// @(#)root/tmva $Id$
// Author: Andreas Hoecker, Peter Speckmayer, Joerg Stelzer, Helge Voss, Kai Voss, Eckhard von Toerne, Jan Therhaag
/**********************************************************************************
* Project: TMVA - a Root-integrated toolkit for multivariate data analysis *
* Package: TMVA *
* Class : Reader *
* Web : http://tmva.sourceforge.net *
* *
* Description: *
* Reader class to be used in the user application to interpret the trained *
* MVAs in an analysis context *
* *
* Authors (alphabetical order): *
* Andreas Hoecker <Andreas.Hocker@cern.ch> - CERN, Switzerland *
* Peter Speckmayer <peter.speckmayer@cern.ch> - CERN, Switzerland *
* Joerg Stelzer <Joerg.Stelzer@cern.ch> - CERN, Switzerland *
* Jan Therhaag <Jan.Therhaag@cern.ch> - U of Bonn, Germany *
* Eckhard v. Toerne <evt@uni-bonn.de> - U of Bonn, Germany *
* Helge Voss <Helge.Voss@cern.ch> - MPI-K Heidelberg, Germany *
* Kai Voss <Kai.Voss@cern.ch> - U. of Victoria, Canada *
* *
* Copyright (c) 2005-2011: *
* CERN, Switzerland *
* U. of Victoria, Canada *
* MPI-K Heidelberg, Germany *
* U. of Bonn, Germany *
* *
* Redistribution and use in source and binary forms, with or without *
* modification, are permitted according to the terms listed in LICENSE *
* (http://ttmva.sourceforge.net/LICENSE) *
**********************************************************************************/
#ifndef ROOT_TMVA_Reader
#define ROOT_TMVA_Reader
//////////////////////////////////////////////////////////////////////////
// //
// Reader //
// //
// Reader class to be used in the user application to interpret the //
// trained MVAs in an analysis context //
// //
//////////////////////////////////////////////////////////////////////////
#ifndef ROOT_TMVA_Configurable
#include "TMVA/Configurable.h"
#endif
#ifndef ROOT_TMVA_Types
#include "TMVA/Types.h"
#endif
#ifndef ROOT_TMVA_DataSetInfo
#include "TMVA/DataSetInfo.h"
#endif
#ifndef ROOT_TMVA_DataInputHandler
#include "TMVA/DataInputHandler.h"
#endif
#ifndef ROOT_TMVA_DataSetManager
#include "TMVA/DataSetManager.h"
#endif
#include <vector>
#include <map>
#include <stdexcept>
namespace TMVA {
class IMethod;
class MethodBase;
class DataSetInfo;
class MethodCuts;
class Reader : public Configurable {
public:
// without prior specification of variables
Reader( const TString& theOption="", Bool_t verbose = 0 );
// STL types
Reader( std::vector<std::string>& varNames, const TString& theOption = "", Bool_t verbose = 0 );
Reader( const std::string& varNames, const TString& theOption, Bool_t verbose = 0 ); // format: "var1:var2:..."
// Root types
Reader( std::vector<TString>& varNames, const TString& theOption = "", Bool_t verbose = 0 );
Reader( const TString& varNames, const TString& theOption, Bool_t verbose = 0 ); // format: "var1:var2:..."
virtual ~Reader( void );
// book MVA method via weight file
IMethod* BookMVA( const TString& methodTag, const TString& weightfile );
IMethod* BookMVA( TMVA::Types::EMVA methodType, const char* xmlstr );
IMethod* FindMVA( const TString& methodTag );
// special function for Cuts to avoid dynamic_casts in ROOT macros,
// which are not properly handled by CINT
MethodCuts* FindCutsMVA( const TString& methodTag );
// returns the MVA response for given event
Double_t EvaluateMVA( const std::vector<Float_t> &, const TString& methodTag, Double_t aux = 0 );
Double_t EvaluateMVA( const std::vector<Double_t>&, const TString& methodTag, Double_t aux = 0 );
Double_t EvaluateMVA( MethodBase* method, Double_t aux = 0 );
Double_t EvaluateMVA( const TString& methodTag, Double_t aux = 0 );
// returns error on MVA response for given event
// NOTE: must be called AFTER "EvaluateMVA(...)" call !
Double_t GetMVAError() const { return fMvaEventError; }
Double_t GetMVAErrorLower() const { return fMvaEventError; }
Double_t GetMVAErrorUpper() const { return fMvaEventErrorUpper; }
// regression response
const std::vector< Float_t >& EvaluateRegression( const TString& methodTag, Double_t aux = 0 );
const std::vector< Float_t >& EvaluateRegression( MethodBase* method, Double_t aux = 0 );
Float_t EvaluateRegression( UInt_t tgtNumber, const TString& methodTag, Double_t aux = 0 );
// multiclass response
const std::vector< Float_t >& EvaluateMulticlass( const TString& methodTag, Double_t aux = 0 );
const std::vector< Float_t >& EvaluateMulticlass( MethodBase* method, Double_t aux = 0 );
Float_t EvaluateMulticlass( UInt_t clsNumber, const TString& methodTag, Double_t aux = 0 );
// probability and rarity accessors (see Users Guide for definition of Rarity)
Double_t GetProba ( const TString& methodTag, Double_t ap_sig=0.5, Double_t mvaVal=-9999999 );
Double_t GetRarity( const TString& methodTag, Double_t mvaVal=-9999999 );
// accessors
virtual const char* GetName() const { return "Reader"; }
Bool_t Verbose( void ) const { return fVerbose; }
void SetVerbose( Bool_t v ) { fVerbose = v; }
const DataSetInfo& DataInfo() const { return fDataSetInfo; }
DataSetInfo& DataInfo() { return fDataSetInfo; }
void AddVariable( const TString& expression, Float_t* );
void AddVariable( const TString& expression, Int_t* );
void AddSpectator( const TString& expression, Float_t* );
void AddSpectator( const TString& expression, Int_t* );
private:
DataSetManager* fDataSetManager; // DSMTEST
TString GetMethodTypeFromFile( const TString& filename );
// this booking method is internal
IMethod* BookMVA( Types::EMVA method, const TString& weightfile );
DataSetInfo fDataSetInfo; // the data set
DataInputHandler fDataInputHandler;
// Init Reader class
void Init( void );
// Decode Constructor string (or TString) and fill variable name std::vector
void DecodeVarNames( const std::string& varNames );
void DecodeVarNames( const TString& varNames );
void DeclareOptions();
Bool_t fVerbose; // verbosity
Bool_t fSilent; // silent mode
Bool_t fColor; // color mode
Bool_t fCalculateError; // error calculation mode
Double_t fMvaEventError; // per-event error returned by MVA
Double_t fMvaEventErrorUpper; // per-event error returned by MVA
std::map<TString, IMethod*> fMethodMap; // map of methods
std::vector<Float_t> fTmpEvalVec; // temporary evaluation vector (if user input is v<double>)
mutable MsgLogger* fLogger; // message logger
MsgLogger& Log() const { return *fLogger; }
ClassDef(Reader,0) // Interpret the trained MVAs in an analysis context
};
}
#endif