def plotAll(file):
outDir = file[:-5] + '/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotAll/"
if not os.path.exists(outDir):
os.mkdir(outDir)
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFile = TFile.Open(file, "READ")
keyList = [key.GetName()
for key in inFile.GetListOfKeys()] #List of top level objects
dirList = [key for key in keyList
if "Iteration" in key] #List of all directories
nomDir = [dir for dir in dirList if "Nominal" in dir]
if (not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDir = inFile.Get(nomDir[0])
c1 = TCanvas()
##################### Plot every single histogram #################################
print "Plotting All Histograms for "
for dir in dirList:
if not "Nominal" in dir:
continue
print " ", dir
if not os.path.exists(outDir + dir):
os.mkdir(outDir + dir)
if not os.path.exists(outDir + dir + '/eps'):
os.mkdir(outDir + dir + '/eps')
thisDir = inFile.Get(dir)
histList = [key.GetName() for key in thisDir.GetListOfKeys()]
### Save all histograms ###
for histName in histList:
print dir, histName
thisHist = thisDir.Get(histName)
if ("Pt" in histName):
thisHist.GetXaxis().SetRangeUser(0, 2000.)
if (not "Nominal" in dir):
nomHist = nomDir.Get(histName)
thisHist.Add(nomHist, -1)
thisHist.Divide(nomHist)
thisHist.GetYaxis().SetTitle("Relative Difference w/ Nominal")
if type(thisHist) == TH2F or type(thisHist) == TH3F:
thisHist.Draw("colz")
else:
thisHist.Draw()
c1.SaveAs(outDir + dir + "/" + thisHist.GetName() + ".png")
c1.SaveAs(outDir + dir + "/eps/" + thisHist.GetName() + ".eps")
c1.Clear()
inFile.Close()
def main():
AtlasStyle.SetAtlasStyle()
gROOT.SetBatch()
parser = argparse.ArgumentParser(description='Error Analysis for TRT logs, input grafana mu dumps and ers log.')
parser.add_argument('-d', '--dir', dest='dir', default='2018', type=str, help="Directory of grafana mu dumps")
parser.add_argument('-f', '--file', dest='log_file', default='', type=str, help="Log file from ERS.")
parser.add_argument('-s', '--print_sb', dest='print_sb', default=False, action='store_true', help="print sb times")
parser.add_argument('-n', '--non_sb',dest='non_sb', default=False, action='store_true', help="get errors for non-sb times")
parser.add_argument('-t', '--text',dest='text_filter', default='rocketio problem', type=str, help="text to filter query")
parser.add_argument('-b', '--date_beg',dest='date_beg', default='2015-04-01 00:00:00', type=str, help="date begin. Formatted yyyy-mm-dd hh:mm:ss format")
parser.add_argument('-e', '--date_end',dest='date_end', default='2100-01-01 00:00:00', type=str, help="date end. Formatted yyyy-mm-dd hh:mm:ss format")
args = parser.parse_args()
if args.print_sb:
beg_sb, end_sb = getsb.get_sb_list(args.dir, args.print_sb)
if args.log_file != '':
beg_sb, end_sb = getsb.get_sb_list(args.dir, args.print_sb)
dbhandler.add_to_db(beg_sb, end_sb, args.log_file)
query_errors = dbhandler.get_query(args.non_sb, args.text_filter, args.date_beg, args.date_end)
print "Query returned " + repr(len(query_errors)) + " results!"
if('rocketio' in args.text_filter):
parse_rocketio_errors(query_errors)
import AtlasStyle
import ROOT
import BasicConfig
import utils
from datetime import date
if __name__ == '__main__':
AtlasStyle.SetAtlasStyle()
mass_list = range(600, 1801, 200)
tfiles = [
utils.open_tfile(
BasicConfig.workdir +
'SysUnc_ISR/SysUnc_ISR_{:04d}_weight.root'.format(mass))
for mass in mass_list
]
c = ROOT.TCanvas('c', 'c', 1000, 800)
c.SetLogx()
tf_out = ROOT.TFile(
BasicConfig.workdir + 'SysUnc_ISR/SysUnc_ISR_weight.root', 'recreate')
for ii, (tfile, mass) in enumerate(zip(tfiles, mass_list)):
tfile.cd()
c2 = ROOT.gROOT.FindObject('c2')
hist = c2.GetPrimitive('ggSystem_SysUnc_ISR')
hist.SetName('ggSystem_SysUnc_ISR_' + str(mass))
utils.decorate_histogram(hist, BasicConfig.colors[ii])
c.cd()
def make_systematic_table():
AtlasStyle.SetAtlasStyle()
#directory = '/afs/cern.ch/work/k/kmotohas/DisplacedVertex/DV_xAODAnalysis/submitDir_LSF/mc/hist_DVPlusMETSys/'
#directory = BasicConfig.workdir + 'hist_DVPlusMETSys/'
directory = '/home/motohash/data/mc15_13TeV/DVPlusMETSys/'
#tfile = TFile(BasicConfig.workdir + 'systTree.root')
tfile = TFile(args.inputFile)
key_list_all = [key.GetName() for key in gDirectory.GetListOfKeys()]
print(len(key_list_all), key_list_all)
regex = re.compile('Nominal|PRW|JET|MET.*')
key_list = [key for key in key_list_all if re.match(regex, key)]
print(len(key_list), key_list)
tfile.Close()
output_tfile = TFile('systematic_summary_SimpleMETFilter.root', 'recreate')
#tchains = [[dsid, [TChain(key, key+str(dsid)) for key in key_list]] for dsid in range(402700, 402740)]
tchains = [[dsid, [TChain(key, key + str(dsid)) for key in key_list]]
for dsid in mc.parameters.keys()]
#tchains = [[dsid, [TChain(key, key+str(dsid)) for key in key_list]] for dsid in range(402070, 402080)]
#tchains = [[dsid, [TChain(key, key+str(dsid)) for key in key_list]] for dsid in range(402070, 402080)]
#trees = [gROOT.FindObject(key) for key in key_list]
#entries_list = [tree.GetEntriesFast() for tree in trees]
gStyle.SetHistMinimumZero()
for dsid, each_tchain in tchains:
print('')
print(dsid)
#print glob(directory + 'systTree_mc15_13TeV.' + str(dsid) + '*.root')
for tchain in each_tchain:
for input in glob(directory + 'systTree_mc15_13TeV.' + str(dsid) +
'*.root'):
#print(input)
tchain.Add(input)
#h_syst_diff = TH1F('syst_diff', ';Difference from Nominal', 101, -50.5, 50.5, 120, 0, 120)
h_syst_diff = TH1F('syst_diff',
';;(N_{shifted} - N_{nominal}) / N_{nominal}',
len(key_list) + 1, 0,
len(key_list) + 1)
for ii, key in enumerate(key_list):
h_syst_diff.GetXaxis().SetBinLabel(ii + 1, key)
h_syst_diff.GetXaxis().SetBinLabel(
len(key_list) + 1, 'ISR_Py2MG_SF_removed')
h_syst_diff.SetMinimum(-0.3)
h_syst_diff.SetMaximum(0.3)
n_events_nominal = 0.
