For a symmetric positive definite matrix @var{S}, return the permutation\n\ |
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349 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a\n\ |
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350 sparser Cholesky@tie{}factor than @var{S}.\n\ |
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351 \n\ |
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352 Sometimes @code{csymamd} works well for symmetric indefinite matrices too. \n\ |
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353 The matrix @var{S} is assumed to be symmetric; only the strictly lower\n\ |
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354 triangular part is referenced. @var{S} must be square. The ordering is\n\ |
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355 followed by an elimination tree post-ordering.\n\ |
5451 | 356 \n\ |
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357 @var{knobs} is an optional 1-element to 3-element input vector, with a\n\ |
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358 default value of @code{[10 1 0]}. Entries not present are set to their\n\ |
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359 defaults.\n\ |
5451 | 360 \n\ |
361 @table @code\n\ | |
362 @item @var{knobs}(1)\n\ | |
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363 If @var{S} is n-by-n, then rows and columns with more than\n\ |
5451 | 364 @code{max(16,@var{knobs}(1)*sqrt(n))} entries are ignored, and ordered\n\ |
365 last in the output permutation (subject to the cmember constraints).\n\ | |
366 \n\ | |
367 @item @var{knobs}(2)\n\ | |
368 If nonzero, aggressive absorption is performed.\n\ | |
369 \n\ | |
370 @item @var{knobs}(3)\n\ | |
371 If nonzero, statistics and knobs are printed.\n\ | |
372 \n\ | |
373 @end table\n\ | |
374 \n\ | |
375 @var{cmember} is an optional vector of length n. It defines the constraints\n\ | |
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376 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is\n\ |
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377 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the\n\ |
5451 | 378 output permutation @var{p}, rows/columns in set 1 appear first, followed\n\ |
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379 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)}\n\ |
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380 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns @code{1:n}.\n\ |
5451 | 381 \n\ |
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382 @code{@var{p} = csymamd (@var{S})} is about the same as\n\ |
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383 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values\n\ |
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384 differ.\n\ |
5451 | 385 \n\ |
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386 @code{@var{stats}(4:7)} provide information if CCOLAMD was able to\n\ |
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387 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if\n\ |
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388 invalid. @code{@var{stats}(5)} is the rightmost column index that is\n\ |
5451 | 389 unsorted or contains duplicate entries, or zero if no such column exists.\n\ |
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390 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row\n\ |
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391 index in the column index given by @code{@var{stats}(5)}, or zero if no\n\ |
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392 such row index exists. @code{@var{stats}(7)} is the number of duplicate\n\ |
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393 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in\n\ |
10840 | 394 the current version of @sc{ccolamd} (reserved for future use).\n\ |
5451 | 395 \n\ |
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396 The authors of the code itself are @nospell{S. Larimore, T. Davis}\n\ |
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397 (Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with\n\ |
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398 @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation\n\ |
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399 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from\n\ |
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400 @nospell{Sandia} National Lab.\n\ |
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401 See @url{http://www.cise.ufl.edu/research/sparse} for\n\ |
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402 ccolamd, csymamd, amd, colamd, symamd, and other related orderings.\n\ |
5642 | 403 @seealso{symamd, ccolamd}\n\ |
404 @end deftypefn") | |
5451 | 405 { |
5771 | 406 octave_value_list retval; |
407 | |
5451 | 408 #if HAVE_CCOLAMD |
5771 | 409 |
5451 | 410 int nargin = args.length (); |
411 int spumoni = 0; | |
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412 |
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413 if (nargout > 2 || nargin < 1 || nargin > 3) |
5451 | 414 usage ("ccolamd: incorrect number of input and/or output arguments"); |
415 else | |
416 { | |
417 // Get knobs | |
418 OCTAVE_LOCAL_BUFFER (double, knobs, CCOLAMD_KNOBS); | |
419 CCOLAMD_NAME (_set_defaults) (knobs); | |
420 | |
421 // Check for user-passed knobs | |
422 if (nargin > 1) | |
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423 { |
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424 NDArray User_knobs = args(1).array_value (); |
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425 int nel_User_knobs = User_knobs.length (); |
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426 |
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427 if (nel_User_knobs > 0) |
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428 knobs[CCOLAMD_DENSE_ROW] = User_knobs(0); |
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429 if (nel_User_knobs > 0) |
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430 knobs[CCOLAMD_AGGRESSIVE] = User_knobs(1); |
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431 if (nel_User_knobs > 1) |
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432 spumoni = static_cast<int> (User_knobs(2)); |
5451 | 433 |
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434 // print knob settings if spumoni is set |
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435 if (spumoni) |
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436 { |
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437 octave_stdout << "\ncsymamd version " << CCOLAMD_MAIN_VERSION |
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438 << "." << CCOLAMD_SUB_VERSION |
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439 << ", " << CCOLAMD_DATE << "\n"; |
5451 | 440 |
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441 if (knobs[CCOLAMD_DENSE_ROW] >= 0) |
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442 octave_stdout << "knobs(1): " << User_knobs(0) |
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443 << ", rows/cols with > max (16," |
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444 << knobs[CCOLAMD_DENSE_ROW] |
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445 << "*sqrt (size(A,2)))" |
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446 << " entries removed\n"; |
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447 else |
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448 octave_stdout << "knobs(1): " << User_knobs(0) |
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449 << ", no dense rows/cols removed\n"; |
5451 | 450 |
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451 if (knobs[CCOLAMD_AGGRESSIVE] != 0) |
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452 octave_stdout << "knobs(2): " << User_knobs(1) |
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453 << ", aggressive absorption: yes"; |
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454 else |
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455 octave_stdout << "knobs(2): " << User_knobs(1) |
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456 << ", aggressive absorption: no"; |
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457 |
5451 | 458 |
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459 octave_stdout << "knobs(3): " << User_knobs(2) |
