Mercurial > hg > octave-lyh
diff scripts/sparse/sprandsym.m @ 5610:9761b7d24e9e
[project @ 2006-02-09 09:12:02 by dbateman]
author | dbateman |
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date | Thu, 09 Feb 2006 09:12:03 +0000 |
parents | |
children | 2618a0750ae6 |
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new file mode 100644 --- /dev/null +++ b/scripts/sparse/sprandsym.m @@ -0,0 +1,75 @@ +## Copyright (C) 2004 David Bateman & Andy Adler +## +## This program is free software; you can redistribute it and/or modify +## it under the terms of the GNU General Public License as published by +## the Free Software Foundation; either version 2 of the License, or +## (at your option) any later version. +## +## This program is distributed in the hope that it will be useful, +## but WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +## GNU General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with this program; if not, write to the Free Software +## Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA +## 02110-1301 USA + +## -*- texinfo -*- +## @deftypefn {Function File} {} sprandsym (@var{n}, @var{d}) +## @deftypefnx {Function File} {} sprandsym (@var{s}) +## Generate a symmetric random sparse matrix. The size of the matrix will be +## @var{n} by @var{n}, with a density of values given by @var{d}. +## @var{d} should be between 0 and 1. Values will be normally +## distributed with mean of zero and variance 1. +## +## Note: sometimes the actual density may be a bit smaller than @var{d}. +## This is unlikely to happen for large really sparse matrices. +## +## If called with a single matrix argument, a random sparse matrix is +## generated wherever the matrix @var{S} is non-zero in its lower +## triangular part. +## @end deftypefn +## @seealso{sprand, sprandn} + +function S = sprandsym(n,d) + if nargin == 1 + [i,j,v,nr,nc] = spfind(tril(n)); + S = sparse(i,j,randn(size(v)),nr,nc); + S = S + tril(S,-1)'; + elseif nargin == 2 + m1 = floor(n/2); + n1 = m1 + 1; + mn1 = m1*n1; + k1 = round(d*mn1); + idx1=unique(fix(rand(min(k1*1.01,k1+10),1)*mn1))+1; + # idx contains random numbers in [1,mn] + # generate 1% or 10 more random values than necessary + # in order to reduce the probability that there are less than k + # distinct values; + # maybe a better strategy could be used + # but I don't think it's worth the price + k1 = min(length(idx1),k1); # actual number of entries in S + j1 = floor((idx1(1:k1)-1)/m1); + i1 = idx1(1:k1) - j1*m1; + + n2 = ceil(n/2); + nn2 = n2*n2; + k2 = round(d*nn2); + idx2=unique(fix(rand(min(k2*1.01,k1+10),1)*nn2))+1; + k2 = min(length(idx2),k2); + j2 = floor((idx2(1:k2)-1)/n2); + i2 = idx2(1:k2) - j2*n2; + + if isempty(i1) && isempty(i2) + S = sparse(n,n); + else + S1 = sparse(i1,j1+1,randn(k1,1),m1,n1); + S = [tril(S1), sparse(m1,m1); ... + sparse(i2,j2+1,randn(k2,1),n2,n2), triu(S1,1)']; + S = S + tril(S,-1)'; + endif + else + usage("sprandsym(n,density) OR sprandsym(S)"); + endif +endfunction