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Histogram2.h
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#ifndef Histogram2_h
#define Histogram2_h
// Header file for ROOT classes
#include <TFile.h>
#include <TH1.h>
#include <TF1.h>
#include <THStack.h>
#include <TPad.h>
#include <TLatex.h>
#include <TLegend.h>
#include <TStyle.h>
#include <TSystem.h>
#include <TCanvas.h>
// Header file for c++ classes
#include <iostream>
#include <string>
#include <sstream>
#include <vector>
#include <map>
#include <iterator>
// CMS STYLE
#include "CMS/tdrstyle.C"
#include "CMS/CMS_lumi.C"
typedef struct TypeInfo {
std::vector<std::string> sample;
std::vector<std::string> cutSelection;
} TypeInfo;
struct DrawInfo {
bool yLogScale;
DrawInfo& operator=(const DrawInfo& a)
{
this->yLogScale = a.yLogScale;
return *this;
}
};
typedef struct VarInfo {
std::string label;
unsigned int nBin;
float min;
float max;
DrawInfo drawInfo;
} VarInfo;
template<typename Out>
void split(const std::string &s, char delim, Out result) {
std::stringstream ss;
ss.str(s);
std::string item;
while (std::getline(ss, item, delim)) {
*(result++) = item;
}
}
std::vector<int> COLOR = { kRed, kGreen+2, kBlue+2, kOrange+2, kViolet+2, kMagenta+2, kAzure-7, kBlack, kViolet };
std::vector<int> MARKER = { 20, 24, 21, 34, 22 };
std::vector<int> LINE = { 2, 1, 3, 4, 5, 6 };
class Histogram2 {
public :
Histogram2();
virtual ~Histogram2();
virtual void Book ( const std::string&, const std::string&, const std::map< std::string , struct VarInfo >& );
virtual void Fill ( const std::string&, const std::string&, const std::map< std::string , float >& );
virtual void Fill ( const std::string&, const std::string&, const std::map< std::string , std::pair< float , float > >& );
virtual void Book ( const std::string& sample, const std::map< std::string , struct VarInfo >& varMap ) { Book(sample, "", varMap); }
virtual void Fill ( const std::string& sample, const std::map< std::string , float >& valueMap ) { Fill(sample, "", valueMap); }
virtual void Fill ( const std::string& sample, const std::map< std::string , std::pair< float , float > >& valueMap ) { Fill(sample, "", valueMap); }
virtual void Draw ( const std::string& tag="", const std::map< std::string , struct TypeInfo >& typeInfo={});
virtual void Delete ( void );
virtual void Norm ( void );
virtual void Fit ( const std::string& fName="gaus" );
virtual void Save ( const std::string& );
virtual void ComputeRatio ( const std::string& rName="DATAvsMC" );
virtual void PrintMean ( void );
virtual void PrintFinalMean ( void );
virtual void PrintFitResults ( void );
private :
virtual void MakeStackHistogram ( const std::string& tag="" );
virtual void setYRange ( TH1D* , TH1D* ref=NULL, bool logScale=false);
virtual void setYRange ( THStack* , TH1D* ref=NULL, bool logScale=false);
virtual std::string getBeam ( const std::string& );
virtual std::string getDecayChannel ( const std::string& );
virtual std::string GetString ( const TF1& );
virtual std::string GetString ( const TH1D& , bool Gauss=false );
std::map< std::string ,std::map< std::string ,std::map< std::string , DrawInfo > > > drawInfo_;
std::map< std::string ,std::map< std::string ,std::map< std::string , TH1D* > > > TH1D_;
std::map< std::string ,std::map< std::string ,std::map< std::string , TH1D* > > > TH1D_RATIO_;
std::map< std::string ,std::map< std::string ,std::map< std::string , TH1D* > > > TH1D_RATIO_NORM_;
std::map< std::string ,std::map< std::string ,std::map< std::string , TF1* > > > TF1_;
std::map< std::string ,std::map< std::string ,std::map< std::string , TF1* > > > TF1_RATIO_;
std::map< std::string ,std::map< std::string ,std::map< std::string , THStack* > > > THStack_;
};
Histogram2::Histogram2()
{
// set the CMS style
setTDRStyle();
}
Histogram2::~Histogram2()
{
Delete();
}
void
Histogram2::Book(const std::string& sample, const std::string& type, const std::map< std::string , struct VarInfo >& varMap)
{
for (auto& var : varMap) {
std::string varName = var.first;
struct VarInfo varInfo = var.second;
std::string histName = (std::string("h_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
if (TH1D_.count(sample)==0 || TH1D_[sample].count(type)==0 || TH1D_[sample][type].count(varName)==0) {
// Create the Histogram
if (TH1D_[sample][type][varName]) delete TH1D_[sample][type][varName];
TH1D_[sample][type][varName] = new TH1D(histName.c_str(), histName.c_str(), varInfo.nBin, varInfo.min, varInfo.max);
drawInfo_[sample][type][varName] = varInfo.drawInfo;
// Initialize the Histogram
TH1D_[sample][type][varName]->GetYaxis()->SetTitle("Number of Entries");
TH1D_[sample][type][varName]->GetXaxis()->SetTitle(varInfo.label.c_str());
TH1D_[sample][type][varName]->Sumw2(kTRUE);
std::cout << "[INFO] Added histogram: " << histName << std::endl;
}
}
}
void
Histogram2::Fill(const std::string& sample, const std::string& type, const std::map< std::string , float >& valueMap)
{
for (auto& value : valueMap) {
std::string varName = value.first;
if (TH1D_.count(sample)>0 && TH1D_.at(sample).count(type)>0 && TH1D_.at(sample).at(type).count(varName)>0 && TH1D_.at(sample).at(type).at(varName)) {
TH1D_.at(sample).at(type).at(varName)->Fill(value.second);
}
}
}
void
Histogram2::Fill(const std::string& sample, const std::string& type, const std::map< std::string , std::pair< float , float > >& valueMap)
