void mexFunction(int nlhs, mxArray *plhs[], int nrhs,
const mxArray *prhs[])
{
double *srwp, *srdp, *srtd, *probs, *Z, *WS, *DS, *ZIN;
double ALPHA,BETA;
mwIndex *irwp, *jcwp, *irdp, *jcdp, *irtd, *jctd;
int *z,*d,*w, *order, *wp, *ztot;
int W,T,D,NN,SEED,OUTPUT, nzmax, nzmaxwp, nzmaxdp, ntokens;
int i,j,c,n,nt,wi,di, startcond, n1,n2, TAVAIL, topic;
/* Check for proper number of arguments. */
if (nrhs < 8) {
mexErrMsgTxt("At least 8 input arguments required");
} else if (nlhs < 3) {
mexErrMsgTxt("3 output arguments required");
}
startcond = 0;
if (nrhs == 9) startcond = 1;
/* process the input arguments */
if (mxIsDouble( prhs[ 0 ] ) != 1) mexErrMsgTxt("WS input vector must be a double precision matrix");
if (mxIsDouble( prhs[ 1 ] ) != 1) mexErrMsgTxt("DS input vector must be a double precision matrix");
// pointer to word indices
WS = mxGetPr( prhs[ 0 ] );
// pointer to document indices
DS = mxGetPr( prhs[ 1 ] );
// get the number of tokens
ntokens = (int) mxGetM( prhs[ 0 ] ) * (int) mxGetN( prhs[ 0 ] );
if (ntokens == 0) mexErrMsgTxt("WS vector is empty");
if (ntokens != ( mxGetM( prhs[ 1 ] ) * mxGetN( prhs[ 1 ] ))) mexErrMsgTxt("WS and DS vectors should have same number of entries");
// Input Sparse-Tag-Document Matrix
srtd = mxGetPr(prhs[2]);
irtd = mxGetIr(prhs[2]);
jctd = mxGetJc(prhs[2]);
nzmaxdp = (int) mxGetNzmax(prhs[2]); // number of nonzero entries in tag-document matrix
NN = (int) mxGetScalar(prhs[3]);
if (NN<0) mexErrMsgTxt("Number of iterations must be positive");
ALPHA = (double) mxGetScalar(prhs[4]);
if (ALPHA<=0) mexErrMsgTxt("ALPHA must be greater than zero");
BETA = (double) mxGetScalar(prhs[5]);
if (BETA<=0) mexErrMsgTxt("BETA must be greater than zero");
SEED = (int) mxGetScalar(prhs[6]);
OUTPUT = (int) mxGetScalar(prhs[7]);
if (startcond == 1) {
ZIN = mxGetPr( prhs[ 8 ] );
if (ntokens != ( mxGetM( prhs[ 8 ] ) * mxGetN( prhs[ 8 ] ))) mexErrMsgTxt("WS and ZIN vectors should have same number of entries");
}
// seeding
seedMT( 1 + SEED * 2 ); // seeding only works on uneven numbers
/* allocate memory */
z = (int *) mxCalloc( ntokens , sizeof( int ));
if (startcond == 1) {
for (i=0; i<ntokens; i++) z[ i ] = (int) ZIN[ i ] - 1;
}
d = (int *) mxCalloc( ntokens , sizeof( int ));
w = (int *) mxCalloc( ntokens , sizeof( int ));
order = (int *) mxCalloc( ntokens , sizeof( int ));
// copy over the word and document indices into internal format
for (i=0; i<ntokens; i++) {
w[ i ] = (int) WS[ i ] - 1;
d[ i ] = (int) DS[ i ] - 1;
}
n = ntokens;
W = 0;
D = 0;
for (i=0; i<n; i++) {
if (w[ i ] > W) W = w[ i ];
if (d[ i ] > D) D = d[ i ];
}
W = W + 1;
D = D + 1;
// Number of topics is based on number of tags in sparse tag-document matrix
T = (int) mxGetM( prhs[ 2 ] );
// check number of docs in sparse tag-document matrix
if (D != (int) mxGetN( prhs[ 2 ])) mexErrMsgTxt("Mismatch in number of documents in DS vector TAGSET sparse matrix");
ztot = (int *) mxCalloc( T , sizeof( int ));
probs = (double *) mxCalloc( T , sizeof( double ));
wp = (int *) mxCalloc( T*W , sizeof( int ));
// create sparse DP matrix that is T x D and not the other way around !!!!
