GNU Octave  9.1.0
A high-level interpreted language, primarily intended for numerical computations, mostly compatible with Matlab
ccolamd.cc
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25 
26 // This is the octave interface to ccolamd, which bore the copyright given
27 // in the help of the functions.
28 
29 #if defined (HAVE_CONFIG_H)
30 # include "config.h"
31 #endif
32 
33 #include <cstdlib>
34 
35 #include "CSparse.h"
36 #include "Sparse.h"
37 #include "dNDArray.h"
38 #include "oct-locbuf.h"
39 #include "oct-sparse.h"
40 
41 #include "defun.h"
42 #include "error.h"
43 #include "errwarn.h"
44 #include "ov.h"
45 #include "pager.h"
46 
48 
49 DEFUN (ccolamd, args, nargout,
50  doc: /* -*- texinfo -*-
51 @deftypefn {} {@var{p} =} ccolamd (@var{S})
52 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs})
53 @deftypefnx {} {@var{p} =} ccolamd (@var{S}, @var{knobs}, @var{cmember})
54 @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{})
55 
56 Constrained column approximate minimum degree permutation.
57 
58 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum
59 degree permutation vector for the sparse matrix @var{S}. For a
60 non-symmetric matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have
61 sparser LU@tie{}factors than @var{S}.
62 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be
63 sparser than @code{chol (@var{S}' * @var{S})}.
64 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for
65 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column
66 elimination tree post-ordering.
67 
68 @var{knobs} is an optional 1-element to 5-element input vector, with a
69 default value of @code{[0 10 10 1 0]} if not present or empty. Entries not
70 present are set to their defaults.
71 
72 @table @code
73 @item @var{knobs}(1)
74 if nonzero, the ordering is optimized for @code{lu (S(:, p))}. It will be a
75 poor ordering for @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}.
76 This is the most important knob for ccolamd.
77 
78 @item @var{knobs}(2)
79 if @var{S} is m-by-n, rows with more than
80 @code{max (16, @var{knobs}(2) * sqrt (n))} entries are ignored.
81 
82 @item @var{knobs}(3)
83 columns with more than
84 @code{max (16, @var{knobs}(3) * sqrt (min (@var{m}, @var{n})))} entries are
85 ignored and ordered last in the output permutation
86 (subject to the cmember constraints).
87 
88 @item @var{knobs}(4)
89 if nonzero, aggressive absorption is performed.
90 
91 @item @var{knobs}(5)
92 if nonzero, statistics and knobs are printed.
93 
94 @end table
95 
96 @var{cmember} is an optional vector of length @math{n}. It defines the
97 constraints on the column ordering. If @code{@var{cmember}(j) = @var{c}},
98 then column @var{j} is in constraint set @var{c} (@var{c} must be in the
99 range 1 to n). In the output permutation @var{p}, all columns in set 1
100 appear first, followed by all columns in set 2, and so on.
101 @code{@var{cmember} = ones (1,n)} if not present or empty.
102 @code{ccolamd (@var{S}, [], 1 : n)} returns @code{1 : n}
103 
104 @code{@var{p} = ccolamd (@var{S})} is about the same as
105 @code{@var{p} = colamd (@var{S})}. @var{knobs} and its default values
106 differ. @code{colamd} always does aggressive absorption, and it finds an
107 ordering suitable for both @code{lu (@var{S}(:, @var{p}))} and @code{chol
108 (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))}; it cannot optimize its
109 ordering for @code{lu (@var{S}(:, @var{p}))} to the extent that
110 @code{ccolamd (@var{S}, 1)} can.
111 
112 @var{stats} is an optional 20-element output vector that provides data
113 about the ordering and the validity of the input matrix @var{S}. Ordering
114 statistics are in @code{@var{stats}(1 : 3)}. @code{@var{stats}(1)} and
115 @code{@var{stats}(2)} are the number of dense or empty rows and columns
116 ignored by @sc{ccolamd} and @code{@var{stats}(3)} is the number of garbage
117 collections performed on the internal data structure used by @sc{ccolamd}
118 (roughly of size @code{2.2 * nnz (@var{S}) + 4 * @var{m} + 7 * @var{n}}
119 integers).
