#include "TFile.h"
#include "TTree.h"
#include "TMVA/Factory.h"
#include "TCut.h"

int main() {
  TFile f("tmva-in.root");
  TTree * sampleTree = dynamic_cast<TTree*>(f.Get("sampleTree"));

  TFile file("tmva-out.root", "RECREATE");
  TMVA::Factory factory("TMVATest", &file, "");
  
  TCut sigCut = "isSignal > 0.5";
  TCut bkgCut = "isSignal < 0.5";
  factory.SetInputTrees(sampleTree, sigCut, bkgCut);

  factory.AddVariable("x", 'F');
  factory.AddVariable("y", 'F');

  TCut preselection = "";
  factory.PrepareTrainingAndTestTree(preselection, TString("NSigTrain=100000:NBkgTrain=100000:NSigTest=100000:NBkgTest=100000:SplitMode=Random"));

  factory.BookMethod(TMVA::Types::kLikelihood, "Likelihood", 
		     "H:!TransformOutput:Spline=2:NSmooth=5:Preprocess=Decorrelate");
  factory.BookMethod(TMVA::Types::kFisher, "Fisher", "Method=Fisher");
  factory.BookMethod(TMVA::Types::kMLP, "NeuralNetwork", "Normalise:NCycles=200:HiddenLayers=N+2,N:NeuronInputType=sum:LearningRate=0.02:DecayRate=0.01");
  factory.BookMethod(TMVA::Types::kBDT, "BDT", "nTrees=200");

  factory.TrainAllMethods();
  factory.TestAllMethods();
  factory.EvaluateAllMethods();

  return 0;
}