namespace defining utility free functions using in Fit for evaluating the various fit method functions (chi2, likelihood, etc..) given the data and the model function More...

Classes
struct	Evaluate

class	IntegralEvaluator

class	LikelihoodAux

class	LikelihoodAux< double >

struct	ParamDerivFunc

class	SimpleGradientCalculator

Typedefs
typedef ROOT::Math::IParamMultiGradFunction	IGradModelFunction

template<class T >
using	IGradModelFunctionTempl = ROOT::Math::IParamMultiGradFunctionTempl< T >

typedef ROOT::Math::IParamMultiFunction	IModelFunction

template<class T >
using	IModelFunctionTempl = ROOT::Math::IParamMultiFunctionTempl< T >

Functions
template<class GFunc >
void	CalculateGradientIntegral (const GFunc &gfunc, const double x1, const double x2, const double p, double g)

bool	CheckInfNaNValue (double &rval)

double	CorrectValue (double rval)

double	EvaluateChi2 (const IModelFunction &func, const BinData &data, const double *p, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy, unsigned nChunks=0)
	Chi2 Functions.

double	EvaluateChi2Effective (const IModelFunction &func, const BinData &data, const double *x, unsigned int &nPoints)
	evaluate the effective Chi2 given a model function and the data at the point x.

void	EvaluateChi2Gradient (const IModelFunction &func, const BinData &data, const double p, double grad, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy=::ROOT::EExecutionPolicy::kSequential, unsigned nChunks=0)
	evaluate the Chi2 gradient given a model function and the data at the point p.

double	EvaluateChi2Residual (const IModelFunction &func, const BinData &data, const double p, unsigned int ipoint, double g=nullptr, double *h=nullptr, bool hasGrad=false, bool fullHessian=false)
	evaluate the residual contribution to the Chi2 given a model function and the BinPoint data and if the pointer g is not null evaluate also the gradient of the residual.

double	EvaluateLogL (const IModelFunction &func, const UnBinData &data, const double *p, int iWeight, bool extended, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy, unsigned nChunks=0)
	evaluate the LogL given a model function and the data at the point x.

void	EvaluateLogLGradient (const IModelFunction &func, const UnBinData &data, const double p, double grad, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy=::ROOT::EExecutionPolicy::kSequential, unsigned nChunks=0)
	evaluate the LogL gradient given a model function and the data at the point p.

double	EvaluatePdf (const IModelFunction &func, const UnBinData &data, const double p, unsigned int ipoint, double g=nullptr, double *h=nullptr, bool hasGrad=false, bool fullHessian=false)
	evaluate the pdf contribution to the LogL given a model function and the BinPoint data.

double	EvaluatePoissonBinPdf (const IModelFunction &func, const BinData &data, const double x, unsigned int ipoint, double g=nullptr, double *h=nullptr, bool hasGrad=false, bool fullHessian=false)
	evaluate the pdf contribution to the Poisson LogL given a model function and the BinPoint data.

double	EvaluatePoissonLogL (const IModelFunction &func, const BinData &data, const double *p, int iWeight, bool extended, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy, unsigned nChunks=0)
	evaluate the Poisson LogL given a model function and the data at the point p.

void	EvaluatePoissonLogLGradient (const IModelFunction &func, const BinData &data, const double p, double grad, unsigned int &nPoints, ::ROOT::EExecutionPolicy executionPolicy=::ROOT::EExecutionPolicy::kSequential, unsigned nChunks=0)
	evaluate the Poisson LogL given a model function and the data at the point p.

unsigned	setAutomaticChunking (unsigned nEvents)

Detailed Description

namespace defining utility free functions using in Fit for evaluating the various fit method functions (chi2, likelihood, etc..) given the data and the model function

Typedef Documentation

◆ IGradModelFunction

typedef ROOT::Math::IParamMultiGradFunction ROOT::Fit::FitUtil::IGradModelFunction

Definition at line 65 of file FitUtil.h.

◆ IGradModelFunctionTempl

template<class T >

using ROOT::Fit::FitUtil::IGradModelFunctionTempl = typedef ROOT::Math::IParamMultiGradFunctionTempl<T>

Definition at line 68 of file FitUtil.h.

◆ IModelFunction

typedef ROOT::Math::IParamMultiFunction ROOT::Fit::FitUtil::IModelFunction

Definition at line 64 of file FitUtil.h.

◆ IModelFunctionTempl

template<class T >

using ROOT::Fit::FitUtil::IModelFunctionTempl = typedef ROOT::Math::IParamMultiFunctionTempl<T>

Definition at line 71 of file FitUtil.h.

Function Documentation

◆ CalculateGradientIntegral()

template<class GFunc >

void ROOT::Fit::FitUtil::CalculateGradientIntegral	(	const GFunc &	gfunc,
		const double *	x1,
		const double *	x2,
		const double *	p,
		double *	g
	)

Definition at line 202 of file FitUtil.cxx.

◆ CheckInfNaNValue()

bool ROOT::Fit::FitUtil::CheckInfNaNValue ( double & rval )

Definition at line 181 of file FitUtil.cxx.

◆ CorrectValue()

double ROOT::Fit::FitUtil::CorrectValue ( double rval )

Definition at line 167 of file FitUtil.cxx.

◆ EvaluateChi2()

double ROOT::Fit::FitUtil::EvaluateChi2	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	p,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy,
		unsigned	nChunks = `0`
	)

Chi2 Functions.

evaluate the Chi2 given a model function and the data at the point x. return also nPoints as the effective number of used points in the Chi2 evaluation

Definition at line 226 of file FitUtil.cxx.

◆ EvaluateChi2Effective()

double ROOT::Fit::FitUtil::EvaluateChi2Effective	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	x,
		unsigned int &	nPoints
	)

evaluate the effective Chi2 given a model function and the data at the point x.

