C++ Factory::AddSignalTree方法代码示例

void makeFactory(TTree* signalTree, TTree* backTree,std::string outfile,std::string factoryname, TTree* bgTree2=NULL)
{
  using namespace TMVA;
  TString jobname(factoryname.c_str());
  TFile *targetFile = new TFile(outfile.c_str(),"RECREATE");
  Factory *factory = new Factory(jobname,targetFile);
  factory->AddSignalTree(signalTree,1.0);
  factory->AddBackgroundTree(backTree,1.0);
  if(bgTree2){
    factory->AddBackgroundTree(bgTree2,1.0);
  }
  factory->AddVariable("track_deta",'F');
  factory->AddVariable("track_dlayer",'I');
  factory->AddVariable("track_layer",'I');
  factory->AddVariable("track_pT",'F');
//  factory->AddVariable("approach_dist",'F');
  factory->AddVariable("vtx_radius",'F');
  //factory->AddVariable("vtx_chi2",'F'); //until reco vtx works this is meaningless
  factory->AddVariable("vtxTrack_dist",'F');
  //factory->AddVariable("photon_m",'F');
  //factory->AddVariable("photon_pT",'F');
  factory->AddVariable("cluster_prob",'F');

  factory->AddSpectator("vtx_chi2",'F'); //until reco vtx works this is meaningless


  string track_pT_cut = "track_pT>0";
  string vtx_radius_cut = "vtx_radius>0";
  string em_prob_cut = "cluster_prob>=0";
  //do I need photon cuts? 
  string tCutInitializer = em_prob_cut+"&&"+ vtx_radius_cut+"&&"+track_pT_cut+"&&track_dlayer>=0&&track_layer>=0&&approach_dist>0&&vtxTrack_dist>0&&photon_m>0&&photon_pT>0";
  TCut preTraingCuts(tCutInitializer.c_str());


  factory->PrepareTrainingAndTestTree(preTraingCuts,"nTrain_Signal=0:nTrain_Background=0:nTest_Signal=0:nTest_Background=0");
  factory->BookMethod( TMVA::Types::kLikelihood, "LikelihoodD",
      "!H:!V:!TransformOutput:PDFInterpol=Spline2:NSmoothSig[0]=20:NSmoothBkg[0]=20:NSmooth=5:NAvEvtPerBin=50:VarTransform=Decorrelate" );
  factory->BookMethod(Types::kCuts,"Cuts","");
  /*factory->BookMethod( Types::kKNN, "kNN", "" ); //>100k events
  factory->BookMethod( Types::kPDERS, "PDERS", "" );//>100k events*/
  /*factory->BookMethod( Types::kPDEFoam, "PDEFoam", "VolFrac=.0588i:SigBgSeparate=True" );//>10k events
  factory->BookMethod( Types::kFisher, "Fisher", "" );
  factory->BookMethod( Types::kLD, "LD" );*/
  /*would need to have the options tuned
   * factory->BookMethod( Types::kFDA, "FDA", "Formula=(0)+(1)*x0+(2)*x1+(3)*x2+(4)*x3:\
      ParRanges=(-1,1);(-10,10);(-10,10);(-10,10);(-10,10):\
      FitMethod=MINUIT:\
      ErrorLevel=1:PrintLevel=-1:FitStrategy=2:UseImprove:UseMinos:SetBatch" );*/
/* nerual network that would need to be worked on 
 * factory->BookMethod( Types::kMLP, "MLP_ANN", "<options>" );*/
  factory->TrainAllMethods();
  factory->TestAllMethods();
  factory->EvaluateAllMethods();
  targetFile->Write();
  targetFile->Close();
}

int mkFactory(const char *fileName="../QG_QCD_Pt-15to3000_TuneZ2_Flat_7TeV_pythia6_Fall11-PU_S6_START42_V14B-v1_fix_new_TREE.root",const char*treeName="tree_passedEvents")
{

TFile *f=TFile::Open(fileName);
if(f==NULL){fprintf(stderr,"No such file or Directory: %s\n",fileName);return 1;}
TTree *t=(TTree*)f->Get(treeName);
if(t==NULL){fprintf(stderr,"No such tree: %s\n",treeName);return 2;}

using namespace TMVA;
TCut mycuts = "abs(pdgIdPartJet0)<4 && 30<ptJet0 && ptJet0<40 && 8<rhoPF && rhoPF<10 && abs(etaJet0)<2"; // for example: TCut mycuts = "abs(var1)<0.5 && abs(var2-0.5)<1";
TCut mycutb = "pdgIdPartJet0==21 && 30<ptJet0 && ptJet0<40 && 8<rhoPF && rhoPF<10 && abs(etaJet0)<2"; // 

TFile *out =TFile::Open("TMVA1_30_40.root","RECREATE");
if(out==NULL){fprintf(stderr,"Unable to create TMVA.root\n");return 3;}

