def plot_deltaR(input_file, out_dir, refPtMin=0, internJet=False, append=""):
"""Plot deltaR distributions for various pT, eta bins"""
tree = cu.get_from_file(input_file, "valid")
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetLogz()
colours = [ROOT.kBlack, ROOT.kRed, ROOT.kBlue, ROOT.kGreen + 2]
# Plot deltaR for various pT, eta bins
for (eta_min, eta_max) in ([0, 0.348], [2.172, 3], [3.5, 4]):
eta_cut = "TMath::Abs(eta)>%g && TMath::Abs(eta)< %g" % (eta_min,
eta_max)
for ptVar in ["ptRef"]:
mg = ROOT.THStack(
"mg_%s_eta_%g_%g" % (ptVar, eta_min, eta_max),
"%g < |#eta^{L1}| < %g;#Delta R(L1, GenJet);" %
(eta_min, eta_max))
leg = ROOT.TLegend(0.6, 0.6, 0.88, 0.88)
for i, (pt_min, pt_max) in enumerate(
([14, 18], [26, 30], [42, 46], [70, 74])):
pt_cut = "%s > %g && %s < %g" % (ptVar, pt_min, ptVar, pt_max)
hname = "h_dr_%s_%g_%g_eta_%g_%g" % (ptVar, pt_min, pt_max,
eta_min, eta_max)
h_dr_pt = ROOT.TH1D(
hname,
"%g < %s < %g, %g < |#eta^{L1}| < %g;#Delta R(L1, GenJet);N"
% (pt_min, ptVar, pt_max, eta_min, eta_max), 35, 0, 0.7)
total_cut = "%s && %s" % (eta_cut, pt_cut)
print total_cut
tree.Draw("dr>>%s" % (hname), total_cut)
h_dr_pt.Scale(1. / h_dr_pt.Integral())
out_name = hname + ".pdf"
canv.SaveAs(out_dir + "/" + out_name)
h_dr_pt.SetLineColor(colours[i])
mg.Add(h_dr_pt)
leg.AddEntry(h_dr_pt, "%g < %s < %g" % (pt_min, ptVar, pt_max),
"L")
mg.Draw("NOSTACK HISTE")
mg.GetHistogram().SetTitle(
"%s < |#eta^{L1}| < %g;#Delta R(L1, GenJet);" %
(eta_min, eta_max))
leg.Draw()
out_name = mg.GetName() + ".pdf"
canv.SaveAs(out_dir + "/" + out_name)
def plot_response_nvtx(input_file, out_dir, nvtx_var="numPUVertices",
eta_min=0, eta_max=5, pt_min=0, pt_max=250, pt_var="pt", append=""):
"""Plot response as a function of number of vertices
nvtx_var is the variable that describes number of vertices, is normally
either numPUVertices or trueNumInteractions.
eta_min/max, pt_min/max are for cuts on TMath::Abs(eta) and pt.
pt_var is the variable name for the pt cut, so you can change the variable to cut on
"""
tree = cu.get_from_file(input_file, "valid")
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetTicks(1, 1)
# check nvtx_var in tree
if not hasattr(tree, nvtx_var):
raise RuntimeError("%s is not a valid branch name" % nvtx_var)
# cuts
eta_cut = "%f < TMath::Abs(eta) && TMath::Abs(eta) < %f" % (eta_min, eta_max)
pt_cut = "%f < %s && %s < %f" % (pt_min, pt_var, pt_var, pt_max)
cuts = [eta_cut, pt_cut]
total_cut = " && ".join(cuts)
print total_cut
# simple 2D plot of response vs nVtx
hname = "h_nvtx_rsp_eta_%g_%g_pt_%g_%g" % (eta_min, eta_max, pt_min, pt_max)
h_nvtx_rsp = ROOT.TH2D(hname,
