Mercurial > hg > octave-nkf
annotate src/DLD-FUNCTIONS/colamd.cc @ 13294:7dce7e110511
make concatenation of class objects work
* data.h: New file.
* src/Makefile.am (octinclude_HEADERS): Add it to the list.
* data.cc (attempt_type_conversion): New static function.
(do_class_concat): New function.
(do_cat): Use it if any elements of the list are objects.
Check whether any elements of the list are objects or cells.
Check whether all elements of the list are complex.
Check whether the first element of the list is a struct.
Maybe convert elements of the list to cells.
New tests for horzcat and vertcat.
* data.h (do_class_concat): Provide decl.
* ov-class.h (octave_class::octave_class): Allow optional parent
list.
* ov.h, ov.h (octave_value::octave_value (const Octave_map&,
const std::string&)): Likewise.
* pt-mat.cc (do_class_concat): New static function.
(tree_matrix::rvalue1): Use it to concatenate objects.
author | John W. Eaton <jwe@octave.org> |
---|---|
date | Fri, 07 Oct 2011 22:16:07 -0400 |
parents | cf5ebc0e47e4 |
children | b0cdd60db5e5 |
rev | line source |
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5164 | 1 /* |
2 | |
11523 | 3 Copyright (C) 2004-2011 David Bateman |
4 Copyright (C) 1998-2004 Andy Adler | |
7016 | 5 |
6 This file is part of Octave. | |
5164 | 7 |
8 Octave is free software; you can redistribute it and/or modify it | |
9 under the terms of the GNU General Public License as published by the | |
7016 | 10 Free Software Foundation; either version 3 of the License, or (at your |
11 option) any later version. | |
5164 | 12 |
13 Octave is distributed in the hope that it will be useful, but WITHOUT | |
14 ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or | |
15 FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License | |
16 for more details. | |
17 | |
18 You should have received a copy of the GNU General Public License | |
7016 | 19 along with Octave; see the file COPYING. If not, see |
20 <http://www.gnu.org/licenses/>. | |
5164 | 21 |
22 */ | |
23 | |
24 // This is the octave interface to colamd, which bore the copyright given | |
25 // in the help of the functions. | |
26 | |
27 #ifdef HAVE_CONFIG_H | |
28 #include <config.h> | |
29 #endif | |
30 | |
31 #include <cstdlib> | |
32 | |
33 #include <string> | |
34 #include <vector> | |
35 | |
36 #include "ov.h" | |
37 #include "defun-dld.h" | |
38 #include "pager.h" | |
39 #include "ov-re-mat.h" | |
40 | |
41 #include "ov-re-sparse.h" | |
42 #include "ov-cx-sparse.h" | |
43 | |
5451 | 44 #include "oct-sparse.h" |
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45 #include "oct-locbuf.h" |
5164 | 46 |
5440 | 47 #ifdef IDX_TYPE_LONG |
48 #define COLAMD_NAME(name) colamd_l ## name | |
49 #define SYMAMD_NAME(name) symamd_l ## name | |
50 #else | |
51 #define COLAMD_NAME(name) colamd ## name | |
52 #define SYMAMD_NAME(name) symamd ## name | |
53 #endif | |
54 | |
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55 // The symmetric column elimination tree code take from the Davis LDL code. |
5164 | 56 // Copyright given elsewhere in this file. |
7924 | 57 static void |
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58 symetree (const octave_idx_type *ridx, const octave_idx_type *cidx, |
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59 octave_idx_type *Parent, octave_idx_type *P, octave_idx_type n) |
5164 | 60 { |
5440 | 61 OCTAVE_LOCAL_BUFFER (octave_idx_type, Flag, n); |
62 OCTAVE_LOCAL_BUFFER (octave_idx_type, Pinv, (P ? n : 0)); | |
5164 | 63 if (P) |
64 // If P is present then compute Pinv, the inverse of P | |
5440 | 65 for (octave_idx_type k = 0 ; k < n ; k++) |
5164 | 66 Pinv [P [k]] = k ; |
67 | |
5440 | 68 for (octave_idx_type k = 0 ; k < n ; k++) |
5164 | 69 { |
70 // L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) | |
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71 Parent [k] = n ; // parent of k is not yet known |
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72 Flag [k] = k ; // mark node k as visited |
5440 | 73 octave_idx_type kk = (P) ? (P [k]) : (k) ; // kth original, or permuted, column |
74 octave_idx_type p2 = cidx [kk+1] ; | |
75 for (octave_idx_type p = cidx [kk] ; p < p2 ; p++) | |
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76 { |
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77 // A (i,k) is nonzero (original or permuted A) |
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78 octave_idx_type i = (Pinv) ? (Pinv [ridx [p]]) : (ridx [p]) ; |
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79 if (i < k) |
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80 { |
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81 // follow path from i to root of etree, stop at flagged node |
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82 for ( ; Flag [i] != k ; i = Parent [i]) |
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83 { |
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84 // find parent of i if not yet determined |
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85 if (Parent [i] == n) |
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86 Parent [i] = k ; |
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87 Flag [i] = k ; // mark i as visited |
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88 } |
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89 } |
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90 } |
5164 | 91 } |
92 } | |
93 | |
94 // The elimination tree post-ordering code below is taken from SuperLU | |
7924 | 95 static inline octave_idx_type |
96 make_set (octave_idx_type i, octave_idx_type *pp) | |
5164 | 97 { |
98 pp[i] = i; | |
99 return i; | |
100 } | |
101 | |
7924 | 102 static inline octave_idx_type |
103 link (octave_idx_type s, octave_idx_type t, octave_idx_type *pp) | |
5164 | 104 { |
105 pp[s] = t; | |
106 return t; | |
107 } | |
108 | |
7924 | 109 static inline octave_idx_type |
110 find (octave_idx_type i, octave_idx_type *pp) | |
5164 | 111 { |
5440 | 112 register octave_idx_type p, gp; |
