BinSampler samples XCombs bins. This default implementation performs flat MC integration. More...

#include <BinSampler.h>

Inheritance diagram for Herwig::BinSampler:

[legend]

Classes
struct	NextIteration
	Exception to be thrown if cross section information should be updated. More...

struct	RandomNumberHistogram
	Define the key for the collinear subtraction data. More...

Public Types
typedef pair< string, size_t >	RandomNumberIndex

Public Types inherited from ThePEG::InterfacedBase
enum	InitState

Public Types inherited from ThePEG::Pointer::ReferenceCounted
typedef unsigned int	CounterType

Public Member Functions
	BinSampler ()
	The default constructor.

Ptr< BinSampler >::ptr	cloneMe () const
	Clone this object.

double	evaluate (vector< double > p, bool remap=true)
	Evaluate the cross section.

double	bias () const
	Return the bias with which this sampler is selected.

void	bias (double b)
	Set the bias with which this sampler is selected.

void	eventHandler (tStdEHPtr eh)
	Set the event handler.

tStdEHPtr	eventHandler () const
	Return the event handler.

void	sampler (Ptr< GeneralSampler >::tptr)
	Set the containing sampler.

Ptr< GeneralSampler >::tptr	sampler () const
	Get the containing sampler.

int	bin () const
	Return the bin.

void	bin (int b)
	Set the bin.

string	process () const
	Return a string describing the process handled by this sampler.

string	shortprocess () const
	Return a short string describing the process handled by this sampler.

string	id () const
	Return a string identifying the process handled by this sampler.

const vector< double > &	lastPoint () const
	Return the last generated point.

vector< double > &	lastPoint ()
	Access the last generated point.

double	referenceWeight () const
	Return the reference weight to be used.

void	referenceWeight (double w)
	Set the reference weight to be used.

virtual bool	canUnweight () const
	Return true, if this sampler can provide unweighted events; if the proposal density is not an overestimate, weights larger than one can be generated, the handling of these points being subject to the GeneralSampler class.

virtual bool	adaptsOnTheFly () const
	Return true, if this sampler adapts on the fly while generating events.

virtual bool	compensating () const
	If this sampler features a compensation algorithm, return true if more events need to be generated to finish the compensation.

bool	weighted () const
	Return true, if weighted events should be generated.

void	doWeighted (bool yes=true)
	Indicate that weighted events should be generated.

virtual double	generate ()
	Generate the next point and return its weight; store the point in lastPoint().

void	fillRemappers (bool progress)
	Fill and finalize the remappers present.

void	saveRemappers () const
	Write remappers to grid file.

void	saveIntegrationData () const
	Write integration data to grid files.

virtual void	saveGrid () const
	Save grid data.

void	readIntegrationData ()
	Read integration data from grid files.

void	setupRemappers (bool progress)
	Read remappers from grid file.

void	runIteration (unsigned long n, bool progress)
	Run a single iteration of n points, optionally printing a progress bar to cout.

virtual void	adapt ()
	Adapt this sampler after an iteration has been run.

virtual void	initialize (bool progress)
	Initialize this bin sampler.

bool	initialized () const
	Return true, if this sampler has already been initialized.

void	isInitialized ()
	Indicate that this sampler has already been initialized.

bool	integrated () const
	Return true, if integration has already been performed.

bool	remappersFilled () const
	Return true, if remappers have been set up.

virtual bool	existsGrid () const
	Return true, if grid data exists for this sampler.

bool	hasGrids () const
	Return true, if this sampler has already read grid data.

void	didReadGrids ()
	Indicate that this sampler has already read grid data.

virtual void	finalize (bool)
	Finalize this sampler.

virtual CrossSection	integratedXSec () const
	Return the total integrated cross section determined from the Monte Carlo sampling so far.

virtual CrossSection	integratedXSecErr () const
	Return the error on the total integrated cross section determined from the Monte Carlo sampling so far.

int	dimension () const
	Return the dimension.

unsigned long	initialPoints () const
	Return the number of points to be used for initial integration.

void	initialPoints (unsigned long n)
	Set the number of points to be used for initial integration.

size_t	nIterations () const
	Return the number of iterations to be considered for initialization.

void	nIterations (size_t n)
	Set the number of iterations to be considered for initialization.

void	enhancementFactor (double f)
	Set the factor to enhance the number of points for the next iteration.

double	enhancementFactor () const
	Return the factor to enhance the number of points for the next iteration.

string	randomNumberString () const
	Return the folder for the random number plots.

double	kappa () const
	In the AlmostUnweighted mode we do not need to unweight the events to the reference weight.

