Interface Class Reference

#include <Interface.h>

Inheritance diagram for Interface:

List of all members.

Public Member Functions
	Interface ()
	Interface (std::string trName, std::string dirName, std::string fileName)
	~Interface ()
void	SetInputVariableAt (Int_t index, TVariable var)
void	SetTargetVariableAt (Int_t index, TVariable var)
TVariable &	GetInputVariable (Int_t index)
TVariable &	GetTargetVariable (Int_t index)
std::string	getTreeName () const
std::string	getNetName ()
TFile *	GetOutFile ()
Double_t	getAverageValidError () const
Double_t	getMinimumValidError () const
Int_t	getMinimumValidErrorEpoch () const
void	SetMaximumEpochs (Int_t i)
void	SetUpdateEpochs (Int_t i)
void	setTreeName (std::string name)
void	setNetName (std::string name)
void	setOutDirectory (std::string name)
void	WriteMasterTree (Bool_t flag)
void	WritePerformanceTree (Bool_t flag)
void	WritePatternTree (Bool_t flag)
void	WriteErrorHistograms (Bool_t flag)
Bool_t	WriteMasterTree ()
Bool_t	WritePerformanceTree ()
Bool_t	WritePatternTree ()
Bool_t	WriteErrorHistograms ()
void	setMinimumValidError (Double_t value)
Int_t	PrintVariables ()
	Prints out definitions of input and target variables.
void	AddInputVariable (TString formula, TString name, Double_t defValue=0.0)
	Adds a variable to the vector of input variables .
void	AddInputVariable (TString formula, Double_t defValue=0.0)
	Adds a variable to the vector of input variables .
void	AddTargetVariable (TString formula, TString name, Double_t defValue=0.0)
	Adds a variable to the vector of target variables .
void	AddTargetVariable (TString formula, Double_t defValue=0.0)
	Adds a variable to the vector of target variables .
Int_t	AllocatePatternSet (std::string type="")
	Creates a new SNNS pattern set in memory by setting activations of input and output NN units.
void	SetSelection (std::string selection="")
void	FillPatternSet (std::string fileName, Int_t startEvent=0, Int_t nOfEvents=-1, std::string type="")
	Fills the pattern set vector with values from an input file given by .
void	savePatternSets ()
	Saves the input, target, and output values of each pattern to a tree in the output file.
std::string	runtimeInput2string ()
std::string	CreateNN (std::vector< Int_t > numHiddenNodes)
	Creates a file containing NN definition in SNNS format with the given number of hidden units.
void	InitializeNN (std::vector< Float_t > initParams=0, std::string initFunc="Randomize_Weights", Int_t randomSeed=12345)
	Initializes the neural network with different initialization functions and corresponding parameters.
void	TrainValidate (std::string trainType, std::string validType, std::vector< Double_t > learnParams)
	The main training proceedure with online validation of the neural network using the pattern set.
void	TrainValidateApply (std::string trainType, std::string validType, std::vector< Double_t > learnParams, std::string genErrType)
void	PropagatePatterns (std::string type="")
	Using this method user can propagate the whole pattern set or its subset specified by through the ANN.
void	ActivateInputs (Pattern pattern)
void	FillPerformanceTree ()
void	CalculateError (std::string type)
	Calculats an error defined as the difference between an actual NN output and a desired target value.
Int_t	AllocNewPatternSet ()
void	LoadNN ()
	Loads a neural network definition from the file and makes it the currently active one.
void	LoadNN (char *filename, char **netname)
	Loads a neural network definition from the file and makes it the currently active one.
void	SaveNN (char *filename, char *netname)
	Saves the currently active neural network to the file.
void	SetSeedNo (long seed)
void	SetLearnFunc (char *learning_func)
char *	GetLearnFunc ()
void	Finalize ()
void	PrintProgress (Int_t i, Int_t iMax)
Int_t	Timer (Int_t i)
std::string	TimeStoHMS (UInt_t diffTime)
Protected Attributes
std::vector< TVariable >	fInputVariables
std::vector< TVariable >	fTargetVariables
std::string	_pathto_ff_bignet
std::string	fNetFilePrefix
std::string	fNetFileSuffix
std::string	fNetName
	The name of a currently active NN.
std::string	fTreeName
std::string	fDirName
std::string	fSelection
TObjArray *	fInputTrees
TFile *	fOutFile
TTree *	fMasterTree
TTree *	fPatternTree
TTree *	fPerformaceTree
Bool_t	fWriteMasterTree
Bool_t	fWritePerformanceTree
Bool_t	fWritePatternTree
Bool_t	fWriteErrorHistograms
Bool_t	fBannerPrinted
Int_t	fMaxEpochs
Int_t	fUpdEpochs
Double_t	averageValidError
Double_t	minimumValidError
Int_t	minimumValidErrorEpoch
Double_t	RMSTestError
Int_t	hiddenLayerSize
Int_t	fRandomSeed

