A class for fitting histograms with functions. More...

#include <BCEfficiencyFitter.h>

Inheritance diagram for BCEfficiencyFitter:

Collaboration diagram for BCEfficiencyFitter:

Classes
class	ToyDataInterface

Public Member Functions
Constructors and destructors
	BCEfficiencyFitter ()

	BCEfficiencyFitter (const char *name)

	BCEfficiencyFitter (TH1D hist1, TH1D hist2, TF1 *func)

	BCEfficiencyFitter (const char name, TH1D hist1, TH1D hist2, TF1 func)

	~BCEfficiencyFitter ()

Member functions (get)
TH1D *	GetHistogram1 ()

TH1D *	GetHistogram2 ()

TGraphAsymmErrors *	GetHistogramRatio ()

TF1 *	GetFitFunction ()

TGraph *	GetErrorBand ()

TGraph *	GetGraphFitFunction ()

int	GetUncertainties (int n, int k, double p, double &xexp, double &xmin, double &xmax)

Member functions (set)
int	SetHistograms (TH1D hist1, TH1D hist2)

int	SetFitFunction (TF1 *func)

void	SetFlagIntegration (bool flag)

void	SetDataPointType (int type)

Member functions (miscellaneous methods)
virtual double	LogLikelihood (const std::vector< double > &parameters)

double	FitFunction (const std::vector< double > &x, const std::vector< double > &parameters)

int	Fit ()

int	Fit (TH1D hist1, TH1D hist2, TF1 *func)

void	DrawFit (const char *options="", bool flaglegend=false)

int	CalculatePValueFast (const std::vector< double > &par, BCEfficiencyFitter::ToyDataInterface *callback, double &pvalue, double &pvalueCorrected, unsigned nIterations=100000)

int	CalculatePValueFast (const std::vector< double > &par, double &pvalue, double &pvalueCorrected, unsigned nIterations=100000)

Public Member Functions inherited from BCFitter
	BCFitter ()

	BCFitter (const char *name)

	~BCFitter ()

TGraph *	GetErrorBand ()

TH2D *	GetErrorBandXY () const

TH2D *	GetErrorBandXY_yellow (double level=.68, int nsmooth=0) const

std::vector< double >	GetErrorBand (double level) const

TGraph *	GetErrorBandGraph (double level1, double level2) const

TGraph *	GetFitFunctionGraph (const std::vector< double > &parameters)

TGraph *	GetFitFunctionGraph ()

TGraph *	GetFitFunctionGraph (const std::vector< double > &parameters, double xmin, double xmax, int n=1000)

void	FixDataAxis (unsigned int index, bool fixed)

bool	GetFixedDataAxis (unsigned int index) const

void	SetFillErrorBand (bool flag=true)

void	SetErrorBandHisto (TH2D *h)

void	UnsetFillErrorBand ()

void	SetFitFunctionIndexX (int index)

void	SetFitFunctionIndexY (int index)

void	SetFitFunctionIndices (int indexx, int indexy)

void	SetErrorBandContinuous (bool flag)

int	ReadErrorBandFromFile (const char *file)

void	MCMCIterationInterface ()

void	MarginalizePreprocess ()

void	MarginalizePostprocess ()

void	FillErrorBand ()

Public Member Functions inherited from BCModel
	BCModel (const char *name="model")

	BCModel (const BCModel &bcmodel)

virtual	~BCModel ()