for ii, tchain in enumerate(each_tchain):
#print('')
print('*** ' + key_list[ii])
n_events_weighted = 0.
n_events_weighted_noISR = 0.
entries = tchain.GetEntries()
if entries == 0:
continue
for entry in xrange(entries):
## get the next tree in the chain and verify
ientry = tchain.LoadTree(entry)
if ientry < 0:
break
## copy next entry into memory and verify
nb = tchain.GetEntry(entry)
if nb <= 0:
continue
#if pass_event_cut(tchain, 7):
#if pass_event_cut(tchain, 5) and tchain.MET > 220 and tchain.PassCut7: # TODO
if pass_event_cut(tchain, len(cut_flow) - 1): # TODO
#if pass_event_cut(tchain, 5) and tchain.MET > 250 and tchain.PassCut7: # TODO
#print(tree.McEventWeight, tree.PileupWeight)
n_events_weighted += tchain.McEventWeight * tchain.PileupWeight * tchain.ISRWeight
n_events_weighted_noISR += tchain.McEventWeight * tchain.PileupWeight
if ii == 0:
n_events_nominal = n_events_weighted
if n_events_nominal < 1e-4:
h_syst_diff.SetBinContent(len(key_list) + 1, 0)
else:
h_syst_diff.SetBinContent(
len(key_list) + 1,
float((n_events_weighted_noISR - n_events_nominal) /
n_events_nominal))
diff = n_events_weighted - n_events_nominal
#print(n_events_nominal, n_events_weighted, diff)
if n_events_nominal < 1e-4:
h_syst_diff.SetBinContent(ii + 1, 0)
else:
h_syst_diff.SetBinContent(ii + 1,
float(diff / n_events_nominal))
#h_syst_diff.SetBinError(ii+1, n_event_weighted-n_events_nominal)
utils.decorate_histogram(h_syst_diff, kPink, fill_style=3001)
h_syst_diff.SetBarWidth(0.9)
h_syst_diff.GetXaxis().SetLabelSize(0.035)
output_tfile.cd()
h_syst_diff.SetName('systematic_table_' + str(dsid))
h_syst_diff.Write()
def fill_ntuple():
print('*** starting fill_ntuple() ')
AtlasStyle.SetAtlasStyle()
# # get key list
# tfile = TFile(BasicConfig.workdir + 'systTree.root')
# key_list_all = [key.GetName() for key in gDirectory.GetListOfKeys()]
# regex = re.compile('PRW|JET|MET.*')
# key_list = [key for key in key_list_all if re.match(regex, key)]
# tfile.Close()
# start making ttree
#output_tfile = TFile('rhadron_v06-00-05.root', 'recreate')
output_tfile = TFile(args.outputFile, 'recreate')
# initialize TTree
tree = TTree('rhadron', 'tree of rhadron properties for limit setting')
# leaf variables
from array import array
mass_gluino = array('f', [0.])
delta_mass = array('f', [0.])
ctau = array('f', [0.])
eff = array('f', [0.])
eff_stat_error = array('f', [0.])
eff_syst_error = array('f', [0.])
eff_syst_error_ISR = array('f', [0.])
eff_syst_error_PRW = array('f', [0.])
eff_syst_error_JET = array('f', [0.])
eff_syst_error_MET = array('f', [0.])
# set branch
tree.Branch("mGluino", mass_gluino, 'mGluino/F')
tree.Branch("deltaM", delta_mass, 'deltaM/F')
tree.Branch("ctau", ctau, 'ctau/F')
tree.Branch("eff", eff, 'eff/F')
tree.Branch("effRelStatErr", eff_stat_error, 'effRelStatErr/F')
tree.Branch("effRelSystErr", eff_syst_error, 'effRelSystErr/F')
tree.Branch("effRelSystErrISR", eff_syst_error_ISR, 'effRelSystErrISR/F')
tree.Branch("effRelSystErrPRW", eff_syst_error_PRW, 'effRelSystErrPRW/F')
tree.Branch("effRelSystErrJET", eff_syst_error_JET, 'effRelSystErrJET/F')
tree.Branch("effRelSystErrMET", eff_syst_error_MET, 'effRelSystErrMET/F')
#directory = '/afs/cern.ch/work/k/kmotohas/DisplacedVertex/DV_xAODAnalysis/submitDir_LSF/mc/hist_DVPlusMETSys/'
#directory = BasicConfig.workdir + 'hist_DVPlusMETSys/'
#directory = '/home/motohash/data/mc15_13TeV/DVPlusMETSys/v06-00-05/'
#tfile = TFile(args.referenceFile)
tfile = TFile(args.inputFile)
key_list_all = [key.GetName() for key in gDirectory.GetListOfKeys()]
print(len(key_list_all), key_list_all)
regex = re.compile('Nominal|PRW|JET|MET.*')
key_list = [key for key in key_list_all if re.match(regex, key)]
print(len(key_list), key_list)
tfile.Close()
#c = 299792458. # [m/s]
#tchains = [[dsid, TChain('Nominal', str(dsid))] for dsid in range(402700, 402740)]
#tchains = [[dsid, TChain('Nominal', str(dsid))] for dsid in mc.parameters.keys()]
#tchains = [[dsid, [TChain(key, key+str(dsid)) for key in key_list]] for dsid in mc.parameters.keys()]
dsids = [args.DSID]
tchains = [[dsid, [TChain(key, key + str(dsid)) for key in key_list]]
for dsid in dsids]
cut_flow = [
'Initial', 'Trigger', 'Filter', 'Cleaning', 'GRL', 'PV', 'NCB veto',
'MET', 'DV Selection'
]
#systematic_tables = TFile('systematic_summary_SimpleMETFilter.root', 'open')
#table = TH1F()
m_MET_min = 250.
# loop over dsid
try:
for dsid, each_tchain in tchains:
print('')
print(dsid)
#index = 0
#for input in glob(directory + 'systTree_' + str(dsid) + '_*.root'):
for tchain in each_tchain:
#for input_file in glob(directory+'systTree_mc15_13TeV.' + str(dsid) + '*.root'):
# print(input_file)
# tchain.Add(input_file)
tchain.Add(args.inputFile)
mass_gluino[0] = mc.parameters[dsid]['g']
delta_mass[0] = mass_gluino[0] - mc.parameters[dsid]['chi0']
n_reweight_steps = 40
xmin = 1.
xmax = 10000.
