void SpacePlane::init(){ static bool initialized = false; if(!initialized){ sq_init(modPath() << _SC("models/SpacePlane.nut"), ModelScaleProcess(modelScale) <<= SingleDoubleProcess(hitRadius, _SC("hitRadius")) <<= MassProcess(defaultMass) <<= SingleDoubleProcess(maxHealthValue, _SC("maxhealth"), false) <<= Vec3dListProcess(engines, _SC("engines")) <<= DrawOverlayProcess(overlayDisp) ); initialized = true; } undocktime = 0.f; health = getMaxHealth(); mass = defaultMass; people = RandomSequence((unsigned long)this).next() % 100 + 100; engineHeat = 0.f; pf.resize(engines.size()); for(int i = 0; i < pf.size(); i++) pf[i] = NULL; }
void UHMMCalibrate::calibrateParallel(WorkPool_s *wpool, TaskStateInfo& si) { HMMERTaskLocalData *tls = getHMMERTaskLocalData(); struct alphabet_s *al = &tls->al; struct plan7_s *hmm = wpool->hmm; struct dpmatrix_s *mx = CreatePlan7Matrix(1, hmm->M, 25, 0); int len; float sc; char *seq; unsigned char *dsq; while(true) { /* generate a sequence */ { QMutexLocker locker(&wpool->lockInput); wpool->nseq++; if (wpool->nseq > wpool->nsample) { /* we're done; release input lock, break loop */ break; } if (wpool->fixedlen) { len = wpool->fixedlen; } else { do { len = (int) Gaussrandom(wpool->lenmean, wpool->lensd); } while (len < 1); } seq = RandomSequence(al->Alphabet, wpool->randomseq.data(), al->Alphabet_size, len); } /* compute score */ dsq = DigitizeSequence(seq, len); if (P7ViterbiSpaceOK(len, hmm->M, mx)) { sc = P7Viterbi(dsq, len, hmm, mx, NULL); } else { int pStub; sc = P7SmallViterbi(dsq, len, hmm, mx, NULL, pStub); } free(dsq); free(seq); /* save output */ QMutexLocker locker(&wpool->lockOutput); AddToHistogram(wpool->hist, sc); wpool->max_score = qMax(wpool->max_score, sc); si.progress = int(100*wpool->nseq/float(wpool->nsample)); //TODO: update progress for all tasks? if (wpool->progress!=NULL) { *wpool->progress = si.progress; } } FreePlan7Matrix(mx); }
/* Function: main_loop_serial() * Date: SRE, Tue Aug 18 16:18:28 1998 [St. Louis] * * Purpose: Given an HMM and parameters for synthesizing random * sequences; return a histogram of scores. * (Serial version) * * Args: hmm - an HMM to calibrate. * seed - random number seed * nsample - number of seqs to synthesize * lenmean - mean length of random sequence * lensd - std dev of random seq length * fixedlen - if nonzero, override lenmean, always this len * ret_hist - RETURN: the score histogram * ret_max - RETURN: highest score seen in simulation * * Returns: (void) * hist is alloc'ed here, and must be free'd by caller. */ static void main_loop_serial(struct plan7_s *hmm, int seed, int nsample, float lenmean, float lensd, int fixedlen, struct histogram_s **ret_hist, float *ret_max) { struct histogram_s *hist; float randomseq[MAXABET]; float p1; float max; char *seq; char *dsq; float score; int sqlen; int idx; /* Initialize. * We assume we've already set the alphabet (safe, because * HMM input sets the alphabet). */ sre_srandom(seed); P7Logoddsify(hmm, TRUE); P7DefaultNullModel(randomseq, &p1); hist = AllocHistogram(-200, 200, 100); max = -FLT_MAX; for (idx = 0; idx < nsample; idx++) { /* choose length of random sequence */ if (fixedlen) sqlen = fixedlen; else do sqlen = (int) Gaussrandom(lenmean, lensd); while (sqlen < 1); /* generate it */ seq = RandomSequence(Alphabet, randomseq, Alphabet_size, sqlen); dsq = DigitizeSequence(seq, sqlen); if (P7ViterbiSize(sqlen, hmm->M) <= RAMLIMIT) score = P7Viterbi(dsq, sqlen, hmm, NULL); else score = P7SmallViterbi(dsq, sqlen, hmm, NULL); AddToHistogram(hist, score); if (score > max) max = score; free(dsq); free(seq); } *ret_hist = hist; *ret_max = max; return; }