BCModel &	operator= (const BCModel &bcmodel)

const std::string &	GetName () const

double	GetModelAPrioriProbability () const

double	GetModelAPosterioriProbability () const

BCDataSet *	GetDataSet () const

BCDataPoint *	GetDataPointLowerBoundaries () const

BCDataPoint *	GetDataPointUpperBoundaries () const

double	GetDataPointLowerBoundary (unsigned int index) const

double	GetDataPointUpperBoundary (unsigned int index) const

bool	GetFlagBoundaries () const

unsigned	GetNDataPoints () const

BCDataPoint *	GetDataPoint (unsigned int index) const

void	SetName (const char *name)

void	SetModelAPrioriProbability (double probability)

void	SetModelAPosterioriProbability (double probability)

virtual int	AddParameter (BCParameter *parameter)

void	SetDataSet (BCDataSet *dataset)

void	SetSingleDataPoint (BCDataPoint *datapoint)

void	SetSingleDataPoint (BCDataSet *dataset, unsigned int index)

void	SetDataBoundaries (unsigned int index, double lowerboundary, double upperboundary, bool fixed=false)

void	SetDataPointLowerBoundaries (BCDataPoint *datasetlowerboundaries)

void	SetDataPointUpperBoundaries (BCDataPoint *datasetupperboundaries)

void	SetDataPointLowerBoundary (int index, double lowerboundary)

void	SetDataPointUpperBoundary (int index, double upperboundary)

int	SetPrior (int index, TF1 *f)

int	SetPrior (const char name, TF1 f)

int	SetPriorDelta (int index, double value)

int	SetPriorDelta (const char *name, double value)

int	SetPriorGauss (int index, double mean, double sigma)

int	SetPriorGauss (const char *name, double mean, double sigma)

int	SetPriorGauss (int index, double mean, double sigmadown, double sigmaup)

int	SetPriorGauss (const char *name, double mean, double sigmadown, double sigmaup)

int	SetPrior (int index, TH1 *h, bool flag=false)

int	SetPrior (const char name, TH1 h, bool flag=false)

int	SetPriorConstant (int index)

int	SetPriorConstant (const char *name)

int	SetPriorConstantAll ()

void	Copy (const BCModel &bcmodel)

double	APrioriProbability (const std::vector< double > &parameters)

virtual double	LogAPrioriProbability (const std::vector< double > &parameters)

virtual double	Likelihood (const std::vector< double > &params)

double	ProbabilityNN (const std::vector< double > &params)

double	LogProbabilityNN (const std::vector< double > &parameters)

double	Probability (const std::vector< double > &parameter)

double	LogProbability (const std::vector< double > &parameter)

virtual double	SamplingFunction (const std::vector< double > &parameters)

double	Eval (const std::vector< double > &parameters)

virtual double	LogEval (const std::vector< double > &parameters)

virtual void	CorrelateDataPointValues (std::vector< double > &x)

double	GetPvalueFromChi2 (const std::vector< double > &par, int sigma_index)

double	GetPvalueFromKolmogorov (const std::vector< double > &par, int index)

double	GetPvalueFromChi2NDoF (std::vector< double > par, int sigma_index)

BCH1D *	CalculatePValue (std::vector< double > par, bool flag_histogram=false)

double	GetPValue ()

double	GetPValueNDoF ()

double	GetChi2NDoF ()

std::vector< double >	GetChi2Runs (int dataIndex, int sigmaIndex)

void	SetGoFNIterationsMax (int n)

void	SetGoFNIterationsRun (int n)

void	SetGoFNChains (int n)

double	HessianMatrixElement (const BCParameter parameter1, const BCParameter parameter2, std::vector< double > point)

void	PrintSummary ()

void	PrintResults (const char *file)

void	PrintShortFitSummary (int chi2flag=0)

void	PrintHessianMatrix (std::vector< double > parameters)

virtual double	CDF (const std::vector< double > &, int, bool)

Additional Inherited Members
Protected Attributes inherited from BCFitter
TH2D *	fErrorBandXY

Protected Attributes inherited from BCModel
std::string	fName

double	fModelAPriori

double	fModelAPosteriori

BCDataSet *	fDataSet

BCDataPoint *	fDataPointLowerBoundaries

BCDataPoint *	fDataPointUpperBoundaries

std::vector< bool >	fDataFixedValues

double	fPValue

double	fChi2NDoF

double	fPValueNDoF

bool	flag_discrete

int	fGoFNIterationsMax

int	fGoFNIterationsRun

int	fGoFNChains

std::vector< TNamed * >	fPriorContainer

bool	fPriorConstantAll

std::vector< bool >	fPriorContainerConstant

std::vector< bool >	fPriorContainerInterpolate

Detailed Description

A class for fitting histograms with functions.