ratio = xmax / xmin
bins = []
for ii in range(n_reweight_steps):
bins.append(
xmax *
10**(ii * TMath.Log10(xmax / xmin) / n_reweight_steps -
TMath.Log10(xmax / xmin)))
#n_passed_w1 = [0. for _ in range(n_reweight_steps)]
#n_passed = [0. for _ in range(n_reweight_steps)]
from array import array
limitsLifetime = array('d', bins)
#
tefficiency = [[
TEfficiency('tefficiency_{0}_{1}_{2}'.format(key, step, dsid),
';c#tau [mm]; Event-level efficiency',
len(limitsLifetime) - 1, limitsLifetime)
for step in range(n_reweight_steps)
] for key in key_list]
#h_syst_diff = [[TH1F('syst_diff_{0}_{1}_{2}'.format(key, step, dsid), ';;(N_{shifted} - N_{nominal}) / N_{nominal}', len(key_list)+1, 0, len(key_list)+1)
# for step in range(n_reweight_steps)] for key in key_list]
h_syst_diff = [
TH1F('syst_diff_{0}_{1}_{2}'.format(key, step, dsid),
';;(N_{shifted} - N_{nominal}) / N_{nominal}',
len(key_list) + 1, 0,
len(key_list) + 1) for step in range(n_reweight_steps)
]
for step in range(n_reweight_steps):
for jj, key in enumerate(key_list):
h_syst_diff[step].GetXaxis().SetBinLabel(jj + 1, key)
h_syst_diff[step].GetXaxis().SetBinLabel(
len(key_list) + 1, 'ISR_Py2MG_SF_removed')
n_events_weighted = [[0. for _ in range(n_reweight_steps)]
for key in key_list]
n_events_weighted_noISR = [[0. for _ in range(n_reweight_steps)]
for key in key_list]
# loop over tchain of each systematic
for ii, tchain in enumerate(each_tchain):
entries = tchain.GetEntries()
print('*** processed systs: {0} / {1}'.format(
ii, len(each_tchain)))
#n_reweight_steps = 50
#for step in range(n_reweight_steps):
# tefficiency.append(TEfficiency('tefficiency_'+str(step), ';c#tau [mm]; Event-level efficiency',
# len(limitsLifetime)-1, limitsLifetime))
# h_syst_diff.append(TH1F('syst_diff_'+str(step), ';;(N_{shifted} - N_{nominal}) / N_{nominal}', len(key_list)+1, 0, len(key_list)+1))
for step in range(n_reweight_steps):
tefficiency[ii][step].SetUseWeightedEvents()
#for jj, key in enumerate(key_list):
# h_syst_diff[ii][step].GetXaxis().SetBinLabel(jj+1, key)
#h_syst_diff[ii][step].GetXaxis().SetBinLabel(len(key_list)+1, 'ISR_Py2MG_SF_removed')
# h_syst_diff[step].SetMinimum(-0.3)
# h_syst_diff[step].SetMaximum(0.3)
if entries == 0:
continue
for entry in range(entries):
#if entry % 1000 == 0:
# print('* processed events: {0} / {1}'.format(entry, entries))
utils.show_progress(entry, entries)
#if entry == 605:
# break
# get the next tree in the chain and verify
ientry = tchain.LoadTree(entry)
if ientry < 0:
break
# copy next entry into memory and verify
nb = tchain.GetEntry(entry)
if nb <= 0:
continue
event_weight = tchain.McEventWeight * tchain.PileupWeight * tchain.ISRWeight
ctau_MC = TMath.C(
) * mc.parameters[dsid]['t'] * 1e-9 # [nm]->[m]
for step in range(n_reweight_steps):
#print(tchain.GetListOfBranches())
pass_all = pass_event_cut(tchain, len(cut_flow) - 1)
if pass_all:
matched = False
for idv in range(len(tchain.DV_x)):
matched = matched or match(
tchain, idv, cut=1.0)
#print('pass_all is ', pass_all, ', matched is ', matched)
pass_all = pass_all and matched
target_ctau = xmax * 10**(
step * TMath.Log10(xmax / xmin) / n_reweight_steps
- TMath.Log10(xmax / xmin)) * 1e-3 # [mm]->[m]
#print(target_ctau)
lifetime_weight = get_lifetime_weight(
tchain, target_ctau, ctau_MC)
n_events_weighted[ii][
step] += event_weight * lifetime_weight
n_events_weighted_noISR[ii][
step] += tchain.McEventWeight * tchain.PileupWeight * lifetime_weight
#print(event_weight)
#print(event_weight*lifetime_weight)
#print(pass_all)
tefficiency[ii][step].FillWeighted(
pass_all, event_weight * lifetime_weight,
target_ctau * 1e3)
# end of loop over entries of each TChain
# end loop over tchain of each systematic
for step in range(n_reweight_steps):
n_events_nominal = [0. for _ in range(n_reweight_steps)]
for ii in range(len(each_tchain)):
# if Nominal TTree, set syst diff of ISR as well
if ii == 0:
n_events_nominal[step] = n_events_weighted[ii][step]
if n_events_nominal[step] < 1e-4:
#h_syst_diff[ii][step].SetBinContent(len(key_list)+1, 0)
h_syst_diff[step].SetBinContent(
len(key_list) + 1, 0)
else:
#h_syst_diff[ii][step].SetBinContent(len(key_list)+1,
h_syst_diff[step].SetBinContent(
len(key_list) + 1,
float((n_events_weighted_noISR[ii][step] -
n_events_nominal[step]) /
n_events_nominal[step]))
#float((n_events_weighted[ii][step]-n_events_nominal[step])/n_events_nominal[step]))
diff = n_events_weighted[ii][step] - n_events_nominal[step]
#print(n_events_nominal, n_events_weighted, diff)
if n_events_nominal[step] < 1e-4:
#h_syst_diff[ii][step].SetBinContent(ii+1, 0)
h_syst_diff[step].SetBinContent(ii + 1, 0)
else:
#h_syst_diff[ii][step].SetBinContent(ii+1, float(diff/n_events_nominal[step]))
h_syst_diff[step].SetBinContent(
ii + 1, float(diff / n_events_nominal[step]))
#systematic_tables.GetObject('systematic_table_'+str(dsid), table)
#syst_up, syst_down = root_sum_squares(table, 'x')
#systs = root_sum_squares(h_syst_diff[ii][step], 'x')
systs = root_sum_squares(h_syst_diff[step], 'x')
#eff_syst_error[0] = max(syst_up, syst_down) # TODO
#eff_syst_error[0] = (syst_up**2 + syst_down**2)**0.5
#### ############################
eff_syst_error[0] = (systs[0]**2 + systs[1]**2)**0.5
eff_syst_error_ISR[0] = systs[2]
eff_syst_error_PRW[0] = systs[3]
eff_syst_error_JET[0] = systs[4]
eff_syst_error_MET[0] = systs[5]
if eff_syst_error[0] > 1:
print('eff_syst_error[0] = ' + str(eff_syst_error[0]))
#eff_syst_error[0] = 1.