plhs[1] = mxCreateSparse( T,D,nzmaxdp,mxREAL);
srdp = mxGetPr(plhs[1]);
irdp = mxGetIr(plhs[1]);
jcdp = mxGetJc(plhs[1]);
// now copy the structure from TD over to DP
for (i=0; i<D; i++) {
n1 = (int) *( jctd + i );
n2 = (int) *( jctd + i + 1 );
// copy over the row-index start and end indices
*( jcdp + i ) = (int) n1;
// number of available topics for this document
TAVAIL = (n2-n1);
for (j = 0; j < TAVAIL; j++) {
topic = (int) *( irtd + n1 + j );
*( irdp + n1 + j ) = topic;
*( srdp + n1 + j ) = 0; // initialize DP counts with ZERO
}
}
// copy over final column indices
n1 = (int) *( jctd + D );
*( jcdp + D ) = (int) n1;
if (OUTPUT==2) {
mexPrintf( "Running LDA Gibbs Sampler Version 1.0\n" );
if (startcond==1) mexPrintf( "Starting from previous state ZIN\n" );
mexPrintf( "Arguments:\n" );
mexPrintf( "\tNumber of words W = %d\n" , W );
mexPrintf( "\tNumber of docs D = %d\n" , D );
mexPrintf( "\tNumber of tags T = %d\n" , T );
mexPrintf( "\tNumber of iterations N = %d\n" , NN );
mexPrintf( "\tHyperparameter ALPHA = %4.4f\n" , ALPHA );
mexPrintf( "\tHyperparameter BETA = %4.4f\n" , BETA );
mexPrintf( "\tSeed number = %d\n" , SEED );
mexPrintf( "\tNumber of tokens = %d\n" , ntokens );
mexPrintf( "\tNumber of nonzeros in tag matrix = %d\n" , nzmaxdp );
}
/* run the model */
GibbsSamplerLDA( ALPHA, BETA, W, T, D, NN, OUTPUT, n, z, d, w, wp, ztot, order, probs, startcond,
irtd, jctd, srdp, irdp, jcdp );
/* convert the full wp matrix into a sparse matrix */
nzmaxwp = 0;
for (i=0; i<W; i++) {
for (j=0; j<T; j++)
nzmaxwp += (int) ( *( wp + j + i*T )) > 0;
}
// MAKE THE WP SPARSE MATRIX
plhs[0] = mxCreateSparse( W,T,nzmaxwp,mxREAL);
srwp = mxGetPr(plhs[0]);
irwp = mxGetIr(plhs[0]);
jcwp = mxGetJc(plhs[0]);
n = 0;
for (j=0; j<T; j++) {
*( jcwp + j ) = n;
for (i=0; i<W; i++) {
c = (int) *( wp + i*T + j );
if (c >0) {
*( srwp + n ) = c;
*( irwp + n ) = i;
n++;
}
}
}
*( jcwp + T ) = n;
plhs[ 2 ] = mxCreateDoubleMatrix( 1,ntokens , mxREAL );
Z = mxGetPr( plhs[ 2 ] );
for (i=0; i<ntokens; i++) Z[ i ] = (double) z[ i ] + 1;
}
void mexFunction(int nlhs, mxArray *plhs[], int nrhs,
const mxArray *prhs[])
{
double *srwp, *srdp, *probs, *Z, *WS, *DS, *ZIN;
double ALPHA,BETA;
mwIndex *irwp, *jcwp, *irdp, *jcdp;
int *z,*d,*w, *order, *wp, *dp, *ztot;
int W,T,D,NN,SEED,OUTPUT, nzmax, nzmaxwp, nzmaxdp, ntokens;
int i,j,c,n,nt,wi,di, startcond;
/* Check for proper number of arguments. */
if (nrhs < 8) {
mexPrintf("1");