Author: Daniel Kollar; Kevin Kröninger

Version: 1.0

Date: 11.2008 This class allows fitting of efficiencies defined as a ratio of two TH1D histograms using a TF1 function. It uses binomial probabilities calculated based on the number of entries in histograms. This is only applicable if the numerator is a subset of the denominator.

Definition at line 39 of file BCEfficiencyFitter.h.

Constructor & Destructor Documentation

BCEfficiencyFitter::BCEfficiencyFitter ( )

The default constructor.

Definition at line 32 of file BCEfficiencyFitter.cxx.

BCEfficiencyFitter::BCEfficiencyFitter ( const char * name )

Constructor

Parameters

name	name fo the model

Definition at line 49 of file BCEfficiencyFitter.cxx.

BCEfficiencyFitter::BCEfficiencyFitter	(	TH1D *	hist1,
		TH1D *	hist2,
		TF1 *	func
	)

A constructor.

Parameters

hist1	The histogram with the larger numbers
hist2	The histogram with the smaller numbers
func	The fit function.

Definition at line 66 of file BCEfficiencyFitter.cxx.

BCEfficiencyFitter::BCEfficiencyFitter	(	const char *	name,
		TH1D *	hist1,
		TH1D *	hist2,
		TF1 *	func
	)

Constructor.

Parameters

name	name fo the model
hist1	The histogram with the larger numbers
hist2	The histogram with the smaller numbers
func	The fit function.

Definition at line 85 of file BCEfficiencyFitter.cxx.

BCEfficiencyFitter::~BCEfficiencyFitter ( )

The default destructor.

Definition at line 211 of file BCEfficiencyFitter.cxx.

Member Function Documentation

int BCEfficiencyFitter::CalculatePValueFast	(	const std::vector< double > &	par,
		BCEfficiencyFitter::ToyDataInterface *	callback,
		double &	pvalue,
		double &	pvalueCorrected,
		unsigned	nIterations = `100000`
	)

Calculate the p-value using fast-MCMC. In every iteration, a new toy data set is created. By providing a suitable implementation of ToyDataInterface, the user can calculate the distribution of an arbitrary statistic. Each toy data set as well as the expected values for the parameter values are passed on to the interface.

Parameters

par	A set of parameter values
pvalue	The p-value for the default likelihood statistic
pvalueCorrected	The p-value for the default likelihood statistic with corrections for DoF to reduce fitting bias, in all nonpathological cases the correction lowers the p-value.
callback	requires class with operator(...) defined.
nIterations	number of toy data sets generated by the Markov chain

Returns: An error code

Definition at line 451 of file BCEfficiencyFitter.cxx.

int BCEfficiencyFitter::CalculatePValueFast	(	const std::vector< double > &	par,
		double &	pvalue,
		double &	pvalueCorrected,
		unsigned	nIterations = `100000`
	)

Calculate the p-value using fast-MCMC.

Parameters

par	A set of parameter values
pvalue	The pvalue
pvalueCorrected	The p-value for the default likelihood statistic with corrections for DoF to reduce fitting bias
nIterations	number of pseudo experiments generated by the Markov chain

Returns: An error code

Definition at line 443 of file BCEfficiencyFitter.cxx.

void BCEfficiencyFitter::DrawFit	(	const char *	options = `""`,
		bool	flaglegend = `false`
	)

virtual

Draw the fit in the current pad.

Implements BCFitter.

Definition at line 349 of file BCEfficiencyFitter.cxx.

int BCEfficiencyFitter::Fit ( )

virtual

Performs the fit.

Returns: An error code.

Implements BCFitter.

Definition at line 309 of file BCEfficiencyFitter.cxx.

int BCEfficiencyFitter::Fit	(	TH1D *	hist1,
		TH1D *	hist2,
		TF1 *	func
	)

Performs the fit.

