#include <NumberCounts1D.h>

Inheritance diagram for cbl::measure::numbercounts::NumberCounts1D:

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Collaboration diagram for cbl::measure::numbercounts::NumberCounts1D:

Public Member Functions
Constructors/destructors
	NumberCounts1D ()
	default constructor More...

virtual	~NumberCounts1D ()=default
	default destructor

	NumberCounts1D (const catalogue::Var var, const BinType bin_type, const catalogue::Catalogue data, const size_t nbins, const double minVar=par::defaultDouble, const double maxVar=par::defaultDouble, const double shift=0.5, const glob::HistogramType hist_type=glob::HistogramType::_N_V_, const double fact=1.)
	constructor More...

	NumberCounts1D (const catalogue::Var var, const std::vector< double > vec_edges, const catalogue::Catalogue data, const glob::HistogramType hist_type=glob::HistogramType::_N_V_, const double fact=1.)
	constructor More...

Member functions to measure the number counts
void	measure (const ErrorType errorType=ErrorType::_Poisson_, const std::string dir_output_resample=par::defaultString, const int nResamplings=0, const int seed=3213, const bool conv=false, const double sigma=0.) override
	measure the number counts More...

void	compute_covariance (const std::vector< std::shared_ptr< glob::Histogram >> hist, const bool JK) override
	compute the covariance matrix More...

Input/Output member functions (customized in all the derived classes)
void	write (const std::string dir=par::defaultString, const std::string file=par::defaultString, const int rank=0) const override
	write the measured number counts More...

void	write_covariance (const std::string dir, const std::string file) const override
	write the measured covariance matrix More...

std::shared_ptr< data::Data >	Gaussian_smoothing (const double sigma) override
	apply a Gaussian filter to the distribution More...

Public Member Functions inherited from cbl::measure::numbercounts::NumberCounts
	NumberCounts ()=default
	default constructor

virtual	~NumberCounts ()=default
	default destructor

void	set_data (const catalogue::Catalogue data)
	add a data catalogue More...

std::shared_ptr< catalogue::Catalogue >	catalogue ()
	function to get the protected member m_data More...

std::shared_ptr< glob::Histogram >	histogram ()
	return the binned counts More...

glob::HistogramType	HistogramType ()
	return the type of histogram normalization More...

double	fact ()
	return the normalization factor More...

Public Member Functions inherited from cbl::measure::Measure
	Measure ()=default
	default constructor

virtual	~Measure ()=default
	default destructor

virtual std::shared_ptr< data::Data >	dataset () const
	get the protected member dataset More...

Protected Member Functions
Protected member functions to measure the number counts
std::shared_ptr< data::Data >	m_measurePoisson () override
	measure the number counts with Poisson errors More...

std::shared_ptr< data::Data >	m_measureJackknife (const std::string dir_output_resample=par::defaultString) override
	measure the number counts with Jackknife covariance matrix More...

std::shared_ptr< data::Data >	m_measureBootstrap (const std::string dir_output_resample=par::defaultString, const int nResamplings=0, const int seed=3213) override
	measure the number counts with Bootstrap covariance matrix More...

Protected member functions to measure the number counts

Protected Attributes
catalogue::Var	m_Var
	the catalogue variable to bin

Protected Attributes inherited from cbl::measure::numbercounts::NumberCounts
std::shared_ptr< catalogue::Catalogue >	m_data
	input data catalogue

glob::HistogramType	m_HistogramType
	the histogram type

double	m_fact
	the normalization factor

std::shared_ptr< glob::Histogram >	m_histogram
	number counts type

Protected Attributes inherited from cbl::measure::Measure
std::shared_ptr< data::Data >	m_dataset
	the dataset of the measure

Detailed Description

The class NumberCounts1D.

"Headers/NumberCounts1D.h"

This is the base class used to measure the number counts of one variable

Definition at line 68 of file NumberCounts1D.h.

Constructor & Destructor Documentation

◆ NumberCounts1D() [1/3]

cbl::measure::numbercounts::NumberCounts1D::NumberCounts1D ( )

inline

default constructor

1D

Definition at line 128 of file NumberCounts1D.h.

◆ NumberCounts1D() [2/3]

cbl::measure::numbercounts::NumberCounts1D::NumberCounts1D	(	const catalogue::Var	var,
		const BinType	bin_type,
		const catalogue::Catalogue	data,
		const size_t	nbins,
		const double	minVar = `par::defaultDouble`,
		const double	maxVar = `par::defaultDouble`,
		const double	shift = `0.5`,
		const glob::HistogramType	hist_type = `glob::HistogramType::_N_V_`,
		const double	fact = `1.`
	)

constructor

Parameters

var	the variable type
bin_type	the bin type
data	object of class Catalogue
nbins	the number of bins
minVar	minimum range
maxVar	maximmum range
shift	the shift of the bin
hist_type	the type of histogram
fact	factor used to normalized the distribution

1D

Definition at line 47 of file NumberCounts1D.cpp.

