//only uses first sequence
int* ghmm_bayes_hmm_fbgibbs(ghmm_bayes_hmm *bayes, ghmm_cmodel *mo, ghmm_cseq* seq,
int burnIn, int seed){
#define CUR_PROC "ghmm_cmodel_fbgibbs"
//XXX seed
GHMM_RNG_SET (RNG, seed);
int max_seq = ghmm_cseq_max_len(seq);
double **alpha = ighmm_cmatrix_alloc(max_seq,mo->N);
double ***pmats = ighmm_cmatrix_3d_alloc(max_seq, mo->N, mo->N);
int **Q;
ARRAY_CALLOC(Q, seq->seq_number);
int seq_iter;
for(seq_iter = 0; seq_iter < seq->seq_number; seq_iter++){
ARRAY_CALLOC(Q[seq_iter], seq->seq_len[seq_iter]);
}
ghmm_sample_data data;
ghmm_alloc_sample_data(bayes, &data);
ghmm_clear_sample_data(&data, bayes);//XXX swap parameter
for(; burnIn > 0; burnIn--){
for(seq_iter = 0; seq_iter < seq->seq_number; seq_iter++){
ghmm_cmodel_fbgibbstep(mo,seq->seq[seq_iter],seq->seq_len[seq_iter], Q[seq_iter],
alpha, pmats, NULL);
ghmm_get_sample_data(&data, bayes, Q[seq_iter], seq->seq[seq_iter],
seq->seq_len[seq_iter]);
ghmm_update_model(mo, bayes, &data);
ghmm_clear_sample_data(&data, bayes);
}
}
ighmm_cmatrix_free(&alpha, max_seq);
ighmm_cmatrix_3d_free(&pmats, max_seq,mo->N);
return Q;
STOP:
return NULL; //XXX error handle
#undef CUR_PROC
}
ghmm_cseq *ghmm_sgenerate_extensions (ghmm_cmodel * smo, ghmm_cseq * sqd_short,
int seed, int global_len,
sgeneration_mode_t mode)
{
#define CUR_PROC "ghmm_sgenerate_extensions"
ghmm_cseq *sq = NULL;
int i, j, t, n, m, len = global_len, short_len, max_short_len = 0, up = 0;
#ifdef bausparkasse
int tilgphase = 0;
#endif
/* int *v_path = NULL; */
double log_p, *initial_distribution, **alpha, *scale, p, sum;
/* aicj */
int class = -1;
int pos;
/* TEMP */
if (mode == all_viterbi || mode == viterbi_viterbi || mode == viterbi_all) {
GHMM_LOG(LCONVERTED, "Error: mode not implemented yet\n");
goto STOP;
}
if (len <= 0)
/* no global length; model should have a final state */
len = (int) GHMM_MAX_SEQ_LEN;
max_short_len = ghmm_cseq_max_len (sqd_short);
/*---------------alloc-------------------------------------------------*/
sq = ghmm_cseq_calloc (sqd_short->seq_number);
if (!sq) {
GHMM_LOG_QUEUED(LCONVERTED);
goto STOP;
}
ARRAY_CALLOC (initial_distribution, smo->N);
/* is needed in cfoba_forward() */
alpha = ighmm_cmatrix_alloc (max_short_len, smo->N);
if (!alpha) {
GHMM_LOG_QUEUED(LCONVERTED);
goto STOP;
}
ARRAY_CALLOC (scale, max_short_len);
ghmm_rng_init ();
GHMM_RNG_SET (RNG, seed);
/*---------------main loop over all seqs-------------------------------*/
for (n = 0; n < sqd_short->seq_number; n++) {
ARRAY_CALLOC (sq->seq[n], len*(smo->dim));
short_len = sqd_short->seq_len[n];
if (len < short_len) {
GHMM_LOG(LCONVERTED, "Error: given sequence is too long\n");
goto STOP;
}
ghmm_cseq_copy (sq->seq[n], sqd_short->seq[n], short_len);
#ifdef GHMM_OBSOLETE
sq->seq_label[n] = sqd_short->seq_label[n];
#endif /* GHMM_OBSOLETE */
/* Initial distribution */
/* 1. Viterbi-state */
#if 0
/* wieder aktivieren, wenn ghmm_cmodel_viterbi realisiert */
if (mode == viterbi_all || mode == viterbi_viterbi) {
v_path = cviterbi (smo, sqd_short->seq[n], short_len, &log_p);
if (v_path[short_len - 1] < 0 || v_path[short_len - 1] >= smo->N) {
GHMM_LOG(LCONVERTED, "Warning:Error: from viterbi()\n");
sq->seq_len[n] = short_len;
m_realloc (sq->seq[n], short_len);
continue;
}
m_memset (initial_distribution, 0, smo->N);
initial_distribution[v_path[short_len - 1]] = 1.0; /* all other 0 */
m_free (v_path);
}
#endif
/* 2. Initial Distribution ???
Pi(i) = alpha_t(i)/P(O|lambda) */
if (mode == all_all || mode == all_viterbi) {
if (short_len > 0) {
if (ghmm_cmodel_forward (smo, sqd_short->seq[n], short_len, NULL /* ?? */ ,
alpha, scale, &log_p)) {
GHMM_LOG_QUEUED(LCONVERTED);
goto STOP;
}
sum = 0.0;
for (i = 0; i < smo->N; i++) {
/* alpha ist skaliert! */
initial_distribution[i] = alpha[short_len - 1][i];
sum += initial_distribution[i];
}
/* nicht ok.? auf eins skalieren? */
for (i = 0; i < smo->N; i++)
initial_distribution[i] /= sum;
}
else {
for (i = 0; i < smo->N; i++)
initial_distribution[i] = smo->s[i].pi;
}
}
/* if short_len > 0:
Initial state == final state from sqd_short; no output here
else
choose inittial state according to pi and do output
*/
p = GHMM_RNG_UNIFORM (RNG);
sum = 0.0;
for (i = 0; i < smo->N; i++) {
sum += initial_distribution[i];
if (sum >= p)
break;
}
/* error due to incorrect normalization ?? */
if (i == smo->N) {
i--;
while (i > 0 && initial_distribution[i] == 0.0)
i--;
}
t = 0;
pos = t * smo->dim;
if (short_len == 0) {
/* Output in state i */
p = GHMM_RNG_UNIFORM (RNG);
sum = 0.0;
for (m = 0; m < smo->M; m++) {
sum += smo->s[i].c[m];
if (sum >= p)
break;
}
/* error due to incorrect normalization ?? */
if (m == smo->M) {
m--;
while (m > 0 && smo->s[i].c[m] == 0.0)
m--;
}
ghmm_cmodel_get_random_var(smo, i, m, sq->seq[n]+pos);
if (smo->cos == 1) {
class = 0;
}
else {
if (!smo->class_change->get_class) {
printf ("ERROR: get_class not initialized\n");
goto STOP;
}
/*printf("1: cos = %d, k = %d, t = %d\n",smo->cos,smo->class_change->k,t);*/
class = smo->class_change->get_class (smo, sq->seq[n], n, t);
}
t++;
pos += smo->dim;
}