Parameters

hist1	The histogram with the larger number.
hist2	The histogram with the smaller number.
func	The fit function.

Returns: An error code.

Definition at line 286 of file BCEfficiencyFitter.cxx.

double BCEfficiencyFitter::FitFunction	(	const std::vector< double > &	x,
		const std::vector< double > &	parameters
	)

virtual

Returns the y-value of the 1-dimensional fit function at an x and for a set of parameters.

Parameters

x	A vector with the x-value.
parameters	A set of parameters.

Reimplemented from BCFitter.

Definition at line 276 of file BCEfficiencyFitter.cxx.

TGraph* BCEfficiencyFitter::GetErrorBand ( )

inline

Returns: pointer to the error band

Definition at line 120 of file BCEfficiencyFitter.h.

TF1* BCEfficiencyFitter::GetFitFunction ( )

inline

Returns: The fit function

Definition at line 115 of file BCEfficiencyFitter.h.

TGraph* BCEfficiencyFitter::GetGraphFitFunction ( )

inline

Returns: pointer to a graph for the fit function

Definition at line 125 of file BCEfficiencyFitter.h.

TH1D* BCEfficiencyFitter::GetHistogram1 ( )

inline

Returns: The histogram 1

Definition at line 100 of file BCEfficiencyFitter.h.

TH1D* BCEfficiencyFitter::GetHistogram2 ( )

inline

Returns: The histogram 2

Definition at line 105 of file BCEfficiencyFitter.h.

TGraphAsymmErrors* BCEfficiencyFitter::GetHistogramRatio ( )

inline

Returns: The histogram ratio

Definition at line 110 of file BCEfficiencyFitter.h.

int BCEfficiencyFitter::GetUncertainties	(	int	n,
		int	k,
		double	p,
		double &	xexp,
		double &	xmin,
		double &	xmax
	)

Calculates the central value and the lower and upper limits for a given probability.

Parameters

n	n for the binomial.
k	k for the binomial.
p	The central probability defining the limits.
xmin	The central value.
xmin	The lower limit.
xmax	The upper limit.

Returns: A flag (=1 plot point, !=1 do not plot point).

Definition at line 576 of file BCEfficiencyFitter.cxx.

double BCEfficiencyFitter::LogLikelihood ( const std::vector< double > & parameters )

virtual

The log of the prior probability. Overloaded from BCModel.

Parameters

parameters	A vector of doubles containing the parameter values. The log of the conditional probability. Overloaded from BCModel.
parameters	A vector of doubles containing the parameter values.

Implements BCModel.

Definition at line 230 of file BCEfficiencyFitter.cxx.

void BCEfficiencyFitter::SetDataPointType ( int type )

Set type of point to be used to plot the efficiency data 0 - mean + rms 1 - mode + smallest 68% 2 - median + central 68%

Definition at line 220 of file BCEfficiencyFitter.cxx.

int BCEfficiencyFitter::SetFitFunction ( TF1 * func )

Parameters

func	The fit function

Returns: An error code (1:pass, 0:fail).

Definition at line 171 of file BCEfficiencyFitter.cxx.

void BCEfficiencyFitter::SetFlagIntegration ( bool flag )

inline

Sets the flag for integration.
true: use ROOT's TH1D::Integrate()
false: use linear interpolation

Definition at line 158 of file BCEfficiencyFitter.h.

int BCEfficiencyFitter::SetHistograms	(	TH1D *	hist1,
		TH1D *	hist2
	)

Parameters

hist	The histogram 1
hist	The histogram 2

Returns: An error code (1:pass, 0:fail).

Definition at line 105 of file BCEfficiencyFitter.cxx.

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

/home/beaujean/workspace/bat/models/base/BCEfficiencyFitter.h
/home/beaujean/workspace/bat/models/base/BCEfficiencyFitter.cxx

Classes

Public Member Functions

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation