Mercurial > octave
annotate libinterp/dldfcn/ccolamd.cc @ 27919:1891570abac8
update Octave Project Developers copyright for the new year
In files that have the "Octave Project Developers" copyright notice,
update for 2020.
author | John W. Eaton <jwe@octave.org> |
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date | Mon, 06 Jan 2020 22:29:51 -0500 |
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3 Copyright (C) 2005-2020 The Octave Project Developers |
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4 |
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5 See the file COPYRIGHT.md in the top-level directory of this distribution |
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6 or <https://octave.org/COPYRIGHT.html/>. |
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7 |
5451 | 8 |
7016 | 9 This file is part of Octave. |
10 | |
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11 Octave is free software: you can redistribute it and/or modify it |
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12 under the terms of the GNU General Public License as published by |
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13 the Free Software Foundation, either version 3 of the License, or |
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14 (at your option) any later version. |
5451 | 15 |
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16 Octave is distributed in the hope that it will be useful, but |
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17 WITHOUT ANY WARRANTY; without even the implied warranty of |
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18 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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19 GNU General Public License for more details. |
5451 | 20 |
21 You should have received a copy of the GNU General Public License | |
7016 | 22 along with Octave; see the file COPYING. If not, see |
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23 <https://www.gnu.org/licenses/>. |
5451 | 24 |
25 */ | |
26 | |
27 // This is the octave interface to ccolamd, which bore the copyright given | |
28 // in the help of the functions. | |
29 | |
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30 #if defined (HAVE_CONFIG_H) |
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31 # include "config.h" |
5451 | 32 #endif |
33 | |
34 #include <cstdlib> | |
35 | |
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36 #include "CSparse.h" |
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37 #include "Sparse.h" |
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38 #include "dNDArray.h" |
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39 #include "oct-locbuf.h" |
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40 #include "oct-sparse.h" |
5451 | 41 |
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42 #include "defun-dld.h" |
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43 #include "error.h" |
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44 #include "errwarn.h" |
5451 | 45 #include "ov.h" |
46 #include "pager.h" | |
47 | |
48 DEFUN_DLD (ccolamd, args, nargout, | |
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49 doc: /* -*- texinfo -*- |
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50 @deftypefn {} {@var{p} =} ccolamd (@var{S}) |
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51 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}) |
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52 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}, @var{cmember}) |
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53 @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{}) |
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54 |
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55 Constrained column approximate minimum degree permutation. |
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56 |
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57 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum |
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58 degree permutation vector for the sparse matrix @var{S}. For a |
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59 non-symmetric matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have |
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60 sparser LU@tie{}factors than @var{S}. |
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61 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be |
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62 sparser than @code{chol (@var{S}' * @var{S})}. |
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63 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for |
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64 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column |
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65 elimination tree post-ordering. |
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66 |
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67 @var{knobs} is an optional 1-element to 5-element input vector, with a |
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68 default value of @code{[0 10 10 1 0]} if not present or empty. Entries not |
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69 present are set to their defaults. |
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70 |
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71 @table @code |
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72 @item @var{knobs}(1) |
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73 if nonzero, the ordering is optimized for @code{lu (S(:, p))}. It will be a |
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74 poor ordering for @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}. |
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75 This is the most important knob for ccolamd. |
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76 |
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77 @item @var{knobs}(2) |
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78 if @var{S} is m-by-n, rows with more than |
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79 @code{max (16, @var{knobs}(2) * sqrt (n))} entries are ignored. |
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80 |
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81 @item @var{knobs}(3) |
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82 columns with more than |
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83 @code{max (16, @var{knobs}(3) * sqrt (min (@var{m}, @var{n})))} entries are |
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84 ignored and ordered last in the output permutation |
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85 (subject to the cmember constraints). |
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86 |
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87 @item @var{knobs}(4) |
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88 if nonzero, aggressive absorption is performed. |
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89 |
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90 @item @var{knobs}(5) |
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91 if nonzero, statistics and knobs are printed. |
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92 |
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93 @end table |
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94 |
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95 @var{cmember} is an optional vector of length @math{n}. It defines the |
