The class Modelling_PowerSpectrum_angular. More...

#include <Modelling_PowerSpectrum_Angular.h>

Inheritance diagram for cbl::modelling::angularpk::Modelling_PowerSpectrum_angular:

Collaboration diagram for cbl::modelling::angularpk::Modelling_PowerSpectrum_angular:

Public Member Functions
Constructors/destructors
	Modelling_PowerSpectrum_angular ()=default
	default constuctor

	Modelling_PowerSpectrum_angular (const std::shared_ptr< cbl::measure::angularpk::PowerSpectrum_angular > Pow)
	constructor More...

	Modelling_PowerSpectrum_angular (const std::shared_ptr< data::Data > dataset)
	constructor More...

virtual	~Modelling_PowerSpectrum_angular ()=default
	default destructor

Member functions used to set the model parameters
void	set_model_limber (const std::vector< cbl::cosmology::CosmologicalParameter > cosmo_param, const std::vector< statistics::PriorDistribution > cosmo_prior, const statistics::PriorDistribution bias_prior)
	set the model to fit the angular power spectrum More...

void	set_model_limber (const std::vector< cbl::cosmology::CosmologicalParameter > cosmo_param, const std::vector< statistics::PriorDistribution > cosmo_prior, const statistics::PriorDistribution bias_prior, const statistics::PriorDistribution offset_slope_prior)
	set the model to fit the angular power spectrum More...

void	set_model_limber_cross (const std::vector< cbl::cosmology::CosmologicalParameter > cosmo_param, const std::vector< statistics::PriorDistribution > cosmo_prior, const statistics::PriorDistribution bias_prior_bin1, const statistics::PriorDistribution bias_prior_bin2)
	set the model to fit the cross correlation angular power spectrum More...

std::shared_ptr< modelling::angularpk::STR_data_model >	data_model ()
	get the member m_data_model More...

void	set_data_model (const cbl::cosmology::Cosmology cosmology, const double z_min=0., const double z_max=10., const std::string method_Pk="CAMB", const bool NL=false, const int norm=-1, const double k_min=0.001, const double k_max=5., const std::vector< double > dN_par={}, const double fsky=1., std::vector< double > ll={}, std::vector< std::vector< double >> mixing_matrix={}, const bool interpolate_power_spectrum=false)
	Set the data used to construct models of the angular power spectrum. More...

void	set_data_model_cross (const cbl::cosmology::Cosmology cosmology, const double z_min=0., const double z_max=10., const std::string method_Pk="CAMB", const bool NL=false, const int norm=-1, const double k_min=0.001, const double k_max=5., const std::vector< double > dN_par={}, const double fsky=1., std::vector< double > ll={}, std::vector< std::vector< double >> mixing_matrix={}, const bool interpolate_power_spectrum=false, const double z_min_bin2=-1., const double z_max_bin2=-1., const std::vector< double > dN_par_bin2={})
	Set the data used to construct models of the angular power spectrum. 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...

Protected Attributes
std::shared_ptr< modelling::angularpk::STR_data_model >	m_data_model
	the container of parameters for angular power spectrum 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

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

Detailed Description

The class Modelling_PowerSpectrum_angular.

Modelling_PowerSpectrum_Angular.h "Headers/Modelling_PowerSpectrum_Angular.h"

This file defines the interface of the base class Modelling_PowerSpectrum_angular, used for modelling the angular power spectrum

Examples: model_power_spectrum_angular.cpp.

Definition at line 61 of file Modelling_PowerSpectrum_Angular.h.

Constructor & Destructor Documentation

◆ Modelling_PowerSpectrum_angular() [1/2]

cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::Modelling_PowerSpectrum_angular ( const std::shared_ptr< cbl::measure::angularpk::PowerSpectrum_angular > Pow )

inline

constructor

Parameters

Pow	the angular power spectrum to model

Definition at line 84 of file Modelling_PowerSpectrum_Angular.h.

◆ Modelling_PowerSpectrum_angular() [2/2]

cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::Modelling_PowerSpectrum_angular ( const std::shared_ptr< data::Data > dataset )

inline

constructor

Parameters

dataset the dataset containing the angular power spectrum to model

Definition at line 93 of file Modelling_PowerSpectrum_Angular.h.

Member Function Documentation

◆ data_model()

std::shared_ptr<modelling::angularpk::STR_data_model> cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::data_model ( )

inline

get the member m_data_model

Returns: the container of parameters for two-point correlation function model computation

Definition at line 198 of file Modelling_PowerSpectrum_Angular.h.

◆ set_data_model()

void cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::set_data_model	(	const cbl::cosmology::Cosmology	cosmology,
		const double	z_min = `0.`,
		const double	z_max = `10.`,
		const std::string	method_Pk = `"CAMB"`,
		const bool	NL = `false`,
		const int	norm = `-1`,
		const double	k_min = `0.001`,
		const double	k_max = `5.`,
		const std::vector< double >	dN_par = `{}`,
		const double	fsky = `1.`,
		std::vector< double >	ll = `{}`,
		std::vector< std::vector< double >>	mixing_matrix = `{}`,
		const bool	interpolate_power_spectrum = `false`
	)

Set the data used to construct models of the angular power spectrum.

Parameters

cosmology	the cosmological model used to measure angular power spectrum
z_min	the minimum redshift of the first redshift slice or of the full integral in one bin case
z_max	the maximum redshift of the first redshift slice or of the full integral in one bin case
method_Pk	method used to compute the power spectrum (i.e. the Boltzmann solver); valid choices for method_Pk are: CAMB [http://camb.info/], CLASS [http://class-code.net/], MPTbreeze-v1 [http://arxiv.org/abs/1207.1465], EisensteinHu [http://background.uchicago.edu/~whu/transfer/transferpage.html]
NL	0 \(\rightarrow\) linear power spectrum; 1 \(\rightarrow\) non-linear power spectrum
norm	0 \(\rightarrow\) don't normalise the power spectrum; 1 \(\rightarrow\) normalise the power spectrum; -1 \(\rightarrow\) normalise only if sigma8 is set
k_min	minimum wave vector module up to which the power spectrum is computed in order to estimate the power spectrum normalisation; this parameter is used only if either norm=1, or norm=-1 and sigma8 is set
k_max	maximum wave vector module up to which the power spectrum is computed to estimate the power spectrum normalisation; this parameter is used only if norm=1
dN_par	offset, slope and parameters of the dN/dz normalized distribution for the first redshift slice
fsky	the fraction of the sky covered by the survey
ll	the vector of the multipoles of the mixing matrix
mixing_matrix	the mixing matrix
interpolate_power_spectrum	default false, true if you want to interpolate the 3D power spectrum on a grid (faster)

Examples: model_power_spectrum_angular.cpp.

Definition at line 48 of file Modelling_PowerSpectrum_Angular.cpp.

◆ set_data_model_cross()

void cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::set_data_model_cross	(	const cbl::cosmology::Cosmology	cosmology,
		const double	z_min = `0.`,
		const double	z_max = `10.`,
		const std::string	method_Pk = `"CAMB"`,
		const bool	NL = `false`,
		const int	norm = `-1`,
		const double	k_min = `0.001`,
		const double	k_max = `5.`,
		const std::vector< double >	dN_par = `{}`,
		const double	fsky = `1.`,
		std::vector< double >	ll = `{}`,
		std::vector< std::vector< double >>	mixing_matrix = `{}`,
		const bool	interpolate_power_spectrum = `false`,
		const double	z_min_bin2 = `-1.`,
		const double	z_max_bin2 = `-1.`,
		const std::vector< double >	dN_par_bin2 = `{}`
	)

Set the data used to construct models of the angular power spectrum.

Parameters

cosmology	the cosmological model used to measure angular power spectrum
z_min	the minimum redshift of the first redshift slice or of the full integral in one bin case
z_max	the maximum redshift of the first redshift slice or of the full integral in one bin case
method_Pk	method used to compute the power spectrum (i.e. the Boltzmann solver); valid choices for method_Pk are: CAMB [http://camb.info/], CLASS [http://class-code.net/], MPTbreeze-v1 [http://arxiv.org/abs/1207.1465], EisensteinHu [http://background.uchicago.edu/~whu/transfer/transferpage.html]
NL	0 \(\rightarrow\) linear power spectrum; 1 \(\rightarrow\) non-linear power spectrum
norm	0 \(\rightarrow\) don't normalise the power spectrum; 1 \(\rightarrow\) normalise the power spectrum; -1 \(\rightarrow\) normalise only if sigma8 is set
k_min	minimum wave vector module up to which the power spectrum is computed in order to estimate the power spectrum normalisation; this parameter is used only if either norm=1, or norm=-1 and sigma8 is set
k_max	maximum wave vector module up to which the power spectrum is computed to estimate the power spectrum normalisation; this parameter is used only if norm=1
dN_par	offset, slope and parameters of the dN/dz normalized distribution for the first redshift slice
fsky	the fraction of the sky covered by the survey
ll	the vector of the multipoles of the mixing matrix
mixing_matrix	the mixing matrix
interpolate_power_spectrum	default false, true if you want to interpolate the 3D power spectrum on a grid (faster)
z_min_bin2	the minimum redshift of the second redshift slice
z_max_bin2	the maximum redshift of the second redshift slice
dN_par_bin2	offset, slope and parameters of the dN/dz normalized distribution for the second redshift slice

Definition at line 76 of file Modelling_PowerSpectrum_Angular.cpp.

