Mercurial > octave
comparison libinterp/dldfcn/ccolamd.cc @ 21547:ad0599a0acc6
doc: Wrap C++ docstrings to 79 characters + newline (80 total).
* besselj.cc, bitfcns.cc, cellfun.cc, data.cc, debug.cc, error.cc,
file-io.cc, graphics.cc, input.cc, lu.cc, matrix_type.cc, nproc.cc,
pr-output.cc, quadcc.cc, regexp.cc, schur.cc, sparse.cc, strfind.cc, strfns.cc,
syscalls.cc, urlwrite.cc, variables.cc, __osmesa_print__.cc, audiodevinfo.cc,
audioread.cc, ccolamd.cc, chol.cc, colamd.cc, convhulln.cc, qr.cc, symbfact.cc,
ov-java.cc, ov-struct.cc, ov-usr-fcn.cc, pt-arg-list.cc:
doc: Wrap C++ docstrings to 79 characters + newline (80 total).
| author | Rik <rik@octave.org> |
|---|---|
| date | Sun, 27 Mar 2016 20:39:19 -0700 |
| parents | 40de9f8f23a6 |
| children | 47c76e56a1de |
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| 21546:f7f97d7e9294 | 21547:ad0599a0acc6 |
|---|---|
| 60 @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\ | 60 @deftypefnx {} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\ |
| 61 \n\ | 61 \n\ |
| 62 Constrained column approximate minimum degree permutation.\n\ | 62 Constrained column approximate minimum degree permutation.\n\ |
| 63 \n\ | 63 \n\ |
| 64 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum\n\ | 64 @code{@var{p} = ccolamd (@var{S})} returns the column approximate minimum\n\ |
| 65 degree permutation vector for the sparse matrix @var{S}. For a non-symmetric\n\ | 65 degree permutation vector for the sparse matrix @var{S}. For a\n\ |
| 66 matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have sparser\n\ | 66 non-symmetric matrix @var{S}, @code{@var{S}(:, @var{p})} tends to have\n\ |
| 67 LU@tie{}factors than @var{S}.\n\ | 67 sparser LU@tie{}factors than @var{S}.\n\ |
| 68 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be\n\ | 68 @code{chol (@var{S}(:, @var{p})' * @var{S}(:, @var{p}))} also tends to be\n\ |
| 69 sparser than @code{chol (@var{S}' * @var{S})}.\n\ | 69 sparser than @code{chol (@var{S}' * @var{S})}.\n\ |
| 70 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for\n\ | 70 @code{@var{p} = ccolamd (@var{S}, 1)} optimizes the ordering for\n\ |
| 71 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column\n\ | 71 @code{lu (@var{S}(:, @var{p}))}. The ordering is followed by a column\n\ |
| 72 elimination tree post-ordering.\n\ | 72 elimination tree post-ordering.\n\ |
| 343 \n\ | 343 \n\ |
| 344 For a symmetric positive definite matrix @var{S}, return the permutation\n\ | 344 For a symmetric positive definite matrix @var{S}, return the permutation\n\ |
| 345 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a\n\ | 345 vector @var{p} such that @code{@var{S}(@var{p},@var{p})} tends to have a\n\ |
| 346 sparser Cholesky@tie{}factor than @var{S}.\n\ | 346 sparser Cholesky@tie{}factor than @var{S}.\n\ |
| 347 \n\ | 347 \n\ |
| 348 Sometimes @code{csymamd} works well for symmetric indefinite matrices too. \n\ | 348 Sometimes @code{csymamd} works well for symmetric indefinite matrices too.\n\ |
| 349 The matrix @var{S} is assumed to be symmetric; only the strictly lower\n\ | 349 The matrix @var{S} is assumed to be symmetric; only the strictly lower\n\ |
| 350 triangular part is referenced. @var{S} must be square. The ordering is\n\ | 350 triangular part is referenced. @var{S} must be square. The ordering is\n\ |
| 351 followed by an elimination tree post-ordering.\n\ | 351 followed by an elimination tree post-ordering.\n\ |
| 352 \n\ | 352 \n\ |
| 353 @var{knobs} is an optional 1-element to 3-element input vector, with a\n\ | 353 @var{knobs} is an optional 1-element to 3-element input vector, with a\n\ |
| 371 @var{cmember} is an optional vector of length n. It defines the constraints\n\ | 371 @var{cmember} is an optional vector of length n. It defines the constraints\n\ |
| 372 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is\n\ | 372 on the ordering. If @code{@var{cmember}(j) = @var{S}}, then row/column j is\n\ |
| 373 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the\n\ | 373 in constraint set @var{c} (@var{c} must be in the range 1 to n). In the\n\ |
| 374 output permutation @var{p}, rows/columns in set 1 appear first, followed\n\ | 374 output permutation @var{p}, rows/columns in set 1 appear first, followed\n\ |
| 375 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)}\n\ | 375 by all rows/columns in set 2, and so on. @code{@var{cmember} = ones (1,n)}\n\ |
| 376 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns @code{1:n}.\n\ | 376 if not present or empty. @code{csymamd (@var{S},[],1:n)} returns\n\ |
| 377 @code{1:n}.\n\ | |
| 377 \n\ | 378 \n\ |
| 378 @code{@var{p} = csymamd (@var{S})} is about the same as\n\ | 379 @code{@var{p} = csymamd (@var{S})} is about the same as\n\ |
| 379 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values\n\ | 380 @code{@var{p} = symamd (@var{S})}. @var{knobs} and its default values\n\ |
| 380 differ.\n\ | 381 differ.\n\ |
| 381 \n\ | 382 \n\ |