//Apply classifier with TMVA

//using namespace TMVA::Experimental;

void apply()
{
TFile* inputFile = new TFile("sig_train.root");
TTree* data = (TTree*)inputFile->Get("b0");

//the name of the output file which will contain the BDT response of each event:

TFile *target = new TFile("mva_output.root","RECREATE" );
TTree *tree = new TTree("tree","calibrated tree");

TMVA::Reader *reader = new TMVA::Reader("!Color:!Silent");

Float_t useCMSFrame__bocosTheta__bc, cosTBTO, cosTBz, KSFWVariables__boet__bc, KSFWVariables__bohso00__bc, KSFWVariables__bohso02__bc, KSFWVariables__bohso04__bc, KSFWVariables__bohso10__bc, KSFWVariables__bohso12__bc, KSFWVariables__bohso14__bc, KSFWVariables__bohso20__bc, KSFWVariables__bohso22__bc, KSFWVariables__bohso24__bc, KSFWVariables__bohoo0__bc, KSFWVariables__bohoo1__bc, KSFWVariables__bohoo2__bc, KSFWVariables__bohoo3__bc, KSFWVariables__bohoo4__bc;

reader->AddVariable( "useCMSFrame__bocosTheta__bc", &useCMSFrame__bocosTheta__bc );
reader->AddVariable( "cosTBTO",                     &cosTBTO );
reader->AddVariable( "cosTBz",                      &cosTBz );
reader->AddVariable( "KSFWVariables__boet__bc",     &KSFWVariables__boet__bc );
//reader->AddVariable( "KSFWVariables__bohso00__bc",  &KSFWVariables__bohso00__bc);
reader->AddVariable( "KSFWVariables__bohso02__bc",  &KSFWVariables__bohso02__bc);
reader->AddVariable( "KSFWVariables__bohso04__bc",  &KSFWVariables__bohso04__bc);
reader->AddVariable( "KSFWVariables__bohso10__bc",  &KSFWVariables__bohso10__bc);
reader->AddVariable( "KSFWVariables__bohso12__bc",  &KSFWVariables__bohso12__bc);
reader->AddVariable( "KSFWVariables__bohso14__bc",  &KSFWVariables__bohso14__bc);
reader->AddVariable( "KSFWVariables__bohso20__bc",  &KSFWVariables__bohso20__bc);
reader->AddVariable( "KSFWVariables__bohso22__bc",  &KSFWVariables__bohso22__bc);
reader->AddVariable( "KSFWVariables__bohso24__bc",  &KSFWVariables__bohso24__bc);
//reader->AddVariable( "KSFWVariables__bohoo0__bc",   &KSFWVariables__bohoo0__bc);
//reader->AddVariable( "KSFWVariables__bohoo1__bc",   &KSFWVariables__bohoo1__bc);
//reader->AddVariable( "KSFWVariables__bohoo2__bc",   &KSFWVariables__bohoo2__bc);
//reader->AddVariable( "KSFWVariables__bohoo3__bc",   &KSFWVariables__bohoo3__bc);
//reader->AddVariable( "KSFWVariables__bohoo4__bc",   &KSFWVariables__bohoo4__bc);

reader->BookMVA( "My BDT", "dataset/weights/TMVAClassification_BDT.weights.xml");
reader->BookMVA( "Fisher discriminant","dataset/weights/TMVAClassification_Fisher.weights.xml");

//RReader *reader;
//RReader reader( "My BDT", "dataset/weights/TMVAClassification_BDT.weights.xml");
//auto variables = reader.GetVariableNames();

Double_t fbdt;
data->SetBranchAddress( "extraInfo__boFastBDT__bc",   &fbdt);

tree->Branch("extraInfo__boFastBDT__bc", &fbdt);

// Book example histogram for probability (the other methods are done similarly)
TH1F *probHistFi(0), *rarityHistFi(0);
probHistFi   = new TH1F( "MVA_BDT_Proba",  "MVA_BDT_Proba",  100, 0, 1 );
rarityHistFi = new TH1F( "MVA_BDT_Rarity", "MVA_BDT_Rarity", 100, 0, 1 );

// Add a branch to store the BDT response of events:

Float_t BDT_response;
tree->Branch("BDT_response",&BDT_response);

// ------- start your event loop
for (Long64_t ievt=0; ievt<data->GetEntries(); ++ievt) {
data->GetEntry(ievt);
BDT_response=reader->EvaluateMVA("My BDT");
//double fisher = reader->EvaluateMVA("Fisher discriminant");
probHistFi->Fill( reader->GetProba ( "My BDT" ) );
TMVA::MethodBDT * methodbase = dynamic_cast<TMVA::MethodBDT *>(reader->FindMVA("My BDT"));
Double_t pdf = reader->EvaluateMVA( "My BDT" );
rarityHistFi->Fill( methodbase->GetRarity( pdf, TMVA::Types::kSignal ) );

tree->Fill();
 }
tree->Write();
if (probHistFi != 0) probHistFi->Write(); if (rarityHistFi != 0) rarityHistFi->Write();
//target->Close();
delete reader;
inputFile->Close();
}