gLcOverD0.Draw('p')
gLcOverD0.Fit('fLcOverD0', 'r')
dfDplus = dfD0FONLL.copy()
for col in dfDplus.columns:
if col not in ['ptmin', 'ptmax']:
dfDplus[col] = dfDplus.apply(lambda x: x[col] * gDplusOverD0.Eval(
(x['ptmax'] + x['ptmin']) / 2),
axis=1)
dfDs = dfD0FONLL.copy()
for col in dfDs.columns:
if col not in ['ptmin', 'ptmax']:
dfDs[col] = dfDs.apply(lambda x: x[col] * gDsOverD0.Eval(
(x['ptmax'] + x['ptmin']) / 2),
axis=1)
dfLc = dfD0FONLL.copy()
for col in dfLc.columns:
if col not in ['ptmin', 'ptmax']:
dfLc[col] = dfLc.apply(lambda x: x[col] * gLcOverD0.Eval(
(x['ptmax'] + x['ptmin']) / 2),
axis=1)
dfDplus.to_csv('models/FONLLDataDriven-Dplus-pp14TeV-y05-measbins.txt',
sep=' ')
dfDs.to_csv('models/FONLLDataDriven-Ds-pp14TeV-y05-measbins.txt', sep=' ')
dfLc.to_csv('models/FONLLDataDriven-Lc-pp14TeV-y05-measbins.txt', sep=' ')
input('Press enter to exit')
def trigger_efficiency(year, separate=False):
from root_numpy import root2array, fill_hist
from aliases import triggers, triggers_PFHT, triggers_Jet, triggers_BTag
import numpy as np
#spec_triggers = {"PFHT": triggers_PFHT, "Jet": triggers_Jet, "BTag": triggers_BTag}
spec_triggers = {
"HT/Jet": "(" + triggers_PFHT + " || " + triggers_Jet + ")",
"BTag": triggers_BTag
}
spec_triggers_colors = {
"PFHT": 418,
"Jet": 4,
"BTag": 6,
"HT/Jet": 4,
"total": 2
}
hist_pass = TH1F("pass", "pass", 100, 0., 10000.)
if separate:
hist_pass_spec = {}
for trig in spec_triggers.keys():
hist_pass_spec[trig] = TH1F("pass_" + trig, "pass_" + trig, 100,
0., 10000.)
hist_all = TH1F("all", "all", 100, 0., 10000.)
file_list = []
data_2016_letters = ["B", "C", "D", "E", "F", "G", "H"]
data_2017_letters = ["B", "C", "D", "E", "F"]
data_2018_letters = ["A", "B", "C", "D"]
sample_names = []
if year == '2016':
letters = data_2016_letters
elif year == '2017':
letters = data_2017_letters
elif year == '2018':
letters = data_2018_letters
else:
print "unknown year"
sys.exit()
for letter in letters:
#dir_content = os.listdir(TRIGGERDIR+"/SingleMuon_{}_{}/".format(year, letter)) ## intended to run directly on ntuples
#for entry in dir_content:
# if "_flatTuple" in entry: file_list.append(TRIGGERDIR+"/SingleMuon_{}_{}/".format(year, letter)+entry)
file_list.append(TRIGGERDIR +
"/SingleMuon_{}_{}.root".format(year, letter))
print "appending:", TRIGGERDIR + "/SingleMuon_{}_{}.root".format(
year, letter)
for file_name in file_list:
temp_array = root2array(file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1")
fill_hist(hist_all, temp_array)
temp_array = root2array(file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1 && " +
triggers)
fill_hist(hist_pass, temp_array)
if separate:
for trig in spec_triggers.keys():
temp_array = root2array(
file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1 && " +
spec_triggers[trig])
fill_hist(hist_pass_spec[trig], temp_array)
temp_array = None
import array
from aliases import dijet_bins
binning = []
for num in dijet_bins:
if num <= 10000: binning.append(num)
#binning = range(0,1500,100)+range(1500,2000,100)+range(2000,3100,150)+range(3100,10000,300)
binning_ = array.array('d', binning)
hist_pass2 = hist_pass.Rebin(
len(binning_) - 1, "hist_pass_rebinned", binning_)
hist_all2 = hist_all.Rebin(
len(binning_) - 1, "hist_all_rebinned", binning_)
if separate:
hist_pass_spec2 = {}
for trig in spec_triggers.keys():
hist_pass_spec2[trig] = hist_pass_spec[trig].Rebin(
len(binning_) - 1, "hist_pass_" + trig + "_rebinned", binning_)
hist_pass2.Sumw2()
hist_all2.Sumw2()
eff = TGraphAsymmErrors()
eff.Divide(hist_pass2, hist_all2)
eff.SetMarkerColor(spec_triggers_colors["total"])
if separate:
eff.SetMarkerStyle(5)
else:
eff.SetMarkerStyle(1)
eff.SetLineColor(spec_triggers_colors["total"])
eff.SetLineWidth(2)
if separate:
eff_spec = {}
for trig in spec_triggers.keys():
hist_pass_spec2[trig].Sumw2()
eff_spec[trig] = TGraphAsymmErrors()
eff_spec[trig].Divide(hist_pass_spec2[trig], hist_all2)
eff_spec[trig].SetMarkerColor(spec_triggers_colors[trig])
eff_spec[trig].SetMarkerStyle(1)
eff_spec[trig].SetLineColor(spec_triggers_colors[trig])
eff_spec[trig].SetLineWidth(2)
one_line = TGraph()
one_line.SetPoint(0, 0., 1.)
one_line.SetPoint(1, 10000., 1.)
one_line.SetLineStyle(2)
c1 = TCanvas("c1", "Trigger Efficiency", 800, 800)
c1.cd(1)
eff.Draw("AP")
one_line.Draw("L")
eff.SetTitle(";m_{jj} (GeV);trigger efficiency")
eff.SetMinimum(0.)
eff.SetMaximum(1.4) #0.65
## new
dijet_bin_centers = []
for b, lthr in enumerate(dijet_bins[:-1]):
if lthr < 1200 or lthr > 2500: continue
dijet_bin_centers.append(0.5 * (dijet_bins[b] + dijet_bins[b + 1]))
print "total trigger efficiency:"
for cval in dijet_bin_centers:
print cval, ":", eff.Eval(cval)
## end new
if separate:
leg = TLegend(0.65, 0.75, 0.9, 0.95)
leg.AddEntry(eff, "total")
for trig in spec_triggers.keys():
leg.AddEntry(eff_spec[trig], trig + "-based")
eff_spec[trig].Draw("P SAME")
## new
print trig, "trigger efficiency"
for cval in dijet_bin_centers:
print cval, ":", eff_spec[trig].Eval(cval)
## end new
leg.Draw()
eff.GetXaxis().SetTitleSize(0.045)
eff.GetYaxis().SetTitleSize(0.045)
eff.GetYaxis().SetTitleOffset(1.1)
eff.GetXaxis().SetTitleOffset(1.05)
eff.GetXaxis().SetLimits(700., 5000.)
c1.SetTopMargin(0.05)
#drawCMS(-1, "Preliminary", year=year) #Preliminary
#drawCMS(-1, "Work in Progress", year=year, suppressCMS=True)
drawCMS(-1, "", year=year, suppressCMS=True)
drawAnalysis("")
suffix = ""
if separate: suffix = "_sep"
c1.Print("plots/Efficiency/trigger_" + year + suffix + ".pdf")
c1.Print("plots/Efficiency/trigger_" + year + suffix + ".png")