◆ set_model_limber() [1/2]

void cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::set_model_limber	(	const std::vector< cbl::cosmology::CosmologicalParameter >	cosmo_param,
		const std::vector< statistics::PriorDistribution >	cosmo_prior,
		const statistics::PriorDistribution	bias_prior
	)

set the model to fit the angular power spectrum

the model is the following:

\[ C_l = \frac{b^2}{N^2}\int_{0}^{\infty} \frac{dN}{dz}\frac{dN}{dz} P_{mat} \left(\frac{l+1/2}{r(z)}\right) \frac{H(z)}{c}\frac{1}{r^2(z)} dz\]

the model has 1 parameters:

\( b \)

offset and slope of the dN/dz distribution are fixed by the user the angular power spectrum is computed using the input cosmological parameters

Parameters

cosmo_param	list of cosmological parameter for the model
cosmo_prior	prior for the cosmological parameters
bias_prior	prior for the parameter \( b \)

Examples: model_power_spectrum_angular.cpp.

Definition at line 151 of file Modelling_PowerSpectrum_Angular.cpp.

◆ set_model_limber() [2/2]

void cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::set_model_limber	(	const std::vector< cbl::cosmology::CosmologicalParameter >	cosmo_param,
		const std::vector< statistics::PriorDistribution >	cosmo_prior,
		const statistics::PriorDistribution	bias_prior,
		const statistics::PriorDistribution	offset_slope_prior
	)

set the model to fit the angular power spectrum

the model is the following:

\[ C_l = \frac{b^2}{N^2}\int_0^\infty \frac{dN}{dz} \frac{dN}{dz} P_{mat} \left(\frac{l+1/2}{r(z)}\right) \frac{H(z)}{c}\frac{1}{r^2(z)} dz\]

the model has 3 parameters:

\( b \)
\( offset \)
\( slope \)

offset and slope reproduce the dN/dz distribution. The angular power spectrum is computed using the input cosmological parameters

Parameters

cosmo_param	list of cosmological parameter for the model
cosmo_prior	prior for the cosmological parameters
bias_prior	prior for the parameter \( b \)
offset_slope_prior	prior for the corralated parameter \( offset \) and \( slope \)

Definition at line 107 of file Modelling_PowerSpectrum_Angular.cpp.

◆ set_model_limber_cross()

void cbl::modelling::angularpk::Modelling_PowerSpectrum_angular::set_model_limber_cross	(	const std::vector< cbl::cosmology::CosmologicalParameter >	cosmo_param,
		const std::vector< statistics::PriorDistribution >	cosmo_prior,
		const statistics::PriorDistribution	bias_prior_bin1,
		const statistics::PriorDistribution	bias_prior_bin2
	)

set the model to fit the cross correlation angular power spectrum

the model is the following:

\[ C_l = \frac{b_i b_j}{N^2}\int_{0}^{\infty} \frac{dN_i}{dz}\frac{dN_j}{dz} P_{mat} \left(\frac{l+1/2}{r(z)}\right) \frac{H(z)}{c}\frac{1}{r^2(z)} dz\]

the model has 1 parameters:

\( b \)

offset and slope of the dN/dz distribution are fixed by the user the angular power spectrum is computed using the input cosmological parameters

Parameters

cosmo_param	list of cosmological parameter for the model
cosmo_prior	prior for the cosmological parameters
bias_prior_bin1	prior for the parameter \( b_i \)
bias_prior_bin2	prior for the parameter \( b_j \)

Definition at line 187 of file Modelling_PowerSpectrum_Angular.cpp.

The documentation for this class was generated from the following files:

Headers/Modelling_PowerSpectrum_Angular.h
Modelling/AngularPowerSpectrum/Modelling_PowerSpectrum_Angular.cpp

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Modelling_PowerSpectrum_angular() [1/2]

◆ Modelling_PowerSpectrum_angular() [2/2]

Member Function Documentation

◆ data_model()

◆ set_data_model()

◆ set_data_model_cross()

◆ set_model_limber() [1/2]

◆ set_model_limber() [2/2]

◆ set_model_limber_cross()