#include <AdaptiveKernelDensity.hh>

Inheritance diagram for AdaptiveKernelDensity:

Public Member Functions
	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, UInt_t bins1, Double_t width1, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 1-dimensional adaptive kernel PDF from the sample of points in an NTuple. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char weight, UInt_t bins1, Double_t width1, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 1-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, UInt_t bins1, UInt_t bins2, Double_t width1, Double_t width2, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 2-dimensional adaptive kernel PDF from the sample of points in an NTUple. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char weight, UInt_t bins1, UInt_t bins2, Double_t width1, Double_t width2, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 2-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, UInt_t bins1, UInt_t bins2, UInt_t bins3, Double_t width1, Double_t width2, Double_t width3, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 3-dimensional adaptive kernel PDF from the sample of points in an NTuple. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, const char weight, UInt_t bins1, UInt_t bins2, UInt_t bins3, Double_t width1, Double_t width2, Double_t width3, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 3-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, const char vars4, UInt_t bins1, UInt_t bins2, UInt_t bins3, UInt_t bins4, Double_t width1, Double_t width2, Double_t width3, Double_t width4, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 4-dimensional adaptive kernel PDF from the sample of points in an NTuple. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, const char vars4, const char weight, UInt_t bins1, UInt_t bins2, UInt_t bins3, UInt_t bins4, Double_t width1, Double_t width2, Double_t width3, Double_t width4, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 4-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, const char vars4, const char vars5, UInt_t bins1, UInt_t bins2, UInt_t bins3, UInt_t bins4, UInt_t bins5, Double_t width1, Double_t width2, Double_t width3, Double_t width4, Double_t width5, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 5-dimensional adaptive kernel PDF from the sample of points in an NTuple. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, const char vars1, const char vars2, const char vars3, const char vars4, const char vars5, const char weight, UInt_t bins1, UInt_t bins2, UInt_t bins3, UInt_t bins4, UInt_t bins5, Double_t width1, Double_t width2, Double_t width3, Double_t width4, Double_t width5, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for 5-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight. More...

	AdaptiveKernelDensity (const char pdfName, AbsPhaseSpace thePhaseSpace, TTree tree, std::vector< TString > &vars, std::vector< UInt_t > &binning, std::vector< Double_t > &width, AbsDensity widthScale, AbsDensity *approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Constructor for adaptive kernel PDF of arbitrary dimensionality from the sample of points in an NTUple. More...

virtual	~AdaptiveKernelDensity ()
	Destructor. More...

void	writeToFile (const char *fileName)
	Write density map to file depending on extension. More...

void	writeToTextFile (const char *fileName)
	Write the binned PDF to a text file. More...

void	writeToRootFile (const char *fileName)
	Write the binned density into a ROOT file. More...

Double_t	density (std::vector< Double_t > &x)
	Calculate PDF density at the point. Multilinear binned interpolation is used which is calculated in the constructor, so this call is fast. More...

AbsPhaseSpace *	phaseSpace ()
	Return the phase space. More...

void	setFractionalMode (Bool_t mode=true)
	Set fractional mode of operation. More...

void	normalise (void)
	Normalise the PDF such that the average PDF value over the allowed phase space equals to 1. More...

Public Member Functions inherited from AbsDensity
	AbsDensity (const char *pdfName)
	Constructor. More...

virtual	~AbsDensity ()
	Destructor. More...

void	slice (std::vector< Double_t > &x, UInt_t num, TH1F *hist)
	Calculate 1D slice of the PDF. More...

void	slice (std::vector< Double_t > &x, UInt_t numx, UInt_t numy, TH2F *hist, Bool_t inPhaseSpace=true)
	Calculate 2D slice of the PDF. More...

double	transform (TH1F hist1, TH1F hist2, double x)

void	project (TH1F *hist)
	Calculate projection of the 1D PDF. More...

void	project (TH2F *hist, Bool_t inPhaseSpace=true)
	Calculate projection of the 2D PDF. More...

void	setMajorant (Double_t majorant)
	Set majorant for accept-reject method. More...

void	setMaxTries (UInt_t maxTries)
	Set maximum number of tries for accept-reject method. More...

Double_t	generate (std::vector< Double_t > &x)
	Generate a single point within the phase space according to the PDF using accept-reject method. More...

void	generate (TNtuple *tree, UInt_t numEvents)
	Generate a sample of points within the phase space according to the PDF using accept-reject method. More...

const char *	name (void)
	Return the name of the PDF. More...

void	setSeed (UInt_t seed=0)
	Set random seed. More...

