Mercurial > octave
annotate libinterp/dldfcn/ccolamd.cc @ 23581:c3075ae020e1
maint: Deprecate is_complex_type and replace with iscomplex.
* ov.h (is_complex_type): Use OCTAVE_DEPRECATED macro around function.
* ov.h (iscomplex): New function.
* __ichol__.cc, __ilu__.cc, balance.cc, bsxfun.cc, cellfun.cc, conv2.cc,
daspk.cc, dasrt.cc, dassl.cc, data.cc, det.cc, dot.cc, fft.cc, fft2.cc,
fftn.cc, filter.cc, find.cc, givens.cc, graphics.cc, gsvd.cc, hess.cc,
hex2num.cc, inv.cc, kron.cc, lookup.cc, ls-mat-ascii.cc, ls-mat4.cc,
ls-mat5.cc, lsode.cc, lu.cc, matrix_type.cc, mex.cc, mgorth.cc, ordschur.cc,
pinv.cc, psi.cc, quad.cc, qz.cc, rcond.cc, schur.cc, sparse-xpow.cc, sparse.cc,
sqrtm.cc, svd.cc, sylvester.cc, symtab.cc, typecast.cc, variables.cc, xnorm.cc,
__eigs__.cc, amd.cc, ccolamd.cc, chol.cc, colamd.cc, qr.cc, symbfact.cc,
ov-base.h, ov-complex.h, ov-cx-diag.h, ov-cx-mat.h, ov-cx-sparse.h,
ov-flt-complex.h, ov-flt-cx-diag.h, ov-flt-cx-mat.h, jit-typeinfo.cc,
pt-tm-const.cc: Replace instances of is_complex_type with iscomplex.
author | Rik <rik@octave.org> |
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date | Mon, 12 Jun 2017 21:18:23 -0700 |
parents | 209e749363a2 |
children | b7747a2c88b2 |
rev | line source |
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5451 | 1 /* |
2 | |
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3 Copyright (C) 2005-2017 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 |
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8 under the terms of the GNU General Public License as published by |
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9 the Free Software Foundation; either version 3 of the License, or |
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10 (at your option) any later version. |
5451 | 11 |
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12 Octave is distributed in the hope that it will be useful, but |
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13 WITHOUT ANY WARRANTY; without even the implied warranty of |
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14 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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15 GNU General Public License for more details. |
5451 | 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 | |
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26 #if defined (HAVE_CONFIG_H) |
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27 # include "config.h" |
5451 | 28 #endif |
29 | |
30 #include <cstdlib> | |
31 | |
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32 #include "CSparse.h" |
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33 #include "Sparse.h" |
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34 #include "dNDArray.h" |
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35 #include "oct-locbuf.h" |
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36 #include "oct-sparse.h" |
5451 | 37 |
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38 #include "defun-dld.h" |
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39 #include "error.h" |
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40 #include "errwarn.h" |
5451 | 41 #include "ov.h" |
42 #include "pager.h" | |
43 | |
44 DEFUN_DLD (ccolamd, args, nargout, | |
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45 doc: /* -*- texinfo -*- |
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46 @deftypefn {} {@var{p} =} ccolamd (@var{S}) |
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47 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}) |
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48 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}, @var{cmember}) |
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49 @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{}) |
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50 |
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51 Constrained column approximate minimum degree permutation. |
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52 |
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53 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum |
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54 degree permutation vector for the sparse matrix @var{S}. For a |
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55 non-symmetric matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have |
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56 sparser LU@tie{}factors than @var{S}. |
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57 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be |
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58 sparser than @code{chol (@var{S}' * @var{S})}. |
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59 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for |
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60 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column |
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61 elimination tree post-ordering. |
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62 |
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63 @var{knobs} is an optional 1-element to 5-element input vector, with a |
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64 default value of @code{[0 10 10 1 0]} if not present or empty. Entries not |
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65 present are set to their defaults. |
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66 |
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67 @table @code |
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68 @item @var{knobs}(1) |
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69 if nonzero, the ordering is optimized for @code{lu (S(:, p))}. It will be a |
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70 poor ordering for @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}. |
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71 This is the most important knob for ccolamd. |
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72 |
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73 @item @var{knobs}(2) |
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74 if @var{S} is m-by-n, rows with more than |
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75 @code{max (16, @var{knobs}(2) * sqrt (n))} entries are ignored. |
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76 |
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77 @item @var{knobs}(3) |
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78 columns with more than |
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79 @code{max (16, @var{knobs}(3) * sqrt (min (@var{m}, @var{n})))} entries are |
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80 ignored and ordered last in the output permutation |
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81 (subject to the cmember constraints). |
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82 |
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83 @item @var{knobs}(4) |
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84 if nonzero, aggressive absorption is performed. |
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85 |
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86 @item @var{knobs}(5) |
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87 if nonzero, statistics and knobs are printed. |
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88 |
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89 @end table |
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90 |
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91 @var{cmember} is an optional vector of length @math{n}. It defines the |
