k Nearsest Neighbor algorithm More...

#include <TkNN.h>

Inheritance diagram for URANIE::Modeler::TkNN:

[legend]

Collaboration diagram for URANIE::Modeler::TkNN:

[legend]

Public Member Functions
Constructor and Destructor
	TkNN (URANIE::DataServer::TDataServer tds, TString architecture, Option_t option="")
	Default constructor with the TDataServer.

	TkNN (URANIE::DataServer::TDataServer tds, const char varexpinput, const char varexpoutput, Int_t nkernel, Option_t option="")
	Default constructor with input and output attributes.

virtual	~TkNN ()
	Default destructor.

Setter and Getter function
void	setK (Int_t k)
	Set the number of neighbor (\it k)

Int_t	getK ()
	Get the number of neighbor (\it k)

void	setQueryPoints (URANIE::DataServer::TDataServer *tds)
	Set the set of query points from a dataserver.

Estimate
void	draw (const char vars, Option_t option="")
	draw

void	estimate (Option_t *option="", Bool_t useGPU=false)
	make the learning

Export the model in extrenal langage
void	exportModelCplusplus (std::ofstream *sourcefile) const
	Export the model in C++ langage in a file.

void	exportModelFortran (std::ofstream *sourcefile) const
	Export the model in Fortran langage in a file.

void	exportModelPMML (const char file="", const char name="", Option_t *option="") const
	Export the model as a PMML function (not implemented)

void	exportModelPython (std::ofstream *sourcefile) const
	Export the model as a Python function (not implemented)

Public Member Functions inherited from URANIE::Modeler::TModeler
	TModeler (URANIE::DataServer::TDataServer tds, TString architecture, Option_t option="")
	Constructor with a dataserver.

	TModeler (URANIE::DataServer::TDataServer tds, const char varexpinput, const char varexpoutput, Option_t option="")
	Default constructor with input and output attributes.

virtual	~TModeler ()
	Default destructor.

TVectorD	getParameters ()
	Return the parameter vector of the model.

Double_t	getR2 () const
	Return the R2 quality.

const char *	getInputName (Int_t i) const
	Return the name of input attributes.

const char *	getOutputName (Int_t i=0)
	Return the name of output attribute.

Int_t	getNInput ()
	Gets the number of input.

Bool_t	getIntercept ()
	Gets the boolean attribut _bIntercept.

void	setDrawProgressBar (Bool_t bbool=kTRUE)
	Set the "draw progress bar" flag.

Bool_t	getDrawProgressBar ()
	Get the "draw progress bar" flag.

void	train (Option_t *option="text")

virtual void	exportFunction (const char lang, const char file="", const char name="", Option_t option="")
	Export the model in an external file with a specified langage.

void	setLog ()

void	unsetLog ()

void	changeLog ()

Bool_t	getLog ()

Public Attributes
Double_t	_dr2a
	The Adjusted R2 quality.

Int_t	_nK
	the number of neighboor to take into account

EDistance	_nDistance

TString	_sDraw
	! The distance normalized for input and output

URANIE::DataServer::TDataServer *	_tdsQuery
	the TDS contins the query points

Public Attributes inherited from URANIE::Modeler::TModeler
Bool_t	_blog
	Boolean for edit the log.

Bool_t	_bdrawProgressBar
	Boolean to know if the progress bar has to be drawn.

Bool_t	_bStoreYHat
	Boolean to specify if we add the \hat{} attribute in the TDS [default kTRUE].

URANIE::DataServer::TDataServer *	_tds

Int_t	_nS
	Pointer to a TDS.

TString	_sInputAttributes
	The string of input attributes (separated by the character ":".

TString	_sOutputAttributes
	The string of output attributes (separated by the character ":".

TString	_sIntermediateArchitecture
	The intermediate (between the first and last character ",") information.

TList *	_listOfInputAttributes
	The list of input Leaf.

TList *	_listOfOutputAttributes
	The list of output Leaf.

Int_t	_nX
	The number of input attributes.

Int_t	_nY
	The number of output attributes.

TString	_sFileName
	The name of the file when export the model without extension.

TString	_sFunctionName
	The name of the function when export the model.

TVectorD	_parameterValues
	The list of parameters.

Double_t	_dr2
	The R2 quality.

Bool_t	_bIntercept
	For certain models, add the intercept (Default is TRUE)

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

void	estimate_cpu (Option_t *option="")

void	LSort (int n, double array, int index, Int_t nbthreads)

void	beginLoop (Int_t iq, Int_t nsq)

void	endLoop (Int_t iq, int nsr, double vecDistance, int vecIndex, Float_t vecReferenceOutput, Double_t tabValue, TBranch *tby, Int_t nbthreads)

Detailed Description

k Nearsest Neighbor algorithm

The TDS in the constructor is the data set to the reference points.

Constructor & Destructor Documentation

◆ TkNN() [1/2]

URANIE::Modeler::TkNN::TkNN	(	URANIE::DataServer::TDataServer *	tds,
		TString	architecture,
		Option_t *	option = `""`
	)

Default constructor with the TDataServer.

Referenced by ClassImp().

◆ TkNN() [2/2]

URANIE::Modeler::TkNN::TkNN	(	URANIE::DataServer::TDataServer *	tds,
		const char *	varexpinput,
		const char *	varexpoutput,
		Int_t	nkernel,
		Option_t *	option = `""`
	)

Default constructor with input and output attributes.

◆ ~TkNN()

virtual URANIE::Modeler::TkNN::~TkNN ( )

virtual

Default destructor.

Referenced by ClassImp().

Member Function Documentation

◆ beginLoop()

void URANIE::Modeler::TkNN::beginLoop	(	Int_t	iq,
		Int_t	nsq
	)

private

Referenced by ClassImp().

◆ draw()

void URANIE::Modeler::TkNN::draw	(	const char *	vars,
		Option_t *	option = `""`
	)

draw

Referenced by ClassImp().

◆ endLoop()

void URANIE::Modeler::TkNN::endLoop	(	Int_t	iq,
		int	nsr,
		double *	vecDistance,
		int *	vecIndex,
		Float_t *	vecReferenceOutput,
		Double_t *	tabValue,
		TBranch *	tby,
		Int_t	nbthreads
	)

private

Referenced by ClassImp().

◆ estimate()

void URANIE::Modeler::TkNN::estimate	(	Option_t *	option = `""`,
		Bool_t	useGPU = `false`
	)

make the learning

Referenced by ClassImp().

◆ estimate_cpu()

void URANIE::Modeler::TkNN::estimate_cpu ( Option_t * option = "" )

private

Referenced by ClassImp().

◆ exportModelCplusplus()

void URANIE::Modeler::TkNN::exportModelCplusplus ( std::ofstream * sourcefile ) const

virtual

Export the model in C++ langage in a file.

Warning: Don't use this method. Use the main method TModeler::exportFunction.

Parameters

sourcefile (ofstream *) the pointer to the file to export the modeler.

Implements URANIE::Modeler::TModeler.

Referenced by ClassImp().

◆ exportModelFortran()

void URANIE::Modeler::TkNN::exportModelFortran ( std::ofstream * sourcefile ) const

virtual

Export the model in Fortran langage in a file.

Warning: Don't use this method. Use the main method TModeler::exportFunction.

Parameters

sourcefile (ofstream *) the pointer to the file to export the modeler.

Implements URANIE::Modeler::TModeler.

Referenced by ClassImp().

◆ exportModelPMML()

void URANIE::Modeler::TkNN::exportModelPMML	(	const char *	file = `""`,
		const char *	name = `""`,
		Option_t *	option = `""`
	)		const

inlinevirtual

Export the model as a PMML function (not implemented)

Implements URANIE::Modeler::TModeler.

◆ exportModelPython()

void URANIE::Modeler::TkNN::exportModelPython ( std::ofstream * sourcefile ) const

inlinevirtual

Export the model as a Python function (not implemented)

Implements URANIE::Modeler::TModeler.

◆ getK()

Int_t URANIE::Modeler::TkNN::getK ( )

inline

Get the number of neighbor (\it k)

References _nK.

◆ LSort()

void URANIE::Modeler::TkNN::LSort	(	int	n,
		double *	array,
		int *	index,
		Int_t	nbthreads
	)

private

Referenced by ClassImp().

◆ printLog()

virtual void URANIE::Modeler::TkNN::printLog ( Option_t * option = "" )

virtual

Reimplemented from URANIE::Modeler::TModeler.

Referenced by ClassImp().

◆ setK()

void URANIE::Modeler::TkNN::setK ( Int_t k )

inline

Set the number of neighbor (\it k)

Parameters

k	(Int_t) k is the number of neighbor into the reference points to select for a query point

References _nK.

◆ setQueryPoints()

void URANIE::Modeler::TkNN::setQueryPoints ( URANIE::DataServer::TDataServer * tds )

Set the set of query points from a dataserver.

Parameters

tds	(URANIE::DataServer::TDataServer) the TDS which contains the set of query points

Referenced by ClassImp().

Member Data Documentation

◆ _dr2a

Double_t URANIE::Modeler::TkNN::_dr2a

The Adjusted R2 quality.

◆ _nDistance

EDistance URANIE::Modeler::TkNN::_nDistance

Referenced by ClassImp().

◆ _nK

Int_t URANIE::Modeler::TkNN::_nK

the number of neighboor to take into account

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

◆ _sDraw

TString URANIE::Modeler::TkNN::_sDraw

! The distance normalized for input and output

Variables to visualize during the learning process

Referenced by ClassImp().

◆ _tdsQuery

URANIE::DataServer::TDataServer* URANIE::Modeler::TkNN::_tdsQuery

the TDS contins the query points

Referenced by ClassImp().

Documentation / Manuel développeur

Modules disponibles

Public Member Functions

Public Attributes

Printing Log

Detailed Description

Constructor & Destructor Documentation

◆ TkNN() [1/2]

◆ TkNN() [2/2]

◆ ~TkNN()

Member Function Documentation

◆ beginLoop()

◆ draw()

◆ endLoop()

◆ estimate()

◆ estimate_cpu()

◆ exportModelCplusplus()

◆ exportModelFortran()

◆ exportModelPMML()

◆ exportModelPython()

◆ getK()

◆ LSort()

◆ printLog()

◆ setK()

◆ setQueryPoints()

Member Data Documentation

◆ _dr2a

◆ _nDistance

◆ _nK

◆ _sDraw

◆ _tdsQuery