"%g < |#eta| < %g, %g < %s < %g;%s;response ( = L1/Ref)" % (eta_min, eta_max, pt_min, pt_var, pt_max, nvtx_var),
40, 0, 40, 60, 0, 3)
tree.Draw("rsp:%s>>%s" % (nvtx_var, hname), total_cut, "COLZ")
# now permutate over log/norm
for norm, log in product([True, False], [True, False]):
canv.Clear()
append_new = append
if log:
canv.SetLogz(1)
append_new += "_log"
else:
canv.SetLogz(0)
if norm:
append_new += "_norm"
hnew = cu.norm_vertical_bins(h_nvtx_rsp)
hnew.Draw("COLZ")
else:
h_nvtx_rsp.Draw("COLZ")
canv.SaveAs(out_dir+"/%s%s.pdf" % (hname, append_new))
def plot_deltaR(input_file, out_dir, refPtMin=0, internJet=False, append=""):
"""Plot deltaR distributions for various pT, eta bins"""
tree = cu.get_from_file(input_file, "valid")
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetLogz()
colours = [ROOT.kBlack, ROOT.kRed, ROOT.kBlue, ROOT.kGreen+2]
# Plot deltaR for various pT, eta bins
for (eta_min, eta_max) in ([0, 0.348], [2.172,3], [3.5,4]):
eta_cut = "TMath::Abs(eta)>%g && TMath::Abs(eta)< %g" % (eta_min, eta_max)
for ptVar in ["ptRef"]:
mg = ROOT.THStack("mg_%s_eta_%g_%g" % (ptVar, eta_min, eta_max),
"%g < |#eta^{L1}| < %g;#Delta R(L1, GenJet);" % (eta_min, eta_max))
leg = ROOT.TLegend(0.6, 0.6, 0.88, 0.88)
for i, (pt_min, pt_max) in enumerate(([14, 18], [26, 30], [42, 46], [70, 74])):
pt_cut = "%s > %g && %s < %g" % (ptVar, pt_min, ptVar, pt_max)
hname = "h_dr_%s_%g_%g_eta_%g_%g" % (ptVar, pt_min, pt_max, eta_min, eta_max)
h_dr_pt = ROOT.TH1D(hname,
"%g < %s < %g, %g < |#eta^{L1}| < %g;#Delta R(L1, GenJet);N" % (pt_min, ptVar, pt_max, eta_min, eta_max),
35, 0, 0.7)
total_cut = "%s && %s" % (eta_cut, pt_cut)
print total_cut
tree.Draw("dr>>%s" % (hname), total_cut)
h_dr_pt.Scale(1./h_dr_pt.Integral())
out_name = hname+".pdf"
canv.SaveAs(out_dir+"/"+out_name)
h_dr_pt.SetLineColor(colours[i])
mg.Add(h_dr_pt)
leg.AddEntry(h_dr_pt, "%g < %s < %g" % (pt_min, ptVar, pt_max), "L")
mg.Draw("NOSTACK HISTE")
mg.GetHistogram().SetTitle("%s < |#eta^{L1}| < %g;#Delta R(L1, GenJet);" % (eta_min, eta_max))
leg.Draw()
out_name = mg.GetName()+".pdf"
canv.SaveAs(out_dir+"/"+out_name)
def plot_response_nvtx_binned(input_file,
out_dir,
no_pu_file,
nvtx_var="numPUVertices",
eta_min=0,
eta_max=5,
pt_min=0,
pt_max=250,
pt_var="pt",
append=""):
"""Make histogram of response for various bins of nVtx
no_pu_file is optional TFile for 0PU sample.
eta_min/max, pt_min/max are for cuts on TMath::Abs(eta) and pt.
pt_var is the variable name for the pt cut, so you can change the variable to cut on.
nvtx_var is the variable that describes number of vertices, is normally
either numPUVertices or trueNumInteractions.