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Constructor & Destructor Documentation

Interface::Interface (   )

Interface::Interface (  std::string  trName, std::string  dirName, std::string  fileName )

Interface::~Interface (   )

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Member Function Documentation

void Interface::ActivateInputs (  Pattern  pattern  )

void Interface::AddInputVariable (  TString  formula, Double_t  defValue = 0.0 )

Adds a variable to the vector of input variables .

void Interface::AddInputVariable (  TString  formula, TString  name, Double_t  defValue = 0.0 )

Adds a variable to the vector of input variables .

void Interface::AddTargetVariable (  TString  formula, Double_t  defValue = 0.0 )

Adds a variable to the vector of target variables .

void Interface::AddTargetVariable (  TString  formula, TString  name, Double_t  defValue = 0.0 )

Adds a variable to the vector of target variables .

Int_t Interface::AllocatePatternSet (  std::string  type = ""  )

Creates a new SNNS pattern set in memory by setting activations of input and output NN units. Input and target values of each pattern are selected from the pattern set vector where type is . If equals "" then all patterns are selected into memory resident SNNS pattern set. NN must be loaded before calling this function.

Int_t Interface::AllocNewPatternSet (   )

void Interface::CalculateError (  std::string  type  )

Calculats an error defined as the difference between an actual NN output and a desired target value. The differences are summed in quadrature for all NN outputs and the final value is normalized as: Reimplemented from PatternManager.

string Interface::CreateNN (  std::vector< Int_t >  numHiddenNodes  )

Creates a file containing NN definition in SNNS format with the given number of hidden units.

void Interface::FillPatternSet (  std::string  fileName, Int_t  startEvent = 0, Int_t  noOfEvents = -1, std::string  type = "" )

Fills the pattern set vector with values from an input file given by .

void Interface::FillPerformanceTree (   )

void Interface::Finalize (   )

Double_t Interface::getAverageValidError (   )  const [inline]

TVariable & Interface::GetInputVariable (  Int_t  index  )  [inline]

char * Interface::GetLearnFunc (   )

Double_t Interface::getMinimumValidError (   )  const [inline]

Int_t Interface::getMinimumValidErrorEpoch (   )  const [inline]

std::string Interface::getNetName (   )  [inline]

TFile* Interface::GetOutFile (   )  [inline]

TVariable & Interface::GetTargetVariable (  Int_t  index  )  [inline]

std::string Interface::getTreeName (   )  const [inline]

void Interface::InitializeNN (  std::vector< Float_t >  initParams = 0, std::string  initFunc = "Randomize_Weights", Int_t  randomSeed = 12345 )

Initializes the neural network with different initialization functions and corresponding parameters. Since initialization is usually random in nature, a random seed number can be provided by the user.

void Interface::LoadNN (  char *  filename, char **  netname )

Loads a neural network definition from the file and makes it the currently active one.

void Interface::LoadNN (   )

Loads a neural network definition from the file and makes it the currently active one.

void Interface::PrintProgress (  Int_t  i, Int_t  iMax )

Int_t Interface::PrintVariables (   )

Prints out definitions of input and target variables.

void Interface::PropagatePatterns (  std::string  type = ""  )