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113 |
5164 | 114 p = pp[i]; |
115 gp = pp[p]; | |
7924 | 116 |
117 while (gp != p) | |
118 { | |
119 pp[i] = gp; | |
120 i = gp; | |
121 p = pp[i]; | |
122 gp = pp[p]; | |
123 } | |
124 | |
125 return p; | |
5164 | 126 } |
127 | |
7924 | 128 static octave_idx_type |
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129 etdfs (octave_idx_type v, octave_idx_type *first_kid, |
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130 octave_idx_type *next_kid, octave_idx_type *post, |
7924 | 131 octave_idx_type postnum) |
5164 | 132 { |
7924 | 133 for (octave_idx_type w = first_kid[v]; w != -1; w = next_kid[w]) |
5164 | 134 postnum = etdfs (w, first_kid, next_kid, post, postnum); |
7924 | 135 |
5164 | 136 post[postnum++] = v; |
137 | |
138 return postnum; | |
139 } | |
140 | |
7924 | 141 static void |
142 tree_postorder (octave_idx_type n, octave_idx_type *parent, | |
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143 octave_idx_type *post) |
5164 | 144 { |
145 // Allocate storage for working arrays and results | |
5440 | 146 OCTAVE_LOCAL_BUFFER (octave_idx_type, first_kid, n+1); |
147 OCTAVE_LOCAL_BUFFER (octave_idx_type, next_kid, n+1); | |
5164 | 148 |
149 // Set up structure describing children | |
7924 | 150 for (octave_idx_type v = 0; v <= n; first_kid[v++] = -1) |
151 /* do nothing */; | |
152 | |
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153 for (octave_idx_type v = n-1; v >= 0; v--) |
5164 | 154 { |
5440 | 155 octave_idx_type dad = parent[v]; |
5164 | 156 next_kid[v] = first_kid[dad]; |
157 first_kid[dad] = v; | |
158 } | |
159 | |
160 // Depth-first search from dummy root vertex #n | |
161 etdfs (n, first_kid, next_kid, post, 0); | |
162 } | |
163 | |
7924 | 164 static void |
165 coletree (const octave_idx_type *ridx, const octave_idx_type *colbeg, | |
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166 octave_idx_type *colend, octave_idx_type *parent, |
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167 octave_idx_type nr, octave_idx_type nc) |
5164 | 168 { |
5440 | 169 OCTAVE_LOCAL_BUFFER (octave_idx_type, root, nc); |
170 OCTAVE_LOCAL_BUFFER (octave_idx_type, pp, nc); | |
171 OCTAVE_LOCAL_BUFFER (octave_idx_type, firstcol, nr); | |
5164 | 172 |
173 // Compute firstcol[row] = first nonzero column in row | |
7924 | 174 for (octave_idx_type row = 0; row < nr; firstcol[row++] = nc) |
175 /* do nothing */; | |
176 | |
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177 for (octave_idx_type col = 0; col < nc; col++) |
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178 for (octave_idx_type p = colbeg[col]; p < colend[col]; p++) |
5164 | 179 { |
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180 octave_idx_type row = ridx[p]; |
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181 if (firstcol[row] > col) |
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182 firstcol[row] = col; |
5164 | 183 } |
184 | |
185 // Compute etree by Liu's algorithm for symmetric matrices, | |
186 // except use (firstcol[r],c) in place of an edge (r,c) of A. | |
187 // Thus each row clique in A'*A is replaced by a star | |
188 // centered at its first vertex, which has the same fill. | |
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189 for (octave_idx_type col = 0; col < nc; col++) |
5164 | 190 { |
5440 | 191 octave_idx_type cset = make_set (col, pp); |
5164 | 192 root[cset] = col; |
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193 parent[col] = nc; |
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194 for (octave_idx_type p = colbeg[col]; p < colend[col]; p++) |
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195 { |
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196 octave_idx_type row = firstcol[ridx[p]]; |
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197 if (row >= col) |
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198 continue; |
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199 octave_idx_type rset = find (row, pp); |
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200 octave_idx_type rroot = root[rset]; |
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201 if (rroot != col) |
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202 { |
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203 parent[rroot] = col; |
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204 cset = link (cset, rset, pp); |
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205 root[cset] = col; |
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206 } |
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207 } |
5164 | 208 } |
209 } | |
210 | |
211 DEFUN_DLD (colamd, args, nargout, | |
212 "-*- texinfo -*-\n\ | |
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213 @deftypefn {Loadable Function} {@var{p} =} colamd (@var{S})\n\ |
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214 @deftypefnx {Loadable Function} {@var{p} =} colamd (@var{S}, @var{knobs})\n\ |
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215 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} colamd (@var{S})\n\ |
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216 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} colamd (@var{S}, @var{knobs})\n\ |
5164 | 217 \n\ |
10840 | 218 Column approximate minimum degree permutation.\n\ |
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219 @code{@var{p} = colamd (@var{S})} returns the column approximate minimum\n\ |
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220 degree permutation vector for the sparse matrix @var{S}. For a\n\ |
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221 non-symmetric matrix @var{S}, @code{@var{S}(:,@var{p})} tends to have\n\ |
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222 sparser LU@tie{}factors than @var{S}. The Cholesky@tie{}factorization of\n\ |
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223 @code{@var{S}(:,@var{p})' * @var{S}(:,@var{p})} also tends to be sparser\n\ |
