Mercurial > octave
annotate libinterp/dldfcn/colamd.cc @ 23450:855122b993da
maint: Wrap tertiary operator in parentheses "(COND ? x : y)".
* Canvas.cc, color-picker.cc, dialog.cc, marker.cc, main-window.cc, Cell.cc,
__magick_read__.cc, __pchip_deriv__.cc, __qp__.cc, bsxfun.cc, call-stack.cc,
cellfun.cc, data.cc, defaults.cc, det.cc, eig.cc, error.cc, file-io.cc,
filter.cc, find.cc, gammainc.cc, gcd.cc, gl-render.cc, graphics.cc,
graphics.in.h, help.cc, hex2num.cc, inv.cc, load-save.cc, lookup.cc,
ls-mat4.cc, ls-mat5.cc, ls-oct-binary.cc, ls-oct-text.cc, lu.cc, max.cc,
mex.cc, oct-hist.cc, oct-map.cc, oct-procbuf.cc, oct-stream.cc, pr-output.cc,
rand.cc, regexp.cc, schur.cc, str2double.cc, strfns.cc, symtab.cc, sysdep.cc,
tril.cc, variables.cc, xdiv.cc, audiodevinfo.cc, audioread.cc, colamd.cc,
gzip.cc, ov-base-diag.cc, ov-base-mat.h, ov-base-scalar.h, ov-class.cc,
ov-classdef.cc, ov-fcn-handle.cc, ov-range.cc, ov-range.h, ov-struct.cc,
ov-usr-fcn.cc, ov.cc, octave.cc, op-class.cc, pt-eval.cc, pt-funcall.cc,
pt-idx.cc, pt-jit.cc, pt-stmt.cc, version.cc, Array-util.cc, Array.cc,
CDiagMatrix.cc, CMatrix.cc, CNDArray.cc, CSparse.cc, Range.cc, Sparse.cc,
chNDArray.cc, dDiagMatrix.cc, dMatrix.cc, dNDArray.cc, dSparse.cc,
dim-vector.cc, fCDiagMatrix.cc, fCMatrix.cc, fCNDArray.cc, fDiagMatrix.cc,
fMatrix.cc, fNDArray.cc, idx-vector.cc, idx-vector.h, Faddeeva.cc, DASPK.cc,
DASRT.cc, DASSL.cc, EIG.cc, fEIG.cc, gsvd.cc, lo-specfun.cc, oct-rand.cc,
qr.cc, qrp.cc, randgamma.cc, schur.cc, svd.cc, Sparse-diag-op-defs.h,
mx-inlines.cc, oct-env.cc, cmd-edit.cc, kpse.cc, oct-inttypes.h, oct-sort.cc:
Wrap tertiary operator in parentheses "(COND ? x : y)".
author | Rik <rik@octave.org> |
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date | Thu, 27 Apr 2017 17:33:10 -0700 |
parents | 209e749363a2 |
children | 21baad6b35c4 |
rev | line source |
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5164 | 1 /* |
2 | |
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3 Copyright (C) 2004-2017 David Bateman |
11523 | 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 | |
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9 under the terms of the GNU General Public License as published by |
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10 the Free Software Foundation; either version 3 of the License, or |
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11 (at your option) any later version. |
5164 | 12 |
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13 Octave is distributed in the hope that it will be useful, but |
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14 WITHOUT ANY WARRANTY; without even the implied warranty of |
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15 MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the |
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16 GNU General Public License for more details. |
5164 | 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 | |
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27 #if defined (HAVE_CONFIG_H) |
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28 # include "config.h" |
5164 | 29 #endif |
30 | |
31 #include <cstdlib> | |
32 | |
33 #include <string> | |
34 | |
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35 #include "CSparse.h" |
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36 #include "dNDArray.h" |
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37 #include "dSparse.h" |
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38 #include "oct-locbuf.h" |
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39 #include "oct-sparse.h" |
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40 |
5164 | 41 #include "defun-dld.h" |
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42 #include "error.h" |
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43 #include "errwarn.h" |
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44 #include "ovl.h" |
5164 | 45 #include "pager.h" |
46 | |
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47 // The symmetric column elimination tree code take from the Davis LDL code. |
5164 | 48 // Copyright given elsewhere in this file. |
7924 | 49 static void |
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50 symetree (const octave_idx_type *ridx, const octave_idx_type *cidx, |
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51 octave_idx_type *Parent, octave_idx_type *P, octave_idx_type n) |
5164 | 52 { |
5440 | 53 OCTAVE_LOCAL_BUFFER (octave_idx_type, Flag, n); |
54 OCTAVE_LOCAL_BUFFER (octave_idx_type, Pinv, (P ? n : 0)); | |
5164 | 55 if (P) |
56 // If P is present then compute Pinv, the inverse of P | |
5440 | 57 for (octave_idx_type k = 0 ; k < n ; k++) |
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58 Pinv[P[k]] = k; |
5164 | 59 |
5440 | 60 for (octave_idx_type k = 0 ; k < n ; k++) |
5164 | 61 { |
62 // L(k,:) pattern: all nodes reachable in etree from nz in A(0:k-1,k) | |
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63 Parent[k] = n ; // parent of k is not yet known |
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64 Flag[k] = k ; // mark node k as visited |
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65 octave_idx_type kk = (P ? P[k] // kth original, or permuted, column |
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66 : (k)); |
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67 octave_idx_type p2 = cidx[kk+1]; |
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68 for (octave_idx_type p = cidx[kk] ; p < p2 ; p++) |
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69 { |
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70 // A (i,k) is nonzero (original or permuted A) |
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71 octave_idx_type i = (Pinv) ? (Pinv[ridx[p]]) : (ridx[p]); |
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72 if (i < k) |
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73 { |
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74 // follow path from i to root of etree, stop at flagged node |
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75 for ( ; Flag[i] != k ; i = Parent[i]) |
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76 { |
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77 // find parent of i if not yet determined |
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78 if (Parent[i] == n) |
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79 Parent[i] = k; |
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80 Flag[i] = k ; // mark i as visited |
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81 } |
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82 } |
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83 } |
5164 | 84 } |
85 } | |
86 | |
87 // The elimination tree post-ordering code below is taken from SuperLU | |
7924 | 88 static inline octave_idx_type |
89 make_set (octave_idx_type i, octave_idx_type *pp) | |
5164 | 90 { |
91 pp[i] = i; | |
92 return i; | |
93 } | |
94 | |
7924 | 95 static inline octave_idx_type |
96 link (octave_idx_type s, octave_idx_type t, octave_idx_type *pp) | |
5164 | 97 { |
98 pp[s] = t; | |
99 return t; | |
100 } | |
101 | |
7924 | 102 static inline octave_idx_type |
