double gauss()
{
static int iset = 0;
static double gset;
double fac, rsq, v1, v2;
seedrand();
if(iset == 0)
{
do
{
v1 = 2. * drand48() - 1.;
v2 = 2. * drand48() - 1.;
rsq = v1 * v1 + v2 * v2;
} while (rsq >= 1. || rsq == .0);
fac = sqrt(-2. * log(rsq) / rsq);
gset = v1 * fac;
iset = 1;
return v2 * fac;
}
else
{
iset = 0;
return gset;
}
}
int
nrand(int n)
{
if(randn == 0)
seedrand();
randn = randn*1103515245 + 12345 + sys->ticks;
return (randn>>16) % n;
}
int
nrand(int n)
{
if(randn == 0)
seedrand();
randn = randn*1103515245 + 12345 + osusectime();
return (randn>>16) % n;
}
int main(int argc, char **argv)
{
seedrand();
#ifdef __UL_UTIL__GAUSS
if(argc < 3)
{
fprintf(stderr, "Usage: gauss <a> <sigma> [n] \n");
exit(-1);
}
double a = atof(argv[1]), sigma = atof(argv[2]);
int n = 1, i;
if(argc > 3)
{
n = atoi(argv[3]);
}
for(i = 0; i < n; i++)
{
printf("%3.8f\n", a + sigma * gauss());
}
#elif defined(__UL_UTIL__IMF)
if(argc < 4 || argc % 2)
{
fprintf(stderr, "Usage: imf m_min m_max alpha0 [m_i alpha_i]* \n");
exit(-1);
}
int i, j, n = argc / 2 - 1;
double *m = (double *)malloc((n+1) * sizeof(double));
double *alpha = (double *)malloc(n * sizeof(double));
double *r = (double *)malloc(n * sizeof(double));
double *f = (double *)malloc((n+1) * sizeof(double));
m[0] = atof(argv[1]);
m[n] = atof(argv[2]);
alpha[0] = -atof(argv[3]);
for(i = 1; i < n; i++)
{
m[i] = atof(argv[2*i+2]);
alpha[i] = -atof(argv[2*i+3]);
}
setup_imf(m, alpha, n, r, f);
int d[] = {0, 0, 0, 0, 0, 0};
/*
for(i = 0; i < n; i++)
printf("f_%d(m) = %1.8f * m ^ %1.1f, F(%1.3f) = %1.8f, F(%1.3f) = %1.8f\n",
i, r[i], alpha[i], m[i], f[i], m[i+1], f[i+1]);
*/
seedrand();
for(j = 0; j < 1000000; j++)
{
double m_ = get_imf_mass(m, alpha, n, r, f);
printf("%e\n", m_);
}
#endif
exit(0);
}
void rjMcMC1DSampler::sample()
{
mBirthDeathFromPrior = false;
starttime = timestamp();
double t1 = gettime();
mChainInfo.resize(nchains);
for (size_t ci = 0; ci < nchains; ci++){
unsigned int seed = (unsigned int)(ci + mRank + (unsigned int)time(NULL));
seedrand(seed);
mChainInfo[ci].reset();
//mChainInfo[ci].modelchain.resize(nsamples);
rjMcMC1DModel mcur;
for (size_t si = 0; si < nsamples; si++){
//Initialis chain
if (si == 0){
mcur = choosefromprior();
set_misfit(mcur);
}
//Initialise "best" models
if (ci == 0 && si==0){
mHighestLikelihood = mcur;
mLowestMisfit = mcur;
}
rjMcMC1DModel mpro = mcur;
size_t nopt = 4;
if (mcur.nnuisances() > 0)nopt = 5;
size_t option = irand((size_t)0, nopt - 1);
bool accept = false;
if (option == 0){
accept = propose_valuechange(mcur, mpro);
}
else if (option == 1){
accept = propose_move(mcur, mpro);
}
else if (option == 2){
accept = propose_birth(mcur, mpro);
}
else if (option == 3){
accept = propose_death(mcur, mpro);
}
else if (option == 4){
accept=propose_nuisancechange(mcur,mpro);
}
else if (option == 5){
accept = propose_independent(mcur, mpro);
}
else{
exit(1);
break;
}
if (accept) mcur = mpro;
if (includeinmap(si)){
pmap.addmodel(mcur);
nmap.addmodel(mcur);
mChainInfo[ci].modelchain.push_back(mcur);
}
if (mcur.logppd() > mHighestLikelihood.logppd()){
mHighestLikelihood = mcur;
}
if (mcur.misfit() < mLowestMisfit.misfit()){
mLowestMisfit = mcur;
}
if (saveconvergencerecord(si)){
mChainInfo[ci].sample.push_back((uint32_t)si);
mChainInfo[ci].nlayers.push_back((uint32_t)mcur.nlayers());
mChainInfo[ci].misfit.push_back((float)mcur.misfit());
mChainInfo[ci].logppd.push_back((float)mcur.logppd());
mChainInfo[ci].ar_valuechange.push_back((float)ar_valuechange());
mChainInfo[ci].ar_move.push_back((float)ar_move());
mChainInfo[ci].ar_birth.push_back((float)ar_birth());
mChainInfo[ci].ar_death.push_back((float)ar_death());
mChainInfo[ci].ar_nuisancechange.push_back((float)ar_nuisancechange());
}
#ifdef _WIN32
if (reportstats){
if (mRank == 0 && isreportable(si)){
//printstats(ci, si, mcur.nlayers(), mcur.misfit() / (double)ndata);
}
}
#endif
}
}
double t2 = gettime();
endtime = timestamp();
samplingtime = t2 - t1;
}
