def plot_distorsion(h_dist, h_deltas, h_deltas_vs_dist, prof, suffix, opt_name, total_events):
cev = TCanvas("canvas_%s_nEv%d_%s" % (suffix, total_events, opt_name),
"canvas_%s_nEv%d_%s" % (suffix, total_events, opt_name),
1400, 1000)
cev.Divide(2, 2)
cev.cd(1)
h_dist.GetXaxis().SetTitle("Numeric %s distortion fluctuation (cm)" % opt_name)
h_dist.GetYaxis().SetTitle("Predicted distortion fluctuation (cm)")
h_dist.Draw("colz")
cev.cd(2)
gPad.SetLogy()
h_deltas_vs_dist.GetXaxis().SetTitle("Numeric %s distorsion fluctuation (cm)" % opt_name)
h_deltas_vs_dist.ProjectionX().Draw()
h_deltas_vs_dist.GetYaxis().SetTitle("Entries")
cev.cd(3)
gPad.SetLogy()
h_deltas.GetXaxis().SetTitle("(Predicted - Numeric) %s distortion fluctuation (cm)"
% opt_name)
h_deltas.GetYaxis().SetTitle("Entries")
h_deltas.Draw()
cev.cd(4)
prof.GetYaxis().SetTitle("(Predicted - Numeric) %s distortion fluctuation (cm)" % opt_name)
prof.GetXaxis().SetTitle("Numeric %s distortion fluctuation (cm)" % opt_name)
prof.Draw()
#cev.cd(5)
#h_deltas_vs_dist.GetXaxis().SetTitle("Numeric R distorsion (cm)")
#h_deltas_vs_dist.GetYaxis().SetTitle("(Predicted - Numeric) R distorsion (cm)")
#h_deltas_vs_dist.Draw("colz")
cev.SaveAs("plots/canvas_%s_nEv%d.pdf" % (suffix, total_events))
def plot_distorsion(h_dist, h_deltas, h_deltasvsdist, prof, suffix,
namevar):
cev = TCanvas("canvas" + suffix, "canvas" + suffix, 1400, 1000)
cev.Divide(2, 2)
cev.cd(1)
h_dist.GetXaxis().SetTitle("Numeric %s distortion fluctuation (cm)" %
namevar)
h_dist.GetYaxis().SetTitle("Predicted distortion fluctuation (cm)")
h_dist.Draw("colz")
cev.cd(2)
gPad.SetLogy()
h_deltasvsdist.GetXaxis().SetTitle(
"Numeric %s distorsion fluctuation (cm)" % namevar)
h_deltasvsdist.GetYaxis().SetTitle("Entries")
h_deltasvsdist.ProjectionX().Draw()
cev.cd(3)
gPad.SetLogy()
h_deltas.GetXaxis().SetTitle(
"(Predicted - Numeric) %s distortion fluctuation (cm)" % namevar)
h_deltas.GetYaxis().SetTitle("Entries")
h_deltas.Draw()
cev.cd(4)
prof.GetYaxis().SetTitle(
"(Predicted - Numeric) %s distortion fluctuation (cm)" % namevar)
prof.GetXaxis().SetTitle("Numeric %s distortion fluctuation (cm)" %
namevar)
prof.Draw()
#cev.cd(5)
#h_deltasvsdist.GetXaxis().SetTitle("Numeric R distorsion (cm)")
#h_deltasvsdist.GetYaxis().SetTitle("(Predicted - Numeric) R distorsion (cm)")
#h_deltasvsdist.Draw("colz")
cev.SaveAs("plots/canvas_%s.pdf" % (suffix))
def MakeCutPlot(c,cal,var,eb,elo,ehi,vb,vlo,vhi,d2Cut,d1Cut,outPlot,fastMode):
""" Creates a channel-specific energy calibration plot. """
# Calculate cut vals (assumes plot range is correct)
h1 = wl.H1D(cal,vb,vlo,vhi,var,d1Cut)
h1Sum = h1.Integral()
if h1Sum == 0:
print "Error: Failed %s, histogram sum is 0 so cannot normalize, setting to [0,0,0,0,0]"%(var)
return 0,0,0,0,0
h1.Scale(1/h1Sum)
try:
cut99,cut95,cut01,cut05,cut90 = wl.GetIntegralPoints(h1)
except:
print "Error: Failed %s using cut %s, setting to [0,0,0,0,0]"%(var,d1Cut)
return 0,0,0,0,0
if fastMode:
print "Returning fastMode output: ", cut99,cut95,cut01,cut05,cut90
return cut99,cut95,cut01,cut05,cut90
# Generate the plot for inspection.
c.cd(2)
gPad.SetLogy(0)
h1.GetXaxis().SetRangeUser(cut01-abs(0.25*cut01), cut99 + abs(0.25*cut99) )
h1.SetTitle("")
h1.GetXaxis().SetTitle(var)
h1.Draw("hist")
c.cd(1)
gPad.SetLogy(0)
cal.Draw("%s:trapENFCal>>b(%d,%d,%d,%d,%.3E,%.3E)"%(var,eb+10,elo-5,ehi+5,vb,cut01-abs(0.25*cut01),cut99+abs(0.25*cut99)) ,d2Cut)
l1, l2, l3 = TLine(), TLine(), TLine()
l1.SetLineColor(ROOT.kGreen)
l2.SetLineColor(ROOT.kRed)
l3.SetLineColor(ROOT.kMagenta)
l1.DrawLine(elo-5, cut99, ehi+5, cut99)
l2.DrawLine(elo-5, cut95, ehi+5, cut95)
l2.DrawLine(elo-5, cut05, ehi+5, cut05)
l1.DrawLine(elo-5, cut01, ehi+5, cut01)
c.cd(3)
x_h1, y_h1 = wl.npTH1D(h1)
int_h1 = wl.integFunc(y_h1)
g2 = TGraph(len(x_h1), x_h1, int_h1)
g2.GetXaxis().SetRangeUser(cut01-abs(0.3*cut01), cut99 + abs(0.3*cut99) )
g2.SetTitle("")
g2.GetXaxis().SetTitle(var)
g2.GetYaxis().SetTitle("Percentile")
g2.Draw("ACP")
l1.DrawLine(cut99, 0, cut99, 1)
l2.DrawLine(cut95, 0, cut95, 1)
l1.DrawLine(cut01, 0, cut01, 1)
l2.DrawLine(cut05, 0, cut05, 1)
c.Print(outPlot)
return cut99,cut95,cut01,cut05,cut90
def plot_distortion(config, h_dist, h_deltas, h_deltas_vs_dist, prof, suffix, opt_name):
cev = TCanvas("canvas_%s_nEv%d_%s" % (suffix, config.train_events, opt_name),
"canvas_%s_nEv%d_%s" % (suffix, config.train_events, opt_name),
1600, 1600)
cev.Divide(2, 2)
c1 = cev.cd(1)
c1.SetMargin(0.12, 0.12, 0.12, 0.05)
gPad.SetLogz()
setup_frame(h_dist, "d#it{%s}_{true} (cm)" % opt_name.lower(),
"d#it{%s}_{pred} (cm)" % opt_name.lower(), x_offset=1.2, y_offset=1.2)
h_dist.Draw("colz")
txt1 = add_desc_to_canvas(config, 0.18, 0.7, 0.3, 0.9, 0.04,
{"add_alice": False, "add_gran": True, "add_inputs": False,
"add_events": True})
txt1.Draw()
c2 = cev.cd(2)
c2.SetMargin(0.12, 0.05, 0.12, 0.05)
gPad.SetLogy()
setup_frame(h_deltas_vs_dist, "d#it{%s}_{true} (cm)" % opt_name.lower(),
"Entries", x_offset=1.2, y_offset=1.2)
h_deltas_vs_dist.ProjectionX().Draw()
txt2 = add_desc_to_canvas(config, 0.18, 0.7, 0.3, 0.9, 0.04,
{"add_alice": False, "add_gran": True, "add_inputs": False,
"add_events": True})
txt2.Draw()
c3 = cev.cd(3)
c3.SetMargin(0.12, 0.05, 0.12, 0.05)
gPad.SetLogy()
setup_frame(h_deltas, "<d#it{%s}_{pred} - d#it{%s}_{true}> (cm)" %\
(opt_name.lower(), opt_name.lower()),
"Entries", x_offset=1.2, y_offset=1.5)
h_deltas.Draw()
txt3 = add_desc_to_canvas(config, 0.18, 0.7, 0.3, 0.9, 0.04,
{"add_alice": False, "add_gran": True, "add_inputs": False,
"add_events": True})
txt3.Draw()
c4 = cev.cd(4)
c4.SetMargin(0.15, 0.05, 0.12, 0.05)