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96 constraints on the column ordering. If @code{@var{cmember}(j) = @var{c}}, |
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97 then column @var{j} is in constraint set @var{c} (@var{c} must be in the |
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98 range 1 to n). In the output permutation @var{p}, all columns in set 1 |
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99 appear first, followed by all columns in set 2, and so on. |
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100 @code{@var{cmember} = ones (1,n)} if not present or empty. |
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101 @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n} |
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102 |
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103 @code{@var{p} = ccolamd (@var{S})} is about the same as |
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104 @code{@var{p} = colamd (@var{S})}. @var{knobs} and its default values |
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105 differ. @code{colamd} always does aggressive absorption, and it finds an |
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106 ordering suitable for both @code{lu (@var{S}(:, @var{p}))} and @code{chol |
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107 (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}; it cannot optimize its |
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108 ordering for @code{lu (@var{S}(:, @var{p}))} to the extent that |
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109 @code{ccolamd (@var{S}, 1)} can. |
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110 |
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111 @var{stats} is an optional 20-element output vector that provides data |
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112 about the ordering and the validity of the input matrix @var{S}. Ordering |
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113 statistics are in @code{@var{stats}(1 : 3)}. @code{@var{stats}(1)} and |
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114 @code{@var{stats}(2)} are the number of dense or empty rows and columns |
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115 ignored by @sc{ccolamd} and @code{@var{stats}(3)} is the number of garbage |
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116 collections performed on the internal data structure used by @sc{ccolamd} |
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117 (roughly of size @code{2.2 * nnz (@var{S}) + 4 * @var{m} + 7 * @var{n}} |
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118 integers). |
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119 |
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120 @code{@var{stats}(4 : 7)} provide information if CCOLAMD was able to |
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121 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if |
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122 invalid. @code{@var{stats}(5)} is the rightmost column index that is |
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123 unsorted or contains duplicate entries, or zero if no such column exists. |
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124 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row |
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125 index in the column index given by @code{@var{stats}(5)}, or zero if no |
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126 such row index exists. @code{@var{stats}(7)} is the number of duplicate |
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127 or out-of-order row indices. @code{@var{stats}(8 : 20)} is always zero in |
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128 the current version of @sc{ccolamd} (reserved for future use). |
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129 |
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130 The authors of the code itself are @nospell{S. Larimore, T. Davis} and |
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131 @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}. |
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132 Supported by the National Science Foundation |
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133 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from |
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134 @nospell{Sandia} National Lab. |
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135 See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd, |
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136 csymamd, amd, colamd, symamd, and other related orderings. |
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137 @seealso{colamd, csymamd} |
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138 @end deftypefn */) |
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140 #if defined (HAVE_CCOLAMD) |
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143 |
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144 if (nargin < 1 || nargin > 3) |
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145 print_usage (); |
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146 |
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147 octave_value_list retval (nargout == 2 ? 2 : 1); |
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148 int spumoni = 0; |
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150 // Get knobs |
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151 static_assert (CCOLAMD_KNOBS <= 40, "ccolamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org"); |
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152 double knob_storage[CCOLAMD_KNOBS]; |
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153 double *knobs = &knob_storage[0]; |
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154 CCOLAMD_NAME (_set_defaults) (knobs); |
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155 |
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156 // Check for user-passed knobs |
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157 if (nargin > 1) |
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158 { |
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159 NDArray User_knobs = args(1).array_value (); |
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160 int nel_User_knobs = User_knobs.numel (); |
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162 if (nel_User_knobs > 0) |
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163 knobs[CCOLAMD_LU] = (User_knobs(0) != 0); |
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164 if (nel_User_knobs > 1) |
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165 knobs[CCOLAMD_DENSE_ROW] = User_knobs(1); |
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166 if (nel_User_knobs > 2) |
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167 knobs[CCOLAMD_DENSE_COL] = User_knobs(2); |
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168 if (nel_User_knobs > 3) |
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169 knobs[CCOLAMD_AGGRESSIVE] = (User_knobs(3) != 0); |
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170 if (nel_User_knobs > 4) |
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171 spumoni = (User_knobs(4) != 0); |
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173 // print knob settings if spumoni is set |
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174 if (spumoni) |
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175 { |
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176 octave_stdout << "\nccolamd version " << CCOLAMD_MAIN_VERSION << '.' |
