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PlotBuilder.cc
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#include <cmath>
#include <cstdlib>
#include <iostream>
#include "TH1D.h"
#include "TH2D.h"
#include "TPad.h"
#include "TStyle.h"
#include "GlobalParameters.h"
#include "PlotBuilder.h"
#include "Selection.h"
#include "Style.h"
#include "Variable.h"
unsigned int PlotBuilder::count_ = 0;
PlotBuilder::PlotBuilder(const Config &cfg, Output &out)
: canSize_(500), out_(out) {
run(cfg,"plot");
}
PlotBuilder::~PlotBuilder() {
}
void PlotBuilder::run(const Config &cfg, const TString &key) const {
std::cout << " - Creating control plots" << std::endl;
//// Loop over the config lines
std::vector<Config::Attributes> attrList = cfg(key);
for(std::vector<Config::Attributes>::const_iterator it = attrList.begin();
it != attrList.end(); ++it) {
if( it->hasName("variable") && it->hasName("histogram") ) {
//// Possible plot types
TString plotDim = "1D";
TString plotType = "SingleDistribution";
//// Parse variables
std::vector<TString> variables;
if( it->value("variable").Contains(" vs ") ) {
// This is a 2D plot; split into variable names
Config::split(it->value("variable")," vs ",variables);
plotDim = "2D";
} else {
// A 1D plot
variables.push_back(it->value("variable"));
plotDim = "1D";
}
for(std::vector<TString>::const_iterator itv = variables.begin();
itv != variables.end(); ++itv) {
if( !Variable::exists(*itv) ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): variable '" << *itv << "' does not exist" << std::endl;
exit(-1);
}
}
if( variables.size() > 2 ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): no plot type supports more than two variables" << std::endl;
exit(-1);
}
//// Parse histogram style
HistParams histParams(it->value("histogram"));
//// Make plots
// Read type of plot
if( it->hasName("dataset") ) {
if( it->value("dataset").Contains("+") ) { // Case of several datasets
// Set default for case of several defined datasets
plotType = "ComparedDistributions";
// Check for specifics
if( it->hasName("type") ) {
if ( it->value("type") == "overlay" ) plotType = "ComparedDistributions";
else if( it->value("type") == "stack" ) plotType = "StackedDistributions";
else if( it->value("type") == "fractions" ) plotType = "FractionalDistributions";
}
} else { // Case of one dataset
plotType = "SingleDistribution";
}
// Read dataset(s)
std::vector<TString> dataSetLabels;
if( plotType == "SingleDistribution" ) {
dataSetLabels.push_back(it->value("dataset"));
} else {
Config::split(it->value("dataset"),"+",dataSetLabels);
}
// Check whether dataset(s) exist
for(std::vector<TString>::const_iterator itd = dataSetLabels.begin();
itd != dataSetLabels.end(); ++itd) {
if( !DataSet::labelExists(*itd) ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): dataset '" << *itd << "' does not exist" << std::endl;
exit(-1);
}
}
// For each selection, get the dataset(s) and make the plots
for(SelectionIt its = Selection::begin(); its != Selection::end(); ++its) {
DataSets dataSets;
for(std::vector<TString>::const_iterator itd = dataSetLabels.begin();
itd != dataSetLabels.end(); ++itd) {
dataSets.push_back(DataSet::find(*itd,*its));
}
if( plotDim == "1D" ) {
if( plotType == "SingleDistribution" ) {
plotDistribution(variables.front(),dataSets.front(),histParams);
} else if( plotType == "StackedDistributions" ) {
plotStackedDistributions(variables.front(),dataSets,histParams);
} else if( plotType == "ComparedDistributions" ) {
plotComparedDistributions(variables.front(),dataSets,histParams);
} else if( plotType == "FractionalDistributions" ) {
plotFractionalDistributions(variables.front(),dataSets,histParams);
}
} else if( plotDim == "2D" ) {
plotDistribution2D(variables.at(1),variables.at(0),dataSets.front(),histParams);
}
}
} else if( it->hasName("data") && it->hasName("background") ) {
plotType = "DataVsBackground";
// Read dataset names
TString dataLabel = it->value("data");
std::vector<TString> bkgLabels;
std::vector<TString> signalLabels;
Config::split(it->value("background"),"+",bkgLabels);
