## Copyright (C) 2004 Paul Kienzle
##
## This program is free software and is in the public domain

## -*- texinfo -*-
## @deftypefn {Function File} {} sprandn (@var{m}, @var{n}, @var{d})
## @deftypefnx {Function File} {} sprandn (@var{s})
## Generate a random sparse matrix. The size of the matrix will be
## @var{m} 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.
## @seealso{sprand}
## @end deftypefn

## This program is public domain
## Author: Paul Kienzle <pkienzle@users.sf.net>

function S = sprandn(m,n,d)
  if nargin == 1
    [i,j,v,nr,nc] = spfind(m);
    S = sparse(i,j,randn(size(v)),nr,nc);
  elseif nargin == 3
    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
    k = min(length(idx),k);  # actual number of entries in S
    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
  else
    usage("sprandn(m,n,density) OR sprandn(S)");
  endif
endfunction