#for step in range(n_reweight_steps):
#for ct in bins:
# print(len(bins), bins)
#print(n_total_w1[step], n_total[step])
#sf = n_total_w1[step] / n_total[step]
#n_passed[step] *= sf
#n_total[step] *= sf
#eff_no_weight, stat_error_no_weight = utils.division_error_propagation(n_passed_w1[step], n_total_w1[step])
#ctau[0] = TMath.Power(300, step/float(n_reweight_steps-1)) * 1e-3 # [mm]->[m]
ct = bins[step]
#print(ct)
ctau[0] = ct * 1e-3 # [mm]->[m]
#print(ctau[0])
bin_ctau = tefficiency[0][step].GetPassedHistogram().FindBin(
ct)
print(tefficiency[0][step].GetPassedHistogram().GetBinContent(
bin_ctau))
print(tefficiency[0][step].GetTotalHistogram().GetBinContent(
bin_ctau))
#print(bin_ctau)
#print('ct', ct, 'bin_ctau', bin_ctau)
eff[0] = tefficiency[0][step].GetEfficiency(bin_ctau)
print(eff[0])
abs_stat_error = (
tefficiency[0][step].GetEfficiencyErrorLow(bin_ctau)**2 +
tefficiency[0][step].GetEfficiencyErrorUp(bin_ctau)**
2)**0.5
#eff[0], abs_stat_error = utils.binomial_ratio_and_error(n_passed[step], n_total[step])
#if eff[0] < 1e-4:
if eff[0] == 0:
eff_stat_error[
0] = 1. # avoid zero division error and divergence
continue # not fill values in tree if efficiency is too small
else:
eff_stat_error[0] = abs_stat_error / eff[0]
#if eff_stat_error[0] > 1:
# print(n_passed[step], n_total[step], abs_stat_error, eff[0], eff_stat_error[0])
# eff_stat_error[0] = 1.
tree.Fill()
# end loop over n_reweight_steps
except KeyboardInterrupt:
pass
output_tfile.Write()
output_tfile.Close()
def create_cut_flow():
AtlasStyle.SetAtlasStyle()
#input_tfile = utils.open_tfile(BasicConfig.workdir + 'DVTree_NTuple_data15_13TeV.root')
#tree = input_tfile.Get('DVTree_NTuple')
input_tfile = utils.open_tfile(args.inputFile)
tree = input_tfile.Get('Nominal')
cut_flow = [
'Initial', 'Trigger', 'Filter', 'Cleaning', 'GRL', 'PV', 'NCB veto',
'MET', 'DV Selection'
]
h_cut_flow = TH1F('cut_flow', ';;Number of Events', len(cut_flow), 0,
len(cut_flow))
#h_cut_flow2 = TH1F('cut_flow2', ';;Number of Events', len(cut_flow), 0, len(cut_flow))
for bin, cut in enumerate(cut_flow):
h_cut_flow.GetXaxis().SetBinLabel(bin + 1, cut)
#
entries = tree.GetEntries()
for entry in range(entries):
#if entry % 10000 == 0:
# print('*** processed {0} out of {1}'.format(entry, entries))
utils.show_progress(entry, entries)
#if entry == 100000:
# break
# get the next tree in the chain and verify
ientry = tree.LoadTree(entry)
if ientry < 0:
break
# copy next entry into memory and verify
nb = tree.GetEntry(entry)
if nb <= 0:
continue
event_weight = tree.McEventWeight * tree.PileupWeight * tree.ISRWeight
for step, cut in enumerate(cut_flow):
if step == 0:
h_cut_flow.Fill(cut, event_weight)
#h_cut_flow2.Fill(cut, event_weight)
#elif step == 2:
# if tree.RandomRunNumber < 309311 and pass_event_cut(tree, 2):
# h_cut_flow.Fill(cut, event_weight)
# if tree.RandomRunNumber > 309311 and pass_event_cut(tree, 2):
# h_cut_flow2.Fill(cut, event_weight)
#elif step == 6:
# if tree.RandomRunNumber < 309311 and pass_event_cut(tree, 6):
# h_cut_flow.Fill(cut, event_weight)
# if tree.RandomRunNumber > 309311 and pass_event_cut(tree, 6):
# h_cut_flow2.Fill(cut, event_weight)
#elif step == 7:
# #have_signal_like_dv = False
# #for dv_index in range(len(tree.DV_passVtxCuts)):
# # have_signal_like_dv = have_signal_like_dv or tree.DV_passVtxCuts[dv_index]
# #if pass_event_cut(tree, 7) and tree.MET > 220 and have_signal_like_dv:
# if tree.RandomRunNumber < 309311 and pass_event_cut(tree, 7):
# h_cut_flow.Fill(cut, event_weight)
# if tree.RandomRunNumber > 309311 and pass_event_cut(tree, 7):
# h_cut_flow2.Fill(cut, event_weight)
elif pass_event_cut(tree, step):
h_cut_flow.Fill(cut, event_weight)
#h_cut_flow2.Fill(cut, event_weight)
output = TFile('cut_flow.root', 'recreate')
h_cut_flow.Write()
output.Close()
def check_n_vertices_vs_met_threshold():
AtlasStyle.SetAtlasStyle()
#input_tfile = utils.open_tfile(BasicConfig.workdir + 'DVTree_NTuple_data15_13TeV.root')
input_tfile = utils.open_tfile(args.inputFile)
#tree = input_tfile.Get('DVTree_NTuple')
tree = input_tfile.Get('Nominal')
#bin_name = ['Base', 'Trigger', 'Filter', 'MET200', 'MET220', 'MET250']
bin_name = ['Base', 'Trigger', 'Filter', 'MET250']
h_nevents_cut = TH1F('nevents_cut', ';;Double Ratio', len(bin_name), 0,
len(bin_name))
h_nevents_all = TH1F('nevents_all', ';;Double Ratio', len(bin_name), 0,
len(bin_name))
h_ndvs_cut = {
ntracks: TH1F('ndvs_cut_' + str(ntracks), ';;Double Ratio',
len(bin_name), 0, len(bin_name))
for ntracks in range(2, 6)
}
h_ndvs_all = {
ntracks: TH1F('ndvs_all_' + str(ntracks), ';;Double Ratio',
len(bin_name), 0, len(bin_name))
for ntracks in range(2, 6)
}
for bin, name in enumerate(bin_name):
h_nevents_cut.GetXaxis().SetBinLabel(bin + 1, name)
h_nevents_all.GetXaxis().SetBinLabel(bin + 1, name)
for ntracks in range(2, 6):
h_ndvs_cut[ntracks].GetXaxis().SetBinLabel(bin + 1, name)
h_ndvs_all[ntracks].GetXaxis().SetBinLabel(bin + 1, name)
entries = tree.GetEntries()
for entry in range(entries):
utils.show_progress(entry, entries)
#if entry == 1000000:
# break
# get the next tree in the chain and verify
ientry = tree.LoadTree(entry)
if ientry < 0:
break
# copy next entry into memory and verify
nb = tree.GetEntry(entry)
if nb <= 0:
continue
if not utils.basic_event_selection(tree):
continue
# fill all
for name in bin_name:
h_nevents_all.Fill(name, 1.)
for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
if utils.basic_dv_selection(tree, dv_index):
if DV_nTracks < 6:
h_ndvs_all[DV_nTracks].Fill(name, 1.)
else:
h_ndvs_all[5].Fill(name, 1.)
