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comparison src/DLD-FUNCTIONS/ccolamd.cc @ 10846:a4f482e66b65

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Grammarcheck more of the documentation. Use @noindent macro appropriately. Limit line length to 80 characters.
author Rik <octave@nomad.inbox5.com>
date Sun, 01 Aug 2010 20:22:17 -0700
parents 89f4d7e294cc
children fd0a3ac60b0e
comparison
equal deleted inserted replaced
10845:c0ffe159ba1a 10846:a4f482e66b65
57 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{s}, @var{knobs})\n\ 57 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{s}, @var{knobs})\n\
58 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{s}, @var{knobs}, @var{cmember})\n\ 58 @deftypefnx {Loadable Function} {@var{p} =} ccolamd (@var{s}, @var{knobs}, @var{cmember})\n\
59 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\ 59 @deftypefnx {Loadable Function} {[@var{p}, @var{stats}] =} ccolamd (@dots{})\n\
60 \n\ 60 \n\
61 Constrained column approximate minimum degree permutation.\n\ 61 Constrained column approximate minimum degree permutation.\n\
62 @code{@var{p} = ccolamd (@var{s})} returns the column approximate minimum degree\n\ 62 @code{@var{p} = ccolamd (@var{s})} returns the column approximate minimum\n\
63 permutation vector for the sparse matrix @var{s}. For a non-symmetric matrix\n\ 63 degree permutation vector for the sparse matrix @var{s}. For a non-symmetric\n\
64 matrix\n\
64 @var{s},\n\ 65 @var{s},\n\
65 @code{@var{s} (:, @var{p})} tends to have sparser LU factors than @var{s}.\n\ 66 @code{@var{s} (:, @var{p})} tends to have sparser LU factors than @var{s}.\n\
66 @code{chol (@var{s} (:, @var{p})' * @var{s} (:, @var{p}))} also tends to be\n\ 67 @code{chol (@var{s} (:, @var{p})' * @var{s} (:, @var{p}))} also tends to be\n\
67 sparser than @code{chol (@var{s}' * @var{s})}.\n\ 68 sparser than @code{chol (@var{s}' * @var{s})}.\n\
68 @code{@var{p} = ccolamd\n\ 69 @code{@var{p} = ccolamd\n\
103 first, followed by all columns in set 2, and so on. @code{@var{cmember} =\n\ 104 first, followed by all columns in set 2, and so on. @code{@var{cmember} =\n\
104 ones(1,n)} if not present or empty.\n\ 105 ones(1,n)} if not present or empty.\n\
105 @code{ccolamd (@var{s}, [], 1 : @var{n})} returns @code{1 : @var{n}}\n\ 106 @code{ccolamd (@var{s}, [], 1 : @var{n})} returns @code{1 : @var{n}}\n\
106 \n\ 107 \n\
107 @code{@var{p} = ccolamd (@var{s})} is about the same as\n\ 108 @code{@var{p} = ccolamd (@var{s})} is about the same as\n\
108 @code{@var{p} = colamd (@var{s})}. @var{knobs} and its default values differ. \n\ 109 @code{@var{p} = colamd (@var{s})}. @var{knobs} and its default values\n\
109 @code{colamd} always does aggressive absorption, and it finds an ordering\n\ 110 differ. @code{colamd} always does aggressive absorption, and it finds an\n\
110 suitable for both @code{lu (@var{s} (:, @var{p}))} and @code{chol (@var{S} (:,\n\ 111 ordering suitable for both @code{lu (@var{s} (:, @var{p}))} and @code{chol\n\
111 @var{p})' * @var{s} (:, @var{p}))}; it cannot optimize its ordering for\n\ 112 (@var{S} (:, @var{p})' * @var{s} (:, @var{p}))}; it cannot optimize its\n\
112 @code{lu (@var{s} (:, @var{p}))} to the extent that\n\ 113 ordering for @code{lu (@var{s} (:, @var{p}))} to the extent that\n\
113 @code{ccolamd (@var{s}, 1)} can.\n\ 114 @code{ccolamd (@var{s}, 1)} can.\n\
114 \n\ 115 \n\
115 @var{stats} is an optional 20-element output vector that provides data\n\ 116 @var{stats} is an optional 20-element output vector that provides data\n\
116 about the ordering and the validity of the input matrix @var{s}. Ordering\n\ 117 about the ordering and the validity of the input matrix @var{s}. Ordering\n\
117 statistics are in @code{@var{stats} (1 : 3)}. @code{@var{stats} (1)} and\n\ 118 statistics are in @code{@var{stats} (1 : 3)}. @code{@var{stats} (1)} and\n\