Description of the class TDataServer. More...

#include <TDataServer.h>

Inheritance diagram for URANIE::DataServer::TDataServer:

Collaboration diagram for URANIE::DataServer::TDataServer:

[legend]

Public Types
enum	EOrigin { kUnknown , kASCIIFile , kTree , kSQL }
	define the origin of the TDS (how it has been constructed) More...

enum	ENormalisation { kCR , kCentered , kCenteredSum0fSquareOne , kMinusOneOne , kZeroOne }
	define the kind of normalisation to be chosen in normalize method More...

enum	ECAHMethod { kWard , kWardExact , kCentroid , kAverage , kSingle , kComplete }
	define the method ued to compute CAH More...

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

	TDataServer (const char name, const char title)
	Default constructor with a name and a title.

	TDataServer (const TDataServer &tds)
	Copy constructor.

virtual	~TDataServer ()
	Default destructor.

Loading data
Three ways to load data: From an ASCII file with at least one line in header to size nb of values. TDataServer fServer = new TDataServer(); tds->fileDataRead("_ntupledataread_.dat"); URANIE::DataServer::TDataServer Description of the class TDataServer. Definition* TDataServer.h:86 URANIE::DataServer::TDataServer::TDataServer TDataServer() Default constructor. If vectors or string are in the file, a second line is mandatory to explicit this: here is an example of three variable file containing a double x, a string s and a vector v. Element of vectors are slit using commas. A blank line is also mandatory after the header #COLUMN_NAMES: x\|s\|v #COLUMN_TYPES: D\|S[V From a TDSNtupleD contained in a ROOT file with selection of variable, added with others possible one by formula then with deletion of patterns verifying a criterion. TDataServer fServer = new TDataServer(); tds->ntupleDataRead("hsimple.root","ntuple","pxxpy::pypx", "pxpx+pypy<2.0"); Thus, we construct a TDataserver tds from the TNtuple ntuple contained in the file hsimple.root where all original variables are stored from beginning (character ). Two new variables are defined by the following equations "pxpy" et "pypx". Points verifying the criterion "pxpx+pypy<2.0" are excluded from new data. Load a TTree* which exists in memory TDataServer fServer = new TDataServer(); fServer->loadTree(TTree tt); URANIE::DataServer::TDataServer::loadTree Bool_t loadTree(TTree *tt) Load a tree.
Bool_t	fileDataRead (const char name, Bool_t bSave=kTRUE, Bool_t bDontAddAttribute=kFALSE, Option_t option="")
	Reads a ASCII file with a header.

Bool_t	ntupleDataRead (const char file, const char tree, const char svar="", const char *cut="")
	Reads data from a TDSNtupleD in a ROOT file.

Bool_t	loadTree (TTree *tt)
	Load a tree.

Export data <br>
Few methods to export the data in order to re-use them
void	exportData (const char filename, const char varexp="", const char select="", Option_t *option="")
	Exports the data in a ASCII file.

void	exportDataHeader (const char filename, const char varexp="", const char select="", Option_t *option="")
	Exports the data in a header file ( C / C++)

void	exportDataNeMo (const char filename, const char varexpinput, const char varexpoutput, const char select="")
	Exports the data in a ASCII file reading by NeMo.

void	exportDataContext (const char filename, const char varexp="", const char select="")
	Export data in a tex file with a ConTex format.

void	saveTuple (Option_t *option)
	Save the ntupleD in the archive (ROOT File)

Select/Cut/Mix patterns
Criterion to keep/exclude individuals in a database. There is an example: tds->setSelect("( x1x1 + x2x2 < 2.0 ) & ( x1 < 30. )"); or to exclude individuals tds->setCut("x1 >= 30.");
void	setSelect (TString str)
	Specifies the criterion by a string to select individuals.

void	setCut (TCut cut)
	Specifies the criterion to exclude individuals.

void	setCut (const char *str)
	Specifies the criterion to exclude individuals.

void	setCut (TString str)
	Specifies the criterion to exclude individuals.

void	clearSelect ()
	Clears the selection of patterns.

void	clearCut ()
	Clears the rejection of patterns.

void	cleanStatAndQuantiles ()
	Utility function to clean the quantiles and stat of all attribute if needed.

void	mix ()
	Mix the patterns.

Statistical method
The functions developed to perform statistical treatments
TMatrixD	computeCAH (const char varexp="", ECAHMethod CAHmethod=kWard, const char selection="", Option_t option="")
	make a CAH

void	computeStatistic (const char varexp="", const char selection="", Option_t option="")
	Computes the statistics features (minimum and maximum values, mean and standard-deviation)

TMatrixD	computeCorrelationMatrix (const char varexp="", const char selection="", Option_t option="")
	Computes the correlation matrix.

void	computeRank (const char varexp="", Option_t *option="")
	Computes the rank.

void	estimateQuantile (const char attName, Int_t nProba, Double_t proba, Double_t quantile, Double_t confidence=0.5, Option_t option="")
	Estimates quantiles of attribute "attName" with confidence level (Wilks method)

void	estimateQuantile (const char attName, Double_t proba, Double_t &quantile, Double_t confidence=0.5, Option_t option="")
	Estimates quantiles of attribute "attName" with confidence level (Wilks method)

void	computeQuantile (const char *attName, Double_t proba, Double_t &quantile, Int_t type=7)
	Compute a quantile of the empirical distribution of an attribute.

double	computeQuantile (const char *attName, Double_t proba, Int_t type=7)
	Compute and return quantiles of the empirical distribution of an decimal attribute.

void	computeQuantile (const char attName, Int_t nProba, Double_t proba, Double_t *quantiles, Int_t type=7)
	Compute quantiles of the empirical distribution of an attribute.

void	computeQuantileCV (TString yname, Double_t alpha, TString zname, Double_t zapha, Double_t &quantile, Double_t &rho)
	Compute the quantile alpha by comtrol variate.

void	internalQuantilesComputation (Int_t nData, Int_t nProba, Double_t data, Double_t quantiles, Double_t proba, Bool_t isSorted=kTRUE, Int_t index=0, Int_t type=7)
	Computes the value of quantile alpha.

Int_t	computeIndexQuantileWilks (Double_t alpha, Double_t beta, Int_t n)
	Computes the index of the quantile alpha with a confidence beta (Wilks method)

Double_t	computeInverseNormalCDF (Double_t p, Double_t mean=0.0, Double_t stddev=1.0)
	Computes the inverse of the cumulative of a normal distribution.

Visualisation
The functions developed to perform visualization of data
Int_t	scan (const char varexp="", const char selection="", Option_t *option="")
	Scan content of the TDS.

Int_t	Scan (const char varexp, const char selection="", Option_t *option="")
	Scan content of the TDS.

void	checkCanvasCreation (Option_t *option="")
	Crate a canvas if needed.

void	draw (const char varexp, const char selection="", Option_t *option="", bool internalCall=kFALSE)
	Draws histogram for a given index of a variable.

void	Draw (const char varexp, const char selection="", Option_t *option="")
	Draws histogram for a given index of a variable.

void	draw (UInt_t nOrder, const char selection="", Option_t option="")
	Draw a histogram of the attribute specified by its index in the TDataServer.

void	drawHistogram (const char sVar, const char selection="", Option_t *option="")
	Histogram of a variable.

void	drawIter (const char sVar, const char selection="", Option_t *option="")
	Graph of a variable depanding of his apparition order in the list.

void	drawECDF (const char varexp, const char selection="", Option_t *option="")
	Experimental CDF of a single variable.

void	drawQQPlot (const char varexp, const char laws, int nq, Option_t *option="")

void	drawPPPlot (const char varexp, const char laws, int nq, Option_t *option="")

void	drawCDF (const char varexp, const char selection="", Option_t *option="")
	CDF d'une variable.

void	drawBoxPlot (const char varexp, const char selection="", Option_t *option="")

void	startViewer ()

void	StartViewer ()

void	drawTufte (const char varexp, const char selection="", Option_t *option="")
	Draw 2D scatterplots "tufte".

void	drawScatterplot (const char varexp, const char selection="", Option_t *option="")
	Draws Scatterplots.

void	drawProfile (const char varexp, const char selection="", Option_t *option="")
	Draws Profile.

void	drawPairs (const char varexp="", const char selection="", Option_t option="")
	draw the scatterplots for each possible pairs

void	drawCopulogram (const char varexp="", const char selection="", Option_t option="")
	draw the scatterplots for each possible pairs and ranks

void	drawCobWeb (const char varexp, const char selection="", Option_t *option="")
	Draw a cobweb.

Setters
This function are used to change parameters
void	SetName (const char *name)
	Change the name.

void	checkName ()
	Check wether the name exists already

void	setIterator (TString sname)
	Sets an iterator.

void	setTuple (TDSNtupleD ntd, bool newismain=true, const char att="*")
	Set the TDSNtupleD of _datatree variable.

void	setTuple (TTree *ntd, bool newismain=true)
	Set the TDSNtupleD of _datatree variable.

Getter functions
TList *	getListOfAttributes (const char sListOfAttributes="", bool onlyAttribute=true)
	Gets the list of attributes from a string.

string	getStringListOfAttributes (bool onlyNumerical=true, bool onlyAttribute=true)
	Gets the list of attributes as a string.

int	getAttributeIndex (TAttribute *att, bool onlyAttribute=false) const
	Returns the index of the attribute.

int	getAttributeIndex (TString name, bool onlyAttribute=false) const
	Returns the index of the attribute.

TAttribute *	getAttribute (TString str)
	Returns a pointer of the attribute given by this name.

TAttribute *	getAttribute (Int_t ind, bool onlyAttribute=kTRUE)
	Returns a pointer of the attribute given by this name.

Double_t	getValue (TString attName, Int_t entry, Int_t ielement=-1)
	Returns the value at index "entry" of the leaf "attName".

vector< double >	getVector (TString attName, Int_t entry)
	Returns a vector of double for entry "entry" of the leaf "attName".

string	getString (TString attName, Int_t entry)
	Returns a string for entry "entry" of the leaf "attName".

TMatrixD	getMatrix (const char varexp="", const char selection="", Option_t option="")
	Returns the matrix of data.

Int_t	getNPatterns ()
	Returns the number of patterns in the TDataServer.

const char *	getIteratorName ()
	Returns the name of the iterator.

void	changeIteratorName (const char *name)

char *	getDataTreeName ()
	Returns the name of the tree.

char *	getDataFileName ()
	Returns the name of the file.

char *	getArchiveFileName ()
	Returns the name of the archive file.

EOrigin	getOrigin ()
	Return the origin of the considered TDS.

Int_t	getNAttributes (bool onlyAttribute=true)
	Returns the number of attributes in the TDataServer.

Int_t	getNInputAttributes ()
	Return the number of input Attributes.

Int_t	getNOutputAttributes ()
	Return the number of output Attributes.

TCut	getCut ()
	Return the selection TCut.

TDataSpecification *	getDataSpecification ()
	Return a TDataSpecification pointer.

TDSNtupleD *	GetTuple (Option_t *option="V")
	Returns a pointer to the TDSNtupleD.

TDSNtupleD *	getTuple (Option_t *option="V")
	Returns a pointer to the TDSNtupleD.

Bootstrap methods
The functions developed to perform bootstrap analysis
void	bootstrap (Int_t nsize=-1, Option_t *option="")
	Define a bootstrap database.

Miscellaneous
void	createTuple (Option_t *option="")
	Creates the tuple of the TDataServer.

void	fillAttribute (TString name, TString formula="", Bool_t update=kTRUE)
	Fills a new Branch for an attribute by applying the given formula.

void	fillConstantAttribute (TString name, UEntry *ConstUEntry)
	Fills a new Branch for an attribute by copying a constant uentry.

Bool_t	isAttribute (TString name) const
	Checks if the attribute given by a name exist.

void	deleteTuple ()
	Delete the TDSNtupleD of _datatree variable.

Bool_t	hasTuple ()
	Check if the data server contains data.

void	keepFinalTuple (bool val)

Internal methods
The internal functions that are called only by other methods
void	drawCDFRaFu (const char varexp, const char selection="", Option_t *option="")
	Draw a CDF of a TPossibility attribute (RaFu)

Public Attributes
TObjArray *	_drawingGarbageCollector
	Garbage collector list for drawing.

Printing Log
ClassDef(URANIE::DataServer::TDataServer, ID_DATASERVER) private TDSNtupleD *	_datatree
	< Specification of data

TCanvas *	_canvas
	The canvas to work on;.

TTree *	_friend
	Tree added by friend method.

Bool_t	_blog
	log printing

Bool_t	_bQuantVectPrinted
	print the message for the vector quantile calculation only once

Bool_t	_biteratorNameChanged
	To know whether this iterator name has been changed.

Bool_t	_bsaveTuple

TString	_sdatafile
	The original data file (ASCII mode)

TString	_sarchivefile
	The archive file (.root)

TString	_shortDataTreeName
	The shortened name of the TDataServer;.

TString	_siteratorChangedName
	The shortened name of the TDataServer;.

TCut	_ccut
	Selection of pattern.

EOrigin	_norigin
	The origin of the dataserver (ASCII File, TTree, SQL...)

TPatternsEventList *	_pelBootstrap
	The bootstrap list of input pattern.

URANIE::DataServer::UMessageLogger *	_fLogger
	Message logger.

void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

virtual void	printLog (Option_t *option="")

void	drawLegend (const char varexp, const char selection="", const char *histname="htemp")

void	drawQQorPPPlot (const char varexp, const char laws, int nq, Option_t *option)
	Internal method, not to be used standalonely.

static TString	getUranieVersion ()

static Int_t	doBanner ()

static void	findParametersLaw (TString soption, vector< double > &vec, bool blog)

Manipulate attributs
Several ways for adding/manipulate attributes through a formula of other existing attributes through a TAttribute merge with an other TDataServer using normalisation methods (CenterReduct, transform the range on the intervals or )
void	addAttribute (TString name, Double_t dmin, Double_t dmax)
	Adds an attribute with the name and the range.

void	addAttributeUsingData (TString name, double *arr, int size)
	Adds an attribute with the name and the content.

void	addAttributeByNameTitle (TString name, TString title)
	Adds an attribute with the name and title.

void	addAttribute (const char *name)
	Adds an attribute with the name only.

void	addAttribute (TString name, TString formula, TString title="", TString unit="", bool update=true)
	Adds a new attribute defined by an analytical function.

void	fillOthersAttributes (bool update=kFALSE)
	fill TFormula attributes

void	addAttribute (URANIE::DataServer::TAttribute *att)
	Adds an attribute from an attribute.

void	delAttribute (TString name)
	Deletes an attribute given by these name.

void	merge (TDataServer tds, const char varexpinput="*", bool bwithFriend=kFALSE)
	Concatenates the variables of two dataservers.

void	normalize (const char varexp="", const char suffix="_CR", ENormalisation method=kCR, bool global=true)
	Normalize attributes by several methods of normalisation (CenterReduct, on the intervals or )

static string	checkAttributes (TDataServer *tds, string varexp, map< string, vector< int > > &mAttributeElements)
	check the attribute content

Detailed Description

Description of the class TDataServer.

To be written by the developper.

Member Enumeration Documentation

◆ ECAHMethod

enum URANIE::DataServer::TDataServer::ECAHMethod

define the method ued to compute CAH

Enumerator
kWard
kWardExact
kCentroid
kAverage
kSingle
kComplete

◆ ENormalisation

enum URANIE::DataServer::TDataServer::ENormalisation

define the kind of normalisation to be chosen in normalize method

Enumerator
kCR
kCentered
kCenteredSum0fSquareOne
kMinusOneOne
kZeroOne

◆ EOrigin

enum URANIE::DataServer::TDataServer::EOrigin

define the origin of the TDS (how it has been constructed)

Enumerator
kUnknown
kASCIIFile
kTree
kSQL

Constructor & Destructor Documentation

◆ TDataServer() [1/3]

URANIE::DataServer::TDataServer::TDataServer ( )

Default constructor.

Referenced by ClassImp().

◆ TDataServer() [2/3]

URANIE::DataServer::TDataServer::TDataServer	(	const char *	name,
		const char *	title
	)

Default constructor with a name and a title.

◆ TDataServer() [3/3]

URANIE::DataServer::TDataServer::TDataServer ( const TDataServer & tds )

Copy constructor.

◆ ~TDataServer()

virtual URANIE::DataServer::TDataServer::~TDataServer ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ addAttribute() [1/4]

void URANIE::DataServer::TDataServer::addAttribute ( const char * name )

Adds an attribute with the name only.

Parameters

name	the name of the attribute
title	the title of the attribute

◆ addAttribute() [2/4]

void URANIE::DataServer::TDataServer::addAttribute	(	TString	name,
		Double_t	dmin,
		Double_t	dmax
	)

Adds an attribute with the name and the range.

Parameters

name	the name of the attribute
dmin	its minimum value
dmax	its maximum value

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

◆ addAttribute() [3/4]

void URANIE::DataServer::TDataServer::addAttribute	(	TString	name,
		TString	formula,
		TString	title = `""`,
		TString	unit = `""`,
		bool	update = `true`
	)

Adds a new attribute defined by an analytical function.

This function creates a new TAttributeFormula object and add it to the TDS. If a data tree exist, a new branch is automatically created and filled with the results of the attribute's function.

Parameters

name	(TString): the name of the new attribute.
formula	(TString): the formula of the new attribute.
title	(TString): the label of the new attribute (default = "").
unit	(TString): the unit of the new attribute (default = "").
update	(TString): update the back up file with resulting tree (default = true).

Exceptions

UErrorException if an attribute with the given name already exist.

◆ addAttribute() [4/4]

void URANIE::DataServer::TDataServer::addAttribute ( URANIE::DataServer::TAttribute * att )

Adds an attribute from an attribute.

◆ addAttributeByNameTitle()

void URANIE::DataServer::TDataServer::addAttributeByNameTitle	(	TString	name,
		TString	title
	)

Adds an attribute with the name and title.

Parameters

name	the name of the attribute
title	the title of the attribute

Referenced by ClassImp().

◆ addAttributeUsingData()

void URANIE::DataServer::TDataServer::addAttributeUsingData	(	TString	name,
		double *	arr,
		int	size
	)

Adds an attribute with the name and the content.

Parameters

name	the name of the attribute
array	the array of data
size	the size of the array

Referenced by ClassImp().

◆ bootstrap()

void URANIE::DataServer::TDataServer::bootstrap	(	Int_t	nsize = `-1`,
		Option_t *	option = `""`
	)

Define a bootstrap database.

When the size is :

equal to 0; the TEventList is put to NULL ( original TEventList = ${1, 2, 3, \cdots, nS}$
is non-positive; the size is given by the size of the TDataServer (nS = tds->getNPatterns())
is greate than 1; it is the size which must be lesser than nS = tds->getNPatterns().

Parameters

nsize	(Int_t) The size of the bootstrap database [-1]
option	(Option_t) The option passed [""]("sort\|seed"). If option contains "sort", the TEventList is sorted If option contains "seed=", the seed parameter is passed to the TRandom object

Referenced by ClassImp().

◆ changeIteratorName()

void URANIE::DataServer::TDataServer::changeIteratorName ( const char * name )

inline

References _biteratorNameChanged, and _siteratorChangedName.

Referenced by ClassImp().

◆ changeLog()

void URANIE::DataServer::TDataServer::changeLog ( )

inline

References _blog.

◆ checkAttributes()

static string URANIE::DataServer::TDataServer::checkAttributes	(	TDataServer *	tds,
		string	varexp,
		map< string, vector< int > > &	mAttributeElements
	)

static

check the attribute content

Parameters

tds	the tds
varexp	list of variable
fromopt	call from option

Referenced by ClassImp().

◆ checkCanvasCreation()

void URANIE::DataServer::TDataServer::checkCanvasCreation ( Option_t * option = "" )

Crate a canvas if needed.

Referenced by ClassImp().

◆ checkName()

void URANIE::DataServer::TDataServer::checkName ( )

Check wether the name exists already

Referenced by ClassImp().

◆ cleanStatAndQuantiles()

void URANIE::DataServer::TDataServer::cleanStatAndQuantiles ( )

inline

Utility function to clean the quantiles and stat of all attribute if needed.

References URANIE::DataServer::TAttribute::clearVectors(), and getListOfAttributes().

Referenced by clearSelect(), setCut(), setCut(), setCut(), and setSelect().

◆ clearCut()

void URANIE::DataServer::TDataServer::clearCut ( )

inline

Clears the rejection of patterns.

References clearSelect().

◆ clearSelect()

void URANIE::DataServer::TDataServer::clearSelect ( )

inline

Clears the selection of patterns.

References _ccut, and cleanStatAndQuantiles().

Referenced by ClassImp(), and clearCut().

◆ computeCAH()

TMatrixD URANIE::DataServer::TDataServer::computeCAH	(	const char *	varexp = `"*"`,
		ECAHMethod	CAHmethod = `kWard`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

make a CAH

Parameters

varexp	(const char *) attributes to make CAH. If mass exists, put it at the last attribute after a character "," (as "x1:x2:x3,mass")
CAHmethod	(ECAHMethod)[ kWard \| kCentroid \| kAverage \| kSingle \| kComplete }(kWard) the method of CAH

Referenced by ClassImp().

◆ computeCorrelationMatrix()

TMatrixD URANIE::DataServer::TDataServer::computeCorrelationMatrix	(	const char *	varexp = `"*"`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Computes the correlation matrix.

Compute the correlation matrix of the list of considered variable. This method deals with both double branch and vectors when their size is constant through patterns. If so every elements is considered as an input of the matrix

Warning: if the vector size is not constant through all considered patterns, no computation is done.

Parameters

varexp	list of variable to be used
selection	additional selection to be used on top of the global one defined by TDataServer::setSelect()
option	can check correlation on rank if "rank" is used in option.

Referenced by ClassImp().

◆ computeIndexQuantileWilks()

Int_t URANIE::DataServer::TDataServer::computeIndexQuantileWilks	(	Double_t	alpha,
		Double_t	beta,
		Int_t	n
	)

Computes the index of the quantile alpha with a confidence beta (Wilks method)

Description

Given a sorted array of n realizations of a random variable X, a quantile alpha and a confidence level beta, this function returns the index of the realization Q for which P(X <= Q) = alpha with a confidence level beta.

For "large" values of n (i.e n > 1000), in order to reduce numerical errors, an approximation of the Wilks formula is used.

(ref. ?)

Usage

TDataServer* tds = new TDataServer("tdsQuantiles","test for quantiles");
tds->computeQuantile("x",0.95,q);

Parameters

alpha	: probability defining the quantile
beta	: confidence level
n	: sample size

Referenced by ClassImp().

◆ computeInverseNormalCDF()

Double_t URANIE::DataServer::TDataServer::computeInverseNormalCDF	(	Double_t	p,
		Double_t	mean = `0.0`,
		Double_t	stddev = `1.0`
	)

Computes the inverse of the cumulative of a normal distribution.

Description

For a given normal distribution N(mean, stddev) and a probability p, this function computes the value X for which the integral of N from -Inf to X is equal to p.

By default, mean = 0.0 and stddev = 1.0.

Usage

TDataServer* tds = new TDataServer("tdsInvCDF","test for inverse of normal CDF");
tds->computeInverseNormalCDF(0.5, 5.0, 2.5);

Parameters

p	: probability
mean	: mean of the normal distribution
stddev	: standard deviation of the normal distribution

Referenced by ClassImp().

◆ computeQuantile() [1/3]

void URANIE::DataServer::TDataServer::computeQuantile	(	const char *	attName,
		Double_t	proba,
		Double_t &	quantile,
		Int_t	type = `7`
	)

Compute a quantile of the empirical distribution of an attribute.

Returns the quantile of the empirical distribution of the attribute "attName". For a given probability p, the corresponding quantile q is given by:

$q = (1-p) x_k + p x_{k+1}$

where $ x_k$ is the kth smallest value of the n attName values. The parameter "type" determines how k is computed.

Warning: if more than one attribute name is given, only the first one will be used !; The result is stored in quantile for double-branch case. In the case of vector, quantile contains only the last element quantile values. In all cases, the quantiles are stored in the attribute itself and can be accessed through getQuantile methods.

Parameters

attName	(const char*) name of the attribute.
proba	(Double_t) Proba for which the quantile is computed.
quantile	(Double_t &) Variable storing the result
type	(Int_t) quantile type (Default = 7). Possible values are: Discontinuous cases: 1: k = Int( p * n); if pn == k, q = x_k; else q = x_{k+1} 2: k = Int( p n); if pn == k, q = 0.5(x_k + x_{k+1}); else q = x_{k+1} 3: k = Int( p n - 0.5); if pn-0.5 == k and k is even, q = x_k; else q = x_{k+1} (Default in SAS) Piecewise linear interpolations: 4: k = Int( p n ) 5: k = Int( p * n - 0.5 ) 6: k = Int( p * (n+1) ) (Default in Minitab and SPSS) 7: k = Int( p * (n-1) + 1) (Default in ROOT, S and R) 8: k = Int( p * (n+1/3) + 1/3 ) (approximately median unbiased) 9: k = Int( p * (n+1/4) + 3/8 ) (approximately unbiased if x is normaly distributed) NOTE: the notation Int(a) represents the integer part of a >= 0.

References:

Hyndman, R.J and Fan, Y, (1996) "Sample quantiles in statistical packages" American Statistician, 50, 361-365
R Project documentation for the function quantile of package {stats}
ROOT documentation of the TMath::Quantiles function

Referenced by ClassImp().

◆ computeQuantile() [2/3]

double URANIE::DataServer::TDataServer::computeQuantile	(	const char *	attName,
		Double_t	proba,
		Int_t	type = `7`
	)

Compute and return quantiles of the empirical distribution of an decimal attribute.

◆ computeQuantile() [3/3]

void URANIE::DataServer::TDataServer::computeQuantile	(	const char *	attName,
		Int_t	nProba,
		Double_t *	proba,
		Double_t *	quantiles,
		Int_t	type = `7`
	)

Compute quantiles of the empirical distribution of an attribute.

Returns the quantile of the empirical distribution of the attribute "attName", running nProba times the TDataServer::computeQuantile(const char *attName, Double_t proba, Double_t &quantile, Int_t type = 7) method. See its explanation for more details

Parameters

nProba	number of quantiles to compute
proba	(Double_t) Proba for which the quantile is computed.
quantile	(Double_t &) Variable storing the result

Warning: The results are stored in quantile for double-branch case. In the case of vector, quantile contains only the last element quantile values. In all cases, the quantiles are stored in the attribute itself and can be accessed through getQuantile methods.

◆ computeQuantileCV()

void URANIE::DataServer::TDataServer::computeQuantileCV	(	TString	yname,
		Double_t	alpha,
		TString	zname,
		Double_t	zapha,
		Double_t &	quantile,
		Double_t &	rho
	)

Compute the quantile alpha by comtrol variate.

Parameters

yname	: name of the attribut
alpha	: Proba for which the quantile is computed
zname	: name of he control variate,
zapha	: quantile of the control variate,
quantile	: Variable storing the quantile
rho	: Variable storing the variance reduction

Description :

The estimation of the quantile is determinate in 4 steps.

compute the wj: $w_j=\frac{\alpha}{N_0} 1\!\!1_{Z_j\le z_\alpha} + \frac{\alpha}{N_1} 1\!\!1_{Z_j>z_\alpha}$
compute the sum of wj: $\sum\limits_{i=1}^j w_i \ \ where \ j=1...nS$
determinate $K=inf\left\{j, \sum_{i=0}^{j} w_i > \alpha \right\} \ \ where \ j=1...nS$
determinate the empirique quantile : $Y_{\alpha,n}=Y_{(K)}$

The coefficient $\rho_l$ need to compute the reduction of variance is compute thanks to this equation: $\rho_l = \frac{P[Y\le y_\alpha ,Z\le z_\alpha]-\alpha^2}{\alpha-\alpha^2}$

Reminder:: The reduction of variance is $1-{\rho_l}^2$

Warning: not modified to take into account vectors

Referenced by ClassImp().

◆ computeRank()

void URANIE::DataServer::TDataServer::computeRank	(	const char *	varexp = `"*"`,
		Option_t *	option = `""`
	)

Computes the rank.

Compute the rank of the chosen attribute through the global list of patterns. This method deals with both double branch and vectors when their size is constant through patterns. If so every elements is considered as an input and a vector of rank is created whose elements ith is the ranl of the ith element of the considered vector through all patterns.

Warning: if the vector size is not constant through all considered patterns, no computation is done.

Parameters

varexp	list of variable to be used
option	no option implemented so far

Referenced by ClassImp().

◆ computeStatistic()

void URANIE::DataServer::TDataServer::computeStatistic	(	const char *	varexp = `"*"`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Computes the statistics features (minimum and maximum values, mean and standard-deviation)

This method compute the statistical properties of the attribute precised in the varexp list. The results is then stored in the considered attribute itself and can be access through the TAttribute::getX method (where X is Minimum, Maximum, Mean or Std). This method deals with both double branch and vectors when their size is constant through patterns.

Warning: if the vector size is not constant through all considered patterns, no computation is done.

Parameters

varexp	list of variable to be used
selection	additional selection to be used on top of the global one defined by TDataServer::setSelect()
option	no specific option so far

Referenced by ClassImp(), and ClassImp().

◆ createTuple()

void URANIE::DataServer::TDataServer::createTuple ( Option_t * option = "" )

Creates the tuple of the TDataServer.

Referenced by ClassImp().

◆ delAttribute()

void URANIE::DataServer::TDataServer::delAttribute ( TString name )

Deletes an attribute given by these name.

This methods remove the TAttribute from the list of attribute but the corresponding branch is not destroyed in the tree.

Parameters

name	(TString) The name of the attribute to delete

Exceptions

the	attribute does not exist

Referenced by ClassImp().

◆ deleteTuple()

void URANIE::DataServer::TDataServer::deleteTuple ( )

Delete the TDSNtupleD of _datatree variable.

Referenced by ClassImp().

◆ doBanner()

static Int_t URANIE::DataServer::TDataServer::doBanner ( )

inlinestatic

◆ Draw()

void URANIE::DataServer::TDataServer::Draw	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

inline

Draws histogram for a given index of a variable.

Calls TDataServer::draw method

References draw().

Referenced by ClassImp().

◆ draw() [1/2]

void URANIE::DataServer::TDataServer::draw	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`,
		bool	internalCall = `kFALSE`
	)

Draws histogram for a given index of a variable.

Parameters

varexp	(const char*) name of the attribute
selection	(const char*) the formula to select pattern ("")
option	(Option_t*) drawing options ("") The "nclass=" option allows to chose the number of histogram bins. Uranie provides 4 choices: nclass=root: uses the ROOT's default number of bins nclass=sturges: computes the number of bins via struges method nclass=fd: computes the number of bins via fd method nclass=scott: computes the number of bins via scott method nclass=n: uses n bins, where n is a positive integer value

Referenced by ClassImp(), ClassImp(), ClassImp(), and Draw().

◆ draw() [2/2]

void URANIE::DataServer::TDataServer::draw	(	UInt_t	nOrder,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draw a histogram of the attribute specified by its index in the TDataServer.

The index refers to the position at which the attribute was inserted into the TDataServer

Parameters

nOrder	(Int_t) Index of the attribute
selection	(const char*) the formula to select pattern ("")
option	(Option_t*) drawing options ("")

◆ drawBoxPlot()

void URANIE::DataServer::TDataServer::drawBoxPlot	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Referenced by ClassImp().

◆ drawCDF()

void URANIE::DataServer::TDataServer::drawCDF	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

CDF d'une variable.

Referenced by ClassImp().

◆ drawCDFRaFu()

void URANIE::DataServer::TDataServer::drawCDFRaFu	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draw a CDF of a TPossibility attribute (RaFu)

Referenced by ClassImp().

◆ drawCobWeb()

void URANIE::DataServer::TDataServer::drawCobWeb	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draw a cobweb.

Referenced by ClassImp().

◆ drawCopulogram()

void URANIE::DataServer::TDataServer::drawCopulogram	(	const char *	varexp = `"*"`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

draw the scatterplots for each possible pairs $(x_j, x_i)$ and ranks $(Rk_x_j, Rk_x_i)$

Parameters

varexp	(const char) the list of attributes to draw the pairs (""). By default, ("*") all the attributs are used.
selection	(const char*) the formula to select pattern ("")
option	(Option_t*) drawing options (""). No more ROOT options are treated.

Referenced by ClassImp().

◆ drawECDF()

void URANIE::DataServer::TDataServer::drawECDF	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Experimental CDF of a single variable.

This function differs from drawCDF on the fact that it doesn't produce a histogram. Instead, each datum is plotted, which produces a curve that is more accurate but maybe not as smooth as the one given by drawCDF.

Referenced by ClassImp().

◆ drawHistogram()

void URANIE::DataServer::TDataServer::drawHistogram	(	const char *	sVar,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Histogram of a variable.

Referenced by ClassImp().

◆ drawIter()

void URANIE::DataServer::TDataServer::drawIter	(	const char *	sVar,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Graph of a variable depanding of his apparition order in the list.

Referenced by ClassImp().

◆ drawLegend()

void URANIE::DataServer::TDataServer::drawLegend	(	const char *	varexp,
		const char *	selection = `""`,
		const char *	histname = `"htemp"`
	)

Referenced by ClassImp().

◆ drawPairs()

void URANIE::DataServer::TDataServer::drawPairs	(	const char *	varexp = `"*"`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

draw the scatterplots for each possible pairs $(x_j, x_i)$

Parameters

varexp	(const char) the list of attributes to draw the pairs (""). By default, ("*") all the attributs are used.
selection	(const char*) the formula to select pattern ("")
option	(Option_t*) drawing options (""). No more ROOT options are treated.

Referenced by ClassImp().

◆ drawPPPlot()

void URANIE::DataServer::TDataServer::drawPPPlot	(	const char *	varexp,
		const char *	laws,
		int	nq,
		Option_t *	option = `""`
	)

Draw the PP plot of a variable. With "same" in option, the plot is drawn on top of existing one.

Referenced by ClassImp().

◆ drawProfile()

void URANIE::DataServer::TDataServer::drawProfile	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draws Profile.

Draw a profile (mean and sigma) from a scatterplot $ y $ versus $ x $

The profile between (xmin, xmax) value in the first abscissis and (ymin, ymax) ine the second one. where

xmin = min(x) + 0.01 [ Max(x) - Min(x) ]
xmax = Max(x) + 0.01 [ Max(x) - Min(x) ]

Exceptions

When	the number of attributes varexp is different to 2

Referenced by ClassImp().

◆ drawQQorPPPlot()

void URANIE::DataServer::TDataServer::drawQQorPPPlot	(	const char *	varexp,
		const char *	laws,
		int	nq,
		Option_t *	option
	)

Internal method, not to be used standalonely.

Draw the QQ plot of a variable. With "same" in option, the plot is drawn on top of existing one.

Referenced by ClassImp().

◆ drawQQPlot()

void URANIE::DataServer::TDataServer::drawQQPlot	(	const char *	varexp,
		const char *	laws,
		int	nq,
		Option_t *	option = `""`
	)

Draw the QQ plot of a variable. With "same" in option, the plot is drawn on top of existing one.

Referenced by ClassImp().

◆ drawScatterplot()

void URANIE::DataServer::TDataServer::drawScatterplot	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draws Scatterplots.

Referenced by ClassImp().

◆ drawTufte()

void URANIE::DataServer::TDataServer::drawTufte	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Draw 2D scatterplots "tufte".

See http://addictedtor.free.fr/graphiques/RGraphGallery.php?graph=81

Referenced by ClassImp().

◆ estimateQuantile() [1/2]

void URANIE::DataServer::TDataServer::estimateQuantile	(	const char *	attName,
		Double_t	proba,
		Double_t &	quantile,
		Double_t	confidence = `0.5`,
		Option_t *	option = `""`
	)

Estimates quantiles of attribute "attName" with confidence level (Wilks method)

Returns an estimate of the quantile of the attribute "attName" corresponding to the given probability and confidence level.

Parameters

attName (const char*) name of the attribute.

Warning: if more than one attribute name is given, only the first one will be used !

Parameters

nProba	number of quantiles to compute
proba	(Double_t) Proba for which the quantile is computed.
quantile	(Double_t &) Variable storing the result
confidence	(Double_t)[0.5] confidence level
option	(Option_t)[""] Options passed to the method if option contains "interpolate", use the interpolate method between two values

Warning: The result is stored in quantile for double-branch case. In the case of vector, quantile contains only the last element quantile values. In all cases, the quantiles are stored in the attribute itself and can be accessed through getQuantile methods.

◆ estimateQuantile() [2/2]

void URANIE::DataServer::TDataServer::estimateQuantile	(	const char *	attName,
		Int_t	nProba,
		Double_t *	proba,
		Double_t *	quantile,
		Double_t	confidence = `0.5`,
		Option_t *	option = `""`
	)

Estimates quantiles of attribute "attName" with confidence level (Wilks method)

Returns an estimate of the quantiles of the attribute "attName" corresponding to the given probabilities and confidence level. This method calls TDataServer::estimateQuantile(const char attName, Int_t nProba, Double_t proba, Double_t* quantile, Double_t confidence = 0.5, Option_t *option = ""). See its explanation for more details

Parameters

nProba	number of quantiles to compute
proba	(Double_t) Proba for which the quantile is computed.
quantile	(Double_t &) Variable storing the result

Warning: The results are stored in quantile for double-branch case. In the case of vector, quantile contains only the last element quantile values. In all cases, the quantiles are stored in the attribute itself and can be accessed through getQuantile methods.

Referenced by ClassImp().

◆ exportData()

void URANIE::DataServer::TDataServer::exportData	(	const char *	filename,
		const char *	varexp = `"*"`,
		const char *	select = `""`,
		Option_t *	option = `""`
	)

Exports the data in a ASCII file.

The ASCII File can be loaded with a TDataServer object

Parameters

filename	(const char *) File name
varexp	(const char )[""] The list of attributes to export separated by the character ":"
select	(const char *)[""] The selection of patterns to the export
option	can precise the precision with which the double are written by typing "precision=" with a digit from 1 to 9

Referenced by ClassImp(), and ClassImp().

◆ exportDataContext()

void URANIE::DataServer::TDataServer::exportDataContext	(	const char *	filename,
		const char *	varexp = `"*"`,
		const char *	select = `""`
	)

Export data in a tex file with a ConTex format.

Exports the data in a tex file (not modified to deal with Vectors/Strings)

Parameters

filename	(const char *) File name
varexp	(const char )[""] The list of attributes to export separated by the character ":"
select	(const char *)[""] The selection of patterns to the export

Referenced by ClassImp().

◆ exportDataHeader()

void URANIE::DataServer::TDataServer::exportDataHeader	(	const char *	filename,
		const char *	varexp = `"*"`,
		const char *	select = `""`,
		Option_t *	option = `""`
	)

Exports the data in a header file ( C / C++)

Export the data as a header file so that they can be included in a C++ code. Vectors used an initialisation style that is only compliant to C++11, but have not yet been tested

Parameters

filename	(const char *) File name
varexp	(const char )[""] The list of attributes to export separated by the character ":"
select	(const char *)[""] The selection of patterns to the export
option	can precise the precision with which the double are written by typing "precision="

Referenced by ClassImp().

◆ exportDataNeMo()

void URANIE::DataServer::TDataServer::exportDataNeMo	(	const char *	filename,
		const char *	varexpinput,
		const char *	varexpoutput,
		const char *	select = `""`
	)

Exports the data in a ASCII file reading by NeMo.

The ASCII File will be load with the NeMo tool

The format of this file is as the following next

#NombreExemples 53
#NombreEntrees 2
#NombreSorties 1
 
1.800000000e+00 5.400000000e+01 5.400000000e+01 
1.950000000e+00 5.100000000e+01 5.100000000e+01 
1.833000000e+00 5.400000000e+01 5.400000000e+01
...

using

TDataServer *tds = new TDataServer("tdsgeyser", "Data from the geyser");
tds->fileDataRead("geyser.dat");
tds->addAttribute("y", "sqrt(x2) * x1");
tds->exportDataNeMo("geyser.nemo", "x1:x2", "y", "x2<55.0");

Parameters

filename	(const char *) File name
varexpinput	(const char *) The list of input attributes to export separated by the character ":"
varexpoutput	(const char *) The list of output attributes to export separated by the character ":"
select	(const char *)[""] The selection of patterns to the export

Referenced by ClassImp().

◆ fileDataRead()

Bool_t URANIE::DataServer::TDataServer::fileDataRead	(	const char *	name,
		Bool_t	bSave = `kTRUE`,
		Bool_t	bDontAddAttribute = `kFALSE`,
		Option_t *	option = `""`
	)

Reads a ASCII file with a header.

The format of the ASCII datafile is similar to the format of \salome , except for the line containing titles of variables.

Parameters

name	(const char*) The name of the ASCII file
bSave	(Bool_t) true if we save the data in a binary file, false else.
bDontAddAttribute	(Bool_t) Default is false. If true and an attribute is already found in TDataSpecification with a given name, no new TAttribute is created. With this option one can use fileDataRead with a TDS in which one needs to specify TStochasticAttribute for instance

Referenced by ClassImp(), and ClassImp().

◆ fillAttribute()

void URANIE::DataServer::TDataServer::fillAttribute	(	TString	name,
		TString	formula = `""`,
		Bool_t	update = `kTRUE`
	)

Fills a new Branch for an attribute by applying the given formula.

This function takes the name of an existing attribute and creates a new branch for it in the data tree. Then, it fills the branch according to the given formula. If the attribute is a TAttributeFormula, its formula is used.

Parameters

name	(TString): name of the attribute.
formula	(TString): formula to apply if the attribute isn't a TAttributeFormula (default = "")
update	(Bool_t): tells to update the "backup" file of the data server or not. As the operation of writting data on disk can be very slow, it can be useful to set this parameter to kFALSE to disable it (default = kTRUE)

Exceptions

UranieError	if there is no data tree.
UranieError	if the attribute doesn't exist
UranieError	if the attribute is a TAttributeFormula and the formula parameter is not empty.
UranieError	if the attribute isn't a TAttributeFormula and the formula parameter is empty
UranieError	if the formula is unvalid.
UranieError	if the attribute is already filled.

Referenced by ClassImp().

◆ fillConstantAttribute()

void URANIE::DataServer::TDataServer::fillConstantAttribute	(	TString	name,
		UEntry *	ConstUEntry
	)

Fills a new Branch for an attribute by copying a constant uentry.

Very advanced, this function is mainly used internly to help dealing with constant attribute that could be string or vector and that could be written in the output sample.

Parameters

name	(TString): name of the attribute.
ConstUEntry(UEntry*)	UEntry containing the information to be stored.
update	(Bool_t): tells to update the "backup" file of the data server or not. As the operation of writting data on disk can be very slow, it can be useful to set this parameter to kFALSE to disable it (default = kTRUE)

Exceptions

UranieError	if there is no data tree.
UranieError	if the UEntry doesn't contains data
UranieError	if the attribute is already filled.

Referenced by ClassImp().

◆ fillOthersAttributes()

void URANIE::DataServer::TDataServer::fillOthersAttributes ( bool update = kFALSE )

fill TFormula attributes

Referenced by ClassImp().

◆ findParametersLaw()

static void URANIE::DataServer::TDataServer::findParametersLaw	(	TString	soption,
		vector< double > &	vec,
		bool	blog
	)

static

Referenced by ClassImp().

◆ getArchiveFileName()

char * URANIE::DataServer::TDataServer::getArchiveFileName ( )

Returns the name of the archive file.

Referenced by ClassImp().

◆ getAttribute() [1/2]

TAttribute * URANIE::DataServer::TDataServer::getAttribute	(	Int_t	ind,
		bool	onlyAttribute = `kTRUE`
	)

Returns a pointer of the attribute given by this name.

Parameters

ind	index of the attribute
onlyAttribute	boolean to specify if the list of attribute should contains only real attribute (kAttribute and kConstant), or all kind of attribute (kInternal and kIterator as well)

Exceptions

If	an attribute with this name does not exist.

◆ getAttribute() [2/2]

TAttribute * URANIE::DataServer::TDataServer::getAttribute ( TString str )

Returns a pointer of the attribute given by this name.

Exceptions

If	an attribute with this name does not exist.

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

◆ getAttributeIndex() [1/2]

int URANIE::DataServer::TDataServer::getAttributeIndex	(	TAttribute *	att,
		bool	onlyAttribute = `false`
	)		const

Returns the index of the attribute.

Return the index of the attribute under study in the list of attribute

Parameters

att	attribute under study
onlyAttribute	boolean to specify if the list of attribute should contains only kAttribute and kConstant, or all kind of attribute (kInternal and kIterator as well)

Referenced by ClassImp().

◆ getAttributeIndex() [2/2]

int URANIE::DataServer::TDataServer::getAttributeIndex	(	TString	name,
		bool	onlyAttribute = `false`
	)		const

Returns the index of the attribute.

Return the index of the attribute under study in the list of attribute

Parameters

att	attribute under study
onlyAttribute	boolean to specify if the list of attribute should contains only real attribute (kAttribute and kConstant), or all kind of attribute (kInternal and kIterator as well)

◆ getCut()

TCut URANIE::DataServer::TDataServer::getCut ( )

inline

Return the selection TCut.

References _ccut.

◆ getDataFileName()

char * URANIE::DataServer::TDataServer::getDataFileName ( )

Returns the name of the file.

Referenced by ClassImp().

◆ getDataSpecification()

TDataSpecification * URANIE::DataServer::TDataServer::getDataSpecification ( )

inline

Return a TDataSpecification pointer.

◆ getDataTreeName()

char * URANIE::DataServer::TDataServer::getDataTreeName ( )

Returns the name of the tree.

Referenced by ClassImp().

◆ getIteratorName()

const char * URANIE::DataServer::TDataServer::getIteratorName ( )

inline

Returns the name of the iterator.

References _biteratorNameChanged, and _siteratorChangedName.

Referenced by ClassImp(), and ClassImp().

◆ getListOfAttributes()

TList * URANIE::DataServer::TDataServer::getListOfAttributes	(	const char *	sListOfAttributes = `"*"`,
		bool	onlyAttribute = `true`
	)

Gets the list of attributes from a string.

Returns the list of attributes. The character "*" means all attributes.

Parameters

onlyAttribute boolean to specify if the list of attribute should contains only kAttribute and kConstant, or all kind of attribute (kInternal and kIterator as well)

Referenced by ClassImp(), and cleanStatAndQuantiles().

◆ getLog()

Bool_t URANIE::DataServer::TDataServer::getLog ( )

inline

References _blog.

◆ getMatrix()

TMatrixD URANIE::DataServer::TDataServer::getMatrix	(	const char *	varexp = `"*"`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Returns the matrix of data.

Works only

Referenced by ClassImp().

◆ getNAttributes()

Int_t URANIE::DataServer::TDataServer::getNAttributes ( bool onlyAttribute = true )

Returns the number of attributes in the TDataServer.

Returns the number of attributes

Parameters

onlyAttribute boolean to specify if the list of attribute should contains only real attribute (kAttribute and kConstant), or all kind of attribute (kInternal and kIterator as well)

Referenced by ClassImp(), and ClassImp().

◆ getNInputAttributes()

Int_t URANIE::DataServer::TDataServer::getNInputAttributes ( )

Return the number of input Attributes.

Return the number of attributes which are Input attributes

Referenced by ClassImp().

◆ getNOutputAttributes()

Int_t URANIE::DataServer::TDataServer::getNOutputAttributes ( )

Return the number of output Attributes.

Return the number of attributes which are Ouput attributes

Referenced by ClassImp().

◆ getNPatterns()

Int_t URANIE::DataServer::TDataServer::getNPatterns ( )

Returns the number of patterns in the TDataServer.

Exceptions

the	TNtuple is NULL

Referenced by ClassImp(), and ClassImp().

◆ getOrigin()

EOrigin URANIE::DataServer::TDataServer::getOrigin ( )

inline

Return the origin of the considered TDS.

References _norigin.

◆ getString()

string URANIE::DataServer::TDataServer::getString	(	TString	attName,
		Int_t	entry
	)

Returns a string for entry "entry" of the leaf "attName".