"""
tree = cu.get_from_file(input_file, "valid")
tree_no_pu = cu.get_from_file(no_pu_file, "valid") if no_pu_file else None
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetTicks(1, 1)
# check nvtx_var in tree
if not hasattr(tree, nvtx_var):
raise RuntimeError("%s is not a valid branch name" % nvtx_var)
# cuts
eta_cut = "%f < TMath::Abs(eta) && TMath::Abs(eta) < %f" % (eta_min,
eta_max)
pt_cut = "%f < %s && %s < %f" % (pt_min, pt_var, pt_var, pt_max)
cuts = [eta_cut, pt_cut]
stack = ROOT.THStack("st", "")
nbins, rsp_min, rsp_max = 40, 0, 2
lw = 2
leg = ROOT.TLegend(0.56, 0.6, 0.87, 0.87)
# make hist if 0PU sample available
if no_pu_file:
hname = "h_rsp_eta_%g_%g_%s_%g_%g_no_pu" % (eta_min, eta_max, pt_var,
pt_min, pt_max)
h = ROOT.TH1D(
hname, "%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." %
(eta_min, eta_max, pt_min, pt_var, pt_max), nbins, rsp_min,
rsp_max)
total_cut = " && ".join(cuts)
print total_cut
tree_no_pu.Draw("rsp>>%s" % hname, total_cut)
h.Scale(1. / h.Integral())
h.SetLineColor(ROOT.kBlack)
h.SetLineWidth(lw)
h.SetMarkerColor(ROOT.kBlack)
leg.AddEntry(h, "nVtx: 0 (0PU sample)", "L")
stack.Add(h)
# make hist for each nVtx bin
nvtx_bins = ([0, 10], [15, 25], [30, 40])
colours = [ROOT.kRed, ROOT.kGreen + 2, ROOT.kBlue]
for i, (nvtx_min, nvtx_max) in enumerate(nvtx_bins):
hname = "h_rsp_eta_%g_%g_%s_%g_%g_nvtx_%g_%g" % (
eta_min, eta_max, pt_var, pt_min, pt_max, nvtx_min, nvtx_max)
h = ROOT.TH1D(
hname, "%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." %
(eta_min, eta_max, pt_min, pt_var, pt_max), nbins, rsp_min,
rsp_max)
nvtx_cut = "%f < %s && %s < %f" % (nvtx_min, nvtx_var, nvtx_var,
nvtx_max)
total_cut = " && ".join(chain(cuts, [nvtx_cut]))
print total_cut
tree.Draw("rsp>>%s" % hname, total_cut)
h.Scale(1. / h.Integral())
h.SetLineColor(colours[i])
h.SetLineWidth(lw)
h.SetMarkerColor(colours[i])
leg.AddEntry(h, "nVtx: %g - %g" % (nvtx_min, nvtx_max), "L")
stack.Add(h)
canv.Clear()
stack.Draw("NOSTACK HISTE")
stack.GetHistogram().SetTitle(
"%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." %
(eta_min, eta_max, pt_min, pt_var, pt_max))
stack.GetHistogram().GetYaxis().SetTitleOffset(1.1)
leg.Draw()
canv.SaveAs(out_dir + "/h_rsp_eta_%g_%g_%s_%g_%g%s.pdf" %
(eta_min, eta_max, pt_var, pt_min, pt_max, append))
def plot_response_nvtx(input_file,
out_dir,
nvtx_var="numPUVertices",
eta_min=0,
eta_max=5,
pt_min=0,
pt_max=250,
pt_var="pt",
append=""):
"""Plot response as a function of number of vertices
nvtx_var is the variable that describes number of vertices, is normally
either numPUVertices or trueNumInteractions.
eta_min/max, pt_min/max are for cuts on TMath::Abs(eta) and pt.
pt_var is the variable name for the pt cut, so you can change the variable to cut on
"""
tree = cu.get_from_file(input_file, "valid")
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetTicks(1, 1)
# check nvtx_var in tree
if not hasattr(tree, nvtx_var):
raise RuntimeError("%s is not a valid branch name" % nvtx_var)
# cuts
eta_cut = "%f < TMath::Abs(eta) && TMath::Abs(eta) < %f" % (eta_min,
eta_max)
pt_cut = "%f < %s && %s < %f" % (pt_min, pt_var, pt_var, pt_max)
cuts = [eta_cut, pt_cut]
total_cut = " && ".join(cuts)
print total_cut
# simple 2D plot of response vs nVtx
hname = "h_nvtx_rsp_eta_%g_%g_pt_%g_%g" % (eta_min, eta_max, pt_min,
pt_max)
h_nvtx_rsp = ROOT.TH2D(
hname, "%g < |#eta| < %g, %g < %s < %g;%s;response ( = L1/Ref)" %
(eta_min, eta_max, pt_min, pt_var, pt_max, nvtx_var), 40, 0, 40, 60, 0,
3)
tree.Draw("rsp:%s>>%s" % (nvtx_var, hname), total_cut, "COLZ")
# now permutate over log/norm
for norm, log in product([True, False], [True, False]):
canv.Clear()
append_new = append
if log:
canv.SetLogz(1)
append_new += "_log"
else:
canv.SetLogz(0)
if norm:
append_new += "_norm"
hnew = cu.norm_vertical_bins(h_nvtx_rsp)
hnew.Draw("COLZ")
else:
h_nvtx_rsp.Draw("COLZ")
canv.SaveAs(out_dir + "/%s%s.pdf" % (hname, append_new))
def plot_response_nvtx_binned(input_file, out_dir, no_pu_file, nvtx_var="numPUVertices",
eta_min=0, eta_max=5, pt_min=0, pt_max=250, pt_var="pt", append=""):
"""Make histogram of response for various bins of nVtx
no_pu_file is optional TFile for 0PU sample.
