void AlexSim::writeHist(const QString filename) const
{
long ii;
long nbins=(long)((t-tStart)/burstDuration*10);
if(nbins==0||photons.size()==0) qWarning()<<"writeHist: no photon records ";
gsl_histogram * histDonor = gsl_histogram_alloc (nbins);
gsl_histogram_set_ranges_uniform (histDonor, tStart, t); // change t to tEnd if the latter is implemented
gsl_histogram * histAcceptor = gsl_histogram_alloc (nbins);
gsl_histogram_set_ranges_uniform (histAcceptor, tStart, t); // change t to tEnd if the latter is implemented
for (ii=0;ii<photons.size();ii++) {
#ifdef PHOTONMACRO
if(isChannel(photons.at(ii),DonorEm)) gsl_histogram_increment (histDonor, photons.at(ii).time);
#else
if(photons.at(ii).isChannel(DonorEm)) gsl_histogram_increment (histDonor, photons.at(ii).time);
#endif
else gsl_histogram_increment (histAcceptor, photons.at(ii).time);
}
QFile file(filename);
if(!file.open(QIODevice::WriteOnly | QIODevice::Text)) QMessageBox::warning(0, "error", file.errorString());
QTextStream out(&file);
out <<"# Simulation data. photon count over time. parameters are:\n";
out <<"# rateDonor="<<rateDemDex<<"\trateAcceptor="<<rateAemAex<<"\trateBackground="<<rateBackground<<"\tburstDuration="<<burstDuration<<"\tsigma="<<sigma<<"\ttStart="<<tStart<<"\ttEnd="<<tEnd()<<"\n";
out.setRealNumberPrecision(11);
out <<"# time in ms \tdonor channel \tacceptor channel\n";
for(ii=0;ii<histDonor->n;ii++) {
out << histDonor->range[ii]*1e3 << "\t" << gsl_histogram_get(histDonor,ii) << "\t" << gsl_histogram_get(histAcceptor,ii) << "\n";
}
file.close();
gsl_histogram_free (histDonor);
gsl_histogram_free (histAcceptor);
qDebug()<<nbins<<"histogram entries written to file "<<filename;
}
void average_bin(double* array_x, double* array_y, double* bins,
double* binned_array, double *error_array, int bin_size, int array_size)
{
#ifdef PRINT_INFO
fprintf(stdout, "\nBinning and averaging into %d bins an array of size:%d...", bin_size, array_size);
#endif
int i=0, j=0;
gsl_histogram *h = gsl_histogram_alloc (bin_size-1);
gsl_histogram *g = gsl_histogram_alloc (bin_size-1);
gsl_histogram_set_ranges (h, bins, bin_size);
gsl_histogram_set_ranges (g, bins, bin_size);
for(i=0; i<array_size; i++)
{
gsl_histogram_increment (h, array_x[i]);
gsl_histogram_accumulate (g, array_x[i], array_y[i]);
}
for(j=0; j<bin_size-1; j++)
{
binned_array[j] = g->bin[j]/h->bin[j];
if(h->bin[j]>0) // Assuming poissonian error
error_array[j] = g->bin[j] / sqrt(h->bin[j]);
}
gsl_histogram_free(h);
gsl_histogram_free(g);
}
void QwtHistogram::loadDataFromMatrix() {
if (!d_matrix)
return;
int size = d_matrix->numRows() * d_matrix->numCols();
const double *data = d_matrix->matrixModel()->dataVector();