Private Member Functions
void	init (AbsPhaseSpace thePhaseSpace, TTree tree, std::vector< TString > &vars, std::vector< UInt_t > &binning, std::vector< Double_t > &width, AbsDensity widthScale, AbsDensity approx=0, UInt_t toyEvents=0, UInt_t maxEvents=0, UInt_t skipEvents=0)
	Common initialise method used by all constructors. More...

UInt_t	iterToIndex (std::vector< UInt_t > &iter)
	Convert an N-dimensional iterator vector into a linear bin index in the bin map. More...

void	addToMap (std::vector< Double_t > &map, std::vector< Double_t > &point, Double_t widthScale=1., Double_t weight=1.)
	Add a kernel density of a single data point to the binned map. More...

void	fillMapFromTree (TTree *tree, std::vector< TString > &vars, UInt_t maxEvents=0, UInt_t skipEvents=0)

void	fillMapFromDensity (AbsDensity *theDensity, UInt_t toyEvents=0)

Double_t	mapDensity (std::vector< Double_t > &map, std::vector< Double_t > &x)
	Calculate the raw density using the binned map (estimated or approximation) at a given point. More...

Private Attributes
std::vector< Double_t >	m_map
	Bin map of estimated PDF. More...

std::vector< Double_t >	m_approxMap
	Bin map of approximation PDF convolved with the kernel. More...

std::vector< UInt_t >	m_binning
	Vector of bin numbers in each variable. More...

AbsPhaseSpace *	m_phaseSpace
	Reference to phase space. More...

AbsDensity *	m_approxDensity
	Reference to approximation PDF. More...

AbsDensity *	m_widthScaleDensity
	Reference to PDF used for kernel width scaling. More...

std::vector< Double_t >	m_width
	Vector of kernel widths. More...

UInt_t	m_dim
	Cached dimensionality of the phase space. More...

Bool_t	m_fractionalMode
	Fractional mode flag. More...

Double_t	m_minValue
	Minimum value of the width scale PDF to be used for scaling. More...

Double_t	m_maxValue
	Maximum value of the width scale PDF to be used for scaling. More...

Double_t	m_minScale
	Minimum width scale factor. More...

Double_t	m_maxScale
	Maximum width scale factor. More...

Additional Inherited Members
Protected Attributes inherited from AbsDensity
char	m_name [256]
	PDF name. More...

Double_t	m_majorant
	PDF majorant (maximum PDF value needed for accept-reject). More...

UInt_t	m_maxTries
	Maximum number of tries for accept-reject method. More...

TRandom3	m_rnd
	Random number generator. More...

Detailed Description

A class to calculate the binned multidimensional density using adaptive kernel estimation technique with approximation PDF.

Definition at line 14 of file AdaptiveKernelDensity.hh.

Constructor & Destructor Documentation

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		UInt_t	bins1,
		Double_t	width1,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 1-dimensional adaptive kernel PDF from the sample of points in an NTuple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	variable name
[in]	bins1	number of bins for the binned interpolation
[in]	width1	average kernel width
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 35 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	weight,
		UInt_t	bins1,
		Double_t	width1,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 1-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	variable name
[in]	weight	weight variable name
[in]	bins1	number of bins for the binned interpolation
[in]	width1	average kernel width
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 59 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		UInt_t	bins1,
		UInt_t	bins2,
		Double_t	width1,
		Double_t	width2,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 2-dimensional adaptive kernel PDF from the sample of points in an NTUple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 85 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	weight,
		UInt_t	bins1,
		UInt_t	bins2,
		Double_t	width1,
		Double_t	width2,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 2-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	weight	weight variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 112 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 3-dimensional adaptive kernel PDF from the sample of points in an NTuple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 141 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		const char *	weight,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 3-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	weight	weight variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 171 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		const char *	vars4,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		UInt_t	bins4,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		Double_t	width4,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 4-dimensional adaptive kernel PDF from the sample of points in an NTuple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	vars4	4th variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	bins4	number of bins for the 4th variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	width4	average kernel width for the 4th variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 203 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		const char *	vars4,
		const char *	weight,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		UInt_t	bins4,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		Double_t	width4,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 4-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	vars4	4th variable name
[in]	weight	weight variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	bins4	number of bins for the 4th variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	width4	average kernel width for the 4th variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 236 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		const char *	vars4,
		const char *	vars5,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		UInt_t	bins4,
		UInt_t	bins5,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		Double_t	width4,
		Double_t	width5,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 5-dimensional adaptive kernel PDF from the sample of points in an NTuple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	vars4	4th variable name
[in]	vars5	5th variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	bins4	number of bins for the 4th variable for the binned interpolation
[in]	bins5	number of bins for the 5th variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	width4	average kernel width for the 4th variable
[in]	width5	average kernel width for the 5th variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 271 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		const char *	vars1,
		const char *	vars2,
		const char *	vars3,
		const char *	vars4,
		const char *	vars5,
		const char *	weight,
		UInt_t	bins1,
		UInt_t	bins2,
		UInt_t	bins3,
		UInt_t	bins4,
		UInt_t	bins5,
		Double_t	width1,
		Double_t	width2,
		Double_t	width3,
		Double_t	width4,
		Double_t	width5,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for 5-dimensional adaptive kernel PDF from the sample of points in an NTuple with weight.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars1	1st variable name
[in]	vars2	2nd variable name
[in]	vars3	3rd variable name
[in]	vars4	4th variable name
[in]	vars5	5th variable name
[in]	weight	weight variable name
[in]	bins1	number of bins for the 1st variable for the binned interpolation
[in]	bins2	number of bins for the 2nd variable for the binned interpolation
[in]	bins3	number of bins for the 3rd variable for the binned interpolation
[in]	bins4	number of bins for the 4th variable for the binned interpolation
[in]	bins5	number of bins for the 5th variable for the binned interpolation
[in]	width1	average kernel width for the 1st variable
[in]	width2	average kernel width for the 2nd variable
[in]	width3	average kernel width for the 3rd variable
[in]	width4	average kernel width for the 4th variable
[in]	width5	average kernel width for the 5th variable
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 307 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::AdaptiveKernelDensity	(	const char *	pdfName,
		AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		std::vector< TString > &	vars,
		std::vector< UInt_t > &	binning,
		std::vector< Double_t > &	width,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

