BNW using Octave instead of Matlab.

This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02

1 files changed, 154 insertions, 0 deletions

diff --git a/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_sparse_table.c b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_sparse_table.c
new file mode 100644
index 00000000..369f5b7e
--- /dev/null
+++ b/sourcecodes/bnt-master/BNT/CPDs/@discrete_CPD/convert_to_sparse_table.c
@@ -0,0 +1,154 @@
+/* convert_to_sparse_table.c  convert a sparse discrete CPD with evidence into sparse table */
+/* convert_to_pot.m located in ../CPDs/discrete_CPD call it */
+/* 3 input */
+/* CPD      prhs[0] with 1D sparse CPT */
+/* domain   prhs[1]                    */
+/* evidence prhs[2]                    */
+/* 1 output */
+/* T        plhs[0] sparse table       */
+
+#include <math.h>
+#include "mex.h"
+
+void ind_subv(int index, const int *cumprod, const int n, int *bsubv){
+	int i;
+
+	for (i = n-1; i >= 0; i--) {
+		bsubv[i] = ((int)floor(index / cumprod[i]));
+		index = index % cumprod[i];
+	}
+}
+
+int subv_ind(const int n, const int *cumprod, const int *subv){
+	int i, index=0;
+
+	for(i=0; i<n; i++){
+		index += subv[i] * cumprod[i];
+	}
+	return index;
+}
+
+void reset_nzmax(mxArray *spArray, const int old_nzmax, const int new_nzmax){
+	double *ptr;
+	void   *newptr;
+	int    *ir, *jc;
+	int    nbytes;
+
+	if(new_nzmax == old_nzmax) return;
+	nbytes = new_nzmax * sizeof(*ptr);
+	ptr = mxGetPr(spArray);
+	newptr = mxRealloc(ptr, nbytes);
+	mxSetPr(spArray, newptr);
+	nbytes = new_nzmax * sizeof(*ir);
+	ir = mxGetIr(spArray);
+	newptr = mxRealloc(ir, nbytes);
+	mxSetIr(spArray, newptr);
+	jc = mxGetJc(spArray);
+	jc[0] = 0;
+	jc[1] = new_nzmax;
+	mxSetNzmax(spArray, new_nzmax);
+}
+
+
+void mexFunction(int nlhs, mxArray *plhs[], int nrhs, const mxArray *prhs[]){
+	int     i, j, NS, NZB, count, bdim, match, domain, bindex, sindex, nzCounts=0;
+	int     *observed, *bsubv, *ssubv, *bir, *sir, *bjc, *sjc, *mask, *ssize, *bcumprod, *scumprod;
+	double  *pDomain, *pSize, *bpr, *spr;
+	mxArray *pTemp;
+
+	pTemp = mxGetField(prhs[0], 0, "CPT");
+	bpr = mxGetPr(pTemp);
+	bir = mxGetIr(pTemp);
+	bjc = mxGetJc(pTemp);
+	NZB = bjc[1];
+	pTemp = mxGetField(prhs[0], 0, "sizes");
+	pSize = mxGetPr(pTemp);
+
+	pDomain = mxGetPr(prhs[1]);
+	bdim = mxGetNumberOfElements(prhs[1]);
+
+	mask = malloc(bdim * sizeof(int));
+	ssize = malloc(bdim * sizeof(int));
+	observed = malloc(bdim * sizeof(int));
+
+	for(i=0; i<bdim; i++){
+		ssize[i] = (int)pSize[i];
+	}
+
+	count = 0;
+	for(i=0; i<bdim; i++){
+		domain = (int)pDomain[i] - 1;
+		pTemp = mxGetCell(prhs[2], domain);
+		if(pTemp){
+			mask[count] = i;
+			ssize[i] = 1;
+			observed[count] = (int)mxGetScalar(pTemp) - 1;
+			count++;
+		}
+	}
+
+	if(count == 0){
+		pTemp = mxGetField(prhs[0], 0, "CPT");
+		plhs[0] = mxDuplicateArray(pTemp);
+		free(mask);
+		free(ssize);
+		free(observed);
+		return;
+	}
+
+	bsubv = malloc(bdim * sizeof(int));
+	ssubv = malloc(count * sizeof(int));
+	bcumprod = malloc(bdim * sizeof(int));
+	scumprod = malloc(bdim * sizeof(int));
+
+	NS = 1;
+	for(i=0; i<bdim; i++){
+		NS *= ssize[i];
+	}
+
+	plhs[0] = mxCreateSparse(NS, 1, NS, mxREAL);
+	spr = mxGetPr(plhs[0]);
+	sir = mxGetIr(plhs[0]);
+	sjc = mxGetJc(plhs[0]);
+	sjc[0] = 0;
+	sjc[1] = NS;
+
+	bcumprod[0] = 1;
+	scumprod[0] = 1;
+	for(i=0; i<bdim-1; i++){
+		bcumprod[i+1] = bcumprod[i] * (int)pSize[i];
+		scumprod[i+1] = scumprod[i] * ssize[i];
+	}
+
+	nzCounts = 0;
+	for(i=0; i<NZB; i++){
+		bindex = bir[i];
+		ind_subv(bindex, bcumprod, bdim, bsubv);
+		for(j=0; j<count; j++){
+			ssubv[j] = bsubv[mask[j]];
+		}
+		match = 1;
+		for(j=0; j<count; j++){
+			if((ssubv[j]) != observed[j]){
+				match = 0;
+				break;
+			}
+		}
+		if(match){
+			spr[nzCounts] = bpr[i];
+			sindex = subv_ind(bdim, scumprod, bsubv);
+			sir[nzCounts] = sindex;
+			nzCounts++;
+		}
+	}
+
+	reset_nzmax(plhs[0], NS, nzCounts);
+	free(mask);
+	free(ssize);
+	free(observed);
+	free(bsubv);
+	free(ssubv);
+	free(bcumprod);
+	free(scumprod);
+}
+