TMVACrossValidationApplication.C File Reference

Detailed Description

This macro provides an example of how to use TMVA for k-folds cross evaluation in application.

This requires that CrossValidation was run with a deterministic split, such as "...:splitExpr=int([eventID])%int([numFolds]):...".

• Project : TMVA - a ROOT-integrated toolkit for multivariate data analysis
• Package : TMVA
• Root Macro: TMVACrossValidationApplication

 
#include <cstdlib>
#include <iostream>
#include <map>
#include <string>
 
#include "TChain.h"
#include "TFile.h"
#include "TTree.h"
#include "TString.h"
#include "TObjString.h"
#include "TSystem.h"
#include "TROOT.h"
 
#include "TMVA/Factory.h"
#include "TMVA/DataLoader.h"
#include "TMVA/Tools.h"
#include "TMVA/TMVAGui.h"
 
// Helper function to load data into TTrees.
TTree *fillTree(TTree * tree, Int_t nPoints, Double_t offset, Double_t scale, UInt_t seed = 100)
{
   TRandom3 rng(seed);
   Float_t x = 0;
   Float_t y = 0;
   Int_t eventID = 0;
 
   tree->SetBranchAddress("x", &x);
   tree->SetBranchAddress("y", &y);
   tree->SetBranchAddress("eventID", &eventID);
 
   for (Int_t n = 0; n < nPoints; ++n) {
      x = rng.Gaus(offset, scale);
      y = rng.Gaus(offset, scale);
 
      // For our simple example it is enough that the id's are uniformly
      // distributed and independent of the data.
      ++eventID;
 
      tree->Fill();
   }
 
   // Important: Disconnects the tree from the memory locations of x and y.
   tree->ResetBranchAddresses();
   return tree;
}
 
int TMVACrossValidationApplication()
{
   // This loads the library
   TMVA::Tools::Instance();
 
   // Set up the TMVA::Reader
   TMVA::Reader *reader = new TMVA::Reader("!Color:!Silent:!V");
 
   Float_t x;
   Float_t y;
   Int_t eventID;
 
   reader->AddVariable("x", &x);
   reader->AddVariable("y", &y);
   reader->AddSpectator("eventID", &eventID);
 
   // Book the serialised methods
   TString jobname("TMVACrossValidation");
   {
      TString methodName = "BDTG";
      TString weightfile = TString("datasetcv/weights/") + jobname + "_" + methodName + TString(".weights.xml");
 
      Bool_t weightfileExists = (gSystem->AccessPathName(weightfile) == kFALSE);
      if (weightfileExists) {
         reader->BookMVA(methodName, weightfile);
      } else {
         std::cout << "Weightfile for method " << methodName << " not found."
                      " Did you run TMVACrossValidation with a specified"
                      " splitExpr?" << std::endl;
         exit(0);
      }
 
   }
   {
      TString methodName = "Fisher";
      TString weightfile = TString("datasetcv/weights/") + jobname + "_" + methodName + TString(".weights.xml");
 
      Bool_t weightfileExists = (gSystem->AccessPathName(weightfile) == kFALSE);
      if (weightfileExists) {
         reader->BookMVA(methodName, weightfile);
      } else {
         std::cout << "Weightfile for method " << methodName << " not found."
                      " Did you run TMVACrossValidation with a specified"
                      " splitExpr?" << std::endl;
         exit(0);
      }
   }
 
   // Load data
   TTree *tree = new TTree();
   tree->Branch("x", &x, "x/F");
   tree->Branch("y", &y, "y/F");
   tree->Branch("eventID", &eventID, "eventID/I");
 
   fillTree(tree, 1000, 1.0, 1.0, 100);
   fillTree(tree, 1000, -1.0, 1.0, 101);
   tree->SetBranchAddress("x", &x);
   tree->SetBranchAddress("y", &y);
   tree->SetBranchAddress("eventID", &eventID);
 
   // Prepare histograms
   Int_t nbin = 100;
   TH1F histBDTG{"BDTG", "BDTG", nbin, -1, 1};
   TH1F histFisher{"Fisher", "Fisher", nbin, -1, 1};
 
   // Evaluate classifiers
   for (Long64_t ievt = 0; ievt < tree->GetEntries(); ievt++) {
      tree->GetEntry(ievt);
 
      Double_t valBDTG = reader->EvaluateMVA("BDTG");
      Double_t valFisher = reader->EvaluateMVA("Fisher");
 
      histBDTG.Fill(valBDTG);
      histFisher.Fill(valFisher);
   }
 
   tree->ResetBranchAddresses();
   delete tree;
 
   if (!gROOT->IsBatch()) {
      auto c = new TCanvas();
      c->Divide(2,1);
      c->cd(1);
      histBDTG.DrawClone();
      c->cd(2);
      histFisher.DrawClone();
   }
   else
   { // Write histograms to output file
      TFile *target = new TFile("TMVACrossEvaluationApp.root", "RECREATE");
      histBDTG.Write();
      histFisher.Write();
      target->Close();
      delete target;
   }
 
   delete reader;
 
   return 0;
}
 
//
// This is used if the macro is compiled. If run through ROOT with
// `root -l -b -q MACRO.C` or similar it is unused.
//
int main(int argc, char **argv)
{
   TMVACrossValidationApplication();
}

 
                         : Booking "BDTG" of type "CrossValidation" from datasetcv/weights/TMVACrossValidation_BDTG.weights.xml.
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_BDTG.weights.xml
<HEADER> DataSetInfo              : [Default] : Added class "Signal"
<HEADER> DataSetInfo              : [Default] : Added class "Background"
                         : Reading weightfile: datasetcv/weights/TMVACrossValidation_BDTG_fold1.weights.xml
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_BDTG_fold1.weights.xml
                         : Reading weightfile: datasetcv/weights/TMVACrossValidation_BDTG_fold2.weights.xml
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_BDTG_fold2.weights.xml
                         : Booked classifier "BDTG" of type: "CrossValidation"
                         : Booking "Fisher" of type "CrossValidation" from datasetcv/weights/TMVACrossValidation_Fisher.weights.xml.
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_Fisher.weights.xml
                         : Reading weightfile: datasetcv/weights/TMVACrossValidation_Fisher_fold1.weights.xml
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_Fisher_fold1.weights.xml
                         : Reading weightfile: datasetcv/weights/TMVACrossValidation_Fisher_fold2.weights.xml
                         : Reading weight file: datasetcv/weights/TMVACrossValidation_Fisher_fold2.weights.xml
                         : Booked classifier "Fisher" of type: "CrossValidation"
                         : Rebuilding Dataset Default
(int) 0

Author

Kim Albertsson (adapted from code originally by Andreas Hoecker)

Definition in file TMVACrossValidationApplication.C.