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177 << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE |
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178 << ":\nknobs(1): " << User_knobs(0) << ", order for "; |
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179 if (knobs[CCOLAMD_LU] != 0) |
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180 octave_stdout << "lu (A)\n"; |
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181 else |
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182 octave_stdout << "chol (A'*A)\n"; |
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184 if (knobs[CCOLAMD_DENSE_ROW] >= 0) |
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185 octave_stdout << "knobs(2): " << User_knobs(1) |
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186 << ", rows with > max (16," |
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187 << knobs[CCOLAMD_DENSE_ROW] |
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188 << "*sqrt (size(A,2)))" |
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189 << " entries removed\n"; |
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190 else |
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191 octave_stdout << "knobs(2): " << User_knobs(1) |
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192 << ", no dense rows removed\n"; |
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194 if (knobs[CCOLAMD_DENSE_COL] >= 0) |
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195 octave_stdout << "knobs(3): " << User_knobs(2) |
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196 << ", cols with > max (16," |
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197 << knobs[CCOLAMD_DENSE_COL] << "*sqrt (size(A)))" |
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198 << " entries removed\n"; |
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199 else |
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200 octave_stdout << "knobs(3): " << User_knobs(2) |
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201 << ", no dense columns removed\n"; |
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202 |
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203 if (knobs[CCOLAMD_AGGRESSIVE] != 0) |
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204 octave_stdout << "knobs(4): " << User_knobs(3) |
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205 << ", aggressive absorption: yes"; |
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206 else |
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207 octave_stdout << "knobs(4): " << User_knobs(3) |
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208 << ", aggressive absorption: no"; |
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210 octave_stdout << "knobs(5): " << User_knobs(4) |
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211 << ", statistics and knobs printed\n"; |
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212 } |
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213 } |
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214 |
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215 octave_idx_type n_row, n_col, nnz; |
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216 octave_idx_type *ridx, *cidx; |
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217 SparseComplexMatrix scm; |
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218 SparseMatrix sm; |
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219 |
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220 if (args(0).issparse ()) |
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221 { |
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222 if (args(0).iscomplex ()) |
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223 { |
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224 scm = args(0).sparse_complex_matrix_value (); |
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225 n_row = scm.rows (); |
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226 n_col = scm.cols (); |
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227 nnz = scm.nnz (); |
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228 ridx = scm.xridx (); |
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229 cidx = scm.xcidx (); |
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230 } |
5451 | 231 else |
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232 { |
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233 sm = args(0).sparse_matrix_value (); |
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235 n_row = sm.rows (); |
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236 n_col = sm.cols (); |
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237 nnz = sm.nnz (); |
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238 ridx = sm.xridx (); |
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239 cidx = sm.xcidx (); |
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240 } |
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241 } |
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242 else |
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243 { |
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244 if (args(0).iscomplex ()) |
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245 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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246 else |
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247 sm = SparseMatrix (args(0).matrix_value ()); |
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249 n_row = sm.rows (); |
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250 n_col = sm.cols (); |
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251 nnz = sm.nnz (); |
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252 ridx = sm.xridx (); |
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253 cidx = sm.xcidx (); |
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254 } |
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256 // Allocate workspace for ccolamd |
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257 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, p, n_col+1); |
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258 for (octave_idx_type i = 0; i < n_col+1; i++) |
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259 p[i] = cidx[i]; |
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260 |
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261 octave_idx_type Alen = CCOLAMD_NAME (_recommended) (nnz, n_row, n_col); |
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262 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, A, Alen); |
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263 for (octave_idx_type i = 0; i < nnz; i++) |
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264 A[i] = ridx[i]; |
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265 |
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266 static_assert (CCOLAMD_STATS <= 40, "ccolamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org"); |
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267 octave::suitesparse_integer stats_storage[CCOLAMD_STATS]; |
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268 octave::suitesparse_integer *stats = &stats_storage[0]; |
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269 |
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270 if (nargin > 2) |
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271 { |
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272 NDArray in_cmember = args(2).array_value (); |