120 
121 @code{@var{stats}(4 : 7)} provide information if CCOLAMD was able to
122 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if
123 invalid. @code{@var{stats}(5)} is the rightmost column index that is
124 unsorted or contains duplicate entries, or zero if no such column exists.
125 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row
126 index in the column index given by @code{@var{stats}(5)}, or zero if no
127 such row index exists. @code{@var{stats}(7)} is the number of duplicate
128 or out-of-order row indices. @code{@var{stats}(8 : 20)} is always zero in
129 the current version of @sc{ccolamd} (reserved for future use).
130 
131 The authors of the code itself are @nospell{S. Larimore, T. Davis} and
132 @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}.
133 Supported by the National Science Foundation
134 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from
135 @nospell{Sandia} National Lab.
136 See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd,
137 csymamd, amd, colamd, symamd, and other related orderings.
138 @seealso{colamd, csymamd}
139 @end deftypefn */)
140 {
141 #if defined (HAVE_CCOLAMD)
142 
143  int nargin = args.length ();
144 
145  if (nargin < 1 || nargin > 3)
146  print_usage ();
147 
148  octave_value_list retval (nargout == 2 ? 2 : 1);
149  int spumoni = 0;
150 
151  // Get knobs
152  static_assert (CCOLAMD_KNOBS <= 40,
153  "ccolamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org");
154  double knob_storage[CCOLAMD_KNOBS];
155  double *knobs = &knob_storage[0];
156  CCOLAMD_NAME (_set_defaults) (knobs);
157 
158  // Check for user-passed knobs
159  if (nargin > 1)
160  {
161  NDArray User_knobs = args(1).array_value ();
162  int nel_User_knobs = User_knobs.numel ();
163 
164  if (nel_User_knobs > 0)
165  knobs[CCOLAMD_LU] = (User_knobs(0) != 0);
166  if (nel_User_knobs > 1)
167  knobs[CCOLAMD_DENSE_ROW] = User_knobs(1);
168  if (nel_User_knobs > 2)
169  knobs[CCOLAMD_DENSE_COL] = User_knobs(2);
170  if (nel_User_knobs > 3)
171  knobs[CCOLAMD_AGGRESSIVE] = (User_knobs(3) != 0);
172  if (nel_User_knobs > 4)
173  spumoni = (User_knobs(4) != 0);
174 
175  // print knob settings if spumoni is set
176  if (spumoni)
177  {
178  octave_stdout << "\nccolamd version " << CCOLAMD_MAIN_VERSION << '.'
179  << CCOLAMD_SUB_VERSION << ", " << CCOLAMD_DATE
180  << ":\nknobs(1): " << User_knobs(0) << ", order for ";
181  if (knobs[CCOLAMD_LU] != 0)
182  octave_stdout << "lu (A)\n";
183  else
184  octave_stdout << "chol (A'*A)\n";
185 
186  if (knobs[CCOLAMD_DENSE_ROW] >= 0)
187  octave_stdout << "knobs(2): " << User_knobs(1)
188  << ", rows with > max (16,"
189  << knobs[CCOLAMD_DENSE_ROW]
190  << "* sqrt (columns(A)))"
191  << " entries removed\n";
192  else
193  octave_stdout << "knobs(2): " << User_knobs(1)
194  << ", no dense rows removed\n";
195 
196  if (knobs[CCOLAMD_DENSE_COL] >= 0)
197  octave_stdout << "knobs(3): " << User_knobs(2)
198  << ", cols with > max (16,"
199  << knobs[CCOLAMD_DENSE_COL] << "* sqrt (size(A)))"
200  << " entries removed\n";
201  else
202  octave_stdout << "knobs(3): " << User_knobs(2)
203  << ", no dense columns removed\n";
204 
205  if (knobs[CCOLAMD_AGGRESSIVE] != 0)
206  octave_stdout << "knobs(4): " << User_knobs(3)
207  << ", aggressive absorption: yes";
208  else
209  octave_stdout << "knobs(4): " << User_knobs(3)
210  << ", aggressive absorption: no";
211 
212  octave_stdout << "knobs(5): " << User_knobs(4)
213  << ", statistics and knobs printed\n";
214  }
215  }
216 
217  octave_idx_type n_row, n_col, nnz;
218  octave_idx_type *ridx, *cidx;
220  SparseMatrix sm;
221 
222  if (args(0).issparse ())