Public Member Functions inherited from Herwig::MultiIterationStatistics
	MultiIterationStatistics ()
	The default constructor.

virtual	~MultiIterationStatistics ()
	The destructor.

void	nextIteration ()
	Indicate the start of a new iteration.

const vector< GeneralStatistics > &	iterations () const
	Return the iterations done so far.

vector< GeneralStatistics > &	iterations ()
	Access the iterations done so far.

virtual double	chi2 () const
	Return the last calculated chi^2.

virtual double	averageWeight (bool useAll=false) const
	Return the average weight.

virtual double	averageAbsWeight (bool useAll=false) const
	Return the average absolute weight.

virtual double	averageWeightVariance (bool useAll=false) const
	Return the variance of the average weight.

virtual double	averageAbsWeightVariance (bool useAll=false) const
	Return the variance of the average absolute weight.

unsigned int	minIterationPoints () const
	Return the minimum number of events per iteration to take this iteration into account when calculating the total cross section.

void	minIterationPoints (unsigned int n)
	Set the minimum number of events per iteration to take this iteration into account when calculating the total cross section.

bool	useAllIterations () const
	Return true if integrals should be combined from all iterations.

void	doUseAllIterations (bool yes=true)
	Indicate that integrals should be combined from all iterations.

void	put (PersistentOStream &os) const
	Function used to write out object persistently.

void	get (PersistentIStream &is)
	Function used to read in object persistently.

void	persistentOutput (PersistentOStream &os) const
	Function used to write out object persistently.

void	persistentInput (PersistentIStream &is, int version)
	Function used to read in object persistently.

void	fromXML (const XML::Element &)
	Fill statistics data from an XML element.

XML::Element	toXML () const
	Return an XML element for the data of this statistics.

Public Member Functions inherited from ThePEG::Interfaced
virtual bool	defaultInit ()

PPtr	getParticle (PID) const

PDPtr	getParticleData (PID) const

bool	used () const

void	useMe () const

tEGPtr	generator () const

void	persistentOutput (PersistentOStream &os) const

void	persistentInput (PersistentIStream &is, int version)

PPtr	getParticle (PID) const

PDPtr	getParticleData (PID) const

bool	used () const

void	useMe () const

tEGPtr	generator () const

Public Member Functions inherited from ThePEG::InterfacedBase
string	fullName () const

string	name () const

string	path () const

string	comment () const

void	setup (istream &is)

void	update ()

void	init ()

virtual bool	preInitialize () const

void	initrun ()

void	finish ()

void	touch ()

void	reset ()

void	clear ()

InitState	state () const

bool	locked () const

bool	touched () const

virtual IBPtr	fullclone () const

void	persistentOutput (PersistentOStream &os) const

void	persistentInput (PersistentIStream &is, int version)

virtual void	debugme () const

void	update ()

void	init ()

virtual bool	preInitialize () const

void	initrun ()

void	finish ()

void	touch ()

void	reset ()

void	clear ()

InitState	state () const

bool	locked () const

bool	touched () const

virtual IBPtr	fullclone () const

Public Member Functions inherited from ThePEG::Base
void	debug () const

virtual void	debugme () const

Public Member Functions inherited from ThePEG::Pointer::ReferenceCounted
CounterType	referenceCount () const

Public Member Functions inherited from ThePEG::Named
	Named (const string &newName=string())

	Named (const Named &)=default

const string &	name () const

bool	operator== (const Named &other) const

bool	operator< (const Named &other) const

Public Member Functions inherited from Herwig::GeneralStatistics
	GeneralStatistics ()
	The default constructor.

virtual	~GeneralStatistics ()
	The destructor.

void	reset ()
	Reset these statistics.

double	lastWeight () const
	Return the last weight encountered.

double	maxWeight () const
	Return the maximum absolute weight.

double	minWeight () const
	Return the minimum absolute weight.

void	maxWeight (double w)
	Set the maximum absolute weight.

void	minWeight (double w)
	Set the minimum absolute weight.

double	sumWeights () const
	Return the sum of weights.

double	sumSquaredWeights () const
	Return the sum of squared weights.

double	sumAbsWeights () const
	Return the sum of absolute weights.

unsigned long	selectedPoints () const
	Return the number of selected points.

unsigned long	acceptedPoints () const
	Return the nnumber of accepted points.

unsigned long	nanPoints () const
	Return the number of points where a nan or inf weight has been encountered.

unsigned long	allPoints () const
	Return the number of all points.

virtual double	averageWeight () const
	Return the average weight.

virtual double	averageAbsWeight () const
	Return the average absolute weight.

double	weightVariance () const
	Return the variance of weights.

double	absWeightVariance () const
	Return the variance of absolute weights.

virtual double	averageWeightVariance () const
	Return the variance of the average weight.

virtual double	averageAbsWeightVariance () const
	Return the variance of the average absolute weight.

virtual void	select (double weight, bool doIntegral=true)
	Select an event.

virtual void	accept ()
	Accept an event.

virtual void	reject ()
	Reject an event.

void	put (PersistentOStream &os) const
	Function used to write out object persistently.

void	get (PersistentIStream &is)
	Function used to read in object persistently.

void	fromXML (const XML::Element &)
	Fill statistics data from an XML element.

XML::Element	toXML () const
	Return an XML element for the data of this statistics.

Public Attributes
map< RandomNumberIndex, pair< RandomNumberHistogram, double > >	RandomNumberHistograms

Public Attributes inherited from ThePEG::InterfacedBase
	initializing

	uninitialized

	initialized

	runready

Public Attributes inherited from ThePEG::Pointer::ReferenceCounted
const unsigned long	uniqueId

Clone Methods.
double	theBias
	The bias with which this sampler is selected.

bool	theWeighted
	True, if weighted events should be generated.

unsigned long	theInitialPoints
	The number of points to use for initial integration.

size_t	theNIterations
	The number of iterations to be considered for initialization.

double	theEnhancementFactor
	Factor to enhance the number of points for the next iteration.

bool	theNonZeroInPresampling
	Switch to count only non zero weights in presampling.

bool	theHalfPoints
	Switch to require that we get half of the points in each iteration below the maximum weight of the iteration.

int	theMaxNewMax
	The maximum number of allowed new maxima, in combination with HalfPoints, in order to prevent unstable processes.

double	theReferenceWeight
	The reference weight to be used.

int	theBin
	The bin to be sampled.

bool	theInitialized
	Wether or not this sampler has already been initialized.

vector< double >	theLastPoint
	The last generated point.

tStdEHPtr	theEventHandler
	The event handler to be used.

Ptr< GeneralSampler >::tptr	theSampler
	The containing sampler.

string	theRandomNumbers
	Folder for the random number plots.

map< size_t, Remapper >	remappers
	Remapper objects indexed by dimension.

unsigned long	theRemapperPoints
	The number of points to be used for initial filling of the remappers.

bool	theRemapChannelDimension
	True if channels should get a remapper.

unsigned long	theLuminosityMapperBins
	The number of bins to be used for luminosity dimensions.

unsigned long	theGeneralMapperBins
	The number of bins to be used for any other dimension.

double	theRemapperMinSelection
	The minimum selection probability for remapper bins.

bool	theIntegrated
	True, if integration has already be performed.

bool	theRemappersFilled
	True, if remappers have been set up.

bool	theHasGrids
	True, if this sampler has already read grid data.

double	theKappa
	In the AlmostUnweighted mode we do not need to unweight the events to the reference weight.

virtual IBPtr	clone () const
	Make a simple clone of this object.

virtual IBPtr	fullclone () const
	Make a clone of this object, possibly modifying the cloned object to make it sane.

BinSampler &	operator= (const BinSampler &)=delete
	The assignment operator is private and must never be called.

Functions used by the persistent I/O system.
void	persistentOutput (PersistentOStream &os) const
	Function used to write out object persistently.

void	persistentInput (PersistentIStream &is, int version)
	Function used to read in object persistently.

static void	Init ()
	The standard Init function used to initialize the interfaces.

Additional Inherited Members
Static Public Member Functions inherited from Herwig::MultiIterationStatistics
static void	Init ()
	The standard Init function used to initialize the interfaces.

Static Public Member Functions inherited from ThePEG::Interfaced
static void	Init ()

Static Public Member Functions inherited from ThePEG::InterfacedBase
static void	Init ()

Static Public Member Functions inherited from ThePEG::Base
static void	Init ()

Protected Member Functions inherited from Herwig::MultiIterationStatistics
Protected Member Functions inherited from ThePEG::Interfaced
void	reporeg (IBPtr object, string name) const

bool	setDefaultReference (PtrT &ptr, string classname, string objectname)

	Interfaced (const string &newName)

	Interfaced (const Interfaced &i)

void	setGenerator (tEGPtr generator)

Protected Member Functions inherited from ThePEG::InterfacedBase
virtual void	readSetup (istream &is)

virtual void	doupdate ()

virtual void	doinit ()

virtual void	doinitrun ()

virtual void	dofinish ()

virtual IVector	getReferences ()

virtual void	rebind (const TranslationMap &)

virtual IBPtr	clone () const=0

	InterfacedBase (string newName)

	InterfacedBase (const InterfacedBase &i)

virtual void	readSetup (istream &is)

virtual void	doupdate ()

virtual void	doinit ()

virtual void	doinitrun ()

virtual void	dofinish ()

virtual IVector	getReferences ()

virtual void	rebind (const TranslationMap &)

Protected Member Functions inherited from ThePEG::Pointer::ReferenceCounted
	ReferenceCounted (const ReferenceCounted &)

ReferenceCounted &	operator= (const ReferenceCounted &)

Protected Member Functions inherited from ThePEG::Named
const Named &	operator= (const Named &other)

const string &	name (const string &newName)

Static Protected Member Functions inherited from ThePEG::Interfaced
static void	registerRepository (IBPtr)

static void	registerRepository (IBPtr, string newName)

Detailed Description

BinSampler samples XCombs bins. This default implementation performs flat MC integration.

Author: Simon Platzer

See also: The interfaces defined for BinSampler.

Definition at line 38 of file BinSampler.h.

Member Typedef Documentation

◆ RandomNumberIndex

typedef pair<string,size_t > Herwig::BinSampler::RandomNumberIndex

Definition at line 330 of file BinSampler.h.

Member Function Documentation

◆ adapt()

virtual void Herwig::BinSampler::adapt ( )

inlinevirtual

Adapt this sampler after an iteration has been run.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

Definition at line 221 of file BinSampler.h.

◆ adaptsOnTheFly()

virtual bool Herwig::BinSampler::adaptsOnTheFly ( ) const

inlinevirtual

Return true, if this sampler adapts on the fly while generating events.

Cross sections in the GeneralSampler class are calculated from adding up the cross sections quoted by individual samplers.

Definition at line 153 of file BinSampler.h.

◆ bias() [1/2]

double Herwig::BinSampler::bias ( ) const

inline

Return the bias with which this sampler is selected.

The sampler needs to divide out this bias in its weight calculation.

Definition at line 68 of file BinSampler.h.

References theBias.

◆ bias() [2/2]

void Herwig::BinSampler::bias ( double b )

inline

Set the bias with which this sampler is selected.

Definition at line 73 of file BinSampler.h.

References theBias.

◆ bin() [1/2]

int Herwig::BinSampler::bin ( ) const

inline

Return the bin.

Definition at line 98 of file BinSampler.h.

References theBin.

Referenced by dimension().

◆ bin() [2/2]

void Herwig::BinSampler::bin ( int b )

inline

Set the bin.

Definition at line 103 of file BinSampler.h.

References theBin.

◆ canUnweight()

virtual bool Herwig::BinSampler::canUnweight ( ) const

inlinevirtual

Return true, if this sampler can provide unweighted events; if the proposal density is not an overestimate, weights larger than one can be generated, the handling of these points being subject to the GeneralSampler class.

Definition at line 146 of file BinSampler.h.

◆ clone()

virtual IBPtr Herwig::BinSampler::clone ( ) const

protectedvirtual

Make a simple clone of this object.

Returns: a pointer to the new object.

Reimplemented from Herwig::MultiIterationStatistics.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

Referenced by cloneMe().

◆ cloneMe()

Ptr< BinSampler >::ptr Herwig::BinSampler::cloneMe ( ) const

inline

Clone this object.

Definition at line 52 of file BinSampler.h.

References clone().

◆ compensating()

virtual bool Herwig::BinSampler::compensating ( ) const

inlinevirtual

If this sampler features a compensation algorithm, return true if more events need to be generated to finish the compensation.

Definition at line 159 of file BinSampler.h.

◆ didReadGrids()

void Herwig::BinSampler::didReadGrids ( )

inline

Indicate that this sampler has already read grid data.

Definition at line 261 of file BinSampler.h.

References theHasGrids.

◆ dimension()

int Herwig::BinSampler::dimension ( ) const

inline

Return the dimension.

Definition at line 339 of file BinSampler.h.

References bin(), and theEventHandler.

◆ doWeighted()

void Herwig::BinSampler::doWeighted ( bool yes = true )

inline

Indicate that weighted events should be generated.

Definition at line 169 of file BinSampler.h.

References theWeighted.

◆ enhancementFactor() [1/2]

double Herwig::BinSampler::enhancementFactor ( ) const

inline

Return the factor to enhance the number of points for the next iteration.

Definition at line 371 of file BinSampler.h.

References theEnhancementFactor.

◆ enhancementFactor() [2/2]

void Herwig::BinSampler::enhancementFactor ( double f )

inline

Set the factor to enhance the number of points for the next iteration.

Definition at line 365 of file BinSampler.h.

References theEnhancementFactor.

◆ eventHandler() [1/2]

tStdEHPtr Herwig::BinSampler::eventHandler ( ) const

inline

Return the event handler.

Definition at line 83 of file BinSampler.h.

References theEventHandler.

◆ eventHandler() [2/2]

void Herwig::BinSampler::eventHandler ( tStdEHPtr eh )

inline

Set the event handler.

Definition at line 78 of file BinSampler.h.

References theEventHandler.

◆ existsGrid()

virtual bool Herwig::BinSampler::existsGrid ( ) const

inlinevirtual

Return true, if grid data exists for this sampler.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

Definition at line 251 of file BinSampler.h.

◆ finalize()

virtual void Herwig::BinSampler::finalize ( bool )

virtual

Finalize this sampler.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

◆ fullclone()

virtual IBPtr Herwig::BinSampler::fullclone ( ) const

protectedvirtual

Make a clone of this object, possibly modifying the cloned object to make it sane.

Returns: a pointer to the new object.

Reimplemented from Herwig::MultiIterationStatistics.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

◆ generate()

virtual double Herwig::BinSampler::generate ( )

virtual

Generate the next point and return its weight; store the point in lastPoint().

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

◆ hasGrids()

bool Herwig::BinSampler::hasGrids ( ) const

inline

Return true, if this sampler has already read grid data.

Definition at line 256 of file BinSampler.h.

References theHasGrids.

◆ Init()

static void Herwig::BinSampler::Init ( )

static

The standard Init function used to initialize the interfaces.

Called exactly once for each class by the class description system before the main function starts or when this class is dynamically loaded.

◆ initialize()

virtual void Herwig::BinSampler::initialize ( bool progress )

virtual

Initialize this bin sampler.

This default version calls runIteration.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

◆ initialized()

bool Herwig::BinSampler::initialized ( ) const

inline

Return true, if this sampler has already been initialized.

Definition at line 231 of file BinSampler.h.

