Description of the class TLogNormalDistribution. More...

#include <TLogNormalDistribution.h>

Inheritance diagram for URANIE::DataServer::TLogNormalDistribution:

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Collaboration diagram for URANIE::DataServer::TLogNormalDistribution:

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Public Member Functions
Constructor and Destructor
	TLogNormalDistribution ()
	Default constructor.

	TLogNormalDistribution (TString name)
	Constructor setting the name.

	TLogNormalDistribution (TString name, Double_t M, Double_t errorfactor, Double_t xmin=0.0)
	Constructor setting name, mean and error factor.

	TLogNormalDistribution (URANIE::DataServer::TAttribute *att, Double_t M, Double_t errorfactor, Double_t xmin=0.0)
	Construction of a TLogNormalDistribution from an existing TAttribute object.

virtual	~TLogNormalDistribution ()
	Default destructor.

Law parameters
This law has three parameters: the mean , the error factor and the minimum value $x_{min}$ . All are defined here. Another function allows to set directly the underlying normal law parameters. Finally, as this law is defined only over the interval $]x_{min}, +\inf)$ , the functions defining the lower and upper bounds must be redefined.
virtual void	setParameterMean (Double_t M, Bool_t recompute=kTRUE)
	Set the mean parameter.

Double_t	getParameterMean ()
	Return the mean parameter.

virtual void	setParameterErrorFactor (Double_t errorfactor, Bool_t recompute=kTRUE)
	Set the error factor parameter.

Double_t	getParameterErrorFactor ()
	Return the error factor parameter.

virtual void	setParameterXMin (Double_t xmin, Bool_t recompute=kTRUE)
	Set the minimum value parameter.

Double_t	getParameterXMin ()
	Return the minimum value parameter.

virtual void	setParameters (Double_t M, Double_t errorfactor, Double_t xmin=0.0, Bool_t recompute=kTRUE)
	Set all the parameters.

virtual void	setUnderlyingNormalParameters (Double_t mu, Double_t sigma, Bool_t recompute=kTRUE)
	Set the parameters of the underlying normal law.

Double_t	getUnderlyingNormalParameterMu ()
	Return the mean parameter of the underlying normal law.

Double_t	getUnderlyingNormalParameterSigma ()
	Return the standard deviation parameter of the underlying normal law.

virtual void	setLowerBound (Double_t val)
	Sets the lower bound of the attribute.

virtual void	setUpperBound (Double_t val)
	Sets the upper bound of the attribute.

virtual void	setBounds (Double_t lower, Double_t upper)
	Sets the lower and upper bounds of the attribute.

Distribution specific methods
PDF, CDF, etc.
virtual void	computeTheoreticalInformation ()
	Computes the theoretical values of various statistical measures.

virtual Double_t	getPDF (Double_t x)
	Returns the probability density for the value x.

virtual Double_t	getCDF (Double_t x)
	Returns the cumulative distribution for the value x.

virtual Double_t	getInvCDF (Double_t p)
	Returns the value corresponding to the cumulative density p.

Printing Log
virtual void	printLog (Option_t *option="")

Public Member Functions inherited from URANIE::DataServer::TInfiniteDistribution
	TInfiniteDistribution ()
	Default Constructor.

	TInfiniteDistribution (TString str)
	Constructor setting the name.

	TInfiniteDistribution (TString str, ELawType value)
	Constructor setting the name and the law type.

	TInfiniteDistribution (TAttribute *object, ELawType value)
	Construction of a TInfiniteDistribution from an existing TAttribute object.

virtual	~TInfiniteDistribution ()
	Default Destructor.

virtual void	printLog ()
	Display information specific to this class.

Public Member Functions inherited from URANIE::DataServer::TStochasticAttribute
	TStochasticAttribute ()
	Default Constructor.

	TStochasticAttribute (TString str)
	Constructor setting the name.

	TStochasticAttribute (TString str, ELawType value)
	Constructor setting the name and the law type.

	TStochasticAttribute (TString str, ELawType value, Double_t min, Double_t max)
	Constructor setting the name, the law type, and the range (lower and upper bounds)

	TStochasticAttribute (TAttribute *object, ELawType value)
	Construction of a TStochasticAttribute from an existing TAttribute object.

virtual	~TStochasticAttribute ()
	Default Destructor.

double	getPDFforTF1 (double *x)

double	getCDFforTF1 (double *x)

double	getInvCDFforTF1 (double *x)

virtual Double_t	getTheoreticalMean ()
	Returns the theoretical value of the mean.

virtual Double_t	getTheoreticalStdDev ()
	Returns the theoretical value of the standard deviation.

virtual Double_t	getTheoreticalMode ()
	Returns the theoretical value of the mode.

void	setLawType (ELawType value)
	Sets the law type from an integer value.

void	setLawType (TString name)
	Sets the law type from a law name.

int	getLawType ()
	Returns the law type as an integer.

void	setStochasticBasis (EStochasticBasis n)
	Defines an orthogonal polynomial family to represent the stochastic attribute.

void	setDefaultStochasticBasis ()
	Sets the default orthogonal polynomial family representing the stochastic attribute.

EStochasticBasis	getStochasticBasis () const
	Returns the orthogonal polynomial which is used to represent the attribute.

virtual Double_t	getPMin ()
	Returns the minimum value of the cumulative distribution function.

virtual Double_t	getPMax ()
	Returns the maximum value of the cumulative distribution function.

Public Member Functions inherited from URANIE::DataServer::TAttribute
	TAttribute ()
	Default constructor.

	TAttribute (const char name, const char title)

	TAttribute (TString name)
	Constructor by name only.

	TAttribute (TString name, EType type)
	Constructor by name and type only.

	TAttribute (TString name, TString value, EType type)
	Constructor by name and range.

	TAttribute (TString name, Double_t lower, Double_t upper)
	Constructor by name and range.

	TAttribute (const TAttribute &attr)
	Copy constructor.

TAttribute *	Clone (const char *newname) const
	Clone an attribute with a new name.

virtual	~TAttribute ()
	Default destructor.

void	checkSizeBeforePush (const char *type, int iel, Double_t val)
	Internal method used to check the validity of all setters when dealing with vectors.

Double_t	checkSizeBeforeGet (const char *type, int iel=0)
	Internal method used to check the validity of all getters when dealing with vectors and return the request.

void	setQuantile (double prob, double quantile, int iel=0)
	Set the quantile value.

void	getQuantilesSize (int &nb, int iel=0)
	Returns the number of quantile computed and stored for element iel.

void	getQuantiles (double prob, double quantile, int iel=0)
	Returns all the probabilities and corresponding quantiles computed for element iel.

void	getQuantile (double &prob, double &quantile, int iel=0)
	Returns the value of the quantile for element iel, given the probability.

void	getQuantileVector (double &prob, vector< double > &quantile)
	Returns the vector of quantile given the probability.

Double_t	getMinimum (int iel=0)

Double_t	getMinimumSize ()
	Returns the size of the vector of minimum.

Bool_t	hasDefault ()
	Details whether this attribute has a default value.

void	setMinimum (Double_t val, int iel=0)
	Set the minimum value oef element iel.

Double_t	getMaximum (int iel=0)

Double_t	getMaximumSize ()
	Returns the size of the vector of maximum.

void	setMaximum (Double_t val, int iel=0)
	Set the maximum value oef element iel.

void	getStatisticalVector (const char *type, vector< double > &vec)
	Returns the vector of considered statistical value.

Double_t	getMean (int iel=0)

Double_t	getMeanSize ()
	Returns the size of the vector of mean.

void	setMean (Double_t val, int iel=0)
	Set the mean value oef element iel.

Double_t	getStd (int iel=0)

Double_t	getStdSize ()
	Returns the size of the vector of std.

void	setStd (Double_t val, int iel=0)
	Set the std value oef element iel.

void	setSlurmOption (TString value)

EType	getDataType () const
	Returns the datatype of the considered attribute.

TString	getDataTypeStr ()
	Returns the datatype as TString.

void	setTitle (const char *title)
	Defines the title of the attribute.

void	setTitle (TString str)

TString	getTitle ()

void	setDataType (EType thetype)
	Change the type of data.

void	setDataType (TString name)
	Change the type of data.

TString	getLegend ()
	Returns the legend of the attribut.

