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CosmoBolognaLib
Free Software C++/Python libraries for cosmological calculations
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CosmoBolognaLib
Free Software C++/Python libraries for cosmological calculations
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The class Modelling_NumberCounts1D. More...
#include <Modelling_NumberCounts1D.h>
Public Member Functions | |
Constructors/destructors | |
| Modelling_NumberCounts1D ()=default | |
| default constuctor | |
| Modelling_NumberCounts1D (const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc) | |
| constuctor More... | |
| Modelling_NumberCounts1D (const std::shared_ptr< cbl::data::Data > dataset, glob::HistogramType hist_type, double fact) | |
| constuctor More... | |
| virtual | ~Modelling_NumberCounts1D ()=default |
| default destructor | |
 Public Member Functions inherited from cbl::modelling::numbercounts::Modelling_NumberCounts | |
| void | set_data_model_SF (const cosmology::Cosmology cosmology, const std::vector< double > radii, const double redshift, const std::string model, const double b_eff, double slope=0.854, double offset=0.420, const double deltav_NL=-0.795, const double del_c=1.69, const std::string method_Pk="EisensteinHu", const double k_Pk_ratio=-1., const bool store_output=true, const std::string output_root="test", const std::string interpType="Linear", const double k_max=100., const std::string input_file=par::defaultString, const bool is_parameter_file=true) |
| Member functions used to set the model parameters. More... | |
| virtual void | set_data_model_snapshot (const cbl::cosmology::Cosmology cosmology={}, const double redshift=0., const std::string method_Pk="CAMB", const double k_min=1.e-4, const double k_max=100., const int step=500, const bool store_output=true, const int norm=-1, const double Delta=200., const bool isDelta_critical=true, const std::string model_MF="Tinker", const double Volume=par::defaultDouble, const double Mass_min=par::defaultDouble, const double Mass_max=par::defaultDouble, const int Mass_step=100, const double prec=1.e-4) |
| set the data used to construct mass number counts of simulation snapshots More... | |
| Modelling_NumberCounts ()=default | |
| default constuctor _NumberCounts | |
| Modelling_NumberCounts (const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc) | |
| constuctor More... | |
| Modelling_NumberCounts (glob::HistogramType hist_type, double fact) | |
| constuctor More... | |
| virtual | ~Modelling_NumberCounts ()=default |
| default destructor | |
| modelling::numbercounts::STR_NC_data_model | data_model () |
| get the member m_data_model More... | |
| modelling::numbercounts::STR_NCSF_data_model | data_model_SF () |
| get the member m_data_model_SF More... | |
| void | set_data_model (const cbl::cosmology::Cosmology cosmology={}, const double redshift=0., const std::string method_Pk="CAMB", const double k_min=1.e-4, const double k_max=100., const int step=500, const bool store_output=true, const int norm=-1, const double Delta=200., const bool isDelta_critical=true, const std::string model_MF="Tinker", const std::string selection_function_file=par::defaultString, const std::vector< int > selection_function_column={}, const double z_min=par::defaultDouble, const double z_max=par::defaultDouble, const int z_step=50, const double Mass_min=par::defaultDouble, const double Mass_max=par::defaultDouble, const int Mass_step=100, const double area_degrees=par::defaultDouble, const double prec=1.e-4) |
| set the data used to construct generic models of number counts More... | |
| void | set_data_model (const cbl::cosmology::Cosmology cosmology, const std::vector< double > SF_weights, const double z_pivot, const double proxy_pivot, const double mass_pivot, const double log_base, const std::string method_Pk, const bool store_output=true, const int norm=-1, const double Delta=200., const bool isDelta_critical=true, const std::string model_MF="Tinker", const std::string model_bias="Tinker", const double z_min=par::defaultDouble, const double z_max=par::defaultDouble, const double area_degrees=par::defaultDouble, const double prec=1.e-4) |
| set the data used to construct a model of number counts as a function of a mass proxy, here expressed as \(\lambda\), with the following functional form: More... | |
| Public Member Functions inherited from cbl::modelling::Modelling | |
| void | m_set_posterior (const int seed) |
| set the interal variable m_posterior More... | |
| Modelling ()=default | |
| default constuctor | |