103 find (octave_idx_type i, octave_idx_type *pp) | |
5164 | 104 { |
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105 octave_idx_type p = pp[i]; |
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106 octave_idx_type gp = pp[p]; |
7924 | 107 |
108 while (gp != p) | |
109 { | |
110 pp[i] = gp; | |
111 i = gp; | |
112 p = pp[i]; | |
113 gp = pp[p]; | |
114 } | |
115 | |
116 return p; | |
5164 | 117 } |
118 | |
7924 | 119 static octave_idx_type |
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120 etdfs (octave_idx_type v, octave_idx_type *first_kid, |
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121 octave_idx_type *next_kid, octave_idx_type *post, |
7924 | 122 octave_idx_type postnum) |
5164 | 123 { |
7924 | 124 for (octave_idx_type w = first_kid[v]; w != -1; w = next_kid[w]) |
5164 | 125 postnum = etdfs (w, first_kid, next_kid, post, postnum); |
7924 | 126 |
5164 | 127 post[postnum++] = v; |
128 | |
129 return postnum; | |
130 } | |
131 | |
7924 | 132 static void |
133 tree_postorder (octave_idx_type n, octave_idx_type *parent, | |
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134 octave_idx_type *post) |
5164 | 135 { |
136 // Allocate storage for working arrays and results | |
5440 | 137 OCTAVE_LOCAL_BUFFER (octave_idx_type, first_kid, n+1); |
138 OCTAVE_LOCAL_BUFFER (octave_idx_type, next_kid, n+1); | |
5164 | 139 |
140 // Set up structure describing children | |
7924 | 141 for (octave_idx_type v = 0; v <= n; first_kid[v++] = -1) |
20946 | 142 ; // do nothing |
7924 | 143 |
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144 for (octave_idx_type v = n-1; v >= 0; v--) |
5164 | 145 { |
5440 | 146 octave_idx_type dad = parent[v]; |
5164 | 147 next_kid[v] = first_kid[dad]; |
148 first_kid[dad] = v; | |
149 } | |
150 | |
151 // Depth-first search from dummy root vertex #n | |
152 etdfs (n, first_kid, next_kid, post, 0); | |
153 } | |
154 | |
7924 | 155 static void |
156 coletree (const octave_idx_type *ridx, const octave_idx_type *colbeg, | |
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157 octave_idx_type *colend, octave_idx_type *parent, |
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158 octave_idx_type nr, octave_idx_type nc) |
5164 | 159 { |
5440 | 160 OCTAVE_LOCAL_BUFFER (octave_idx_type, root, nc); |
161 OCTAVE_LOCAL_BUFFER (octave_idx_type, pp, nc); | |
162 OCTAVE_LOCAL_BUFFER (octave_idx_type, firstcol, nr); | |
5164 | 163 |
164 // Compute firstcol[row] = first nonzero column in row | |
7924 | 165 for (octave_idx_type row = 0; row < nr; firstcol[row++] = nc) |
20946 | 166 ; // do nothing |
7924 | 167 |
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168 for (octave_idx_type col = 0; col < nc; col++) |
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169 for (octave_idx_type p = colbeg[col]; p < colend[col]; p++) |
5164 | 170 { |
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171 octave_idx_type row = ridx[p]; |
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172 if (firstcol[row] > col) |
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173 firstcol[row] = col; |
5164 | 174 } |
175 | |
176 // Compute etree by Liu's algorithm for symmetric matrices, | |
177 // except use (firstcol[r],c) in place of an edge (r,c) of A. | |
178 // Thus each row clique in A'*A is replaced by a star | |
179 // centered at its first vertex, which has the same fill. | |
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180 for (octave_idx_type col = 0; col < nc; col++) |
5164 | 181 { |
5440 | 182 octave_idx_type cset = make_set (col, pp); |
5164 | 183 root[cset] = col; |
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184 parent[col] = nc; |
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185 for (octave_idx_type p = colbeg[col]; p < colend[col]; p++) |
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186 { |
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187 octave_idx_type row = firstcol[ridx[p]]; |
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188 if (row >= col) |
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189 continue; |
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190 octave_idx_type rset = find (row, pp); |
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191 octave_idx_type rroot = root[rset]; |
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192 if (rroot != col) |
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193 { |
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194 parent[rroot] = col; |
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195 cset = link (cset, rset, pp); |
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196 root[cset] = col; |
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197 } |
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198 } |
5164 | 199 } |
200 } | |
201 | |
202 DEFUN_DLD (colamd, args, nargout, | |
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203 doc: /* -*- texinfo -*- |
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204 @deftypefn {} {@var{p} =} colamd (@var{S}) |
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205 @deftypefnx {} {@var{p} =} colamd (@var{S}, @var{knobs}) |
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206 @deftypefnx {} {[@var{p}, @var{stats}] =} colamd (@var{S}) |
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207 @deftypefnx {} {[@var{p}, @var{stats}] =} colamd (@var{S}, @var{knobs}) |
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208 |
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209 Compute the column approximate minimum degree permutation. |
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210 |
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211 @code{@var{p} = colamd (@var{S})} returns the column approximate minimum |
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212 degree permutation vector for the sparse matrix @var{S}. For a |
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213 non-symmetric matrix @var{S}, @code{@var{S}(:,@var{p})} tends to have |
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214 sparser LU@tie{}factors than @var{S}. The Cholesky@tie{}factorization of |
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215 @code{@var{S}(:,@var{p})' * @var{S}(:,@var{p})} also tends to be sparser |
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216 than that of @code{@var{S}' * @var{S}}. |
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217 |
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218 @var{knobs} is an optional one- to three-element input vector. If @var{S} |
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219 is m-by-n, then rows with more than @code{max(16,@var{knobs}(1)*sqrt(n))} |
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220 entries are ignored. Columns with more than |
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221 @code{max (16,@var{knobs}(2)*sqrt(min(m,n)))} entries are removed prior to |
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222 ordering, and ordered last in the output permutation @var{p}. Only |
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223 completely dense rows or columns are removed if @code{@var{knobs}(1)} and |
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224 @code{@var{knobs}(2)} are < 0, respectively. If @code{@var{knobs}(3)} is |