TString	getUnit ()

void	setUnit (TString str)

TString	getUnity ()

void	setUnity (TString str)

TString	getNote ()

void	setNote (TString str)

Bool_t	setDefault (TString value)

TString	getDefault (TString format="%e")

Bool_t	setDefaultValue (Double_t val)

Bool_t	getDefaultValue (Double_t &val)

Bool_t	hasDefaultValue ()

Bool_t	setDefaultVector (vector< double > &vec)

Bool_t	getDefaultVector (vector< double > *val)

Bool_t	hasDefaultVector ()

Bool_t	setDefaultString (TString str)

Bool_t	getDefaultString (string &str)

Bool_t	hasDefaultString ()

void	setStepValue (Double_t val)

Bool_t	getStepValue (Double_t &val)

TString	getSlurmOption ()

EOrigin	getOrigin ()

void	setOrigin (EOrigin ind)

Int_t	getShare ()

void	setOutput ()
	Sets the attribute as an output attribute.

void	setInput ()
	Sets the attribute as Input.

EAttribute	getInputOutput ()
	Returns the input/Output information of the attribute.

void	setFileNameOfKey (TString str)
	Sets the file name for a key.

list< URANIE::DataServer::TAttributeFileKey * >	getKeyList ()
	Gets KeyList for the attribute.

void	setFieldOfKey (Int_t ind)
	Sets index ind in the unique field related to a unique key.

void	setFieldOfKey (Int_t sIndex, Int_t ind)

void	setFileKey (TString sfile, TString skey="", TString sformatToSubstitute="%e", TAttributeFileKey::EFileType FileType=TAttributeFileKey::kKey)
	Defines the input files and eventually others informations like key, format to substitute.

void	setFileFlag (TString sfile, TString skey="", TString sformatToSubstitute="%e")
	Defines the input files as in the "flag" format and eventually others informations like key, format to substitute.

void	setFileXMLAttribute (TString sfile, TString sXPathAttribute, TString sformatToSubstitute="%e")
	Defines the input files as an "XML" input file with XPath attribute format and eventually the format to substitute.

void	setFileXMLField (TString sfile, TString sXPathField, TString sformatToSubstitute="%e")
	Defines the input files as an "XML" input file with XPath field and eventually the format to substitute.

void	setFileFMU (TString sfile, TString sXPathField, TString sformatToSubstitute="%e")

const char *	getFormatToSubstitute ()
	Returns the format of substitution.

void	setFormatToSubstitute (TString str)
	Sets the format of substitution.

Bool_t	isInput ()
	Tests if the attribute is an input attribute.

Bool_t	isOutput ()
	Tests if the attribute is an output attribute.

void	addShare ()

void	delShare ()

void	initShare ()

void	clearVectors ()

virtual void	setLowerBound (Double_t val, bool internalcall=false)
	Sets the lower bound value of the attribute.

Double_t	getLowerBound ()
	Gets the lower bound value of the attribute.

Bool_t	isLowerBounded ()
	Returns a boolean if the attribute have a lower bound.

virtual void	setUpperBound (Double_t val, bool internalcall=false)
	Sets the upper bound value of the attribute.

Double_t	getUpperBound ()
	Gets the upper bound value of the attribute.

Bool_t	isUpperBounded ()
	Returns a boolean if the attribute have an upper bound.

Bool_t	isBounded ()
	Returns a boolean if the attribute have a lower AND an upper bounds.

void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

TAttribute *	getSonAttribute ()

void	setSonAttribute (TAttribute *tatt)

void	removeSonAttribute ()

Int_t	getLevel ()

void	setLevel (Int_t nlevel)

Bool_t	haveSon ()

Private Member Functions
void	createUnderlyingNormal (Double_t M, Double_t errorfactor)
	Creates the underlying normal distribution.

Private Attributes
TNormalDistribution *	_unormal
	The underlying Normal law.

Double_t	_dparameterXMin
	The minimum value parameter of the LogNormal law.

Double_t	_dparameterMean
	The mean parameter of the LogNormal law.

Double_t	_dparameterErrorFactor
	The error factor parameter of the LogNormal law.

Additional Inherited Members
Public Types inherited from URANIE::DataServer::TStochasticAttribute
enum	ELawType { kUniform , kLogUniform , kNormal , kStudent , kLogNormal , kTrapezium , kTriangular , kLogTriangular , kExponential , kBeta , kGamma , kInvGamma , kCauchy , kUniformByParts , kWeibull , kGumbel , kMultinomial , kGenPareto , kGeneralizedNormal , kGeneralizedNormalV2 , kCompose , kUnknown }
	The list of laws that a TStochasticAttribute can follow. More...

enum	EStochasticBasis { kUnknownBasis , kHermite , kLegendre , kLaguerre , kJacobi }
	The list of orthogonal polynomial families that can represent a given TStochasticAttribute. More...