setup_frame(prof, "d#it{%s}_{true} (cm)" % opt_name.lower(),
"<d#it{%s}_{pred} - d#it{%s}_{true}> (cm)" %\
(opt_name.lower(), opt_name.lower()),
x_offset=1.2, y_offset=1.8)
prof.Draw()
txt4 = add_desc_to_canvas(config, 0.45, 0.7, 0.85, 0.9, 0.04,
{"add_alice": False, "add_gran": True, "add_inputs": False,
"add_events": True})
txt4.Draw()
#cev.cd(5)
#h_deltas_vs_dist.GetXaxis().SetTitle("Numeric R distortion (cm)")
#h_deltas_vs_dist.GetYaxis().SetTitle("(Predicted - Numeric) R distortion (cm)")
#h_deltas_vs_dist.Draw("colz")
cev.SaveAs("%s/canvas_%s_nEv%d.pdf" % (config.dirplots, suffix,
config.train_events))
def plot_dSigDtheta():
# dSigma / dTheta according to ZEUS parametrization
Ee = 18
gen = gen_zeus(Ee, 275) # Ee, Ep, GeV
sig = gen.dSigDtheta
can = ut.box_canvas()
sig.SetLineWidth(3)
sig.SetNpx(1000)
sig.SetTitle("")
sig.Draw()
sig.GetXaxis().SetTitle("#theta_{#gamma} (rad)")
sig.GetYaxis().SetTitle("a. u.")
sig.GetYaxis().SetTitleOffset(1.5)
sig.GetXaxis().SetTitleOffset(1.3)
gPad.SetTopMargin(0.01)
gPad.SetRightMargin(0.08)
leg = ut.prepare_leg(0.58, 0.78, 0.24, 0.15, 0.035) # x, y, dx, dy, tsiz
leg.AddEntry(sig, "#frac{d#sigma}{d#theta_{#gamma}}", "l")
leg.AddEntry(None, "E_{e} = 18 GeV", "")
leg.Draw("same")
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def el_en_tag():
#energy for electrons hitting the tagger
#bins in energy
ebin = 0.1
emin = 0
emax = 30
#sel = ""
#sel = "lowQ2s1_IsHit==1"
sel = "lowQ2s2_IsHit==1"
#sel = "lowQ2s1_IsHit==1 || lowQ2s2_IsHit==1"
can = ut.box_canvas()
hEnTag = ut.prepare_TH1D("hEnTag", ebin, emin, emax)
#hEnTag = ut.prepare_TH1D_n("hEnTag", 10, emin, emax)
#tree.Draw("el_gen >> hEnTag", sel)
tree.Draw("true_el_E >> hEnTag", sel)
hEnTag.Draw()
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def el_theta_tag():
#electron generated polar angle for electrons hitting the tagger
#tbin = 5e-2
#tmin = 0
#tmax = TMath.Pi() + 1e-2
tbin = 2e-4
tmin = TMath.Pi() - 2.1e-2
tmax = TMath.Pi() + 0.5e-2
#sel = ""
sel = "lowQ2s1_IsHit==1"
#sel = "lowQ2s2_IsHit==1"
#sel = "lowQ2s1_IsHit==1 || lowQ2s2_IsHit==1"
can = ut.box_canvas()
hThetaTag = ut.prepare_TH1D("hThetaTag", tbin, tmin, tmax)
#tree.Draw("el_theta >> hThetaTag", sel)
tree.Draw("true_el_theta >> hThetaTag", sel)
gPad.SetGrid()
gPad.SetLogy()
hThetaTag.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def el_pT_tag():
#electron pT
#ptbin = 0.1
#ptmin = 0
#ptmax = 80
ptbin = 3e-3
ptmin = 0
ptmax = 0.3
#sel = ""
#sel = "lowQ2s1_IsHit==1"
sel = "lowQ2s2_IsHit==1"
#sel = "lowQ2s1_IsHit==1 || lowQ2s2_IsHit==1"
can = ut.box_canvas()
hPt = ut.prepare_TH1D("hPt", ptbin, ptmin, ptmax)
tree.Draw("true_el_pT >> hPt", sel)
gPad.SetGrid()
gPad.SetLogy()