#
h_nevents_cut.Fill('Base', 1.)
for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
if utils.basic_dv_selection(tree, dv_index):
if DV_nTracks < 6:
h_ndvs_cut[DV_nTracks].Fill('Base', 1.)
else:
h_ndvs_cut[5].Fill('Base', 1.)
# Trigger
if not tree.PassCut1:
continue
h_nevents_cut.Fill('Trigger', 1.)
for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
if utils.basic_dv_selection(tree, dv_index):
if DV_nTracks < 6:
h_ndvs_cut[DV_nTracks].Fill('Trigger', 1.)
else:
h_ndvs_cut[5].Fill('Trigger', 1.)
# Filter
if not tree.PassCut2:
continue
h_nevents_cut.Fill('Filter', 1.)
for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
if utils.basic_dv_selection(tree, dv_index):
if DV_nTracks < 6:
h_ndvs_cut[DV_nTracks].Fill('Filter', 1.)
else:
h_ndvs_cut[5].Fill('Filter', 1.)
##
#if not tree.MET > 200:
# continue
#h_nevents_cut.Fill('MET200', 1.)
#for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
# if pass_base_dv_selection(tree, dv_index):
# if DV_nTracks < 6:
# h_ndvs_cut[DV_nTracks].Fill(name, 1.)
# else:
# h_ndvs_cut[5].Fill(name, 1.)
##
#if not tree.MET > 220:
# continue
#h_nevents_cut.Fill('MET220', 1.)
#for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
# if pass_base_dv_selection(tree, dv_index):
# if DV_nTracks < 6:
# h_ndvs_cut[DV_nTracks].Fill(name, 1.)
# else:
# h_ndvs_cut[5].Fill(name, 1.)
#
if not tree.MET > 250:
continue
h_nevents_cut.Fill('MET250', 1.)
for dv_index, DV_nTracks in enumerate(tree.DV_nTracks):
if utils.basic_dv_selection(tree, dv_index):
if DV_nTracks < 6:
h_ndvs_cut[DV_nTracks].Fill('MET250', 1.)
else:
h_ndvs_cut[5].Fill('MET250', 1.)
#
output_tfile = TFile(args.outputFile, 'recreate')
#
#canvas = TCanvas('canvas', 'canvas', 1200, 800) #h_ndvs_all_clone = h_ndvs_all[2].Clone('unit')
#h_ndvs_all_clone.Divide(h_ndvs_all[2])
#h_ndvs_all_clone.SetMaximum(3)
#h_ndvs_all_clone.SetMinimum(0)
#h_ndvs_all_clone.Draw()
#legend = TLegend(0.5, 0.6, 0.85, 0.85)
h_nevents_cut.Write()
h_nevents_all.Write()
for DV_nTracks in range(2, 6):
h_ndvs_cut[DV_nTracks].Write()
h_ndvs_all[DV_nTracks].Write()
#
# h_ndvs_cut[DV_nTracks].Sumw2()
# h_ndvs_cut[DV_nTracks].Divide(h_ndvs_all[DV_nTracks])
# h_ndvs_cut[DV_nTracks].Divide(h_nevents_cut)
# h_ndvs_cut[DV_nTracks].Multiply(h_nevents_all)
# utils.decorate_histogram(h_ndvs_cut[DV_nTracks], BasicConfig.colors[DV_nTracks])
# h_ndvs_cut[DV_nTracks].Draw('same,hist')
# legend.AddEntry(h_ndvs_cut[DV_nTracks],
# '('+str(DV_nTracks)+'trk-DVs(cut)/2trk-DVs(all))/(Events(cut)/Events(all))', 'l')
#utils.decorate_legend(legend)
#legend.Draw()
#utils.save_as(canvas, BasicConfig.plotdir + 'nVerts_met_dependency')
#output = TFile('nVerts_met_dependency.root', 'recreate')
#canvas.Write()
output_tfile.Close()
def plotFiles(filenames,
variables,
key,
weight_plots=False,
weight_plots_tx=True,
plot_dict={},
tex_dict={}):
# plot a bunch of files and get stats of variables
ROOT.gROOT.SetBatch(True)
atlas.SetAtlasStyle()
print filenames
# check how many cv folds are represented in this list of files
cv_folds = filter(
lambda x: x.find('cv') != -1 and x.endswith('root') and x.find('train')
!= -1, filenames)
# get the cv_xxx name and only return unique values
cv_nums = list(
set(
map(lambda x: 'cv_' + x.split('_')[-1].replace('.root', ''),
cv_folds)))
print cv_nums
# create a dictionary for the stats of each cv fold
stats = {}
# create a dict for the event counts of each cv fold
event_counts = {}
for c in cv_nums:
stats[c] = {'Train': {}, 'Valid': {}}
event_counts[c] = {'Train': {}, 'Valid': {}}
# dict for the stats of the full dataset
stats['Full'] = {}
event_counts['Full'] = {}
# add this to the end of the filenames to differentiate between weighted and not weighted
weight_id = '_weighted' if weight_plots or weight_plots_tx else ''
for i, f in enumerate(filenames):
pt4_16 = False
pt8_12 = False
if f.find('400_1600') != -1 or f.find('4_16') != -1:
pt4_16 = True
elif f.find('800_1200') != -1 or f.find('8_12') != -1:
pt8_12 = True
# is this a test or train file?
file_type = "Full"
if f.lower().find('train') != -1:
file_type = "Train"
elif f.lower().find('test') != -1:
file_type = 'Valid'
# what cv split is it? look for cv_xyz.root
cv_num = ''
if file_type != 'Full':
cv_num = 'cv_' + f.split('_')[-1].replace('.root', '')
# open the file and get the tree
f_open = ROOT.TFile.Open('folds/' + f)
tree = f_open.Get('outputTree')
leg = ROOT.TLegend(0.7, 0.60, 0.9, 0.50)
leg.SetFillColor(ROOT.kWhite)
c = ROOT.TCanvas(f)
total_events = tree.GetEntries()
signal_events = tree.GetEntries("label==1")
bkg_events = tree.GetEntries("label==0")
# this is the full dataset
if cv_num != '':
event_counts[cv_num][
file_type] = '{0:15} {1:10} {2:14}{3:10}'.format(
file_type + ' ' + cv_num, str(signal_events),
str(bkg_events), str(total_events))
else:
# this is a cv split
event_counts['Full'] = '{0:15} {1:10} {2:14}{3:10}'.format(
file_type, str(signal_events), str(bkg_events),
str(total_events))
# create histograms for each variable
hists = {}
for v in variables:
# set up the names for the different histograms
ispt = False
if v.find('pt') != -1:
ispt = True
hist_full_name = v
hist_sig_name = 'sig_' + v
hist_bkg_name = 'bkg_' + v
# first get the full histogram to get an idea of the combined mean and rms
if ispt:
tree.Draw(v + '/1000>>' + v)
else:
tree.Draw(v + '>>' + v)
# pull from the global space
hist_full = ROOT.gDirectory.Get(hist_full_name).Clone()
mean = '{0:.4f}'.format(float(hist_full.GetMean()))
std = '{0:.4f}'.format(float(hist_full.GetRMS()))
