From db284f1157b65041e5639d41c73e92e63d32a052 Mon Sep 17 00:00:00 2001
From: Jihee Kim <jihee.kim@anl.gov>
Date: Wed, 20 Jan 2021 14:35:41 -0600
Subject: [PATCH] Eres fit
---
.../scripts/rec_emcal_resolution_analysis.cxx | 237 ++++++++++++++++++
1 file changed, 237 insertions(+)
create mode 100644 ecal/scripts/rec_emcal_resolution_analysis.cxx
diff --git a/ecal/scripts/rec_emcal_resolution_analysis.cxx b/ecal/scripts/rec_emcal_resolution_analysis.cxx
new file mode 100644
index 00000000..e03b4a2e
--- /dev/null
+++ b/ecal/scripts/rec_emcal_resolution_analysis.cxx
@@ -0,0 +1,237 @@
+////////////////////////////////////////
+// Read reconstruction ROOT output file
+// Plot energy resolution
+// 2021/01/20
+////////////////////////////////////////
+
+#include "ROOT/RDataFrame.hxx"
+#include <iostream>
+
+#include "dd4pod/Geant4ParticleCollection.h"
+#include "dd4pod/CalorimeterHitCollection.h"
+#include "dd4pod/TrackerHitCollection.h"
+#include "eicd/CalorimeterHitCollection.h"
+#include "eicd/CalorimeterHitData.h"
+#include "eicd/ClusterCollection.h"
+#include "eicd/ClusterData.h"
+
+#include "TCanvas.h"
+#include "TStyle.h"
+#include "TMath.h"
+#include "TH1.h"
+#include "TH1D.h"
+
+// If root cannot find a dd4pod header make sure to add the include dir to ROOT_INCLUDE_PATH:
+// export ROOT_INCLUDE_PATH=$HOME/include:$ROOT_INCLUDE_PATH
+// export ROOT_INCLUDE_PATH=/home/jihee/stow/development/include:$ROOT_INCLUDE_PATH
+
+using ROOT::RDataFrame;
+using namespace ROOT::VecOps;
+
+void rec_emcal_resolution_analysis(const char* input_fname = "rec_emcal_uniform_electrons.root")
+{
+ // Setting for graphs
+ gROOT->SetStyle("Plain");
+ gStyle->SetOptFit(1);
+ gStyle->SetLineWidth(2);
+ gStyle->SetPadTickX(1);
+ gStyle->SetPadTickY(1);
+ gStyle->SetPadGridX(1);
+ gStyle->SetPadGridY(1);
+ gStyle->SetPadLeftMargin(0.14);
+ gStyle->SetPadRightMargin(0.14);
+
+ ROOT::EnableImplicitMT();
+ ROOT::RDataFrame d0("events", input_fname);
+
+ // Number of Clusters
+ auto ncluster = [] (const std::vector<eic::ClusterData>& evt) {return (int) evt.size(); };
+
+ // Cluster Energy [GeV]
+ auto clusterE = [] (const std::vector<eic::ClusterData>& evt) {
+ std::vector<double> result;
+ for (const auto& i: evt)
+ result.push_back(i.energy);
+ return result;
+ };
+
+ // Thrown Energy [GeV]
+ auto E_thr = [](std::vector<dd4pod::Geant4ParticleData> const& input) {
+ std::vector<double> result;
+ result.push_back(TMath::Sqrt(input[2].psx*input[2].psx + input[2].psy*input[2].psy + input[2].psz*input[2].psz + input[2].mass*input[2].mass));
+ return result;
+ };
+
+ // Energy Resolution = delta(E)/E
+ // delta(E) = (Erec - Ethr)
+ // E = Ethr
+ auto E_res = [] (const std::vector<double>& Erec, const std::vector<double>& Ethr) {
+ std::vector<double> result;
+ for (const auto& E1 : Ethr) {
+ for (const auto& E2 : Erec) {
+ result.push_back((E2-E1)/E1);
+ }
+ }
+ return result;
+ };
+
+ // Define variables
+ auto d1 = d0.Define("ncluster", ncluster, {"EcalClusters"})
+ .Define("clusterE", clusterE, {"EcalClusters"})
+ .Define("E_thr", E_thr, {"mcparticles2"})
+ .Define("E_res", E_res, {"clusterE","E_thr"})
+ ;
+
+ // Define Cuts
+ // d2: Select Events with One Cluster
+ // d3: Select Events which determined their center of cluster not being on the edge of detector in addition to d2 cut
+ auto d2 = d1.Filter("ncluster==1");
+ auto d3 = d2.Filter([=] (const std::vector<eic::ClusterData>& evt) {
+ for(const auto& i: evt) {
+ auto pos_x = i.position.x;
+ auto pos_y = i.position.y;