Using this method user can propagate the whole pattern set or its subset specified by through the ANN. A memory-resident SNNS pattern set is not created due to very slow and inefficient memory allocation for SNNS pattern sets with a large number of patterns, instead the inputs are taken directly from the pattern set. The inputs from each pattern in this pattern (sub)set are then propagated through the current ANN and outputs are caluclated and saved to the pattern.

string Interface::runtimeInput2string (   )

void Interface::SaveNN (  char *  filename, char *  netname )

Saves the currently active neural network to the file.

void Interface::savePatternSets (   )

Saves the input, target, and output values of each pattern to a tree in the output file.

void Interface::SetInputVariableAt (  Int_t  index, TVariable  var )  [inline]

void Interface::SetLearnFunc (  char *  learnFuncName  )

void Interface::SetMaximumEpochs (  Int_t  i  )  [inline]

void Interface::setMinimumValidError (  Double_t  value  )  [inline]

void Interface::setNetName (  std::string  name  )  [inline]

void Interface::setOutDirectory (  std::string  name  )  [inline]

void Interface::SetSeedNo (  long  seed  )

void Interface::SetSelection (  std::string  selection = ""  )

void Interface::SetTargetVariableAt (  Int_t  index, TVariable  var )  [inline]

void Interface::setTreeName (  std::string  name  )  [inline]

void Interface::SetUpdateEpochs (  Int_t  i  )  [inline]

Int_t Interface::Timer (  Int_t  i  )

string Interface::TimeStoHMS (  UInt_t  diffTime  )

void Interface::TrainValidate (  std::string  trainType, std::string  validType, std::vector< Double_t >  learnParams )

The main training proceedure with online validation of the neural network using the pattern set. The training and validation subsets (samples) are defined by and strings. The learning parameters is used for online validation of the training.

void Interface::TrainValidateApply (  std::string  trainType, std::string  validType, std::vector< Double_t >  learnParams, std::string  genErrType )

Bool_t Interface::WriteErrorHistograms (   )  [inline]

void Interface::WriteErrorHistograms (  Bool_t  flag  )  [inline]

Bool_t Interface::WriteMasterTree (   )  [inline]

void Interface::WriteMasterTree (  Bool_t  flag  )  [inline]

Bool_t Interface::WritePatternTree (   )  [inline]

void Interface::WritePatternTree (  Bool_t  flag  )  [inline]

Bool_t Interface::WritePerformanceTree (   )  [inline]

void Interface::WritePerformanceTree (  Bool_t  flag  )  [inline]

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Member Data Documentation

std::string Interface::_pathto_ff_bignet [protected]

Double_t Interface::averageValidError [protected]

Bool_t Interface::fBannerPrinted [protected]

std::string Interface::fDirName [protected]

TObjArray* Interface::fInputTrees [protected]

std::vector<TVariable> Interface::fInputVariables [protected]

TTree* Interface::fMasterTree [protected]

Int_t Interface::fMaxEpochs [protected]

std::string Interface::fNetFilePrefix [protected]

std::string Interface::fNetFileSuffix [protected]

std::string Interface::fNetName [protected]

The name of a currently active NN.

TFile* Interface::fOutFile [protected]

TTree* Interface::fPatternTree [protected]

TTree* Interface::fPerformaceTree [protected]

Int_t Interface::fRandomSeed [protected]

std::string Interface::fSelection [protected]

std::vector<TVariable> Interface::fTargetVariables [protected]

std::string Interface::fTreeName [protected]

Int_t Interface::fUpdEpochs [protected]

Bool_t Interface::fWriteErrorHistograms [protected]

Bool_t Interface::fWriteMasterTree [protected]

Bool_t Interface::fWritePatternTree [protected]

Bool_t Interface::fWritePerformanceTree [protected]

Int_t Interface::hiddenLayerSize [protected]

Double_t Interface::minimumValidError [protected]

Int_t Interface::minimumValidErrorEpoch [protected]

Double_t Interface::RMSTestError [protected]

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

• Interface.h
• Interface.cxx

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