223  {
224  if (args(0).iscomplex ())
225  {
226  scm = args(0).sparse_complex_matrix_value ();
227  n_row = scm.rows ();
228  n_col = scm.cols ();
229  nnz = scm.nnz ();
230  ridx = scm.xridx ();
231  cidx = scm.xcidx ();
232  }
233  else
234  {
235  sm = args(0).sparse_matrix_value ();
236 
237  n_row = sm.rows ();
238  n_col = sm.cols ();
239  nnz = sm.nnz ();
240  ridx = sm.xridx ();
241  cidx = sm.xcidx ();
242  }
243  }
244  else
245  {
246  if (args(0).iscomplex ())
247  sm = SparseMatrix (real (args(0).complex_matrix_value ()));
248  else
249  sm = SparseMatrix (args(0).matrix_value ());
250 
251  n_row = sm.rows ();
252  n_col = sm.cols ();
253  nnz = sm.nnz ();
254  ridx = sm.xridx ();
255  cidx = sm.xcidx ();
256  }
257 
258  // Allocate workspace for ccolamd
260  for (octave_idx_type i = 0; i < n_col+1; i++)
261  p[i] = cidx[i];
262 
263  octave_idx_type Alen = CCOLAMD_NAME (_recommended) (nnz, n_row, n_col);
265  for (octave_idx_type i = 0; i < nnz; i++)
266  A[i] = ridx[i];
267 
268  static_assert (CCOLAMD_STATS <= 40,
269  "ccolamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org");
270  suitesparse_integer stats_storage[CCOLAMD_STATS];
271  suitesparse_integer *stats = &stats_storage[0];
272 
273  if (nargin > 2)
274  {
275  NDArray in_cmember = args(2).array_value ();
276  octave_idx_type cslen = in_cmember.numel ();
277  OCTAVE_LOCAL_BUFFER (suitesparse_integer, cmember, cslen);
278  for (octave_idx_type i = 0; i < cslen; i++)
279  // convert cmember from 1-based to 0-based
280  cmember[i] = static_cast<suitesparse_integer> (in_cmember(i) - 1);
281 
282  if (cslen != n_col)
283  error ("ccolamd: CMEMBER must be of length equal to #cols of A");
284 
285  // Order the columns (destroys A)
286  if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, cmember))
287  {
288  CCOLAMD_NAME (_report) (stats);
289 
290  error ("ccolamd: internal error!");
291  }
292  }
293  else
294  {
295  // Order the columns (destroys A)
296  if (! CCOLAMD_NAME () (n_row, n_col, Alen, A, p, knobs, stats, nullptr))
297  {
298  CCOLAMD_NAME (_report) (stats);
299 
300  error ("ccolamd: internal error!");
301  }
302  }
303 
304  // return the permutation vector
305  NDArray out_perm (dim_vector (1, n_col));
306  for (octave_idx_type i = 0; i < n_col; i++)
307  out_perm(i) = p[i] + 1;
308 
309  retval(0) = out_perm;
310 
311  // print stats if spumoni > 0
312  if (spumoni > 0)
313  CCOLAMD_NAME (_report) (stats);
314 
315  // Return the stats vector
316  if (nargout == 2)
317  {
318  NDArray out_stats (dim_vector (1, CCOLAMD_STATS));
319  for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++)
320  out_stats(i) = stats[i];
321  retval(1) = out_stats;
322 
323  // fix stats (5) and (6), for 1-based information on
324  // jumbled matrix. note that this correction doesn't
325  // occur if symamd returns FALSE
326  out_stats(CCOLAMD_INFO1)++;
327  out_stats(CCOLAMD_INFO2)++;
328  }
329 
330  return retval;
331 
332 #else
333 
334  octave_unused_parameter (args);
335  octave_unused_parameter (nargout);
336 
337  err_disabled_feature ("ccolamd", "CCOLAMD");
338 
339 #endif
340 }
341 
342 DEFUN (csymamd, args, nargout,
343  doc: /* -*- texinfo -*-
344 @deftypefn {} {@var{p} =} csymamd (@var{S})
345 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs})
346 @deftypefnx {} {@var{p} =} csymamd (@var{S}, @var{knobs}, @var{cmember})
347 @deftypefnx {} {[@var{p}, @var{stats}] =} csymamd (@dots{})
348 
349 For a symmetric positive definite matrix @var{S}, return the permutation
350 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a
351 sparser Cholesky@tie{}factor than @var{S}.
