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jengbou |
1.1 |
#if !defined(__CINT__) && !defined(__MAKECINT__)
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#include "DataFormats/FWLite/interface/Handle.h"
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#include "DataFormats/FWLite/interface/Event.h"
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#include "DataFormats/FWLite/interface/ChainEvent.h"
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//Headers for the data items
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#include "DataFormats/VertexReco/interface/Vertex.h"
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#include "DataFormats/BeamSpot/interface/BeamSpot.h"
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#endif
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#include "TROOT.h"
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#include "TH2F.h"
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#include "TFile.h"
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#include "TF1.h"
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#include "TCanvas.h"
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#include "TMath.h"
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#include "TBox.h"
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#include <vector>
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#include <map>
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#include <string>
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using namespace std;
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typedef map<unsigned int, unsigned int> RunNumberMap;
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//
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// iterative fit of +- 2 sigma Gaussian core on a 1d histogram
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//
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bool fitHistogram (TH1* slice, TF1& fg, double* pars, double* epars, bool dbg = false) {
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// initialization of parameters
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pars[0] = slice->GetMaximum();
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pars[1] = slice->GetMean();
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pars[2] = slice->GetRMS();
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epars[0] = 0;
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epars[1] = 0;
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epars[2] = 0;
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// some iterations
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bool converged(false);
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for ( unsigned int it=0; it<10; ++it) {
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const double nSigRange = 2.;
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fg.SetParameters(pars);
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double oldMean = pars[1];
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double oldWidth = pars[2];
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if ( it>0 ) {
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fg.SetRange(pars[1]-nSigRange*pars[2],
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pars[1]+nSigRange*pars[2]);
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// if ( dbg ) {
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// cout << "Setting range to " << pars[1]-nSigRange*pars[2]
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// << " " << pars[1]+nSigRange*pars[2] << endl;
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// }
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}
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else {
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fg.SetRange(slice->GetXaxis()->GetXmin(),
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slice->GetXaxis()->GetXmax());
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// if ( dbg ) {
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// cout << "Setting range to " << slice->GetXaxis()->GetXmin()
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// << " " << slice->GetXaxis()->GetXmax() << endl;
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// }
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}
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if ( dbg )
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slice->Fit(&fg,"QLR+");
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else
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slice->Fit(&fg,"QLR");
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fg.GetParameters(pars);
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epars[0] = fg.GetParError(0);
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epars[1] = fg.GetParError(1);
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epars[2] = fg.GetParError(2);
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if ( converged ) {
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cout << "terminating at iteration " << it << " "
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<< pars[1] << " " << oldMean << " " << epars[1] << " "
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<< pars[2] << " " << oldWidth << " " << epars[2] << endl;
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break;
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}
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else if ( dbg ) {
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cout << " at iteration " << it << " "
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<< pars[1] << " " << oldMean << " " << epars[1] << " "
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<< pars[2] << " " << oldWidth << " " << epars[2] << endl;
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}
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// convergence criterion
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if ( it>2 &&
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fabs((pars[1]-oldMean))<max(fabs(0.01*epars[1]),0.0010) &&
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fabs((pars[2]-oldWidth))<max(fabs(0.01*epars[2]),0.0010) ) {