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224 than that of @code{@var{S}' * @var{S}}.\n\ |
5164 | 225 \n\ |
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226 @var{knobs} is an optional one- to three-element input vector. If @var{S} is\n\ |
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227 m-by-n, then rows with more than @code{max(16,@var{knobs}(1)*sqrt(n))}\n\ |
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228 entries are ignored. Columns with more than\n\ |
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229 @code{max(16,@var{knobs}(2)*sqrt(min(m,n)))} entries are removed prior to\n\ |
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230 ordering, and ordered last in the output permutation @var{p}. Only\n\ |
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231 completely dense rows or columns are removed if @code{@var{knobs}(1)} and\n\ |
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232 @code{@var{knobs}(2)} are < 0, respectively. If @code{@var{knobs}(3)} is\n\ |
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233 nonzero, @var{stats} and @var{knobs} are printed. The default is\n\ |
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234 @code{@var{knobs} = [10 10 0]}. Note that @var{knobs} differs from earlier\n\ |
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235 versions of colamd.\n\ |
5164 | 236 \n\ |
237 @var{stats} is an optional 20-element output vector that provides data\n\ | |
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238 about the ordering and the validity of the input matrix @var{S}. Ordering\n\ |
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239 statistics are in @code{@var{stats}(1:3)}. @code{@var{stats}(1)} and\n\ |
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240 @code{@var{stats}(2)} are the number of dense or empty rows and columns\n\ |
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241 ignored by @sc{colamd} and @code{@var{stats}(3)} is the number of garbage\n\ |
10840 | 242 collections performed on the internal data structure used by @sc{colamd}\n\ |
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243 (roughly of size @code{2.2 * nnz(@var{S}) + 4 * @var{m} + 7 * @var{n}}\n\ |
5164 | 244 integers).\n\ |
245 \n\ | |
246 Octave built-in functions are intended to generate valid sparse matrices,\n\ | |
247 with no duplicate entries, with ascending row indices of the nonzeros\n\ | |
248 in each column, with a non-negative number of entries in each column (!)\n\ | |
10840 | 249 and so on. If a matrix is invalid, then @sc{colamd} may or may not be able\n\ |
5164 | 250 to continue. If there are duplicate entries (a row index appears two or\n\ |
251 more times in the same column) or if the row indices in a column are out\n\ | |
10840 | 252 of order, then @sc{colamd} can correct these errors by ignoring the duplicate\n\ |
5164 | 253 entries and sorting each column of its internal copy of the matrix\n\ |
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254 @var{S} (the input matrix @var{S} is not repaired, however). If a matrix\n\ |
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255 is invalid in other ways then @sc{colamd} cannot continue, an error message\n\ |
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256 is printed, and no output arguments (@var{p} or @var{stats}) are returned.\n\ |
10840 | 257 @sc{colamd} is thus a simple way to check a sparse matrix to see if it's\n\ |
5164 | 258 valid.\n\ |
259 \n\ | |
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260 @code{@var{stats}(4:7)} provide information if COLAMD was able to\n\ |
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261 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if\n\ |
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262 invalid. @code{@var{stats}(5)} is the rightmost column index that is\n\ |
5164 | 263 unsorted or contains duplicate entries, or zero if no such column exists.\n\ |
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264 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row\n\ |
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265 index in the column index given by @code{@var{stats}(5)}, or zero if no\n\ |
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266 such row index exists. @code{@var{stats}(7)} is the number of duplicate\n\ |
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267 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in\n\ |
10840 | 268 the current version of @sc{colamd} (reserved for future use).\n\ |
5164 | 269 \n\ |
270 The ordering is followed by a column elimination tree post-ordering.\n\ | |
271 \n\ | |
272 The authors of the code itself are Stefan I. Larimore and Timothy A.\n\ | |
10840 | 273 Davis @email{davis@@cise.ufl.edu}, University of Florida. The algorithm was\n\ |
5164 | 274 developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\ |
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275 Ng, Oak Ridge National Laboratory. (see\n\ |
5164 | 276 @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\ |
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277 @seealso{colperm, symamd, ccolamd}\n\ |
5642 | 278 @end deftypefn") |
5164 | 279 { |
280 octave_value_list retval; | |
5451 | 281 |
282 #ifdef HAVE_COLAMD | |
283 | |
5164 | 284 int nargin = args.length (); |
285 int spumoni = 0; | |
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286 |
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287 if (nargout > 2 || nargin < 1 || nargin > 2) |
5823 | 288 print_usage (); |
5164 | 289 else |
290 { | |
291 // Get knobs | |
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292 OCTAVE_LOCAL_BUFFER (double, knobs, COLAMD_KNOBS); |
5440 | 293 COLAMD_NAME (_set_defaults) (knobs); |
5164 | 294 |
295 // Check for user-passed knobs | |
296 if (nargin == 2) | |
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297 { |
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298 NDArray User_knobs = args(1).array_value (); |
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299 int nel_User_knobs = User_knobs.length (); |