Public Types inherited from URANIE::DataServer::TAttribute
enum	EOrigin { kInternal , kIterator , kConstant , kAttribute , kDeleted }

enum	EAttribute { kInput , kOutput }

enum	EType { kDefault , kReal , kVector , kString , kCategory , kInconnu }

Protected Attributes inherited from URANIE::DataServer::TStochasticAttribute
ELawType	_lawType
	The law type ELawType.

Double_t	_dtheoreticalMean
	The theoretical mean.

Double_t	_dtheoreticalStdDev
	The theoretical standard deviation.

Double_t	_dtheoreticalMode
	The theoretical mode.

Double_t	_pmin
	The min value of cumulative density function.

Double_t	_pmax
	The max value of cumulative density function.

EStochasticBasis	_nStochasticBasis
	The stochastic representation of an orthogonal basis.

Protected Attributes inherited from URANIE::DataServer::TAttribute
TString	_sunity
	Unity.

TString	_snote
	Note.

Bool_t	_blog
	Log printing.

Int_t	_nshare
	The number of time this attribute is shared in TDataServer.

TAttribute *	_attSon
	Son attribute.

Int_t	_nlevel
	level to its "father"

Bool_t	_haveSon
	true if the attribute have a son

TString	_sFormatSubstitute
	Format to substitute the value.

list< TEventList * >	_nfields
	List of all TEventLists created for the attribute.

list< TAttributeFileKey * >	_KeyList
	List of Keys Attributes structures.

Double_t	upperBound
	Upper bound.

Bool_t	_bHaveUpperBound
	If have an upper bound.

Double_t	lowerBound
	Lower bound.

Bool_t	_bHaveLowerBound
	If have a lower bound.

Double_t	_defaultValue
	Default value.

Bool_t	_bHaveDefaultValue
	If have a default value.

vector< double >	_defaultVector
	Default value for vector.

Bool_t	_bHaveDefaultVector
	If have a default value for vector.

string	_defaultString
	Default value for string.

Bool_t	_bHaveDefaultString
	If have a default value for string.

Double_t	_stepValue
	Step value when using in Optimization.

Bool_t	_bHaveStepValue
	If have a step value.

vector< Double_t >	_vminimum
	All minimun calculated.

vector< Double_t >	_vmaximum
	All maximun calculated.

vector< Double_t >	_vmean
	All mean calculated.

vector< Double_t >	_vstd
	All std calculated.

vector< Double_t > *	_vbuffer

vector< map< double, double > * >	_vquantile
	‍buffer pointer to check addresses

EOrigin	_norigin
	The origin of the attribute (Internal of uranie, attribute or Input, Output...)

EAttribute	_nAttribute
	The nature of attributes : kInput (default) or kOutput.

EType	_nType
	The type of attribute: real (double), vector (of double), string...

TString	_slurmValue

Detailed Description

Description of the class TLogNormalDistribution.

This class defines a stochastic attribute following an LogNormal distribution.

A positive random variable $ x $ is said to follow a LogNormal law when $\ln{x}$ follows a Normal law.

In URANIE, the LogNormal law is defined by three parameters: the minimum value of the distribution $x_{min}$ , the mean of the LogNormal law $M = \mathrm{I\!E}\left[~x~\right]$ and a coefficient, called Error Factor which represents the ratio between the value of the $95^\textrm{th}$ percentile and the median value of the LogNormal distribution. The mean is strictly positive, and the error factor is greater than 1.0.

The error factor can be computed from the mean and variance of the LogNormal law:

$ErrorFactor = \exp(1.645 * \sqrt{\ln(A+1)})$ where $A = V/(M-x_{min})^2$ and is the variance of the LogNormal law.

In addition, each LogNormal law is related to a Normal law. The relation between the Normal law parameters and the LogNormal law parameters is given by:

$\sigma = \ln{\left(ErrorFactor\right)} / 1.645$

$\mu = \ln{\left(M-x_{min}\right)} - 0.5 * \sigma^2$

In the equations below, the parameters $\mu$ and $\sigma$ are the parameters of the related Normal law.