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92 constraints on the column ordering. If @code{@var{cmember}(j) = @var{c}}, |
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93 then column @var{j} is in constraint set @var{c} (@var{c} must be in the |
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94 range 1 to n). In the output permutation @var{p}, all columns in set 1 |
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95 appear first, followed by all columns in set 2, and so on. |
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96 @code{@var{cmember} = ones (1,n)} if not present or empty. |
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97 @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n} |
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98 |
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99 @code{@var{p} = ccolamd (@var{S})} is about the same as |
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100 @code{@var{p} = colamd (@var{S})}. @var{knobs} and its default values |
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101 differ. @code{colamd} always does aggressive absorption, and it finds an |
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102 ordering suitable for both @code{lu (@var{S}(:, @var{p}))} and @code{chol |
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103 (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}; it cannot optimize its |
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104 ordering for @code{lu (@var{S}(:, @var{p}))} to the extent that |
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105 @code{ccolamd (@var{S}, 1)} can. |
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106 |
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107 @var{stats} is an optional 20-element output vector that provides data |
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108 about the ordering and the validity of the input matrix @var{S}. Ordering |
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109 statistics are in @code{@var{stats}(1 : 3)}. @code{@var{stats}(1)} and |
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110 @code{@var{stats}(2)} are the number of dense or empty rows and columns |
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111 ignored by @sc{ccolamd} and @code{@var{stats}(3)} is the number of garbage |
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112 collections performed on the internal data structure used by @sc{ccolamd} |
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113 (roughly of size @code{2.2 * nnz (@var{S}) + 4 * @var{m} + 7 * @var{n}} |
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114 integers). |
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115 |
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116 @code{@var{stats}(4 : 7)} provide information if CCOLAMD was able to |
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117 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if |
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118 invalid. @code{@var{stats}(5)} is the rightmost column index that is |
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119 unsorted or contains duplicate entries, or zero if no such column exists. |
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120 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row |
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121 index in the column index given by @code{@var{stats}(5)}, or zero if no |
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122 such row index exists. @code{@var{stats}(7)} is the number of duplicate |
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123 or out-of-order row indices. @code{@var{stats}(8 : 20)} is always zero in |
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124 the current version of @sc{ccolamd} (reserved for future use). |
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125 |
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126 The authors of the code itself are @nospell{S. Larimore, T. Davis} |
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127 (Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with |
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128 @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation |
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129 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from |
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130 @nospell{Sandia} National Lab. |
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131 See @url{http://www.cise.ufl.edu/research/sparse} for |
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132 ccolamd, csymamd, amd, colamd, symamd, and other related orderings. |
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133 @seealso{colamd, csymamd} |
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134 @end deftypefn */) |
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136 #if defined (HAVE_CCOLAMD) |
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139 |
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140 if (nargin < 1 || nargin > 3) |
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141 print_usage (); |
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142 |
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143 octave_value_list retval (nargout == 2 ? 2 : 1); |
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144 int spumoni = 0; |
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146 // Get knobs |
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147 OCTAVE_LOCAL_BUFFER (double, knobs, CCOLAMD_KNOBS); |
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148 CCOLAMD_NAME (_set_defaults) (knobs); |
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149 |
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150 // Check for user-passed knobs |
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151 if (nargin > 1) |
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152 { |
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153 NDArray User_knobs = args(1).array_value (); |
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154 int nel_User_knobs = User_knobs.numel (); |
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156 if (nel_User_knobs > 0) |
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157 knobs[CCOLAMD_LU] = (User_knobs(0) != 0); |
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158 if (nel_User_knobs > 1) |
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159 knobs[CCOLAMD_DENSE_ROW] = User_knobs(1); |
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160 if (nel_User_knobs > 2) |
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161 knobs[CCOLAMD_DENSE_COL] = User_knobs(2); |
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162 if (nel_User_knobs > 3) |
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163 knobs[CCOLAMD_AGGRESSIVE] = (User_knobs(3) != 0); |
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164 if (nel_User_knobs > 4) |
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165 spumoni = (User_knobs(4) != 0); |
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167 // print knob settings if spumoni is set |
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168 if (spumoni) |
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169 { |
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170 octave_stdout << "\nccolamd version " << CCOLAMD_MAIN_VERSION << "." |
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171 << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE |
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172 << ":\nknobs(1): " << User_knobs(0) << ", order for "; |