{
for (auto& value : valueMap) {
std::string varName = value.first;
if (TH1D_.count(sample)>0 && TH1D_.at(sample).count(type)>0 && TH1D_.at(sample).at(type).count(varName)>0 && TH1D_.at(sample).at(type).at(varName)) {
TH1D_.at(sample).at(type).at(varName)->Fill(value.second.first, value.second.second);
}
}
}
void
Histogram2::Norm(void)
{
for (auto& s : TH1D_) {
for (auto& t : s.second) {
for (auto& v : t.second) {
if (v.second) {
if (v.second->GetEntries()>0.) {
v.second->ClearUnderflowAndOverflow();
v.second->Scale(1.0/v.second->GetSumOfWeights());
}
}
}
}
}
}
void
Histogram2::Fit(const std::string& fName)
{
for (auto& s : TH1D_) {
std::string sample = s.first;
for (auto& t : TH1D_[sample]) {
std::string type = t.first;
for (auto& elem : TH1D_[sample][type]) {
std::string varName = elem.first;
std::string funcName = (std::string("f_") + sample + "_" + type + "_" + varName);
if (type=="") { funcName = (std::string("f_") + sample + "_" + varName); }
std::string funcRATIOName = (std::string("f_RATIO_") + sample + "_" + type + "_" + varName);
if (type=="") { funcRATIOName = (std::string("f_RATIO_") + sample + "_" + varName); }
double minX = TH1D_[sample][type][varName]->GetXaxis()->GetXmin();
double maxX = TH1D_[sample][type][varName]->GetXaxis()->GetXmax();
if (fName=="gaus") {
if (TF1_[sample][type][varName]) delete TF1_[sample][type][varName];
TF1_[sample][type][varName] = new TF1(funcName.c_str(), "gaus", minX, maxX);
double maxY = TH1D_[sample][type][varName]->GetBinContent(TH1D_[sample][type][varName]->GetMaximumBin());
TF1_[sample][type][varName]->SetParameter(0,maxY);
//TF1_[sample][type][varName]->FixParameter(0,maxY);
TF1_[sample][type][varName]->SetParameter(1,TH1D_[sample][type][varName]->GetMean());
TF1_[sample][type][varName]->SetParameter(2,TH1D_[sample][type][varName]->GetStdDev());
if (TF1_RATIO_[sample][type][varName]) delete TF1_RATIO_[sample][type][varName];
TF1_RATIO_[sample][type][varName] = new TF1(funcRATIOName.c_str(), "gaus(0)/(gaus(3))", minX, maxX);
}
if (TF1_[sample][type][varName]) {
TH1D_[sample][type][varName]->Fit(funcName.c_str(),"0");
}
}
}
}
// Apply General Settings to all TF1
for (auto& s : TF1_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->SetLineColor(kBlack);
v.second->SetLineWidth(3);
}
}
}
}
}
void
Histogram2::ComputeRatio(const std::string& rName)
{
// For TH1D
if (rName=="DATAvsFIT" || rName=="DATAvsMC") {
for (auto& s : TH1D_) {
std::string sample = s.first;
for (auto& t : s.second) {
std::string type = t.first;
for (auto& v : t.second) {
std::string varName = v.first;
std::string histName = (std::string("hRATIO_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
std::string histNormName = (std::string("hRATIO_NORM_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
double minX = v.second->GetXaxis()->GetXmin();
double maxX = v.second->GetXaxis()->GetXmax();
if (rName=="DATAvsMC" && sample.find("MC")!=std::string::npos) {
// Create Data Histogram
if (TH1D_RATIO_[sample][type][varName]!=NULL) delete TH1D_RATIO_[sample][type][varName];
TH1D_RATIO_[sample][type][varName] = new TH1D(histName.c_str(), histName.c_str(), v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->SetDirectory(0);
if (TH1D_RATIO_NORM_[sample][type][varName]!=NULL) delete TH1D_RATIO_NORM_[sample][type][varName];
TH1D_RATIO_NORM_[sample][type][varName] = new TH1D(histNormName.c_str(), histNormName.c_str(), v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->SetDirectory(0);
// Initialize the Histogram
TH1D_RATIO_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
// Make the ratio
std::string sampleData = "DATA_" + getBeam(sample);
if (TH1D_.count(sampleData)>0 && TH1D_.at(sampleData).count(type)>0 && TH1D_.at(sampleData).at(type).count(varName)>0 &&
TH1D_.at(sampleData).at(type).at(varName) && TH1D_.at(sampleData).at(type).at(varName)->GetEntries()>5.) {
TH1D_.at(sampleData).at(type).at(varName)->ClearUnderflowAndOverflow();
bool isNorm = false; //if (v.second->GetSumOfWeights()<=1.5) { isNorm = true; }
if (isNorm) { v.second->Scale(v.second->GetSumOfWeights()); }
if (isNorm) { TH1D_.at(sampleData).at(type).at(varName)->Scale(TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights()); }
if (isNorm) {
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(TH1D_.at(sampleData).at(type).at(varName), v.second,
(1./TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights()),
(1./v.second->GetSumOfWeights()),
"b");
}
else {
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(TH1D_.at(sampleData).at(type).at(varName), v.second, 1.0, 1.0, "b");
}
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->Divide(TH1D_.at(sampleData).at(type).at(varName), v.second,
(1./TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights()),
(1./v.second->GetSumOfWeights()),
"b");
if (isNorm) { v.second->Scale(1./v.second->GetSumOfWeights()); }
if (isNorm) { TH1D_.at(sampleData).at(type).at(varName)->Scale(1./TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights()); }
}
else {
TH1D* tmp = new TH1D("TMP", "TMP", v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(tmp, v.second, 1.0, 1.0, "b");
delete tmp;
}
if (TF1_.count(sampleData)>0 && TF1_.at(sampleData).count(type)>0 && TF1_.at(sampleData).at(type).count(varName)>0 && TF1_.at(sampleData).at(type).at(varName)) {
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(0, TF1_.at(sampleData).at(type).at(varName)->GetParameter(0));
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(1, TF1_.at(sampleData).at(type).at(varName)->GetParameter(1));
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(2, TF1_.at(sampleData).at(type).at(varName)->GetParameter(2));
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(3, TF1_.at(sample).at(type).at(varName)->GetParameter(0));
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(4, TF1_.at(sample).at(type).at(varName)->GetParameter(1));
TF1_RATIO_.at(sample).at(type).at(varName)->SetParameter(5, TF1_.at(sample).at(type).at(varName)->GetParameter(2));
}
}
if (rName=="DATAvsFIT" && TF1_RATIO_.count(sample)>0 && TF1_RATIO_.at(sample).count(type)>0 && TF1_RATIO_.at(sample).at(type).count(varName)>0 && TF1_RATIO_.at(sample).at(type).at(varName)) {
// Create Data Histogram
if (TH1D_RATIO_.at(sample).at(type).at(varName)) delete TH1D_RATIO_.at(sample).at(type).at(varName);
TH1D_RATIO_.at(sample).at(type).at(varName) = new TH1D(histName.c_str(), histName.c_str(), v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->SetDirectory(0);
// Create Fit Histogram
TH1D* Ref = (TH1D *) TH1D_RATIO_.at(sample).at(type).at(varName)->Clone("REF");
Ref->FillRandom(TF1_.at(sample).at(type).at(varName)->GetName(), v.second->GetEffectiveEntries());
if (v.second->GetSumOfWeights()<=1.5) { Ref->Scale(1.0/Ref->Integral()); }
// Initialize the Histogram
TH1D_RATIO_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("DATA/FIT");
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(v.second, Ref, 1., 1., "b");
delete Ref;
}
}
}
}
}
// For THStack
if (rName=="DATAvsMCStack") {
for (auto& s : THStack_) {
std::string sample = s.first;
for (auto& t : s.second) {
std::string type = t.first;
for (auto& v : t.second) {
if (v.second) {
std::string varName = v.first;
std::string histName = (std::string("hRATIO_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
std::string histNormName = (std::string("hRATIO_NORM_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
TH1D* hStack = ((TH1D*)v.second->GetStack()->At(v.second->GetNhists()-1));
double minX = hStack->GetXaxis()->GetXmin();
double maxX = hStack->GetXaxis()->GetXmax();
if (rName=="DATAvsMCStack" && sample.find("MC")!=std::string::npos) {
// Create Data Histogram
if (TH1D_RATIO_[sample][type][varName]!=NULL) delete TH1D_RATIO_[sample][type][varName];
TH1D_RATIO_[sample][type][varName] = new TH1D(histName.c_str(), histName.c_str(), hStack->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->SetDirectory(0);
if (TH1D_RATIO_NORM_[sample][type][varName]!=NULL) delete TH1D_RATIO_NORM_[sample][type][varName];
TH1D_RATIO_NORM_[sample][type][varName] = new TH1D(histNormName.c_str(), histNormName.c_str(), hStack->GetNbinsX(), minX, maxX);
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->SetDirectory(0);
// Initialize the Histogram
TH1D_RATIO_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
// Make the ratio
std::string sampleData = "DATA_" + getBeam(sample);
if (TH1D_.count(sampleData)>0 && TH1D_.at(sampleData).count(type)>0 && TH1D_.at(sampleData).at(type).count(varName)>0 &&
TH1D_.at(sampleData).at(type).at(varName) && TH1D_.at(sampleData).at(type).at(varName)->GetEntries()>5.) {
TH1D_.at(sampleData).at(type).at(varName)->ClearUnderflowAndOverflow();
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(TH1D_.at(sampleData).at(type).at(varName), hStack, 1.0, 1.0, "b");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->Divide(TH1D_.at(sampleData).at(type).at(varName), hStack,
1.0/TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights(),
1.0/hStack->GetSumOfWeights(),
"b");
}
else {
TH1D* tmp = new TH1D("TMP", "TMP", hStack->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(tmp, hStack, 1.0, 1.0, "b");
delete tmp;
}
}
}
}
}
}
}
// For TH1D
if (rName=="MCVarvsMCOff") {
for (auto& s : TH1D_) {
std::string sample = s.first;
for (auto& t : s.second) {
std::string type = t.first;
for (auto& v : t.second) {
std::string varName = v.first;
std::string histName = (std::string("hRATIO_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
std::string histNormName = (std::string("hRATIO_NORM_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
double minX = v.second->GetXaxis()->GetXmin();
double maxX = v.second->GetXaxis()->GetXmax();
if (rName=="MCVarvsMCOff" && sample.find("_Official")==std::string::npos) {
// Create Data Histogram
if (TH1D_RATIO_[sample][type][varName]!=NULL) delete TH1D_RATIO_[sample][type][varName];
TH1D_RATIO_[sample][type][varName] = new TH1D(histName.c_str(), histName.c_str(), v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->SetDirectory(0);
if (TH1D_RATIO_NORM_[sample][type][varName]!=NULL) delete TH1D_RATIO_NORM_[sample][type][varName];
TH1D_RATIO_NORM_[sample][type][varName] = new TH1D(histNormName.c_str(), histNormName.c_str(), v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->SetDirectory(0);
// Initialize the Histogram
TH1D_RATIO_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{Variation}{Official}");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{Variation}{Official}");
TH1D_RATIO_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetXaxis()->SetTitle(v.second->GetXaxis()->GetTitle());
// Make the ratio
std::string sampleMCOff = "MC_" + getDecayChannel(sample) + "Official_"+ getBeam(sample);
if (TH1D_.count(sampleMCOff)>0 && TH1D_.at(sampleMCOff).count(type)>0 && TH1D_.at(sampleMCOff).at(type).count(varName)>0 &&
TH1D_.at(sampleMCOff).at(type).at(varName) && TH1D_.at(sampleMCOff).at(type).at(varName)->GetEntries()>0.) {
TH1D_.at(sampleMCOff).at(type).at(varName)->ClearUnderflowAndOverflow();
bool isNorm = false; if (v.second->GetSumOfWeights()<=1.5) { isNorm = true; }
if (isNorm) { v.second->Scale(v.second->GetSumOfWeights()); }
if (isNorm) { TH1D_.at(sampleMCOff).at(type).at(varName)->Scale(TH1D_.at(sampleMCOff).at(type).at(varName)->GetSumOfWeights()); }
if (isNorm) {
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(v.second, TH1D_.at(sampleMCOff).at(type).at(varName),
(1./v.second->GetSumOfWeights()),
(1./TH1D_.at(sampleMCOff).at(type).at(varName)->GetSumOfWeights()),
"b");
}
else {
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(v.second, TH1D_.at(sampleMCOff).at(type).at(varName), 1.0, 1.0, "b");
}
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->Divide(v.second, TH1D_.at(sampleMCOff).at(type).at(varName),
(1./v.second->GetSumOfWeights()),
(1./TH1D_.at(sampleMCOff).at(type).at(varName)->GetSumOfWeights()),
"b");
if (isNorm) { v.second->Scale(1./v.second->GetSumOfWeights()); }
if (isNorm) { TH1D_.at(sampleMCOff).at(type).at(varName)->Scale(1./TH1D_.at(sampleMCOff).at(type).at(varName)->GetSumOfWeights()); }
}
else {
TH1D* tmp = new TH1D("TMP", "TMP", v.second->GetNbinsX(), minX, maxX);
TH1D_RATIO_.at(sample).at(type).at(varName)->Divide(tmp, v.second, 1.0, 1.0, "b");
delete tmp;
}
}
}
}
}
}
// Apply General Settings to all TH1D_RATIO_
for (auto& s : TH1D_RATIO_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->SetTitle("");
v.second->GetYaxis()->CenterTitle(kTRUE);
v.second->GetYaxis()->SetTitleOffset(0.4);
v.second->GetYaxis()->SetTitleSize(0.15);
v.second->GetYaxis()->SetLabelSize(0.13);
v.second->GetYaxis()->SetNdivisions(204);
v.second->GetYaxis()->SetTitle("");
v.second->GetXaxis()->SetTitleOffset(1);
v.second->GetXaxis()->SetTitleSize(0.15);
v.second->GetXaxis()->SetLabelSize(0.15);
if (rName=="MCVarvsMCOff") { v.second->GetYaxis()->SetRangeUser(0.9, 1.1); }
else { v.second->GetYaxis()->SetRangeUser(0.7, 1.3); }
v.second->SetMarkerColor(kBlue);
}
}
}
}
// Apply General Settings to all TH1D_RATIO_
for (auto& s : TH1D_RATIO_NORM_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->SetTitle("");
v.second->GetYaxis()->CenterTitle(kTRUE);
v.second->GetYaxis()->SetTitleOffset(0.4);
v.second->GetYaxis()->SetTitleSize(0.15);
v.second->GetYaxis()->SetLabelSize(0.13);
v.second->GetYaxis()->SetNdivisions(204);
v.second->GetYaxis()->SetTitle("");
v.second->GetXaxis()->SetTitleOffset(1);
v.second->GetXaxis()->SetTitleSize(0.15);
v.second->GetXaxis()->SetLabelSize(0.15);
if (rName=="MCVarvsMCOff") { v.second->GetYaxis()->SetRangeUser(0.9, 1.1); }
else { v.second->GetYaxis()->SetRangeUser(0.7, 1.3); }
v.second->SetMarkerColor(kBlue);
}
}
}
}
// Apply General Settings to all TF1_RATIO
for (auto& s : TF1_RATIO_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->SetLineColor(kBlack);
v.second->SetLineWidth(3);
}
}
}
}
}
void
Histogram2::MakeStackHistogram(const std::string& tag)
{
std::map< std::string ,std::map< std::string ,std::map< std::string , int> > > iSH;
for (auto& s : TH1D_) {
if (s.first.find("MC_")==std::string::npos) continue;
for (auto& t : s.second) {
for (auto& v : t.second) {
if (v.second && v.second->GetEntries()>5) {
const std::string sample = "MC_" + getBeam(s.first);
const std::string type = t.first;
const std::string varName = v.first;
const std::string name = "sh_" + (type!="" ? (sample + "_" + type) : sample) + "_" + varName;
if (THStack_[sample][type][varName]==NULL) {
THStack_[sample][type][varName] = new THStack(name.c_str(), name.c_str());
iSH[sample][type][varName] = 0;
}
v.second->SetMarkerColor(COLOR[iSH.at(sample).at(type).at(varName)]);
v.second->SetFillColor(COLOR[iSH.at(sample).at(type).at(varName)]);
v.second->SetMarkerStyle(MARKER[0]);
v.second->SetFillStyle(3001);
THStack_.at(sample).at(type).at(varName)->Add(v.second);
iSH.at(sample).at(type).at(varName)++;
}
}
}
}
// Apply General Settings to all THStack
for (auto& s : THStack_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->Draw();
v.second->GetYaxis()->SetTitleOffset(1.7);
v.second->GetYaxis()->SetTitleSize(0.04);
v.second->GetYaxis()->SetLabelSize(0.04);
v.second->GetXaxis()->SetTitle(((TH1D*)v.second->GetHists()->At(0))->GetXaxis()->GetTitle());
v.second->GetYaxis()->SetTitle(((TH1D*)v.second->GetHists()->At(0))->GetYaxis()->GetTitle());
if (v.second->GetMaximum()<=1.5) { v.second->GetYaxis()->SetTitle("Normalized Entries"); }
v.second->GetXaxis()->SetTitleOffset(1.0);
v.second->GetXaxis()->SetTitleSize(0.048);
v.second->GetXaxis()->SetLabelSize(0.035);
setYRange(v.second, NULL, drawInfo_.begin()->second.at(t.first).at(v.first).yLogScale);
if (tag=="DATAvsMCStack" || TH1D_RATIO_.size()>0) {
v.second->GetYaxis()->SetTitleSize(0.04*(1./0.8));
v.second->GetYaxis()->SetLabelSize(0.04*(1./0.8));
v.second->GetXaxis()->SetTitleOffset(3);
v.second->GetXaxis()->SetLabelOffset(3);
}
}
}
}
}
}
void
Histogram2::PrintMean(void)
{
std::vector< std::string > sampleV;
std::vector< std::string > typeV;
std::vector< std::string > varNameV;
for (auto& s : TH1D_) { sampleV.push_back(s.first); }
for (auto& t : TH1D_[sampleV[0]]) { typeV.push_back(t.first); }
for (auto& e : TH1D_[sampleV[0]][typeV[0]]) { varNameV.push_back(e.first); }
for (auto& varName : varNameV) {
std::cout << " " << std::endl;
std::cout << " Histrogram Statistics " << std::endl;
std::cout << " " << std::endl;
for (auto& type : typeV) {
for (auto& sample : sampleV) {
if (TH1D_[sample][type][varName]) {
double maxY = TH1D_[sample][type][varName]->GetBinContent(TH1D_[sample][type][varName]->GetMaximumBin());
std::cout << (((type!="")?(sample+"_"+type):sample)+"_"+varName)
<< " has Norm: " << maxY << "+-" << 0.0
<< " has Mean: " << TH1D_[sample][type][varName]->GetMean() << "+-" << TH1D_[sample][type][varName]->GetMeanError()
<< " has Sigma: " << TH1D_[sample][type][varName]->GetStdDev() << "+-" << TH1D_[sample][type][varName]->GetStdDevError()
<< std::endl;
}
}
}
std::cout << " " << std::endl;
std::cout << " " << std::endl;
}
}
std::string
Histogram2::GetString(const TH1D& h, bool Gauss)
{
std::string out = "";
if (Gauss) {
double maxY = h.GetBinContent(h.GetMaximumBin());
double mean = h.GetMean();
double sigm = h.GetStdDev();;
double maxYErr = (sqrt(maxY*h.Integral())/h.Integral());
double meanErr = h.GetMeanError();
double sigmErr = h.GetStdDevError();;
out = Form("N: %.4f#pm%.4f , #mu: %.4f#pm%.4f , #sigma: %.4f#pm%.4f",
maxY , maxYErr ,
mean , meanErr ,
sigm , sigmErr);
}
else {
double numEntries = h.GetSumOfWeights();
double numEntriesErr = sqrt(numEntries);
double mean = h.GetMean();
double meanErr = h.GetMeanError();
out = Form("Entries: %.3f#pm%.3f , Mean: %.3f#pm%.3f",
numEntries , numEntriesErr ,
mean , meanErr);
}
return out;
}
std::string
Histogram2::GetString(const TF1& f)
{
std::string out = "";
double maxY = f.GetParameter(0);
double mean = f.GetParameter(1);
double sigm = f.GetParameter(2);
double maxYErr = f.GetParError(0);
double meanErr = f.GetParError(1);
double sigmErr = f.GetParError(2);
out = Form("N: %.4f#pm%.4f , #mu: %.4f#pm%.4f , #sigma: %.4f#pm%.4f",
maxY , maxYErr ,
mean , meanErr ,
sigm , sigmErr);
return out;
}
void
Histogram2::PrintFinalMean(void)
{
std::vector< std::string > sampleV;
std::vector< std::string > typeV;
std::vector< std::string > varNameV;
for (auto& s : TH1D_) { sampleV.push_back(s.first); }
for (auto& t : TH1D_[sampleV[0]]) { typeV.push_back(t.first); }
for (auto& e : TH1D_[sampleV[0]][typeV[0]]) { varNameV.push_back(e.first); }
for (auto& varName : varNameV) {
double n_norm_Data=0, n_mean_Data=0, n_sigma_Data=0, n_norm_MC=0, n_mean_MC=0, n_sigma_MC=0;
double norm_Data=0, mean_Data=0, sigma_Data=0, norm_MC=0, mean_MC=0, sigma_MC=0;
std::cout << " " << std::endl;
std::cout << " Final Results " << std::endl;
std::cout << " " << std::endl;
for (auto& type : typeV) {
for (auto& sample : sampleV) {
if (TH1D_[sample][type][varName]) {
if (sample.find("DATA")!=std::string::npos) {
norm_Data += TF1_[sample][type][varName]->GetParameter(0)*((TF1_[sample][type][varName]->GetParError(0)>0.) ? TF1_[sample][type][varName]->GetParError(0) : 1.0);
mean_Data += TF1_[sample][type][varName]->GetParameter(1)*((TF1_[sample][type][varName]->GetParError(1)>0.) ? TF1_[sample][type][varName]->GetParError(1) : 1.0);
sigma_Data += TF1_[sample][type][varName]->GetParameter(2)*((TF1_[sample][type][varName]->GetParError(2)>0.) ? TF1_[sample][type][varName]->GetParError(2) : 1.0);
n_norm_Data += ((TF1_[sample][type][varName]->GetParError(0)>0.) ? TF1_[sample][type][varName]->GetParError(0) : 1.0);;
n_mean_Data += ((TF1_[sample][type][varName]->GetParError(1)>0.) ? TF1_[sample][type][varName]->GetParError(1) : 1.0);;
n_sigma_Data += ((TF1_[sample][type][varName]->GetParError(2)>0.) ? TF1_[sample][type][varName]->GetParError(2) : 1.0);;
}
if (sample.find("MC")!=std::string::npos) {
norm_MC += TF1_[sample][type][varName]->GetParameter(0)*((TF1_[sample][type][varName]->GetParError(0)>0.) ? TF1_[sample][type][varName]->GetParError(0) : 1.0);
mean_MC += TF1_[sample][type][varName]->GetParameter(1)*((TF1_[sample][type][varName]->GetParError(1)>0.) ? TF1_[sample][type][varName]->GetParError(1) : 1.0);
sigma_MC += TF1_[sample][type][varName]->GetParameter(2)*((TF1_[sample][type][varName]->GetParError(2)>0.) ? TF1_[sample][type][varName]->GetParError(2) : 1.0);
n_norm_MC += ((TF1_[sample][type][varName]->GetParError(0)>0.) ? TF1_[sample][type][varName]->GetParError(0) : 1.0);
n_mean_MC += ((TF1_[sample][type][varName]->GetParError(1)>0.) ? TF1_[sample][type][varName]->GetParError(1) : 1.0);
n_sigma_MC += ((TF1_[sample][type][varName]->GetParError(2)>0.) ? TF1_[sample][type][varName]->GetParError(2) : 1.0);
}
}
}
std::cout << ("DATA_"+varName)
<< " has Norm: " << (norm_Data/n_norm_Data) << "+-" << 0.0
<< " has Mean: " << (mean_Data/n_mean_Data) << "+-" << 0.0
<< " has Sigma: " << (sigma_Data/n_sigma_Data) << "+-" << 0.0
<< std::endl;
std::cout << " " << std::endl;
std::cout << ("MC_"+varName)
<< " has Norm: " << (norm_MC/n_norm_MC) << "+-" << 0.0
<< " has Mean: " << (mean_MC/n_mean_MC) << "+-" << 0.0
<< " has Sigma: " << (sigma_MC/n_sigma_MC) << "+-" << 0.0
<< std::endl;
std::cout << " " << std::endl;
std::cout << " " << std::endl;
}
}
}
void
Histogram2::PrintFitResults(void)
{
std::vector< std::string > sampleV;