if( it->hasName("signals") ) {
Config::split(it->value("signals"),"+",signalLabels);
}
// Check whether datasets exist
if( !DataSet::labelExists(dataLabel) ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): dataset '" << dataLabel << "' does not exist" << std::endl;
exit(-1);
}
for(std::vector<TString>::const_iterator itd = bkgLabels.begin();
itd != bkgLabels.end(); ++itd) {
if( !DataSet::labelExists(*itd) ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): dataset '" << *itd << "' does not exist" << std::endl;
exit(-1);
}
}
for(std::vector<TString>::const_iterator itd = signalLabels.begin();
itd != signalLabels.end(); ++itd) {
if( !DataSet::labelExists(*itd) ) {
std::cerr << "\n\nERROR in PlotBuilder::run(): dataset '" << *itd << "' does not exist" << std::endl;
exit(-1);
}
}
// For each selection, plot data vs bkg
for(SelectionIt its = Selection::begin(); its != Selection::end(); ++its) {
const DataSet* data = DataSet::find(dataLabel,*its);
DataSets bkgs;
for(std::vector<TString>::const_iterator itd = bkgLabels.begin();
itd != bkgLabels.end(); ++itd) {
bkgs.push_back(DataSet::find(*itd,*its));
}
DataSets signals;
for(std::vector<TString>::const_iterator itd = signalLabels.begin();
itd != signalLabels.end(); ++itd) {
signals.push_back(DataSet::find(*itd,*its));
}
plotDataVsBkg(variables.front(),data,bkgs,signals,histParams);
}
}
} else {
// no 'plot' or 'histogram' definitions
std::cerr << "\n\nERROR in PlotBuilder::run(): wrong syntax" << std::endl;
std::cerr << " in line with key '" << key << "'" << std::endl;
std::cerr << " in config file '" << cfg.fileName() << "'" << std::endl;
exit(-1);
}
} // End of loop over config lines
}
void PlotBuilder::plotDistribution(const TString &var, const DataSet *dataSet, const HistParams &histParams) const {
TH1* h = 0;
TGraphAsymmErrors* u = 0;
createDistribution1D(dataSet,var,h,u,histParams);
// Under-/Overflow warning
checkForUnderOverFlow(h,var,dataSet);
TCanvas *can = new TCanvas("can","",canSize_,canSize_);
//can->SetWindowSize(canSize_+(canSize_-can->GetWw()),canSize_+(canSize_-can->GetWh()));
if( dataSet->type() == DataSet::Data ) {
h->Draw("PE");
if( u ) {
u->Draw("E2same");
h->Draw("PEsame");
}
} else if( dataSet->type() == DataSet::Signal ) {
h->Draw("HIST");
if( u ) {
u->Draw("E2same");
}
} else {
h->SetLineColor(kBlack);
h->SetLineStyle(1);
h->SetLineWidth(1);
h->Draw("HISTE");
if( u ) {
u->Draw("E2same");
}
}
TPaveText* title = header(dataSet,true,Style::tlatexLabel(dataSet)+", "+Style::tlatexLabel(dataSet->selectionUid()));
title->Draw("same");
if( histParams.logx() ) can->SetLogx();
if( histParams.logy() ) can->SetLogy();
gPad->RedrawAxis();
storeCanvas(can,var,dataSet);
delete title;
delete h;
if( u ) delete u;
delete can;
}
void PlotBuilder::plotDistribution2D(const TString &var1, const TString &var2, const DataSet *dataSet, const HistParams &histParams) const {
TH2* h = 0;
createDistribution2D(dataSet,var1,var2,h,histParams);
TCanvas *can = new TCanvas("can","",canSize_,canSize_);
can->SetRightMargin(can->GetRightMargin()+0.06);
can->SetBottomMargin(can->GetBottomMargin()+0.03);
can->SetTopMargin(can->GetTopMargin()+0.03);
//can->SetWindowSize(canSize_+(canSize_-can->GetWw()),canSize_+(canSize_-can->GetWh()));
h->Draw("COLZ");
TPaveText* title = header(dataSet,true,Style::tlatexLabel(dataSet)+", "+Style::tlatexLabel(dataSet->selectionUid()));
title->Draw("same");
if( histParams.logx() ) can->SetLogx();
if( histParams.logy() ) can->SetLogy();
if( histParams.logz() ) can->SetLogz();
gPad->RedrawAxis();
storeCanvas(can,var1+"vs"+var2,dataSet);
delete title;
delete h;
delete can;
}
void PlotBuilder::plotComparedDistributions(const TString &var, const DataSets &dataSets, const HistParams &histParams) const {
std::vector<TH1*> hists;
TLegend* leg = legend(dataSets.size());
// Loop over datasets and create distributions
for(DataSetIt itd = dataSets.begin();
itd != dataSets.end(); ++itd) {
TH1* h = 0;
TGraphAsymmErrors* u = 0;
createDistribution1D(*itd,var,h,u,histParams);
if( u ) delete u;
if( histParams.norm() && h->Integral() ) {
h->Scale(1./h->Integral("width"));
h->GetYaxis()->SetTitle("Probability Density");
}
if( (*itd)->type() != DataSet::Data ) {
h->SetLineColor(h->GetFillColor());
h->SetLineWidth(3);
h->SetFillStyle(0);
leg->AddEntry(h," "+Style::tlatexLabel(*itd),"L");
} else {
leg->AddEntry(h," "+Style::tlatexLabel(*itd),"P");
}
if( histParams.norm() ) setYRange(h,histParams.logy()?3E-6:-1.);
else setYRange(h,histParams.logy()?3E-1:-1.);
hists.push_back(h);
}
TCanvas *can = new TCanvas("can","",canSize_,canSize_);
if( dataSets.back()->type() == DataSet::Data ) {
hists.back()->Draw("PE");
} else {
hists.back()->Draw("HIST");
}
for(int i = hists.size()-2; i >= 0; --i) {
if( dataSets.at(i)->type() == DataSet::Data ) {
hists.at(i)->Draw("PEsame");
} else {
hists.at(i)->Draw("HISTsame");
}
}
TPaveText* title = header(dataSets,false,Style::tlatexLabel(dataSets.front()->selectionUid()));
title->Draw("same");
leg->Draw("same");
gPad->RedrawAxis();
if( histParams.logx() ) can->SetLogx();
if( histParams.logy() ) can->SetLogy();
storeCanvas(can,var,dataSets,"overlayed");
delete title;
delete leg;
for(std::vector<TH1*>::iterator it = hists.begin();
it != hists.end(); ++it) {
delete *it;
}
delete can;
}
// Plot stacked datasets
void PlotBuilder::plotStackedDistributions(const TString &var, const DataSets &dataSets, const HistParams &histParams) const {
std::vector<TH1*> hists;
std::vector<TString> legEntries;
TGraphAsymmErrors* unc = 0;
createStack1D(dataSets,var,hists,legEntries,unc,histParams);
TLegend* leg = legend(hists.size());
std::vector<TString>::const_iterator itL = legEntries.begin();
for(std::vector<TH1*>::iterator itH = hists.begin();
itH != hists.end(); ++itH,++itL) {
leg->AddEntry(*itH,*itL,"F");
}
bool onlySimulatedDataSets = true;
TPaveText* title = header(dataSets,true,Style::tlatexLabel(dataSets.front()->selectionUid()));
// Draw
TCanvas* can = new TCanvas("can","",canSize_,canSize_);
can->cd();
setYRange(hists.front(),histParams.logy()?3E-1:-1.);
hists.front()->Draw("HISTE");
for(std::vector<TH1*>::iterator it = hists.begin()+1;
it != hists.end(); ++it) {
(*it)->Draw("HISTsame");
}
// Plot uncertainty band
if( unc ) unc->Draw("E2same");
title->Draw("same");
leg->Draw("same");
gPad->RedrawAxis();
if( histParams.logx() ) can->SetLogx();
if( histParams.logy() ) can->SetLogy();
storeCanvas(can,var,dataSets,"stack");
for(std::vector<TH1*>::iterator it = hists.begin();
it != hists.end(); ++it) {
delete *it;
}
if( unc ) delete unc;
delete leg;
delete title;
delete can;
}
// Plot stacked distributions where each bin is normalized to 1
void PlotBuilder::plotFractionalDistributions(const TString &var, const DataSets &dataSets, const HistParams &histParams) const {
// Create stack
std::vector<TH1*> hists;
std::vector<TString> legEntries;
TGraphAsymmErrors* unc = 0;
createStack1D(dataSets,var,hists,legEntries,unc,histParams);
if( unc ) delete unc; // No uncertainty band so far
// Norm each bin to 1
for(int bin = 1; bin <= hists.front()->GetNbinsX(); ++bin) {
// First histogram in stack in sum of all datasets
// It's bin content is norm
double norm = hists.front()->GetBinContent(bin);
// Loop over all histograms and normalize bin content
if( norm > 0. ) {
for(std::vector<TH1*>::iterator it = hists.begin();
it != hists.end(); ++it) {
(*it)->SetBinContent( bin, (*it)->GetBinContent(bin) / norm );
}
}
}
// Create legends and labels
unsigned int nEntriesRight = hists.size()/2;
unsigned int nEntriesLeft = hists.size() - nEntriesRight;
TLegend* legL = legendLeft(nEntriesLeft);
TLegend* legR = legendRight(nEntriesRight);
unsigned int entry = 0;
for(; entry < nEntriesLeft; ++entry) {
legL->AddEntry(hists.at(entry),legEntries.at(entry),"F");
}
for(; entry < hists.size(); ++entry) {
legR->AddEntry(hists.at(entry),legEntries.at(entry),"F");
}
TPaveText* title = header(dataSets,true,Style::tlatexLabel(dataSets.front()->selectionUid()));
// Axis range (so far only for linear scale)
double relHistHeight = 1 - gStyle->GetPadBottomMargin() - gStyle->GetPadTopMargin();
double relLegHeight = 0.06*nEntriesLeft; // Should be retrieved from legend, but ROOT sucks...