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225 nonzero, @var{stats} and @var{knobs} are printed. The default is |
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226 @code{@var{knobs} = [10 10 0]}. Note that @var{knobs} differs from earlier |
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227 versions of colamd. |
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228 |
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229 @var{stats} is an optional 20-element output vector that provides data |
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230 about the ordering and the validity of the input matrix @var{S}. Ordering |
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231 statistics are in @code{@var{stats}(1:3)}. @code{@var{stats}(1)} and |
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232 @code{@var{stats}(2)} are the number of dense or empty rows and columns |
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233 ignored by @sc{colamd} and @code{@var{stats}(3)} is the number of garbage |
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234 collections performed on the internal data structure used by @sc{colamd} |
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235 (roughly of size @code{2.2 * nnz(@var{S}) + 4 * @var{m} + 7 * @var{n}} |
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236 integers). |
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237 |
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238 Octave built-in functions are intended to generate valid sparse matrices, |
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239 with no duplicate entries, with ascending row indices of the nonzeros |
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240 in each column, with a non-negative number of entries in each column (!) |
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241 and so on. If a matrix is invalid, then @sc{colamd} may or may not be able |
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242 to continue. If there are duplicate entries (a row index appears two or |
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243 more times in the same column) or if the row indices in a column are out |
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244 of order, then @sc{colamd} can correct these errors by ignoring the |
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245 duplicate entries and sorting each column of its internal copy of the |
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246 matrix @var{S} (the input matrix @var{S} is not repaired, however). If a |
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247 matrix is invalid in other ways then @sc{colamd} cannot continue, an error |
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248 message is printed, and no output arguments (@var{p} or @var{stats}) are |
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249 returned. |
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250 @sc{colamd} is thus a simple way to check a sparse matrix to see if it's |
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251 valid. |
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252 |
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253 @code{@var{stats}(4:7)} provide information if @sc{colamd} was able to |
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254 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if |
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255 invalid. @code{@var{stats}(5)} is the rightmost column index that is |
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256 unsorted or contains duplicate entries, or zero if no such column exists. |
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257 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row |
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258 index in the column index given by @code{@var{stats}(5)}, or zero if no |
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259 such row index exists. @code{@var{stats}(7)} is the number of duplicate |
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260 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in |
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261 the current version of @sc{colamd} (reserved for future use). |
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262 |
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263 The ordering is followed by a column elimination tree post-ordering. |
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264 |
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265 The authors of the code itself are @nospell{Stefan I. Larimore} and |
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266 @nospell{Timothy A. Davis @email{davis@@cise.ufl.edu}}, University of Florida. The algorithm was developed in collaboration with @nospell{John Gilbert}, |
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267 Xerox PARC, and @nospell{Esmond Ng}, Oak Ridge National Laboratory. (see |
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268 @url{http://www.cise.ufl.edu/research/sparse/colamd}) |
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269 @seealso{colperm, symamd, ccolamd} |
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270 @end deftypefn */) |
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272 #if defined (HAVE_COLAMD) |
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273 |
5164 | 274 int nargin = args.length (); |
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275 |
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276 if (nargin < 1 || nargin > 2) |
5823 | 277 print_usage (); |
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278 |
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279 octave_value_list retval (nargout == 2 ? 2 : 1); |
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280 int spumoni = 0; |
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281 |
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282 // Get knobs |
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283 OCTAVE_LOCAL_BUFFER (double, knobs, COLAMD_KNOBS); |
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284 COLAMD_NAME (_set_defaults) (knobs); |
5164 | 285 |
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286 // Check for user-passed knobs |
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287 if (nargin == 2) |
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288 { |
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289 NDArray User_knobs = args(1).array_value (); |
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290 int nel_User_knobs = User_knobs.numel (); |
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291 |
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292 if (nel_User_knobs > 0) |
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293 knobs[COLAMD_DENSE_ROW] = User_knobs(0); |
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294 if (nel_User_knobs > 1) |
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295 knobs[COLAMD_DENSE_COL] = User_knobs(1); |
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296 if (nel_User_knobs > 2) |