int n;
gsl_histogram *h;
if (d_autoBin) {
double min, max;
d_matrix->range(&min, &max);
d_begin = floor(min);
d_end = ceil(max);
d_bin_size = 1.0;
n = static_cast<int>(floor((d_end - d_begin) / d_bin_size));
if (!n)
return;
h = gsl_histogram_alloc(n);
if (!h)
return;
gsl_histogram_set_ranges_uniform(h, floor(min), ceil(max));
} else {
n = static_cast<int>((d_end - d_begin) / d_bin_size + 1);
if (!n)
return;
h = gsl_histogram_alloc(n);
if (!h)
return;
double *range = new double[n + 2];
for (int i = 0; i <= n + 1; i++)
range[i] = d_begin + i * d_bin_size;
gsl_histogram_set_ranges(h, range, n + 1);
delete[] range;
}
for (int i = 0; i < size; i++)
gsl_histogram_increment(h, data[i]);
QVarLengthArray<double> X(n), Y(n); // stores ranges (x) and bins (y)
for (int i = 0; i < n; i++) {
Y[i] = gsl_histogram_get(h, i);
double lower, upper;
gsl_histogram_get_range(h, i, &lower, &upper);
X[i] = lower;
}
setData(X.data(), Y.data(), n);
d_mean = gsl_histogram_mean(h);
d_standard_deviation = gsl_histogram_sigma(h);
d_min = gsl_histogram_min_val(h);
d_max = gsl_histogram_max_val(h);
gsl_histogram_free(h);
}
bool myHistogram::Convert(vector<double> &x)
{
gsl_histogram *r;
size_t n=x.size();
if(n<=2) return false;
double *res;
res=new double[n];
size_t i;
for(i=0;i<n;i++) res[i]=x[i];
double std=gsl_stats_sd(res,1,n);
double bin=3.49*std/pow(n*1.0,1.0/3);//Scott's ruler
if(bin<=0)
{
delete []res;
return false;
}
double a=gsl_stats_min(res,1,n);
double b=gsl_stats_max(res,1,n);
int num=(int)((b-a)/bin);
r=gsl_histogram_alloc(num);
gsl_histogram_set_ranges_uniform(r,a,b);
for(i=0;i<n;i++)
{
gsl_histogram_increment(r,res[i]);
}
Convert(r,n);
gsl_histogram_free(r);
delete []res;
return true;
}
gsl_histogram * calc_hist(const gsl_vector * v, int nbins) {
double max;
double min;
unsigned int i;
double binwidth;
double sum = 0;
double val;
gsl_histogram * h;
gsl_vector_minmax(v, &min, &max);
binwidth = (max - min) / nbins;
dump_d("min", min);
dump_d("max", max);
debug("allocating the histogram");
h = gsl_histogram_alloc(v->size);
debug("setting range");
require(gsl_histogram_set_ranges_uniform (h, min, max));
/* with out the following, the max element doesn't fall in the last bin */
h->range[h->n] += 1;
debug("summing up");
for (i = 0; i < v->size; i++) {
val = gsl_vector_get(v, i);
sum += val;
require(gsl_histogram_increment (h, val));
}
debug("scaling");
/* double gsl_histogram_sum (const gsl_histogram * h) */
require(gsl_histogram_scale (h, 1/sum));
debug("done");
return h;
}
// receive vector<vector<unsigned int>> representing a list of tuples
// these tuples have pairs of particleTypeIds which should be considered
// in rdf calculation.