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300 |
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301 if (nel_User_knobs > 0) |
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302 knobs [COLAMD_DENSE_ROW] = User_knobs (0); |
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303 if (nel_User_knobs > 1) |
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304 knobs [COLAMD_DENSE_COL] = User_knobs (1) ; |
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305 if (nel_User_knobs > 2) |
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306 spumoni = static_cast<int> (User_knobs (2)); |
5440 | 307 |
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308 // print knob settings if spumoni is set |
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309 if (spumoni) |
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310 { |
5440 | 311 |
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312 octave_stdout << "\ncolamd version " << COLAMD_MAIN_VERSION << "." |
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313 << COLAMD_SUB_VERSION << ", " << COLAMD_DATE << ":\n"; |
5164 | 314 |
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315 if (knobs [COLAMD_DENSE_ROW] >= 0) |
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316 octave_stdout << "knobs(1): " << User_knobs (0) |
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317 << ", rows with > max(16," |
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318 << knobs [COLAMD_DENSE_ROW] << "*sqrt(size(A,2)))" |
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319 << " entries removed\n"; |
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320 else |
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321 octave_stdout << "knobs(1): " << User_knobs (0) |
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322 << ", only completely dense rows removed\n"; |
5440 | 323 |
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324 if (knobs [COLAMD_DENSE_COL] >= 0) |
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325 octave_stdout << "knobs(2): " << User_knobs (1) |
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326 << ", cols with > max(16," |
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327 << knobs [COLAMD_DENSE_COL] << "*sqrt(size(A)))" |
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328 << " entries removed\n"; |
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329 else |
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330 octave_stdout << "knobs(2): " << User_knobs (1) |
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331 << ", only completely dense columns removed\n"; |
5440 | 332 |
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333 octave_stdout << "knobs(3): " << User_knobs (2) |
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334 << ", statistics and knobs printed\n"; |
5440 | 335 |
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336 } |
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337 } |
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338 |
5440 | 339 octave_idx_type n_row, n_col, nnz; |
340 octave_idx_type *ridx, *cidx; | |
5164 | 341 SparseComplexMatrix scm; |
342 SparseMatrix sm; | |
343 | |
5631 | 344 if (args(0).is_sparse_type ()) |
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345 { |
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346 if (args(0).is_complex_type ()) |
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347 { |
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348 scm = args(0). sparse_complex_matrix_value (); |
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349 n_row = scm.rows (); |
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350 n_col = scm.cols (); |
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351 nnz = scm.nnz (); |
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352 ridx = scm.xridx (); |
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353 cidx = scm.xcidx (); |
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354 } |
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355 else |
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356 { |
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357 sm = args(0).sparse_matrix_value (); |
5164 | 358 |
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359 n_row = sm.rows (); |
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360 n_col = sm.cols (); |
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361 nnz = sm.nnz (); |
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362 ridx = sm.xridx (); |
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363 cidx = sm.xcidx (); |
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364 } |
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365 } |
5164 | 366 else |
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367 { |
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368 if (args(0).is_complex_type ()) |
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369 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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370 else |
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371 sm = SparseMatrix (args(0).matrix_value ()); |
5164 | 372 |
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373 n_row = sm.rows (); |
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374 n_col = sm.cols (); |
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375 nnz = sm.nnz (); |
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376 ridx = sm.xridx (); |
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377 cidx = sm.xcidx (); |
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378 } |
5164 | 379 |
380 // Allocate workspace for colamd | |
5440 | 381 OCTAVE_LOCAL_BUFFER (octave_idx_type, p, n_col+1); |
382 for (octave_idx_type i = 0; i < n_col+1; i++) | |
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383 p[i] = cidx [i]; |
5164 | 384 |
5440 | 385 octave_idx_type Alen = COLAMD_NAME (_recommended) (nnz, n_row, n_col); |