hists.front()->GetYaxis()->SetRangeUser(0.,1.1 + relLegHeight/relHistHeight);
// Set y title
hists.front()->GetYaxis()->SetTitle("Fractional Contribution");
// draw
TCanvas* can = new TCanvas("can","",canSize_,canSize_);
can->cd();
hists.front()->Draw("HIST");
for(std::vector<TH1*>::iterator it = hists.begin()+1;
it != hists.end(); ++it) {
(*it)->Draw("HISTsame");
}
title->Draw("same");
legL->Draw("same");
legR->Draw("same");
if( histParams.logx() ) can->SetLogx();
gPad->RedrawAxis();
storeCanvas(can,var,dataSets,"fractions");
for(std::vector<TH1*>::iterator it = hists.begin();
it != hists.end(); ++it) {
delete *it;
}
delete legL;
delete legR;
delete title;
delete can;
}
void PlotBuilder::plotDataVsBkg(const TString &var, const DataSet *data, const DataSets &bkgs, const DataSets &signals, const HistParams &histParams) const {
//// Create the data distribution
// Fill distribution
TH1* hData = 0;
TGraphAsymmErrors* u = 0;
createDistribution1D(data,var,hData,u,histParams);
if( u ) delete u;
TString legEntryData = dataSetLegEntry(hData,data);
// Under-/Overflow warning
checkForUnderOverFlow(hData,var,data);
// We want a data-vs-bkg like plot. Therefore, make
// sure that markers are set, even if data is of
// type DataSet::MC or DataSet::MCPrediction, e.g. for
// closure tests
setMarkerStyle(hData,data);
bool simulationOnlyPlot = data->isSimulated();
//// Create the background stack
std::vector<TH1*> stack;
std::vector<TString> legEntriesBkgs;
TGraphAsymmErrors* uncBkg = 0;
createStack1D(bkgs,var,stack,legEntriesBkgs,uncBkg,histParams);
if( simulationOnlyPlot ) {
for(DataSetIt itd = bkgs.begin(); itd != bkgs.end(); ++itd) {
if( !( (*itd)->isSimulated() ) ) {
simulationOnlyPlot = false;
break;
}
}
}
//// Create the signal distributions
std::vector<TH1*> hSigs;
std::vector<TString> legEntriesSigs;
for(DataSetIt itd = signals.begin();
itd != signals.end(); ++itd) {
TH1* h = 0;
TGraphAsymmErrors* u = 0;
createDistribution1D(*itd,var,h,u,histParams);
hSigs.push_back(h);
if( u ) delete u;
legEntriesSigs.push_back(dataSetLegEntry(h,*itd));
if( simulationOnlyPlot ) {
if( !( (*itd)->isSimulated() ) ) {
simulationOnlyPlot = false;
}
}
}
//// Create the ratio plot (data/bkg)
// ratio frame
TH1 *hRatioFrame = static_cast<TH1*>(hData->Clone("RatioFrame"));
for(int xBin = 1; xBin <= hRatioFrame->GetNbinsX(); ++xBin) {
hRatioFrame->SetBinContent(xBin,1.);
}
hRatioFrame->GetXaxis()->SetTitle(hData->GetXaxis()->GetTitle());
hRatioFrame->GetYaxis()->SetRangeUser(0.55,1.95);
hRatioFrame->SetLineStyle(2);
hRatioFrame->SetLineColor(kBlack);
hRatioFrame->SetLineWidth(2);
hRatioFrame->SetFillColor(0);
hRatioFrame->GetYaxis()->SetNdivisions(205);
hRatioFrame->GetYaxis()->SetTickLength(gStyle->GetTickLength("Y")/0.2);
hRatioFrame->GetXaxis()->SetLabelSize(gStyle->GetLabelSize("X"));
hRatioFrame->GetYaxis()->CenterTitle();
hRatioFrame->GetYaxis()->SetTitleOffset(0.9*hRatioFrame->GetYaxis()->GetTitleOffset());
// Adapt the top histograms
hData->GetXaxis()->SetLabelSize(0);
hData->GetXaxis()->SetTitle("");
hData->GetYaxis()->SetTickLength(gStyle->GetTickLength("Y")/0.8);
for(std::vector<TH1*>::iterator it = stack.begin();
it != stack.end(); ++it) {
(*it)->GetXaxis()->SetLabelSize(0);
(*it)->GetXaxis()->SetTitle("");
(*it)->GetYaxis()->SetTickLength(gStyle->GetTickLength("Y")/0.8);
}
for(std::vector<TH1*>::iterator it = hSigs.begin();
it != hSigs.end(); ++it) {
(*it)->GetXaxis()->SetLabelSize(0);
(*it)->GetXaxis()->SetTitle("");