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273 octave_idx_type cslen = in_cmember.numel (); |
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274 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, cmember, cslen); |
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275 for (octave_idx_type i = 0; i < cslen; i++) |
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276 // convert cmember from 1-based to 0-based |
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277 cmember[i] = static_cast<octave::suitesparse_integer>(in_cmember(i) - 1); |
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278 |
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279 if (cslen != n_col) |
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280 error ("ccolamd: CMEMBER must be of length equal to #cols of A"); |
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281 |
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282 // Order the columns (destroys A) |
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283 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats,cmember)) |
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284 { |
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285 CCOLAMD_NAME (_report) (stats); |
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286 |
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287 error ("ccolamd: internal error!"); |
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288 } |
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289 } |
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290 else |
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291 { |
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292 // Order the columns (destroys A) |
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293 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, nullptr)) |
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294 { |
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295 CCOLAMD_NAME (_report) (stats); |
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297 error ("ccolamd: internal error!"); |
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298 } |
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299 } |
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301 // return the permutation vector |
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302 NDArray out_perm (dim_vector (1, n_col)); |
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303 for (octave_idx_type i = 0; i < n_col; i++) |
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304 out_perm(i) = p[i] + 1; |
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305 |
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306 retval(0) = out_perm; |
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307 |
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308 // print stats if spumoni > 0 |
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309 if (spumoni > 0) |
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310 CCOLAMD_NAME (_report) (stats); |
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312 // Return the stats vector |
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313 if (nargout == 2) |
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314 { |
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315 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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316 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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317 out_stats(i) = stats[i]; |
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318 retval(1) = out_stats; |
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320 // fix stats (5) and (6), for 1-based information on |
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321 // jumbled matrix. note that this correction doesn't |
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322 // occur if symamd returns FALSE |
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323 out_stats(CCOLAMD_INFO1)++; |
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324 out_stats(CCOLAMD_INFO2)++; |
5451 | 325 } |
326 | |
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327 return retval; |
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328 |
5451 | 329 #else |
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330 |
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331 octave_unused_parameter (args); |
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332 octave_unused_parameter (nargout); |
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333 |
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334 err_disabled_feature ("ccolamd", "CCOLAMD"); |
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335 |
5451 | 336 #endif |
337 } | |
338 | |
339 DEFUN_DLD (csymamd, args, nargout, | |
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340 doc: /* -*- texinfo -*- |
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341 @deftypefn {} {@var{p} =} csymamd (@var{S}) |
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342 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}) |
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343 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}, @var{cmember}) |
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344 @deftypefnx {} {[@var{p}, @var{stats}] =} csymamd (@dots{}) |
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345 |
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346 For a symmetric positive definite matrix @var{S}, return the permutation |
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347 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a |
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348 sparser Cholesky@tie{}factor than @var{S}. |
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349 |
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350 Sometimes @code{csymamd} works well for symmetric indefinite matrices too. |
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351 The matrix @var{S} is assumed to be symmetric; only the strictly lower |
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352 triangular part is referenced. @var{S} must be square. The ordering is |
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353 followed by an elimination tree post-ordering. |
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354 |
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355 @var{knobs} is an optional 1-element to 3-element input vector, with a |
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356 default value of @code{[10 1 0]}. Entries not present are set to their |
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357 defaults. |
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358 |
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359 @table @code |
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360 @item @var{knobs}(1) |
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361 If @var{S} is n-by-n, then rows and columns with more than |
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362 @code{max(16,@var{knobs}(1)*sqrt(n))} entries are ignored, and ordered |
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363 last in the output permutation (subject to the cmember constraints). |
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364 |
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365 @item @var{knobs}(2) |
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366 If nonzero, aggressive absorption is performed. |
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367 |
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368 @item @var{knobs}(3) |
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369 If nonzero, statistics and knobs are printed. |
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370 |
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371 @end table |
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372 |
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373 @var{cmember} is an optional vector of length n. It defines the constraints |
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374 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is |
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375 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the |
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376 output permutation @var{p}, rows/columns in set 1 appear first, followed |
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377 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)} |
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378 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns |
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379 @code{1:n}. |
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380 |
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381 @code{@var{p} = csymamd (@var{S})} is about the same as |
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382 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values |
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383 differ. |
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384 |
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385 @code{@var{stats}(4:7)} provide information if CCOLAMD was able to |
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386 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if |
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387 invalid. @code{@var{stats}(5)} is the rightmost column index that is |
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388 unsorted or contains duplicate entries, or zero if no such column exists. |
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389 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row |
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390 index in the column index given by @code{@var{stats}(5)}, or zero if no |
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391 such row index exists. @code{@var{stats}(7)} is the number of duplicate |
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392 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in |
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393 the current version of @sc{ccolamd} (reserved for future use). |
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394 |
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395 The authors of the code itself are @nospell{S. Larimore, T. Davis} and |
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396 @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}. |
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397 Supported by the National Science Foundation |
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398 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from |
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399 @nospell{Sandia} National Lab. |
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400 See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd, |
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401 colamd, csymamd, amd, colamd, symamd, and other related orderings. |
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402 @seealso{symamd, ccolamd} |
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403 @end deftypefn */) |
5451 | 404 { |
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405 #if defined (HAVE_CCOLAMD) |
5771 | 406 |
5451 | 407 int nargin = args.length (); |
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408 |
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409 if (nargin < 1 || nargin > 3) |
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410 print_usage (); |
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411 |
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412 octave_value_list retval (nargout == 2 ? 2 : 1); |
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413 int spumoni = 0; |
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414 |
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415 // Get knobs |
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416 static_assert (CCOLAMD_KNOBS <= 40, "csymamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org"); |
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417 double knob_storage[CCOLAMD_KNOBS]; |
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418 double *knobs = &knob_storage[0]; |
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419 CCOLAMD_NAME (_set_defaults) (knobs); |
5451 | 420 |
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421 // Check for user-passed knobs |
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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.numel (); |
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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 > 1) |
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430 knobs[CCOLAMD_AGGRESSIVE] = User_knobs(1); |
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431 if (nel_User_knobs > 2) |
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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 |
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458 octave_stdout << "knobs(3): " << User_knobs(2) |
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459 << ", statistics and knobs printed\n"; |
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460 } |
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461 } |
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462 |
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463 octave_idx_type n_row, n_col; |
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464 octave_idx_type *ridx, *cidx; |
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465 SparseMatrix sm; |
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466 SparseComplexMatrix scm; |
5451 | 467 |
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468 if (args(0).issparse ()) |
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469 { |
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470 if (args(0).iscomplex ()) |
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471 { |
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472 scm = args(0).sparse_complex_matrix_value (); |
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473 n_row = scm.rows (); |
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474 n_col = scm.cols (); |
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475 ridx = scm.xridx (); |
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476 cidx = scm.xcidx (); |
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477 } |
5451 | 478 else |
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479 { |
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480 sm = args(0).sparse_matrix_value (); |
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481 n_row = sm.rows (); |
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482 n_col = sm.cols (); |
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483 ridx = sm.xridx (); |
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484 cidx = sm.xcidx (); |
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485 } |
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486 } |
