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C++ Factory::AddBackgroundTrainingEvent方法代码示例

本文整理汇总了C++中tmva::Factory::AddBackgroundTrainingEvent方法的典型用法代码示例。如果您正苦于以下问题:C++ Factory::AddBackgroundTrainingEvent方法的具体用法?C++ Factory::AddBackgroundTrainingEvent怎么用?C++ Factory::AddBackgroundTrainingEvent使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在tmva::Factory的用法示例。


在下文中一共展示了Factory::AddBackgroundTrainingEvent方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的C++代码示例。

示例1: TMVAClassification


//.........这里部分代码省略.........
"trackIP2dSig_2","trackIP3dSig_0","trackIP3dSig_1","trackIP3dSig_2","trackIP2d_0","trackIP2d_1",
"trackIP2d_2","trackIP3d_0","trackIP3d_1","trackIP3d_2","trackJetDist_0","trackDecayLenVal_0","svJetDeltaR",
"trackSumJetDeltaR","svtxNtrkInCone","svtxntrk","nIP"};

   //std::string variables[nvars] = {"jtpt","refpt","rawpt","refparton_flavorForB","svtxptFrac","svtxdl","svtxdls","closestDPt","closestDType","closestDMass","svtxm","svtxmcorr","svJetDeltaR","trackSumJetDeltaR","svtxpt","sv2Trkdl","svtxTrkSumChi2","svtxTrkNetCharge","svtxNtrkInCone","svtxntrk"};
   signal->SetBranchAddress("weight", &weight);
	
   for (UInt_t ivar=0; ivar<nvars-nvarsWithInt; ivar++) signal->SetBranchAddress( variables[ivar].c_str(), &(treevars[ivar]) );
   for (UInt_t ivar=nvars-nvarsWithInt; ivar<nvars; ivar++) signal->SetBranchAddress( variables[ivar].c_str(), &(treevars2[ivar]) );
   for (UInt_t i=0; i<signal->GetEntries(); i++) {
     signal->GetEntry(i);
     for (UInt_t ivar=0; ivar<nvars-nvarsWithInt; ivar++) vars[ivar] = treevars[ivar];
      for (UInt_t ivar=nvars-nvarsWithInt; ivar<nvars; ivar++) vars[ivar] = treevars2[ivar];
     // add training and test events; here: first half is training, second is testing
     // note that the weight can also be event-wise
     //for(int ij=0; ij<nvars; ij++) cout << ij << " " << vars[ij] << endl;
     if(isMC && (abs(vars[3])==4)) {
       if (i%2==0)  factory->AddSignalTrainingEvent( vars, weight );
       else                              factory->AddSignalTestEvent    ( vars, weight );
     }
   }
   //   
   //     // Background (has event weights)
   background->SetBranchAddress( "weight", &weight );
   for (UInt_t ivar=0; ivar<nvars-nvarsWithInt; ivar++) background->SetBranchAddress( variables[ivar].c_str(), &(treevars[ivar]) );
   for (UInt_t ivar=nvars-nvarsWithInt; ivar<nvars; ivar++) background->SetBranchAddress( variables[ivar].c_str(), &(treevars2[ivar]) );
   for (UInt_t i=0; i<background->GetEntries(); i++) {
     background->GetEntry(i);
     for (UInt_t ivar=0; ivar<nvars-nvarsWithInt; ivar++) vars[ivar] = treevars[ivar];
      for (UInt_t ivar=nvars-nvarsWithInt; ivar<nvars; ivar++) vars[ivar] = treevars2[ivar];
     // add training and test events; here: first half is training, second is testing
     // note that the weight can also be event-wise
     if(isMC && (abs(vars[3])==5)) {
       if (i%2==0) factory->AddBackgroundTrainingEvent( vars, weight );
       else                                factory->AddBackgroundTestEvent    ( vars, weight );
     }
   }
   // --- end ------------------------------------------------------------
   //
   // --- end of tree registration 

   // Set individual event weights (the variables must exist in the original TTree)
   //    for signal    : factory->SetSignalWeightExpression    ("weight1*weight2");
   //    for background: factory->SetBackgroundWeightExpression("weight1*weight2");
   factory->SetSignalWeightExpression("weight");
   factory->SetBackgroundWeightExpression( "weight" );

   // Apply additional cuts on the signal and background samples (can be different)
   TCut mycuts = ""; // for example: TCut mycuts = "abs(var1)<0.5 && abs(var2-0.5)<1";
   TCut mycutb = ""; // for example: TCut mycutb = "abs(var1)<0.5";
   
   // Tell the factory how to use the training and testing events
   //
   // If no numbers of events are given, half of the events in the tree are used 
   // for training, and the other half for testing:
   //    factory->PrepareTrainingAndTestTree( mycut, "SplitMode=random:!V" );
   // To also specify the number of testing events, use:
   //    factory->PrepareTrainingAndTestTree( mycut,
   //                                         "NSigTrain=3000:NBkgTrain=3000:NSigTest=3000:NBkgTest=3000:SplitMode=Random:!V" );
   factory->PrepareTrainingAndTestTree( mycuts, mycutb,
                                        "nTrain_Signal=0:nTrain_Background=0:SplitMode=Random:NormMode=NumEvents:!V" );

   // ---- Book MVA methods
   //
   // Please lookup the various method configuration options in the corresponding cxx files, eg:
   // src/MethoCuts.cxx, etc, or here: http://tmva.sourceforge.net/optionRef.html
开发者ID:kurtejung,项目名称:charmJets,代码行数:67,代码来源:TMVAClassification.C


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