Mercurial > hg > octave-lyh
diff scripts/sparse/sprandn.m @ 13197:6db186dfdeaa
Refactor sprandn/sprand code, move common code to common function (bug #34352)
* __sprand_impl__.m: New file
* module.mk: Add new file
* sprand.m: Remove comment in docstring about inaccuracy of density.
Put sprandsym in @seealso. Refactor repeated code into
__sprand_impl__.m
* sprandn.m: Ditto. Also enable test for exact density.
author | Jordi Gutiérrez Hermoso <jordigh@octave.org> |
---|---|
date | Fri, 23 Sep 2011 02:40:05 -0500 |
parents | bae887ebea48 |
children | 72c96de7a403 |
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--- a/scripts/sparse/sprandn.m +++ b/scripts/sparse/sprandn.m @@ -27,68 +27,30 @@ ## @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. -## @seealso{sprand} +## @seealso{sprand, sprandsym} ## @end deftypefn ## Author: Paul Kienzle <pkienzle@users.sf.net> function S = sprandn (m, n, d) - if (nargin != 1 && nargin != 3) + if (nargin == 1 ) + S = __sprand_impl__ (m, @randn); + elseif ( nargin == 3) + S = __sprand_impl__ (m, n, d, "sprandn", @randn); + else print_usage (); endif - if (nargin == 1) - [i, j] = find (m); - [nr, nc] = size (m); - S = sparse (i, j, randn (size (i)), nr, nc); - return; - endif - - if (!(isscalar (m) && m == fix (m) && m > 0)) - error ("sprand: M must be an integer greater than 0"); - endif - - if (!(isscalar (n) && n == fix (n) && n > 0)) - error ("sprand: N must be an integer greater than 0"); - endif - - if (d < 0 || d > 1) - error ("sprand: density D must be between 0 and 1"); - endif - - mn = m*n; - k = round (d*mn); - idx = unique (fix (rand (min (k*1.01, k+10), 1) * mn)) + 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. - - ## actual number of entries in S - k = min (length (idx), k); - j = floor ((idx(1:k)-1)/m); - i = idx(1:k) - j*m; - if (isempty (i)) - S = sparse (m, n); - else - S = sparse (i, j+1, randn (k, 1), m, n); - endif - endfunction -## FIXME: Test for density can't happen until code of sprandn is improved %!test %! s = sprandn (4, 10, 0.1); %! assert (size (s), [4, 10]); -##%! assert (nnz (s) / numel (s), 0.1, .01); +%! assert (nnz (s) / numel (s), 0.1); %% Test 1-input calling form %!test