/*********************
void WtCDSample
Using the parameters contained in the array theta, obtain the
network statistics for a sample of size samplesize. burnin is the
initial number of Markov chain steps before sampling anything
and interval is the number of MC steps between successive
networks in the sample. Put all the sampled statistics into
the networkstatistics array.
*********************/
WtMCMCStatus WtCDSample(WtMHproposal *MHp,
double *theta, double *networkstatistics,
int samplesize, int *CDparams, Vertex *undotail, Vertex *undohead, double *undoweight, int fVerbose,
WtNetwork *nwp, WtModel *m, double *extraworkspace){
/*********************
networkstatistics are modified in groups of m->n_stats, and they
reflect the CHANGE in the values of the statistics from the
original (observed) network. Thus, when we begin, the initial
values of the first group of m->n_stats networkstatistics should
all be zero
*********************/
/*for (j=0; j < m->n_stats; j++) */
/* networkstatistics[j] = 0.0; */
/* Rprintf("\n"); */
/* for (j=0; j < m->n_stats; j++){ */
/* Rprintf("j %d %f\n",j,networkstatistics[j]); */
/* } */
/* Rprintf("\n"); */
int staken=0;
/* Now sample networks */
unsigned int i=0, sattempted=0;
while(i<samplesize){
if(WtCDStep(MHp, theta, networkstatistics, CDparams, &staken, undotail, undohead, undoweight,
fVerbose, nwp, m, extraworkspace)!=WtMCMC_OK)
return WtMCMC_MH_FAILED;
#ifdef Win32
if( ((100*i) % samplesize)==0 && samplesize > 500){
R_FlushConsole();
R_ProcessEvents();
}
#endif
networkstatistics += m->n_stats;
i++;
sattempted++;
}
if (fVerbose){
Rprintf("Sampler accepted %7.3f%% of %d proposed steps.\n",
staken*100.0/(1.0*sattempted*CDparams[0]), sattempted*CDparams[0]);
}
return WtMCMC_OK;
}
/*********************
void WtMCMCSample
Using the parameters contained in the array theta, obtain the
network statistics for a sample of size samplesize. burnin is the
initial number of Markov chain steps before sampling anything
and interval is the number of MC steps between successive
networks in the sample. Put all the sampled statistics into
the networkstatistics array.
*********************/
WtMCMCStatus WtCDSample(WtMHproposal *MHp,
double *theta, double *networkstatistics,
int samplesize, int nsteps, Vertex *undotail, Vertex *undohead, double *undoweight, int fVerbose,
WtNetwork *nwp, WtModel *m) {
int i, j;
/*********************
networkstatistics are modified in groups of m->n_stats, and they
reflect the CHANGE in the values of the statistics from the
original (observed) network. Thus, when we begin, the initial
values of the first group of m->n_stats networkstatistics should
all be zero
*********************/
/*for (j=0; j < m->n_stats; j++) */
/* networkstatistics[j] = 0.0; */
/* Rprintf("\n"); */
/* for (j=0; j < m->n_stats; j++){ */
/* Rprintf("j %d %f\n",j,networkstatistics[j]); */
/* } */
/* Rprintf("\n"); */
/* Now sample networks */
for (i=0; i < samplesize; i++){
if(WtCDStep(MHp, theta, networkstatistics, nsteps, undotail, undohead, undoweight,
fVerbose, nwp, m)!=WtMCMC_OK)
return WtMCMC_MH_FAILED;
#ifdef Win32
if( ((100*i) % samplesize)==0 && samplesize > 500){
R_FlushConsole();
R_ProcessEvents();
}
#endif
networkstatistics += m->n_stats;
}
return WtMCMC_OK;
}
