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added new method to TMVA::DataLoader #176

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b508224
added new method to TMVA::DataLoader
qati May 23, 2016
77ebf8d
New method TMVA::DataLoader::GetInputVariableHist
qati May 26, 2016
29ee3a9
added DataLoader::GetInputVariableHist
qati May 26, 2016
5fb9fac
fixes in DataLoader::GetInputVariableHist
qati May 26, 2016
46542c0
fixes in DataLoader::GetInputVariableHist
qati May 26, 2016
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33 changes: 18 additions & 15 deletions tmva/tmva/inc/TMVA/DataLoader.h
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Original file line number Diff line number Diff line change
Expand Up @@ -46,6 +46,9 @@
#include "TMVA/DataSet.h"
#endif

#include "TH1F.h"
#include "TH2.h"

class TFile;
class TTree;
class TDirectory;
Expand Down Expand Up @@ -88,16 +91,16 @@ namespace TMVA {
// special case: signal/background

// Data input related
void SetInputTrees( const TString& signalFileName, const TString& backgroundFileName,
void SetInputTrees( const TString& signalFileName, const TString& backgroundFileName,
Double_t signalWeight=1.0, Double_t backgroundWeight=1.0 );
void SetInputTrees( TTree* inputTree, const TCut& SigCut, const TCut& BgCut );
// Set input trees at once
void SetInputTrees( TTree* signal, TTree* background,
void SetInputTrees( TTree* signal, TTree* background,
Double_t signalWeight=1.0, Double_t backgroundWeight=1.0) ;

void AddSignalTree( TTree* signal, Double_t weight=1.0, Types::ETreeType treetype = Types::kMaxTreeType );
void AddSignalTree( TString datFileS, Double_t weight=1.0, Types::ETreeType treetype = Types::kMaxTreeType );
void AddSignalTree( TTree* signal, Double_t weight, const TString& treetype );
void AddSignalTree( TTree* signal, Double_t weight, const TString& treetype );

// ... depreciated, kept for backwards compatibility
void SetSignalTree( TTree* signal, Double_t weight=1.0);
Expand All @@ -113,9 +116,9 @@ namespace TMVA {
void SetBackgroundWeightExpression( const TString& variable );

// special case: regression
void AddRegressionTree( TTree* tree, Double_t weight = 1.0,
Types::ETreeType treetype = Types::kMaxTreeType ) {
AddTree( tree, "Regression", weight, "", treetype );
void AddRegressionTree( TTree* tree, Double_t weight = 1.0,
Types::ETreeType treetype = Types::kMaxTreeType ) {
AddTree( tree, "Regression", weight, "", treetype );
}

// general
Expand Down Expand Up @@ -157,10 +160,10 @@ namespace TMVA {
void PrepareTrainingAndTestTree( const TCut& cut, const TString& splitOpt );
void PrepareTrainingAndTestTree( TCut sigcut, TCut bkgcut, const TString& splitOpt );

// ... deprecated, kept for backwards compatibility
// ... deprecated, kept for backwards compatibility
void PrepareTrainingAndTestTree( const TCut& cut, Int_t Ntrain, Int_t Ntest = -1 );

void PrepareTrainingAndTestTree( const TCut& cut, Int_t NsigTrain, Int_t NbkgTrain, Int_t NsigTest, Int_t NbkgTest,
void PrepareTrainingAndTestTree( const TCut& cut, Int_t NsigTrain, Int_t NbkgTrain, Int_t NsigTest, Int_t NbkgTest,
const TString& otherOpt="SplitMode=Random:!V" );

void PrepareTrainingAndTestTree( int foldNumber, Types::ETreeType tt );
Expand All @@ -169,11 +172,12 @@ namespace TMVA {
void ValidationKFoldSet();
std::vector<TTree*> SplitSets(TTree * oldTree, int seedNum, int numFolds);



TH1F* GetInputVariableHist( const TString& className, const TString& variableName, UInt_t numBin, const TString& processTrfs);
TH2* GetCorrelationMatrix( const TString& className );

private:


DataInputHandler& DataInput() { return *fDataInputHandler; }
DataSetInfo& DefaultDataSetInfo();
void SetInputTreesFromEventAssignTrees();
Expand All @@ -186,7 +190,7 @@ namespace TMVA {

DataSetManager* fDataSetManager; // DSMTEST


DataInputHandler* fDataInputHandler;

std::vector<TMVA::VariableTransformBase*> fDefaultTrfs; //! list of transformations on default DataSet
Expand All @@ -199,7 +203,7 @@ namespace TMVA {
TString fName; //! name, used as directory in output

// flag determining the way training and test data are assigned to DataLoader
enum DataAssignType { kUndefined = 0,
enum DataAssignType { kUndefined = 0,
kAssignTrees,
kAssignEvents };
DataAssignType fDataAssignType; //! flags for data assigning
Expand All @@ -214,7 +218,7 @@ namespace TMVA {
Int_t fATreeType; // type of event (=classIndex)
Float_t fATreeWeight; // weight of the event
Float_t* fATreeEvent; // event variables

Types::EAnalysisType fAnalysisType; //! the training type

protected:
Expand All @@ -225,4 +229,3 @@ namespace TMVA {
} // namespace TMVA

#endif

4 changes: 3 additions & 1 deletion tmva/tmva/inc/TMVA/MethodBase.h
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Original file line number Diff line number Diff line change
Expand Up @@ -88,10 +88,12 @@ namespace TMVA {
class MethodCuts;
class MethodBoost;
class DataSetInfo;
class DataLoader;

class MethodBase : virtual public IMethod, public Configurable {

friend class Factory;
friend class DataLoader;

public:

Expand Down Expand Up @@ -182,7 +184,7 @@ namespace TMVA {
// helper function to set errors to -1
void NoErrorCalc(Double_t* const err, Double_t* const errUpper);

// signal/background classification response for all current set of data
// signal/background classification response for all current set of data
virtual std::vector<Double_t> GetMvaValues(Long64_t firstEvt = 0, Long64_t lastEvt = -1, Bool_t logProgress = false);


Expand Down
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