The effective chi2 uses the errors on the coordinates : W = 1/(sigma_y**2 + ( sigma_x_i * df/dx_i )**2 ) return also nPoints as the effective number of used points in the Chi2 evaluation

Definition at line 425 of file FitUtil.cxx.

◆ EvaluateChi2Gradient()

void ROOT::Fit::FitUtil::EvaluateChi2Gradient	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	p,
		double *	grad,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy = `::ROOT::EExecutionPolicy::kSequential`,
		unsigned	nChunks = `0`
	)

evaluate the Chi2 gradient given a model function and the data at the point p.

return also nPoints as the effective number of used points in the Chi2 evaluation

◆ EvaluateChi2Residual()

double ROOT::Fit::FitUtil::EvaluateChi2Residual	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	p,
		unsigned int	i,
		double *	g = `nullptr`,
		double *	h = `nullptr`,
		bool	hasGrad = `false`,
		bool	useFullHessian = `false`
	)

evaluate the residual contribution to the Chi2 given a model function and the BinPoint data and if the pointer g is not null evaluate also the gradient of the residual.

evaluate the chi2 contribution (residual term) only for data with no coord-errors This function is used in the specialized least square algorithms like FUMILI or L.M.

If the function provides parameter derivatives they are used otherwise a simple derivative calculation is used

if we have error on the coordinates the residual weight depends on the function value and the approximation used by Fumili and Levenberg-Marquardt cannot be used. Also the expected error and bin integral options should not be used in this case

Definition at line 546 of file FitUtil.cxx.

◆ EvaluateLogL()

double ROOT::Fit::FitUtil::EvaluateLogL	(	const IModelFunction &	func,
		const UnBinData &	data,
		const double *	p,
		int	iWeight,
		bool	extended,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy,
		unsigned	nChunks = `0`
	)

evaluate the LogL given a model function and the data at the point x.

return also nPoints as the effective number of used points in the LogL evaluation

◆ EvaluateLogLGradient()

void ROOT::Fit::FitUtil::EvaluateLogLGradient	(	const IModelFunction &	func,
		const UnBinData &	data,
		const double *	p,
		double *	grad,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy = `::ROOT::EExecutionPolicy::kSequential`,
		unsigned	nChunks = `0`
	)

evaluate the LogL gradient given a model function and the data at the point p.

return also nPoints as the effective number of used points in the LogL evaluation

◆ EvaluatePdf()

double ROOT::Fit::FitUtil::EvaluatePdf	(	const IModelFunction &	func,
		const UnBinData &	data,
		const double *	p,
		unsigned int	ipoint,
		double *	g = `nullptr`,
		double *	h = `nullptr`,
		bool	hasGrad = `false`,
		bool	fullHessian = `false`
	)

evaluate the pdf contribution to the LogL given a model function and the BinPoint data.

If the pointer g is not null evaluate also the gradient of the pdf. If the function provides parameter derivatives they are used otherwise a simple derivative calculation is used

Definition at line 891 of file FitUtil.cxx.

◆ EvaluatePoissonBinPdf()

double ROOT::Fit::FitUtil::EvaluatePoissonBinPdf	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	x,
		unsigned int	ipoint,
		double *	g = `nullptr`,
		double *	h = `nullptr`,
		bool	hasGrad = `false`,
		bool	fullHessian = `false`
	)

evaluate the pdf contribution to the Poisson LogL given a model function and the BinPoint data.

evaluate the pdf (Poisson) contribution to the logl (return actually log of pdf) and its gradient (gradient of log(pdf))

If the pointer g is not null evaluate also the gradient of the Poisson pdf. If the function provides parameter derivatives they are used otherwise a simple derivative calculation is used

Definition at line 1297 of file FitUtil.cxx.

◆ EvaluatePoissonLogL()

double ROOT::Fit::FitUtil::EvaluatePoissonLogL	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	p,
		int	iWeight,
		bool	extended,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy,
		unsigned	nChunks = `0`
	)

evaluate the Poisson LogL given a model function and the data at the point p.

return also nPoints as the effective number of used points in the LogL evaluation By default is extended, pass extend to false if want to be not extended (MultiNomial)

◆ EvaluatePoissonLogLGradient()

void ROOT::Fit::FitUtil::EvaluatePoissonLogLGradient	(	const IModelFunction &	func,
		const BinData &	data,
		const double *	p,
		double *	grad,
		unsigned int &	nPoints,
		::ROOT::EExecutionPolicy	executionPolicy = `::ROOT::EExecutionPolicy::kSequential`,
		unsigned	nChunks = `0`
	)

evaluate the Poisson LogL given a model function and the data at the point p.

return also nPoints as the effective number of used points in the LogL evaluation

◆ setAutomaticChunking()

unsigned ROOT::Fit::FitUtil::setAutomaticChunking ( unsigned nEvents )

Definition at line 1841 of file FitUtil.cxx.

Classes

Typedefs

Functions

Detailed Description

Typedef Documentation

◆ IGradModelFunction

◆ IGradModelFunctionTempl

◆ IModelFunction

◆ IModelFunctionTempl

Function Documentation

◆ CalculateGradientIntegral()

◆ CheckInfNaNValue()

◆ CorrectValue()

◆ EvaluateChi2()

◆ EvaluateChi2Effective()

◆ EvaluateChi2Gradient()

◆ EvaluateChi2Residual()

◆ EvaluateLogL()

◆ EvaluateLogLGradient()

◆ EvaluatePdf()

◆ EvaluatePoissonBinPdf()

◆ EvaluatePoissonLogL()

◆ EvaluatePoissonLogLGradient()

◆ setAutomaticChunking()