386 OCTAVE_LOCAL_BUFFER (octave_idx_type, A, Alen); | |
387 for (octave_idx_type i = 0; i < nnz; i++) | |
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388 A[i] = ridx [i]; |
5164 | 389 |
390 // Order the columns (destroys A) | |
5440 | 391 OCTAVE_LOCAL_BUFFER (octave_idx_type, stats, COLAMD_STATS); |
392 if (! COLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats)) | |
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393 { |
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394 COLAMD_NAME (_report) (stats) ; |
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395 error ("colamd: internal error!"); |
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396 return retval; |
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397 } |
5164 | 398 |
399 // column elimination tree post-ordering (reuse variables) | |
5440 | 400 OCTAVE_LOCAL_BUFFER (octave_idx_type, colbeg, n_col + 1); |
401 OCTAVE_LOCAL_BUFFER (octave_idx_type, colend, n_col + 1); | |
402 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); | |
5164 | 403 |
5440 | 404 for (octave_idx_type i = 0; i < n_col; i++) |
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405 { |
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406 colbeg[i] = cidx[p[i]]; |
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407 colend[i] = cidx[p[i]+1]; |
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408 } |
5164 | 409 |
410 coletree (ridx, colbeg, colend, etree, n_row, n_col); | |
411 | |
412 // Calculate the tree post-ordering | |
7924 | 413 tree_postorder (n_col, etree, colbeg); |
5164 | 414 |
415 // return the permutation vector | |
416 NDArray out_perm (dim_vector (1, n_col)); | |
5440 | 417 for (octave_idx_type i = 0; i < n_col; i++) |
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418 out_perm(i) = p [colbeg [i]] + 1; |
5164 | 419 |
7924 | 420 retval(0) = out_perm; |
5164 | 421 |
422 // print stats if spumoni > 0 | |
423 if (spumoni > 0) | |
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424 COLAMD_NAME (_report) (stats) ; |
5164 | 425 |
426 // Return the stats vector | |
427 if (nargout == 2) | |
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428 { |
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429 NDArray out_stats (dim_vector (1, COLAMD_STATS)); |
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430 for (octave_idx_type i = 0 ; i < COLAMD_STATS ; i++) |
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431 out_stats (i) = stats [i] ; |
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432 retval(1) = out_stats; |
5164 | 433 |
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434 // fix stats (5) and (6), for 1-based information on |
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435 // jumbled matrix. note that this correction doesn't |
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436 // occur if symamd returns FALSE |
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437 out_stats (COLAMD_INFO1) ++ ; |
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438 out_stats (COLAMD_INFO2) ++ ; |
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439 } |
5164 | 440 } |
441 | |
5451 | 442 #else |
443 | |
444 error ("colamd: not available in this version of Octave"); | |
445 | |
446 #endif | |
447 | |
5164 | 448 return retval; |
449 } | |
450 | |
451 DEFUN_DLD (symamd, args, nargout, | |
452 "-*- texinfo -*-\n\ | |
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453 @deftypefn {Loadable Function} {@var{p} =} symamd (@var{S})\n\ |
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454 @deftypefnx {Loadable Function} {@var{p} =} symamd (@var{S}, @var{knobs})\n\ |
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455 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} symamd (@var{S})\n\ |
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456 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} symamd (@var{S}, @var{knobs})\n\ |
5164 | 457 \n\ |
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458 For a symmetric positive definite matrix @var{S}, returns the permutation\n\ |
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459 vector p such that @code{@var{S}(@var{p}, @var{p})} tends to have a\n\ |
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460 sparser Cholesky@tie{}factor than @var{S}. Sometimes @code{symamd} works\n\ |
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461 well for symmetric indefinite matrices too. The matrix @var{S} is assumed\n\ |
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462 to be symmetric; only the strictly lower triangular part is referenced.\n\ |
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463 @var{S} must be square.\n\ |
5164 | 464 \n\ |
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465 @var{knobs} is an optional one- to two-element input vector. If @var{S} is\n\ |
5440 | 466 n-by-n, then rows and columns with more than\n\ |
467 @code{max(16,@var{knobs}(1)*sqrt(n))} entries are removed prior to ordering,\n\ | |
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468 and ordered last in the output permutation @var{p}. No rows/columns are\n\ |
5440 | 469 removed if @code{@var{knobs}(1) < 0}. If @code{@var{knobs} (2)} is nonzero,\n\ |
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470 @code{stats} and @var{knobs} are printed. The default is @code{@var{knobs}\n\ |
5440 | 471 = [10 0]}. Note that @var{knobs} differs from earlier versions of symamd.\n\ |
5164 | 472 \n\ |
473 @var{stats} is an optional 20-element output vector that provides data\n\ | |
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474 about the ordering and the validity of the input matrix @var{S}. Ordering\n\ |
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475 statistics are in @code{@var{stats}(1:3)}. @code{@var{stats}(1) =\n\ |
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476 @var{stats}(2)} is the number of dense or empty rows and columns\n\ |
