TTree tree("HiggsTree","The tree cont");
auto nevt = tree.ReadFile("Hgg.txt","x");
if (nevt <= 0) { 
    Error("fitHgg","Error reading data from input file ");
    }
std::cout << "Read " << nevt << " events from the file." << std::endl;

RooWorkspace w("Workspace for the Higgs fit");
w.factory("x[110,160]");  // invariant mass

// Backround Model
w.factory("nbackground[10000, 0, 10000]");
w.var("nbackground")->setVal(nevt);
w.var("nbackground")->setMin(0.1*nevt);
w.var("nbackground")->setMax(10*nevt);

// Create exponential distribution characterised by two components
w.factory("a1[ 7.5, -500, 500]");
w.factory("a2[-1.5, -500, 500]");
w.factory("expr::z('-(a1*x/100 + a2*(x/100)^2)', a1, a2, x)");
w.factory("Exponential::bmodel(z, 1)");

// Signal Model
w.factory("nsignal[100, 0.0, 1000.0]");
w.factory("mass[130, 110, 150]");
w.factory("width[1, 0.5, 5]");
w.factory("Gaussian::smodel(x, mass, width)");

// Signal + Background Model
w.factory("SUM::model(nbackground*bmodel, nsignal*smodel)");

auto smodel = w.pdf("smodel");
auto model = w.pdf("model");
auto x = w.var("x");

RooDataSet dataset("data","data",*x,RooFit::Import(tree) )

w.Print();

auto r = model->fitTo(dataset, RooFit::Minimizer("Minuit"),RooFit::Save(true), RooFit::Offset(true));

auto plot = x->frame();
dataset.plotOn(plot);
model->plotOn(plot);
model->plotOn(plot, RooFit::Components("bmodel"),RooFit::LineStyle(kDashed));
model->plotOn(plot, RooFit::Components("smodel"),RooFit::LineColor(kRed));
model->paramOn(plot);

%jsroot on
TCanvas c;
plot->Draw();
c.Draw();

w.writeToFile("HiggsModel.root",true);