hPt.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def hit_en():
#energy in tagger
#infile = "lmon.root"
infile = "dd.root"
emin = 0
emax = 19
ebin = 0.1
#emax = 1.1
#ebin = 0.01
inp = TFile.Open(infile)
tree = inp.Get("event")
can = ut.box_canvas()
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
#nev = tree.Draw("hit_s1_en >> hE", "s1_IsHit==1")
nev = tree.Draw("hit_s2_en >> hE", "s2_IsHit==1")
#nev = tree.Draw("hit_s1_en/gen_en >> hE", "s1_IsHit==1")
#nev = tree.Draw("hit_s2_en/gen_en >> hE", "s2_IsHit==1")
#nev = tree.Draw("hit_s1_en >> hE", "(s1_IsHit==1)&&((hit_s1_en/gen_en)>0.9)")
#nev = tree.Draw("hit_s2_en >> hE", "(s2_IsHit==1)&&((hit_s2_en/gen_en)>0.9)")
print(nev)
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def phot_en_conv():
#photon energy with conversions or clean conversions
#plot range
emin = 0
emax = 19
ebin = 0.1
inp = TFile.Open("ew.root")
tree = inp.Get("conv_tree")
can = ut.box_canvas()
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
nev = tree.Draw("gen_en >> hE")
#nev = tree.Draw("gen_en >> hE", "conv==1")
#nev = tree.Draw("gen_en >> hE", "clean==1")
print(nev)
ut.line_h1(hE)
ut.put_yx_tit(hE, "Counts", "#it{E} (GeV)")
ut.set_margin_lbtr(gPad, 0.11, 0.09, 0.02, 0.01)
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def efficiencytracking():
hadron_list = ["pion", "proton", "electron", "muon"]
color_list = [1, 2, 4, 6]
fileo2 = TFile("../codeHF/AnalysisResults_O2.root")
c1 = TCanvas("c1", "A Simple Graph Example")
c1.SetCanvasSize(1500, 1500)
c1.cd()
gPad.SetLogx()
gPad.SetLogy()
eff_list = []
hempty = TH1F("hempty", ";p_{T};efficiency", 100, 0.001, 5.0)
hempty.Draw()
leg = TLegend(0.1, 0.7, 0.3, 0.9, "")
leg.SetFillColor(0)
for i, had in enumerate(hadron_list):
hnum = fileo2.Get("qa-tracking-efficiency-%s/num" % had)
hden = fileo2.Get("qa-tracking-efficiency-%s/den" % had)
hnum.Rebin(4)
hden.Rebin(4)
eff = TEfficiency(hnum, hden)
eff.SetLineColor(color_list[i])
eff_list.append(eff)
eff.Draw("same")
leg.AddEntry(eff_list[i], had)
leg.Draw()
c1.SaveAs("efficiency_tracking.pdf")
def makeROC(fpr, tpr, thresholds, AUC, outfile, signal_label,
background_label):
c = TCanvas("c", "c", 700, 600)
gPad.SetMargin(0.15, 0.07, 0.15, 0.05)
gPad.SetLogy(0)
gPad.SetGrid(1, 1)
gStyle.SetGridColor(15)
roc = TGraph(len(fpr), tpr, fpr)
roc.SetLineColor(2)
roc.SetLineWidth(2)
roc.SetTitle(";Signal efficiency (%s); Background efficiency (%s)" %
(signal_label, background_label))
roc.GetXaxis().SetTitleOffset(1.4)
roc.GetXaxis().SetTitleSize(0.045)
roc.GetYaxis().SetTitleOffset(1.4)
roc.GetYaxis().SetTitleSize(0.045)
roc.GetXaxis().SetRangeUser(0, 1)
roc.GetYaxis().SetRangeUser(0.000, 1)
