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oldMCSAnalysis.cpp
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#include "MCSAnalysis.h"
#include "TRint.h"
#include "TROOT.h"
#include "TVirtualFFT.h"
MCSAnalysis::MCSAnalysis(std::string tree, std::string mctree, std::string reftree, std::string outname, std::map<std::string, double> histlimits)
//: p_vec(TVectorD(19)), res(TVectorD(30)), pStart_vec(TVectorD(19)),
// pStart_vec_y(TVectorD(19)), theta_true_x(TVectorD(19)), theta_true_y(TVectorD(19))
{
chain = new TChain(tree.c_str());
refchain = new TChain(reftree.c_str());
mcchain = new TChain(mctree.c_str());
mcemptychain = new TChain(mctree.c_str());
outfile = new TFile(outname.c_str(), "recreate");
_sys["alXUS"] = 0.0; //-0.0356;
_sys["alYUS"] = 0.0; //1.13;
_sys["alXDS"] = 0.0; //-0.126;
_sys["alYDS"] = 0.0; //0.118;
_sys["thXUS"] = 0.0; //-0.0031;
_sys["thYUS"] = 0.0; //-0.005;
_sys["thXDS"] = 0.0; //-0.003;
_sys["thYDS"] = 0.0; //-0.0151;
_sys["resX"] = 1.0;
_sys["resY"] = 1.0;
_sys["psel_lcut"] = -1.;
_sys["psel_ucut"] = -1.;
_sys["TOF0_z"] = 5287.24720607;
_sys["TOF1_z"] = 12929.2608098;
_sys["TOF2_z"] = 21138.306769;
_sys["USref"] = 15062;
_sys["DSref"] = 18849;
_sys["niter"] = 10;
_sys["abspos"] = 16952.5;
_sys["diffpos"] = 13620;
_sys["Nevents"] = -1.;
_sys["FracEvents"] = 1.;
isEmpty=false;
modelname2 = "Cobb";
modelname1 = "GEANT";
modelname3 = "Moliere";
_histlimits["NbinsXY"] = histlimits.count("NbinsXY") != 0 ? histlimits["NbinsXY"]: 200;
_histlimits["minXY"] = histlimits.count("minXY") != 0 ? histlimits["minXY"]: -0.2;
_histlimits["maxXY"] = histlimits.count("maxXY") != 0 ? histlimits["maxXY"]: 0.2;
_histlimits["NbinsTh"] = histlimits.count("NbinsTh") != 0 ? histlimits["NbinsTh"]: 100;
_histlimits["minTh"] = histlimits.count("minTh") != 0 ? histlimits["minTh"]: 0.0;
_histlimits["maxTh"] = histlimits.count("maxTh") != 0 ? histlimits["maxTh"]: 0.2;
_histlimits["NbinsTh2"] = histlimits.count("NbinsTh2") != 0 ? histlimits["NbinsTh2"]: 400;
_histlimits["minTh2"] = histlimits.count("minTh2") != 0 ? histlimits["minTh2"]: 0.0;
_histlimits["maxTh2"] = histlimits.count("maxTh2") != 0 ? histlimits["maxTh2"]: 0.004;
resp_thetaX.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
resp_thetaY.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
resp_thetaScatt.Setup(_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
resp_theta2Scatt.Setup(_histlimits["NbinsTh2"], _histlimits["minTh2"], _histlimits["maxTh2"]);
tresp_thetaX.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
tresp_thetaY.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
tresp_thetaScatt.Setup(_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
tresp_theta2Scatt.Setup(_histlimits["NbinsTh2"], _histlimits["minTh2"], _histlimits["maxTh2"]);
mresp_thetaX.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
mresp_thetaY.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
mresp_thetaScatt.Setup(_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
mresp_theta2Scatt.Setup(_histlimits["NbinsTh2"], _histlimits["minTh2"], _histlimits["maxTh2"]);
fresp_thetaX.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
fresp_thetaY.Setup(_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
fresp_thetaScatt.Setup(_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
fresp_theta2Scatt.Setup(_histlimits["NbinsTh2"], _histlimits["minTh2"], _histlimits["maxTh2"]);
const int NBINS = 19;
const int NPBINS = 30;
double scat_bin_array[NBINS+1] =
{-0.1151, -0.0938, -0.0754, -0.0597, -0.0463,
-0.0347, -0.0248, -0.0162, -0.00895, -0.00269,
0.00269, 0.00895, 0.0162, 0.0248, 0.0347,
0.0463, 0.0597, 0.0754, 0.0938, 0.1151};
double pos_array[NPBINS+1];
for(int i=0; i<NPBINS+1; i++) pos_array[i] = -100 + (6.67 * i);
runnumber = 0;
LastRunNumber = 0;
tofevent = new MAUS::TOFEvent();
scifievent = new MAUS::SciFiEvent();
klevent = new MAUS::KLEvent();
ckovevent = new MAUS::CkovEvent();
emrevent = new MAUS::EMREvent();
mcevent = new MAUS::MCEvent();
primary = new MAUS::Primary();
sphitarray = new MAUS::SpecialVirtualHitArray();
// set some default values that may be adjusted later.