References theInitialized.

◆ initialPoints() [1/2]

unsigned long Herwig::BinSampler::initialPoints ( ) const

inline

Return the number of points to be used for initial integration.

Definition at line 344 of file BinSampler.h.

References theInitialPoints.

◆ initialPoints() [2/2]

void Herwig::BinSampler::initialPoints ( unsigned long n )

inline

Set the number of points to be used for initial integration.

Definition at line 349 of file BinSampler.h.

References theInitialPoints.

◆ integrated()

bool Herwig::BinSampler::integrated ( ) const

inline

Return true, if integration has already been performed.

Definition at line 241 of file BinSampler.h.

References theIntegrated.

◆ integratedXSec()

virtual CrossSection Herwig::BinSampler::integratedXSec ( ) const

inlinevirtual

Return the total integrated cross section determined from the Monte Carlo sampling so far.

Definition at line 272 of file BinSampler.h.

References Herwig::GeneralStatistics::averageWeight().

◆ integratedXSecErr()

virtual CrossSection Herwig::BinSampler::integratedXSecErr ( ) const

inlinevirtual

Return the error on the total integrated cross section determined from the Monte Carlo sampling so far.

Definition at line 280 of file BinSampler.h.

References Herwig::GeneralStatistics::averageWeightVariance(), and ThePEG::sqrt().

◆ isInitialized()

void Herwig::BinSampler::isInitialized ( )

inline

Indicate that this sampler has already been initialized.

Definition at line 236 of file BinSampler.h.

References theInitialized.

◆ kappa()

double Herwig::BinSampler::kappa ( ) const

inline

In the AlmostUnweighted mode we do not need to unweight the events to the reference weight.

Kappa reduces effectivly the reference weight. This can be used for processes, where unweighting is hardly feasable.

Definition at line 385 of file BinSampler.h.

References theKappa.

◆ lastPoint() [1/2]

vector< double > & Herwig::BinSampler::lastPoint ( )

inline

Access the last generated point.

Definition at line 128 of file BinSampler.h.

References theLastPoint.

◆ lastPoint() [2/2]

const vector< double > & Herwig::BinSampler::lastPoint ( ) const

inline

Return the last generated point.

Definition at line 123 of file BinSampler.h.

References theLastPoint.

◆ nIterations() [1/2]

size_t Herwig::BinSampler::nIterations ( ) const

inline

Return the number of iterations to be considered for initialization.

Definition at line 354 of file BinSampler.h.

References theNIterations.

◆ nIterations() [2/2]

void Herwig::BinSampler::nIterations ( size_t n )

inline

Set the number of iterations to be considered for initialization.

Definition at line 359 of file BinSampler.h.

References theNIterations.

◆ operator=()

BinSampler & Herwig::BinSampler::operator= ( const BinSampler & )

privatedelete

The assignment operator is private and must never be called.

In fact, it should not even be implemented.

◆ persistentInput()

void Herwig::BinSampler::persistentInput	(	PersistentIStream &	is,
		int	version
	)

Function used to read in object persistently.

Parameters

is	the persistent input stream read from.
version	the version number of the object when written.

◆ persistentOutput()

void Herwig::BinSampler::persistentOutput ( PersistentOStream & os ) const

Function used to write out object persistently.

Parameters

os	the persistent output stream written to.

◆ randomNumberString()

string Herwig::BinSampler::randomNumberString ( ) const

inline

Return the folder for the random number plots.

Definition at line 376 of file BinSampler.h.

References theRandomNumbers.

◆ referenceWeight() [1/2]

double Herwig::BinSampler::referenceWeight ( ) const

inline

Return the reference weight to be used.

Definition at line 133 of file BinSampler.h.

References theReferenceWeight.

◆ referenceWeight() [2/2]

void Herwig::BinSampler::referenceWeight ( double w )

inline

Set the reference weight to be used.

Definition at line 138 of file BinSampler.h.

References theReferenceWeight.

◆ remappersFilled()

bool Herwig::BinSampler::remappersFilled ( ) const

inline

Return true, if remappers have been set up.

Definition at line 246 of file BinSampler.h.

References theRemappersFilled.

◆ runIteration()

void Herwig::BinSampler::runIteration	(	unsigned long	n,
		bool	progress
	)

Run a single iteration of n points, optionally printing a progress bar to cout.

Calls generate n times.

◆ saveGrid()

virtual void Herwig::BinSampler::saveGrid ( ) const

inlinevirtual

Save grid data.

Reimplemented in Herwig::CellGridSampler, and Herwig::MonacoSampler.

Definition at line 200 of file BinSampler.h.

◆ weighted()

bool Herwig::BinSampler::weighted ( ) const

inline

Return true, if weighted events should be generated.

Definition at line 164 of file BinSampler.h.

References theWeighted.

Member Data Documentation

◆ RandomNumberHistograms

map<RandomNumberIndex,pair<RandomNumberHistogram,double> > Herwig::BinSampler::RandomNumberHistograms

Definition at line 332 of file BinSampler.h.

◆ remappers

map<size_t,Remapper> Herwig::BinSampler::remappers

private

Remapper objects indexed by dimension.

Definition at line 519 of file BinSampler.h.

◆ theBias

double Herwig::BinSampler::theBias

private

The bias with which this sampler is selected.

Definition at line 439 of file BinSampler.h.

Referenced by bias().

◆ theBin

int Herwig::BinSampler::theBin

private

The bin to be sampled.

Definition at line 489 of file BinSampler.h.

Referenced by bin().

◆ theEnhancementFactor

double Herwig::BinSampler::theEnhancementFactor

private

Factor to enhance the number of points for the next iteration.

Definition at line 459 of file BinSampler.h.

Referenced by enhancementFactor().

◆ theEventHandler

tStdEHPtr Herwig::BinSampler::theEventHandler

private

The event handler to be used.

Definition at line 504 of file BinSampler.h.

Referenced by dimension(), and eventHandler().

◆ theGeneralMapperBins

unsigned long Herwig::BinSampler::theGeneralMapperBins

private

The number of bins to be used for any other dimension.

Definition at line 539 of file BinSampler.h.

◆ theHalfPoints

bool Herwig::BinSampler::theHalfPoints

private

Switch to require that we get half of the points in each iteration below the maximum weight of the iteration.

Definition at line 472 of file BinSampler.h.

◆ theHasGrids

bool Herwig::BinSampler::theHasGrids

private

True, if this sampler has already read grid data.

Definition at line 559 of file BinSampler.h.

Referenced by didReadGrids(), and hasGrids().

◆ theInitialized

bool Herwig::BinSampler::theInitialized

private

Wether or not this sampler has already been initialized.

Definition at line 494 of file BinSampler.h.

Referenced by initialized(), and isInitialized().

◆ theInitialPoints

unsigned long Herwig::BinSampler::theInitialPoints

private

The number of points to use for initial integration.

Definition at line 449 of file BinSampler.h.

Referenced by initialPoints().

◆ theIntegrated

bool Herwig::BinSampler::theIntegrated

private

True, if integration has already be performed.

Definition at line 549 of file BinSampler.h.

Referenced by integrated().

◆ theKappa

double Herwig::BinSampler::theKappa

private

In the AlmostUnweighted mode we do not need to unweight the events to the reference weight.

Kappa reduces effectivly the reference weight. This can be used for processes, where unweighting is hardly feasable.

Definition at line 570 of file BinSampler.h.

Referenced by kappa().

◆ theLastPoint

vector<double> Herwig::BinSampler::theLastPoint

private

The last generated point.

Definition at line 499 of file BinSampler.h.

Referenced by lastPoint().

◆ theLuminosityMapperBins

unsigned long Herwig::BinSampler::theLuminosityMapperBins

private

The number of bins to be used for luminosity dimensions.

Definition at line 534 of file BinSampler.h.

◆ theMaxNewMax

int Herwig::BinSampler::theMaxNewMax

private

The maximum number of allowed new maxima, in combination with HalfPoints, in order to prevent unstable processes.

Definition at line 479 of file BinSampler.h.

◆ theNIterations

size_t Herwig::BinSampler::theNIterations

private

The number of iterations to be considered for initialization.

Definition at line 454 of file BinSampler.h.

Referenced by nIterations().

◆ theNonZeroInPresampling

bool Herwig::BinSampler::theNonZeroInPresampling

private

Switch to count only non zero weights in presampling.

Definition at line 465 of file BinSampler.h.

◆ theRandomNumbers

string Herwig::BinSampler::theRandomNumbers

private

Folder for the random number plots.

Definition at line 514 of file BinSampler.h.

Referenced by randomNumberString().

◆ theReferenceWeight

double Herwig::BinSampler::theReferenceWeight

private

The reference weight to be used.

Definition at line 484 of file BinSampler.h.

Referenced by referenceWeight().

◆ theRemapChannelDimension

bool Herwig::BinSampler::theRemapChannelDimension

private

True if channels should get a remapper.

Definition at line 529 of file BinSampler.h.

◆ theRemapperMinSelection

double Herwig::BinSampler::theRemapperMinSelection

private

The minimum selection probability for remapper bins.

Definition at line 544 of file BinSampler.h.

◆ theRemapperPoints

unsigned long Herwig::BinSampler::theRemapperPoints

private

The number of points to be used for initial filling of the remappers.

Definition at line 524 of file BinSampler.h.

◆ theRemappersFilled

bool Herwig::BinSampler::theRemappersFilled

private

True, if remappers have been set up.

Definition at line 554 of file BinSampler.h.

Referenced by remappersFilled().

◆ theSampler

Ptr<GeneralSampler>::tptr Herwig::BinSampler::theSampler

private

The containing sampler.

Definition at line 509 of file BinSampler.h.

◆ theWeighted

bool Herwig::BinSampler::theWeighted

private

True, if weighted events should be generated.

Definition at line 444 of file BinSampler.h.

Referenced by doWeighted(), and weighted().

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

BinSampler.h

Classes

Public Types

Public Member Functions

Public Attributes

Clone Methods.

Functions used by the persistent I/O system.

Additional Inherited Members

Detailed Description

Member Typedef Documentation

◆ RandomNumberIndex

Member Function Documentation

◆ adapt()

◆ adaptsOnTheFly()

◆ bias() [1/2]

◆ bias() [2/2]

◆ bin() [1/2]

◆ bin() [2/2]

◆ canUnweight()

◆ clone()

◆ cloneMe()

◆ compensating()

◆ didReadGrids()

◆ dimension()

◆ doWeighted()

◆ enhancementFactor() [1/2]

◆ enhancementFactor() [2/2]

◆ eventHandler() [1/2]

◆ eventHandler() [2/2]

◆ existsGrid()

◆ finalize()

◆ fullclone()

◆ generate()

◆ hasGrids()

◆ Init()

◆ initialize()

◆ initialized()

◆ initialPoints() [1/2]

◆ initialPoints() [2/2]

◆ integrated()

◆ integratedXSec()

◆ integratedXSecErr()

◆ isInitialized()

◆ kappa()

◆ lastPoint() [1/2]

◆ lastPoint() [2/2]

◆ nIterations() [1/2]

◆ nIterations() [2/2]

◆ operator=()

◆ persistentInput()

◆ persistentOutput()

◆ randomNumberString()

◆ referenceWeight() [1/2]

◆ referenceWeight() [2/2]

◆ remappersFilled()

◆ runIteration()

◆ saveGrid()

◆ weighted()

Member Data Documentation

◆ RandomNumberHistograms

◆ remappers

◆ theBias

◆ theBin

◆ theEnhancementFactor

◆ theEventHandler

◆ theGeneralMapperBins

◆ theHalfPoints

◆ theHasGrids

◆ theInitialized

◆ theInitialPoints

◆ theIntegrated

◆ theKappa

◆ theLastPoint

◆ theLuminosityMapperBins

◆ theMaxNewMax

◆ theNIterations

◆ theNonZeroInPresampling

◆ theRandomNumbers

◆ theReferenceWeight

◆ theRemapChannelDimension

◆ theRemapperMinSelection