mexErrMsgTxt("At least 8 input arguments required");
} else if (nlhs < 3) {
mexPrintf("2");
mexErrMsgTxt("3 output arguments required");
}
startcond = 0;
if (nrhs == 9) {
mexPrintf("3");
startcond = 1;
}
/* process the input arguments */
if (mxIsDouble( prhs[ 0 ] ) != 1) mexErrMsgTxt("WS input vector must be a double precision matrix");
if (mxIsDouble( prhs[ 1 ] ) != 1) mexErrMsgTxt("DS input vector must be a double precision matrix");
// pointer to word indices
WS = mxGetPr( prhs[ 0 ] );
// pointer to document indices
DS = mxGetPr( prhs[ 1 ] );
// get the number of tokens
ntokens = mxGetM( prhs[ 0 ] ) * mxGetN( prhs[ 0 ] );
if (ntokens == 0){
mexPrintf("4");
mexErrMsgTxt("WS vector is empty");
}
if (ntokens != ( mxGetM( prhs[ 1 ] ) * mxGetN( prhs[ 1 ] ))) mexErrMsgTxt("WS and DS vectors should have same number of entries");
T = (int) mxGetScalar(prhs[2]);
if (T<=0){
mexPrintf("5");
mexErrMsgTxt("Number of topics must be greater than zero");
}
NN = (int) mxGetScalar(prhs[3]);
if (NN<0) mexErrMsgTxt("Number of iterations must be positive");
ALPHA = (double) mxGetScalar(prhs[4]);
if (ALPHA<=0) mexErrMsgTxt("ALPHA must be greater than zero");
BETA = (double) mxGetScalar(prhs[5]);
if (BETA<=0) mexErrMsgTxt("BETA must be greater than zero");
SEED = (int) mxGetScalar(prhs[6]);
OUTPUT = (int) mxGetScalar(prhs[7]);
mexPrintf("ok");
if (startcond == 1) {
mexPrintf("6");
ZIN = mxGetPr( prhs[ 8 ] );
if (ntokens != ( mxGetM( prhs[ 8 ] ) * mxGetN( prhs[ 8 ] ))) mexErrMsgTxt("WS and ZIN vectors should have same number of entries");
}
// seeding
seedMT( 1 + SEED * 2 ); // seeding only works on uneven numbers
/* allocate memory */
z = (int *) mxCalloc( ntokens , sizeof( int ));
if (startcond == 1) {
for (i=0; i<ntokens; i++) z[ i ] = (int) ZIN[ i ] - 1;
}
d = (int *) mxCalloc( ntokens , sizeof( int ));
w = (int *) mxCalloc( ntokens , sizeof( int ));
order = (int *) mxCalloc( ntokens , sizeof( int ));
ztot = (int *) mxCalloc( T , sizeof( int ));
probs = (double *) mxCalloc( T , sizeof( double ));
// copy over the word and document indices into internal format
for (i=0; i<ntokens; i++) {
w[ i ] = (int) WS[ i ] - 1;
d[ i ] = (int) DS[ i ] - 1;
}
n = ntokens;
W = 0;
D = 0;
for (i=0; i<n; i++) {
if (w[ i ] > W) W = w[ i ];
if (d[ i ] > D) D = d[ i ];
}
W = W + 1;
D = D + 1;
wp = (int *) mxCalloc( T*W , sizeof( int ));
dp = (int *) mxCalloc( T*D , sizeof( int ));
//mexPrintf( "N=%d T=%d W=%d D=%d\n" , ntokens , T , W , D );
if (OUTPUT==2) {