Probability Density Function (PDF):

$f(x) = 1/((x-x_{min})\sigma\sqrt{2\pi}) * \exp\left( -\left(\ln(x-x_{min})-\mu\right)^2 / 2\sigma^2 \right)$ for $x > x_{min}$

Cumulative Distribution Function (CDF):

$F(x) = 0.5 * \left( 1 + erf\left( \left(\ln(x-x_{min}) - \mu\right) / \sqrt{2\sigma^2} \right) \right)$ for

Inverse CDF:

For a given

, if

is generated from the inverse of the related Normal law:

$F^{-1}(p) = \exp(X) + x_{min}$

Constructor & Destructor Documentation

◆ TLogNormalDistribution() [1/4]

URANIE::DataServer::TLogNormalDistribution::TLogNormalDistribution ( )

Default constructor.

Default mean is 0.01, default error factor is 10.0, default minimum value is 0.0

Referenced by ClassImp().

◆ TLogNormalDistribution() [2/4]

URANIE::DataServer::TLogNormalDistribution::TLogNormalDistribution ( TString name )

Constructor setting the name.

Default mean is 0.01, default error factor is 10.0, default minimum value is 0.0

Parameters

name	(TString) Name of the attribute

◆ TLogNormalDistribution() [3/4]

URANIE::DataServer::TLogNormalDistribution::TLogNormalDistribution	(	TString	name,
		Double_t	M,
		Double_t	errorfactor,
		Double_t	xmin = `0.0`
	)

Constructor setting name, mean and error factor.

Parameters

name	(TString) Name of the attribute
M	(Double_t) Mean parameter
errorfactor	(Double_t) Error factor parameter
xmin	(Double_t) Minimum value parameter (Default = 0.0)

◆ TLogNormalDistribution() [4/4]

URANIE::DataServer::TLogNormalDistribution::TLogNormalDistribution	(	URANIE::DataServer::TAttribute *	att,
		Double_t	M,
		Double_t	errorfactor,
		Double_t	xmin = `0.0`
	)

Construction of a TLogNormalDistribution from an existing TAttribute object.

Warning: this copy constructor is incomplete. Please do not use. (Nicolas Gilardi, 2010.06.11)

Parameters

att	(TAttribute *) Pointer to an existing TAttribute object
M	(Double_t) Mean parameter
errorfactor	(Double_t) Error factor parameter
xmin	(Double_t) Minimum value parameter (Default = 0.0)

◆ ~TLogNormalDistribution()

virtual URANIE::DataServer::TLogNormalDistribution::~TLogNormalDistribution ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ computeTheoreticalInformation()

virtual void URANIE::DataServer::TLogNormalDistribution::computeTheoreticalInformation ( )

virtual

Computes the theoretical values of various statistical measures.

Implements URANIE::DataServer::TStochasticAttribute.

Referenced by ClassImp().

◆ createUnderlyingNormal()

void URANIE::DataServer::TLogNormalDistribution::createUnderlyingNormal	(	Double_t	M,
		Double_t	errorfactor
	)

private

Creates the underlying normal distribution.

Parameters

M	(Double_t) the mean of the LogNormal law
errorfactor	(Double_t) the error factor of the LogNormal law

Referenced by ClassImp().

◆ getCDF()

virtual Double_t URANIE::DataServer::TLogNormalDistribution::getCDF ( Double_t x )

virtual

Returns the cumulative distribution for the value x.

Parameters

x	(Double_t) An acceptable value for the attribute

Implements URANIE::DataServer::TStochasticAttribute.

Referenced by ClassImp().

◆ getInvCDF()

virtual Double_t URANIE::DataServer::TLogNormalDistribution::getInvCDF ( Double_t p )

virtual

Returns the value corresponding to the cumulative density p.

Parameters

p	(Double_t) A valid probability

Exceptions

UErrorExceptions if p is outside of the interval [0,1]

Implements URANIE::DataServer::TStochasticAttribute.

Referenced by ClassImp().

◆ getParameterErrorFactor()

Double_t URANIE::DataServer::TLogNormalDistribution::getParameterErrorFactor ( )

inline

Return the error factor parameter.

