Bug when using min() with sparse matrices?

5 views (last 30 days)
Ingo
Ingo on 8 Jan 2012
Hi,
I translated one of my Matlab routines to C and now I've encountered a really strange behaviour which seems to be a bug. M is a sparse matrix and I printed M, M', min(M, M') and min(full(M), full(M')), but all of them as full matrices to see the problem better:
The last matrix is what I want and what I'm supposed to already get by using min(M, M'), but for some reason min(M, M') shows some really weird behaviour. Any gueses what causes this?
Edit: Here's the mex file:
#include "mex.h"
void mexFunction(int nlhs, mxArray* plhs[], int nrhs, const mxArray *prhs[])
{
mxArray *tempArray, *outputDist[1], *inputDist[2], *outputSort[2];
double *tempVal, *pr, *sr, *sorted, *order;
mwSize n, nzmax;
mwIndex *irs, *jcs, i, j, k;
// distance function call
tempArray = mxCreateDoubleMatrix(1, 1, mxREAL);
tempVal = mxGetPr(tempArray);
inputDist[0] = prhs[0];
inputDist[1] = tempArray;
// read input matrix size
n = mxGetN(prhs[0]);
// read real part of input matrix
pr = mxGetPr(prhs[0]);
// read parameter for k
k = (mwIndex)*mxGetPr(prhs[1]);
// create output sparse matrix
nzmax = (mwSize)(n*k);
plhs[0] = mxCreateSparse(n, n, nzmax, mxREAL);
sr = mxGetPr(plhs[0]);
irs = mxGetIr(plhs[0]);
jcs = mxGetJc(plhs[0]);
// go through data points
for (i = 0; i < n; i++)
{
// calculate distance vector
tempVal[0] = (double)(i+1);
mexCallMATLAB(1, outputDist, 2, inputDist, "distEuclidean2");
// sort vector
mexCallMATLAB(2, outputSort, 1, &outputDist[0], "sort");
sorted = mxGetPr(outputSort[0]);
order = mxGetPr(outputSort[1]);
// assign values to sparse matrix
jcs[i] = i*k;
for (j = 0; j < k; j++)
{
irs[i*k+j] = (mwIndex)(order[j]-1);
sr[i*k+j] = sorted[j];
}
}
jcs[n] = n*k;
}
And here is the called distEuclidean2:
function [ d ] = distEuclidean2( M, ii )
d = sqrt(sum((repmat(M(:, ii), 1, size(M, 2)) - M) .^ 2, 1));
emd
  6 Comments
Ingo
Ingo on 9 Jan 2012
I added the mex source code now. The function is called with a d-by-n matrix of n data points and a number k as the second parameter. It then calculates the n-by-n distance matrix, but only keeps the k smallest distances, all other values are set to zero (thus making it sparse).
I added distEuclidean2.m as well. I compile the mex file with "mex filename.c -largeArrayDims" and I'm running a 64-bit Matlab. One can then run it with
A = (1:5);
M = whateveryoucalledit(A, 3);
for example.

Sign in to comment.

Accepted Answer

James Tursa
James Tursa on 9 Jan 2012
You might try using this to check the matrix:
href=""<http://www.mathworks.com/matlabcentral/fileexchange/20186-spok-checks-if-a-matlab-sparse-matrix-is-ok</a>>
Not sure if it works for 64-bit.
  1 Comment
Ingo
Ingo on 9 Jan 2012
Thanks. I could use it by modifying the installation to 64-bit. I knew about having explicit zero entries (didn't they they'd be a problem), but I also have row index problems. After using M = 1*M and M = M'' the min(M, M') command works. Now I know where the problem is!

Sign in to comment.

More Answers (0)

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!