roc.Draw("AL")
latex = TLatex()
latex.SetTextFont(42)
latex.SetTextSize(0.05)
latex.DrawLatexNDC(0.2, 0.88, 'AUC = %.3f' % AUC)
c.SaveAs(outfile)
def plot_en():
#energy distribution of generated photons
ebin = 0.1
emin = 4
emax = 28
can = ut.box_canvas()
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
tree.Draw("phot_en >> hE")
hE.SetYTitle("Events / ({0:.3f}".format(ebin) + " GeV)")
hE.SetXTitle("#it{E}_{#gamma} (GeV)")
hE.SetTitleOffset(1.9, "Y")
hE.SetTitleOffset(1.3, "X")
gPad.SetTopMargin(0.02)
gPad.SetRightMargin(0.01)
gPad.SetBottomMargin(0.1)
gPad.SetLeftMargin(0.14)
hE.GetYaxis().SetMoreLogLabels()
hE.Draw()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def neut_eta():
#neutron pseudorapidity
etabin = 0.05
etamin = -20
etamax = 20
hEta = ut.prepare_TH1D("hEta", etabin, etamin, etamax)
can = ut.box_canvas()
particles = TClonesArray("TParticle", 200)
tree.SetBranchAddress("particles", particles)
nev = tree.GetEntriesFast()
#nev = 24
for iev in xrange(nev):
tree.GetEntry(iev)
for imc in xrange(particles.GetEntriesFast()):
part = particles.At(imc)
if part.GetPdgCode() != 2112: continue
hEta.Fill(part.Eta())
ut.put_yx_tit(hEta, "Events", "#eta", 1.4, 1.2)
hEta.Draw()
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def plot_theta():
#polar angle of generated photons
tbin = 0.01
tmax = 3
can = ut.box_canvas()
ht = ut.prepare_TH1D("ht", tbin, 0, tmax)
tree.Draw("(TMath::Pi()-phot_theta)*1000 >> ht")
ht.SetYTitle("Events / ({0:.3f}".format(tbin) + " mrad)")
ht.SetXTitle("#vartheta (mrad)")
ht.SetTitleOffset(1.5, "Y")
ht.SetTitleOffset(1.3, "X")
gPad.SetTopMargin(0.02)
gPad.SetRightMargin(0.025)
gPad.SetBottomMargin(0.1)
gPad.SetLeftMargin(0.11)
ht.Draw()
leg = ut.prepare_leg(0.2, 0.87, 0.18, 0.08, 0.035)
leg.AddEntry(None, "Angular distribution of Bethe-Heitler photons", "")
#leg.Draw("same")
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gamma_p_ys():
#distribution of total gamma-proton cross section over a given CM energy s and generated y
sqrt_s = 28.6 # GeV
#gamma-p range
gpbin = 0.01
gpmin = 0
gpmax = 1
hGP = ut.prepare_TH1D("hGP", gpbin, gpmin, gpmax)
scm = sqrt_s**2
form = "0.0677*TMath::Power((true_y*" + str(scm) + "), 0.0808)"
form += "+0.129*TMath::Power((true_y*" + str(scm) + "), -0.4525)"
#print form
tree.Draw(form + " >> hGP")
can = ut.box_canvas()
ut.put_yx_tit(hGP, "Events", "#sigma(#gamma p) (mb)", 1.4, 1.2)
hGP.Draw()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_eta():
#electron pseudorapidity
#eta range
etabin = 0.3
etamin = -20
etamax = 10
hEta = ut.prepare_TH1D("hEta", etabin, etamin, etamax)
can = ut.box_canvas()
form = "-TMath::Log(TMath::Tan(true_el_theta/2.))"