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460 << ", statistics and knobs printed\n"; |
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461 } |
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462 } |
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463 |
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464 octave_idx_type n_row, n_col; |
5451 | 465 octave_idx_type *ridx, *cidx; |
466 SparseMatrix sm; | |
467 SparseComplexMatrix scm; | |
468 | |
5631 | 469 if (args(0).is_sparse_type ()) |
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470 { |
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471 if (args(0).is_complex_type ()) |
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472 { |
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473 scm = args(0).sparse_complex_matrix_value (); |
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474 n_row = scm.rows (); |
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475 n_col = scm.cols (); |
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476 ridx = scm.xridx (); |
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477 cidx = scm.xcidx (); |
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478 } |
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479 else |
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480 { |
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481 sm = args(0).sparse_matrix_value (); |
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482 n_row = sm.rows (); |
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483 n_col = sm.cols (); |
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484 ridx = sm.xridx (); |
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485 cidx = sm.xcidx (); |
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486 } |
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487 } |
5451 | 488 else |
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489 { |
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490 if (args(0).is_complex_type ()) |
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491 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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492 else |
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493 sm = SparseMatrix (args(0).matrix_value ()); |
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494 |
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495 n_row = sm.rows (); |
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496 n_col = sm.cols (); |
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497 ridx = sm.xridx (); |
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498 cidx = sm.xcidx (); |
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499 } |
5451 | 500 |
501 if (n_row != n_col) | |
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502 { |
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503 error ("csymamd: matrix S must be square"); |
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504 return retval; |
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505 } |
5451 | 506 |
507 // Allocate workspace for symamd | |
508 OCTAVE_LOCAL_BUFFER (octave_idx_type, perm, n_col+1); | |
509 OCTAVE_LOCAL_BUFFER (octave_idx_type, stats, CCOLAMD_STATS); | |
510 | |
511 if (nargin > 2) | |
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512 { |
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513 NDArray in_cmember = args(2).array_value (); |
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514 octave_idx_type cslen = in_cmember.length (); |
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515 OCTAVE_LOCAL_BUFFER (octave_idx_type, cmember, cslen); |
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516 for (octave_idx_type i = 0; i < cslen; i++) |
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517 // convert cmember from 1-based to 0-based |
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518 cmember[i] = static_cast<octave_idx_type>(in_cmember(i) - 1); |
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519 |
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520 if (cslen != n_col) |
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521 error ("csymamd: CMEMBER must be of length equal to #cols of A"); |
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522 else if (!CSYMAMD_NAME () (n_col, ridx, cidx, perm, knobs, stats, |
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523 &calloc, &free, cmember, -1)) |
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524 { |
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525 CSYMAMD_NAME (_report) (stats) ; |
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526 error ("csymamd: internal error!") ; |
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527 return retval; |
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528 } |
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529 } |
5451 | 530 else |
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531 { |
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532 if (!CSYMAMD_NAME () (n_col, ridx, cidx, perm, knobs, stats, |
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533 &calloc, &free, 0, -1)) |
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534 { |
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535 CSYMAMD_NAME (_report) (stats) ; |
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536 error ("csymamd: internal error!") ; |
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537 return retval; |
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538 } |
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539 } |
5451 | 540 |
541 // return the permutation vector | |
542 NDArray out_perm (dim_vector (1, n_col)); | |
543 for (octave_idx_type i = 0; i < n_col; i++) | |
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544 out_perm(i) = perm[i] + 1; |
5451 | 545 |
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546 retval(0) = out_perm; |
5451 | 547 |
548 // Return the stats vector | |
549 if (nargout == 2) | |
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550 { |
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551 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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552 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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553 out_stats(i) = stats[i] ; |
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554 retval(1) = out_stats; |
5451 | 555 |
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556 // fix stats (5) and (6), for 1-based information on |
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557 // jumbled matrix. note that this correction doesn't |
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558 // occur if symamd returns FALSE |
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559 out_stats (CCOLAMD_INFO1) ++ ; |
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560 out_stats (CCOLAMD_INFO2) ++ ; |
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561 } |
5451 | 562 |
563 // print stats if spumoni > 0 | |
564 if (spumoni > 0) | |
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565 CSYMAMD_NAME (_report) (stats) ; |
5451 | 566 |
567 // Return the stats vector | |
568 if (nargout == 2) | |
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569 { |
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570 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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571 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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572 out_stats(i) = stats[i] ; |
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573 retval(1) = out_stats; |
5451 | 574 |
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575 // fix stats (5) and (6), for 1-based information on |
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576 // jumbled matrix. note that this correction doesn't |
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577 // occur if symamd returns FALSE |
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578 out_stats (CCOLAMD_INFO1) ++ ; |
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579 out_stats (CCOLAMD_INFO2) ++ ; |
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580 } |
5451 | 581 } |
582 | |
583 #else | |
584 | |
585 error ("csymamd: not available in this version of Octave"); | |
586 | |
587 #endif | |
5771 | 588 |
589 return retval; | |
5451 | 590 } |