+ auto radial_dist = TMath::Sqrt(pos_x*pos_x + pos_y*pos_y);
+ if (radial_dist > 8.0 && radial_dist < 30.0)
+ return true;
+ }
+ return false;}, {"EcalClusters"});
+
+ // Define histograms
+ auto hEresNC1 = d2.Histo1D({"hEresNC1", "Energy Resolution CE vs Ethr w/ NC1; #DeltaE/E; Events", 100, -0.5, 0.5}, "E_res");
+ auto hEresNC1EGCUT = d3.Histo1D({"hEresNC1EGCUT", "Energy Resolution CE vs Ethr w/ NC1 EGCUT; #DeltaE/E; Events", 100, -0.5, 0.5}, "E_res");
+
+ // Energy Resolution Graphs
+ // Divided into serveral energy bin group
+ // Do gaussian git to extract mean and sigma
+ int nbin = 12; // number of energy bin group
+ double maxEnergy = 30.0; // maximum of energy in dataset
+ double multiple = maxEnergy / (double)nbin; // energy interval between energy bin group
+ double maximumE; // high end in each energy bin group
+ double minimumE; // low end in each energy bin group
+ double mean[nbin]; // mean from gaussian fit
+ double sigma[nbin]; // sigma from gaussian fit
+ double dmean[nbin]; // error on mean
+ double dsigma[nbin]; // error on sigma
+ double gEbin[nbin]; // center of energy in each group
+ double invSqrtgEbin[nbin]; // inverse sqrt center of energy in each group
+ double resolution[nbin]; // resolution = sigma/mean
+ double resolutionError[nbin]; // error on resolution
+ double resolutionErrorSigma; // error on resolution sigma term
+ double resolutionErrorMean; // error on resolution mean term
+ double xerror[nbin]; // set to 0.0 for all
+ // Loop over each energy bin group
+ // Define hitogram and do gaussian fit
+ // Save fit results; mean, sigma, error on mean & sigam
+ // Calculate resolution and resolution error
+ for(int n=1; n <= nbin; n++) {
+ maximumE = n * multiple;
+ minimumE = maximumE - multiple;
+ gEbin[n-1] = (maximumE + minimumE) / 2.0;
+ invSqrtgEbin[n-1] = 1.0 / TMath::Sqrt(gEbin[n-1]);
+ // Define histogram
+ auto h = d3.Filter([=] (const std::vector<eic::ClusterData>& evt) {
+ for (const auto& i: evt) {
+ auto eng = i.energy;
+ if (eng >= minimumE && eng < maximumE)
+ return true;
+ }
+ return false;}, {"EcalClusters"})
+ .Histo1D({"h", "Energy Resolution; #DeltaE/E; Events", 100, -0.5, 0.5}, "E_res");
+ // Gaussian fit
+ h->Fit("gaus","W,E");
+ // Save fit results
+ // how to access how many events in histogram: h->GetEntries();
+ if(h->GetFunction("gaus")) {
+ mean[n-1] = TMath::Abs(h->GetFunction("gaus")->GetParameter(1));
+ dmean[n-1] = h->GetFunction("gaus")->GetParError(1);
+ sigma[n-1] = h->GetFunction("gaus")->GetParameter(2);
+ dsigma[n-1] = h->GetFunction("gaus")->GetParError(2);
+ resolution[n-1] = sigma[n-1] / mean[n-1];
+ resolutionErrorSigma = dsigma[n-1] / mean[n-1];
+ resolutionErrorMean = dmean[n-1] * sigma[n-1];
+ resolutionError[n-1] = TMath::Sqrt(resolutionErrorSigma*resolutionErrorSigma + resolutionErrorMean*resolutionErrorMean);
+ xerror[n-1] = 0.0;
+ }
+ // Draw histogram, but
+ // Just save fit results
+ //TCanvas *c = new TCanvas("c", "c", 500, 500);
+ //h->GetYaxis()->SetTitleOffset(1.4);
+ //h->SetLineWidth(2);
+ //h->SetLineColor(kBlue);
+ //h->Fit("gaus","W,E");
+ //h->DrawClone();
+ //c->SaveAs("results/h.png");
+ }
+
+ // Generate graphs using gaussian fit results
+ // Cluster energy VS Simga
+ TGraphErrors* gCEVsSigmaNC1EGCUT = new TGraphErrors(nbin,gEbin,sigma,xerror,dsigma);
+ TCanvas *c1 = new TCanvas("c1","c1",500,500);
+ gCEVsSigmaNC1EGCUT->SetTitle("Cluster Energy vs #sigma");
+ gCEVsSigmaNC1EGCUT->GetYaxis()->SetTitleOffset(1.4);