#form = "-TMath::Log(TMath::Tan(el_theta/2.))"
tree.Draw(form + " >> hEta")
ut.put_yx_tit(hEta, "Events", "#eta", 1.4, 1.2)
hEta.Draw()
gPad.SetLogy()
gPad.SetGrid()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def aXe():
can = TCanvas("can", "can", 1000, 900)
gPad.SetLogy(1)
gStyle.SetOptStat(0)
VariablesNum = {}
VariablesDen = {}
treeG = {}
for tre in darkFactors:
# treeG[tre] = darkFiles[tre].Get("darkGens")
VariablesNum[tre] = TH1F(
tre + "-num", ";Dark Photon Pt [GeV];Acceptance x Efficiency", 26,
150, 800)
VariablesDen[tre] = TH1F(
tre + "-den", ";Dark Photon Pt [GeV];Acceptance x Efficiency", 26,
150, 800)
VariablesNum[tre].SetLineColor(colors[tre])
VariablesNum[tre].SetLineWidth(2)
treepj[tre].Draw("GenDarkPho_pt>>" + tre + "-num")
treeTrig[tre].Draw("GenDarkPho_pt>>" + tre + "-den")
VariablesNum[tre].Sumw2()
VariablesDen[tre].Sumw2()
VariablesNum[tre].Divide(VariablesDen[tre])
VariablesNum[tre].SetMaximum(10.0)
VariablesNum['df1en0'].Draw('e1')
VariablesNum['df1en1'].Draw('e1same')
VariablesNum['df1en2'].Draw('e1same')
VariablesNum['df1en3'].Draw('e1same')
led = TLegend(0.6, 0.6, 0.9, 0.9)
led.AddEntry(VariablesNum['df1en0'], "f_{D} = 1E0")
led.AddEntry(VariablesNum['df1en1'], "f_{D} = 1E-1")
led.AddEntry(VariablesNum['df1en2'], "f_{D} = 1E-2")
led.AddEntry(VariablesNum['df1en3'], "f_{D} = 1E-3")
led.SetFillColor(0)
led.Draw("same")
can.SaveAs("plots/aXe.pdf")
def plot_pt():
#ptbin = 0.03
#ptmax = 1.1
#ptbin = 1e-2
ptbin = 0.5e-2
ptmax = 0.11
mmin = 2.8
mmax = 3.2
east_1n = 120.3335
west_1n = 138.9685
strsel = "(jRecM>{0:.3f} && jRecM<{1:.3f})".format(mmin, mmax)
#strsel += " && (jZDCUnAttEast<{0:.3f} && jZDCUnAttWest<{1:.3f})".format(east_1n, west_1n)
strsel += " && (jZDCUnAttEast>{0:.3f} && jZDCUnAttWest>{1:.3f})".format(east_1n, west_1n)
can = ut.box_canvas()
hPt = ut.prepare_TH1D("hPt", ptbin, 0, ptmax)
#tree.Draw("jRecPt >> hPt", strsel)
tree.Draw("jRecPt*jRecPt >> hPt", strsel)
print("Entries: ", hPt.GetEntries())
hPt.Draw()
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_mlt():
#electron mlt = -log_10(pi-true_el_theta)
#mlt range
tbin = 0.1
tmin = -2
tmax = 8
hT = ut.prepare_TH1D("hT", tbin, tmin, tmax)
can = ut.box_canvas()
form = "-TMath::Log10(TMath::Pi()-true_el_theta)"
tree.Draw(form + " >> hT")
ut.put_yx_tit(hT, "Events", "mlt", 1.4, 1.2)
hT.Draw()
gPad.SetLogy()
gPad.SetGrid()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def hit_z():
#hit z position
#detector = "up"
#detector = "down"
detector = "phot"
#plot range
zbin = 1e-3
zmin = -0.1
zmax = 0.1
inp_lmon = TFile.Open("lmon.root")
tree = inp_lmon.Get(detector)
can = ut.box_canvas()
hZ = ut.prepare_TH1D("hZ", zbin, zmin, zmax)
tree.Draw("z >> hZ")
print("Entries:", hZ.GetEntries())
ut.set_H1D_col(hZ, rt.kBlue)
ut.put_yx_tit(hZ, "Counts", "Hit #it{z} (mm)", 1.5, 1.4)
