#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"

void high_granularity_roc() {
    TFile f("output_R6.root");
    auto TestTree = (TTree*) f.Get("Dataset_R6/TestTree");

    TCanvas *c1 = new TCanvas("c1", "", 1000, 900);

    // retrieve from the Testing tree the mva output plus weight and class id
    int n = TestTree->Draw("BDTG:weight:classID","");
    c1->Clear();
    // fill vector for the 3 quantities
    std::vector<float> mvas(TestTree->GetV1(), TestTree->GetV1()+n);
    std::vector<float> weights(TestTree->GetV2(), TestTree->GetV2()+n);
    std::vector<bool> targets(TestTree->GetV3(), TestTree->GetV3()+n);
    // classID ==0 is signal , instead for ROC target==1 is considered signal

    //for(unsigned int i = 0; i < mvas.size(); i++)
    //{
    //    cout << mvas.at(i) << ", " << weights.at(i) << ", " << targets.at(i) << endl;
    //}

    // need to flip boolean vector
    targets.flip();
    TMVA::ROCCurve roc( mvas, targets,weights);
    // get a graph given number of points (e.g. 1000)
    auto curve = roc.GetROCCurve(1000);
    curve->Draw("AP");
    c1->Update();
}