std::vector< std::string > typeV;
std::vector< std::string > varNameV;
for (auto& s : TH1D_) { sampleV.push_back(s.first); }
for (auto& t : TH1D_[sampleV[0]]) { typeV.push_back(t.first); }
for (auto& e : TH1D_[sampleV[0]][typeV[0]]) { varNameV.push_back(e.first); }
for (auto& varName : varNameV) {
std::cout << " Fitting Results " << std::endl;
std::cout << " " << std::endl;
for (auto& type : typeV) {
for (auto& sample : sampleV) {
if (TF1_[sample][type][varName]) {
std::cout << (((type!="")?(sample+"_"+type):sample)+"_"+varName)
<< " has Norm: " << TF1_[sample][type][varName]->GetParameter(0) << "+-" << TF1_[sample][type][varName]->GetParError(0)
<< " has Mean: " << TF1_[sample][type][varName]->GetParameter(1) << "+-" << TF1_[sample][type][varName]->GetParError(1)
<< " has Sigma: " << TF1_[sample][type][varName]->GetParameter(2) << "+-" << TF1_[sample][type][varName]->GetParError(2)
<< std::endl;
}
}
}
std::cout << " " << std::endl;
std::cout << " " << std::endl;
}
}
void
Histogram2::Draw(const std::string& tag, const std::map< std::string , struct TypeInfo >& typeInfo)
{
if (tag=="") return;
// set the CMS style
setTDRStyle();
gStyle->SetOptStat(0);
gStyle->SetOptFit(0);
gSystem->mkdir("Plots", kTRUE);
// Apply General Settings to all TH1D
for (auto& s : TH1D_) { for (auto& t : s.second) { for (auto& v : t.second) { if (v.second) {
v.second->GetYaxis()->SetTitleOffset(1.7);
v.second->GetYaxis()->SetTitleSize(0.04);
v.second->GetYaxis()->SetLabelSize(0.04);
if (v.second->GetSumOfWeights()<=1.5) { v.second->GetYaxis()->SetTitle("Normalized Entries"); }
v.second->GetXaxis()->SetTitleOffset(1.0);
v.second->GetXaxis()->SetTitleSize(0.048);
v.second->GetXaxis()->SetLabelSize(0.035);
v.second->SetMarkerColor(kBlack);
v.second->SetFillStyle(3001);
v.second->SetFillColor(kBlue);
setYRange(v.second, NULL, drawInfo_.at(s.first).at(t.first).at(v.first).yLogScale);
if (tag=="DATAvsMC" || tag=="DATAvsFIT" || tag!="DATAvsMCStack" || TH1D_RATIO_.size()>0) {
v.second->GetYaxis()->SetTitleSize(0.04*(1./0.8));
v.second->GetYaxis()->SetLabelSize(0.04*(1./0.8));
v.second->GetXaxis()->SetTitleOffset(3);
v.second->GetXaxis()->SetLabelOffset(3);
}
}
}
}
}
// Case: Separate With Data -> Use one canvas for each histogram
if (tag=="separate") {
Double_t xl1=.20, yl1=0.62, xl2=xl1+.3, yl2=yl1+.250;
for (const auto& s : TH1D_) {
const std::string sample = s.first;
for (const auto& t : s.second) {
const std::string type = t.first;
gSystem->mkdir(Form("Plots/%s/%s/%s/png/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
gSystem->mkdir(Form("Plots/%s/%s/%s/pdf/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
for (const auto& v : t.second) {
const std::string varName = v.first;
if (v.second) {
std::string cName = (std::string("c_") + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
TCanvas* c = new TCanvas(cName.c_str(), cName.c_str(), 1000, 1000);
TLegend *leg = new TLegend(xl1,yl1,xl2,yl2);
c->cd();
if (v.second->GetEntries()>0) {
c->SetLogy(drawInfo_.at(sample).at(type).at(varName).yLogScale);
v.second->Draw("p");
leg->AddEntry(v.second, (type!="" ? (sample+"_"+type) : sample).c_str(), "p");
if (TF1_.count(sample)>0 && TF1_.at(sample).count(type)>0 && TF1_.at(sample).at(type).count(varName)>0 && TF1_.at(sample).at(type).at(varName)) {
leg->AddEntry(TF1_.at(sample).at(type).at(varName), "Fit", "l");
}
leg->Draw("SAME");
c->Update();
int option = 117;
if (sample.find("pPb")!=std::string::npos) option = 115;
if (sample.find("Pbp")!=std::string::npos) option = 116;
CMS_lumi(c, option, 33, "");
c->Update();
c->SaveAs(Form("Plots/%s/%s/%s/png/%s.png", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
c->SaveAs(Form("Plots/%s/%s/%s/pdf/%s.pdf", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
}
c->Clear();
c->Close();
delete c;
delete leg;
}
}
}
}
return;
}
// Case: Data vs StackMC -> Use one canvas for each stack histogram comparing MC vs Data
if (tag=="DATAvsMCStack") {
MakeStackHistogram("DATAvsMCStack");
ComputeRatio("DATAvsMCStack");
Double_t xl1=.20, yl1=0.75, xl2=xl1+.3, yl2=yl1+.135;
for (const auto& s : THStack_) {
const std::string sample = s.first;
for (auto& t : s.second) {
const std::string type = t.first;
gSystem->mkdir(Form("Plots/%s/%s/%s/png/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
gSystem->mkdir(Form("Plots/%s/%s/%s/pdf/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
for (auto& v : t.second) {
const std::string varName = v.first;
if (v.second) {
std::string cName = (std::string("c_") + "DATAvsMCStack" + "_" + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
TCanvas* c = new TCanvas(cName.c_str(), cName.c_str(), 1000, 1000);
TLegend *leg = new TLegend(xl1,yl1,xl2,yl2);
TLatex *tex = new TLatex(); tex->SetNDC(); tex->SetTextSize(0.025); float dy = 0;
TPad* padRATIO = NULL; TPad* padMAIN = NULL;
bool draw = false;
TH1D* hStack = ((TH1D*)v.second->GetStack()->At(v.second->GetNhists()-1));
c->cd();
if (v.second->GetMaximum()>0.) {
padMAIN = NULL;
if (TH1D_RATIO_.count(sample)>0 && TH1D_RATIO_.at(sample).count(type)>0 && TH1D_RATIO_.at(sample).at(type).count(varName)>0 && TH1D_RATIO_.at(sample).at(type).at(varName)) {
padMAIN = new TPad( "padMAIN", "", 0, 0.2, 1, 1 );
padMAIN->SetFixedAspectRatio(kTRUE);
padMAIN->SetBottomMargin(0.015);
}
else { padMAIN = new TPad( "padMAIN", "", 0, 0, 1, 1 ); }
padMAIN->Draw();
padMAIN->cd();
padMAIN->SetLogy(drawInfo_.begin()->second.at(type).at(varName).yLogScale);
v.second->GetXaxis()->SetTitle("");
v.second->GetYaxis()->SetTitle("Normalized Entries");
for (int i=0; i<v.second->GetNhists(); i++) {
((TH1D*)v.second->GetStack()->At(i))->ClearUnderflowAndOverflow();
((TH1D*)v.second->GetStack()->At(i))->Scale(1.0/hStack->GetSumOfWeights());
}
v.second->Draw("HISTF");
std::map<std::string , double> nEntries;
for (int i=0; i<v.second->GetNhists(); i++) {
std::string name = ((TH1D*)v.second->GetHists()->At(i))->GetTitle();
std::string tmp = name.substr(name.find("MC_")+3, name.length()); tmp = tmp.substr(0, tmp.find("_"));
name = "MC_" + tmp + "_" + getBeam(name);
leg->AddEntry(v.second->GetHists()->At(i), name.c_str(), "f");
nEntries[tmp] = ((TH1D*)v.second->GetHists()->At(i))->GetSumOfWeights();
}
if (typeInfo.count(type)>0) {
double dy = 0.00; for (const auto& s: typeInfo.at(type).cutSelection) { tex->DrawLatex(0.66, 0.72-dy, s.c_str()); dy+=0.04; }
}
// Plot Data
std::string sampleData = "DATA_" + getBeam(sample);
//tex->DrawLatex(0.20, 0.72-dy, ("MC : " + GetString(*hStack)).c_str()); dy+=0.040;
if (TH1D_.count(sampleData)>0 && TH1D_.at(sampleData).count(type)>0 && TH1D_.at(sampleData).at(type).count(varName)>0 &&
TH1D_.at(sampleData).at(type).at(varName) && TH1D_.at(sampleData).at(type).at(varName)->GetEntries()>0.) {
TH1D_.at(sampleData).at(type).at(varName)->ClearUnderflowAndOverflow();
TH1D_.at(sampleData).at(type).at(varName)->Scale(1.0/TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights());
TH1D_.at(sampleData).at(type).at(varName)->SetMarkerColor(kRed); TH1D_.at(sampleData).at(type).at(varName)->Draw("samep");
leg->AddEntry(TH1D_.at(sampleData).at(type).at(varName), sampleData.c_str(), "p");
//tex->DrawLatex(0.20, 0.72-dy, ("DATA: " + GetString(*TH1D_.at(sampleData).at(type).at(varName))).c_str()); dy+=0.040;
setYRange(v.second, TH1D_.at(sampleData).at(type).at(varName), drawInfo_.at(sampleData).at(type).at(varName).yLogScale);
double ratio = TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights()/hStack->GetSumOfWeights();
const double pValue_Chi2 = hStack->Chi2Test(TH1D_.at(sampleData).at(type).at(varName), "WW");
//tex->DrawLatex(0.20, 0.72-dy, Form("p-Value: #Chi^{2}: %.3f", pValue_Chi2)); dy+=0.04;
if (std::abs(ratio-1.0)>0.001) { tex->DrawLatex(0.20, 0.72-dy, Form("DATA/MC: %.4f", ratio)); }
if (typeInfo.count(type)>0) {
std::vector<std::string> typeSample = typeInfo.at(type).sample;
double bkgN = 0.; for (const auto& n : nEntries) { bool isSig=false; for (const auto& s : typeSample) { if (n.first==s) {isSig=true; break;} } if (!isSig) bkgN += n.second; }
double sigN = 0.; for (const auto& s : typeSample) { if (nEntries.count(s)>0) sigN += nEntries.at(s); }
if (sigN>0.) {
double ratio = ( (TH1D_.at(sampleData).at(type).at(varName)->GetSumOfWeights() - bkgN) / sigN );
tex->DrawLatex(0.37, 0.72-dy, Form("%s: %.4f", typeSample.at(0).c_str(), ratio));
}
}
}
leg->Draw("SAME");
padMAIN->Modified();
padMAIN->Update();
int option = 117;
if (sample.find("pPb")!=std::string::npos) option = 115;
if (sample.find("Pbp")!=std::string::npos) option = 116;
CMS_lumi(padMAIN, option, 33, "");
padMAIN->Modified();
padMAIN->Update();
draw = true;
}
c->cd();
if (draw) {
if (sample.find("MC")!=std::string::npos) {
padRATIO = new TPad( "padRATIO", "", 0, 0, 1, 0.20 );
padRATIO->SetFixedAspectRatio(kTRUE);
padRATIO->SetTopMargin(0.02);
padRATIO->SetBottomMargin(0.4);
padRATIO->SetFillStyle(4000);
padRATIO->SetFrameFillStyle(4000);
padRATIO->SetGridx(kTRUE);
padRATIO->SetGridy(kTRUE);
padRATIO->Draw();
padRATIO->cd();
if (TH1D_RATIO_.count(sample)>0 && TH1D_RATIO_.at(sample).count(type)>0 && TH1D_RATIO_.at(sample).at(type).count(varName)>0 && TH1D_RATIO_.at(sample).at(type).at(varName)) {
TH1D_RATIO_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->GetYaxis()->SetTitle("#frac{DATA}{MC}");
TH1D_RATIO_NORM_.at(sample).at(type).at(varName)->Draw("p");
if (TF1_RATIO_[sample][type][varName]!=NULL) TF1_RATIO_[sample][type][varName]->Draw("samel");
}
padRATIO->Modified();
padRATIO->Update();
}
c->Modified();
c->Update();
c->SaveAs(Form("Plots/%s/%s/%s/png/%s.png", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
c->SaveAs(Form("Plots/%s/%s/%s/pdf/%s.pdf", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
}
c->Clear();
c->Close();
delete c;
delete leg;
delete tex;
}
}
}
}
return;
}
// Case: Data vs Fit -> Use one canvas for each histogram comparing Fit vs Data
if (tag=="DATAvsFIT") {
ComputeRatio("DATAvsFIT");
Double_t xl1=.20, yl1=0.75, xl2=xl1+.3, yl2=yl1+.125;
for (const auto& s : TH1D_) {
const std::string sample = s.first;
for (auto& t : s.second) {
const std::string type = t.first;
gSystem->mkdir(Form("Plots/%s/%s/%s/png/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
gSystem->mkdir(Form("Plots/%s/%s/%s/pdf/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
for (auto& v : t.second) {
const std::string varName = v.first;
if (v.second) {
std::string cName = (std::string("c_") + "DATAvsFIT" + "_" + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
TCanvas* c = new TCanvas(cName.c_str(), cName.c_str(), 1000, 1000);
TLegend *leg = new TLegend(xl1,yl1,xl2,yl2);
TLatex *tex = new TLatex(); tex->SetNDC(); tex->SetTextSize(0.025); float dy = 0;