static void main_loop_serial(struct plan7_s *hmm, int seed, int nsample, float lenmean, float lensd, int fixedlen, struct histogram_s **ret_hist, float *ret_max, int& cancelFlag, int& progress) { struct histogram_s *hist; struct dpmatrix_s *mx; float randomseq[MAXABET]; float p1; float max; char *seq; unsigned char *dsq; float score; int sqlen; int idx; // Initialize. // We assume we've already set the alphabet (safe, because // HMM input sets the alphabet). sre_srandom(seed); //get HMMERTaskLocalData HMMERTaskLocalData *tls = getHMMERTaskLocalData(); alphabet_s &al = tls->al; SetAlphabet(hmm->atype); P7Logoddsify(hmm, TRUE); P7DefaultNullModel(randomseq, &p1); hist = AllocHistogram(-200, 200, 100); mx = CreatePlan7Matrix(1, hmm->M, 25, 0); max = -FLT_MAX; progress = 0; int pStub; for (idx = 0; idx < nsample && !cancelFlag; idx++) { // choose length of random sequence if (fixedlen) { sqlen = fixedlen; } else { do sqlen = (int) Gaussrandom(lenmean, lensd); while (sqlen < 1); } // generate it seq = RandomSequence(al.Alphabet, randomseq, al.Alphabet_size, sqlen); dsq = DigitizeSequence(seq, sqlen); if (P7ViterbiSpaceOK(sqlen, hmm->M, mx)) { score = P7Viterbi(dsq, sqlen, hmm, mx, NULL); } else { score = P7SmallViterbi(dsq, sqlen, hmm, mx, NULL, pStub); } AddToHistogram(hist, score); max = qMax(score, max); progress = int(100*idx/float(nsample)); free(dsq); free(seq); } FreePlan7Matrix(mx); *ret_hist = hist; *ret_max = max; }
int main(void) { int master_tid; /* PVM TID of our master */ int slaveidx; /* my slave index (0..nslaves-1) */ struct plan7_s *hmm; /* HMM to calibrate, sent from master */ struct histogram_s *hist; /* score histogram */ int hmmidx; /* index of this HMM */ char *seq; /* synthetic random sequence */ char *dsq; /* digitized seq */ int len; /* length of seq */ float sc; /* score of seq aligned to HMM */ float max; /* maximum score seen in sample */ int seed; /* random number seed */ int nsample; /* number of seqs to sample */ int fixedlen; /* if nonzero, fixed length of seq */ float lenmean; /* Gaussian mean length of seq */ float lensd; /* Gaussian length std. dev. for seq */ int fitok; /* TRUE if EVD fit was OK */ float randomseq[MAXABET]; /* iid frequencies of residues */ float p1; int alphatype; /* alphabet type, hmmAMINO or hmmNUCLEIC */ int idx; int code; /* Register leave_pvm() cleanup function so any exit() call * first calls pvm_exit(). */ if (atexit(leave_pvm) != 0) { pvm_exit(); Die("slave couldn't register leave_pvm()"); } /***************************************************************** * initialization. * Master broadcasts the problem to us: parameters of the * HMM calibration. ******************************************************************/ master_tid = pvm_parent(); /* who's our master? */ pvm_recv(master_tid, HMMPVM_INIT); pvm_upkint(&nsample, 1, 1); pvm_upkint(&fixedlen, 1, 1); pvm_upkfloat(&lenmean, 