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477 ignored by SYMAMD and @code{@var{stats}(3)} is the number of garbage\n\ |
5164 | 478 collections performed on the internal data structure used by SYMAMD\n\ |
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479 (roughly of size @code{8.4 * nnz (tril (@var{S}, -1)) + 9 * @var{n}}\n\ |
5164 | 480 integers).\n\ |
481 \n\ | |
482 Octave built-in functions are intended to generate valid sparse matrices,\n\ | |
483 with no duplicate entries, with ascending row indices of the nonzeros\n\ | |
484 in each column, with a non-negative number of entries in each column (!)\n\ | |
485 and so on. If a matrix is invalid, then SYMAMD may or may not be able\n\ | |
486 to continue. If there are duplicate entries (a row index appears two or\n\ | |
487 more times in the same column) or if the row indices in a column are out\n\ | |
488 of order, then SYMAMD can correct these errors by ignoring the duplicate\n\ | |
489 entries and sorting each column of its internal copy of the matrix S (the\n\ | |
490 input matrix S is not repaired, however). If a matrix is invalid in\n\ | |
491 other ways then SYMAMD cannot continue, an error message is printed, and\n\ | |
492 no output arguments (@var{p} or @var{stats}) are returned. SYMAMD is\n\ | |
493 thus a simple way to check a sparse matrix to see if it's valid.\n\ | |
494 \n\ | |
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495 @code{@var{stats}(4:7)} provide information if SYMAMD was able to\n\ |
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496 continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1\n\ |
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497 if invalid. @code{@var{stats}(5)} is the rightmost column index that\n\ |
5164 | 498 is unsorted or contains duplicate entries, or zero if no such column\n\ |
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499 exists. @code{@var{stats}(6)} is the last seen duplicate or out-of-order\n\ |
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500 row index in the column index given by @code{@var{stats}(5)}, or zero\n\ |
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501 if no such row index exists. @code{@var{stats}(7)} is the number of\n\ |
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502 duplicate or out-of-order row indices. @code{@var{stats}(8:20)} is\n\ |
5164 | 503 always zero in the current version of SYMAMD (reserved for future use).\n\ |
504 \n\ | |
505 The ordering is followed by a column elimination tree post-ordering.\n\ | |
506 \n\ | |
507 The authors of the code itself are Stefan I. Larimore and Timothy A.\n\ | |
10840 | 508 Davis @email{davis@@cise.ufl.edu}, University of Florida. The algorithm was\n\ |
5164 | 509 developed in collaboration with John Gilbert, Xerox PARC, and Esmond\n\ |
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510 Ng, Oak Ridge National Laboratory. (see\n\ |
5164 | 511 @url{http://www.cise.ufl.edu/research/sparse/colamd})\n\ |
5642 | 512 @seealso{colperm, colamd}\n\ |
513 @end deftypefn") | |
5164 | 514 { |
515 octave_value_list retval; | |
5451 | 516 |
517 #ifdef HAVE_COLAMD | |
518 | |
5164 | 519 int nargin = args.length (); |
520 int spumoni = 0; | |
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521 |
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522 if (nargout > 2 || nargin < 1 || nargin > 2) |
5823 | 523 print_usage (); |
5164 | 524 else |
525 { | |
526 // Get knobs | |
527 OCTAVE_LOCAL_BUFFER (double, knobs, COLAMD_KNOBS); | |
5440 | 528 COLAMD_NAME (_set_defaults) (knobs); |
5164 | 529 |
530 // Check for user-passed knobs | |
531 if (nargin == 2) | |
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532 { |
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533 NDArray User_knobs = args(1).array_value (); |
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534 int nel_User_knobs = User_knobs.length (); |
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535 |
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536 if (nel_User_knobs > 0) |
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537 knobs [COLAMD_DENSE_ROW] = User_knobs (COLAMD_DENSE_ROW); |
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538 if (nel_User_knobs > 1) |
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539 spumoni = static_cast<int> (User_knobs (1)); |
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540 } |
5164 | 541 |
542 // print knob settings if spumoni is set | |
543 if (spumoni > 0) | |
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544 octave_stdout << "symamd: dense row/col fraction: " |
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545 << knobs [COLAMD_DENSE_ROW] << std::endl; |
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546 |
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547 octave_idx_type n_row, n_col; |
5440 | 548 octave_idx_type *ridx, *cidx; |
5164 | 549 SparseMatrix sm; |
550 SparseComplexMatrix scm; | |
551 | |
5631 | 552 if (args(0).is_sparse_type ()) |
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553 { |
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554 if (args(0).is_complex_type ()) |
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555 { |
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556 scm = args(0).sparse_complex_matrix_value (); |
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557 n_row = scm.rows (); |
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558 n_col = scm.cols (); |
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559 ridx = scm.xridx (); |
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560 cidx = scm.xcidx (); |
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561 } |
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562 else |
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563 { |
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564 sm = args(0).sparse_matrix_value (); |
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565 n_row = sm.rows (); |
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566 n_col = sm.cols (); |