# for some of the variables the labels overlap with the distributions. Visually inspecting this it doesn't
# look like there is an easy fix. I think maybe the best is to rebook the histogram and change the limits to
# something higher on the x axis....
# eec c2
#
# set up the variable expression that gets used in the Draw function
if not ispt:
varexp = v + ">>" + hist_sig_name
else:
varexp = v + "/1000>>" + hist_sig_name
# cut string to select signal only. An additional string can be added here to apply the weights.
cutstring = '(label==1)' #*(weight)'
#if weight_plots:
#cutstring += ('*atan(1/weight)')
cutstring += '*(weight)'
# create the signal histogram and retrieve it
tree.Draw(varexp, cutstring)
mult = 1.0
xmax = -1
addBins = 0
if v.find('eec_c2_1') != -1 or v.find('mu12') != -1 or v.find(
'planarflow') != -1 or v.find(
'tauwta2tauwta1') != -1 or v.find(
'zcut12') != -1 or ispt:
hist_sig_tmp = ROOT.gDirectory.Get(hist_sig_name).Clone()
xmax = hist_sig_tmp.GetXaxis().GetXmax()
width = float(hist_sig_tmp.GetXaxis().GetBinWidth(1))
# tauwta21 and planarflow need more than 1.2...
if v.find('tauwta2tauwta1') != -1:
mult = 1.65
elif v.find('planarflow') != -1:
mult = 1.9
elif ispt and pt4_16:
mult = 1.35
else:
mult = 1.2
addBins = float((xmax * mult - xmax)) / width
hist_sig = ROOT.TH1F('hist_sig', 'hist_sig',
int(hist_sig_tmp.GetNbinsX() + addBins),
hist_sig_tmp.GetXaxis().GetXmin(),
xmax * mult) # how many bins? :(
#fill it
for n in xrange(1, hist_sig_tmp.GetNbinsX() + 1):
hist_sig.SetBinContent(n, hist_sig_tmp.GetBinContent(n))
else:
hist_sig = ROOT.gDirectory.Get(hist_sig_name).Clone()
# stats
sig_mean = '{0:.4f}'.format(float(hist_sig.GetMean()))
sig_std = '{0:.4f}'.format(float(hist_sig.GetRMS()))
# normalise
if hist_sig.Integral() != 0:
hist_sig.Scale(1 / hist_sig.Integral())
# set some drawing options and titles
hist_sig.SetLineColor(2)
hist_sig.SetTitle('Signal')
hist_sig.GetXaxis().SetTitle(v)
# now get the background histogram
cutstring = cutstring.replace('==1', '==0')
#cutstring += ('*(weight)')
#if weight_plots_tx:
# cutstring = cutstring.replace('*weight','*atan(1/weight)')
tree.Draw(varexp.replace('sig', 'bkg'), cutstring)
if v.find('eec_c2_1') != -1 or v.find('mu12') != -1 or v.find(
'planarflow') != -1 or v.find(
'tauwta2tauwta1') != -1 or v.find(
'zcut12') != -1 or ispt:
hist_bkg_tmp = ROOT.gDirectory.Get(
hist_bkg_name).Clone() # pull from global
hist_bkg = ROOT.TH1F('hist_bkg', 'hist_bkg',
int(hist_sig.GetNbinsX()),
hist_sig.GetXaxis().GetXmin(),
xmax * mult)
for n in xrange(1, hist_bkg_tmp.GetNbinsX() + 1):
hist_bkg.SetBinContent(n, hist_bkg_tmp.GetBinContent(n))
else:
hist_bkg = ROOT.gDirectory.Get(
hist_bkg_name).Clone() # pull from global
# stats
bkg_mean = '{0:.4f}'.format(float(hist_bkg.GetMean()))
bkg_std = '{0:.4f}'.format(float(hist_bkg.GetRMS()))
# normalise
if hist_bkg.Integral() != 0:
hist_bkg.Scale(1 / hist_bkg.Integral())
# drawing options and titles
hist_bkg.SetLineColor(4)
hist_bkg.SetTitle('Background')
hist_sig.GetXaxis().SetTitle(v)
leg.Clear()
# add the legend entries
leg.AddEntry(hist_sig, 'Signal', 'l')
leg.AddEntry(hist_bkg, 'Background', 'l')
# find the maximum for when we draw them together on a single canvas
sig_max = hist_sig.GetMaximum()
bkg_max = hist_bkg.GetMaximum()
max_val = max(sig_max, bkg_max)
hist_sig.SetMaximum(max_val * 1.1)
hist_bkg.SetMaximum(max_val * 1.1)
if v.strip() in plot_dict.keys():
hist_sig.GetXaxis().SetTitle(plot_dict[v])
hist_bkg.GetXaxis().SetTitle(plot_dict[v])
fnum = 'Full' if cv_num == '' else cv_num
hist_sig.SetTitle('Fold ' + fnum + ': ' + plot_dict[v])
hist_bkg.SetTitle('Fold ' + fnum + ': ' + plot_dict[v])
hist_sig.Draw()
hist_bkg.Draw('same')
leg.Draw('same')
# add the grooming algorithm too
galg = ROOT.TLatex()
galg.SetNDC()
galg.SetTextFont(42)
galg.SetTextSize(0.03)
galg.SetTextColor(ROOT.kBlack)
galg.DrawLatex(
0.7, 0.71,
"#splitline{anti-k_{t} R=1.0 jets}{#splitline{Trimmed}{f_{cut}=5%,R_{sub}=0.2}}"
)
scl = ROOT.TLatex()
scl.SetNDC()
scl.SetTextFont(42)
scl.SetTextSize(0.03)
scl.SetTextColor(ROOT.kBlack)
scl.DrawLatex(0.7, 0.61, "Standardised")
e = ROOT.TLatex()
e.SetNDC()
e.SetTextFont(42)
e.SetTextSize(0.035)
e.SetTextColor(ROOT.kBlack)
e.DrawLatex(0.7, 0.88, "#sqrt{s}=13 TeV")
m = ROOT.TLatex()
m.SetNDC()
m.SetTextFont(42)
m.SetTextSize(0.035)
m.SetTextColor(ROOT.kBlack)
m.DrawLatex(0.7, 0.78, "68% mass window")
# need to put the pt range on here....
# okay, so this is nasty and poor form, but I'm super stressed and running out of time
# to finish my thesis, so whatever. The algorithm name should have the pt range in it in gev
# At this point things are narrowed down to the point where we are only considering two
# pt ranges: 400-1600 GeV or 800-1200 GeV, so just look for those.
ptrange = ''
if pt4_16:
ptrange = '400<p_{T}^{Truth}<1600 GeV'
elif pt8_12:
ptrange = '800<p_{T}^{Truth}<1200 GeV'
if ptrange != '':
# draw it
ptl = ROOT.TLatex()
ptl.SetNDC()
ptl.SetTextFont(42)
ptl.SetTextSize(0.035)
ptl.SetTextColor(ROOT.kBlack)
ptl.DrawLatex(0.7, 0.83, ptrange)
#"Internal Simulation");
if cv_num == '':
c.SaveAs('fold_plots/' + key + '_Full_' + v + weight_id +
'.pdf')
else:
c.SaveAs('fold_plots/' + key + '_Full_' + cv_num + '_' + v +
weight_id + '.pdf')
# write the means and std to the stats file
result = '{0:15}: {1:10} {2:10} {3:10} {4:10} {5:10} {6:10}'.format(
file_type + ' ' + cv_num, str(mean), str(std), str(sig_mean),
str(sig_std), str(bkg_mean), str(bkg_std))
# check that this variable has a dictionary entry
#if v not in stats[cv_num][file_type].keys():
#stats[cv_num][file_type][v] = {}
if cv_num != '': # full dataset
stats[cv_num][file_type][v] = result
else: # cv split
stats['Full'][v] = result
# now all of the stats can be written to file!
# first write the combined stats
combined_stats = open(
'fold_stats/combined_stats_' + key + weight_id + '.txt', 'w')
combined_stats.write('{0:15} {1:10} {2:14}{3:10}'.format(
'Sample', 'Signal', 'Background', 'Total') + '\n')
print event_counts['Full']
combined_stats.write(str(event_counts['Full']) + '\n')
# write out all of the cv splits
for cv in cv_nums:
for f in ['Train', 'Valid']:
combined_stats.write(str(event_counts[cv][f]) + '\n')
combined_stats.write('\n' + '\n')
# now start doing the variables
combined_stats.write('\n{0:15}: {1:10} {2:10} {3:10} {4:10} {5:10} {6:10}'.
format('Variable', 'Mean', 'Std', 'Mean Sig',
'Std Sig', 'Mean Bkg', 'Std Bkg') + '\n\n')
print 'stats full keys', stats['Full'].keys()
print 'stats keys', stats.keys()
print 'stats train keys', stats['cv_000']['Train'].keys()
for v in variables:
print v
v = v.strip()
if not v.strip() in stats['Full'].keys():
continue
if v.strip() in tex_dict.keys():
combined_stats.write(tex_dict[v] + '\n')
else:
combined_stats.write(v + '\n')
combined_stats.write(stats['Full'][v] + '\n')
for c in cv_nums:
combined_stats.write(str(stats[c]['Train'][v]) + '\n')
combined_stats.write(str(stats[c]['Valid'][v]) + '\n')
combined_stats.write('\n')
combined_stats.close()
# write the stats for each cv fold
for cv in cv_nums:
print cv
stats_file = open('fold_stats/' + key + '_' + cv + weight_id + '.txt',
'w')
stats_file.write('{0:15} {1:10} {2:14}{3:10}'.format(
'Sample', 'Signal', 'Background', 'Total') + '\n')
stats_file.write(str(event_counts['Full']) + '\n')
stats_file.write(str(event_counts[cv]['Train']) + '\n')
stats_file.write(str(event_counts[cv]['Valid']) + '\n')
stats_file.write('\n{0:15}: {1:10} {2:10} {3:10} {4:10} {5:10} {6:10}'.
format('Variable', 'Mean', 'Std', 'Mean Sig',
'Std Sig', 'Mean Bkg', 'Std Bkg') + '\n\n')
# now write each variable
for v in variables:
if v.strip() in tex_dict.keys():
stats_file.write(tex_dict[v] + '\n')
else:
stats_file.write(v + '\n')
stats_file.write(stats['Full'][v] + '\n')
stats_file.write(stats[cv]['Train'][v] + '\n')
stats_file.write(stats[cv]['Valid'][v] + '\n')
stats_file.write('\n')
stats_file.close()
def combinedPlotNominal(files, normalize, ratio):
files = files.split(',')
dataFile = [file for file in files if ".data." in file][0]
files.remove(dataFile)
files.insert(0, dataFile)
if any("Pythia" in file for file in files):
pythiaFile = [file for file in files if "Pythia" in file][0]
files.remove(pythiaFile)
files.insert(1, pythiaFile)
if any("Sherpa" in file for file in files):
sherpaFile = [file for file in files if "Sherpa" in file][0]
files.remove(sherpaFile)
files.insert(2, sherpaFile)
# Save output to directory of first file
outDir = dataFile[:-5] + '/'
if not os.path.exists(outDir):
os.mkdir(outDir)
if normalize:
outDir += "combinedPlotNominal_normalized/"
else:
outDir += "combinedPlotNominal/"
if not os.path.exists(outDir):
os.mkdir(outDir)
if not os.path.exists(outDir + '/eps'):
os.mkdir(outDir + '/eps')
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFiles = []
nomDirs = []
for file in files:
inFiles.append(TFile.Open(file, "READ"))
keyList = [key.GetName() for key in inFiles[-1].GetListOfKeys()
] #List of top level objects
dirList = [key for key in keyList
if "Iteration" in key] #List of all directories
nomDir = [dir for dir in dirList if "Nominal" in dir]
if (not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDirs.append(inFiles[-1].Get(nomDir[0]))
c1 = TCanvas()
################ Set Color Palate ####################3
# Data, Herwig, Pythia8, Sherpa
colors = [kBlack, kRed, kBlue, kViolet, kCyan]
markers = [20, 21, 23, 22, 33, 34]