(*it)->GetYaxis()->SetTickLength(gStyle->GetTickLength("Y")/0.8);
}
// Fill the ratio plot
TH1 *hRatio = static_cast<TH1*>(hData->Clone("Ratio"));
hRatio->Divide(stack.front());
hRatioFrame->GetYaxis()->SetTitle("#frac{"+Style::tlatexType(data)+"}{"+Style::tlatexType(bkgs.front())+"}");
// Create the error band
TGraphAsymmErrors* uncRatio = 0;
if( uncBkg ) {
uncRatio = static_cast<TGraphAsymmErrors*>(uncBkg->Clone());
for(unsigned int i = 0; i < uncRatio->GetN(); ++i) {
double denom = uncRatio->GetY()[i];
if( denom > 0. ) {
uncRatio->GetY()[i] = 1.;
uncRatio->GetEYlow()[i] = uncRatio->GetEYlow()[i]/denom;
uncRatio->GetEYhigh()[i] = uncRatio->GetEYhigh()[i]/denom;
}
}
}
//// Legend and labels
TLegend* leg = legend(1+stack.size()+hSigs.size());
TPaveText* title = header(simulationOnlyPlot,(data->type()==DataSet::Data ? true : false),Style::tlatexLabel(data->selectionUid())); // show lumi only if data plot is of type DataSet::Data
leg->AddEntry(hData,legEntryData,"P");
std::vector<TString>::const_iterator itL = legEntriesBkgs.begin();
for(std::vector<TH1*>::const_iterator itH = stack.begin();
itH != stack.end(); ++itH,++itL) {
leg->AddEntry(*itH,*itL,"F");
}
itL = legEntriesSigs.begin();
for(std::vector<TH1*>::const_iterator itH = hSigs.begin();
itH != hSigs.end(); ++itH,++itL) {
leg->AddEntry(*itH,*itL,"L");
}
//// Canvases and pads
TCanvas* can = new TCanvas("can","",canSize_,canSize_);
can->SetBottomMargin(0.2 + 0.8*can->GetBottomMargin()-0.2*can->GetTopMargin());
can->cd();
TPad *ratioPad = new TPad("bpad","",0,0,1,1);
ratioPad->SetTopMargin(0.8 - 0.8*ratioPad->GetBottomMargin()+0.2*ratioPad->GetTopMargin());
ratioPad->SetFillStyle(0);
ratioPad->SetFrameFillColor(10);
ratioPad->SetFrameBorderMode(0);
//// Draw everything
can->cd();
setYRange(stack.front(),histParams.logy()?3E-1:-1.);
stack.front()->Draw("HISTE");
for(std::vector<TH1*>::iterator it = stack.begin()+1;
it != stack.end(); ++it) {
(*it)->Draw("HISTsame");
}
// Plot bkg uncertainty band
if( uncBkg ) uncBkg->Draw("E2same");
// Plot signals
for(std::vector<TH1*>::iterator it = hSigs.begin();
it != hSigs.end(); ++it) {
(*it)->Draw("HISTsame");
}
// Plot data
hData->Draw("PEsame");
gPad->RedrawAxis();
// Plot ratio plot
ratioPad->Draw();
ratioPad->cd();
hRatioFrame->Draw("HIST");
if( uncRatio ) {
uncRatio->Draw("E2same");
}
hRatio->Draw("PEsame");
title->Draw("same");
leg->Draw("same");
gPad->RedrawAxis();
if( histParams.logx() ) can->SetLogx();
if( histParams.logy() ) can->SetLogy();
storeCanvas(can,var,data,bkgs);
//// Clean up
delete hData;
for(std::vector<TH1*>::iterator it = stack.begin();
it != stack.end(); ++it) {
delete *it;
}
for(std::vector<TH1*>::iterator it = hSigs.begin();
it != hSigs.end(); ++it) {
delete *it;
}
if( uncBkg ) delete uncBkg;
if( uncRatio ) delete uncRatio;
delete leg;
delete title;
delete can;
delete hRatio;
delete hRatioFrame;
}
// Fill distribution of variable 'var' for dataSet with label 'dataSetLabel'
// and an uncertainty band 'uncert'.
// ----------------------------------------------------------------------------
void PlotBuilder::createDistribution1D(const DataSet *dataSet, const TString &var, TH1* &h, TGraphAsymmErrors* &uncert, const HistParams &histParams) const {
++PlotBuilder::count_;
// Create histogram
TString name = "plot";
name += count_;
h = new TH1D(name,"",histParams.nBinsX(),histParams.xMin(),histParams.xMax());
h->Sumw2();
if( histParams.xMax() > 1000. ) {
h->GetXaxis()->SetNdivisions(505);
}
setXTitle(h,var);
setYTitle(h,var);
setGenericStyle(h,dataSet);
// Create temporary histograms to store uncertainties
TH1* hDn = static_cast<TH1*>(h->Clone(name+"Dn"));
TH1* hUp = static_cast<TH1*>(h->Clone(name+"Up"));
// Fill distributions
for(EventIt itd = dataSet->evtsBegin(); itd != dataSet->evtsEnd(); ++itd) {
double v = (*itd)->get(var);
h->Fill(v,(*itd)->weight());
if( (*itd)->hasUnc() ) {
hDn->Fill(v,(*itd)->weightUncDn());
hUp->Fill(v,(*itd)->weightUncUp());
}
}
// Fill overflow bin
if( histParams.hasOverflowBin() ) {
double val = h->GetBinContent(h->GetNbinsX()) + h->GetBinContent(h->GetNbinsX()+1);
double err = sqrt( h->GetBinError(h->GetNbinsX())*h->GetBinError(h->GetNbinsX()) + h->GetBinError(h->GetNbinsX()+1)*h->GetBinError(h->GetNbinsX()+1) );
h->SetBinContent(h->GetNbinsX(),val);
h->SetBinError(h->GetNbinsX(),err);
if( hDn->GetEntries() ) {
val = hDn->GetBinContent(hDn->GetNbinsX()) + hDn->GetBinContent(hDn->GetNbinsX()+1);
err = sqrt( hDn->GetBinError(hDn->GetNbinsX())*hDn->GetBinError(hDn->GetNbinsX()) + hDn->GetBinError(hDn->GetNbinsX()+1)*hDn->GetBinError(hDn->GetNbinsX()+1) );
hDn->SetBinContent(hDn->GetNbinsX(),val);
hDn->SetBinError(hDn->GetNbinsX(),err);
}
if( hUp->GetEntries() ) {
val = hUp->GetBinContent(hUp->GetNbinsX()) + hUp->GetBinContent(hUp->GetNbinsX()+1);
err = sqrt( hUp->GetBinError(hUp->GetNbinsX())*hUp->GetBinError(hUp->GetNbinsX()) + hUp->GetBinError(hUp->GetNbinsX()+1)*hUp->GetBinError(hUp->GetNbinsX()+1) );
hUp->SetBinContent(hUp->GetNbinsX(),val);
hUp->SetBinError(hUp->GetNbinsX(),err);
}
}
// Create uncertainty band
if( hDn->GetEntries() && hUp->GetEntries() ) {
std::vector<double> x(h->GetNbinsX());
std::vector<double> xe(h->GetNbinsX());
std::vector<double> y(h->GetNbinsX());
std::vector<double> yed(h->GetNbinsX());
std::vector<double> yeu(h->GetNbinsX());
for(unsigned int i = 0; i < x.size(); ++i) {
int bin = i+1;
x.at(i) = h->GetBinCenter(bin);
xe.at(i) = h->GetBinWidth(bin)/2.;
y.at(i) = h->GetBinContent(bin);
yed.at(i) = std::abs(h->GetBinContent(bin)-hDn->GetBinContent(bin));
yeu.at(i) = std::abs(h->GetBinContent(bin)-hUp->GetBinContent(bin));
}
uncert = new TGraphAsymmErrors(x.size(),&(x.front()),&(y.front()),&(xe.front()),&(xe.front()),&(yed.front()),&(yeu.front()));
uncert->SetMarkerStyle(1);
uncert->SetMarkerColor(kBlue+2);
uncert->SetFillColor(uncert->GetMarkerColor());
uncert->SetLineColor(uncert->GetMarkerColor());
uncert->SetFillStyle(3004);
}
// Delete temporary hists
delete hDn;
delete hUp;
}
// Fill distribution of variable 'var2' vs 'var1' for dataSet with label
// 'dataSetLabel'.
// ----------------------------------------------------------------------------
void PlotBuilder::createDistribution2D(const DataSet *dataSet, const TString &var1, const TString &var2, TH2* &h, const HistParams &histParams) const {
++PlotBuilder::count_;
// Create histogram
TString name = "plot";
name += count_;
h = new TH2D(name,"",histParams.nBinsX(),histParams.xMin(),histParams.xMax(),histParams.nBinsY(),histParams.yMin(),histParams.yMax());
h->Sumw2();
if( histParams.xMax() > 1000. ) {
h->GetXaxis()->SetNdivisions(505);
}
if( histParams.yMax() > 1000. ) {
h->GetYaxis()->SetNdivisions(505);
}
setXTitle(h,var1);
setYTitle(h,var2);
// Fill distribution
for(EventIt itd = dataSet->evtsBegin(); itd != dataSet->evtsEnd(); ++itd) {
h->Fill((*itd)->get(var1),(*itd)->get(var2),(*itd)->weight());
}
}
// Fill distribution of 'var1'/'var2' for dataSet with label 'dataSetLabel'
// and an uncertainty band 'uncert'.
// ----------------------------------------------------------------------------
void PlotBuilder::createDistributionRatio(const DataSet *dataSet, const TString &var1, const TString &var2, TH1* &h, TGraphAsymmErrors* &uncert, const HistParams &histParams) const {
++PlotBuilder::count_;
// Create histogram
TString name = "plot";
name += count_;
h = new TH1D(name,"",histParams.nBinsX(),histParams.xMin(),histParams.xMax());
h->Sumw2();
if( histParams.xMax() > 1000. ) {
h->GetXaxis()->SetNdivisions(505);
}
setXTitle(h,var1,var2);
setYTitle(h,"");
setGenericStyle(h,dataSet);
// Create temporary histograms to store uncertainties
TH1* hDn = static_cast<TH1*>(h->Clone(name+"Dn"));
TH1* hUp = static_cast<TH1*>(h->Clone(name+"Up"));
// Fill distributions
for(EventIt itd = dataSet->evtsBegin(); itd != dataSet->evtsEnd(); ++itd) {
double v1 = (*itd)->get(var1);
double v2 = (*itd)->get(var2);
if( v2 > 0. ) v1 /= v2;
h->Fill(v1,(*itd)->weight());
if( (*itd)->hasUnc() ) {
hDn->Fill(v1,(*itd)->weightUncDn());
hUp->Fill(v1,(*itd)->weightUncUp());
}
}
// Fill overflow bin
if( histParams.hasOverflowBin() ) {
double val = h->GetBinContent(h->GetNbinsX()) + h->GetBinContent(h->GetNbinsX()+1);
double err = sqrt( h->GetBinError(h->GetNbinsX())*h->GetBinError(h->GetNbinsX()) + h->GetBinError(h->GetNbinsX()+1)*h->GetBinError(h->GetNbinsX()+1) );
h->SetBinContent(h->GetNbinsX(),val);
h->SetBinError(h->GetNbinsX(),err);
if( hDn->GetEntries() ) {
val = hDn->GetBinContent(hDn->GetNbinsX()) + hDn->GetBinContent(hDn->GetNbinsX()+1);
err = sqrt( hDn->GetBinError(hDn->GetNbinsX())*hDn->GetBinError(hDn->GetNbinsX()) + hDn->GetBinError(hDn->GetNbinsX()+1)*hDn->GetBinError(hDn->GetNbinsX()+1) );
hDn->SetBinContent(hDn->GetNbinsX(),val);
hDn->SetBinError(hDn->GetNbinsX(),err);
}
if( hUp->GetEntries() ) {
val = hUp->GetBinContent(hUp->GetNbinsX()) + hUp->GetBinContent(hUp->GetNbinsX()+1);
err = sqrt( hUp->GetBinError(hUp->GetNbinsX())*hUp->GetBinError(hUp->GetNbinsX()) + hUp->GetBinError(hUp->GetNbinsX()+1)*hUp->GetBinError(hUp->GetNbinsX()+1) );
hUp->SetBinContent(hUp->GetNbinsX(),val);
hUp->SetBinError(hUp->GetNbinsX(),err);
}
}
// Create uncertainty band
if( hDn->GetEntries() && hUp->GetEntries() ) {
std::vector<double> x(h->GetNbinsX());
std::vector<double> xe(h->GetNbinsX());
std::vector<double> y(h->GetNbinsX());
std::vector<double> yed(h->GetNbinsX());
std::vector<double> yeu(h->GetNbinsX());
for(unsigned int i = 0; i < x.size(); ++i) {
int bin = i+1;
x.at(i) = h->GetBinCenter(bin);
xe.at(i) = h->GetBinWidth(bin)/2.;
y.at(i) = h->GetBinContent(bin);
yed.at(i) = std::abs(h->GetBinContent(bin)-hDn->GetBinContent(bin));
yeu.at(i) = std::abs(h->GetBinContent(bin)-hUp->GetBinContent(bin));
}
uncert = new TGraphAsymmErrors(x.size(),&(x.front()),&(y.front()),&(xe.front()),&(xe.front()),&(yed.front()),&(yeu.front()));
uncert->SetMarkerStyle(1);
uncert->SetMarkerColor(kBlue+2);
uncert->SetFillColor(uncert->GetMarkerColor());
uncert->SetLineColor(uncert->GetMarkerColor());
uncert->SetFillStyle(3004);
}
// Delete temporary hists
delete hDn;
delete hUp;
}
// Fills vector with stack of histograms
// First histogram is sum of all datasets
// Last histogram is only first dataset
void PlotBuilder::createStack1D(const DataSets &dataSets, const TString &var, std::vector<TH1*> &hists, std::vector<TString> &legEntries, TGraphAsymmErrors* &uncert, const HistParams &histParams) const {
uncert = 0;
for(DataSetRIt itd = dataSets.rbegin();
itd != dataSets.rend(); ++itd) {
TH1* h = 0;
TGraphAsymmErrors* u = 0;
createDistribution1D(*itd,var,h,u,histParams);
if( u ) {
if( uncert ) { // Add uncertainties in quadrature
for(unsigned int i = 0; i < uncert->GetN(); ++i) {
double y1 = uncert->GetY()[i];
double ed1 = uncert->GetEYlow()[i];
double eu1 = uncert->GetEYhigh()[i];
double y2 = u->GetY()[i];
double ed2 = u->GetEYlow()[i];
double eu2 = u->GetEYhigh()[i];
uncert->GetY()[i] = y1+y2;
uncert->SetPointEYlow(i,sqrt(ed1*ed1+ed2*ed2));
uncert->SetPointEYhigh(i,sqrt(eu1*eu1+eu2*eu2));
}
} else {
uncert = u;
}
}
setGenericStyle(h,*itd);
legEntries.push_back(dataSetLegEntry(h,*itd));