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converged = true;
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}
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}
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return converged;
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}
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//
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// fit Gaussian to slices of the 2d "run" histogram
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//
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void fitRunHistogram (TH2* histo, TH1*& hmean, TH1*& hwidth) {
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//
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// create histograms for mean and width vs. run
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//
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TDirectory* saveDir = gDirectory;
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gROOT->cd();
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int nbin = histo->GetNbinsX();
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string title = histo->GetName();
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TAxis* xhisto = histo->GetXaxis();
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hmean = new TH1F((title+"Mean").c_str(),title.c_str(),nbin,-0.5,nbin-0.5);
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TAxis* xhmean = hmean->GetXaxis();
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hwidth = new TH1F((title+"Width").c_str(),title.c_str(),nbin,-0.5,nbin-0.5);
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TAxis* xhwidth = hwidth->GetXaxis();
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//
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// fit function
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//
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TF1 fg("fg","gaus");
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//
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// loop over runs
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//
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bool converged;
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double pars[3];
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double epars[3];
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for ( unsigned int ib=1; ib<=nbin; ++ib ) {
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//
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// initialize mean and width to 0 error
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//
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hmean->SetBinError(ib,0.);
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hwidth->SetBinError(ib,0.);
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//
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// get slice
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//
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TH1* slice =
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histo->ProjectionY((title+xhisto->GetBinLabel(ib)).c_str(),ib,ib);
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// drop histograms with too few entries
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if ( slice->GetEntries()<100 ) {
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delete slice;
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continue;
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}
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//
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// fit slice
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//
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converged = fitHistogram(slice,fg,pars,epars);
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if ( converged ) {
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// copy parameters and errors
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hmean->SetBinContent(ib,pars[1]);
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hmean->SetBinError(ib,epars[1]);
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hwidth->SetBinContent(ib,pars[2]);
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hwidth->SetBinError(ib,epars[2]);
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}
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else {
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cout << "No convergence for " << histo->GetName() << " / run "
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<< histo->GetXaxis()->GetBinLabel(ib) << endl;
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// refit with debug flag
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// fitHistogram(slice,fg,pars,epars,true);
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hmean->SetBinContent(ib,pars[1]);
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hmean->SetBinError(ib,epars[1]);
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hwidth->SetBinContent(ib,pars[2]);
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hwidth->SetBinError(ib,epars[2]);
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}
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// keep failing fits for debugging
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// if ( converged ) delete slice;
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xhmean->SetBinLabel(ib,xhisto->GetBinLabel(ib));
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xhwidth->SetBinLabel(ib,xhisto->GetBinLabel(ib));
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}
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saveDir->cd();
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}
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//
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// set x-axis labels to run number
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//
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void setRunNumberLabels (TH1* histo, RunNumberMap& runNumbers) {
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char label[32];
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TAxis* axis = histo->GetXaxis();
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for ( RunNumberMap::const_iterator i=runNumbers.begin();
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i!=runNumbers.end(); ++i ) {
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sprintf(label,"%d",(*i).first);
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axis->SetBinLabel((*i).second+1,label);
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}
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}
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//
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// plot PV distribution for a single run with indication of BS position
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//
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void plotRun (char coord, int run)
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{
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char title[64];
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sprintf(title,"pv%cVsRun%d",coord,run);
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TH1* hpv = (TH1*)gROOT->FindObject(title);
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if ( hpv==0 ) return;
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sprintf(title,"pv%cRun%d",coord,run);
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TCanvas* c = new TCanvas(title);
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hpv->Draw();
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sprintf(title,"bs%cVsRunMean",coord);
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TH1* hbs = (TH1*)gROOT->FindObject(title);
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sprintf(title,"%d",run);
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double vbs(0.);
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double ebs(0.);
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for ( unsigned int ib=1; ib<=hbs->GetNbinsX(); ++ib ) {
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const char* label = hbs->GetXaxis()->GetBinLabel(ib);
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if ( strcmp(title,label)==0 ) {
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vbs = hbs->GetBinContent(ib);
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ebs = hbs->GetBinError(ib);
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break;
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}
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}
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TBox* box = new TBox(vbs-ebs,0,vbs+ebs,hpv->GetMaximum());
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box->SetFillStyle(1001);
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box->SetFillColor(7);
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box->Draw();
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hpv->Draw("same");
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sprintf(title,"pv%cRun%d.png",coord,run);
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c->SaveAs(title);
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delete c;
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}
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//
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// summary plots (PV + BS) vs run
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//
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void plotPvVsBs () {
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char coord[] = { "xyz" };
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for ( int ic=0; ic<3; ++ic ) {
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string canvasTitle("pvVsBs");
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canvasTitle += coord[ic];
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TCanvas* c = new TCanvas(canvasTitle.c_str(),canvasTitle.c_str(),
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700,500);
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string bsTitle("bs.VsRunMean");
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bsTitle.replace(2,1,1,coord[ic]);
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TH1* bsVsRun = (TH1*)gROOT->FindObject(bsTitle.c_str());
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string pvTitle("pv.VsRunMean");
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pvTitle.replace(2,1,1,coord[ic]);
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TH1* pvVsRun = (TH1*)gROOT->FindObject(pvTitle.c_str());
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pvVsRun->SetMarkerStyle(20);
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pvVsRun->Draw();
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bsVsRun->SetFillStyle(1001);
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bsVsRun->SetFillColor(7);
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bsVsRun->Draw("E2 same");
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pvVsRun->Draw("same");
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}
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}
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//
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// main entry point
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//
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void pvHistory (const vector<string>& fileNames) {
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fwlite::ChainEvent ev(fileNames);
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fwlite::Handle< reco::BeamSpot > bsHandle;
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fwlite::Handle< vector<reco::Vertex> > pvHandle;
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//
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// create list of runs with > 100 PVs
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//
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RunNumberMap runNumberCounts;
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int lastRun(0);
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for( ev.toBegin(); !ev.atEnd(); ++ev) {
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unsigned int run = ev.id().run();
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pvHandle.getByLabel(ev,"offlinePrimaryVertices");
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const reco::Vertex& pv = (*pvHandle)[0];
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if ( pv.tracksSize()>0 && pv.ndof()>2 &&
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(pv.ndof()+3.)/2./pv.tracksSize()>0.5 ) {
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++runNumberCounts[run];
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}
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}
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// create list of bin indices
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unsigned int nRun(0);
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RunNumberMap runNumberIndices;
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for ( RunNumberMap::iterator i=runNumberCounts.begin();
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i!=runNumberCounts.end(); ++i ) {
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if ( (*i).second>100 ) runNumberIndices[(*i).first] = nRun++;
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}
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cout << "Found " << nRun << " run numbers" << endl;
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//
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// create histograms
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//
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TDirectory* saveDir = gDirectory;
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gROOT->cd();
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TH2* pvxVsRun = new TH2F("pvxVsRun","pvxVsRun",nRun,-0.5,nRun-0.5,80,-0.1,0.3);
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TH2* pvyVsRun = new TH2F("pvyVsRun","pvyVsRun",nRun,-0.5,nRun-0.5,80,-0.2,0.2);
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TH2* pvzVsRun = new TH2F("pvzVsRun","pvzVsRun",nRun,-0.5,nRun-0.5,80,-20,20);
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TH2* bsxVsRun = new TH2F("bsxVsRun","bsxVsRun",nRun,-0.5,nRun-0.5,80,0,0.4);
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TH2* bsyVsRun = new TH2F("bsyVsRun","bsyVsRun",nRun,-0.5,nRun-0.5,80,0,0.4);
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TH2* bszVsRun = new TH2F("bszVsRun","bszVsRun",nRun,-0.5,nRun-0.5,80,-20,20);
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| 283 |
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TH1* bsxVsRunMean = new TH1F("bsxVsRunMean","bsxVsRunMean",nRun,-0.5,nRun-0.5);
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TH1* bsyVsRunMean = new TH1F("bsyVsRunMean","bsyVsRunMean",nRun,-0.5,nRun-0.5);
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TH1* bszVsRunMean = new TH1F("bszVsRunMean","bszVsRunMean",nRun,-0.5,nRun-0.5);
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saveDir->cd();
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| 287 |
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| 288 |
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//
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| 289 |
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// fill histograms
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| 290 |
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//
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| 291 |
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lastRun = -1;
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| 292 |
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int idx(-1);
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| 293 |
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int nev(0);
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| 294 |
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for( ev.toBegin(); !ev.atEnd(); ++ev) {
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| 295 |
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int run = ev.id().run();
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| 296 |
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// if ( (++nev)%1000 == 0 ) cout << "processing record " << nev << " ( run "
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| 297 |
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// << ev.id().run() << " " << " evt "
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| 298 |
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// << ev.id().event() << " )" << endl;
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| 299 |
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//
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| 300 |
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// update bin index if run changed
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| 301 |
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//
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| 302 |
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if ( run!=lastRun ) {
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| 303 |
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RunNumberMap::const_iterator irun = runNumberIndices.find(run);
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| 304 |
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if ( irun == runNumberIndices.end() ) {
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| 305 |
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idx = -1;
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| 306 |
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}
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| 307 |
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else {
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| 308 |
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idx = (*irun).second;
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| 309 |
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}
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| 310 |
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lastRun = run;
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| 311 |
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// cout << "Run " << run << " idx " << idx << endl;
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| 312 |