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173 if (knobs[CCOLAMD_LU] != 0) |
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174 octave_stdout << "lu (A)\n"; |
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175 else |
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176 octave_stdout << "chol (A'*A)\n"; |
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178 if (knobs[CCOLAMD_DENSE_ROW] >= 0) |
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179 octave_stdout << "knobs(2): " << User_knobs(1) |
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180 << ", rows with > max (16," |
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181 << knobs[CCOLAMD_DENSE_ROW] |
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182 << "*sqrt (size(A,2)))" |
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183 << " entries removed\n"; |
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184 else |
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185 octave_stdout << "knobs(2): " << User_knobs(1) |
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186 << ", no dense rows removed\n"; |
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188 if (knobs[CCOLAMD_DENSE_COL] >= 0) |
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189 octave_stdout << "knobs(3): " << User_knobs(2) |
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190 << ", cols with > max (16," |
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191 << knobs[CCOLAMD_DENSE_COL] << "*sqrt (size(A)))" |
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192 << " entries removed\n"; |
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193 else |
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194 octave_stdout << "knobs(3): " << User_knobs(2) |
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195 << ", no dense columns removed\n"; |
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196 |
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197 if (knobs[CCOLAMD_AGGRESSIVE] != 0) |
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198 octave_stdout << "knobs(4): " << User_knobs(3) |
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199 << ", aggressive absorption: yes"; |
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200 else |
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201 octave_stdout << "knobs(4): " << User_knobs(3) |
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202 << ", aggressive absorption: no"; |
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204 octave_stdout << "knobs(5): " << User_knobs(4) |
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205 << ", statistics and knobs printed\n"; |
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206 } |
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207 } |
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208 |
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209 octave_idx_type n_row, n_col, nnz; |
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210 octave_idx_type *ridx, *cidx; |
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211 SparseComplexMatrix scm; |
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212 SparseMatrix sm; |
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213 |
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214 if (args(0).is_sparse_type ()) |
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215 { |
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216 if (args(0).iscomplex ()) |
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217 { |
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218 scm = args(0).sparse_complex_matrix_value (); |
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219 n_row = scm.rows (); |
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220 n_col = scm.cols (); |
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221 nnz = scm.nnz (); |
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222 ridx = scm.xridx (); |
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223 cidx = scm.xcidx (); |
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224 } |
5451 | 225 else |
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226 { |
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227 sm = args(0).sparse_matrix_value (); |
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229 n_row = sm.rows (); |
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230 n_col = sm.cols (); |
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231 nnz = sm.nnz (); |
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232 ridx = sm.xridx (); |
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233 cidx = sm.xcidx (); |
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234 } |
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235 } |
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236 else |
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237 { |
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238 if (args(0).iscomplex ()) |
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239 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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240 else |
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241 sm = SparseMatrix (args(0).matrix_value ()); |
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243 n_row = sm.rows (); |
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244 n_col = sm.cols (); |
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245 nnz = sm.nnz (); |
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246 ridx = sm.xridx (); |
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247 cidx = sm.xcidx (); |
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248 } |
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250 // Allocate workspace for ccolamd |
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251 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, p, n_col+1); |
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252 for (octave_idx_type i = 0; i < n_col+1; i++) |
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253 p[i] = cidx[i]; |
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254 |
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255 octave_idx_type Alen = CCOLAMD_NAME (_recommended) (nnz, n_row, n_col); |
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256 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, A, Alen); |
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257 for (octave_idx_type i = 0; i < nnz; i++) |
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258 A[i] = ridx[i]; |
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259 |
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260 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, stats, CCOLAMD_STATS); |
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261 |
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262 if (nargin > 2) |
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263 { |
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264 NDArray in_cmember = args(2).array_value (); |
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265 octave_idx_type cslen = in_cmember.numel (); |
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266 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, cmember, cslen); |
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267 for (octave_idx_type i = 0; i < cslen; i++) |
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268 // convert cmember from 1-based to 0-based |
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269 cmember[i] = static_cast<octave::suitesparse_integer>(in_cmember(i) - 1); |
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270 |
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271 if (cslen != n_col) |
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272 error ("ccolamd: CMEMBER must be of length equal to #cols of A"); |
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273 |
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274 // Order the columns (destroys A) |
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275 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats,cmember)) |
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276 { |
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277 CCOLAMD_NAME (_report) (stats); |
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278 |
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279 error ("ccolamd: internal error!"); |
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280 } |
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281 } |
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282 else |
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283 { |
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284 // Order the columns (destroys A) |
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285 if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, 0)) |
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286 { |
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287 CCOLAMD_NAME (_report) (stats); |
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289 error ("ccolamd: internal error!"); |
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290 } |
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291 } |
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293 // return the permutation vector |
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294 NDArray out_perm (dim_vector (1, n_col)); |
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295 for (octave_idx_type i = 0; i < n_col; i++) |
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296 out_perm(i) = p[i] + 1; |
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297 |
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298 retval(0) = out_perm; |
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299 |
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300 // print stats if spumoni > 0 |
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301 if (spumoni > 0) |
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302 CCOLAMD_NAME (_report) (stats); |
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304 // Return the stats vector |
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305 if (nargout == 2) |
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306 { |
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307 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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308 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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309 out_stats(i) = stats[i]; |
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310 retval(1) = out_stats; |
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312 // fix stats (5) and (6), for 1-based information on |
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313 // jumbled matrix. note that this correction doesn't |
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314 // occur if symamd returns FALSE |
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315 out_stats(CCOLAMD_INFO1)++; |
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316 out_stats(CCOLAMD_INFO2)++; |
5451 | 317 } |
318 | |
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319 return retval; |
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320 |
5451 | 321 #else |
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322 |
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323 octave_unused_parameter (args); |
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324 octave_unused_parameter (nargout); |
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325 |
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326 err_disabled_feature ("ccolamd", "CCOLAMD"); |
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327 |
5451 | 328 #endif |
329 } | |
330 | |
331 DEFUN_DLD (csymamd, args, nargout, | |
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332 doc: /* -*- texinfo -*- |
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333 @deftypefn {} {@var{p} =} csymamd (@var{S}) |
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334 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}) |
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335 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}, @var{cmember}) |
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336 @deftypefnx {} {[@var{p}, @var{stats}] =} csymamd (@dots{}) |
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337 |
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338 For a symmetric positive definite matrix @var{S}, return the permutation |
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339 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a |
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340 sparser Cholesky@tie{}factor than @var{S}. |
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341 |
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342 Sometimes @code{csymamd} works well for symmetric indefinite matrices too. |
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343 The matrix @var{S} is assumed to be symmetric; only the strictly lower |
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344 triangular part is referenced. @var{S} must be square. The ordering is |
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345 followed by an elimination tree post-ordering. |
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346 |
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347 @var{knobs} is an optional 1-element to 3-element input vector, with a |
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348 default value of @code{[10 1 0]}. Entries not present are set to their |
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349 defaults. |
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350 |
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351 @table @code |
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352 @item @var{knobs}(1) |
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353 If @var{S} is n-by-n, then rows and columns with more than |
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354 @code{max(16,@var{knobs}(1)*sqrt(n))} entries are ignored, and ordered |
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355 last in the output permutation (subject to the cmember constraints). |
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356 |
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357 @item @var{knobs}(2) |
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358 If nonzero, aggressive absorption is performed. |
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359 |
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360 @item @var{knobs}(3) |
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361 If nonzero, statistics and knobs are printed. |
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362 |
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363 @end table |
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364 |
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365 @var{cmember} is an optional vector of length n. It defines the constraints |
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366 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is |