TPad* padRATIO = NULL; TPad* padMAIN = NULL;
bool draw = false;
c->cd();
if (v.second->GetEntries()>0.) {
padMAIN = NULL;
if (TH1D_RATIO_.count(sample)>0 && TH1D_RATIO_.at(sample).count(type)>0 && TH1D_RATIO_.at(sample).at(type).count(varName)>0 && TH1D_RATIO_.at(sample).at(type).at(varName)) {
padMAIN = new TPad( "padMAIN", "", 0, 0.2, 1, 1 );
padMAIN->SetFixedAspectRatio(kTRUE);
padMAIN->SetBottomMargin(0.015);
}
else { padMAIN = new TPad( "padMAIN", "", 0, 0, 1, 1 ); }
padMAIN->Draw();
padMAIN->cd();
padMAIN->SetLogy(drawInfo_.at(sample).at(type).at(varName).yLogScale);
v.second->Draw("p");
leg->AddEntry(v.second, (type!="" ? (sample+"_"+type) : sample).c_str(), "p");
tex->DrawLatex(0.20, 0.72-dy, ("HIST: " + GetString(*v.second)).c_str()); dy+=0.040;
if (TF1_.count(sample)>0 && TF1_.at(sample).count(type)>0 && TF1_.at(sample).at(type).count(varName)>0 && TF1_.at(sample).at(type).at(varName)) {
TF1_.at(sample).at(type).at(varName)->Draw("samel");
if (sample.find("DATA")!=std::string::npos) { leg->AddEntry(TF1_.at(sample).at(type).at(varName), "Fit DATA", "l"); }
if (sample.find("MC")!=std::string::npos ) { leg->AddEntry(TF1_.at(sample).at(type).at(varName), "Fit MC", "l"); }
tex->DrawLatex(0.20, 0.72-dy, ("FIT : " + GetString(*TF1_.at(sample).at(type).at(varName))).c_str()); dy+=0.040;
}
leg->Draw("SAME");
padMAIN->Update();
int option = 117;
if (sample.find("pPb")!=std::string::npos) option = 115;
if (sample.find("Pbp")!=std::string::npos) option = 116;
CMS_lumi(padMAIN, option, 33, "");
padMAIN->Update();
draw = true;
}
c->cd();
if (draw) {
padRATIO = new TPad( "padRATIO", "", 0, 0, 1, 0.20 );
padRATIO->SetFixedAspectRatio(kTRUE);
padRATIO->SetTopMargin(0.02);
padRATIO->SetBottomMargin(0.4);
padRATIO->SetFillStyle(4000);
padRATIO->SetFrameFillStyle(4000);
padRATIO->SetGridx(kTRUE);
padRATIO->SetGridy(kTRUE);
padRATIO->Draw();
padRATIO->cd();
if (TH1D_RATIO_.count(sample)>0 && TH1D_RATIO_.at(sample).count(type)>0 && TH1D_RATIO_.at(sample).at(type).count(varName)>0 && TH1D_RATIO_.at(sample).at(type).at(varName)) {
TH1D_RATIO_[sample][type][varName]->GetYaxis()->SetTitle("#frac{DATA}{FIT}");
TH1D_RATIO_[sample][type][varName]->Draw("p");
}
padRATIO->Update();
c->Update();
c->SaveAs(Form("Plots/%s/%s/%s/png/%s.png", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
c->SaveAs(Form("Plots/%s/%s/%s/pdf/%s.pdf", tag.c_str(), type.c_str(), sample.c_str(), cName.c_str()));
}
c->Clear();
c->Close();
delete c;
delete leg;
delete tex;
}
}
}
}
return;
}
// Case: Data vs MC -> Use one canvas for each histogram comparing MC vs Data
if (tag=="DATAvsMC") {
ComputeRatio("DATAvsMC");
Double_t xl1=.20, yl1=0.75, xl2=xl1+.3, yl2=yl1+.125;
for (const auto& s : TH1D_) {
const std::string sample = s.first;
if ( tag=="DATAvsMC" && sample.find("MC")==std::string::npos) continue;
for (auto& t : s.second) {
const std::string type = t.first;
gSystem->mkdir(Form("Plots/%s/%s/%s/png/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
gSystem->mkdir(Form("Plots/%s/%s/%s/pdf/", tag.c_str(), type.c_str(), sample.c_str()), kTRUE);
for (auto& v : t.second) {
const std::string varName = v.first;
if (v.second) {
std::string cName = (std::string("c_") + "DATAvsMC" + "_" + (type!="" ? (sample + "_" + type) : sample) + "_" + varName);
TCanvas* c = new TCanvas(cName.c_str(), cName.c_str(), 1000, 1000);
TLegend *leg = new TLegend(xl1,yl1,xl2,yl2);
TLatex *tex = new TLatex(); tex->SetNDC(); tex->SetTextSize(0.025); float dy = 0;
TPad* padRATIO = NULL; TPad* padMAIN = NULL;
bool draw = false;
c->cd();
if (v.second->GetEntries()>0.) {
padMAIN = NULL;
if (TH1D_RATIO_.count(sample)>0 && TH1D_RATIO_.at(sample).count(type)>0 && TH1D_RATIO_.at(sample).at(type).count(varName)>0 && TH1D_RATIO_.at(sample).at(type).at(varName)) {
padMAIN = new TPad( "padMAIN", "", 0, 0.2, 1, 1 );
padMAIN->SetFixedAspectRatio(kTRUE);
padMAIN->SetBottomMargin(0.015);
}
else { padMAIN = new TPad( "padMAIN", "", 0, 0, 1, 1 ); }
padMAIN->Draw();
padMAIN->cd();
padMAIN->SetLogy(drawInfo_.at(sample).at(type).at(varName).yLogScale);
v.second->GetXaxis()->SetTitle("");
v.second->Draw("histf");
leg->AddEntry(v.second, (type!="" ? (sample+"_"+type) : sample).c_str(), "f");
if (typeInfo.count(type)>0) {
double dy = 0.08; for (const auto& s: typeInfo.at(type).cutSelection) { tex->DrawLatex(0.66, 0.72-dy, s.c_str()); dy+=0.04; }
}
if (TF1_.count(sample)>0 && TF1_.at(sample).count(type)>0 && TF1_.at(sample).at(type).count(varName)>0 && TF1_.at(sample).at(type).at(varName)) {
TF1_.at(sample).at(type).at(varName)->Draw("samel");
if (sample.find("DATA")!=std::string::npos) { leg->AddEntry(TF1_.at(sample).at(type).at(varName), "Fit DATA", "l"); }
if (sample.find("MC")!=std::string::npos ) { leg->AddEntry(TF1_.at(sample).at(type).at(varName), "Fit MC", "l"); }
tex->DrawLatex(0.20, 0.72-dy, ("FIT : " + GetString(*TF1_.at(sample).at(type).at(varName))).c_str()); dy+=0.040;
}
// Plot Data
std::string sampleData = "DATA_" + getBeam(sample);
//if (TF1_[sample][type][varName]==NULL) { tex->DrawLatex(0.20, 0.72-dy, ("MC : " + GetString(*v.second)).c_str()); dy+=0.040; }
if (TH1D_.count(sampleData)>0 && TH1D_.at(sampleData).count(type)>0 && TH1D_.at(sampleData).at(type).count(varName)>0 &&
TH1D_.at(sampleData).at(type).at(varName) && TH1D_.at(sampleData).at(type).at(varName)->GetEntries()>5.) {