ut.set_margin_lbtr(gPad, 0.11, 0.11, 0.02, 0.03)
gPad.SetGrid()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_Log10_Q2():
#plot the log_10(Q^2)
lqbin = 0.02
lqmin = -11
lqmax = 6
hLog10Q2 = ut.prepare_TH1D("hLog10Q2", lqbin, lqmin, lqmax)
tree.Draw("TMath::Log10(true_Q2) >> hLog10Q2")
#tree.Draw("TMath::Log10(gen_el_Q2) >> hLog10Q2")
can = ut.box_canvas()
gPad.SetGrid()
ut.put_yx_tit(hLog10Q2, "Events", "log_{10}(#it{Q}^{2})", 1.4, 1.2)
gPad.SetLogy()
hLog10Q2.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_E():
#electron energy
ebin = 0.01
emin = 0
emax = 20
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
#tree.Draw("gen_E >> hE")
tree.Draw("true_el_E >> hE")
can = ut.box_canvas()
ut.put_yx_tit(hE, "Events", "#it{E'}", 1.4, 1.2)
hE.Draw()
gPad.SetLogy()
gPad.SetGrid()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_theta():
#electron polar angle theta
#theta range, rad
tbin = 1e-3
#tmin = 0
#tmax = 0.2
tmin = 2.9
tmax = 3.15
hTheta = ut.prepare_TH1D("hTheta", tbin, tmin, tmax)
#tree.Draw("TMath::Pi()-true_el_theta >> hTheta")
tree.Draw("true_el_theta >> hTheta")
can = ut.box_canvas()
ut.put_yx_tit(hTheta, "Events", "#theta (rad)", 1.4, 1.2)
hTheta.Draw()
gPad.SetLogy()
gPad.SetGrid()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def el_eta_tag():
#electron pseudorapidity
etabin = 0.3
etamin = -20
etamax = 10
#sel = ""
#sel = "lowQ2s1_IsHit==1"
#sel = "lowQ2s2_IsHit==1"
sel = "lowQ2s1_IsHit==1 || lowQ2s2_IsHit==1"
can = ut.box_canvas()
hEta = ut.prepare_TH1D("hEta", etabin, etamin, etamax)
form = "-TMath::Log(TMath::Tan(true_el_theta/2.))"
#form = "-TMath::Log(TMath::Tan(el_theta/2.))"
tree.Draw(form + " >> hEta", sel)
gPad.SetGrid()
gPad.SetLogy()
hEta.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_Log10x_y():
#distribution of log_10(x) and y
xbin = 0.01
xmin = -13.5
xmax = -3.5
ybin = 5e-5
#ymin = 0.06
ymin = 0
ymax = 1.1
hXY = ut.prepare_TH2D("hXY", xbin, xmin, xmax, ybin, ymin, ymax)
can = ut.box_canvas()
tree.Draw("gen_y:TMath::Log10(gen_x) >> hXY")
#tree.Draw("gen_y:gen_u >> hXY")
ytit = "#it{y}" + " / {0:.3f}".format(ybin)
xtit = "log_{10}(x)" + " / {0:.3f}".format(xbin)
ut.put_yx_tit(hXY, ytit, xtit, 1.4, 1.4)
ut.set_margin_lbtr(gPad, 0.1, 0.11, 0.03, 0.12)
hXY.Draw()
gPad.SetLogy()
gPad.SetLogz()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def evt_Q2_theta():
#Q^2 and theta
qbin = 5e-6
qmin = 1e-10
qmax = 1e-1
tbin = 1e-4
tmin = 0
tmax = 0.011
qform = "2.*18.*el_gen*(1.-TMath::Cos(TMath::Pi()-el_theta))"
hQ2thetaTag = ut.prepare_TH2D("hQ2thetaTag", tbin, tmin, tmax, qbin, qmin,
qmax)
tree.Draw(qform + ":TMath::Pi()-el_theta >> hQ2thetaTag", gQ2sel)
ytit = "Q^{2} / 5x10^{-6} GeV^{2}"
xtit = "Polar angle #theta (rad) / {0:.2f} mrad".format(tbin * 1e3)
ut.put_yx_tit(hQ2thetaTag, ytit, xtit, 1.6, 1.4)