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297 spumoni = static_cast<int> (User_knobs(2)); |
5440 | 298 |
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299 // print knob settings if spumoni is set |
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300 if (spumoni) |
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301 { |
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303 octave_stdout << "\ncolamd version " << COLAMD_MAIN_VERSION |
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304 << "." << COLAMD_SUB_VERSION |
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305 << ", " << COLAMD_DATE << ":\n"; |
5440 | 306 |
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307 if (knobs[COLAMD_DENSE_ROW] >= 0) |
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308 octave_stdout << "knobs(1): " << User_knobs (0) |
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309 << ", rows with > max (16," |
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310 << knobs[COLAMD_DENSE_ROW] << "*sqrt (size(A,2)))" |
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311 << " entries removed\n"; |
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312 else |
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313 octave_stdout << "knobs(1): " << User_knobs (0) |
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314 << ", only completely dense rows removed\n"; |
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316 if (knobs[COLAMD_DENSE_COL] >= 0) |
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317 octave_stdout << "knobs(2): " << User_knobs (1) |
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318 << ", cols with > max (16," |
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319 << knobs[COLAMD_DENSE_COL] << "*sqrt (size(A)))" |
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320 << " entries removed\n"; |
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321 else |
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322 octave_stdout << "knobs(2): " << User_knobs (1) |
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323 << ", only completely dense columns removed\n"; |
5164 | 324 |
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325 octave_stdout << "knobs(3): " << User_knobs (2) |
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326 << ", statistics and knobs printed\n"; |
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327 |
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328 } |
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329 } |
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330 |
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331 octave_idx_type n_row, n_col, nnz; |
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332 octave_idx_type *ridx, *cidx; |
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333 SparseComplexMatrix scm; |
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334 SparseMatrix sm; |
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335 |
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336 if (args(0).is_sparse_type ()) |
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337 { |
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338 if (args(0).is_complex_type ()) |
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339 { |
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340 scm = args(0).sparse_complex_matrix_value (); |
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341 n_row = scm.rows (); |
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342 n_col = scm.cols (); |
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343 nnz = scm.nnz (); |
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344 ridx = scm.xridx (); |
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345 cidx = scm.xcidx (); |
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346 } |
5164 | 347 else |
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348 { |
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349 sm = args(0).sparse_matrix_value (); |
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351 n_row = sm.rows (); |
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352 n_col = sm.cols (); |
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353 nnz = sm.nnz (); |
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354 ridx = sm.xridx (); |
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355 cidx = sm.xcidx (); |
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356 } |
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357 } |
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358 else |
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359 { |
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360 if (args(0).is_complex_type ()) |
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361 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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362 else |
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363 sm = SparseMatrix (args(0).matrix_value ()); |
5164 | 364 |
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365 n_row = sm.rows (); |
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366 n_col = sm.cols (); |
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367 nnz = sm.nnz (); |
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368 ridx = sm.xridx (); |
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369 cidx = sm.xcidx (); |
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370 } |
5164 | 371 |
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372 // Allocate workspace for colamd |
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373 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, p, n_col+1); |
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374 for (octave_idx_type i = 0; i < n_col+1; i++) |
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375 p[i] = cidx[i]; |
5164 | 376 |
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377 octave_idx_type Alen = COLAMD_NAME (_recommended) (nnz, n_row, n_col); |
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378 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, A, Alen); |
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379 for (octave_idx_type i = 0; i < nnz; i++) |
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380 A[i] = ridx[i]; |
5164 | 381 |
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382 // Order the columns (destroys A) |
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383 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, stats, COLAMD_STATS); |
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384 if (! COLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats)) |
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385 { |
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386 COLAMD_NAME (_report)(stats); |
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387 |
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388 error ("colamd: internal error!"); |
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389 } |
5164 | 390 |
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391 // column elimination tree post-ordering (reuse variables) |