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567 ridx = sm.xridx (); |
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568 cidx = sm.xcidx (); |
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569 } |
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570 } |
5164 | 571 else |
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572 { |
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573 if (args(0).is_complex_type ()) |
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574 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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575 else |
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576 sm = SparseMatrix (args(0).matrix_value ()); |
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577 |
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578 n_row = sm.rows (); |
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579 n_col = sm.cols (); |
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580 ridx = sm.xridx (); |
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581 cidx = sm.xcidx (); |
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582 } |
5164 | 583 |
584 if (n_row != n_col) | |
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585 { |
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586 error ("symamd: matrix S must be square"); |
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587 return retval; |
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588 } |
5164 | 589 |
590 // Allocate workspace for symamd | |
5440 | 591 OCTAVE_LOCAL_BUFFER (octave_idx_type, perm, n_col+1); |
592 OCTAVE_LOCAL_BUFFER (octave_idx_type, stats, COLAMD_STATS); | |
593 if (!SYMAMD_NAME () (n_col, ridx, cidx, perm, knobs, stats, &calloc, &free)) | |
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594 { |
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595 SYMAMD_NAME (_report) (stats) ; |
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596 error ("symamd: internal error!") ; |
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597 return retval; |
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598 } |
5164 | 599 |
600 // column elimination tree post-ordering | |
5440 | 601 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); |
5164 | 602 symetree (ridx, cidx, etree, perm, n_col); |
603 | |
604 // Calculate the tree post-ordering | |
5440 | 605 OCTAVE_LOCAL_BUFFER (octave_idx_type, post, n_col + 1); |
7924 | 606 tree_postorder (n_col, etree, post); |
5164 | 607 |
608 // return the permutation vector | |
609 NDArray out_perm (dim_vector (1, n_col)); | |
5440 | 610 for (octave_idx_type i = 0; i < n_col; i++) |
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611 out_perm(i) = perm [post [i]] + 1; |
5164 | 612 |
7924 | 613 retval(0) = out_perm; |
5164 | 614 |
615 // print stats if spumoni > 0 | |
616 if (spumoni > 0) | |
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617 SYMAMD_NAME (_report) (stats) ; |
5164 | 618 |
619 // Return the stats vector | |
620 if (nargout == 2) | |
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621 { |
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622 NDArray out_stats (dim_vector (1, COLAMD_STATS)); |
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623 for (octave_idx_type i = 0 ; i < COLAMD_STATS ; i++) |
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624 out_stats (i) = stats [i] ; |
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625 retval(1) = out_stats; |
5164 | 626 |
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627 // fix stats (5) and (6), for 1-based information on |
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628 // jumbled matrix. note that this correction doesn't |
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629 // occur if symamd returns FALSE |
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630 out_stats (COLAMD_INFO1) ++ ; |
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631 out_stats (COLAMD_INFO2) ++ ; |
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632 } |
5164 | 633 } |
634 | |
5451 | 635 #else |
636 | |
637 error ("symamd: not available in this version of Octave"); | |
638 | |
639 #endif | |
640 | |
5164 | 641 return retval; |
642 } | |
643 | |
644 DEFUN_DLD (etree, args, nargout, | |
645 "-*- texinfo -*-\n\ | |
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646 @deftypefn {Loadable Function} {@var{p} =} etree (@var{S})\n\ |
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647 @deftypefnx {Loadable Function} {@var{p} =} etree (@var{S}, @var{typ})\n\ |
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648 @deftypefnx {Loadable Function} {[@var{p}, @var{q}] =} etree (@var{S}, @var{typ})\n\ |
5164 | 649 \n\ |
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650 Returns the elimination tree for the matrix @var{S}. By default @var{S}\n\ |
5164 | 651 is assumed to be symmetric and the symmetric elimination tree is\n\ |
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652 returned. The argument @var{typ} controls whether a symmetric or\n\ |
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653 column elimination tree is returned. Valid values of @var{typ} are\n\ |
5164 | 654 'sym' or 'col', for symmetric or column elimination tree respectively\n\ |
655 \n\ | |
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656 Called with a second argument, @code{etree} also returns the postorder\n\ |
5164 | 657 permutations on the tree.\n\ |
658 @end deftypefn") | |
659 { | |
660 octave_value_list retval; | |
5297 | 661 |
5164 | 662 int nargin = args.length (); |
663 | |
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664 if (nargout > 2 || nargin < 1 || nargin > 2) |
5823 | 665 print_usage (); |
5164 | 666 else |
667 { | |
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668 octave_idx_type n_row, n_col; |
5440 | 669 octave_idx_type *ridx, *cidx; |
5164 | 670 bool is_sym = true; |
671 SparseMatrix sm; | |
672 SparseComplexMatrix scm; | |
673 | |
5631 | 674 if (args(0).is_sparse_type ()) |
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675 { |
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676 if (args(0).is_complex_type ()) |
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677 { |
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678 scm = args(0).sparse_complex_matrix_value (); |
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679 n_row = scm.rows (); |
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680 n_col = scm.cols (); |
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681 ridx = scm.xridx (); |
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682 cidx = scm.xcidx (); |
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683 } |
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684 else |
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685 { |
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686 sm = args(0).sparse_matrix_value (); |
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687 n_row = sm.rows (); |
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688 n_col = sm.cols (); |
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689 ridx = sm.xridx (); |
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690 cidx = sm.xcidx (); |
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691 } |
5164 | 692 |
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693 } |
5164 | 694 else |
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695 { |
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696 error ("etree: S must be a sparse matrix"); |
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697 return retval; |
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698 } |
5164 | 699 |
700 if (nargin == 2) | |
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701 { |
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702 if (args(1).is_string ()) |
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703 { |
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704 std::string str = args(1).string_value (); |
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705 if (str.find ("C") == 0 || str.find ("c") == 0) |
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706 is_sym = false; |
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707 } |
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708 else |
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709 { |
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710 error ("etree: TYP must be a string"); |
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711 return retval; |
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712 } |
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713 } |
7924 | 714 |
5164 | 715 // column elimination tree post-ordering (reuse variables) |
5440 | 716 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); |
5164 | 717 |
718 if (is_sym) | |
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719 { |
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720 if (n_row != n_col) |
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721 { |
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722 error ("etree: S is marked as symmetric, but is not square"); |
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723 return retval; |
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724 } |
7924 | 725 |
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726 symetree (ridx, cidx, etree, 0, n_col); |
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727 } |
5164 | 728 else |
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729 { |
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730 OCTAVE_LOCAL_BUFFER (octave_idx_type, colbeg, n_col); |
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731 OCTAVE_LOCAL_BUFFER (octave_idx_type, colend, n_col); |
5164 | 732 |
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733 for (octave_idx_type i = 0; i < n_col; i++) |
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734 { |
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735 colbeg[i] = cidx[i]; |
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736 colend[i] = cidx[i+1]; |
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737 } |
5164 | 738 |
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739 coletree (ridx, colbeg, colend, etree, n_row, n_col); |
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740 } |
5164 | 741 |
742 NDArray tree (dim_vector (1, n_col)); | |
5440 | 743 for (octave_idx_type i = 0; i < n_col; i++) |
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744 // We flag a root with n_col while Matlab does it with zero |
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745 // Convert for matlab compatiable output |
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746 if (etree[i] == n_col) |
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747 tree(i) = 0; |
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748 else |
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749 tree(i) = etree[i] + 1; |
5164 | 750 |
7924 | 751 retval(0) = tree; |
5164 | 752 |
753 if (nargout == 2) | |
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754 { |
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755 // Calculate the tree post-ordering |
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756 OCTAVE_LOCAL_BUFFER (octave_idx_type, post, n_col + 1); |
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757 tree_postorder (n_col, etree, post); |
5164 | 758 |
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759 NDArray postorder (dim_vector (1, n_col)); |
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760 for (octave_idx_type i = 0; i < n_col; i++) |
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761 postorder(i) = post[i] + 1; |
5164 | 762 |
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763 retval(1) = postorder; |
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764 } |
5164 | 765 } |
766 | |
767 return retval; | |
768 } |