can = ut.box_canvas()
ut.set_margin_lbtr(gPad, 0.11, 0.1, 0.03, 0.11)
gPad.SetLogy()
gPad.SetLogz()
hQ2thetaTag.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def gen_ys():
#CM energy s * generated y as input to gamma-p total cross section
sqrt_s = 28.6 # GeV
#ys range
ysbin = 0.1
ysmin = 0
ysmax = 30
hYS = ut.prepare_TH1D("hYS", ysbin, ysmin, ysmax)
tree.Draw("true_y*" + str(sqrt_s) + " >> hYS")
can = ut.box_canvas()
ut.put_yx_tit(hYS, "Events", "#ys (GeV^{2})", 1.4, 1.2)
hYS.Draw()
gPad.SetLogy()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def evt_Log10_Q2_ecal_compare():
#compare log_10(Q^2) from ecal for two separate inputs
infile1 = "../data/ir6/lmon_pythia_5M_beff2_5Mevt_v2.root"
#infile2 = "../data/ir6_close/lmon_pythia_5M_beff2_close_5Mevt.root"
#infile2 = "../data/ir6/lmon_pythia_5M_beff2_1p5T_5Mevt.root"
infile2 = "../data/ir6/lmon_pythia_5M_beff2_1p5T_5Mevt_v2.root"
lqbin = 5e-2
lqmin = -2.5
lqmax = 2.5
inp1 = TFile.Open(infile1)
inp2 = TFile.Open(infile2)
tree1 = inp1.Get("DetectorTree")
tree2 = inp2.Get("DetectorTree")
hQ2ecal = ut.prepare_TH1D("hQ2ecal", lqbin, lqmin, lqmax)
hQ2ecal_close = ut.prepare_TH1D("hQ2ecal_close", lqbin, lqmin, lqmax)
tree1.Draw(gL10Q2 + " >> hQ2ecal", "ecal_IsHit==1")
tree2.Draw(gL10Q2 + " >> hQ2ecal_close", "ecal_IsHit==1")
print "All events:", hQ2ecal.GetEntries()
#print "Selected :", hLog10Q2Tag.GetEntries()
can = ut.box_canvas()
frame = gPad.DrawFrame(lqmin, 10, lqmax, 1e5)
frame.Draw()
ytit = "Events / {0:.3f}".format(lqbin)
ut.put_yx_tit(frame, ytit, "log_{10}(#it{Q}^{2})", 1.4, 1.2)
ut.set_margin_lbtr(gPad, 0.1, 0.1, 0.03, 0.02)
ut.line_h1(hQ2ecal, rt.kBlue, 3)
ut.line_h1(hQ2ecal_close, rt.kRed, 3)
#hQ2ecal.SetMinimum(10)
gPad.SetLogy()
gPad.SetGrid()
hQ2ecal.Draw("e1same")
hQ2ecal_close.Draw("e1same")
#hLog10Q2.SetMaximum(2e5) # for qr
leg = ut.prepare_leg(0.6, 0.83, 0.2, 0.1, 0.035)
#leg.AddEntry(hLog10Q2, "All electrons from quasi-real photoproduction", "l")
#leg.AddEntry(hLog10Q2, "All Pythia6 scattered electrons", "l")
#leg.AddEntry(hLog10Q2Tag, "Electrons hitting the tagger", "l")
leg.AddEntry(hQ2ecal, "Default geometry", "l")
#leg.AddEntry(hQ2ecal_close, "Magnets in central det", "l")
leg.AddEntry(hQ2ecal_close, "1.5T solenoid", "l")
leg.Draw("same")
#ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
def en_2n():
#energy for two neutrons in both + and - eta for mean of 2n energy
ebin = 2
emin = 0
emax = 500
can = ut.box_canvas()
hE = ut.prepare_TH1D("hE", ebin, emin, emax)
tree.Draw("epos >> hE", "npos == 2")
tree.Draw("eneg >>+ hE", "nneg == 2")
print "UO:", hE.GetBinContent(0), hE.GetBinContent(hE.GetNbinsX() + 1)
print "Mean:", hE.GetMean(), "+/-", hE.GetMeanError()
gPad.SetGrid()
gPad.SetLogy()
hE.Draw()
ut.invert_col(rt.gPad)
can.SaveAs("01fig.pdf")