TOF_lower_limit = 27;
TOF_upper_limit = 28;
meanp = 300.0;
sigmap = 0.035;
binlimit = 22;
int counter = 0;
double semom = 0;
double rmsmom = 0;
double errrmsmom = 0;
double bwmom = 0;
// histograms of selection variables
chi2pern = new TH1D("chi2n","chi2n", 40, 0, 10);
diffradius = new TH1D("diffradius","diffradius", 500, 0, 500);
projradius = new TH1D("projradius","projradius", 500, 0, 500);
trackno = new TH2D("trackno","trackno",5,0,4,5,0,4);
eventnovspz = new TH2D("eventnovspz","eventnovspz",50,150,250,60000,0,59999);
tofhitno = new TH2D("tofhitno","tofhitno",5,0,4,5,0,4);
pathlengthabs = new TH1D("pathlengthabs","pathlengthabs", 500, 0, 500);
t_cor = new TH2D("t_cor","t_cor", 1000, 0, 1000,100, 8.05, 9.15);
TOF0Energy = new TH1D("TOF0Energy","TOF0Energy", 200, 150, 350);
TOF1Energy = new TH1D("TOF1Energy","TOF1Energy", 200, 150, 350);
TOF2Energy = new TH1D("TOF2Energy","TOF2Energy", 200, 150, 350);
difEloss = new TH1D("difEloss","difEloss", 10, 0, 10);
energylossproj = new TH1D("energylossproj","energylossproj", 40, 5000, 24000);
//energylosspro = new TH1D("energylosspro","energylosspro", 40, 5000, 24000);
residual01 = new TH1D("residual01","residual01", 36, -50, 100);
residual12 = new TH1D("residual12","residual12", 36, -50, 100);
residual12p6 = new TH1D("residual12","residual12", 36, -50, 100);
residual01j = new TH1D("residual12","residual01", 36, -50, 100);
residual12p2 = new TH1D("residual12","residual12", 36, -50, 100);
residual01p6 = new TH1D("residual12","residual12", 36, -50, 100);
residual01short = new TH1D("residual01short","residual01short", 36, -50, 100);
residualcobb = new TH1D("residualcobb","residualcobb", 36, -50, 100);
pzdEdx = new TH2D("pzdEdx","pzdEdz", 100, 1, 100,250, -500, 500);
TOFcom = new TH2D("TOF01 vs TOF12","TOF01 vs TOF12", 33, 100, 350,33, 100, 350);
energyloss = new TH2D("energyloss","energyloss", 40, 5000, 24000,350, 100, 450);
TOF01vsMCTruth = new TH2D("TOF01vsMCTruth","TOF01vsMCTruth", 33, 100, 350,33, 100, 350);
TOF12vsMCTruth = new TH2D("TOF12vsMCTruth","TOF12vsMCTruth", 33, 100, 350,33, 100, 350);
TOF12Paul6thforvsMCTruth = new TH2D("TOF12forupvsMCTruth","TOF12forupvsMCTruth", 33, 100, 350, 33, 100, 350);
TOF12longPaul6thforvsMCTruth = new TH2D("TOF12longforupvsMCTruth","TOF12longforupvsMCTruth", 33, 100, 350, 33, 100, 350);
TOF12Paul2ndforvsMCTruth = new TH2D("TOF01forupvsMCTruth","TOF01forupvsMCTruth", 33, 100, 350, 33, 100, 350);
TOF01Paul6thforvsMCTruth = new TH2D("TOF01forupvsMCTruth","TOF01forupvsMCTruth", 33, 100, 350, 33, 100, 350);
TOF01shortPaul6thforvsMCTruth = new TH2D("TOF01shortforupvsMCTruth","TOF01shortforupvsMCTruth", 33, 100, 350, 33, 100, 350);
TOF01fordownvsMCTruth = new TH2D("TOF01fordownvsMCTruth","TOF01fordownvsMCTruth", 33, 100, 350,33, 100, 350);
TOF12fordownvsMCTruth = new TH2D("TOF12fordownvsMCTruth","TOF12fordownvsMCTruth", 33, 100, 350,33, 100, 350);
TOF12cobbvsMCTruth = new TH2D("TOF12cobbvsMCTruth","TOF12cobbvsMCTruth", 33, 100, 350,33, 100, 350);
TOF01forupvsTOF01fordown = new TH2D("TOF01forupvsTOF01fordown","TOF01forupvsTOF01fordown", 33, 100, 350,33, 100, 350);
tof10 = new TH1D("tof10","TOF Between Stations 1 and 0; t_{TOF1} - t_{TOF0} (ns)", 150, 10, 40);
tof10_sel = new TH1D("tof10_sel","TOF Selection Between Stations 1 and 0; t_{TOF1} - t_{TOF0} (ns)", 150, 10, 40);
tof21 = new TH1D("tof21","TOF Between Stations 2 and 1; t_{TOF2} - t_{TOF1} (ns)", 150, 0, 50);
tof21_sel = new TH1D("tof21_sel","TOF Selection Between Stations 2 and 1; t_{TOF2} - t_{TOF1} (ns)", 150, 0, 50);
mctof10 = new TH1D("mctof10","TOF Between Stations 1 and 0; t_{TOF1} - t_{TOF0} (ns)", 150, 10, 40);
mctof10_sel = new TH1D("mctof10_sel","TOF Selection Between Stations 1 and 0; t_{TOF1} - t_{TOF0} (ns)", 150, 10, 40);
mctof21 = new TH1D("mctof21","TOF Between Stations 2 and 1; t_{TOF2} - t_{TOF1} (ns)", 150, 0, 50);
mctof21_sel = new TH1D("mctof21_sel","TOF Selection Between Stations 2 and 1; t_{TOF2} - t_{TOF1} (ns)", 150, 0, 50);
calc_mom = new TH1D("calc_mom","Momentum Calculated from TOF; Momentum (MeV/c)", 100, 0, 400);
cor_mom = new TH1D("cor_mom","Cor Momentum Calculated from TOF; Momentum (MeV/c)", 180, 120, 300);
mccalc_mom = new TH1D("mccalc_mom","Momentum Calculated from TOF; Momentum (MeV/c)", 130, 120, 250);
mctrue_mom = new TH1D("mctrue_mom","Momentum from Virtual Planes; Momentum (MeV/c)", 400, 0, 400);
cuts_accept = new TH1D("cuts_accept",
";Selection Criteria; Surviving Events", 6, 0, 6);
mccuts_accept = new TH1D("mccuts_accept",
";Selection Criteria; Surviving Events", 6, 0, 6);
scattering_pos_x =
new TH1D("scattering_pos_x",
"Change in Position (X);#Delta X; Events per mm",
NBINS, scat_bin_array);
scattering_pos_y =
new TH1D("scattering_pos_y",
"Change in Position (Y);#Delta Y; Events per mm",
NBINS, scat_bin_array);
theta_true_x_graph =
new TH1D("thetaX_graph","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
theta_true_y_graph =
new TH1D("thetaY_graph","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
minustheta_true_x_graph =
new TH1D("minusthetaX_graph","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
minustheta_true_y_graph =
new TH1D("minusthetaY_graph","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
theta_true_scat_graph =
new TH1D("theta_true_scat_graph","Scattering Angle between Momentum Vectors;#theta_{Scatt}; Events per mrad",
_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
mctheta_true_x_graph =
new TH1D("thetaX_graphmc","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
mctheta_true_y_graph =
new TH1D("thetaY_graphmc","Change in Projected Angle (X);#Delta#theta_{X}; Events",_histlimits["NbinsXY"], _histlimits["minXY"], _histlimits["maxXY"]);
mctheta_true_scat_graph =
new TH1D("theta_true_scat_graphmc","Scattering Angle between Momentum Vectors;#theta_{Scatt}; Events per mrad",
_histlimits["NbinsTh"], _histlimits["minTh"], _histlimits["maxTh"]);
scattering_proj_x_resp =
new TH2D("scattering_proj_x_resp",
"Change in Projected Angle (X);#Delta#theta^{Measured}_{X}; #Delta#theta^{True}_{X}",
NBINS, scat_bin_array, NBINS, scat_bin_array);
scattering_proj_y_resp =
new TH2D("scattering_proj_y_resp",
"Change in Projected Angle (Y);#Delta#theta^{Measured}_{Y}; #Delta#theta^{True}_{Y}",
NBINS, scat_bin_array, NBINS, scat_bin_array);
scattering_proj_x_R =
new TH2D("scattering_proj_x_R",
"Change in Projected Angle (X);#Delta#theta^{Measured}_{X}; #Delta#theta^{True}_{Y}",
NPBINS, pos_array, NBINS, scat_bin_array);
scattering_proj_y_R =
new TH2D("scattering_proj_y_R",
"Change in Projected Angle (Y);#Delta#theta^{Measured}_{Y}; #Delta#theta^{True}_{X}",
NPBINS, pos_array, NBINS, scat_bin_array);
theta_meas_x_graph =
new TH1D("theta_meas_x_graph","Accepted Events;#Delta#theta^{True}_X",
NBINS, scat_bin_array);
theta_meas_y_graph =
new TH1D("theta_meas_y_graph","Accepted Events;#Delta#theta^{True}_Y",
NBINS, scat_bin_array);
jUS=-1;
jDS=-1;
kUS=-1;
kDS=-1;
lUS=-1;
lDS=-1;
USrefplaneI = -1;
DSrefplaneI = -1;
USrefplaneZ = 0.;
DSrefplaneZ = 0.;
USabsPlaneI = -1;
DSabsPlaneI = -1;
centre = 0;
}
MCSAnalysis::~MCSAnalysis(){
delete chain;
delete refchain;
delete mcchain;
// delete tof10;
// delete tof21;
// delete tof10_sel;
// delete tof21_sel;
// delete calc_mom;
}
void MCSAnalysis::Write(){
TText t1 = TText(0.12,0.785,"MICE Preliminary");
TText t3 = TText(0.12,0.75,"ISIS cycle 2015/04");
TText t2 = TText(0.12,0.715,"LiH, MAUS v3.1.2");
t1.SetNDC(1);
t1.SetTextSize(0.04);
t1.SetTextFont(42);
t2.SetNDC(1);
t2.SetTextSize(0.03);
t2.SetTextFont(42);
t3.SetNDC(1);
t3.SetTextSize(0.04);
t3.SetTextFont(42);
outfile->cd();
theta_true_scat_graph->Write();
tof10->Write();
tof21->Write();
tof10_sel->Write();
tof21_sel->Write();
calc_mom->Write();
mctof10->Write();
mctof21->Write();
mctof10_sel->Write();
mctof21_sel->Write();
mccalc_mom->Write();
mctrue_mom->Write();
cuts_accept->Write();
mccuts_accept->Write();
trackno->Write();
tofhitno->Write();
diffradius->Write();
projradius->Write();
TCanvas *c1 = new TCanvas();
//calc_mom->GetXaxis()->SetRangeUser(120,280);
//calc_mom->Draw();
cor_mom->SetLineColor(2);
cor_mom->Draw();
semom = cor_mom->GetMeanError();
rmsmom = cor_mom->GetRMS();
errrmsmom = cor_mom->GetRMSError();
cor_mom->Fit("gaus", "N");
c1->SaveAs("calc_mom.pdf");
c1->SaveAs("calc_mom.root");
cor_mom->Write();
c1->Clear();
calc_mom->GetXaxis()->SetRangeUser(120,280);
cor_mom->Draw();
c1->SaveAs("cor_mom.pdf");
c1->Clear();
TOFcom->GetXaxis()->SetTitle("pz analytic formula");
TOFcom->GetYaxis()->SetTitle("pz Bethe-Bloch");
TOFcom->Draw("colz");
TLine *line2 = new TLine(100,100,350,350);
line2->SetLineColor(kRed);
line2->Draw();
c1->SaveAs("TOFcom.pdf");
c1->Clear();
TOF01vsMCTruth->GetXaxis()->SetTitle("pz TOF01");
TOF01vsMCTruth->GetYaxis()->SetTitle("MCTruth");
TOF01vsMCTruth->Draw("colz");
TLine *line3 = new TLine(100,100,350,350);
line3->SetLineColor(kRed);
line3->Draw();
c1->SaveAs("TOF01vsMCTruth.pdf");
c1->Clear();
TOF12vsMCTruth->GetXaxis()->SetTitle("pz TOF12");
TOF12vsMCTruth->GetYaxis()->SetTitle("MCTruth");
TOF12vsMCTruth->Draw("colz");
float col1 = 0.2082*0.9;
float col2 = 0.1664*0.9;
float col3 = 0.5293*0.9;
double fillcolour = TColor::GetColor(col1, col2, col3);
c1->GetFrame()->SetFillColor(fillcolour);
c1->SetFrameFillColor(fillcolour);
TLine *line4 = new TLine(100,100,350,350);
line4->SetLineColor(kRed);
line4->Draw();
c1->SaveAs("TOF12vsMCTruth.pdf");
c1->Clear();
c1->SetFrameFillColor(0);
energyloss->GetXaxis()->SetTitle("position (mm)");
energyloss->GetYaxis()->SetTitle("MCTruth energy (MeV)");
energyloss->Draw("colz");
c1->SaveAs("energyloss.pdf");
c1->Clear();
energylossproj=energyloss->ProjectionX();
energylossproj->SetTitle("position (mm)");
energylossproj->Draw();
c1->SaveAs("energylossproj.pdf");
c1->Clear();
energylosspro=energyloss->ProfileX();
//energylosspro->SetTitle("position (mm)");
energylosspro->Draw();
c1->SaveAs("energylosspro.pdf");
c1->Clear();
gStyle->SetOptStat(0);
TOF12Paul6thforvsMCTruth->SetTitle("Corrected P downstream vs MC Truth");
TOF12Paul6thforvsMCTruth->GetXaxis()->SetTitle("pz TOF12");
TOF12Paul6thforvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF12Paul6thforvsMCTruth->Draw("colz");
t1.Draw();
t3.Draw();
t2.Draw();
TLine *line5 = new TLine(100,100,350,350);
line5->SetLineColor(kRed);
line5->Draw();
c1->SaveAs("TOF12Paul6thforvsMCTruth.pdf");
c1->Clear();
TOF12longPaul6thforvsMCTruth->GetXaxis()->SetTitle("pz TOF12 long Paul 6th for");
TOF12longPaul6thforvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF12longPaul6thforvsMCTruth->Draw("colz");
TLine *line25 = new TLine(100,100,350,350);
line25->SetLineColor(kRed);
line25->Draw();
c1->SaveAs("TOF12longPaul6thforvsMCTruth.pdf");
c1->Clear();
TOF12Paul2ndforvsMCTruth->GetXaxis()->SetTitle("pz TOF12 Paul 2nd for");
TOF12Paul2ndforvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF12Paul2ndforvsMCTruth->Draw("colz");
TLine *line15 = new TLine(100,100,350,350);
line15->SetLineColor(kRed);
line15->Draw();
c1->SaveAs("TOF12Paul2ndforvsMCTruth.pdf");
c1->Clear();
TOF01Paul6thforvsMCTruth->GetXaxis()->SetTitle("pz TOF01 Paul 6th for");
TOF01Paul6thforvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF01Paul6thforvsMCTruth->Draw("colz");
TLine *line16 = new TLine(100,100,350,350);
line16->SetLineColor(kRed);
line16->Draw();
c1->SaveAs("TOF01Paul6thforvsMCTruth.pdf");
c1->Clear();
gStyle->SetOptStat(0);
gStyle->SetOptFit();
//TOF01shortPaul6thforvsMCTruth->Fit("pol1","","",170,270);
//TF1 *f3 = TOF01shortPaul6thforvsMCTruth->GetFunction("pol1");
TOF01shortPaul6thforvsMCTruth->SetTitle("Corrected P upstream vs MC Truth");
TOF01shortPaul6thforvsMCTruth->GetXaxis()->SetTitle("pz TOF01");
TOF01shortPaul6thforvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF01shortPaul6thforvsMCTruth->SetFillColor(kViolet+1);
//double fillcolour =GetColor(0.2082*0.9, 0.1664*0.9, 0.5293*0.9)
c1->GetFrame()->SetFillColor(fillcolour);
c1->SetFrameFillColor(fillcolour);
TOF01shortPaul6thforvsMCTruth->Draw("colz");
t1.Draw();
t3.Draw();
t2.Draw();
TLine *line46 = new TLine(100,100,350,350);
line46->SetLineColor(kRed);
line46->Draw();
c1->Update();
c1->SaveAs("TOF01shortPaul6thforvsMCTruth.pdf");
c1->Clear();
c1->SetFrameFillColor(0);
TOF01fordownvsMCTruth->GetXaxis()->SetTitle("pz John's formula TOF01");
TOF01fordownvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF01fordownvsMCTruth->Draw("colz");
TLine *line6 = new TLine(100,100,350,350);
line6->SetLineColor(kRed);
line6->Draw();
c1->SaveAs("TOF01fordownvsMCTruth.pdf");
c1->Clear();
TOF12fordownvsMCTruth->GetXaxis()->SetTitle("pz John's formula TOF12");
TOF12fordownvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF12fordownvsMCTruth->Draw("colz");
TLine *line26 = new TLine(100,100,350,350);
line26->SetLineColor(kRed);
line26->Draw();
c1->SaveAs("TOF12fordownvsMCTruth.pdf");
c1->Clear();
TOF12cobbvsMCTruth->GetXaxis()->SetTitle("pz cobb's formula TOF12");
TOF12cobbvsMCTruth->GetYaxis()->SetTitle("pz MCTruth");
TOF12cobbvsMCTruth->Draw("colz");
TLine *line36 = new TLine(100,100,350,350);
line36->SetLineColor(kRed);
line36->Draw();
c1->SaveAs("TOF12cobbvsMCTruth.pdf");
c1->Clear();
TOF01forupvsTOF01fordown->GetXaxis()->SetTitle("pz Ryan's formula downstream TOF12");
TOF01forupvsTOF01fordown->GetYaxis()->SetTitle("pz John's formula TOF01");
TOF01forupvsTOF01fordown->Draw("colz");
TLine *line7 = new TLine(100,100,350,350);
line7->SetLineColor(kRed);
line7->Draw();
c1->SaveAs("TOF01forupvsTOF01fordown.pdf");
c1->Clear();
residual01p6->GetXaxis()->SetTitle("residual01p6");
residual01p6->GetYaxis()->SetTitle("No. of events");
residual01p6->Draw();
c1->SaveAs("residual01p6.pdf");
c1->Clear();
residual01j->GetXaxis()->SetTitle("residual01j");
residual01j->GetYaxis()->SetTitle("No. of events");
residual01j->Draw();
c1->SaveAs("residual01j.pdf");
TText t11 = TText(0.63,0.785,"MICE Preliminary");
TText t13 = TText(0.63,0.75,"ISIS cycle 2015/04");
TText t12 = TText(0.63,0.715,"LiH, MAUS v3.1.2");
t11.SetNDC(1);
t11.SetTextSize(0.04);
t11.SetTextFont(42);
t12.SetNDC(1);
t12.SetTextSize(0.03);
t12.SetTextFont(42);
t13.SetNDC(1);
t13.SetTextSize(0.04);
t13.SetTextFont(42);
c1->Clear();
residual12->GetXaxis()->SetTitle("residual12");
residual12->GetYaxis()->SetTitle("No. of events");
residual12->Draw();
c1->SaveAs("residual12.pdf");
c1->Clear();
//gStyle->SetOptStat(01);
residual12p6->SetTitle("");
residual12p6->GetXaxis()->SetTitle("Momentum residual downstream");
residual12p6->GetYaxis()->SetTitle("No. of events");
residual12p6->GetYaxis()->SetTitleOffset(1.5);
residual12p6->Draw();
residual12p6->GetYaxis()->SetRangeUser(0,50000);
t11.Draw();
t13.Draw();
t12.Draw();
residual12->Draw("SAMES");
residual12->SetLineColor(kRed);
gPad->Update();
TLegend * legend2 = new TLegend(0.1,0.7,0.34,0.9);
legend2->AddEntry(residual12p6,"Corrected momentum","l");
legend2->AddEntry(residual12,"Naive momentum","l");
legend2->Draw();
/*
TPaveStats *st = (TPaveStats*)residual12->FindObject("stats");
st->SetY1NDC(0.4);
st->SetY2NDC(0.6);
*/
c1->SaveAs("residual12p6.pdf");
c1->Clear();
residualcobb->GetXaxis()->SetTitle("residualcobb");
residualcobb->GetYaxis()->SetTitle("No. of events");
residualcobb->Draw();
c1->SaveAs("residualcobb.pdf");
c1->Clear();
residual01short->SetTitle("");
residual01short->GetXaxis()->SetTitle("Momentum residual upstream");
residual01short->GetYaxis()->SetTitle("No. of events");
residual01short->GetYaxis()->SetTitleOffset(1.5);
residual01short->Draw();
//residual01short->GetYaxis()->SetRangeUser(0,35000);
t11.Draw();
t13.Draw();
t12.Draw();
residual01->Draw("SAMES");
residual01->SetLineColor(kRed);
TLegend * legend = new TLegend(0.1,0.7,0.34,0.9);
legend->AddEntry(residual01short,"Corrected momentum","l");
legend->AddEntry(residual01,"Naive Momentum","l");
legend->Draw();
gPad->Update();
/*
TPaveStats *st2 = (TPaveStats*)residual01->FindObject("stats");
st2->SetY1NDC(0.4);
st2->SetY2NDC(0.6);
*/
c1->SaveAs("residual01short.pdf");
c1->Clear();
TOF0Energy->GetXaxis()->SetTitle("TOF0Energy");
TOF0Energy->GetYaxis()->SetTitle("No. of events");
TOF0Energy->Draw();
c1->SaveAs("TOF0Energy.pdf");
c1->Clear();
TOF1Energy->GetXaxis()->SetTitle("TOF1Energy");
TOF1Energy->GetYaxis()->SetTitle("No. of events");
TOF1Energy->Draw();
c1->SaveAs("TOF1Energy.pdf");
c1->Clear();
TOF2Energy->GetXaxis()->SetTitle("TOF2Energy");
TOF2Energy->GetYaxis()->SetTitle("No. of events");
TOF2Energy->Draw();
c1->SaveAs("TOF2Energy.pdf");
c1->Clear();
difEloss->GetXaxis()->SetTitle("difEloss");
difEloss->GetYaxis()->SetTitle("No. of events");
difEloss->Draw();
c1->SaveAs("difEloss.pdf");
c1->Clear();
gStyle->SetOptStat(1);
pathlengthabs->GetXaxis()->SetTitle("Path Length in Absorber (mm)");
pathlengthabs->GetYaxis()->SetTitle("No. of events");
pathlengthabs->Draw();
c1->SaveAs("pathlengthabs.pdf");
c1->SaveAs("pathlengthabs.root");
c1->Clear();
gStyle->SetOptStat(1);
gStyle->SetOptStat("nemR");
theta_true_x_graph->GetXaxis()->SetTitle("#Delta#theta_{x} (mrad)");
theta_true_x_graph->GetYaxis()->SetTitle("No. of events");
//theta_true_x_graph->Sumw2();
theta_true_x_graph->SetFillColor(kOrange-2);
theta_true_x_graph->DrawNormalized();
theta_true_x_graph->Write();
TH1D* thetaX_reco = (TH1D*)outfile->Get("thetaX_recoGEANT");
thetaX_reco->SetMarkerStyle(20);
//thetaX_reco->Sumw2();
thetaX_reco->DrawNormalized("e1 p SAMES");
TLegend * legend20 = new TLegend(0.1,0.7,0.34,0.9);
legend20->AddEntry(theta_true_x_graph,"MC","f");
legend20->AddEntry(thetaX_reco,"Reco sim","p");
legend20->Draw();
gPad->Update();
//TPaveStats *st = (TPaveStats*)thetaX_reco->FindObject("stats");
//st->SetY1NDC(0.4);
//st->SetY2NDC(0.6);
double chi2 = theta_true_x_graph->Chi2Test(thetaX_reco,"WUP");
TText t10 = TText(0.12,0.585,Form("Chi^2 = %f",chi2));
t10.SetNDC(1);
t10.SetTextSize(0.03);
t10.SetTextFont(42);
t10.Draw();
double Kol = theta_true_x_graph->KolmogorovTest(thetaX_reco);
std::cout << "Kolmogorov " << Kol << std::endl;
TText t20 = TText(0.12,0.55,Form("Kolmogorov = %f",Kol));
t20.SetNDC(1);
t20.SetTextSize(0.03);
t20.SetTextFont(42);
t20.Draw();
TText t100 = TText(0.652,0.585,"MICE Preliminary");
TText t300 = TText(0.652,0.55,"ISIS cycle 2015/04");
TText t200 = TText(0.652,0.515,"LiH, MAUS v3.1.2");
t100.SetNDC(1);
t100.SetTextSize(0.04);
t100.SetTextFont(42);
t200.SetNDC(1);
t200.SetTextSize(0.03);
t200.SetTextFont(42);
t300.SetNDC(1);
t300.SetTextSize(0.04);
t300.SetTextFont(42);
t100.Draw();
t300.Draw();
t200.Draw();
c1->SaveAs("theta_true_x_graph.pdf");
c1->SaveAs("theta_true_x_graph.root");
c1->Clear();
gStyle->SetOptStat(1);
gStyle->SetOptStat("nemR");
theta_true_y_graph->GetXaxis()->SetTitle("#Delta#theta_y (mrad)");
theta_true_y_graph->GetYaxis()->SetTitle("No. of events");
theta_true_y_graph->DrawNormalized();
theta_true_y_graph->Write();
theta_true_y_graph->SetFillColor(kOrange-2);
//theta_true_y_graph->Sumw2();
TH1D* thetaY_reco = (TH1D*)outfile->Get("thetaY_recoGEANT");
thetaY_reco->SetMarkerStyle(20);
//thetaY_reco->Sumw2();
thetaY_reco->DrawNormalized("e1 p SAMES");
TLegend * legend21 = new TLegend(0.1,0.7,0.34,0.9);
legend21->AddEntry(theta_true_y_graph,"MC","f");
legend21->AddEntry(thetaY_reco,"Reco sim","p");
legend21->Draw();
gPad->Update();
//TPaveStats *st1 = (TPaveStats*)thetaY_reco->FindObject("stats");
//st1->SetY1NDC(0.4);
//st1->SetY2NDC(0.6);
chi2 = theta_true_y_graph->Chi2Test(thetaY_reco,"WUP");
TText t101 = TText(0.12,0.585,Form("Chi^2 = %.17g",chi2));
t101.SetNDC(1);
t101.SetTextSize(0.03);
t101.SetTextFont(42);
t101.Draw();
Kol = theta_true_y_graph->KolmogorovTest(thetaY_reco);
std::cout << "Kolmogorov " << Kol << std::endl;
TText t21 = TText(0.12,0.55,Form("Kolmogorov = %.17g",Kol));
t21.SetNDC(1);
t21.SetTextSize(0.03);
t21.SetTextFont(42);
t21.Draw();
c1->SaveAs("theta_true_y_graph.pdf");
c1->SaveAs("theta_true_y_graph.root");
c1->Clear();
eventnovspz->Draw("colz");
c1->SaveAs("eventnovspz.pdf");
c1->SaveAs("eventnovspz.root");
chi2pern->Write();
//outfile->Close();
mctheta_true_x_graph->Write();
mctheta_true_y_graph->Write();
mctheta_true_scat_graph->Write();
delete c1;
}
void MCSAnalysis::print(){
std::cout << "standard error on mean momentum " << semom << std::endl;
std::cout << "rms of momentum " << rmsmom << std::endl;
std::cout << "Error on rms of momentum " << errrmsmom << std::endl;
bwmom = (1.357e3/pow(TOF_upper_limit - 24.28,2)) - (1.357e3/pow(TOF_lower_limit - 24.28,2));
std::cout << "width of bin mom " << bwmom << std::endl;
std::cout << "bin width sqrt12 " << bwmom/sqrt(12) << std::endl;
}
void MCSAnalysis::Execute(int mode){
int verbose_level = 1;
// MAUS::GlobalsManager::InitialiseGlobals(JsonWrapper::JsonToString(SetupConfig(verbose_level)));
dataSelection(mode);
if (mode == 0){
generateMCSResponse();
// DoUnfolding();
DoDeconvolution(modelname1.c_str(), 1);
TruthData(mode);
}
else if (mode == 1){
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
ConvolveWithInputDistribution(modelname1.c_str());
DoDeconvolution(modelname1.c_str(), 1);
ConvolveWithInputDistribution(modelname2.c_str());
DoDeconvolution(modelname2.c_str(), 1);
//FitGaussian(outfilename.c_str());
//CalculateChi2(outfilename.c_str(), modelname2.c_str());
//Write();
}
else if (mode == -1){
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
ConvolveWithInputDistribution(modelname1.c_str());
DoDeconvolution(modelname1.c_str(), 1);
ConvolveWithInputDistribution(modelname2.c_str());
DoDeconvolution(modelname2.c_str(), 1);
ConvolveWithInputDistribution(modelname3.c_str());
DoDeconvolution(modelname3.c_str(), 1);
TruthData(mode);
//FitGaussian(outfilename.c_str());
//CalculateChi2(outfilename.c_str(), modelname2.c_str());
Write();
print();
}
else if (mode == -7){
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
ConvolveWithInputDistribution(modelname1.c_str());
DoDeconvolution(modelname1.c_str(), 1);
ConvolveWithInputDistribution(modelname2.c_str());
DoDeconvolution(modelname2.c_str(), 1);
ConvolveWithInputDistribution(modelname3.c_str());
DoDeconvolution(modelname3.c_str(), 1);
TruthData(mode);
//FitGaussian(outfilename.c_str());
//CalculateChi2(outfilename.c_str(), modelname2.c_str());
Write();
print();
}
else if (mode == -2){
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
ConvolveWithInputDistribution(modelname1.c_str());
DoDeconvolution(modelname1.c_str(), 1);
ConvolveWithInputDistribution(modelname2.c_str());
DoDeconvolution(modelname2.c_str(), 1);
ConvolveWithInputDistribution(modelname3.c_str());
DoDeconvolution(modelname3.c_str(), 1);
TruthData(mode);
//FitGaussian(outfilename.c_str());
//CalculateChi2(outfilename.c_str(), modelname2.c_str());
Write();
print();
}
else if (mode == 2){
TruthData(mode);
}
else if (mode == 5){
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
TruthData(mode);
ConvolveWithVirtualInputDistribution(modelname1.c_str());
DoDeconvolution(modelname1.c_str(), 1);
ConvolveWithVirtualInputDistribution(modelname2.c_str());
DoDeconvolution(modelname2.c_str(), 1);
ConvolveWithVirtualInputDistribution(modelname3.c_str());
DoDeconvolution(modelname3.c_str(), 1);
}
else if (mode == 4){
TruthData(mode-1);
referenceSelection();
DoUnfolding();
DoFFTDeconvolution();
TruthData(mode);
ConvolveWithVirtualInputDistribution(modelname1.c_str());
DoVirtualDeconvolution(modelname1.c_str(), 1);
ConvolveWithVirtualInputDistribution(modelname2.c_str());
DoVirtualDeconvolution(modelname2.c_str(), 1);
ConvolveWithVirtualInputDistribution(modelname3.c_str());
DoVirtualDeconvolution(modelname3.c_str(), 1);
}
else {
std::cout<<"Unknown operation mode"<<std::endl;
}
}
void MCSAnalysis::dataSelection(int mode){
// Set addresses for tree selection
chain->SetBranchAddress("RunNumber", &runnumber);
chain->SetBranchAddress("TOFBranch", &tofevent);
chain->SetBranchAddress("SciFiBranch", &scifievent);
chain->SetBranchAddress("CkovBranch", &ckovevent);
chain->SetBranchAddress("KLBranch", &klevent);
chain->SetBranchAddress("EMRBranch", &emrevent);
chain->SetBranchAddress("MCEvent", &mcevent);
int no=0;
// Restrict the number of entries to less than or equal to the mcchain entries
int Nentries = chain->GetEntries();
// < mcchain->GetEntries() ?
// chain->GetEntries() : mcchain->GetEntries();
// Loop over all tree entries.
Collection USAllTOF, DSAllTOF, USPreRadSel, DSPreRadSel;
Collection MCUSAllTOF, MCDSAllTOF, MCUSPreRadSel, MCDSPreRadSel;
double pz = 0.;
std::cout << Nentries << std::endl;
int Nevents = 0;
// Nentries *= int(_sys["FracEvents"]) > 0 ? _sys["FracEvents"] : 1.0;
for (int i=0; i<1000000; i++){
isEmpty=false;
chain->GetEntry(i);
if (i%100000==0) std::cout<<"Event "<<i<<"\n";
if (isMC==1) {
if( !findVirtualPlanes() ) continue;
}
// Set cuts based on the TOFs, ckov, kl, and EMR information
// Locate the tracker reference planes. To be agnostic locate
// the downstream most station of the upstream tracker and the
// upstream most station of the downstream tracker.
cuts_accept->Fill("All Events",1);
// if (scifievent->scifitracks().size() != 2) continue;
// if ( !SelectMomentum() ) continue;
if ( !MatchUSDS() ) {
if (jUS == -1 || kUS == -1){
continue;
}
}
if (mode==-7) {
if (jDS == -1 || kDS == -1){
continue;
std::cout << "here2" << std::endl;
}
}
cuts_accept->Fill("US Track Found",1);
FillCollectionSciFi(USAllTOF, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(DSAllTOF, jDS, kDS, lDS, pz, 1);
Vars mcUSTruthAbsHit, mcDSTruthAbsHit;
centre = USabsPlaneI + 1;
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
FillVarsVirtual(mcUSTruthAbsHit, USabsPlaneI, centre);
FillVarsVirtual(mcDSTruthAbsHit, DSabsPlaneI, centre);
MCUSAllTOF.append_instance(mcUSTruthAbsHit);
MCDSAllTOF.append_instance(mcDSTruthAbsHit);
}
if ( !PIDSelection(true) ) continue;
//if ( !TruthTime12(true) ) continue; // event_ok=false;
if (mode==-2) {
if (mcevent->GetVirtualHits()->size() >= 49) {
if (mcevent->GetVirtualHits()->at(48).GetParticleId()!=-13) continue;
}
}
//pz = MomentumFromTOF(true);
double diff = 0;
pz = CorMomFromTOF(pz, 0, diff);
pz += 1.8;
//if (pz >213 || pz<193) continue;
cuts_accept->Fill("TOF Selection",1);
FillCollectionSciFi(USPreRadSel, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(DSPreRadSel, jDS, kDS, lDS, pz, 1);
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
MCUSPreRadSel.append_instance(mcUSTruthAbsHit);
MCDSPreRadSel.append_instance(mcDSTruthAbsHit);
}
if ( !RadialSelection(pz,19948.8,meanp) ) continue;
cuts_accept->Fill("Fiducial Selection",1);
if ( !RadialSelection(pz,_sys["diffpos"],90) ) continue; //diff=1;
cuts_accept->Fill("Diffuser Cut",1);
if ( _sys["psel_lcut"] > 0 && _sys["psel_ucut"] > 0 ){
if ( pz < _sys["psel_lcut"] || pz > _sys["psel_ucut"] )
// Cut out events to evaluate systematic uncertainties.
continue;
}
Nevents++;
//
if (!FillCrossCheck()) continue;
cuts_accept->Fill("chi2ndf",1);
if(_sys["Nevents"] > 0 && Nevents > int(_sys["Nevents"]))
break;
//if (scifievent->scifitracks()[jUS]->scifitrackpoints()[kUS]->pos().x()<30 && scifievent->scifitracks()[jUS]->scifitrackpoints()[kUS]->pos().y()<30 && scifievent->scifitracks()[jUS]->scifitrackpoints()[kUS]->pos().x()>-30 && scifievent->scifitracks()[jUS]->scifitrackpoints()[kUS]->pos().y()>-30) {
/*
double MCTruth_pz_mid;
for ( size_t iter=0; iter < mcevent->GetVirtualHits()->size(); iter++){
if (mcevent->GetVirtualHits()->at(iter).GetPosition().z()-17000<50 && mcevent->GetVirtualHits()->at(iter).GetPosition().z()-17000>-50) {
MCTruth_pz_mid = mcevent->GetVirtualHits()->at(iter).GetMomentum().z();
}
}
if (MCTruth_pz_mid>202 && MCTruth_pz_mid<198) continue;
*/
FillCollectionSciFi(_USset, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(_DSset, jDS, kDS, lDS, pz, 1);
FillCollectionSciFi(_UStmpset, jUS, kUS, lUS, pz, 0);
//mcUSTruthAbsHit.pz = pz;
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
mcreconUSTruthSet.append_instance(mcUSTruthAbsHit);
mcreconDSTruthSet.append_instance(mcDSTruthAbsHit);
}
no+=1;
//}
if (runnumber != LastRunNumber){
UpdateRunInfo();
}
cor_mom->Fill(pz);
}
TruthGraph(mcreconUSTruthSet, mcreconDSTruthSet, true);
data_make_beam_histograms(USAllTOF, "Upstream, Data", "dataUS_alltof", MCUSAllTOF);
data_make_beam_histograms(DSAllTOF, "Downstream, Data", "dataDS_alltof", MCDSAllTOF);
//make_acceptance_histograms(USAllTOF, DSAllTOF,"Data Projection", "dataAcc_alltof");
data_make_beam_histograms(USPreRadSel, "Upstream, Data", "dataUS_prerad", MCUSPreRadSel);
data_make_beam_histograms(DSPreRadSel, "Downstream, Data", "dataDS_prerad", MCDSPreRadSel);
data_make_beam_histograms(_USset, "Upstream, Data", "dataUS", mcreconUSTruthSet);
data_make_beam_histograms(_DSset, "Downstream, Data", "dataDS", mcreconDSTruthSet);
make_acceptance_histograms(_USset, _DSset, "", "dataAcc");
PlotRunInfo();
}
void MCSAnalysis::referenceSelection(){
// Set addresses for tree selection
refchain->SetBranchAddress("TOFBranch", &tofevent);
refchain->SetBranchAddress("SciFiBranch", &scifievent);
refchain->SetBranchAddress("CkovBranch", &ckovevent);
refchain->SetBranchAddress("KLBranch", &klevent);
refchain->SetBranchAddress("EMRBranch", &emrevent);
refchain->SetBranchAddress("MCEvent", &mcevent);
// Restrict the number of entries to less than or equal to the refchain entries
int Nentries = refchain->GetEntries();
// < mcchain->GetEntries() ?
// chain->GetEntries() : mcchain->GetEntries();
Collection USAllTOFEmpty, DSAllTOFEmpty, USPreRadSelEmpty, DSPreRadSelEmpty;
Collection MCUSAllTOFEmpty, MCDSAllTOFEmpty, MCUSPreRadSelEmpty, MCDSPreRadSelEmpty, MCUSEmpty, MCDSEmpty;
double pz = 0.;
// Loop over all tree entries.
for (int i=0; i<1000000; i++){
isEmpty=true;
refchain->GetEntry(i);
if (i%100000==0) std::cout<<"Event "<<i<<"\n";
if (isMC==1) {
if( !findVirtualPlanes() ) continue;
}
// Set cuts based on the TOFs, ckov, kl, and EMR information
// Locate the tracker reference planes. To be agnostic locate
// the downstream most station of the upstream tracker and the
//// upstream most station of the downstream tracker.
cuts_accept->Fill("All Events",1);
if ( !MatchUSDS() ) {
if (jUS == -1 || kUS == -1){
continue;
}
}
cuts_accept->Fill("US Track Found",1);
FillCollectionSciFi(USAllTOFEmpty, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(DSAllTOFEmpty, jDS, kDS, lDS, pz, 1);
Vars mcUSTruthAbsHitEmpty, mcDSTruthAbsHitEmpty;
int centre = 51;
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
FillVarsVirtual(mcUSTruthAbsHitEmpty, centre, centre);
FillVarsVirtual(mcDSTruthAbsHitEmpty, centre, centre);
MCUSAllTOFEmpty.append_instance(mcUSTruthAbsHitEmpty);
MCDSAllTOFEmpty.append_instance(mcDSTruthAbsHitEmpty);
}
if ( !PIDSelection(false) ) continue;
//if ( !TruthTime12(false) ) continue; // event_ok=false;
cuts_accept->Fill("TOF Selection",1);
//pz = MomentumFromTOF(false);
double diff;
pz = CorMomFromTOF(pz, 1, diff);
pz += 2.4;
//if (pz >213 || pz<193) continue;
// if (scifievent->scifitracks().size() != 2) continue;
// if ( !SelectMomentum() ) continue;
FillCollectionSciFi(USPreRadSelEmpty, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(DSPreRadSelEmpty, jDS, kDS, lDS, pz, 1);
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
MCUSPreRadSelEmpty.append_instance(mcUSTruthAbsHitEmpty);
MCDSPreRadSelEmpty.append_instance(mcDSTruthAbsHitEmpty);
}
if ( !RadialSelection(pz,19948.8,meanp) ) continue;
cuts_accept->Fill("Fiducial Selection",1);
if ( !RadialSelection(pz,_sys["diffpos"],90) ) continue;
cuts_accept->Fill("Diffuser Cut",1);
/*
double MCTruth_pz_mid;
for ( size_t iter=0; iter < mcevent->GetVirtualHits()->size(); iter++){
if (mcevent->GetVirtualHits()->at(iter).GetPosition().z()-17000<50 && mcevent->GetVirtualHits()->at(iter).GetPosition().z()-17000>-50) {
MCTruth_pz_mid = mcevent->GetVirtualHits()->at(iter).GetMomentum().z();
}
}
if (MCTruth_pz_mid>202 && MCTruth_pz_mid<198) continue;
*/
if (!FillCrossCheck()) continue;
cuts_accept->Fill("chi2ndf",1);
FillCollectionSciFi(_USMCset, jUS, kUS, lUS, pz, 0);
FillCollectionSciFi(_DSMCset, jDS, kDS, lDS, pz, 1);
if (USrefplaneI > 0 && USabsPlaneI >0 &&
DSrefplaneI > 0 && DSabsPlaneI >0 ){
MCUSEmpty.append_instance(mcUSTruthAbsHitEmpty);
MCDSEmpty.append_instance(mcDSTruthAbsHitEmpty);
}
mccalc_mom->Fill(pz);
}
data_make_beam_histograms(USAllTOFEmpty, "Upstream, Data Reference", "dataUSref_alltof", MCUSAllTOFEmpty);
data_make_beam_histograms(DSAllTOFEmpty, "Downstream, Data Reference", "dataDSref_alltof", MCDSAllTOFEmpty);
//make_acceptance_histograms(USAllTOF, DSAllTOF, "Data Reference", "dataProj_alltof");
data_make_beam_histograms(USPreRadSelEmpty, "Upstream, Data Reference", "dataUSref_prerad", MCUSPreRadSelEmpty);
data_make_beam_histograms(DSPreRadSelEmpty, "Downstream, Data Reference", "dataDSref_prerad", MCDSPreRadSelEmpty);
//make_acceptance_histograms(USPreRadSel, DSPreRadSel, "Data Reference", "dataProj_prerad");
data_make_beam_histograms(_USMCset, "Upstream, Data Reference", "dataUSref", MCUSEmpty);
data_make_beam_histograms(_DSMCset, "Downstream, Data Reference", "dataDSref", MCDSEmpty);
make_acceptance_histograms(_USMCset, _DSMCset, "Data Reference", "dataProj");
}
void MCSAnalysis::generateMCSResponse(){
chain->SetBranchAddress("TOFBranch", &tofevent);
chain->SetBranchAddress("SciFiBranch", &scifievent);
chain->SetBranchAddress("CkovBranch", &ckovevent);
chain->SetBranchAddress("KLBranch", &klevent);
chain->SetBranchAddress("EMRBranch", &emrevent);
chain->SetBranchAddress("MCEvent", &mcevent);
// Loop over the training sample.