+ gCEVsSigmaNC1EGCUT->GetXaxis()->SetTitle("Cluster Energy [GeV]");
+ gCEVsSigmaNC1EGCUT->GetYaxis()->SetTitle("#sigma");
+ gCEVsSigmaNC1EGCUT->GetYaxis()->SetRangeUser(0.0,0.05);
+ gCEVsSigmaNC1EGCUT->SetMarkerStyle(21);
+ gCEVsSigmaNC1EGCUT->DrawClone("AEP");
+ c1->SaveAs("results/emcal_electrons_gCEVsSigmaNC1EGCUT.png");
+ c1->SaveAs("results/emcal_electrons_gCEVsSigmaNC1EGCUT.pdf");
+ // Cluster energy VS Mean
+ TGraphErrors* gCEVsMeanNC1EGCUT = new TGraphErrors(nbin,gEbin,mean,xerror,dmean);
+ TCanvas *c2 = new TCanvas("c2","c2",500,500);
+ gCEVsMeanNC1EGCUT->SetTitle("Cluster Energy vs #mu");
+ gCEVsMeanNC1EGCUT->GetYaxis()->SetTitleOffset(1.4);
+ gCEVsMeanNC1EGCUT->GetXaxis()->SetTitle("Cluster Energy [GeV]");
+ gCEVsMeanNC1EGCUT->GetYaxis()->SetTitle("#mu");
+ gCEVsMeanNC1EGCUT->GetYaxis()->SetRangeUser(0.0,0.1);
+ gCEVsMeanNC1EGCUT->SetMarkerStyle(21);
+ gCEVsMeanNC1EGCUT->DrawClone("AEP");
+ c2->SaveAs("results/emcal_electrons_gCEVsMeanNC1EGCUT.png");
+ c2->SaveAs("results/emcal_electrons_gCEVsMeanNC1EGCUT.pdf");
+ // Inverse of sqrt(cluster energy) VS resolution
+ TGraphErrors* gInvSqCEVsSigmaENC1EGCUT = new TGraphErrors(nbin,invSqrtgEbin,resolution,xerror,resolutionError);
+ TCanvas *c3 = new TCanvas("c3","c3",500,500);
+ gInvSqCEVsSigmaENC1EGCUT->SetTitle("#sigma/E [%] vs 1/sqrt(Cluster Energy)");
+ gInvSqCEVsSigmaENC1EGCUT->GetYaxis()->SetTitleOffset(1.4);
+ gInvSqCEVsSigmaENC1EGCUT->GetXaxis()->SetTitle("1/sqrt(Cluster Energy)");
+ gInvSqCEVsSigmaENC1EGCUT->GetYaxis()->SetTitle("#sigma/E [%]");
+ gInvSqCEVsSigmaENC1EGCUT->GetYaxis()->SetRangeUser(0.0,1.5);
+ gInvSqCEVsSigmaENC1EGCUT->GetXaxis()->SetRangeUser(0.0,1.5);
+ gInvSqCEVsSigmaENC1EGCUT->SetMarkerStyle(21);
+ gInvSqCEVsSigmaENC1EGCUT->DrawClone("AEP");
+ c3->SaveAs("results/emcal_electrons_gInvSqCEVsSimgaENC1EGCUT.png");
+ c3->SaveAs("results/emcal_electrons_gInvSqCEVsSigmaENC1EGCUT.pdf");
+
+ // Fit Function
+ // sigma/E = S/sqrt(E) + N/E + C; added in quadrature
+ // S: Stochastic term
+ // N: Niose term
+ // C: Constant term
+ TF1 *f1 = new TF1("f1","sqrt([0]*[0] + pow([1]/sqrt(x),2) + pow([2]/x,2))", 0.5, 30.0);
+ f1->SetParNames("C", "S", "N"); // param names
+ f1->SetParameters(0.30,2.80,0.12); // initial param values
+ f1->SetLineWidth(2);
+ f1->SetLineColor(kRed);
+
+ // Cluster energy VS resolution
+ TGraphErrors* gCEVsSigmaENC1EGCUT = new TGraphErrors(nbin,gEbin,resolution,xerror,resolutionError);
+ TCanvas *c4 = new TCanvas("c4","c4",500,500);
+ gCEVsSigmaENC1EGCUT->SetTitle("Cluster Energy vs #sigma/E [%]");
+ gCEVsSigmaENC1EGCUT->GetYaxis()->SetTitleOffset(1.4);
+ gCEVsSigmaENC1EGCUT->GetXaxis()->SetTitle("Cluster Energy [GeV]");
+ gCEVsSigmaENC1EGCUT->GetYaxis()->SetTitle("#sigma/E [%]");
+ gCEVsSigmaENC1EGCUT->GetYaxis()->SetRangeUser(0.0,1.5);
+ gCEVsSigmaENC1EGCUT->SetMarkerStyle(21);
+ gCEVsSigmaENC1EGCUT->Fit("f1","W,E");
+ gCEVsSigmaENC1EGCUT->DrawClone("AEP");
+ c4->SaveAs("results/emcal_electrons_gCEVsSimgaENC1EGCUT.png");
+ c4->SaveAs("results/emcal_electrons_gCEVsSigmaENC1EGCUT.pdf");
+
+ // Event Counts
+ auto nevents_thrown = d1.Count();
+ auto nevents_cluster1 = d2.Count();
+ auto nevents_cluster1cut = d3.Count();
+
+ std::cout << "Number of Events: " << (*nevents_cluster1) << " / " << (*nevents_thrown) << " = single cluster events/all \n";
+ std::cout << "Number of Events: " << (*nevents_cluster1cut) << " / " << (*nevents_thrown) << " = single cluster events that passed edge cut/all \n";
+}
--
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