References _dparameterErrorFactor.

◆ getParameterMean()

Double_t URANIE::DataServer::TLogNormalDistribution::getParameterMean ( )

inline

Return the mean parameter.

References _dparameterMean.

◆ getParameterXMin()

Double_t URANIE::DataServer::TLogNormalDistribution::getParameterXMin ( )

inline

Return the minimum value parameter.

References _dparameterXMin.

◆ getPDF()

virtual Double_t URANIE::DataServer::TLogNormalDistribution::getPDF ( Double_t x )

virtual

Returns the probability density for the value x.

Parameters

x	(Double_t) An acceptable value for the attribute

Implements URANIE::DataServer::TStochasticAttribute.

Referenced by ClassImp().

◆ getUnderlyingNormalParameterMu()

Double_t URANIE::DataServer::TLogNormalDistribution::getUnderlyingNormalParameterMu ( )

inline

Return the mean parameter of the underlying normal law.

References _unormal, and URANIE::DataServer::TNormalDistribution::getParameterMu().

◆ getUnderlyingNormalParameterSigma()

Double_t URANIE::DataServer::TLogNormalDistribution::getUnderlyingNormalParameterSigma ( )

inline

Return the standard deviation parameter of the underlying normal law.

References _unormal, and URANIE::DataServer::TNormalDistribution::getParameterSigma().

◆ printLog()

virtual void URANIE::DataServer::TLogNormalDistribution::printLog ( Option_t * option = "" )

virtual

◆ setBounds()

virtual void URANIE::DataServer::TLogNormalDistribution::setBounds	(	Double_t	lower,
		Double_t	upper
	)

virtual

Sets the lower and upper bounds of the attribute.

As we are dealing with a law defined over the interval $]0, +\inf)$ , setting a finite upper bound or a lower bound greater than 0.0 means that the law is truncated. The _pmin and _pmax values must be recalculated.

Parameters

lower	(Double_t) The value of the new lower bound
upper	(Double_t) The value of the new upper bound

Exceptions

UErrorExceptions if the upper bound is inferior to the lower bound

Reimplemented from URANIE::DataServer::TInfiniteDistribution.

Referenced by ClassImp().

◆ setLowerBound()

virtual void URANIE::DataServer::TLogNormalDistribution::setLowerBound ( Double_t val )

virtual

Sets the lower bound of the attribute.

As we are dealing with a law defined over the interval $]0, +\inf)$ , setting a lower bound greater than 0 means the law is truncated. The _pmin value must be recalculated.

Parameters

val	(Double_t) The value of the new lower bound

Exceptions

UErrorExceptions	if val is superior to the upper bound
UErrorExceptions	if val is smaller than $x_{min}$

Reimplemented from URANIE::DataServer::TInfiniteDistribution.

Referenced by ClassImp().

◆ setParameterErrorFactor()

virtual void URANIE::DataServer::TLogNormalDistribution::setParameterErrorFactor	(	Double_t	errorfactor,
		Bool_t	recompute = `kTRUE`
	)

virtual

Set the error factor parameter.

Parameters

errorfactor	(Double_t) Error factor parameter
recompute	(Bool_t) should we recompute the theoretical information ? (Default = kTRUE)

Exceptions

UErrorExceptions if (errorfactor - 1) < 1e-6

Referenced by ClassImp().

◆ setParameterMean()

virtual void URANIE::DataServer::TLogNormalDistribution::setParameterMean	(	Double_t	M,
		Bool_t	recompute = `kTRUE`
	)

virtual

Set the mean parameter.

Parameters

M	(Double_t) Mean parameter $\mu$
recompute	(Bool_t) should we recompute the theoretical information ? (Default = kTRUE)

Exceptions

UErrorExceptions if $M - x_{min} < x_{min} * 1e-6$

Referenced by ClassImp().

◆ setParameters()

virtual void URANIE::DataServer::TLogNormalDistribution::setParameters	(	Double_t	M,
		Double_t	errorfactor,
		Double_t	xmin = `0.0`,
		Bool_t	recompute = `kTRUE`
	)

virtual

Set all the parameters.

Parameters

M	(Double_t) Mean parameter
errorfactor	(Double_t) Error factor parameter
xmin	(Double_t) Minimum value parameter (Default = 0.0)
recompute	(Bool_t) should we recompute the theoretical information ? (Default = kTRUE)

Exceptions

UErrorExceptions if $M - x_{min} < x_{min} * 1e-6$

Referenced by ClassImp().

