#include "Headers/Likelihood.h"

Inheritance diagram for cbl::statistics::Likelihood:

[legend]

Public Member Functions
std::shared_ptr< ModelParameters >	parameters () const
	return the likelihood parameters More...

double	operator() (std::vector< double > &pp) const
	evaluate the likelihood More...

double	log (std::vector< double > &parameter) const
	evaluate the logarithm of the likelihood for the input parameters More...

void	set_data (std::shared_ptr< data::Data > data)
	set the data for the likelihood analysis More...

void	set_model (std::shared_ptr< Model > model=NULL, const std::shared_ptr< ModelParameters > model_parameters=NULL)
	set the model for the likelihood analysis More...

void	unset_grid ()
	set the likelihood function with internal values of LikelihoodType

std::shared_ptr< Model >	get_m_model ()
	get the values of the internal variable m_model More...

std::shared_ptr< ModelParameters >	get_model_parameters ()
	get the values of the internal variable m_model More...

std::shared_ptr< data::Data >	get_m_data ()
	get the values of the internal variable m_data More...

void	set_grid (const int npoints, const std::vector< std::vector< double >> parameter_limits, const std::string file, const bool read=false)
	set the likelihood function as a grid, to speed up computation: this only works for one or two free parameters More...

void	set_function (const 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 type using the LikelihoodType object More...

void	set_function (const LogLikelihood_function likelihood_function)
	set the likelihood function More...

void	set_log_function (const LogLikelihood_function loglikelihood_function)
	set the natural logarithm of the likelihood function More...

void	write_results (const std::string dir_output, const std::string file)
	write best-fit results on a file More...

void	maximize (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 likelihood, finds the best-fit parameters and stores them in the model More...

void	write_model (const std::string output_dir, const std::string output_file, const std::vector< double > parameters, const std::vector< double > xx={}, const std::vector< double > yy={})
	write the model at xx at bestfit More...

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 at bestfit More...

Constructors/destructors
	Likelihood ()
	default constructor

	Likelihood (const std::shared_ptr< data::Data > data, const std::shared_ptr< Model > model, const LikelihoodType likelihood_type, const std::vector< size_t > x_index={0, 2}, const int w_index=-1, const std::shared_ptr< ModelParameters > model_parameters=NULL, const double prec=1.e-10, const int Nres=-1)
	constructor More...

	Likelihood (const std::shared_ptr< data::Data > data, const std::shared_ptr< Model > model, const Likelihood_function log_likelihood_function, const std::shared_ptr< ModelParameters > model_parameters=NULL)
	constructor More...

virtual	~Likelihood ()=default
	default destructor

Protected Member Functions
void	m_set_grid_likelihood_1D (const int npoints, const std::vector< std::vector< double >> parameter_limits, const std::string output_file)
	set the likelihood grid and write the grid on a file More...

void	m_set_grid_likelihood_1D (const std::string input_file)
	set the likelihood grid from file More...

void	m_set_grid_likelihood_2D (const int npoints, const std::vector< std::vector< double >> parameter_limits, const std::string output_file)
	set the likelihood grid and write the grid on a file More...

void	m_set_grid_likelihood_2D (const std::string input_file)
	set the likelihood grid from file More...

Protected Attributes
std::shared_ptr< data::Data >	m_data
	data containers

std::shared_ptr< Model >	m_model
	model to test

std::shared_ptr< void >	m_likelihood_inputs
	likelihood inputs

std::shared_ptr< ModelParameters >	m_model_parameters
	likelihood parameters

LikelihoodType	m_likelihood_type = LikelihoodType::_NotSet_
	type of the likelihood

LogLikelihood_function	m_log_likelihood_function
	log-likelihood function

Likelihood_function	m_likelihood_function
	likelihood function

LogLikelihood_function	m_likelihood_function_grid
	likelihood function on a grid

LogLikelihood_function	m_log_likelihood_function_grid
	log-likelihood function on a grid

std::vector< size_t >	m_x_index

int	m_w_index
	the index in extra info where the bin weight is stored

bool	m_use_grid = false
	use grid

Detailed Description

The class Likelihood.

This class is used to handle objects of type Likelihood. It is used for all kind of likelihood maximization

Examples: fit.cpp.

Definition at line 55 of file Likelihood.h.

Constructor & Destructor Documentation

◆ Likelihood() [1/2]

cbl::statistics::Likelihood::Likelihood	(	const std::shared_ptr< data::Data >	data,
		const std::shared_ptr< Model >	model,
		const LikelihoodType	likelihood_type,
		const std::vector< size_t >	x_index = `{0,2}`,
		const int	w_index = `-1`,
		const std::shared_ptr< ModelParameters >	model_parameters = `NULL`,
		const double	prec = `1.e-10`,
		const int	Nres = `-1`
	)

constructor

Parameters

data	pointers to the data container
model	pointers to the model
likelihood_type	type of likelihood
x_index	index(s) of the extra info std::vector containing the point(s) where to evaluate the model
w_index	std::vector containing the data point weight
model_parameters	parameters of the likelihood
prec	the precision required in the inversion of the covariance matrix
Nres	\(N_{res}\), the number of catalogue resamplings used to estimate the covariance matrix; \(N_{res}=-1\) if the covariance matrix has not been estimated with resampling methods

Definition at line 146 of file Likelihood.cpp.