RadialDistribution::RadialDistribution(
std::vector<double>& range,
bool isPeriodic,
double boxsize,
std::vector< std::vector<unsigned int> > considered,
std::string inFilename)
{
this->recPeriod = 1;
this->clearPeriod = 0;
this->filename = inFilename;
this->isPeriodic = isPeriodic;
this->boxsize = boxsize;
this->numberOfBins = range.size() - 1;
this->radialDistribution = gsl_histogram_alloc(this->numberOfBins);
this->rangeOfBins = range;
const double * cRange = &range[0];
gsl_histogram_set_ranges(this->radialDistribution, cRange, range.size());
// calculate centers of bins
double center;
for (int i=0; i < (rangeOfBins.size() - 1) ; i++) {
center = 0.5 * ( rangeOfBins[i] + rangeOfBins[i+1] );
this->binCenters.push_back(center);
this->bins.push_back(0.);
}
this->consideredPairs = considered;
}
int main(void) {
struct data ntuple_row;
gsl_ntuple *ntuple
= gsl_ntuple_open ("test.dat", &ntuple_row,
sizeof (ntuple_row));
double lower = 1.5;
gsl_ntuple_select_fn S;
gsl_ntuple_value_fn V;
gsl_histogram *h = gsl_histogram_alloc (100);
gsl_histogram_set_ranges_uniform(h, 0.0, 10.0);
S.function = &sel_func;
S.params = &lower;
V.function = &val_func;
V.params = 0;
gsl_ntuple_project (h, ntuple, &V, &S);
gsl_histogram_fprintf (stdout, h, "%f", "%f");
gsl_histogram_free (h);
gsl_ntuple_close (ntuple);
return 0;
}
int histc(double *data, int length, double *xmesh, int n , double *bins)
{
XML_IN;
printf("-1\n");
gsl_histogram * h = gsl_histogram_alloc(n-1);
printf("0\n");
gsl_histogram_set_ranges (h, xmesh, n);
double h_max = gsl_histogram_max(h);
double h_min = gsl_histogram_min(h);
printf("h_min: %g h_max: %g\n",h_min,h_max);
for (int i=0; i<length; i++)
gsl_histogram_increment (h, data[i]);
printf("2\n");
for (int i=0;i<n-1;i++)
bins[i] = gsl_histogram_get (h, i);
printf("3\n");
gsl_histogram_fprintf (stdout, h, "%g", "%g");
/*...*/
gsl_histogram_free(h);
XML_OUT;
return 0;
}
gsl_histogram *
gsl_histogram_calloc (size_t n)
{
gsl_histogram * h = gsl_histogram_alloc (n);
if (h == 0)
{
return h;
}
{
size_t i;
for (i = 0; i < n + 1; i++)
{
h->range[i] = i;
}
for (i = 0; i < n; i++)
{
h->bin[i] = 0;
}
}
h->n = n;
return h;
}
//calls the Point(int) constructor, creating Point object parameters, before calling MCMC's
MCMC::MCMC() : parameters(DIMENSION), proposal_mean(DIMENSION,0.0), proposal_var(DIMENSION,PROPOSAL_VAR) {
rng = gsl_rng_alloc(gsl_rng_ranlxs0); //assigning a RNG to an MCMC object
simulationLength = 5000000;
accepts = 0;
rejects = 0;
bin_num = 50;
range_min = 0;
range_max = 5.0;
thin_factor = 25;
h = gsl_histogram_alloc(bin_num);
gsl_histogram_set_ranges_uniform(h, range_min, range_max);
bin_num_X = 50;
bin_num_Y = 50;
X_min = 0;
X_max = 2;
Y_min = 0;
Y_max = 2;
h2d = gsl_histogram2d_alloc (bin_num_X, bin_num_Y);
gsl_histogram2d_set_ranges_uniform (h2d, X_min, X_max, Y_min, Y_max);
}
//Overloaded Constructors
population::population(int N_in, int L_in, double r_in, int seed_in, gsl_rng* rng_in) { //Neutral Evolution!
try {
if (r_in < 0 || r_in > 1 || N_in < 0 || L_in <0) {throw "Bad inputs. Check arguments.";}
else {
N = N_in;
L = L_in;
r = r_in;
gen_pop = 0;
neutral = true;
avgFit = 0;
selective_weight = vector<double>(N); //All zeros
genetic_weight = vector< vector<int> >(N,vector<int>(L));
fixations = vector< vector<fixation_event> > (N);
seed = seed_in ? seed_in:get_random_seed();
rng = rng_in;
gsl_rng_set(rng,seed);
blockHist = gsl_histogram_alloc(L);
gsl_histogram_set_ranges_uniform(blockHist,1,L+1);
for(int i=0;i<N;i++) {
pop.push_back(genome(i,L,rng));
}
updateBlockSizes();
}
}
catch(const char* Message) {cout << "Error: " << Message << "\n";}
}
population::population(int N_in, int L_in, double r_in, int seed_in, gsl_rng* rng_in, vector< vector<double> >& fit) {
try {
if (fit.size() != N_in || fit[0].size() != L_in) {throw "Incorrect Fitness Landscape dimensions!";}
else if (r_in < 0 || r_in > 1 || N_in < 0 || L_in <0) {throw "Bad inputs. Check arguments.";}
else {
N = N_in;
L = L_in;
r = r_in;
gen_pop = 0;
neutral = false;
avgFit = 0;
selective_weight = vector<double>(N);
genetic_weight = vector< vector<int> >(N,vector<int>(L));
fixations = vector< vector<fixation_event> > (N);
seed = seed_in ? seed_in : get_random_seed();
rng = rng_in;
gsl_rng_set(rng,seed);
blockHist = gsl_histogram_alloc(L);
gsl_histogram_set_ranges_uniform(blockHist,1,L+1); //Questionable range choice. As it stands now, the bins are partitioned as follows {[1,2),[2,3)......[L,L+1)}. Thus if all have length L, then average will come out to be (L+.5). Will have to rescale.
