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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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This is the complete list of members for cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy, including all inherited members.
| data() | cbl::modelling::Modelling | inline |
| data_fit() | cbl::modelling::Modelling | inline |
| data_model() | cbl::modelling::numbercounts::Modelling_NumberCounts | inline |
| data_model_SF() | cbl::modelling::numbercounts::Modelling_NumberCounts | inline |
| get_parameter_from_string(const std::string parameter) const | cbl::modelling::Modelling | inlinevirtual |
| get_prior(const int i) | cbl::modelling::Modelling | inline |
| get_response_function() | cbl::modelling::Modelling | inline |
| 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) | cbl::modelling::Modelling | |
| likelihood() | cbl::modelling::Modelling | |
| likelihood_parameters() | cbl::modelling::Modelling | |
| m_data | cbl::modelling::Modelling | protected |
| m_data_fit | cbl::modelling::Modelling | protected |
| m_data_model | cbl::modelling::numbercounts::Modelling_NumberCounts | protected |
| m_data_model_SF | cbl::modelling::numbercounts::Modelling_NumberCounts | protected |
| m_fact | cbl::modelling::numbercounts::Modelling_NumberCounts | protected |
| m_fit_range | cbl::modelling::Modelling | protected |
| m_HistogramType | cbl::modelling::numbercounts::Modelling_NumberCounts | protected |
| m_isSet_response() | cbl::modelling::Modelling | inlineprotected |
| m_likelihood | cbl::modelling::Modelling | protected |
| m_model | cbl::modelling::Modelling | protected |
| m_parameter_priors | cbl::modelling::Modelling | protected |
| m_posterior | cbl::modelling::Modelling | protected |
| m_response_func | cbl::modelling::Modelling | protected |
| m_set_posterior(const int seed) | cbl::modelling::Modelling | |
| m_set_prior(std::vector< statistics::PriorDistribution > prior_distribution) | cbl::modelling::Modelling | protected |
| 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) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| Modelling()=default | cbl::modelling::Modelling | |
| Modelling_NumberCounts()=default | cbl::modelling::numbercounts::Modelling_NumberCounts | |
| Modelling_NumberCounts(const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc) | cbl::modelling::numbercounts::Modelling_NumberCounts | inline |
| Modelling_NumberCounts(glob::HistogramType hist_type, double fact) | cbl::modelling::numbercounts::Modelling_NumberCounts | inline |
| Modelling_NumberCounts1D()=default | cbl::modelling::numbercounts::Modelling_NumberCounts1D | |
| Modelling_NumberCounts1D(const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc) | cbl::modelling::numbercounts::Modelling_NumberCounts1D | inline |
| Modelling_NumberCounts1D(const std::shared_ptr< cbl::data::Data > dataset, glob::HistogramType hist_type, double fact) | cbl::modelling::numbercounts::Modelling_NumberCounts1D | inline |
| Modelling_NumberCounts1D_MassProxy()=default | cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy | |
| Modelling_NumberCounts1D_MassProxy(const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc) | cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy | inline |
| Modelling_NumberCounts1D_MassProxy(const std::shared_ptr< cbl::data::Data > dataset, glob::HistogramType hist_type, double fact) | cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy | inline |
| posterior() | cbl::modelling::Modelling | |
| posterior_parameters() | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| reduced_chi2(const std::vector< double > parameter={}) | cbl::modelling::Modelling | |
| reset_fit_range() | cbl::modelling::Modelling | inline |
| sample_posterior(const int chain_size, const int nwalkers, const int seed=666, const double aa=2, const bool parallel=true) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| set_data(const std::shared_ptr< data::Data > dataset) | cbl::modelling::Modelling | inline |
| 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) | cbl::modelling::numbercounts::Modelling_NumberCounts | |
| 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) | cbl::modelling::numbercounts::Modelling_NumberCounts | |
| 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) | cbl::modelling::numbercounts::Modelling_NumberCounts | |
| 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) | cbl::modelling::numbercounts::Modelling_NumberCounts | inlinevirtual |
| set_fit_range(const double xmin, const double xmax) | cbl::modelling::Modelling | |
| set_fit_range(const double xmin, const double xmax, const double ymin, const double ymax) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| set_likelihood(const cbl::statistics::Likelihood_function log_likelihood_function) | cbl::modelling::Modelling | |
| set_model_NumberCounts_cosmology(const std::string scalrel_z_evo, const std::string z_error_type, const std::string proxy_error_type, const std::vector< cbl::cosmology::CosmologicalParameter > cosmo_param, const std::vector< statistics::PriorDistribution > cosmo_param_prior, const statistics::PriorDistribution alpha_prior, const statistics::PriorDistribution beta_prior, const statistics::PriorDistribution gamma_prior, const statistics::PriorDistribution scatter0_prior, const statistics::PriorDistribution scatterM_prior, const statistics::PriorDistribution scatterM_exponent_prior, const statistics::PriorDistribution scatterz_prior, const statistics::PriorDistribution scatterz_exponent_prior, const statistics::PriorDistribution z_bias_prior, const statistics::PriorDistribution proxy_bias_prior, const statistics::PriorDistribution z_error_prior, const statistics::PriorDistribution proxy_error_prior, const std::vector< statistics::PriorDistribution > Plambda_prior) | cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy | |
| set_parameter_from_string(const std::string parameter, const double value) | cbl::modelling::Modelling | inlinevirtual |
| show_results(const int start=0, const int thin=1, const int nbins=50, const bool show_mode=false, const int ns=-1) | cbl::modelling::Modelling | |
| 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) | cbl::modelling::Modelling | |
| write_model(const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > parameters) | cbl::modelling::Modelling | virtual |
| 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) | cbl::modelling::Modelling | virtual |
| write_model_at_bestfit(const std::string output_dir, const std::string output_file, const std::vector< double > xx) | cbl::modelling::Modelling | virtual |
| write_model_at_bestfit(const std::string output_dir, const std::string output_file, const std::vector< double > xx, const std::vector< double > yy) | cbl::modelling::Modelling | virtual |
| 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) | cbl::modelling::Modelling | virtual |
| 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) | cbl::modelling::Modelling | virtual |
| 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) | cbl::modelling::Modelling | |
| ~Modelling()=default | cbl::modelling::Modelling | virtual |
| ~Modelling_NumberCounts()=default | cbl::modelling::numbercounts::Modelling_NumberCounts | virtual |
| ~Modelling_NumberCounts1D()=default | cbl::modelling::numbercounts::Modelling_NumberCounts1D | virtual |
| ~Modelling_NumberCounts1D_MassProxy()=default | cbl::modelling::numbercounts::Modelling_NumberCounts1D_MassProxy | virtual |
1.9.1