1, 1); pvm_upkfloat(&lensd, 1, 1); /* tell the master we're OK and ready to go (or not) */ code = HMMPVM_OK; pvm_initsend(PvmDataDefault); pvm_pkint(&code, 1, 1); pvm_send(master_tid, HMMPVM_RESULTS); /***************************************************************** * Main loop. * Receive a random number seed, then an HMM to search against. * If we receive a -1 seed, we shut down. *****************************************************************/ slaveidx = -1; for (;;) { pvm_recv(master_tid, HMMPVM_WORK); pvm_upkint(&seed, 1, 1); if (seed == -1) break; /* shutdown signal */ pvm_upkint(&hmmidx, 1, 1); pvm_upkint(&alphatype,1, 1); SetAlphabet(alphatype); hmm = PVMUnpackHMM(); if (hmm == NULL) Die("oh no, the HMM never arrived"); if (slaveidx == -1) slaveidx = hmmidx; P7DefaultNullModel(randomseq, &p1); sre_srandom(seed); P7Logoddsify(hmm, TRUE); hist = AllocHistogram(-200, 200, 100); max = -FLT_MAX; for (idx = 0; idx < nsample; idx++) { /* choose length of random sequence */ if (fixedlen) len = fixedlen; else do len = (int) Gaussrandom(lenmean, lensd); while (len < 1); /* generate it */ seq = RandomSequence(Alphabet, randomseq, Alphabet_size, len); dsq = DigitizeSequence(seq, len); if (P7ViterbiSize(len, hmm->M) <= RAMLIMIT) sc = P7Viterbi(dsq, len, hmm, NULL); else sc = P7SmallViterbi(dsq, len, hmm, NULL); AddToHistogram(hist, sc); if (sc > max) max = sc; free(seq); free(dsq); } /* Fit an EVD to the observed histogram. * The TRUE left-censors and fits only the right slope of the histogram. * The 9999. is an arbitrary high number that means we won't trim outliers * on the right. */ fitok = ExtremeValueFitHistogram(hist, TRUE, 9999.); /* Return output to master. * Currently we don't send the histogram back, but we could. */ pvm_initsend(PvmDataDefault); pvm_pkint(&slaveidx, 1, 1); pvm_pkint(&hmmidx, 1, 1); PVMPackString(hmm->name); pvm_pkint(&fitok, 1, 1); pvm_pkfloat(&(hist->param[EVD_MU]), 1, 1); pvm_pkfloat(&(hist->param[EVD_LAMBDA]), 1, 1); pvm_pkfloat(&max, 1, 1); pvm_send(master_tid, HMMPVM_RESULTS); /* cleanup */ FreeHistogram(hist); FreePlan7(hmm); } /*********************************************** * Cleanup, return. ***********************************************/ return 0; /* pvm_exit() is called by atexit() registration. */ }
/* Function: worker_thread() * Date: SRE, Thu Jul 16 10:41:02 1998 [St. Louis] * * Purpose: The procedure executed by the worker threads. * * Args: ptr - (void *) that is recast to a pointer to * the workpool. * * Returns: (void *) */ void * worker_thread(void *ptr) { struct plan7_s *hmm; struct workpool_s *wpool; char *seq; char *dsq; int len; float sc; int rtn; Stopwatch_t thread_watch; StopwatchStart(&thread_watch); wpool = (struct workpool_s *) ptr; hmm = wpool->hmm; for (;;) { /* 1. Synthesize a random sequence. * The input sequence number is a shared resource, * and sre_random() isn't thread-safe, so protect * the whole section with mutex. */ /* acquire a lock */ if ((rtn = pthread_mutex_lock(&(wpool->input_lock))) != 0) Die("pthread_mutex_lock failure: %s\n", strerror(rtn)); /* generate a sequence */ wpool->nseq++; if (wpool->nseq > wpool->nsample) { /* we're done; release input lock, break loop */ if ((rtn = pthread_mutex_unlock(&(wpool->input_lock))) != 