mexPrintf("7");
mexPrintf( "Running LDA Gibbs Sampler Version 1.0\n" );
if (startcond==1) mexPrintf( "Starting from previous state ZIN\n" );
mexPrintf( "Arguments:\n" );
mexPrintf( "\tNumber of words W = %d\n" , W );
mexPrintf( "\tNumber of docs D = %d\n" , D );
mexPrintf( "\tNumber of topics T = %d\n" , T );
mexPrintf( "\tNumber of iterations N = %d\n" , NN );
mexPrintf( "\tHyperparameter ALPHA = %4.4f\n" , ALPHA );
mexPrintf( "\tHyperparameter BETA = %4.4f\n" , BETA );
mexPrintf( "\tSeed number = %d\n" , SEED );
mexPrintf( "\tNumber of tokens = %d\n" , ntokens );
mexPrintf( "Internal Memory Allocation\n" );
mexPrintf( "\tw,d,z,order indices combined = %d bytes\n" , 4 * sizeof( int) * ntokens );
mexPrintf( "\twp (full) matrix = %d bytes\n" , sizeof( int ) * W * T );
mexPrintf( "\tdp (full) matrix = %d bytes\n" , sizeof( int ) * D * T );
//mexPrintf( "Checking: sizeof(int)=%d sizeof(long)=%d sizeof(double)=%d\n" , sizeof(int) , sizeof(long) , sizeof(double));
}
/* run the model */
GibbsSamplerLDA( ALPHA, BETA, W, T, D, NN, OUTPUT, n, z, d, w, wp, dp, ztot, order, probs, startcond );
/* convert the full wp matrix into a sparse matrix */
nzmaxwp = 0;
for (i=0; i<W; i++) {
for (j=0; j<T; j++)
nzmaxwp += (int) ( *( wp + j + i*T )) > 0;
}
/*if (OUTPUT==2) {
mexPrintf( "Constructing sparse output matrix wp\n" );
mexPrintf( "Number of nonzero entries for WP = %d\n" , nzmaxwp );
}*/
// MAKE THE WP SPARSE MATRIX
plhs[0] = mxCreateSparse( W,T,nzmaxwp,mxREAL);
srwp = mxGetPr(plhs[0]);
irwp = mxGetIr(plhs[0]);
jcwp = mxGetJc(plhs[0]);
n = 0;
for (j=0; j<T; j++) {
*( jcwp + j ) = n;
for (i=0; i<W; i++) {
c = (int) *( wp + i*T + j );
if (c >0) {
*( srwp + n ) = c;
*( irwp + n ) = i;
n++;
}
}
}
*( jcwp + T ) = n;
// MAKE THE DP SPARSE MATRIX
nzmaxdp = 0;
for (i=0; i<D; i++) {
for (j=0; j<T; j++)
nzmaxdp += (int) ( *( dp + j + i*T )) > 0;
}
/*if (OUTPUT==2) {
mexPrintf( "Constructing sparse output matrix dp\n" );
mexPrintf( "Number of nonzero entries for DP = %d\n" , nzmaxdp );
} */
plhs[1] = mxCreateSparse( D,T,nzmaxdp,mxREAL);
srdp = mxGetPr(plhs[1]);
irdp = mxGetIr(plhs[1]);
jcdp = mxGetJc(plhs[1]);
n = 0;
for (j=0; j<T; j++) {
*( jcdp + j ) = n;
for (i=0; i<D; i++) {
c = (int) *( dp + i*T + j );
if (c >0) {
*( srdp + n ) = c;
*( irdp + n ) = i;
n++;
}
}
}
*( jcdp + T ) = n;
plhs[ 2 ] = mxCreateDoubleMatrix( 1,ntokens , mxREAL );
Z = mxGetPr( plhs[ 2 ] );
for (i=0; i<ntokens; i++) Z[ i ] = (double) z[ i ] + 1;
}