Constructor for adaptive kernel PDF of arbitrary dimensionality from the sample of points in an NTUple.

Parameters

[in]	pdfName	PDF name
[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars	vector of variable names. The size of vector should match the dimensionality of phase space or be one larger.
[in]	binning	vector of numbers of bins for the binned interpolation. The size of vector should match the dimensionality of phase space.
[in]	width	vector of average kernel widths. The size of vector should match the dimensionality of phase space.
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 20 of file AdaptiveKernelDensity.cpp.

AdaptiveKernelDensity::~AdaptiveKernelDensity ( )

virtual

Destructor.

Definition at line 346 of file AdaptiveKernelDensity.cpp.

Member Function Documentation

void AdaptiveKernelDensity::addToMap	(	std::vector< Double_t > &	map,
		std::vector< Double_t > &	point,
		Double_t	widthScale = `1.`,
		Double_t	weight = `1.`
	)

private

Add a kernel density of a single data point to the binned map.

Parameters

[in]	map	pointer to the binned map
[in]	point	data point coordinates
[in]	widthScale	kernel width scale factor
[in]	weight	point weight

Definition at line 429 of file AdaptiveKernelDensity.cpp.

Double_t AdaptiveKernelDensity::density ( std::vector< Double_t > & x )

virtual

Calculate PDF density at the point. Multilinear binned interpolation is used which is calculated in the constructor, so this call is fast.

Parameters

[in] x point

Returns: PDF value

Implements AbsDensity.

Definition at line 1072 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::fillMapFromDensity	(	AbsDensity *	theDensity,
		UInt_t	toyEvents = `0`
	)

private

Definition at line 615 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::fillMapFromTree	(	TTree *	tree,
		std::vector< TString > &	vars,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

private

Definition at line 528 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::init	(	AbsPhaseSpace *	thePhaseSpace,
		TTree *	tree,
		std::vector< TString > &	vars,
		std::vector< UInt_t > &	binning,
		std::vector< Double_t > &	width,
		AbsDensity *	widthScale,
		AbsDensity *	approx = `0`,
		UInt_t	toyEvents = `0`,
		UInt_t	maxEvents = `0`,
		UInt_t	skipEvents = `0`
	)

private

Common initialise method used by all constructors.

Initialise method used by all constructors.

Parameters

[in]	thePhaseSpace	phase space
[in]	tree	ROOT NTuple
[in]	vars	vector of variable names. The size of vector should match the dimensionality of phase space.
[in]	binning	vector of numbers of bins for the binned interpolation. The size of vector should match the dimensionality of phase space.
[in]	width	vector of average kernel widths. The size of vector should match the dimensionality of phase space.
[in]	widthScale	PDF for width scaling
[in]	approx	approximation PDF. Uniform approximation is used for approx=0
[in]	toyEvents	number of toy events for MC convolution of the approximation PDF. Use binned convolution if toyEvents=0
[in]	maxEvents	maximum number of events to read from NTuple. Read all events if maxEvents=0
[in]	skipEvents	number of NTuple events to skip from the beginning

Definition at line 352 of file AdaptiveKernelDensity.cpp.

