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421 lines
16 KiB
421 lines
16 KiB
//Renata Kopecna
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#include <backgroundfit.hh>
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#include <fstream>
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#include <sstream> // std::istringstream
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#include <bu2kstarmumu_parameters.hh>
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#include <bu2kstarmumu_plotter.hh>
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#include <bu2kstarmumu_pdf.hh>
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#include <folder.hh>
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#include <fitter.hh>
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#include <paths.hh>
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#include <design.hh>
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#include <helpers.hh>
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#include <event.hh>
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#include <spdlog.h>
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#include <TStyle.h>
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#include <TH2D.h>
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#include <TLatex.h>
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#include <TCanvas.h>
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#include <TROOT.h>
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//Do the actuall background fit
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int backgroundfit(fcnc::options opts,
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bool fitReference, bool LowMassFit, bool HighMassFit, bool fitKpi,
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bool Use2DAngularBins, basic_params params){
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//params now only used to tag nBins in the names
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//Technically, this should be simFit between Run 1 and 2, but since we need it only for the toys atm, no need for it
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gROOT->SetBatch(kTRUE);
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gROOT->SetStyle("Plain");
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set_gStyle();
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//Open texFile
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std::ofstream myFile;
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open_Latex_noteFile(latex_bkgFit(), myFile);
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spdlog::info("[FIT]\t\tFit only angular and m(Kpi) background");
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//Used to check whether the background is "correlated" between each other
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//TODO: not needed atm, maybe fix later
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/* 1D angular bins
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1: ctl < -0.5
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2: -0.5 < ctl < 0.0
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3: 0.0 < ctl < 0.5
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4: 0.5 < ctl
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5: ctk < -0.5
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6: -0.5 < ctk < 0.0
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7: 0.0 < ctk < 0.5
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8: 0.5 < ctk
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*/
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/* 2D angular bins
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1: ctl < 0.0 && ctk < 0.0
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2: ctl < 0.0 && ctk > 0.0
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3: ctl > 0.0 && ctk < 0.0
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4: ctl > 0.0 && ctk > 0.0
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*/
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double HighBpeakCut = fitReference ? B_MASS_HIGH_BKG_REF : B_MASS_HIGH_BKG;
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double LowBpeakCut = fitReference ? B_MASS_LOW_BKG_REF : B_MASS_LOW_BKG;
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assert(!(HighMassFit && LowMassFit));
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opts.fit_full_angular_bkg = true;
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opts.only_angles = !(HighMassFit || LowMassFit); //Fit mass only if one sideband is selected
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opts.only_Bmass = false;
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opts.only_mkpi = false;
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opts.swave = false;
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opts.bkg_order_costhetak = 5;
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opts.shift_lh = false; //keep it, it was there before
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opts.weighted_fit = true;
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opts.squared_hesse = true;
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opts.minos_errors = false;
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opts.asymptotic = false;
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opts.flat_bkg = false;
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opts.fit_mkpi = false; //set to true only later
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opts.use_mkpi = false;
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opts.simple_mkpi = false; //S-wave model
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opts.isobar = false; //S-wave model
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//Plotting options
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opts.plot_chi2 = false;
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opts.plots_m_bins = 20;
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opts.plots_mkpi_bins = 20;
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//load events from data tuple
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std::vector<std::vector<fcnc::event>>events;
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std::vector<int> run_idx;
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if (opts.run == 1 || opts.run == 12){
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std::vector<fcnc::event> tmp = fcnc::load_events(get_theFCNCpath(0,1), "Events", -1);
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if (!fitReference) events.push_back(fcnc::filterResonances(tmp));
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else events.push_back(tmp);
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run_idx.push_back(1);
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}
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if (opts.run == 2 || opts.run == 12){
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std::vector<fcnc::event> tmp = fcnc::load_events(get_theFCNCpath(0,2), "Events", -1);
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if (!fitReference) events.push_back(fcnc::filterResonances(tmp));
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else events.push_back(tmp);
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run_idx.push_back(2);
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}
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std::vector<int> fitresults;
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//determine number of bins:
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const UInt_t nBins = opts.TheQ2binsmin.size();
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//current fitter, plotter, parameteres and pdfs:
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fcnc::fitter f(&opts);
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fcnc::folder fldr(&opts);
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fcnc::bu2kstarmumu_plotter thePlotter(&opts);
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fcnc::bu2kstarmumu_parameters * theParams[nBins];
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fcnc::bu2kstarmumu_pdf * theProb[nBins];
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std::vector<fcnc::event> * theEvents[nBins];
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for(UInt_t b = 0; b < nBins; b++){
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theParams[b] = new fcnc::bu2kstarmumu_parameters(&opts);
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theProb[b] = new fcnc::bu2kstarmumu_pdf(&opts, theParams[b]);
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theEvents[b] = new std::vector<fcnc::event>();
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//Init parameters
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theParams[b]->f_sig.init_fixed(0.0);
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theParams[b]->m_b.init(PDGMASS_B, HighMassFit ? HighBpeakCut : B_MASS_LOW, LowMassFit ? LowBpeakCut : B_MASS_HIGH, 0.0);
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//The rest of the mass parameters can be left to default values
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//They are defined in bu2kstamumu_parameters
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//Init the bkg shape
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theParams[b]->init_angular_background_parameters(fitReference,0.1);
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//Init the mass bkg shape
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theParams[b]->init_mass_background_parameters(nBins,b,true);
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//theParams[b]->cbkgctk3.init_fixed(-2.5);
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//Select events
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for_indexed(auto evts: events){
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//update weights according to sub-set for all events
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opts.run = run_idx.at(i);
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opts.update_efficiencies = true;
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theProb[b]->load_coeffs_eff_phsp_4d();
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theProb[b]->update_cached_normalization(theParams[b]);
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theProb[b]->update_cached_efficiencies(theParams[b], &evts);
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opts.update_angle_ranges(); //Update angles to get rid of events that cannot be folded
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//select events
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spdlog::debug("Loop over {0:d} events and select the suitable ones", evts.size());
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for(auto meas: evts){
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if(meas.q2 < opts.TheQ2binsmin.at(b) || meas.q2 > opts.TheQ2binsmax.at(b)) continue;
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if(meas.m < opts.m_low || meas.m > opts.m_high) continue;
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if(LowMassFit && meas.m > LowBpeakCut) continue;
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else if(HighMassFit && meas.m < HighBpeakCut) continue;
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else if(meas.m > LowBpeakCut && meas.m < HighBpeakCut) continue;
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if(meas.mkpi < opts.mkpi_min || meas.mkpi > opts.mkpi_max) continue;
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if(params.bin > 1){
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bool keep_event = true;
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if(Use2DAngularBins){
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switch(params.bin){
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case 2:
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if(meas.costhetal > 0.0 || meas.costhetak > 0.0) keep_event = false;
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break;
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case 3:
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if(meas.costhetal > 0.0 || meas.costhetak < 0.0) keep_event = false;
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break;
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case 4:
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if(meas.costhetal < 0.0 || meas.costhetak > 0.0) keep_event = false;
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break;
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case 5:
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if(meas.costhetal < 0.0 || meas.costhetak < 0.0) keep_event = false;
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break;
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}
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}
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else{ //1D angular bins
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switch(params.bin){
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case 2:
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if(meas.costhetal > -0.5) keep_event = false;
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break;
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case 3:
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if(meas.costhetal < -0.5 || meas.costhetal > 0.0) keep_event = false;;
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break;
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case 4:
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if(meas.costhetal < 0.0 || meas.costhetal > 0.5) keep_event = false;;
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break;
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case 5:
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if(meas.costhetal > 0.5) keep_event = false;;
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break;
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case 6:
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if(meas.costhetak > -0.5) keep_event = false;;
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break;
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case 7:
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if(meas.costhetak < -0.5 || meas.costhetak > 0.0) keep_event = false;;
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break;
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case 8:
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if(meas.costhetak < 0.0 || meas.costhetak > 0.5) keep_event = false;;
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break;
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case 9:
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if(meas.costhetak > 0.5) keep_event = false;;
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break;
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}
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}
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if(!keep_event) continue;
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}
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if(!filterFldFour(&meas, &opts)) continue;
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fldr.fold(&meas);
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//only one combined event vector
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theEvents[b]->push_back(meas);
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}
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spdlog::debug("Selected {0:d} events.", theEvents[b]->size());
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}
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spdlog::info("[BIN {0:d}]\tDone!",b);
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}//end loop over bins
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//do not update cached efficiencies anyomre, to keep individual ones for four sub-sets
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opts.update_efficiencies = false;
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//create 2D correlation plots for all angles (3) and all bins (8): 3! * 8 = 24
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const unsigned int nANGLES = 3;
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double hmin[nANGLES] = {CTL_MIN, CTK_MIN, PHI_MIN};
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double hmax[nANGLES] = {CTL_MAX, CTK_MAX, PHI_MAX};
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double corrfactor[nBins][nANGLES][nANGLES];
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const int nCorrBins = 10;
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for(UInt_t b = 0; b < nBins; b++){
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spdlog::info("[START]\tStart the background 2D correlation plotting for bin #{0:d}", b);
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for(UInt_t a = 0; a < nANGLES - 1; a++){
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for(UInt_t aa = a + 1; aa < nANGLES; aa++){
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std::string mainName = "bckgnd_correl_"+ANGLES[a]+"_"+ANGLES[aa]+"_q2bin"+std::to_string(b);
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TCanvas * cAngCorr = new TCanvas(("c"+mainName).c_str(),
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("c"+mainName).c_str(), 1400, 1200);
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cAngCorr->cd()->SetMargin(0.1,0.125,0.125,0.125);
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cAngCorr->cd();
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TH2D * h = new TH2D((mainName).c_str(),
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(mainName+";"+latex_angles[a]+";"+latex_angles[aa]).c_str(),
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nCorrBins, hmin[a], hmax[a], nCorrBins, hmin[aa], hmax[aa]);
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for(UInt_t e = 0; e < theEvents[b]->size(); e++){
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fcnc::event meas = theEvents[b]->at(e);
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double x=0.0, y=0.0;
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switch(a){ //TODO: make a function in helpers
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case 0:
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x = meas.costhetal;
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break;
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case 1:
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x = meas.costhetak;
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break;
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}
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switch(aa){
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case 1:
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y = meas.costhetak;
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break;
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case 2:
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y = meas.phi;
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break;
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}
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h->Fill(x, y);
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}
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h->GetZaxis()->SetRangeUser(0, fitReference ? 25 : 5);
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h->GetZaxis()->SetTitle("Number of entries");
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h->GetXaxis()->SetTitleSize(0.05);
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h->GetXaxis()->SetLabelSize(0.05);
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h->GetXaxis()->SetTitleOffset(0.95);
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h->GetYaxis()->SetTitleSize(0.05);
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h->GetYaxis()->SetLabelSize(0.05);
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h->GetYaxis()->SetTitleOffset(0.75);
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h->GetZaxis()->SetTitleSize(0.05);
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h->GetZaxis()->SetLabelSize(0.05);
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h->GetZaxis()->SetTitleOffset(0.75);
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h->SetTitle("");
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h->Draw("COLZ");
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corrfactor[b][a][aa] = h->GetCorrelationFactor();
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TLatex * leg = getPrettyTex(0.06,13);
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leg->SetTextColor(kBlack);
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std::ostringstream sCorrout; //TODO: move the path
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sCorrout << std::fixed << std::setprecision(2) << "corr(" << latex_angles[a] << ", " << latex_angles[aa] <<") = " << corrfactor[b][a][aa]*100. << "\%";
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leg->DrawLatex(0.22,0.98, sCorrout.str().c_str());
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leg->SetTextSize(0.04);
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leg->DrawLatex(0.25,0.92, ("Events: "+std::to_string((int) h->GetEntries())).c_str());
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cAngCorr->Print(get_bkgCorrPlot_path(ANGLES[a],ANGLES[aa],b,nBins,fitReference, LowMassFit, HighMassFit, fitKpi, params).c_str(), "eps");
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}
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}
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//Save the correlations s
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myFile << "\\begin{tabular}{r|ccc}\\hline" << std::endl;
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myFile << std::fixed << std::setprecision(2) << "[" << opts.TheQ2binsmin.at(b) << ", " << opts.TheQ2binsmax.at(b) << "]";
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for(UInt_t a = 0; a < nANGLES; a++) myFile << "\t&" << latex_2angles[a];
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myFile << "\\\\" << std::endl;
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myFile << "\\hline\\hline" << std::endl;
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for(UInt_t a = 0; a < nANGLES; a++){
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myFile << latex_2angles[a];
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for(UInt_t aa = 0; aa < nANGLES; aa++){
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myFile << "\t&";
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if(aa > a) myFile << std::setprecision(3) << std::fixed << corrfactor[b][a][aa];
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else if(aa == a) myFile << "1.00";
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else if(aa < a) myFile << " ";
