| 12
 3
 4
 5
 6
 7
 8
 9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 
 | function [p, Info] = camd (A, Control, C)				    %#ok
%CAMD p = camd (A), the approximate minimum degree ordering of A
%    P = CAMD (S) returns the approximate minimum degree permutation vector for
%    the sparse matrix C = S+S'.  The Cholesky factorization of C (P,P), or
%    S (P,P), tends to be sparser than that of C or S.  CAMD tends to be faster
%    than SYMMMD and SYMAMD, and tends to return better orderings than SYMMMD.
%    S must be square. If S is full, camd(S) is equivalent to camd(sparse(S)).
%
%    Usage:  P = camd (S) ;                   % finds the ordering
%            [P, Info] = camd (S,Control,C) ; % optional parameters & statistics
%            Control = camd ;                 % returns default parameters
%            camd ;                           % prints default parameters.
%
%       Control (1); If S is n-by-n, then rows/columns with more than
%           max (16, (Control (1))* sqrt(n)) entries in S+S' are considered
%           "dense", and ignored during ordering.  They are placed last in the
%           output permutation.  The default is 10.0 if Control is not present.
%       Control (2): If nonzero, then aggressive absorption is performed.
%           This is the default if Control is not present.
%       Control (3): If nonzero, print statistics about the ordering.
%
%       Info (1): status (0: ok, -1: out of memory, -2: matrix invalid)
%       Info (2): n = size (A,1)
%       Info (3): nnz (A)
%       Info (4): the symmetry of the matrix S (0.0 means purely unsymmetric,
%           1.0 means purely symmetric).  Computed as:
%           B = tril (S, -1) + triu (S, 1) ; symmetry = nnz (B & B') / nnz (B);
%       Info (5): nnz (diag (S))
%       Info (6): nnz in S+S', excluding the diagonal (= nnz (B+B'))
%       Info (7): number "dense" rows/columns in S+S'
%       Info (8): the amount of memory used by CAMD, in bytes
%       Info (9): the number of memory compactions performed by CAMD
%
%    The following statistics are slight upper bounds because of the
%    approximate degree in CAMD.  The bounds are looser if "dense" rows/columns
%    are ignored during ordering (Info (7) > 0).  The statistics are for a
%    subsequent factorization of the matrix C (P,P).  The LU factorization
%    statistics assume no pivoting.
%
%       Info (10): the number of nonzeros in L, excluding the diagonal
%       Info (11): the number of divide operations for LL', LDL', or LU
%       Info (12): the number of multiply-subtract pairs for LL' or LDL'
%       Info (13): the number of multiply-subtract pairs for LU
%       Info (14): the max # of nonzeros in any column of L (incl. diagonal)
%       Info (15:20): unused, reserved for future use
%
%    An assembly tree post-ordering is performed, which is typically the same
%    as an elimination tree post-ordering.  It is not always identical because
%    of the approximate degree update used, and because "dense" rows/columns
%    do not take part in the post-order.  It well-suited for a subsequent
%    "chol", however.  If you require a precise elimination tree post-ordering,
%    then do the following:
%
%    Example:
%       P = camd (S) ;
%       C = spones (S) + spones (S') ;  % skip this if S already symmetric
%       [ignore, Q] = etree (C (P,P)) ;
%       P = P (Q) ;
%
%    CAMD has the ability to order the matrix with constraints.  Each
%    node i in the graph (row/column i in the matrix) has a constraint,
%    C(i), which is in the range 1 to n.  All nodes with C(i) = 1 are
%    ordered first, followed by all nodes with constraint 2, and so on.
%    That is, C(P) is monotonically non-decreasing.  If C is not provided,
%    no constraints are used (the ordering will be similar to AMD's ordering,
%    except that the postordering is different).
%
%    See also AMD, COLMMD, COLAMD, COLPERM, SYMAMD, SYMMMD, SYMRCM.
% CAMD, Copyright (c) 2007-2022, Timothy A. Davis, Yanqing Chen, Patrick R.
% Amestoy, and Iain S. Duff.  All Rights Reserved.
% SPDX-License-Identifier: BSD-3-clause
%    Acknowledgements: This work was supported by the National Science
%       Foundation, under grants ASC-9111263, DMS-9223088, and CCR-0203270,
%       and by Sandia National Laboratories.
help camd
error ('camd mexFunction not found!  Type "camd_make" in MATLAB to compile camd');
 |