The class Modelling_NumberCounts. More...

#include <Modelling_NumberCounts.h>

Inheritance diagram for cbl::modelling::numbercounts::Modelling_NumberCounts:

[legend]

Collaboration diagram for cbl::modelling::numbercounts::Modelling_NumberCounts:

[legend]

Public Member Functions
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...

Constructors/destructors
	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

Member functions used to get the protected members of the class
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...

Member functions used to set the model parameters
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...

Protected Attributes
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

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_NumberCounts.

Modelling_NumberCounts.h "Headers/Modelling_NumberCounts.h"

This file defines the interface of the base class Modelling_NumberCounts, used for modelling any kind of number counts measurements

Definition at line 70 of file Modelling_NumberCounts.h.

Constructor & Destructor Documentation

◆ Modelling_NumberCounts() [1/2]

cbl::modelling::numbercounts::Modelling_NumberCounts::Modelling_NumberCounts ( const std::shared_ptr< cbl::measure::numbercounts::NumberCounts > nc )

inline

constuctor

Parameters

nc	the number counts to model _NumberCounts

Definition at line 104 of file Modelling_NumberCounts.h.

◆ Modelling_NumberCounts() [2/2]

cbl::modelling::numbercounts::Modelling_NumberCounts::Modelling_NumberCounts	(	glob::HistogramType	hist_type,
		double	fact
	)

inline

constuctor

Parameters

hist_type	the histogram type
fact	the normalization factor _NumberCounts

Definition at line 113 of file Modelling_NumberCounts.h.

Member Function Documentation

◆ data_model()

modelling::numbercounts::STR_NC_data_model cbl::modelling::numbercounts::Modelling_NumberCounts::data_model ( )

inline

get the member m_data_model

Returns: the container of parameters for number counts model computation

Definition at line 134 of file Modelling_NumberCounts.h.

◆ data_model_SF()

modelling::numbercounts::STR_NCSF_data_model cbl::modelling::numbercounts::Modelling_NumberCounts::data_model_SF ( )

inline

get the member m_data_model_SF

Returns: the container of parameters for size number counts model computation

Definition at line 144 of file Modelling_NumberCounts.h.

◆ set_data_model() [1/2]

void 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`
	)

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:

\( \langle N(\Delta{\lambda_{\text{ob},i}},\Delta z_{\text{ob},j})\rangle = w(\Delta{\lambda_{\text{ob},i}},\Delta z_{\text{ob},j})\,\,\Omega \int_{0}^{\infty} {\rm d} z_{\rm tr}\,\, \frac{{\rm d} V}{{\rm d} z_{\rm tr}{\rm d}\Omega}\int_{0}^{\infty} {\rm d} M_{\rm tr} \,\,\frac{{\rm d} n(M_{\rm tr},z_{\rm tr})}{{\rm d} M_{\rm tr}}\,\, \int_{0}^{\infty}{\rm d}\lambda_{\rm tr}\,\, P(\lambda_{\rm tr}| M_{\rm tr},z_{\rm tr})\, \int_{\Delta z_{\text{ob},j}}{\rm d} z_{\rm ob} \,\,P(z_{\rm ob}|z_{\rm tr})\, \int_{\Delta\lambda_{\text{ob},i}}{\rm d} \lambda_{\rm ob} \,\,P(\lambda_{\rm ob}|\lambda_{\rm tr}), \)

where \( w(\Delta{\lambda_{\text{ob},i}},\Delta z_{\text{ob},j}) \) is the weight derived from the selection function (see e.g. Lesci et al. 2021), and \(\Omega\) is the survey effective area.

Furthermore, \(P(z_{\rm ob}|z_{\rm tr})\) and \(P(\lambda_{\rm ob}|\lambda_{\rm tr})\) are Gaussian distributions.

Parameters

cosmology	the cosmological model
SF_weights	the counts weights derived from the selection function (see e.g. Lesci et al. 2021)
z_pivot	the redshift pivot in the scaling relation
proxy_pivot	the mass proxy pivot in the scaling relation
mass_pivot	the mass pivot; for example, if the scaling relation is written as \( \log [M/(10^{14}M_\odot /h)] = \alpha+\beta \log(\lambda/\lambda_{piv})+\gamma\log f(z) \), then mass_pivot = 1.e14
log_base	the base of the logarithm used in the mass-mass proxy scaling relation
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]
store_output	if true the output files created by the Boltzmann solver are stored; if false the output files are removed
norm	0 → don't normalize the power spectrum; 1 → normalize the power spectrum
Delta	\(\Delta\), the overdensity
isDelta_critical	\(\rightarrow\) \(\Delta\) is the overdensity defined with respect to the critical density
model_MF	author(s) who proposed the mass function
model_bias	author(s) who proposed the bias function, used for the transfer function necessary for the super-sample covariance
z_min	minimum redshift
z_max	maximum redshift
area_degrees	the area in degrees
prec	the precision

Definition at line 106 of file Modelling_NumberCounts.cpp.

◆ set_data_model() [2/2]

void cbl::modelling::numbercounts::Modelling_NumberCounts::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

Parameters

cosmology	the cosmological model used to compute ξ_DM
redshift	redshift
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]
k_min	minimum wave vector module up to which the binned dark matter power spectrum is computed
k_max	maximum wave vector module up to which the binned dark matter power spectrum is computed
step	number of steps used to compute the binned power spectrum
store_output	if true the output files created by the Boltzmann solver are stored; if false the output files are removed
norm	0 → don't normalize the power spectrum; 1 → normalize the power spectrum
Delta	\(\Delta\), the overdensity
isDelta_critical	\(\rightarrow\) \(\Delta\) is the overdensity defined with respect to the critical density
model_MF	author(s) who proposed the mass function
selection_function_file	input file with the selection function
selection_function_column	vector containing the columns with {mass, redshift, selection function}
z_min	minimum redshift
z_max	maximum redshift
z_step	the number of bins for redshift vector
Mass_min	minimum halo mass
Mass_max	maximum halo mass
Mass_step	the number of bins for mass vector
area_degrees	the area in degrees
prec	the precision

Definition at line 47 of file Modelling_NumberCounts.cpp.

◆ set_data_model_SF()

void 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`
	)

Member functions used to set the model parameters.

Parameters

cosmology	the cosmological model used to compute the void size function
radii	the void radii
redshift	the redshift
model	size function model name; valid choices for model name are SvdW (Sheth and van de Weygaert, 2004), linear and Vdn (Jennings et al., 2013)
b_eff	the effective bias of the sample
slope	first coefficent to convert the effective bias (default value set to \(0.854\))
offset	second coefficent to convert the effective bias (default value set to \(0.420\))
deltav_NL	the non linear density contrast: \(\rho_v/\rho_m\) (default value set to \(-0.795\))
del_c	critical value of the linear density field (default value set to \(1.06\))
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]
k_Pk_ratio	wave vector module required to compute the growth factor (cbl::cosmology::Cosmology::DD_norm()) with the method "Pk_ratio". This parameter represents wavenumber at which the ratio between the the power spectra at different redshift is computed. It is recommended to use this method when dealing with cosmologies alternative to the LCDM. To avoid to compute the growth factor with this method, set k_Pk_ratio=-1.
store_output	if true the output files created by the Boltzmann solver are stored; if false the output files are removed
output_root	output_root of the parameter file used to compute the power spectrum and σ(mass); it can be any name
interpType	method to interpolate the power spectrum
k_max	maximum wave vector module up to which the power spectrum is computed
input_file	either the parameter file or the power spectrum file; if a parameter file is provided, i.e. input_file!=NULL and is_parameter_file=true, it will be used to compute the power spectrum; if a power spectrum file is provided, i.e. input_file!=NULL and is_parameter_file=false, then the provided power spectrum will be used directly; in both cases σ²(M) is computed by integrating the computed/provided power spectrum ignoring the cosmological parameters of the object
is_parameter_file	true \(\rightarrow\) the input_file is a parameter file, used to compute the power spectrum with the method specified by method_Pk; false \(\rightarrow\) the input_file is a file containing the power spectrum

Examples: modelling_VoidAbundances.cpp.

Definition at line 163 of file Modelling_NumberCounts.cpp.

◆ set_data_model_snapshot()

virtual void 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`
	)

inlinevirtual

set the data used to construct mass number counts of simulation snapshots

Parameters

cosmology	the cosmological model used to compute ξ_DM
redshift	redshift
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]
k_min	minimum wave vector module up to which the binned dark matter power spectrum is computed
k_max	maximum wave vector module up to which the binned dark matter power spectrum is computed
step	number of steps used to compute the binned power spectrum
store_output	if true the output files created by the Boltzmann solver are stored; if false the output files are removed
norm	0 → don't normalize the power spectrum; 1 → normalize the power spectrum
Delta	\(\Delta\), the overdensity
isDelta_critical	\(\rightarrow\) \(\Delta\) is the overdensity defined with respect to the critical density
model_MF	author(s) who proposed the mass function
Volume	the snapshot volume
Mass_min	minimum halo mass
Mass_max	maximum halo mass
Mass_step	the number of bins for mass vector
prec	the precision

Definition at line 430 of file Modelling_NumberCounts.h.

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

Headers/Modelling_NumberCounts.h
Modelling/NumberCounts/Modelling_NumberCounts.cpp

Public Member Functions

Protected Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ Modelling_NumberCounts() [1/2]

◆ Modelling_NumberCounts() [2/2]

Member Function Documentation

◆ data_model()

◆ data_model_SF()

◆ set_data_model() [1/2]

◆ set_data_model() [2/2]

◆ set_data_model_SF()

◆ set_data_model_snapshot()