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}
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myFile << "\\\\" << std::endl;
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}
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myFile << "\\hline" << std::endl;
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myFile << "\\end{tabular}"<< std::endl;
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myFile << std::endl;
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}
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//FIT ANGULAR BACKGROUND + B mass
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opts.update_angle_ranges(); //Just in case
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//fit all bins:
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for(UInt_t b = 0; b < nBins; b++){
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spdlog::info("[START]\tStart the fit for bin #{0:d}", b);
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//fit the events:
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int fitresult = f.fit(theProb[b], theParams[b], theEvents[b]);
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fitresults.push_back(fitresult);
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spdlog::info("[BIN{0:d}]:\tFitresult: {1:d}", b, fitresult);
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//plot pdf with the data points:
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opts.plot_label = "LHCb data";
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opts.q2_label = q2_label(opts.TheQ2binsmin.at(b), opts.TheQ2binsmax.at(b));
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if(opts.write_eps){
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std::string label = get_bkg_tag(b,nBins,fitReference, LowMassFit, HighMassFit, false, params);
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spdlog::info("[PLOT]\t" + label);
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thePlotter.plot_data(theProb[b], theParams[b], theEvents[b], get_bkgFitPlot_path(), label, false);
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}
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//print all parameters
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std::string fitResultTxt = get_bkgFitResult_path()+ "fitresult_" + get_bkg_tag(b,nBins,fitReference, LowMassFit, HighMassFit, false, params);
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spdlog::debug("Saving into "+fitResultTxt);
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print_all_parameters(nBins, theParams, 2, fitResultTxt);
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}
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//print all fitresults
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print_fit_results(nBins, fitresults);
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//Save results to root file
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std::string results_file = final_result_name_bkg(nBins, fitReference, LowMassFit, HighMassFit, false, params);
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save_results(results_file, nBins, params.Run, fitresults, theParams, &opts);
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//FIT M(KPI) BACKGROUND
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if (!fitKpi){ //first check if you really want to fit M(KPI) :)
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//Close Latex file
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myFile.close();
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return 0;
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}
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//Reset the options
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opts.only_angles = false;
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opts.only_mkpi = true;
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opts.fit_mkpi = true;
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//fit all bins:
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spdlog::info("[BKGFIT]\tFit the Kpi mass");
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for(UInt_t b = 0; b < nBins; b++){
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theParams[b]->use_default_bkg();
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//null the lambda(s) and taus
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theParams[b]->m_lambda.init_fixed(0.0);
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theParams[b]->m_lambda_2.init_fixed(0.0);
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theParams[b]->m_tau.init_fixed(0.0);
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theParams[b]->m_tau_2.init_fixed(0.0);
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//Init the floating parameters
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theParams[b]->init_kpi_background_parameters(fitReference,0.01);
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spdlog::info("[START]\tStart the fit for bin #{0:d}", b);
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//fit the events:
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fitresults.push_back(f.fit(theProb[b], theParams[b], theEvents[b]));
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spdlog::info("[BIN{0:d} ]:\tFitresult: {1:d}",b, fitresults.at(b));
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//plot pdf with the data points:
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opts.q2_label = q2_label(opts.TheQ2binsmin.at(b), opts.TheQ2binsmax.at(b));
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if(opts.write_eps){
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std::string label = get_bkg_tag(b,nBins,fitReference, LowMassFit, HighMassFit, false, params);
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spdlog::info("[PLOT]\t" + label);
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thePlotter.plot_data(theProb[b], theParams[b], theEvents[b], get_bkgFitPlot_path(), label, false);
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}
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//Print all parameters, but don't save
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print_all_parameters(nBins, theParams, 2, "");
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//print all parameters to txt file
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std::string fitResultTxt = get_bkgFitResult_path()+ "fitresult_" + get_bkg_tag(b,nBins,fitReference, LowMassFit, HighMassFit, true, params);
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spdlog::debug("Saving into "+fitResultTxt);
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print_all_parameters(nBins, theParams, 2, fitResultTxt);
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}
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spdlog::info("[BKGFIT]\tDone with Kpi fit.");
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//Save results to root file
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results_file = final_result_name_bkg(nBins, fitReference, LowMassFit, HighMassFit, true, params);
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save_results(results_file, nBins, params.Run, fitresults, theParams, &opts);
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//Close Latex file
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myFile.close();
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spdlog::info("[BKGFIT]\tFinished.");
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return 0;
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}
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