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}
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| 313 |
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if ( idx<0 ) continue;
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| 314 |
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| 315 |
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//
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| 316 |
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// retrieve beam spot and PV
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| 317 |
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//
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| 318 |
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bsHandle.getByLabel(ev,"offlineBeamSpot");
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| 319 |
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pvHandle.getByLabel(ev,"offlinePrimaryVertices");
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| 320 |
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//
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| 321 |
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// fill PV histograms (after quality cut)
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| 322 |
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//
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| 323 |
|
|
const reco::Vertex& pv = (*pvHandle)[0];
|
| 324 |
|
|
if ( pv.tracksSize()>0 && pv.ndof()>2 &&
|
| 325 |
|
|
(pv.ndof()+3.)/2./pv.tracksSize()>0.5 ) {
|
| 326 |
|
|
pvxVsRun->Fill(idx,pv.x());
|
| 327 |
|
|
pvyVsRun->Fill(idx,pv.y());
|
| 328 |
|
|
pvzVsRun->Fill(idx,pv.z());
|
| 329 |
|
|
}
|
| 330 |
|
|
//
|
| 331 |
|
|
// fill BS histograms
|
| 332 |
|
|
//
|
| 333 |
|
|
bsxVsRun->Fill(idx,bsHandle->x0());
|
| 334 |
|
|
bsyVsRun->Fill(idx,bsHandle->y0());
|
| 335 |
|
|
bszVsRun->Fill(idx,bsHandle->z0());
|
| 336 |
|
|
if ( idx>=0 && idx<bsxVsRun->GetNbinsX() ) {
|
| 337 |
|
|
// assume BS is constant / run: fill current value into 1d histogram
|
| 338 |
|
|
bsxVsRunMean->SetBinContent(idx+1,bsHandle->x0());
|
| 339 |
|
|
bsxVsRunMean->SetBinError(idx+1,bsHandle->x0Error());
|
| 340 |
|
|
bsyVsRunMean->SetBinContent(idx+1,bsHandle->y0());
|
| 341 |
|
|
bsyVsRunMean->SetBinError(idx+1,bsHandle->y0Error());
|
| 342 |
|
|
bszVsRunMean->SetBinContent(idx+1,bsHandle->z0());
|
| 343 |
|
|
bszVsRunMean->SetBinError(idx+1,bsHandle->z0Error());
|
| 344 |
|
|
}
|
| 345 |
|
|
|
| 346 |
|
|
}
|
| 347 |
|
|
saveDir = gDirectory;
|
| 348 |
|
|
//
|
| 349 |
|
|
// number of entries / run
|
| 350 |
|
|
//
|
| 351 |
|
|
gROOT->cd();
|
| 352 |
|
|
TH1* npvVsRun = pvzVsRun->ProjectionX("npvVsRun");
|
| 353 |
|
|
npvVsRun->SetTitle("npvVsRun");
|
| 354 |
|
|
TH1* nbsVsRun = bszVsRun->ProjectionX("nbsVsRun");
|
| 355 |
|
|
npvVsRun->SetTitle("nbsVsRun");
|
| 356 |
|
|
saveDir->cd();
|
| 357 |
|
|
//
|
| 358 |
|
|
// set run numbers on x-axis labels
|
| 359 |
|
|
//
|
| 360 |
|
|
setRunNumberLabels(npvVsRun,runNumberIndices);
|
| 361 |
|
|
setRunNumberLabels(pvxVsRun,runNumberIndices);
|
| 362 |
|
|
setRunNumberLabels(pvyVsRun,runNumberIndices);
|
| 363 |
|
|
setRunNumberLabels(pvzVsRun,runNumberIndices);
|
| 364 |
|
|
setRunNumberLabels(nbsVsRun,runNumberIndices);
|
| 365 |
|
|
setRunNumberLabels(bsxVsRun,runNumberIndices);
|
| 366 |
|
|
setRunNumberLabels(bsyVsRun,runNumberIndices);
|
| 367 |
|
|
setRunNumberLabels(bszVsRun,runNumberIndices);
|
| 368 |
|
|
setRunNumberLabels(bsxVsRunMean,runNumberIndices);
|
| 369 |
|
|
setRunNumberLabels(bsyVsRunMean,runNumberIndices);
|
| 370 |
|
|
setRunNumberLabels(bszVsRunMean,runNumberIndices);
|
| 371 |
|
|
//
|
| 372 |
|
|
// fit histograms
|
| 373 |
|
|
//
|
| 374 |
|
|
TH1* pvxMean; TH1* pvxWidth;
|
| 375 |
|
|
fitRunHistogram(pvxVsRun,pvxMean,pvxWidth);
|
| 376 |
|
|
TH1* pvyMean; TH1* pvyWidth;
|
| 377 |
|
|
fitRunHistogram(pvyVsRun,pvyMean,pvyWidth);
|
| 378 |
|
|
TH1* pvzMean; TH1* pvzWidth;
|
| 379 |
|
|
fitRunHistogram(pvzVsRun,pvzMean,pvzWidth);
|
| 380 |
|
|
|
| 381 |
|
|
// cout << pvxMean << endl;
|
| 382 |
|
|
// cout << pvxMean->GetNbinsX() << " " << pvxMean->GetXaxis() << endl;
|
| 383 |
|
|
//
|
| 384 |
|
|
// summary table
|
| 385 |
|
|
//
|
| 386 |
|
|
for ( unsigned int i=1; i<=pvxMean->GetNbinsX(); ++i ) {
|
| 387 |
|
|
if ( pvxMean->GetBinError(i)>1.e-10 ||
|
| 388 |
|
|
pvxMean->GetBinError(i)>1.e-10 ||
|
| 389 |
|
|
pvxMean->GetBinError(i)>1.e-10 ) {
|
| 390 |
|
|
printf(" %-6s : %8.4f +- %6.4f %6.4f +- %6.4f %8.4f +- %6.4f %6.4f +- %6.4f %9.4f +- %7.4f %6.4f +- %7.4f\n",
|
| 391 |
|
|
pvxMean->GetXaxis()->GetBinLabel(i),
|
| 392 |
|
|
pvxMean->GetBinContent(i),pvxMean->GetBinError(i),
|
| 393 |
|
|
pvxWidth->GetBinContent(i),pvxWidth->GetBinError(i),
|
| 394 |
|
|
pvyMean->GetBinContent(i),pvyMean->GetBinError(i),
|
| 395 |
|
|
pvyWidth->GetBinContent(i),pvyWidth->GetBinError(i),
|
| 396 |
|
|
pvzMean->GetBinContent(i),pvzMean->GetBinError(i),
|
| 397 |
|
|
pvzWidth->GetBinContent(i),pvzWidth->GetBinError(i));
|
| 398 |
|
|
}
|
| 399 |
|
|
}
|
| 400 |
|
|
|
| 401 |
|
|
//
|
| 402 |
|
|
// save histograms
|
| 403 |
|
|
//
|
| 404 |
|
|
TFile* fo = new TFile("../skim_BSC0_AND_40OR41_MinBias_Dec19th_v1.root","recreate");
|
| 405 |
|
|
pvxVsRun->Write();
|
| 406 |
|
|
pvyVsRun->Write();
|
| 407 |
|
|
pvzVsRun->Write();
|
| 408 |
|
|
pvxMean->Write();
|
| 409 |
|
|
pvxWidth->Write();
|
| 410 |
|
|
pvyMean->Write();
|
| 411 |
|
|
pvyWidth->Write();
|
| 412 |
|
|
pvzMean->Write();
|
| 413 |
|
|
pvzWidth->Write();
|
| 414 |
|
|
fo->Write();
|
| 415 |
|
|
delete fo;
|
| 416 |
|
|
|
| 417 |
|
|
plotPvVsBs();
|
| 418 |
|
|
//
|
| 419 |
|
|
// plot inidividual histograms / run
|
| 420 |
|
|
//
|
| 421 |
|
|
// for ( RunNumberMap::iterator i=runNumberIndices.begin();
|
| 422 |
|
|
// i!=runNumberIndices.end(); ++i ) {
|
| 423 |
|
|
// plotRun('x',(*i).first);
|
| 424 |
|
|
// plotRun('y',(*i).first);
|
| 425 |
|
|
// plotRun('z',(*i).first);
|
| 426 |
|
|
// }
|
| 427 |
|
|
|
| 428 |
|
|
}
|
| 429 |
|
|
//
|
| 430 |
|
|
// call with single file name
|
| 431 |
|
|
//
|
| 432 |
|
|
void pvHistory (const char* fileName) {
|
| 433 |
|
|
vector<string> fileNames(1,fileName);
|
| 434 |
|
|
pvHistory(fileNames);
|
| 435 |
|
|
}
|