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392 OCTAVE_LOCAL_BUFFER (octave_idx_type, colbeg, n_col + 1); |
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393 OCTAVE_LOCAL_BUFFER (octave_idx_type, colend, n_col + 1); |
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394 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); |
5164 | 395 |
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396 for (octave_idx_type i = 0; i < n_col; i++) |
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397 { |
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398 colbeg[i] = cidx[p[i]]; |
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399 colend[i] = cidx[p[i]+1]; |
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400 } |
5164 | 401 |
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402 coletree (ridx, colbeg, colend, etree, n_row, n_col); |
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403 |
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404 // Calculate the tree post-ordering |
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405 tree_postorder (n_col, etree, colbeg); |
5164 | 406 |
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407 // return the permutation vector |
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408 NDArray out_perm (dim_vector (1, n_col)); |
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409 for (octave_idx_type i = 0; i < n_col; i++) |
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410 out_perm(i) = p[colbeg[i]] + 1; |
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411 |
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412 retval(0) = out_perm; |
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413 |
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414 // print stats if spumoni > 0 |
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415 if (spumoni > 0) |
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416 COLAMD_NAME (_report)(stats); |
5164 | 417 |
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418 // Return the stats vector |
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419 if (nargout == 2) |
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420 { |
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421 NDArray out_stats (dim_vector (1, COLAMD_STATS)); |
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422 for (octave_idx_type i = 0 ; i < COLAMD_STATS ; i++) |
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423 out_stats(i) = stats[i]; |
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424 retval(1) = out_stats; |
5164 | 425 |
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426 // fix stats (5) and (6), for 1-based information on |
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427 // jumbled matrix. note that this correction doesn't |
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428 // occur if symamd returns FALSE |
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429 out_stats(COLAMD_INFO1)++; |
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430 out_stats(COLAMD_INFO2)++; |
5164 | 431 } |
432 | |
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433 return retval; |
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434 |
5451 | 435 #else |
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436 |
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437 octave_unused_parameter (args); |
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438 octave_unused_parameter (nargout); |
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439 |
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440 err_disabled_feature ("colamd", "COLAMD"); |
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441 |
5451 | 442 #endif |
5164 | 443 } |
444 | |
445 DEFUN_DLD (symamd, args, nargout, | |
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446 doc: /* -*- texinfo -*- |
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447 @deftypefn {} {@var{p} =} symamd (@var{S}) |
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448 @deftypefnx {} {@var{p} =} symamd (@var{S}, @var{knobs}) |
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449 @deftypefnx {} {[@var{p}, @var{stats}] =} symamd (@var{S}) |
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450 @deftypefnx {} {[@var{p}, @var{stats}] =} symamd (@var{S}, @var{knobs}) |
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451 |
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452 For a symmetric positive definite matrix @var{S}, returns the permutation |
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453 vector p such that @code{@var{S}(@var{p}, @var{p})} tends to have a |
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454 sparser Cholesky@tie{}factor than @var{S}. |
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455 |
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456 Sometimes @code{symamd} works well for symmetric indefinite matrices too. |
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457 The matrix @var{S} is assumed to be symmetric; only the strictly lower |
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458 triangular part is referenced. @var{S} must be square. |
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459 |
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460 @var{knobs} is an optional one- to two-element input vector. If @var{S} is |
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461 n-by-n, then rows and columns with more than |
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462 @code{max (16,@var{knobs}(1)*sqrt(n))} entries are removed prior to |
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463 ordering, and ordered last in the output permutation @var{p}. No |
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464 rows/columns are removed if @code{@var{knobs}(1) < 0}. If |
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465 @code{@var{knobs} (2)} is nonzero, @code{stats} and @var{knobs} are |
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466 printed. The default is @code{@var{knobs} = [10 0]}. Note that |
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467 @var{knobs} differs from earlier versions of @code{symamd}. |
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468 |
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469 @var{stats} is an optional 20-element output vector that provides data |
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470 about the ordering and the validity of the input matrix @var{S}. Ordering |
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471 statistics are in @code{@var{stats}(1:3)}. |
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472 @code{@var{stats}(1) = @var{stats}(2)} is the number of dense or empty rows |
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473 and columns ignored by SYMAMD and @code{@var{stats}(3)} is the number of |
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474 garbage collections performed on the internal data structure used by SYMAMD |
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475 (roughly of size @code{8.4 * nnz (tril (@var{S}, -1)) + 9 * @var{n}} |
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476 integers). |
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477 |
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478 Octave built-in functions are intended to generate valid sparse matrices, |
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479 with no duplicate entries, with ascending row indices of the nonzeros |
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480 in each column, with a non-negative number of entries in each column (!) |
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481 and so on. If a matrix is invalid, then SYMAMD may or may not be able |
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482 to continue. If there are duplicate entries (a row index appears two or |
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483 more times in the same column) or if the row indices in a column are out |
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484 of order, then SYMAMD can correct these errors by ignoring the duplicate |
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485 entries and sorting each column of its internal copy of the matrix S (the |
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486 input matrix S is not repaired, however). If a matrix is invalid in |
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487 other ways then SYMAMD cannot continue, an error message is printed, and |
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488 no output arguments (@var{p} or @var{stats}) are returned. SYMAMD is |
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489 thus a simple way to check a sparse matrix to see if it's valid. |
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490 |
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491 @code{@var{stats}(4:7)} provide information if SYMAMD was able to |
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492 continue. The matrix is OK if @code{@var{stats} (4)} is zero, or 1 |
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493 if invalid. @code{@var{stats}(5)} is the rightmost column index that |
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494 is unsorted or contains duplicate entries, or zero if no such column |
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495 exists. @code{@var{stats}(6)} is the last seen duplicate or out-of-order |
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496 row index in the column index given by @code{@var{stats}(5)}, or zero |
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497 if no such row index exists. @code{@var{stats}(7)} is the number of |
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498 duplicate or out-of-order row indices. @code{@var{stats}(8:20)} is |
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499 always zero in the current version of SYMAMD (reserved for future use). |
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500 |
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501 The ordering is followed by a column elimination tree post-ordering. |
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502 |
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503 The authors of the code itself are @nospell{Stefan I. Larimore} and |
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504 @nospell{Timothy A. Davis @email{davis@@cise.ufl.edu}}, University of Florida. The algorithm was developed in collaboration with @nospell{John Gilbert}, |
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505 Xerox PARC, and @nospell{Esmond Ng}, Oak Ridge National Laboratory. (see |
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506 @url{http://www.cise.ufl.edu/research/sparse/colamd}) |
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507 @seealso{colperm, colamd} |
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508 @end deftypefn */) |
5164 | 509 { |
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510 #if defined (HAVE_COLAMD) |
5451 | 511 |
5164 | 512 int nargin = args.length (); |
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513 |
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514 if (nargin < 1 || nargin > 2) |
5823 | 515 print_usage (); |
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516 |
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517 octave_value_list retval (nargin == 2 ? 2 : 1); |
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518 int spumoni = 0; |
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519 |
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520 // Get knobs |
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521 OCTAVE_LOCAL_BUFFER (double, knobs, COLAMD_KNOBS); |
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522 COLAMD_NAME (_set_defaults) (knobs); |
5164 | 523 |
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524 // Check for user-passed knobs |
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525 if (nargin == 2) |
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526 { |
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527 NDArray User_knobs = args(1).array_value (); |
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528 int nel_User_knobs = User_knobs.numel (); |
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529 |
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530 if (nel_User_knobs > 0) |
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531 knobs[COLAMD_DENSE_ROW] = User_knobs(COLAMD_DENSE_ROW); |
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532 if (nel_User_knobs > 1) |
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533 spumoni = static_cast<int> (User_knobs (1)); |
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534 } |
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535 |
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536 // print knob settings if spumoni is set |
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537 if (spumoni > 0) |
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538 octave_stdout << "symamd: dense row/col fraction: " |
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539 << knobs[COLAMD_DENSE_ROW] << std::endl; |
5164 | 540 |
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541 octave_idx_type n_row, n_col; |
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542 octave_idx_type *ridx, *cidx; |
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543 SparseMatrix sm; |
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544 SparseComplexMatrix scm; |
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545 |
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546 if (args(0).is_sparse_type ()) |
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547 { |
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548 if (args(0).is_complex_type ()) |
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549 { |
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550 scm = args(0).sparse_complex_matrix_value (); |
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551 n_row = scm.rows (); |
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552 n_col = scm.cols (); |
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553 ridx = scm.xridx (); |
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554 cidx = scm.xcidx (); |
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555 } |
5164 | 556 else |
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557 { |
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558 sm = args(0).sparse_matrix_value (); |
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559 n_row = sm.rows (); |
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560 n_col = sm.cols (); |
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561 ridx = sm.xridx (); |
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562 cidx = sm.xcidx (); |
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563 } |
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564 } |
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565 else |
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566 { |
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567 if (args(0).is_complex_type ()) |
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568 sm = SparseMatrix (real (args(0).complex_matrix_value ())); |
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569 else |
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570 sm = SparseMatrix (args(0).matrix_value ()); |
5164 | 571 |
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572 n_row = sm.rows (); |
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573 n_col = sm.cols (); |
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574 ridx = sm.xridx (); |
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575 cidx = sm.xcidx (); |
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576 } |
5164 | 577 |
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578 if (n_row != n_col) |
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579 err_square_matrix_required ("symamd", "S"); |
5164 | 580 |
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581 // Allocate workspace for symamd |
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582 OCTAVE_LOCAL_BUFFER (octave_idx_type, perm, n_col+1); |
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583 OCTAVE_LOCAL_BUFFER (octave::suitesparse_integer, stats, COLAMD_STATS); |
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584 if (! SYMAMD_NAME () (n_col, octave::to_suitesparse_intptr (ridx), |
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585 octave::to_suitesparse_intptr (cidx), |
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586 octave::to_suitesparse_intptr (perm), |
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587 knobs, stats, &calloc, &free)) |
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588 { |
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589 SYMAMD_NAME (_report)(stats); |
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590 |
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591 error ("symamd: internal error!"); |
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592 } |
5164 | 593 |
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594 // column elimination tree post-ordering |
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595 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); |
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596 symetree (ridx, cidx, etree, perm, n_col); |
5164 | 597 |
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598 // Calculate the tree post-ordering |
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599 OCTAVE_LOCAL_BUFFER (octave_idx_type, post, n_col + 1); |
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600 tree_postorder (n_col, etree, post); |
5164 | 601 |
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602 // return the permutation vector |
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603 NDArray out_perm (dim_vector (1, n_col)); |
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604 for (octave_idx_type i = 0; i < n_col; i++) |
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605 out_perm(i) = perm[post[i]] + 1; |
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606 |
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607 retval(0) = out_perm; |
5164 | 608 |
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609 // print stats if spumoni > 0 |
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610 if (spumoni > 0) |
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611 SYMAMD_NAME (_report)(stats); |
5164 | 612 |
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613 // Return the stats vector |
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614 if (nargout == 2) |
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615 { |
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616 NDArray out_stats (dim_vector (1, COLAMD_STATS)); |
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617 for (octave_idx_type i = 0 ; i < COLAMD_STATS ; i++) |
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618 out_stats(i) = stats[i]; |
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619 retval(1) = out_stats; |
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620 |
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621 // fix stats (5) and (6), for 1-based information on |
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622 // jumbled matrix. note that this correction doesn't |
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623 // occur if symamd returns FALSE |
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624 out_stats(COLAMD_INFO1)++; |
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625 out_stats(COLAMD_INFO2)++; |
5164 | 626 } |
627 | |
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628 return retval; |
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629 |
5451 | 630 #else |
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631 |
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632 octave_unused_parameter (args); |
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633 octave_unused_parameter (nargout); |
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634 |
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635 err_disabled_feature ("symamd", "COLAMD"); |
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636 |
5451 | 637 #endif |
5164 | 638 } |
639 | |
640 DEFUN_DLD (etree, args, nargout, | |
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641 doc: /* -*- texinfo -*- |
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642 @deftypefn {} {@var{p} =} etree (@var{S}) |
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643 @deftypefnx {} {@var{p} =} etree (@var{S}, @var{typ}) |
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644 @deftypefnx {} {[@var{p}, @var{q}] =} etree (@var{S}, @var{typ}) |
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645 |
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646 Return the elimination tree for the matrix @var{S}. |
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647 |
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648 By default @var{S} is assumed to be symmetric and the symmetric elimination |
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649 tree is returned. The argument @var{typ} controls whether a symmetric or |
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650 column elimination tree is returned. Valid values of @var{typ} are |
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651 @qcode{"sym"} or @qcode{"col"}, for symmetric or column elimination tree |
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652 respectively. |
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653 |
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654 Called with a second argument, @code{etree} also returns the postorder |
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655 permutations on the tree. |
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656 @end deftypefn */) |
5164 | 657 { |
658 int nargin = args.length (); | |
659 | |
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660 if (nargin < 1 || nargin > 2) |
5823 | 661 print_usage (); |
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662 |
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663 octave_value_list retval (nargout == 2 ? 2 : 1); |
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664 |
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665 octave_idx_type n_row = 0; |
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666 octave_idx_type n_col = 0; |
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667 octave_idx_type *ridx = 0; |
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668 octave_idx_type *cidx = 0; |
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669 |
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670 if (args(0).is_sparse_type ()) |
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671 error ("etree: S must be a sparse matrix"); |
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672 |
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673 if (args(0).is_complex_type ()) |
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674 { |
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675 SparseComplexMatrix scm = args(0).sparse_complex_matrix_value (); |
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676 |
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677 n_row = scm.rows (); |
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678 n_col = scm.cols (); |
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679 ridx = scm.xridx (); |
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680 cidx = scm.xcidx (); |
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681 } |
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682 else |
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683 { |
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684 SparseMatrix sm = args(0).sparse_matrix_value (); |
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685 |
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686 n_row = sm.rows (); |
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687 n_col = sm.cols (); |
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688 ridx = sm.xridx (); |
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689 cidx = sm.xcidx (); |
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690 } |
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691 |
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692 bool is_sym = true; |
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693 |
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694 if (nargin == 2) |
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695 { |
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696 std::string str = args(1).xstring_value ("etree: TYP must be a string"); |
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697 if (str.find ("C") == 0 || str.find ("c") == 0) |
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698 is_sym = false; |
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699 } |
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700 |
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701 // column elimination tree post-ordering (reuse variables) |
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702 OCTAVE_LOCAL_BUFFER (octave_idx_type, etree, n_col + 1); |
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703 |
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704 if (is_sym) |
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705 { |
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706 if (n_row != n_col) |
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707 error ("etree: S is marked as symmetric, but is not square"); |
5164 | 708 |
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709 symetree (ridx, cidx, etree, 0, n_col); |
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710 } |
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711 else |
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712 { |
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713 OCTAVE_LOCAL_BUFFER (octave_idx_type, colbeg, n_col); |
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714 OCTAVE_LOCAL_BUFFER (octave_idx_type, colend, n_col); |
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715 |
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716 for (octave_idx_type i = 0; i < n_col; i++) |
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717 { |
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718 colbeg[i] = cidx[i]; |
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719 colend[i] = cidx[i+1]; |
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720 } |
7924 | 721 |
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722 coletree (ridx, colbeg, colend, etree, n_row, n_col); |
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723 } |
7924 | 724 |
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725 NDArray tree (dim_vector (1, n_col)); |
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726 for (octave_idx_type i = 0; i < n_col; i++) |
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727 // We flag a root with n_col while Matlab does it with zero |
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728 // Convert for matlab compatiable output |
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729 if (etree[i] == n_col) |
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730 tree(i) = 0; |
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731 else |
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732 tree(i) = etree[i] + 1; |
5164 | 733 |
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734 retval(0) = tree; |
5164 | 735 |
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736 if (nargout == 2) |
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737 { |
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738 // Calculate the tree post-ordering |
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739 OCTAVE_LOCAL_BUFFER (octave_idx_type, post, n_col + 1); |
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740 tree_postorder (n_col, etree, post); |
5164 | 741 |
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742 NDArray postorder (dim_vector (1, n_col)); |
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743 for (octave_idx_type i = 0; i < n_col; i++) |
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744 postorder(i) = post[i] + 1; |
5164 | 745 |
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746 retval(1) = postorder; |
5164 | 747 } |
748 | |
749 return retval; | |
750 } |