| virtual | ~Modelling ()=default |
| default destructor | |
| std::shared_ptr< data::Data > | data () |
| return the dataset More... | |
| std::shared_ptr< data::Data > | data_fit () |
| return the dataset More... | |
| std::shared_ptr< statistics::Likelihood > | likelihood () |
| return the likelihood parameters More... | |
| std::shared_ptr< statistics::Posterior > | posterior () |
| return the posterior parameters More... | |
| std::shared_ptr< statistics::ModelParameters > | likelihood_parameters () |
| return the likelihood parameters More... | |
| std::shared_ptr< statistics::ModelParameters > | posterior_parameters () |
| return the posterior parameters More... | |
| virtual void | set_parameter_from_string (const std::string parameter, const double value) |
| set the value of a parameter providing its name string More... | |
| virtual double | get_parameter_from_string (const std::string parameter) const |
| get the value of a parameter providing its name string More... | |
| std::shared_ptr< statistics::PriorDistribution > | get_prior (const int i) |
| get the internal variable m_parameter_priors More... | |
| std::shared_ptr< statistics::Model > | get_response_function () |
| return the response function used to compute the super-sample covariance More... | |
| void | reset_fit_range () |
| reset the fit range More... | |
| void | set_fit_range (const double xmin, const double xmax) |
| set the fit range More... | |
| void | set_fit_range (const double xmin, const double xmax, const double ymin, const double ymax) |
| set the fit range More... | |
| void | set_data (const std::shared_ptr< data::Data > dataset) |
| set the dataset More... | |
| void | set_likelihood (const statistics::LikelihoodType likelihood_type, const std::vector< size_t > x_index={0, 2}, const int w_index=-1, const double prec=1.e-10, const int Nres=-1) |
| set the likelihood function More... | |
| void | set_likelihood (const cbl::statistics::Likelihood_function log_likelihood_function) |
| set the likelihood function, given a user-defined log-likelihood function More... | |
| void | maximize_likelihood (const std::vector< double > start, const std::vector< std::vector< double >> parameter_limits, const unsigned int max_iter=10000, const double tol=1.e-6, const double epsilon=1.e-3) |
| function that maximizes the posterior, finds the best-fit parameters and stores them in the model More... | |
| void | maximize_posterior (const std::vector< double > start, const unsigned int max_iter=10000, const double tol=1.e-6, const double epsilon=1.e-3, const int seed=666) |
| function that maximizes the posterior, finds the best-fit parameters and stores them in the model More... | |
| void | sample_posterior (const int chain_size, const int nwalkers, const int seed=666, const double aa=2, const bool parallel=true) |
| sample the posterior, initializing the chains by drawing from the prior distributions More... | |
| void | sample_posterior (const int chain_size, const int nwalkers, const double radius, const std::vector< double > start, const unsigned int max_iter=10000, const double tol=1.e-6, const double epsilon=1.e-3, const int seed=666, const double aa=2, const bool parallel=true) |
| sample the posterior, initializing the chains in a ball around the posterior best-fit parameters values More... | |
| void | sample_posterior (const int chain_size, const int nwalkers, std::vector< double > &value, const double radius, const int seed=666, const double aa=2, const bool parallel=true) |
| sample the posterior, initializing the chains by drawing from the prior distributions More... | |
| void | sample_posterior (const int chain_size, const std::vector< std::vector< double >> chain_value, const int seed=666, const double aa=2, const bool parallel=true) |
| sample the posterior, initializing the chains with input values More... | |
| void | sample_posterior (const int chain_size, const int nwalkers, const std::string input_dir, const std::string input_file, const int seed=666, const double aa=2, const bool parallel=true) |
| sample the posterior, initializing the chains reading the input values from an input file More... | |
| void | importance_sampling (const std::string input_dir, const std::string input_file, const int seed=666, const std::vector< size_t > column={}, const int header_lines_to_skip=1, const bool is_FITS_format=false, const bool apply_to_likelihood=false) |
| perform importance sampling More... | |
| void | write_chain (const std::string output_dir, const std::string output_file, const int start=0, const int thin=1, const bool is_FITS_format=false, const int prec=5, const int ww=14) |
| write the chains obtained after the MCMC sampling More... | |
| void | read_chain (const std::string input_dir, const std::string input_file, const int nwalkers, const std::vector< size_t > columns={}, const int skip_header=1, const bool fits=false) |
| read the chains More... | |
| void | show_results (const int start=0, const int thin=1, const int nbins=50, const bool show_mode=false, const int ns=-1) |
| show the results of the MCMC sampling on screen More... | |
| void | write_results (const std::string output_dir, const std::string root_file, const int start=0, const int thin=1, const int nbins=50, const bool fits=false, const bool compute_mode=false, const int ns=-1) |
| write the results of the MCMC sampling to file More... | |
| virtual void | write_model (const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > parameters) |
| write the model at xx for given parameters More... | |
| virtual void | write_model (const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > yy, const std::vector< double > parameters) |
| write the model at xx, yy for given parameters More... | |
| virtual void | write_model_at_bestfit (const std::string output_dir, const std::string output_file, const std::vector< double > xx) |
| write the model at xx with best-fit parameters obtained from posterior maximization More... | |
| virtual void | write_model_at_bestfit (const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > yy) |
| write the model at xx, yy with best-fit parameters obtained from likelihood maximization More... | |
| virtual void | write_model_from_chains (const std::string output_dir, const std::string output_file, const std::vector< double > xx, const int start=0, const int thin=1) |
| write the model at xx computing 16th, 50th and 84th percentiles from the chains More... | |
| virtual void | write_model_from_chains (const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > yy, const int start=0, const int thin=1) |
| write the model at xx, yy computing 16th, 50th and 84th percentiles from the chains More... | |
| double | reduced_chi2 (const std::vector< double > parameter={}) |
| the reduced \(\chi^2\) More... | |
Additional Inherited Members | |
| Protected Member Functions inherited from cbl::modelling::Modelling | |
| void | m_set_prior (std::vector< statistics::PriorDistribution > prior_distribution) |
| set the internal variable m_parameter_priors More... | |
| void | m_isSet_response () |
| check if the response function used to compute the super-sample covariance is set | |
| Protected Attributes inherited from cbl::modelling::numbercounts::Modelling_NumberCounts | |
| glob::HistogramType | m_HistogramType |
| the histogram type | |
| double | m_fact |
| the normalization factor | |
| modelling::numbercounts::STR_NC_data_model | m_data_model |
| the container of parameters for number counts model computation | |
| modelling::numbercounts::STR_NCSF_data_model | m_data_model_SF |
| the container of parameters for size number counts model computation | |
| Protected Attributes inherited from cbl::modelling::Modelling | |
| std::shared_ptr< data::Data > | m_data = NULL |
| input data to be modelled | |
| bool | m_fit_range = false |
| check if fit range has been set | |
| std::shared_ptr< data::Data > | m_data_fit |
| input data restricted to the range used for the fit | |
| std::shared_ptr< statistics::Model > | m_model = NULL |
| input model | |
| std::shared_ptr< statistics::Model > | m_response_func = NULL |
| response function for the computation of the super-sample covariance | |
| std::shared_ptr< statistics::Likelihood > | m_likelihood = NULL |
| likelihood | |
| std::vector< std::shared_ptr< statistics::PriorDistribution > > | m_parameter_priors |
| prior | |
| std::shared_ptr< statistics::Posterior > | m_posterior = NULL |
| posterior | |
The class Modelling_NumberCounts1D.
"Headers/Modelling_NumberCounts1D.h"
This file defines the interface of the base class Modelling_NumberCounts1D, used for modelling 1D number counts measurements
Definition at line 67 of file Modelling_NumberCounts1D.h.
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inline |
constuctor
| nc | the number counts to model |
Definition at line 86 of file Modelling_NumberCounts1D.h.
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inline |
constuctor
| dataset | the number counts dataset |
| hist_type | the histogram type |
| fact | the normalization factor |
Definition at line 95 of file Modelling_NumberCounts1D.h.
1.9.1