eta_min/max, pt_min/max are for cuts on TMath::Abs(eta) and pt.
pt_var is the variable name for the pt cut, so you can change the variable to cut on.
nvtx_var is the variable that describes number of vertices, is normally
either numPUVertices or trueNumInteractions.
"""
tree = cu.get_from_file(input_file, "valid")
tree_no_pu = cu.get_from_file(no_pu_file, "valid") if no_pu_file else None
canv = ROOT.TCanvas("canv", "", 800, 600)
canv.SetTicks(1, 1)
# check nvtx_var in tree
if not hasattr(tree, nvtx_var):
raise RuntimeError("%s is not a valid branch name" % nvtx_var)
# cuts
eta_cut = "%f < TMath::Abs(eta) && TMath::Abs(eta) < %f" % (eta_min, eta_max)
pt_cut = "%f < %s && %s < %f" % (pt_min, pt_var, pt_var, pt_max)
cuts = [eta_cut, pt_cut]
stack = ROOT.THStack("st", "")
nbins, rsp_min, rsp_max = 40, 0, 2
lw = 2
leg = ROOT.TLegend(0.56, 0.6, 0.87, 0.87)
# make hist if 0PU sample available
if no_pu_file:
hname = "h_rsp_eta_%g_%g_%s_%g_%g_no_pu" % (eta_min, eta_max, pt_var, pt_min, pt_max)
h = ROOT.TH1D(hname,
"%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." % (eta_min, eta_max, pt_min, pt_var, pt_max),
nbins, rsp_min, rsp_max)
total_cut = " && ".join(cuts)
print total_cut
tree_no_pu.Draw("rsp>>%s" % hname, total_cut)
h.Scale(1. / h.Integral())
h.SetLineColor(ROOT.kBlack)
h.SetLineWidth(lw)
h.SetMarkerColor(ROOT.kBlack)
leg.AddEntry(h, "nVtx: 0 (0PU sample)", "L")
stack.Add(h)
# make hist for each nVtx bin
nvtx_bins = ([0, 10], [15, 25], [30, 40])
colours = [ROOT.kRed, ROOT.kGreen+2, ROOT.kBlue]
for i, (nvtx_min, nvtx_max) in enumerate(nvtx_bins):
hname = "h_rsp_eta_%g_%g_%s_%g_%g_nvtx_%g_%g" % (eta_min, eta_max, pt_var, pt_min, pt_max, nvtx_min, nvtx_max)
h = ROOT.TH1D(hname,
"%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." % (eta_min, eta_max, pt_min, pt_var, pt_max),
nbins, rsp_min, rsp_max)
nvtx_cut = "%f < %s && %s < %f" % (nvtx_min, nvtx_var, nvtx_var, nvtx_max)
total_cut = " && ".join(chain(cuts, [nvtx_cut]))
print total_cut
tree.Draw("rsp>>%s" % hname, total_cut)
h.Scale(1. / h.Integral())
h.SetLineColor(colours[i])
h.SetLineWidth(lw)
h.SetMarkerColor(colours[i])
leg.AddEntry(h, "nVtx: %g - %g" % (nvtx_min, nvtx_max), "L")
stack.Add(h)
canv.Clear()
stack.Draw("NOSTACK HISTE")
stack.GetHistogram().SetTitle("%g < |#eta| < %g, %g < %s < %g;response (=L1/ref);p.d.f." % (eta_min, eta_max, pt_min, pt_var, pt_max))
stack.GetHistogram().GetYaxis().SetTitleOffset(1.1)
leg.Draw()
canv.SaveAs(out_dir+"/h_rsp_eta_%g_%g_%s_%g_%g%s.pdf" % (eta_min, eta_max, pt_var, pt_min, pt_max, append))