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367 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the |
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368 output permutation @var{p}, rows/columns in set 1 appear first, followed |
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369 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)} |
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370 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns |
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371 @code{1:n}. |
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372 |
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373 @code{@var{p} = csymamd (@var{S})} is about the same as |
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374 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values |
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375 differ. |
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376 |
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377 @code{@var{stats}(4:7)} provide information if CCOLAMD was able to |
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378 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if |
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379 invalid. @code{@var{stats}(5)} is the rightmost column index that is |
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380 unsorted or contains duplicate entries, or zero if no such column exists. |
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381 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row |
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382 index in the column index given by @code{@var{stats}(5)}, or zero if no |
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383 such row index exists. @code{@var{stats}(7)} is the number of duplicate |
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384 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in |
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385 the current version of @sc{ccolamd} (reserved for future use). |
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386 |
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387 The authors of the code itself are @nospell{S. Larimore, T. Davis} |
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388 (Univ. of Florida) and @nospell{S. Rajamanickam} in collaboration with |
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389 @nospell{J. Bilbert and E. Ng}. Supported by the National Science Foundation |
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390 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from |
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391 @nospell{Sandia} National Lab. |
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392 See @url{http://www.cise.ufl.edu/research/sparse} for |
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393 ccolamd, csymamd, amd, colamd, symamd, and other related orderings. |
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394 @seealso{symamd, ccolamd} |
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395 @end deftypefn */) |
5451 | 396 { |
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397 #if defined (HAVE_CCOLAMD) |
5771 | 398 |
5451 | 399 int nargin = args.length (); |
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400 |
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401 if (nargin < 1 || nargin > 3) |
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402 print_usage (); |
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403 |
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404 octave_value_list retval (nargout == 2 ? 2 : 1); |
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405 int spumoni = 0; |
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406 |
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407 // Get knobs |
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408 OCTAVE_LOCAL_BUFFER (double, knobs, CCOLAMD_KNOBS); |
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409 CCOLAMD_NAME (_set_defaults) (knobs); |
5451 | 410 |
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411 // Check for user-passed knobs |
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412 if (nargin > 1) |
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413 { |
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414 NDArray User_knobs = args(1).array_value (); |
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415 int nel_User_knobs = User_knobs.numel (); |
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416 |
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417 if (nel_User_knobs > 0) |
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418 knobs[CCOLAMD_DENSE_ROW] = User_knobs(0); |
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419 if (nel_User_knobs > 0) |
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420 knobs[CCOLAMD_AGGRESSIVE] = User_knobs(1); |
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421 if (nel_User_knobs > 1) |
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422 spumoni = static_cast<int> (User_knobs(2)); |
5451 | 423 |
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424 // print knob settings if spumoni is set |
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425 if (spumoni) |
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426 { |
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427 octave_stdout << "\ncsymamd version " << CCOLAMD_MAIN_VERSION |
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428 << "." << CCOLAMD_SUB_VERSION |
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429 << ", " << CCOLAMD_DATE << "\n"; |
5451 | 430 |
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431 if (knobs[CCOLAMD_DENSE_ROW] >= 0) |
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432 octave_stdout << "knobs(1): " << User_knobs(0) |
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433 << ", rows/cols with > max (16," |
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434 << knobs[CCOLAMD_DENSE_ROW] |
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435 << "*sqrt (size(A,2)))" |
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436 << " entries removed\n"; |
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437 else |
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438 octave_stdout << "knobs(1): " << User_knobs(0) |
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439 << ", no dense rows/cols removed\n"; |
5451 | 440 |
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441 if (knobs[CCOLAMD_AGGRESSIVE] != 0) |
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442 octave_stdout << "knobs(2): " << User_knobs(1) |
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443 << ", aggressive absorption: yes"; |
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444 else |
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445 octave_stdout << "knobs(2): " << User_knobs(1) |
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446 << ", aggressive absorption: no"; |
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447 |
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448 octave_stdout << "knobs(3): " << User_knobs(2) |
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449 << ", statistics and knobs printed\n"; |
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450 } |
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451 } |
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452 |
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453 octave_idx_type n_row, n_col; |
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454 octave_idx_type *ridx, *cidx; |
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455 SparseMatrix sm; |
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456 SparseComplexMatrix scm; |
5451 | 457 |
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458 if (args(0).is_sparse_type ()) |
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459 { |
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460 if (args(0).iscomplex ()) |
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461 { |
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462 scm = args(0).sparse_complex_matrix_value (); |
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463 n_row = scm.rows (); |
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464 n_col = scm.cols (); |
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465 ridx = scm.xridx (); |
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466 cidx = scm.xcidx (); |
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467 } |
5451 | 468 else |
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469 { |
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470 sm = args(0).sparse_matrix_value (); |
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471 n_row = sm.rows (); |
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472 n_col = sm.cols (); |
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473 ridx = sm.xridx (); |
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474 cidx = sm.xcidx (); |
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475 } |
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476 } |
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477 else |
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478 { |
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479 if (args(0).iscomplex ()) |
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480 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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481 else |
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482 sm = SparseMatrix (args(0).matrix_value ()); |
5451 | 483 |
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484 n_row = sm.rows (); |
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485 n_col = sm.cols (); |
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486 ridx = sm.xridx (); |
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487 cidx = sm.xcidx (); |
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488 } |
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489 |
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490 if (n_row != n_col) |
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491 err_square_matrix_required ("csymamd", "S"); |
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492 |
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493 // Allocate workspace for symamd |
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494 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, perm, n_col+1); |
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495 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, stats, CCOLAMD_STATS); |
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496 |
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497 if (nargin > 2) |
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498 { |
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499 NDArray in_cmember = args(2).array_value (); |
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500 octave_idx_type cslen = in_cmember.numel (); |
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501 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, cmember, cslen); |
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502 for (octave_idx_type i = 0; i < cslen; i++) |
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503 // convert cmember from 1-based to 0-based |
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504 cmember[i] = static_cast<octave_idx_type>(in_cmember(i) - 1); |
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505 |
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506 if (cslen != n_col) |
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507 error ("csymamd: CMEMBER must be of length equal to #cols of A"); |
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508 |
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509 if (! CSYMAMD_NAME () (n_col, |
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510 octave::to_suitesparse_intptr (ridx), |
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511 octave::to_suitesparse_intptr (cidx), |
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512 perm, knobs, stats, &calloc, &free, cmember, -1)) |
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513 { |
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514 CSYMAMD_NAME (_report)(stats); |
5451 | 515 |
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516 error ("csymamd: internal error!"); |
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517 } |
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518 } |
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519 else |
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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, 0, -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 |
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532 // return the permutation vector |
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533 NDArray out_perm (dim_vector (1, n_col)); |
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534 for (octave_idx_type i = 0; i < n_col; i++) |
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535 out_perm(i) = perm[i] + 1; |
5451 | 536 |
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537 retval(0) = out_perm; |
5451 | 538 |
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539 // print stats if spumoni > 0 |
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540 if (spumoni > 0) |
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541 CSYMAMD_NAME (_report)(stats); |
5451 | 542 |
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543 // Return the stats vector |
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544 if (nargout == 2) |
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545 { |
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546 NDArray out_stats (dim_vector (1, CCOLAMD_STATS)); |
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547 for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++) |
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548 out_stats(i) = stats[i]; |
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549 retval(1) = out_stats; |
5451 | 550 |
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551 // fix stats (5) and (6), for 1-based information on |
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552 // jumbled matrix. note that this correction doesn't |
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553 // occur if symamd returns FALSE |
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554 out_stats(CCOLAMD_INFO1)++; |
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555 out_stats(CCOLAMD_INFO2)++; |
5451 | 556 } |
557 | |
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558 return retval; |
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559 |
5451 | 560 #else |
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561 |
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562 octave_unused_parameter (args); |
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563 octave_unused_parameter (nargout); |
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564 |
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565 err_disabled_feature ("csymamd", "CCOLAMD"); |
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566 |
5451 | 567 #endif |
568 } |