0) Die("pthread_mutex_unlock failure: %s\n", strerror(rtn)); break; } if (wpool->fixedlen) len = wpool->fixedlen; else do len = (int) Gaussrandom(wpool->lenmean, wpool->lensd); while (len < 1); seq = RandomSequence(Alphabet, wpool->randomseq, Alphabet_size, len); /* release the lock */ if ((rtn = pthread_mutex_unlock(&(wpool->input_lock))) != 0) Die("pthread_mutex_unlock failure: %s\n", strerror(rtn)); /* 2. Score the sequence against the model. */ dsq = DigitizeSequence(seq, len); if (P7ViterbiSize(len, hmm->M) <= RAMLIMIT) sc = P7Viterbi(dsq, len, hmm, NULL); else sc = P7SmallViterbi(dsq, len, hmm, NULL); free(dsq); free(seq); /* 3. Save the output; hist and max_score are shared, * so protect this section with the output mutex. */ /* acquire lock on the output queue */ if ((rtn = pthread_mutex_lock(&(wpool->output_lock))) != 0) Die("pthread_mutex_lock failure: %s\n", strerror(rtn)); /* save output */ AddToHistogram(wpool->hist, sc); if (sc > wpool->max_score) wpool->max_score = sc; /* release our lock */ if ((rtn = pthread_mutex_unlock(&(wpool->output_lock))) != 0) Die("pthread_mutex_unlock failure: %s\n", strerror(rtn)); } StopwatchStop(&thread_watch); /* acquire lock on the output queue */ if ((rtn = pthread_mutex_lock(&(wpool->output_lock))) != 0) Die("pthread_mutex_lock failure: %s\n", strerror(rtn)); /* accumulate cpu time into main stopwatch */ StopwatchInclude(&(wpool->watch), &thread_watch); /* release our lock */ if ((rtn = pthread_mutex_unlock(&(wpool->output_lock))) != 0) Die("pthread_mutex_unlock failure: %s\n", strerror(rtn)); pthread_exit(NULL); return NULL; /* solely to silence compiler warnings */ }
int main(int argc, char *argv[]) { struct sigaction sig; int StationSeq[SENSOR_MAX_NUM]; int sfd, maxWait, i, j, rand; int anzSensors; char buf[BUF_SIZE]; SensorData sensor; float deltaT; float tempPreset[8] = {20, 45, 30, 20, 15, 10, 15, 20}; float startup[8] = {0, 0, 0, 0, 0, 0, 0, 0}; int sequenceNr[8] = {0, 0, 0, 0, 0, 0, 0, 0}; //*** check for hostname ... a kind of hack if (argc < 4) { printf("Need number of devices, hostname or IP address and port number\n"); exit(-1); } if ((anzSensors = numOfSensors(atoi(argv[1]))) < 0) { printf("\n*** invalid number of sensor devices ***\n\n"); exit(0); } // set up signal handlers sigemptyset(&sig.sa_mask); sig.sa_handler = SignalHandler; sig.sa_flags = 0; sigaction(SIGTERM, &sig, NULL); sigaction(SIGKILL, &sig, NULL); sigaction(SIGINT, &sig, NULL); sleep(2); printf("Sensor device starting up\n"); globalK = 0; while (globalK < MAX_ITERATIONS) { RandomSequence(StationSeq, anzSensors); for (i = 0; i < anzSensors; i++) { // for all devices deltaT = intRand(-2, 2); sensor.deviceID = StationSeq[i]; sensor.sequenceNr = sequenceNr[sensor.deviceID]; sensor.valIS = deltaT + startup[sensor.deviceID]; sensor.valREF = tempPreset[sensor.deviceID]; sensor.status = 0; sequenceNr[sensor.deviceID]++; sfd = connToServer(argv[2], atoi(argv[3])); write(sfd, (char *)&sensor,sizeof(SensorData)); close(sfd); maxWait = 4000000; maxWait = maxWait / anzSensors; rand = intRand(maxWait/3, maxWait); usleep(rand); } for (j = 0; j < anzSensors; j++) { if (startup[j] < tempPreset[j]) startup[j] += 2; else startup[j] = tempPreset[j]; } globalK++; } exit(0); } // end main