// Add histogram to all previous histograms
for(std::vector<TH1*>::iterator itH = hists.begin();
itH != hists.end(); ++itH) {
(*itH)->Add(h);
}
// Add this histogram as new entry
hists.push_back(h);
}
}
void PlotBuilder::storeCanvas(TCanvas* can, const TString &var, const DataSet* dataSet) const {
out_.addPlot(can,var,dataSet->label(),dataSet->selectionUid());
}
void PlotBuilder::storeCanvas(TCanvas* can, const TString &var, const DataSets &dataSets, const TString &plotType) const {
std::vector<TString> dataSetLabels;
for(DataSetIt itd = dataSets.begin(); itd != dataSets.end(); ++itd) {
dataSetLabels.push_back((*itd)->label());
}
out_.addPlot(can,var,dataSetLabels,plotType,dataSets.front()->selectionUid());
}
void PlotBuilder::storeCanvas(TCanvas* can, const TString &var, const DataSet *dataSet, const DataSets &dataSets) const {
std::vector<TString> dataSetLabels1;
dataSetLabels1.push_back(dataSet->label());
std::vector<TString> dataSetLabels2;
for(DataSetIt itd = dataSets.begin(); itd != dataSets.end(); ++itd) {
dataSetLabels2.push_back((*itd)->label());
}
out_.addPlot(can,var,dataSetLabels1,dataSetLabels2,dataSet->selectionUid());
}
void PlotBuilder::setXTitle(TH1* h, const TString &var) const {
TString xTitle = Variable::label(var);
if( Variable::unit(var) != "" ) {
xTitle += " ["+Variable::unit(var)+"]";
}
h->GetXaxis()->SetTitle(xTitle);
}
void PlotBuilder::setXTitle(TH1* h, const TString &var1, const TString &var2) const {
TString xTitle = Variable::label(var1) + " / " + Variable::label(var2);
if( Variable::unit(var1) != "" || Variable::unit(var2) != "" ) {
if( Variable::unit(var1) != "" ) {
xTitle += " ["+Variable::unit(var1)+"]";
} else {
xTitle += " 1";
}
if( Variable::unit(var2) != "" ) {
xTitle += " / ["+Variable::unit(var2)+"]";
}
}
h->GetXaxis()->SetTitle(xTitle);
}
void PlotBuilder::setYTitle(TH1* h, const TString &var) const {
TString yTitle = "Events";
TString className = h->ClassName();
if( className.Contains("TH2") ) {
yTitle = Variable::label(var);
if( Variable::unit(var) != "" ) {
yTitle += " ["+Variable::unit(var)+"]";
}
} else {
if( h->GetBinWidth(1) != 1. || Variable::unit(var) != "" ) {
yTitle += " / ";
if( h->GetBinWidth(1) != 1. ) {
TString bw = "";
bw += h->GetBinWidth(1);
if( bw.Contains(".") && bw.Length() > 5 ) bw = bw(0,5);
yTitle += bw;
}
if( Variable::unit(var) != "" ) {
yTitle += " "+Variable::unit(var);
}
}
}
h->GetYaxis()->SetTitle(yTitle);
}
int PlotBuilder::color(const DataSet *dataSet) const {
// Userdefined color
int color = Style::color(dataSet);
if( color < 0 ) { // Default colors
if( dataSet->type() == DataSet::Data ) {
color = kBlack;
} else {
color = kGray;
}
}
return color;
}
int PlotBuilder::markerStyle(const DataSet *dataSet) const {
// Userdefined style
int style = Style::markerStyle(dataSet);
if( style < 0 ) {
// Default styles
if( dataSet->type() == DataSet::Data ) {
style = 21;
}
}
return style;
}
void PlotBuilder::setMarkerStyle(TH1* h, const DataSet *dataSet) const {
h->SetMarkerStyle(markerStyle(dataSet));
h->SetMarkerColor(color(dataSet));
h->SetLineColor(h->GetMarkerColor());
}
void PlotBuilder::setGenericStyle(TH1* h, const DataSet *dataSet) const {
if( dataSet->type() == DataSet::Data ) {
setMarkerStyle(h,dataSet);
} else if( dataSet->type() == DataSet::MC || dataSet->type() == DataSet::Prediction || dataSet->type() == DataSet::MCPrediction ) {
int c = color(dataSet);
h->SetMarkerStyle(0);
h->SetMarkerColor(c);
h->SetLineColor(c);
h->SetFillColor(c);
} else if( dataSet->type() == DataSet::Signal ) {
int c = color(dataSet);
h->SetMarkerStyle(0);
h->SetMarkerColor(c);
h->SetLineColor(c);
h->SetLineWidth(3);
}
}
TPaveText* PlotBuilder::header(const DataSet* ds, bool showLumi, const TString &info) const {
return header(ds->isSimulated(),showLumi,info);
}
TPaveText* PlotBuilder::header(const DataSets &ds, bool isSimulation, bool showLumi, const TString &info) const {
bool simulationOnly = true;
for(DataSetIt itd = ds.begin(); itd != ds.end(); ++itd) {
if( !( (*itd)->isSimulated() ) ) {
simulationOnly = false;
break;
}
}