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487 else |
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488 { |
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489 if (args(0).iscomplex ()) |
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490 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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491 else |
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492 sm = SparseMatrix (args(0).matrix_value ()); |
5451 | 493 |
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494 n_row = sm.rows (); |
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495 n_col = sm.cols (); |
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496 ridx = sm.xridx (); |
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497 cidx = sm.xcidx (); |
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498 } |
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499 |
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500 if (n_row != n_col) |
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501 err_square_matrix_required ("csymamd", "S"); |
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502 |
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503 // Allocate workspace for symamd |
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504 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, perm, n_col+1); |
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505 static_assert (CCOLAMD_STATS <= 40, "csymamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org"); |
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506 octave::suitesparse_integer stats_storage[CCOLAMD_STATS]; |
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507 octave::suitesparse_integer *stats = &stats_storage[0]; |
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508 |
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509 if (nargin > 2) |
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510 { |
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511 NDArray in_cmember = args(2).array_value (); |
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512 octave_idx_type cslen = in_cmember.numel (); |
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513 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, cmember, cslen); |
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514 for (octave_idx_type i = 0; i < cslen; i++) |
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515 // convert cmember from 1-based to 0-based |
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516 cmember[i] = static_cast<octave_idx_type> (in_cmember(i) - 1); |
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517 |
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518 if (cslen != n_col) |
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519 error ("csymamd: CMEMBER must be of length equal to #cols of A"); |
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520 |
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521 if (! CSYMAMD_NAME () (n_col, |
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522 octave::to_suitesparse_intptr (ridx), |
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523 octave::to_suitesparse_intptr (cidx), |
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524 perm, knobs, stats, &calloc, &free, cmember, -1)) |
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525 { |
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526 CSYMAMD_NAME (_report)(stats); |
5451 | 527 |
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528 error ("csymamd: internal error!"); |
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529 } |
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530 } |
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531 else |
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532 { |
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533 if (! CSYMAMD_NAME () (n_col, |
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534 octave::to_suitesparse_intptr (ridx), |
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535 octave::to_suitesparse_intptr (cidx), |
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536 perm, knobs, stats, &calloc, &free, nullptr, -1)) |
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537 { |
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538 CSYMAMD_NAME (_report)(stats); |
5451 | 539 |
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540 error ("csymamd: internal error!"); |
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541 } |
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542 } |
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543 |
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544 // return the permutation vector |
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2015 Code Sprint: ccolamd.cc: use ovl().
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545 NDArray out_perm (dim_vector (1, n_col)); |
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546 for (octave_idx_type i = 0; i < n_col; i++) |
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547 out_perm(i) = perm[i] + 1; |
5451 | 548 |
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549 retval(0) = out_perm; |
5451 | 550 |
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551 // print stats if spumoni > 0 |
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552 if (spumoni > 0) |
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553 CSYMAMD_NAME (_report)(stats); |
5451 | 554 |
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555 // Return the stats vector |
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556 if (nargout == 2) |
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557 { |
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558 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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559 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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560 out_stats(i) = stats[i]; |
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561 retval(1) = out_stats; |
5451 | 562 |
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563 // fix stats (5) and (6), for 1-based information on |
4c9df9f444db
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564 // jumbled matrix. note that this correction doesn't |
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2015 Code Sprint: ccolamd.cc: use ovl().
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565 // occur if symamd returns FALSE |
21602
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|
566 out_stats(CCOLAMD_INFO1)++; |
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567 out_stats(CCOLAMD_INFO2)++; |
5451 | 568 } |
569 | |
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570 return retval; |
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571 |
5451 | 572 #else |
21691
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Eliminate unused variable warnings for conditionally compiled code.
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|
573 |
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574 octave_unused_parameter (args); |
263d18409fdf
Eliminate unused variable warnings for conditionally compiled code.
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575 octave_unused_parameter (nargout); |
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|
576 |
21109
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|
577 err_disabled_feature ("csymamd", "CCOLAMD"); |
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578 |
5451 | 579 #endif |
580 } |