UInt_t AdaptiveKernelDensity::iterToIndex ( std::vector< UInt_t > & iter )

private

Convert an N-dimensional iterator vector into a linear bin index in the bin map.

Calculate map index for a given iterator vector.

Parameters

[in] iter iterator vector

Returns: bin index in the map

Definition at line 416 of file AdaptiveKernelDensity.cpp.

Double_t AdaptiveKernelDensity::mapDensity	(	std::vector< Double_t > &	map,
		std::vector< Double_t > &	x
	)

private

Calculate the raw density using the binned map (estimated or approximation) at a given point.

Parameters

[in]	map	reference to the bin map
[in]	x	point

Definition at line 971 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::normalise ( void )

Normalise the PDF such that the average PDF value over the allowed phase space equals to 1.

Normalise density to have the average PDF value over the allowed phase space equal to 1 In addition, determine the maximum value of the PDF to be use as a majorant for toy MC generation.

Definition at line 898 of file AdaptiveKernelDensity.cpp.

AbsPhaseSpace* AdaptiveKernelDensity::phaseSpace ( )

inlinevirtual

Return the phase space.

Returns: phase space

Implements AbsDensity.

Definition at line 418 of file AdaptiveKernelDensity.hh.

void AdaptiveKernelDensity::setFractionalMode ( Bool_t mode = true )

inline

Set fractional mode of operation.

Parameters

mode	If mode==true, the density returned will be the ratio of the kernel and approximation density.

Definition at line 424 of file AdaptiveKernelDensity.hh.

void AdaptiveKernelDensity::writeToFile ( const char * fileName )

Write density map to file depending on extension.

Write the binned PDF to a file. Can be used later by BinnedDensity. Format of the file (text or ROOT) is decided based on the extension of the file name.

Parameters

[in] fileName file name

Definition at line 739 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::writeToRootFile ( const char * fileName )

Write the binned density into a ROOT file.

Write density map to a ROOT file.

Parameters

[in] fileName output ROOT file name

Definition at line 814 of file AdaptiveKernelDensity.cpp.

void AdaptiveKernelDensity::writeToTextFile ( const char * fileName )

Write the binned PDF to a text file.

Write density map to file.

Parameters

[in] fileName file name

Definition at line 751 of file AdaptiveKernelDensity.cpp.

Member Data Documentation

AbsDensity* AdaptiveKernelDensity::m_approxDensity

private

Reference to approximation PDF.

Definition at line 498 of file AdaptiveKernelDensity.hh.

std::vector<Double_t> AdaptiveKernelDensity::m_approxMap

private

Bin map of approximation PDF convolved with the kernel.

Definition at line 489 of file AdaptiveKernelDensity.hh.

std::vector<UInt_t> AdaptiveKernelDensity::m_binning

private

Vector of bin numbers in each variable.

Definition at line 492 of file AdaptiveKernelDensity.hh.

UInt_t AdaptiveKernelDensity::m_dim

private

Cached dimensionality of the phase space.

Definition at line 507 of file AdaptiveKernelDensity.hh.

Bool_t AdaptiveKernelDensity::m_fractionalMode

private

Fractional mode flag.

Definition at line 510 of file AdaptiveKernelDensity.hh.

std::vector<Double_t> AdaptiveKernelDensity::m_map

private

Bin map of estimated PDF.

Definition at line 486 of file AdaptiveKernelDensity.hh.

Double_t AdaptiveKernelDensity::m_maxScale

private

Maximum width scale factor.

Definition at line 522 of file AdaptiveKernelDensity.hh.

Double_t AdaptiveKernelDensity::m_maxValue

private

Maximum value of the width scale PDF to be used for scaling.

Definition at line 516 of file AdaptiveKernelDensity.hh.

Double_t AdaptiveKernelDensity::m_minScale

private

Minimum width scale factor.

Definition at line 519 of file AdaptiveKernelDensity.hh.

Double_t AdaptiveKernelDensity::m_minValue

private

Minimum value of the width scale PDF to be used for scaling.

Definition at line 513 of file AdaptiveKernelDensity.hh.

AbsPhaseSpace* AdaptiveKernelDensity::m_phaseSpace

private

Reference to phase space.

Definition at line 495 of file AdaptiveKernelDensity.hh.

std::vector<Double_t> AdaptiveKernelDensity::m_width

private

Vector of kernel widths.

Definition at line 504 of file AdaptiveKernelDensity.hh.

AbsDensity* AdaptiveKernelDensity::m_widthScaleDensity

private

Reference to PDF used for kernel width scaling.

Definition at line 501 of file AdaptiveKernelDensity.hh.

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

inc/AdaptiveKernelDensity.hh
src/AdaptiveKernelDensity.cpp

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation