34 #ifndef __MODELLINGDISTR__
35 #define __MODELLINGDISTR__
183 std::vector<double>
model_gaussian (
const std::vector<double> x,
const std::shared_ptr<void> inputs, std::vector<double> ¶meter);
203 std::vector<double>
model_gaussian2 (
const std::vector<double> x,
const std::shared_ptr<void> inputs, std::vector<double> ¶meter);
std::shared_ptr< data::Data > m_data
input data to be modelled
The class Modelling_Distribution.
virtual ~Modelling_Distribution()=default
default destructor
STR_Distr_model m_data_model
the container of fixed parameters
Modelling_Distribution()=default
default constuctor
Modelling_Distribution(const std::shared_ptr< cbl::data::Data > dataset)
constuctor
void set_model_Distribution(const statistics::PriorDistribution mean_prior, const statistics::PriorDistribution std_prior, const std::string mean_name, const std::string std_name)
set the parameters of a Gaussian PDF
The class PriorDistribution.
std::vector< double > model_gaussian2(const std::vector< double > x, const std::shared_ptr< void > inputs, std::vector< double > ¶meter)
compute a Gaussian PDF, where the standard deviation, , is expressed as
std::vector< double > model_gaussian(const std::vector< double > x, const std::shared_ptr< void > inputs, std::vector< double > ¶meter)
compute a Gaussian PDF
The global namespace of the CosmoBolognaLib
void distribution(std::vector< double > &xx, std::vector< double > &fx, std::vector< double > &err, const std::vector< double > FF, const std::vector< double > WW, const int nbin, const bool linear=true, const std::string file_out=par::defaultString, const double fact=1., const double V1=par::defaultDouble, const double V2=par::defaultDouble, const std::string bin_type="Linear", const bool conv=false, const double sigma=0.)
derive and store the number distribution of a given std::vector
the structure STR_Distr_model
STR_Distr_model()=default
default constructor