352 
353 Sometimes @code{csymamd} works well for symmetric indefinite matrices too.
354 The matrix @var{S} is assumed to be symmetric; only the strictly lower
355 triangular part is referenced. @var{S} must be square. The ordering is
356 followed by an elimination tree post-ordering.
357 
358 @var{knobs} is an optional 1-element to 3-element input vector, with a
359 default value of @code{[10 1 0]}. Entries not present are set to their
360 defaults.
361 
362 @table @code
363 @item @var{knobs}(1)
364 If @var{S} is n-by-n, then rows and columns with more than
365 @code{max(16,@var{knobs}(1)*sqrt(n))} entries are ignored, and ordered
366 last in the output permutation (subject to the cmember constraints).
367 
368 @item @var{knobs}(2)
369 If nonzero, aggressive absorption is performed.
370 
371 @item @var{knobs}(3)
372 If nonzero, statistics and knobs are printed.
373 
374 @end table
375 
376 @var{cmember} is an optional vector of length n. It defines the constraints
377 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is
378 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the
379 output permutation @var{p}, rows/columns in set 1 appear first, followed
380 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)}
381 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns
382 @code{1:n}.
383 
384 @code{@var{p} = csymamd (@var{S})} is about the same as
385 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values
386 differ.
387 
388 @code{@var{stats}(4:7)} provide information if CCOLAMD was able to
389 continue. The matrix is OK if @code{@var{stats}(4)} is zero, or 1 if
390 invalid. @code{@var{stats}(5)} is the rightmost column index that is
391 unsorted or contains duplicate entries, or zero if no such column exists.
392 @code{@var{stats}(6)} is the last seen duplicate or out-of-order row
393 index in the column index given by @code{@var{stats}(5)}, or zero if no
394 such row index exists. @code{@var{stats}(7)} is the number of duplicate
395 or out-of-order row indices. @code{@var{stats}(8:20)} is always zero in
396 the current version of @sc{ccolamd} (reserved for future use).
397 
398 The authors of the code itself are @nospell{S. Larimore, T. Davis} and
399 @nospell{S. Rajamanickam} in collaboration with @nospell{J. Bilbert and E. Ng}.
400 Supported by the National Science Foundation
401 @nospell{(DMS-9504974, DMS-9803599, CCR-0203270)}, and a grant from
402 @nospell{Sandia} National Lab.
403 See @url{http://faculty.cse.tamu.edu/davis/suitesparse.html} for ccolamd,
404 colamd, csymamd, amd, colamd, symamd, and other related orderings.
405 @seealso{symamd, ccolamd}
406 @end deftypefn */)
407 {
408 #if defined (HAVE_CCOLAMD)
409 
410  int nargin = args.length ();
411 
412  if (nargin < 1 || nargin > 3)
413  print_usage ();
414 
415  octave_value_list retval (nargout == 2 ? 2 : 1);
416  int spumoni = 0;
417 
418  // Get knobs
419  static_assert (CCOLAMD_KNOBS <= 40,
420  "csymamd: # of CCOLAMD_KNOBS exceeded. Please report this to bugs.octave.org");
421  double knob_storage[CCOLAMD_KNOBS];
422  double *knobs = &knob_storage[0];
423  CCOLAMD_NAME (_set_defaults) (knobs);
424 
425  // Check for user-passed knobs
426  if (nargin > 1)
427  {
428  NDArray User_knobs = args(1).array_value ();
429  int nel_User_knobs = User_knobs.numel ();
430 
431  if (nel_User_knobs > 0)
432  knobs[CCOLAMD_DENSE_ROW] = User_knobs(0);
433  if (nel_User_knobs > 1)
434  knobs[CCOLAMD_AGGRESSIVE] = User_knobs(1);
435  if (nel_User_knobs > 2)
436  spumoni = static_cast<int> (User_knobs(2));
437 
438  // print knob settings if spumoni is set
439  if (spumoni)
440  {
441  octave_stdout << "\ncsymamd version " << CCOLAMD_MAIN_VERSION
442  << '.' << CCOLAMD_SUB_VERSION
443  << ", " << CCOLAMD_DATE << "\n";
444 
445  if (knobs[CCOLAMD_DENSE_ROW] >= 0)
446  octave_stdout << "knobs(1): " << User_knobs(0)
447  << ", rows/cols with > max (16,"
448  << knobs[CCOLAMD_DENSE_ROW]
449  << "* sqrt (columns(A)))"
450  << " entries removed\n";
451  else
452  octave_stdout << "knobs(1): " << User_knobs(0)
453  << ", no dense rows/cols removed\n";
454 
455  if (knobs[CCOLAMD_AGGRESSIVE] != 0)
456  octave_stdout << "knobs(2): " << User_knobs(1)
457  << ", aggressive absorption: yes";
458  else
459  octave_stdout << "knobs(2): " << User_knobs(1)
460  << ", aggressive absorption: no";
461 
462  octave_stdout << "knobs(3): " << User_knobs(2)
463  << ", statistics and knobs printed\n";
464  }
465  }
466 
467  octave_idx_type n_row, n_col;
468  octave_idx_type *ridx, *cidx;
469  SparseMatrix sm;
471 
472  if (args(0).issparse ())
473  {
474  if (args(0).iscomplex ())
475  {
476  scm = args(0).sparse_complex_matrix_value ();
477  n_row = scm.rows ();
478  n_col = scm.cols ();
479  ridx = scm.xridx ();
480  cidx = scm.xcidx ();
481  }
482  else
483  {
484  sm = args(0).sparse_matrix_value ();
485  n_row = sm.rows ();
486  n_col = sm.cols ();
487  ridx = sm.xridx ();
488  cidx = sm.xcidx ();
489  }
490  }
491  else
492  {
493  if (args(0).iscomplex ())
494  sm = SparseMatrix (real (args(0).complex_matrix_value ()));
495  else
496  sm = SparseMatrix (args(0).matrix_value ());
497 
498  n_row = sm.rows ();
499  n_col = sm.cols ();
500  ridx = sm.xridx ();
501  cidx = sm.xcidx ();
502  }
503 
504  if (n_row != n_col)
505  err_square_matrix_required ("csymamd", "S");
506 
507  // Allocate workspace for symamd
508  OCTAVE_LOCAL_BUFFER (suitesparse_integer, perm, n_col+1);
509  static_assert (CCOLAMD_STATS <= 40,
510  "csymamd: # of CCOLAMD_STATS exceeded. Please report this to bugs.octave.org");
511  suitesparse_integer stats_storage[CCOLAMD_STATS];
512  suitesparse_integer *stats = &stats_storage[0];
513 
514  if (nargin > 2)
515  {
516  NDArray in_cmember = args(2).array_value ();
517  octave_idx_type cslen = in_cmember.numel ();
518  OCTAVE_LOCAL_BUFFER (suitesparse_integer, cmember, cslen);