map<int,double> genome_fit;
for(int i=0;i<N;i++) {
genome_fit = convert_vector_toMap(fit[i]);
if (!genome_fit.empty()) {pop.push_back(genome(i, L, rng, genome_fit));}
else {pop.push_back(genome(i,L,rng));}
avgFit += pop[i].get_fit();
}
avgFit/=N;
update_selection_weights();
updateBlockSizes();
}
}
catch (const char* Message) {
cout << "Error:" << Message << "\n";
}
}
/* Histogram a PETSC vector
*
* x is the vector
* nbins -- number of bins
* xmin, xmax -- histogram xmin, xmax -- assume uniform bins
* hh -- output vector -- assumed to be defined.
*/
void VecHist(const Vec& x, int nbins, double xmin, double xmax, vector<double>& hh) {
gsl_histogram *h1;
double *_x, x1;
PetscInt lo, hi;
vector<double> tmp(nbins);
// Set up the histogram struct
h1 = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(h1, xmin, xmax);
// Get the array
VecGetOwnershipRange(x, &lo, &hi);
hi -= lo;
VecGetArray(x, &_x);
for (PetscInt ii=0; ii < hi; ++ii) {
x1 = _x[ii];
if (x1 < xmin) x1 = xmin;
if (x1 >= xmax) x1 = xmax - 1.e-10;
gsl_histogram_increment(h1, x1);
}
VecRestoreArray(x, &_x);
// Fill the temporary output vector
for (int ii =0; ii<nbins; ++ii)
tmp[ii] = gsl_histogram_get(h1, ii);
// MPI Allreduce
MPI_Allreduce(&tmp[0], &hh[0], nbins, MPI_DOUBLE, MPI_SUM, PETSC_COMM_WORLD);
// Clean up
gsl_histogram_free(h1);
}
void AlexSim::simTestLognormal()
{
int n=10000; // number of samples
int nbins=100; // number of bins for the histogram
QFile file("./AlexSimTestLognormal.txt");
if(!file.open(QIODevice::WriteOnly | QIODevice::Text)) QMessageBox::information(0, "error", file.errorString());
QTextStream out(&file);
out <<"# Test lognormal distribution. Parameters are: burstDuration="<<burstDuration<<"\tvariance="<<burstDurationVar<<"\n";
out <<"# burst duration in ms\tfrequency\n";
out.setRealNumberPrecision(11);
gsl_histogram * hist = gsl_histogram_alloc (nbins);
gsl_histogram_set_ranges_uniform (hist, 0, 10*burstDuration);
for (int ii=0;ii<n;ii++) {
gsl_histogram_increment (hist,gsl_ran_lognormal(r,mu,sigma));
}
for(unsigned int ii=0;ii<hist->n;ii++) {
out << hist->range[ii]*1e3 << "\t" << gsl_histogram_get(hist,ii) << "\n";
}
file.close();
gsl_histogram_free (hist);
}
/* ==== */
static gsl_histogram *
ini_histogram_uniform(const int n,
const double min,
const double max)
{
gsl_histogram *a = gsl_histogram_alloc(n);
gsl_histogram_set_ranges_uniform(a,min,max);
return a;
}
gsl_histogram *AlexData::burstRateDistribution(size_t nbins)
{
gsl_histogram *hist = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(hist,burstSearchParamsGlobal.MinBurstrate*1e-3,burstSearchParamsGlobal.MaxBurstrate*1e-3);
for(int i=0;i<burstVectorDual.size();++i)
gsl_histogram_increment(hist, burstVectorDual.at(i).burstrate()*1e-3);
return hist;
}
gsl_histogram * create_hist(int nbins, double min, double max) {
gsl_histogram * h;
h = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(h, min, max);
/* with out the following, the max element doesn't fall in the last bin */
h->range[h->n] += (max - min) / 10000;
return h;
}
gsl_histogram *AlexData::burstDurationDistribution(size_t nbins)
{
gsl_histogram *hist = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(hist,0,burstSearchParamsGlobal.MaxDuration*1e3);
for(int i=0;i<burstVectorDual.size();++i)
gsl_histogram_increment(hist, burstVectorDual.at(i).duration*1e3);
return hist;
}
void QwtHistogram::initData(double *Y, int size)
{
if(size<2 || (size == 2 && Y[0] == Y[1]))
{//non valid histogram data
double x[2], y[2];
for (int i = 0; i<2; i++ ){
y[i] = 0;
x[i] = 0;
}
setData(x, y, 2);
return;
}
int n = 10;//default value
QVarLengthArray<double> x(n), y(n);//double x[n], y[n]; //store ranges (x) and bins (y)
gsl_histogram * h = gsl_histogram_alloc (n);
if (!h)
return;
gsl_vector *v;
v = gsl_vector_alloc (size);
for (int i = 0; i<size; i++ )
gsl_vector_set (v, i, Y[i]);
double min, max;
gsl_vector_minmax (v, &min, &max);
gsl_vector_free (v);
d_begin = floor(min);
d_end = ceil(max);
gsl_histogram_set_ranges_uniform (h, floor(min), ceil(max));
for (int i = 0; i<size; i++ )
gsl_histogram_increment (h, Y[i]);
for (int i = 0; i<n; i++ ){
y[i] = gsl_histogram_get (h, i);
double lower, upper;
gsl_histogram_get_range (h, i, &lower, &upper);
x[i] = lower;
}
setData(x.data(), y.data(), n);//setData(x, y, n);
d_bin_size = (d_end - d_begin)/(double)n;
d_autoBin = true;
d_mean = gsl_histogram_mean(h);
d_standard_deviation = gsl_histogram_sigma(h);
d_min = gsl_histogram_min_val(h);
d_max = gsl_histogram_max_val(h);
gsl_histogram_free (h);
}
int
main (int argc, char **argv)
{
double a = 0.0, b = 1.0;
size_t n = 10;
if (argc != 3 && argc !=4)
{
printf ("Usage: gsl-histogram xmin xmax [n]\n");
printf (
"Computes a histogram of the data on stdin using n bins from xmin to xmax.\n"
"If n is unspecified then bins of integer width are used.\n");
exit (0);
}
a = atof (argv[1]);
b = atof (argv[2]);
if (argc == 4)
{
n = atoi (argv[3]);
}
else
{
n = (int)(b - a) ;
}
{
double x;
gsl_histogram *h = gsl_histogram_alloc (n);
gsl_histogram_set_ranges_uniform (h, a, b);
while (fscanf(stdin, "%lg", &x) == 1)
{
gsl_histogram_increment(h, x);
}
#ifdef DISPLAY_STATS
{
double mean = gsl_histogram_mean (h);
double sigma = gsl_histogram_sigma (h);
fprintf (stdout, "# mean = %g\n", mean);
fprintf (stdout, "# sigma = %g\n", sigma);
}
#endif
gsl_histogram_fprintf (stdout, h, "%g", "%g");
gsl_histogram_free (h);
}
return 0;
}
gsl_histogram* population::get_cumulant_fit_hist(int l, double sigma) {
//Initialize histogram.
gsl_histogram* fit_hist = gsl_histogram_alloc(1000); //Think more about bin size.
gsl_histogram_set_ranges_uniform(fit_hist, -10*l*sigma, 10*l*sigma);
for (int n=0; n<N; n++) { //Iterate over the entire population.
for (int i=0; i<L-l; i+l/2) { //Center Locus @ i+l/2
gsl_histogram_increment(fit_hist,pop[n].sub_cumulant_fit(i,l)); //Histogram delta_f values.
}
}
return fit_hist;
}
gsl_histogram *AlexData::burstSizeDistribution(size_t nbins, double maxBurstSize)
{
if(maxBurstSize==0) maxBurstSize = burstSearchParamsGlobal.MaxBurstrate*burstSearchParamsGlobal.MaxDuration;
gsl_histogram *hist = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(hist,burstSearchParamsGlobal.MinBurstSize,maxBurstSize);
for(int i=0;i<burstVectorDual.size();++i)
gsl_histogram_increment(hist, burstVectorDual.at(i).numberOfPhotons);
return hist;
}
void DistToPA(gsl_histogram * h, double mag, double sigma)
{
double m1 = 0.5*mag + 0.5;
double s1 = 0.25*sigma;
double n1 = m1*(1. - m1)/s1 - 1.;
double a1 = m1*n1;
double b1 = (1. - m1)*n1;
for (int pa = 1; pa < 8; pa++) {
char line[80];
double x;
double data[6000];
int size = 0;
int nbins = h->n;
gsl_histogram * hpa = gsl_histogram_alloc( nbins);
gsl_histogram_set_ranges_uniform( hpa, 0.0, 1.0);
char fname[50];
sprintf(fname,"/home/jonatas/mzanlz/mZ_pa%d.dat",pa);
FILE * fp;
fp = fopen(fname,"rt");
while(fgets(line,80,fp) != NULL){
x = atof(line);
size++;
data[size] = x;
gsl_histogram_increment( hpa, x);
}
double m2 = 0.5*gsl_stats_mean( data, 1, size ) + 0.5;
double s2 = 0.25*gsl_stats_variance( data, 1, size );
double n2 = m2*(1. - m2)/s2 - 1.;
double a2 = m2*n2;
double b2 = (1. - m2)*n2;
NormalizaGSLHistograma( hpa );
//char hname[100];
//sprintf(hname,"pa%d",pa);
//PrintGSLHistogram( hpa, hname );
gsl_histogram_sub( hpa, h);
double D = 0;
for (size_t i = 0; i < nbins; i++) {
D += gsl_histogram_get( hpa , i )*gsl_histogram_get( hpa , i );
}
// printf("%g %g ", sqrt(D), KLbetas(a1,b1,a2,b2));
fclose(fp);
gsl_histogram_free( hpa );
}
}
static gsl_histogram *new_hist()
{
gsl_histogram *h;
/* allocate bins and set ranges uniformally */
h = gsl_histogram_alloc(N_BINS);
gsl_histogram_set_ranges_uniform(h,0,N_BINS*BINS_SEP);
/* last bin should hold everything greater
* than (N_BINS-1)*BINS_SEP */
h->range[h->n] = DBL_MAX;
return h;
}
size_t histogram (size_t N, double *data, size_t nbins, double bin_min, double bin_max, gsl_histogram **hist) {
size_t i;
/* prepare the gsl_histogram structure */
*hist = gsl_histogram_alloc (nbins);
gsl_histogram_set_ranges_uniform (*hist, bin_min, bin_max);
/* populate the bins in the histogram */
for (i=0; i<N; i++)
gsl_histogram_increment (*hist, data [i]);
/* success */
return MYLIB_SUCCESS;
}
/* Number the entries per bin in a given array */
void lin_bin(double* array, double* bins, int bin_size, int array_size, int* binned_array)
{
int i=0, j=0;
#ifdef PRINT_INFO
fprintf(stdout, "\nBinning into %d bins an array of size:%d...", bin_size, array_size);
#endif
gsl_histogram *h = gsl_histogram_alloc (bin_size-1);
gsl_histogram_set_ranges (h, bins, bin_size);
for(i=0; i<array_size; i++)
gsl_histogram_increment(h, array[i]);
for(j=0; j<bin_size-1; j++)
binned_array[j] = (int) h->bin[j];
gsl_histogram_free(h);
}
bool myHistogram::Convert(double *res,int n)
{
gsl_histogram *r;
if(n<=2) return false;
double std=gsl_stats_sd(res,1,n);
double bin=3.49*std/pow(n*1.0,1.0/3);//Scott's ruler
if(bin<=0) return false;
double a=gsl_stats_min(res,1,n);
double b=gsl_stats_max(res,1,n);
int num=(int)((b-a)/bin);
r=gsl_histogram_alloc(num);
gsl_histogram_set_ranges_uniform(r,a,b);
for(int i=0;i<n;i++)
{
gsl_histogram_increment(r,res[i]);
}
Convert(r,n);
gsl_histogram_free(r);
return true;
}
bool HistList::AddHist(double *res,int n,double m,double sd,CString raw)
{
gsl_histogram *r;
if(n<=0) return false;
double std=gsl_stats_sd(res,1,n);
double bin=3.49*std/pow(n*1.0,1.0/3);//Scott's ruler
if(bin<=0) return false;
double a=gsl_stats_min(res,1,n);
double b=gsl_stats_max(res,1,n);
int num=(int)((b-a)/bin);
r=gsl_histogram_alloc(num);
gsl_histogram_set_ranges_uniform(r,a,b);
for(int i=0;i<n;i++)
{
gsl_histogram_increment(r,res[i]);
}
bool bResult=AddHist(r,m,sd,raw);
gsl_histogram_free(r);
return bResult;
}
/** @short Markov Chain Monte Carlo
@param rng the GSL random number generator
@param p the vector of parameters being searched over
@param x the vector of observations */
void mcmc(const gsl_rng *rng, gsl_vector *p, const gsl_vector *x)
{
gsl_vector * p_test = gsl_vector_alloc(p->size);
size_t i;
gsl_histogram * hist = gsl_histogram_alloc(nbins);
gsl_histogram_set_ranges_uniform(hist, min, max);
for(i=0; i < chain_length; i++)
{
gsl_vector_memcpy(p_test,p);
propose(rng, p_test);
double lnLikelihoodRatio = ln_lik_fn(p_test, x) - ln_lik_fn(p, x);
if (take_step(rng, lnLikelihoodRatio))
p = p_test;
gsl_histogram_increment(hist, p->data[1]);
}
gsl_vector_free(p_test);
gsl_histogram_fprintf(stdout, hist, "%g", "%g");
gsl_histogram_free(hist);
}
QVector<QPointF> DistanceToAtom::histogram(int bins) {
QVector<QPointF> histogramVector;
if(!m_isValid) {
qFatal("DistanceToAtom is not valid. Run compute() first.");
exit(1);
}
float minValue = 1e90;
float maxValue = 0;
for(const float &val : m_values) {
if(val >= 0) {
minValue = std::min(minValue, (float)sqrt(val));
maxValue = std::max(maxValue, (float)sqrt(val));
}
}
gsl_histogram *hist = gsl_histogram_alloc (bins);
gsl_histogram_set_ranges_uniform (hist, minValue, maxValue);
for(const float &value : m_values) {
if(value >= 0) {
gsl_histogram_increment (hist, sqrt(value));
}
}
histogramVector.resize(bins);
for(int i=0; i<bins; i++) {
double upper, lower;
gsl_histogram_get_range(hist, i, &lower, &upper);
float middle = 0.5*(upper+lower);
histogramVector[i].setX(middle);
histogramVector[i].setY(gsl_histogram_get(hist,i));
}
gsl_histogram_free (hist);
return histogramVector;
}