◆ setParameterXMin()

virtual void URANIE::DataServer::TLogNormalDistribution::setParameterXMin	(	Double_t	xmin,
		Bool_t	recompute = `kTRUE`
	)

virtual

Set the minimum value parameter.

Parameters

xmin	(Double_t) Minimum value parameter $x_{min}$
recompute	(Bool_t) should we recompute the theoretical information ? (Default = kTRUE)

Exceptions

UErrorExceptions if $M - x_{min} < x_{min} * 1e-6$

Referenced by ClassImp().

◆ setUnderlyingNormalParameters()

virtual void URANIE::DataServer::TLogNormalDistribution::setUnderlyingNormalParameters	(	Double_t	mu,
		Double_t	sigma,
		Bool_t	recompute = `kTRUE`
	)

virtual

Set the parameters of the underlying normal law.

This function allows to set the parameters of the underlying Normal law. The LogNormal law parameters (mean and error factor) are automatically updated.

Parameters

mu	(Double_t) Mean parameter of the underlying normal law
sigma	(Double_t) Standard deviation parameter of the underlying normal law
recompute	(Bool_t) should we recompute the theoretical information ? (Default = kTRUE)

Warning: the minimum value $x_{min}$ of the LogNormal law is unknown to the underlying normal law. If $x_{min} \neq 0.0$ , it must be set using TLogNormalDistribution::setParameterXMin()

Referenced by ClassImp().

◆ setUpperBound()

virtual void URANIE::DataServer::TLogNormalDistribution::setUpperBound ( Double_t val )

virtual

Sets the upper bound of the attribute.

As we are dealing with a law defined over the interval $]0, +\inf)$ , setting a finite upper bound means that the law is truncated. The _pmax value must be recalculated.

Parameters

val	(Double_t) The value of the new upper bound

Exceptions

UErrorExceptions if val is inferior to the lower bound

Reimplemented from URANIE::DataServer::TInfiniteDistribution.

Referenced by ClassImp().

Member Data Documentation

◆ _dparameterErrorFactor

Double_t URANIE::DataServer::TLogNormalDistribution::_dparameterErrorFactor

private

The error factor parameter of the LogNormal law.

Referenced by ClassImp(), and getParameterErrorFactor().

◆ _dparameterMean

Double_t URANIE::DataServer::TLogNormalDistribution::_dparameterMean

private

The mean parameter of the LogNormal law.

Referenced by ClassImp(), and getParameterMean().

◆ _dparameterXMin

Double_t URANIE::DataServer::TLogNormalDistribution::_dparameterXMin

private

The minimum value parameter of the LogNormal law.

Referenced by ClassImp(), and getParameterXMin().

◆ _unormal

TNormalDistribution* URANIE::DataServer::TLogNormalDistribution::_unormal

private

The underlying Normal law.

Referenced by ClassImp(), getUnderlyingNormalParameterMu(), and getUnderlyingNormalParameterSigma().

Documentation / Developer's manual

Available modules

Public Member Functions

Private Member Functions

Private Attributes

Additional Inherited Members

Detailed Description

Constructor & Destructor Documentation

◆ TLogNormalDistribution() [1/4]

◆ TLogNormalDistribution() [2/4]

◆ TLogNormalDistribution() [3/4]

◆ TLogNormalDistribution() [4/4]

◆ ~TLogNormalDistribution()

Member Function Documentation

◆ computeTheoreticalInformation()

◆ createUnderlyingNormal()

◆ getCDF()

◆ getInvCDF()

◆ getParameterErrorFactor()

◆ getParameterMean()

◆ getParameterXMin()

◆ getPDF()

◆ getUnderlyingNormalParameterMu()

◆ getUnderlyingNormalParameterSigma()

◆ printLog()

◆ setBounds()

◆ setLowerBound()

◆ setParameterErrorFactor()

◆ setParameterMean()

◆ setParameters()

◆ setParameterXMin()

◆ setUnderlyingNormalParameters()

◆ setUpperBound()

Member Data Documentation

◆ _dparameterErrorFactor

◆ _dparameterMean

◆ _dparameterXMin

◆ _unormal