◆ Likelihood() [2/2]

cbl::statistics::Likelihood::Likelihood	(	const std::shared_ptr< data::Data >	data,
		const std::shared_ptr< Model >	model,
		const Likelihood_function	log_likelihood_function,
		const std::shared_ptr< ModelParameters >	model_parameters = `NULL`
	)

constructor

Parameters

data	pointers to the data container
model	pointers to the model
log_likelihood_function	user-defined log-likelihood function (natural logarithm)
model_parameters	parameters of the likelihood

Definition at line 157 of file Likelihood.cpp.

Member Function Documentation

◆ get_m_data()

std::shared_ptr<data::Data> cbl::statistics::Likelihood::get_m_data ( )

inline

get the values of the internal variable m_data

Returns: pointer containing the data containers

Definition at line 286 of file Likelihood.h.

◆ get_m_model()

std::shared_ptr<Model> cbl::statistics::Likelihood::get_m_model ( )

inline

get the values of the internal variable m_model

Returns: pointer containing the model to test

Definition at line 272 of file Likelihood.h.

◆ get_model_parameters()

std::shared_ptr<ModelParameters> cbl::statistics::Likelihood::get_model_parameters ( )

inline

get the values of the internal variable m_model

Returns: pointer containing the model parameters

Definition at line 279 of file Likelihood.h.

◆ log()

double cbl::statistics::Likelihood::log ( std::vector< double > & parameter ) const

evaluate the logarithm of the likelihood for the input parameters

Parameters

parameter the likelihood parameters

Returns: the log-likelihood \( \log(\mathcal{L}) \)

Definition at line 177 of file Likelihood.cpp.

◆ m_set_grid_likelihood_1D() [1/2]

void cbl::statistics::Likelihood::m_set_grid_likelihood_1D	(	const int	npoints,
		const std::vector< std::vector< double >>	parameter_limits,
		const std::string	output_file
	)

protected

set the likelihood grid and write the grid on a file

Parameters

npoints	the number of points to bin the parameter space
parameter_limits	the limits for the parameter space
output_file	the input file

Definition at line 43 of file Likelihood.cpp.

◆ m_set_grid_likelihood_1D() [2/2]

void cbl::statistics::Likelihood::m_set_grid_likelihood_1D ( const std::string input_file )

protected

set the likelihood grid from file

Parameters

input_file the input file

Definition at line 110 of file Likelihood.cpp.

◆ m_set_grid_likelihood_2D() [1/2]

void cbl::statistics::Likelihood::m_set_grid_likelihood_2D	(	const int	npoints,
		const std::vector< std::vector< double >>	parameter_limits,
		const std::string	output_file
	)

protected

set the likelihood grid and write the grid on a file

Parameters

npoints	the number of points to bin the parameter space
parameter_limits	the limits for the parameter space
output_file	the input file

Definition at line 72 of file Likelihood.cpp.

◆ m_set_grid_likelihood_2D() [2/2]

void cbl::statistics::Likelihood::m_set_grid_likelihood_2D ( const std::string input_file )

protected

set the likelihood grid from file

Parameters

input_file the input file

Definition at line 128 of file Likelihood.cpp.

◆ maximize()

void cbl::statistics::Likelihood::maximize	(	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 likelihood, finds the best-fit parameters and stores them in the model

this function exploits the Nelder-Mead method https://en.wikipedia.org/wiki/Nelder%E2%80%93Mead_method

the algorithm defines a simplex (i.e a k-dimensional polytope which is the convex hull of its k+1 vertices) in the parameter space. At each step, it identifies the simplex vertex at which the function to be minimised (i.e. the negative likelihood in this case) has the greatest value, and moves it, via reflections and scaling, to a new position in which the function has a lower value. This iteration stops when the simplex area becomes lower than the tolerance. For instance, in 2D, the starting vertices of the simplex (a triangle in 2D) are the following: (start[0], start[1]) ; (start[0]+epsilon, start[1]) ; (start[0], start[1]+epsilon)

Parameters

start	std::vector containing initial values for the likelihood maximization
parameter_limits	limits for the parameters
max_iter	the maximum number of iterations
tol	the tolerance in finding convergence
epsilon	the simplex side

Definition at line 356 of file Likelihood.cpp.

◆ operator()()

double cbl::statistics::Likelihood::operator() ( std::vector< double > & pp ) const

evaluate the likelihood

Parameters

pp	the likelihood parameters

Returns: the likelihood \( \mathcal{L} \)

Definition at line 168 of file Likelihood.cpp.

◆ parameters()

std::shared_ptr<ModelParameters> cbl::statistics::Likelihood::parameters ( ) const

inline

return the likelihood parameters

Returns: pointer containing the likelihood parameters

Definition at line 218 of file Likelihood.h.

◆ set_data()

void cbl::statistics::Likelihood::set_data ( std::shared_ptr< data::Data > data )

set the data for the likelihood analysis

Parameters

data	pointer to the dataset

Definition at line 186 of file Likelihood.cpp.

◆ set_function() [1/2]

void cbl::statistics::Likelihood::set_function	(	const 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 type using the LikelihoodType object

Parameters

likelihood_type	the likelihood type, specified with the LikelihoodType object
x_index	index(s) of the extra info std::vector containing the point(s) where to evaluate the model
w_index	index of the extra info std::vector containing the data point weight
prec	the precision required in the inversion of the covariance matrix
Nres	\(N_{res}\), the number of catalogue resamplings used to estimate the covariance matrix; \(N_{res}=-1\) if the covariance matrix has not been estimated with resampling methods

Definition at line 262 of file Likelihood.cpp.

◆ set_function() [2/2]

void cbl::statistics::Likelihood::set_function ( const LogLikelihood_function likelihood_function )

set the likelihood function

Parameters

likelihood_function the likelihood function

Definition at line 334 of file Likelihood.cpp.

◆ set_grid()

void cbl::statistics::Likelihood::set_grid	(	const int	npoints,
		const std::vector< std::vector< double >>	parameter_limits,
		const std::string	file,
		const bool	read = `false`
	)

set the likelihood function as a grid, to speed up computation: this only works for one or two free parameters

Parameters

npoints	the number of grid points
parameter_limits
file	the file to read/write the likelihood computed on a grid
read	if true, read the likelihood grid from a list

Definition at line 225 of file Likelihood.cpp.

◆ set_log_function()

void cbl::statistics::Likelihood::set_log_function ( const LogLikelihood_function loglikelihood_function )

set the natural logarithm of the likelihood function

Parameters

loglikelihood_function the loglikelihood function

Definition at line 345 of file Likelihood.cpp.

◆ set_model()

void cbl::statistics::Likelihood::set_model	(	std::shared_ptr< Model >	model = `NULL`,
		const std::shared_ptr< ModelParameters >	model_parameters = `NULL`
	)

set the model for the likelihood analysis

Parameters

model	pointer to the model
model_parameters	parameters of the likelihood

Definition at line 195 of file Likelihood.cpp.

◆ write_model()

void cbl::statistics::Likelihood::write_model	(	const std::string	output_dir,
		const std::string	output_file,
		const std::vector< double >	parameters,
		const std::vector< double >	xx = `{}`,
		const std::vector< double >	yy = `{}`
	)

write the model at xx at bestfit

Parameters

output_dir	the output directory
output_file	the output file
parameters	the model parameters
xx	vector of points at which the model is computed
yy	vector of points at which the model is computed

Definition at line 435 of file Likelihood.cpp.

◆ write_model_at_bestfit()

void cbl::statistics::Likelihood::write_model_at_bestfit	(	const std::string	output_dir,
		const std::string	output_file,
		const std::vector< double >	xx = `{}`,
		const std::vector< double >	yy = `{}`
	)

inline

write the model at xx at bestfit

Parameters

output_dir	the output directory
output_file	the output file
xx	vector of points at which the model is computed
yy	vector of points at which the model is computed

Definition at line 407 of file Likelihood.h.

◆ write_results()

void cbl::statistics::Likelihood::write_results	(	const std::string	dir_output,
		const std::string	file
	)

write best-fit results on a file

Parameters

dir_output	output directory
file	output file

Definition at line 402 of file Likelihood.cpp.

Member Data Documentation

◆ m_x_index

std::vector<size_t> cbl::statistics::Likelihood::m_x_index

protected

the index in extra info for the coordinates in which the model is computed

Definition at line 89 of file Likelihood.h.

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

Headers/Likelihood.h
Statistics/Likelihood.cpp

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ Likelihood() [1/2]

◆ Likelihood() [2/2]

Member Function Documentation

◆ get_m_data()

◆ get_m_model()

◆ get_model_parameters()

◆ log()

◆ m_set_grid_likelihood_1D() [1/2]

◆ m_set_grid_likelihood_1D() [2/2]

◆ m_set_grid_likelihood_2D() [1/2]

◆ m_set_grid_likelihood_2D() [2/2]

◆ maximize()

◆ operator()()

◆ parameters()

◆ set_data()

◆ set_function() [1/2]

◆ set_function() [2/2]

◆ set_grid()

◆ set_log_function()

◆ set_model()

◆ write_model()

◆ write_model_at_bestfit()

◆ write_results()

Member Data Documentation

◆ m_x_index