Exceptions

if	attribute is a vector or double
if	attribute is not existing

Referenced by ClassImp(), and ClassImp().

◆ getStringListOfAttributes()

string URANIE::DataServer::TDataServer::getStringListOfAttributes	(	bool	onlyNumerical = `true`,
		bool	onlyAttribute = `true`
	)

Gets the list of attributes as a string.

Returns the list of attributes as a string in classical uranie format.

Parameters

onlyNumerical	boolean to specify if the list of attribute should contains only kDouble and kVector, or whether it should include kString as well.
onlyAttribute	boolean to specify if the list of attribute should contains only kAttribute and kConstant, or all kind of attribute (kInternal and kIterator as well)

Referenced by ClassImp().

◆ GetTuple()

TDSNtupleD * URANIE::DataServer::TDataServer::GetTuple ( Option_t * option = "V" )

inline

Returns a pointer to the TDSNtupleD.

Parameters

option useless so far

References getTuple().

Referenced by ClassImp().

◆ getTuple()

TDSNtupleD * URANIE::DataServer::TDataServer::getTuple ( Option_t * option = "V" )

Returns a pointer to the TDSNtupleD.

Parameters

option useless so far

Referenced by ClassImp(), ClassImp(), ClassImp(), ClassImp(), and GetTuple().

◆ getUranieVersion()

static TString URANIE::DataServer::TDataServer::getUranieVersion ( )

inlinestatic

◆ getValue()

Double_t URANIE::DataServer::TDataServer::getValue	(	TString	attName,
		Int_t	entry,
		Int_t	ielement = `-1`
	)

Returns the value at index "entry" of the leaf "attName".

If ielement != -1 it returns the ielement-th of the vector, if the concerned attribute is a vector

Exceptions

if	attribute is a string
if	attribute is a string and ielement == -1 or ielement > vector.size()

Referenced by ClassImp(), and ClassImp().

◆ getVector()

vector< double > URANIE::DataServer::TDataServer::getVector	(	TString	attName,
		Int_t	entry
	)

Returns a vector of double for entry "entry" of the leaf "attName".

Exceptions

if	attribute is a string or double
if	attribute is not existing

Referenced by ClassImp().

◆ hasTuple()

Bool_t URANIE::DataServer::TDataServer::hasTuple ( )

inline

Check if the data server contains data.

This function returns TRUE if the data server contains a TDSNtupleD. It returns FALSE otherwise.

References _datatree.

◆ internalQuantilesComputation()

void URANIE::DataServer::TDataServer::internalQuantilesComputation	(	Int_t	nData,
		Int_t	nProba,
		Double_t *	data,
		Double_t *	quantiles,
		Double_t *	proba,
		Bool_t	isSorted = `kTRUE`,
		Int_t *	index = `0`,
		Int_t	type = `7`
	)

Computes the value of quantile alpha.

Description

This is a rewriting of the ROOT::TMath::Quantiles() function which was found buggy as of February 2010. The present algorithm is derived from http://mathworld.wolfram.com/Quantile.html. The function prototype is the same as ROOT::TMath::Quantiles.

Warning: Internal method not to be called by users

Referenced by ClassImp().

◆ isAttribute()

Bool_t URANIE::DataServer::TDataServer::isAttribute ( TString name ) const

Checks if the attribute given by a name exist.

Returns: kTRUE if an attribute given by the name exist, else kFALSE

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

◆ keepFinalTuple()

void URANIE::DataServer::TDataServer::keepFinalTuple ( bool val )

inline

References _bsaveTuple.

◆ loadTree()

Bool_t URANIE::DataServer::TDataServer::loadTree ( TTree * tt )

Load a tree.

Referenced by ClassImp().

◆ merge()

void URANIE::DataServer::TDataServer::merge	(	TDataServer *	tds,
		const char *	varexpinput = `"*"`,
		bool	bwithFriend = `kFALSE`
	)

Concatenates the variables of two dataservers.

Both dataservers must have the name numbers of entries. Variables names are tested before considering their value, so if a variable already exists in both tables the second one is copied as well, changing its name to "tdsname.variablename"

One of the optional argument set the use of ROOT::AddFriend method (previous default). This method does not make the new variable visible from a TTree::Scan or when looking at list of Attributes available in the TDS. The new default (bwithFriend==false) is a proper concatenation that allows to close and delete the second tds once the merging is done.

Parameters

tds	(TDataServer *) pointer of the DataServer to be merged into the original tds.
varexpinput	list of attribute from the second tds to be merged
bwithFriends	use ROOT friend method or copy the information completely in the original tds

Exceptions

if	both dataservers have not the same number of patterns

Referenced by ClassImp().

◆ mix()

void URANIE::DataServer::TDataServer::mix ( )

Mix the patterns.

To mix the patterns

Referenced by ClassImp().

◆ normalize()

void URANIE::DataServer::TDataServer::normalize	(	const char *	varexp = `""`,
		const char *	suffix = `"_CR"`,
		ENormalisation	method = `kCR`,
		bool	global = `true`
	)

Normalize attributes by several methods of normalisation (CenterReduct, on the intervals $[-1.0, 1.0]$ or $[0.0, 1.0]$ )

Several methods of normalisation are provided:

CenterReduct : kCR [Default]
$\tilde{x} = \frac{x - \mu_{x}}{\sigma_{x}}$
Centered : kCentered
$\tilde{x} = x - \mu_{x}$
transform on the interval : kMinusOneOne
$\tilde{x} = 2.0 * \frac{ x - x_{Min}}{x_{Max} - x_{Min}} -1.0$
transform on the interval : kZeroOne
$\tilde{x} = \frac{ x - x_{Min}}{x_{Max} - x_{Min}}$

The name of the normalized attribute is given by the name of the original attribute and the suffix string.

Parameters

varexp	(const char*) The list of attributes
suffix	(const char*)["CR"] The suffix caracter to add of each attributes to create the normalize attribute
method	(ENormalisation)[kCR] the method of normalisation
global	(bool)[true]: Use only in the case of vector, this boolean explicitely state whether the min, max, mean and std are the global one (only one for all patterns and all vector elements) or not (then specific min, max, mean and std are used for every component of the vector)

Referenced by ClassImp().

◆ ntupleDataRead()

Bool_t URANIE::DataServer::TDataServer::ntupleDataRead	(	const char *	file,
		const char *	tree,
		const char *	svar = `"*"`,
		const char *	cut = `""`
	)

Reads data from a TDSNtupleD in a ROOT file.

This methods takes an existing file and read the tree to load it. On the contrary to loadTree, TDataSpecification is assumed to be empty while the TDSNtupleD is rebuilt completly deleting.

Parameters

file	The name of the root file
tree	The name of the TDSNtupleD
svar	The list of attributes. Formula are possible
cut	The selection of patterns. Points that verify this criterion are excluded (as explicitely said by the name cut)

Exceptions

Can't open a file, the tree is not found in the input file or is empty, the TDS is not empty,

Referenced by ClassImp().

◆ printLog()

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

virtual

Referenced by ClassImp(), and ClassImp().

◆ saveTuple()

void URANIE::DataServer::TDataServer::saveTuple ( Option_t * option )

Save the ntupleD in the archive (ROOT File)

The name of the ROOT file is given by the name of

Parameters

option (Option_t*) [""] The option is the second argument of TFile::Open method (UPDATE|NEW|RECREATE)

Referenced by ClassImp().

◆ Scan()

Int_t URANIE::DataServer::TDataServer::Scan	(	const char *	varexp,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

inline

Scan content of the TDS.

Calls TDataServer::scan method

References scan().

Referenced by ClassImp().

◆ scan()

Int_t URANIE::DataServer::TDataServer::scan	(	const char *	varexp = `""`,
		const char *	selection = `""`,
		Option_t *	option = `""`
	)

Scan content of the TDS.

Print out the content of the tree given the parameter requested

Parameters

varexp	list of attribute to be dumped
selection	selection criterion to be applied on top of the global one
option	option to be passed to ROOT::TTree::Scan method (which is call at the end)

Referenced by ClassImp(), and Scan().

◆ setCut() [1/3]

void URANIE::DataServer::TDataServer::setCut ( const char * str )

inline

Specifies the criterion to exclude individuals.