◆ NumberCounts1D() [3/3]

cbl::measure::numbercounts::NumberCounts1D::NumberCounts1D	(	const catalogue::Var	var,
		const std::vector< double >	vec_edges,
		const catalogue::Catalogue	data,
		const glob::HistogramType	hist_type = `glob::HistogramType::_N_V_`,
		const double	fact = `1.`
	)

constructor

Parameters

var	the variable type
vec_edges	bin edges, used only in case of a custom binning
data	object of class Catalogue
hist_type	the type of histogram
fact	factor used to normalized the distribution

1D

Definition at line 72 of file NumberCounts1D.cpp.

Member Function Documentation

◆ compute_covariance()

void cbl::measure::numbercounts::NumberCounts1D::compute_covariance	(	const std::vector< std::shared_ptr< glob::Histogram >>	hist,
		const bool	JK
	)

overridevirtual

compute the covariance matrix

Parameters

hist	vector containing the measures used to compute the covariance matrix
JK	true → compute the jackknife covariance matrix; false compute the standard covariance matrix

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 261 of file NumberCounts1D.cpp.

◆ Gaussian_smoothing()

shared_ptr< data::Data > cbl::measure::numbercounts::NumberCounts1D::Gaussian_smoothing ( const double sigma )

overridevirtual

apply a Gaussian filter to the distribution

Parameters

σ	of the Gaussian kernel

Returns: pointer to object of type Data

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 305 of file NumberCounts1D.cpp.

◆ m_measureBootstrap()

shared_ptr< data::Data > cbl::measure::numbercounts::NumberCounts1D::m_measureBootstrap	(	const std::string	dir_output_resample = `par::defaultString`,
		const int	nResamplings = `0`,
		const int	seed = `3213`
	)

overrideprotectedvirtual

measure the number counts with Bootstrap covariance matrix

Parameters

dir_output_resample	output directory of the resampling correlation functions
nResamplings	number of resampling used for bootstrap
seed	the seed for random number generation

Returns: point to object of type Data

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 187 of file NumberCounts1D.cpp.

◆ m_measureJackknife()

shared_ptr< data::Data > cbl::measure::numbercounts::NumberCounts1D::m_measureJackknife ( const std::string dir_output_resample = par::defaultString )

overrideprotectedvirtual

measure the number counts with Jackknife covariance matrix

Parameters

dir_output_resample output directory of the resampling correlation functions

Returns: point to object of type Data

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 139 of file NumberCounts1D.cpp.

◆ m_measurePoisson()

shared_ptr< data::Data > cbl::measure::numbercounts::NumberCounts1D::m_measurePoisson ( )

overrideprotectedvirtual

measure the number counts with Poisson errors

Returns: point to object of type Data

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 96 of file NumberCounts1D.cpp.

◆ measure()

void cbl::measure::numbercounts::NumberCounts1D::measure	(	const ErrorType	errorType = `ErrorType::_Poisson_`,
		const std::string	dir_output_resample = `par::defaultString`,
		const int	nResamplings = `0`,
		const int	seed = `3213`,
		const bool	conv = `false`,
		const double	sigma = `0.`
	)

overridevirtual

measure the number counts

Parameters

errorType	type of error
dir_output_resample	output directory of the resampling correlation functions
nResamplings	number of resampling used for bootstrap
seed	the seed for random number generation
conv	true → compute the Gaussian convolvolution of the distribution; false → do not convolve
sigma	σ of the Gaussian kernel

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Examples: numberCounts.cpp, and numberCounts_errors.cpp.

Definition at line 239 of file NumberCounts1D.cpp.

◆ write()

void cbl::measure::numbercounts::NumberCounts1D::write	(	const std::string	dir = `par::defaultString`,
		const std::string	file = `par::defaultString`,
		const int	rank = `0`
	)		const

overridevirtual

write the measured number counts

Parameters

dir	output directory
file	output file
rank	cpu index (for MPI usage)

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 278 of file NumberCounts1D.cpp.

◆ write_covariance()

void cbl::measure::numbercounts::NumberCounts1D::write_covariance	(	const std::string	dir,
		const std::string	file
	)		const

overridevirtual

write the measured covariance matrix

Parameters

dir	output directory
file	output file

Reimplemented from cbl::measure::numbercounts::NumberCounts.

Definition at line 293 of file NumberCounts1D.cpp.

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

Headers/NumberCounts1D.h
Measure/NumberCounts/NumberCounts1D.cpp

Public Member Functions

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ NumberCounts1D() [1/3]

◆ NumberCounts1D() [2/3]

◆ NumberCounts1D() [3/3]

Member Function Documentation

◆ compute_covariance()

◆ Gaussian_smoothing()

◆ m_measureBootstrap()

◆ m_measureJackknife()

◆ m_measurePoisson()

◆ measure()

◆ write()

◆ write_covariance()