519  for (octave_idx_type i = 0; i < cslen; i++)
520  // convert cmember from 1-based to 0-based
521  cmember[i] = static_cast<octave_idx_type> (in_cmember(i) - 1);
522 
523  if (cslen != n_col)
524  error ("csymamd: CMEMBER must be of length equal to #cols of A");
525 
526  if (! CSYMAMD_NAME () (n_col,
527  to_suitesparse_intptr (ridx),
528  to_suitesparse_intptr (cidx),
529  perm, knobs, stats, &calloc, &free, cmember, -1))
530  {
531  CSYMAMD_NAME (_report)(stats);
532 
533  error ("csymamd: internal error!");
534  }
535  }
536  else
537  {
538  if (! CSYMAMD_NAME () (n_col,
539  to_suitesparse_intptr (ridx),
540  to_suitesparse_intptr (cidx),
541  perm, knobs, stats, &calloc, &free, nullptr, -1))
542  {
543  CSYMAMD_NAME (_report)(stats);
544 
545  error ("csymamd: internal error!");
546  }
547  }
548 
549  // return the permutation vector
550  NDArray out_perm (dim_vector (1, n_col));
551  for (octave_idx_type i = 0; i < n_col; i++)
552  out_perm(i) = perm[i] + 1;
553 
554  retval(0) = out_perm;
555 
556  // print stats if spumoni > 0
557  if (spumoni > 0)
558  CSYMAMD_NAME (_report)(stats);
559 
560  // Return the stats vector
561  if (nargout == 2)
562  {
563  NDArray out_stats (dim_vector (1, CCOLAMD_STATS));
564  for (octave_idx_type i = 0 ; i < CCOLAMD_STATS ; i++)
565  out_stats(i) = stats[i];
566  retval(1) = out_stats;
567 
568  // fix stats (5) and (6), for 1-based information on
569  // jumbled matrix. note that this correction doesn't
570  // occur if symamd returns FALSE
571  out_stats(CCOLAMD_INFO1)++;
572  out_stats(CCOLAMD_INFO2)++;
573  }
574 
575  return retval;
576 
577 #else
578 
579  octave_unused_parameter (args);
580  octave_unused_parameter (nargout);
581 
582  err_disabled_feature ("csymamd", "CCOLAMD");
583 
584 #endif
585 }
586 
587 OCTAVE_END_NAMESPACE(octave)
octave_idx_type numel() const
Number of elements in the array.
Definition: Array.h:414
octave_idx_type cols() const
Definition: Sparse.h:352
octave_idx_type * xcidx()
Definition: Sparse.h:602
octave_idx_type nnz() const
Actual number of nonzero terms.
Definition: Sparse.h:339
octave_idx_type rows() const
Definition: Sparse.h:351
octave_idx_type * xridx()
Definition: Sparse.h:589
Vector representing the dimensions (size) of an Array.
Definition: dim-vector.h:94
ColumnVector real(const ComplexColumnVector &a)
Definition: dColVector.cc:137
OCTAVE_BEGIN_NAMESPACE(octave) static octave_value daspk_fcn
void print_usage(void)
Definition: defun-int.h:72
#define DEFUN(name, args_name, nargout_name, doc)
Macro to define a builtin function.
Definition: defun.h:56
void() error(const char *fmt,...)
Definition: error.cc:988
void err_square_matrix_required(const char *fcn, const char *name)
Definition: errwarn.cc:122
void err_disabled_feature(const std::string &fcn, const std::string &feature, const std::string &pkg)
Definition: errwarn.cc:53
F77_RET_T const F77_INT F77_CMPLX * A
#define OCTAVE_LOCAL_BUFFER(T, buf, size)
Definition: oct-locbuf.h:44
suitesparse_integer * to_suitesparse_intptr(octave_idx_type *i)
Definition: oct-sparse.cc:51
#define CCOLAMD_NAME(name)
Definition: oct-sparse.h:131
int suitesparse_integer
Definition: oct-sparse.h:184
#define CSYMAMD_NAME(name)
Definition: oct-sparse.h:132
void free(void *)
#define octave_stdout
Definition: pager.h:309