References _ccut, and cleanStatAndQuantiles().

◆ setCut() [2/3]

void URANIE::DataServer::TDataServer::setCut ( TCut cut )

inline

Specifies the criterion to exclude individuals.

References _ccut, and cleanStatAndQuantiles().

◆ setCut() [3/3]

void URANIE::DataServer::TDataServer::setCut ( TString str )

inline

Specifies the criterion to exclude individuals.

The cut is tested and if it differs from the previous one (currently used) the quantiles and statistical caracteristic of the attributes are cleared.

Parameters

str	(TString) A string to define rejection criterion.

References _ccut, and cleanStatAndQuantiles().

◆ setIterator()

void URANIE::DataServer::TDataServer::setIterator ( TString sname )

Sets an iterator.

Defines the attribute named sname as an index.

Parameters

sname (TString) The name of the attribute which is defined as an index

Referenced by ClassImp().

◆ setLog()

void URANIE::DataServer::TDataServer::setLog ( )

inline

References _blog.

◆ SetName()

void URANIE::DataServer::TDataServer::SetName ( const char * name )

Change the name.

Method added to deal with the registration of the dataserver in gROOT; It overwrite the TObject one.

Referenced by ClassImp().

◆ setSelect()

void URANIE::DataServer::TDataServer::setSelect ( TString str )

inline

Specifies the criterion by a string to select individuals.

The selection is tested and if it differs from the previous one (currently used) the quantiles and statistical caracteristic of the attributes are cleared.

Parameters

str	(TString) A string to define selection criterion.

References _ccut, and cleanStatAndQuantiles().

◆ setTuple() [1/2]

void URANIE::DataServer::TDataServer::setTuple	(	TDSNtupleD *	ntd,
		bool	newismain = `true`,
		const char *	att = `"*"`
	)

inline

Set the TDSNtupleD of _datatree variable.

Parameters

ntd	(TDSNtupleD *) a pointer on a TDSNtupleD. The pointer is not deleted before the (new) value is set. If _datatree has already been initialized, you might want to use the deleteTuple method before to avoid memory leak.

References _datatree.

◆ setTuple() [2/2]

void URANIE::DataServer::TDataServer::setTuple	(	TTree *	ntd,
		bool	newismain = `true`
	)

inline

Set the TDSNtupleD of _datatree variable.

Parameters

ntd	(TTree *) a pointer on a TTree. The pointer is not deleted before the (new) value is set. If _datatree has already been initialized, you might want to use the deleteTuple method before to avoid memory leak.

References _datatree.

◆ startViewer()

void URANIE::DataServer::TDataServer::startViewer ( )

Referenced by ClassImp(), and StartViewer().

◆ StartViewer()

void URANIE::DataServer::TDataServer::StartViewer ( )

inline

References startViewer().

Referenced by ClassImp().

◆ unsetLog()

void URANIE::DataServer::TDataServer::unsetLog ( )

inline

References _blog.

Member Data Documentation

◆ _biteratorNameChanged

Bool_t URANIE::DataServer::TDataServer::_biteratorNameChanged

To know whether this iterator name has been changed.

Referenced by changeIteratorName(), and getIteratorName().

◆ _blog

Bool_t URANIE::DataServer::TDataServer::_blog

log printing

Referenced by changeLog(), ClassImp(), getLog(), setLog(), and unsetLog().

◆ _bQuantVectPrinted

Bool_t URANIE::DataServer::TDataServer::_bQuantVectPrinted

print the message for the vector quantile calculation only once

Referenced by ClassImp().

◆ _bsaveTuple

Bool_t URANIE::DataServer::TDataServer::_bsaveTuple

Referenced by ClassImp(), and keepFinalTuple().

◆ _canvas

TCanvas* URANIE::DataServer::TDataServer::_canvas

The canvas to work on;.

Referenced by ClassImp().

◆ _ccut

TCut URANIE::DataServer::TDataServer::_ccut

Selection of pattern.

Referenced by ClassImp(), clearSelect(), getCut(), setCut(), setCut(), setCut(), and setSelect().

◆ _datatree

ClassDef (URANIE::DataServer::TDataServer, ID_DATASERVER) private TDSNtupleD* URANIE::DataServer::TDataServer::_datatree

< Specification of data

Tree with data

Referenced by ClassImp(), hasTuple(), setTuple(), and setTuple().

◆ _drawingGarbageCollector

TObjArray* URANIE::DataServer::TDataServer::_drawingGarbageCollector

Garbage collector list for drawing.

Referenced by ClassImp().

◆ _fLogger

URANIE::DataServer::UMessageLogger* URANIE::DataServer::TDataServer::_fLogger

Message logger.

Referenced by ClassImp().

◆ _friend

TTree* URANIE::DataServer::TDataServer::_friend

Tree added by friend method.

Referenced by ClassImp().

◆ _norigin

EOrigin URANIE::DataServer::TDataServer::_norigin

The origin of the dataserver (ASCII File, TTree, SQL...)

Referenced by ClassImp(), and getOrigin().

◆ _pelBootstrap

TPatternsEventList* URANIE::DataServer::TDataServer::_pelBootstrap

The bootstrap list of input pattern.

Referenced by ClassImp().

◆ _sarchivefile

TString URANIE::DataServer::TDataServer::_sarchivefile

The archive file (.root)

Referenced by ClassImp().

◆ _sdatafile

TString URANIE::DataServer::TDataServer::_sdatafile

The original data file (ASCII mode)

Referenced by ClassImp().

◆ _shortDataTreeName

TString URANIE::DataServer::TDataServer::_shortDataTreeName

The shortened name of the TDataServer;.

Referenced by ClassImp().

◆ _siteratorChangedName

TString URANIE::DataServer::TDataServer::_siteratorChangedName

The shortened name of the TDataServer;.

Referenced by changeIteratorName(), and getIteratorName().

Documentation / Developer's manual

Available modules

Public Types

Public Member Functions

Public Attributes

Printing Log

Manipulate attributs

Detailed Description

Member Enumeration Documentation

◆ ECAHMethod

◆ ENormalisation

◆ EOrigin

Constructor & Destructor Documentation

◆ TDataServer() [1/3]

◆ TDataServer() [2/3]

◆ TDataServer() [3/3]

◆ ~TDataServer()

Member Function Documentation

◆ addAttribute() [1/4]

◆ addAttribute() [2/4]

◆ addAttribute() [3/4]

◆ addAttribute() [4/4]

◆ addAttributeByNameTitle()

◆ addAttributeUsingData()

◆ bootstrap()

◆ changeIteratorName()

◆ changeLog()

◆ checkAttributes()

◆ checkCanvasCreation()

◆ checkName()

◆ cleanStatAndQuantiles()

◆ clearCut()

◆ clearSelect()

◆ computeCAH()

◆ computeCorrelationMatrix()

◆ computeIndexQuantileWilks()

◆ computeInverseNormalCDF()

◆ computeQuantile() [1/3]

◆ computeQuantile() [2/3]

◆ computeQuantile() [3/3]

◆ computeQuantileCV()

◆ computeRank()

◆ computeStatistic()

◆ createTuple()

◆ delAttribute()

◆ deleteTuple()

◆ doBanner()

◆ Draw()

◆ draw() [1/2]

◆ draw() [2/2]

◆ drawBoxPlot()

◆ drawCDF()

◆ drawCDFRaFu()

◆ drawCobWeb()

◆ drawCopulogram()

◆ drawECDF()

◆ drawHistogram()

◆ drawIter()

◆ drawLegend()

◆ drawPairs()

◆ drawPPPlot()

◆ drawProfile()

◆ drawQQorPPPlot()

◆ drawQQPlot()

◆ drawScatterplot()

◆ drawTufte()

◆ estimateQuantile() [1/2]

◆ estimateQuantile() [2/2]

◆ exportData()

◆ exportDataContext()

◆ exportDataHeader()

◆ exportDataNeMo()

◆ fileDataRead()

◆ fillAttribute()

◆ fillConstantAttribute()

◆ fillOthersAttributes()

◆ findParametersLaw()

◆ getArchiveFileName()

◆ getAttribute() [1/2]

◆ getAttribute() [2/2]