Factory *fac =new Factory( "TMVAClassification", out, "!V:!Silent:Color:DrawProgressBar:Transformations=I;D;P;G,D" );

fac->AddVariable("ptD_QCJet0",'F');
fac->AddVariable("(nChargedJet0+nNeutralJet0)",'F');
//fac->AddVariable("nNeutralJet0",'F');
//fac->AddVariable("rmsCandJet0",'F');
//fac->AddVariable("axis1Jet0",'F');
//fac->AddVariable("axis2Jet0",'F');
//fac->AddVariable("pullJet0",'F');
//fac->AddVariable("RJet0",'F');
//fac->AddVariable("pull_QCJet0",'F');
fac->AddVariable("axis1_QCJet0",'F');
fac->AddVariable("TMath::Max(axis2_QCJet0,0)",'F');
//fac->AddVariable("ptD_QCJet0",'F');
//fac->AddVariable("rmsCand_QCJet0",'F');



fac->AddSignalTree(t);
fac->AddBackgroundTree(t);

fac->PrepareTrainingAndTestTree(mycuts,mycutb,"!V:SplitMode=Random");
fac->BookMethod(TMVA::Types::kBDT, "BDT",
	            "!H:!V:NTrees=850:nEventsMin=150:MaxDepth=6:BoostType=AdaBoost:AdaBoostBeta=0.5:SeparationType=GiniIndex:nCuts=20:PruneMethod=NoPruning");
fac->BookMethod(TMVA::Types::kLikelihood, "Likelihood","!H:!V");
	 
	fac->TrainAllMethods();
	fac->TestAllMethods();
	fac->EvaluateAllMethods();
//
TFile *out2=TFile::Open("TMVA2_30_40.root","RECREATE");
Factory *fac2=new Factory( "TMVAClassification2", out2, "!V:!Silent:Color:DrawProgressBar" );
// PAOLO
//fac2->AddVariable("qglPaoloJet0",'F');
fac2->AddVariable("nChargedJet0",'F');
fac2->AddVariable("axis1_QCJet0",'F');
fac2->AddVariable("TMath::Max(axis2_QCJet0,0)",'F');
fac2->AddVariable("RJet0",'F');
fac2->AddVariable("pullJet0",'F');

fac2->AddSignalTree(t);
fac2->AddBackgroundTree(t);


fac2->PrepareTrainingAndTestTree(mycuts,mycutb,"!V:SplitMode=Random");
fac2->BookMethod(TMVA::Types::kBDT, "BDT",
	            "!H:!V:NTrees=850:nEventsMin=150:MaxDepth=6:BoostType=AdaBoost:AdaBoostBeta=0.5:SeparationType=GiniIndex:nCuts=20:PruneMethod=NoPruning");
fac2->BookMethod(TMVA::Types::kLikelihood, "Likelihood","!H:!V");
	 
	fac2->TrainAllMethods();
	fac2->TestAllMethods();
	fac2->EvaluateAllMethods();
//
TFile *out3=TFile::Open("TMVA3_30_40.root","RECREATE");
Factory *fac3=new Factory( "TMVAClassification3", out3, "!V:!Silent:Color:DrawProgressBar" );
//QGL
fac3->AddVariable("qglJet0",'F');

fac3->AddSignalTree(t);
fac3->AddBackgroundTree(t);

fac3->PrepareTrainingAndTestTree(mycuts,mycutb,"!V:SplitMode=Random");
fac3->BookMethod(TMVA::Types::kBDT, "BDT",
	            "!H:!V:NTrees=10:nEventsMin=150:MaxDepth=1:BoostType=AdaBoost:AdaBoostBeta=0.5:SeparationType=GiniIndex:nCuts=20:PruneMethod=NoPruning");
fac3->BookMethod(TMVA::Types::kLikelihood, "Likelihood","!H:!V");
	 
	fac3->TrainAllMethods();
	fac3->TestAllMethods();
	fac3->EvaluateAllMethods();

TFile *out4=TFile::Open("TMVA4_30_40.root","RECREATE");
Factory *fac4=new Factory( "TMVAClassification4", out4, "!V:!Silent:Color:DrawProgressBar" );
//QGL
fac4->AddVariable("ptD_QCJet0",'F');
fac4->AddVariable("nChargedJet0",'F');
fac4->AddVariable("axis1_QCJet0",'F');
fac4->AddVariable("TMath::Max(axis2_QCJet0,0)",'F');

fac4->AddSignalTree(t);
fac4->AddBackgroundTree(t);

fac4->PrepareTrainingAndTestTree(mycuts,mycutb,"!V:SplitMode=Random");
//fac4->BookMethod(TMVA::Types::kBDT, "BDT",
//	            "!H:!V:NTrees=10:nEventsMin=150:MaxDepth=1:BoostType=AdaBoost:AdaBoostBeta=0.5:SeparationType=GiniIndex:nCuts=20:PruneMethod=NoPruning");
fac4->BookMethod(TMVA::Types::kLikelihood, "Likelihood","!H:!V");
//.........这里部分代码省略.........