# colorMax = 240.
# colorMin = 0. #20.
# numInputs = len( nomDirs )
# colors = []
# if len(nomDirs) == 2:
# colors = [kBlack, kRed]
# else:
# for iDir, nomDir in enumerate(nomDirs):
# colorNum = int( colorMin+(colorMax-colorMin)*iDir/numInputs)
# colors.append( gStyle.GetColorPalette( colorNum ))
##################### Plot All Nominal #################################
print "Plotting nominal hists "
oneLine = TF1("zl1", "1", -10000, 10000)
oneLine.SetTitle("")
oneLine.SetLineWidth(1)
oneLine.SetLineStyle(2)
oneLine.SetLineColor(kBlack)
histList = [key.GetName() for key in nomDirs[0].GetListOfKeys()]
for histName in histList:
if "prof_" in histName or "ptSlice" in histName:
continue
tmpHist = nomDirs[0].Get(histName)
if not type(tmpHist) == TH1F and not type(
tmpHist) == TH1D and not type(
tmpHist) == TGraphErrors: #Can't draw bands if not 1D
continue
leg = TLegend(0.65, 0.72, 0.9, 0.93)
leg.SetFillStyle(0)
leg.SetTextFont(42)
#! leg = TLegend(0.83, 0.15, 0.99, 0.95)
if ratio:
pad1 = TPad("pad1", "", 0, 0.32, 1, 1)
pad2 = TPad("pad2", "", 0, 0, 1, 0.32)
#! pad1 = TPad("pad1", "", 0, 0.3, 0.83, 1)
#! pad2 = TPad("pad2", "", 0, 0, 0.83, 0.3)
pad1.SetBottomMargin(0.01)
pad2.SetTopMargin(0)
pad2.SetBottomMargin(0.45)
pad1.Draw()
pad2.Draw()
else:
#! pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.Draw()
pad1.cd()
nomHists = []
drawString = ""
maxVal = []
maxBinX = []
for iDir, nomDir in enumerate(nomDirs):
thisFileStr = files[iDir].split('.')[2]
if "all" in thisFileStr:
thisFileStr = files[iDir].split('.')[1]
nomHist = nomDir.Get(histName)
nomHist.SetName(nomHist.GetName())
if "Beta" in histName:
nomHist.Rebin(2)
if "alpha" in histName:
nomHist.Rebin(4)
if "ptAsym" in histName:
nomHist.Rebin(4)
if "Eta" in histName and not type(nomHist) == TGraphErrors:
nomHist.Rebin(4)
if ("recoilPt" in histName):
for iBin in range(1, nomHist.GetNbinsX() + 1):
nomHist.SetBinContent(
iBin,
nomHist.GetBinContent(iBin) /
nomHist.GetBinWidth(iBin))
if normalize and not type(
nomHist) == TGraphErrors and nomHist.Integral() > 0.:
nomHist.Scale(1. / nomHist.Integral())
if "Sherpa" in files[iDir] and "MJB" in histName:
for iBin in range(31, nomHist.GetNbinsX() + 1):
nomHist.SetBinContent(iBin, 0)
nomHist.SetBinError(iBin, 0)
nomHist.SetLineColor(colors[iDir])
nomHist.SetMarkerColor(colors[iDir])
nomHist.SetMarkerStyle(markers[iDir])
thisEntry = leg.AddEntry(
nomHist,
thisFileStr.replace('d', 'D').replace(
'Sherpa', 'Sherpa 2.1').replace('Herwig', 'Herwig++'),
"lp")
thisEntry.SetTextColor(colors[iDir])
#nomHist.SetMinimum(0.9)
# if( "jetPt" in histName or "jetEnergy" in histName):
# maxBinX.append(nomHist.FindLastBinAbove(0)+1)
# nomHist.SetMaximum(1.5*nomHist.GetMaximum())
# nomHist.SetMinimum(0.000101)
# else:
nomHist.SetMaximum(1.5 * nomHist.GetMaximum())
#nomHist.SetMinimum(0.000101)
if ("MJB" in histName):
nomHist.SetMinimum(0.0000101)
#nomHist.GetXaxis().SetRangeUser( 500, 2800 ) #!!public
#nomHist.SetMaximum(1.06) #!!public
#nomHist.SetMinimum(0.9701) #!!public
nomHist.GetXaxis().SetRangeUser(300, 2800)
nomHist.SetMaximum(1.2)
nomHist.SetMinimum(0.8999)
nomHist.GetXaxis().SetMoreLogLabels(True)
nomHist.GetYaxis().SetTitle(
"#LT p_{T}^{lead jet}/p_{T}^{recoil} #GT")
nomHist.GetYaxis().SetTitleSize(0.09)
nomHist.GetYaxis().SetTitleOffset(0.7)
nomHist.GetYaxis().SetLabelSize(0.06)
nomHist.GetYaxis().SetLabelOffset(0.01)
nomHist.SetMarkerSize(.8)
nomHist.SetLineWidth(1)
elif ("Pt" in histName):
nomHist.GetYaxis().SetTitle("AU")
if ("jet0" in histName):
nomHist.GetXaxis().SetRangeUser(200, 2000)
else:
nomHist.GetXaxis().SetRangeUser(0, 800)
else:
nomHist.GetYaxis().SetTitle("AU")
if ("recoilPt" in histName):
nomHist.GetYaxis().SetTitle("1/N dp_{T}^{recoil}/dN")
nomHist.GetXaxis().SetRangeUser(300, 3000)
if not type(nomHist) == TGraphErrors:
#drawString = "histsamep"
drawString = "psame"
else:
drawString = "apsame"
nomHist.SetMarkerStyle(33)
nomHist.SetMarkerSize(1.5)
nomHist.SetLineWidth(4)
nomHists.append(nomHist)
maxVal.append(nomHist.GetMaximum())
maxDir = maxVal.index(max(maxVal))
nomHists[maxDir].Draw(drawString)
if maxBinX:
maxBinX = max(maxBinX)
for iDir, nomDir in enumerate(nomDirs):
nomHists[iDir].GetXaxis().SetRange(1, maxBinX)
for iDir, nomDir in enumerate(nomDirs):
nomHists[iDir].Draw(drawString)
oneLine.Draw("same")
for iDir, nomDir in enumerate(nomDirs):
nomHists[iDir].Draw(drawString)
nomHists[0].Draw(drawString) ## Draw data on top
if ratio:
pad2.cd()
ratioHists = []
for iDir in range(1, len(nomDirs)):
#ratioHists.append( nomHists[0].Clone() )
#ratioHists[iDir-1].Add(nomHists[iDir], -1.)
#ratioHists[iDir-1].Divide(nomHists[iDir])
ratioHists.append(nomHists[iDir].Clone())
ratioHists[iDir - 1].Divide(nomHists[0])
ratioHists[iDir - 1].SetMarkerColor(colors[iDir])
ratioHists[iDir - 1].SetMarkerStyle(markers[iDir])
ratioHists[iDir - 1].SetLineColor(colors[iDir])
if iDir == 1:
ratioHists[iDir - 1].SetMaximum(2)
ratioHists[iDir - 1].SetMinimum(0.5)
ratioHists[iDir - 1].GetXaxis().SetLabelOffset(.015)
ratioHists[iDir - 1].GetXaxis().SetTitleOffset(1.3)
ratioHists[iDir - 1].GetXaxis().SetLabelSize(0.13)
ratioHists[iDir - 1].GetXaxis().SetTitleSize(0.16)
# ratioHists[iDir-1].GetXaxis().SetTitle(nomHists[0].GetXaxis().GetTitle());
ratioHists[iDir - 1].GetXaxis().SetMoreLogLabels()
ratioHists[iDir - 1].GetYaxis().SetLabelSize(0.13)
ratioHists[iDir - 1].GetYaxis().SetTitleSize(0.16)
ratioHists[iDir - 1].GetYaxis().SetLabelOffset(.01)
ratioHists[iDir - 1].GetYaxis().SetTitleOffset(0.37)
#ratioHists[iDir-1].GetYaxis().SetTitle("Significance")
ratioHists[iDir - 1].GetYaxis().SetTitle(" MC / Data")
ratioHists[iDir - 1].GetYaxis().SetNdivisions(7)
if ("Pt" in histName):
if ("jet0" in histName):
ratioHists[iDir - 1].GetXaxis().SetRangeUser(
200, 2000)
else:
ratioHists[iDir - 1].GetXaxis().SetRangeUser(
0, 800)
if ("MJB" in histName):
#ratioHists[iDir-1].GetXaxis().SetRangeUser( 500, 2800 ) #!!public
ratioHists[iDir - 1].GetXaxis().SetRangeUser(300, 2500)
ratioHists[iDir - 1].SetMaximum(1.05)
ratioHists[iDir - 1].SetMinimum(0.95)
ratioHists[iDir - 1].GetXaxis().SetTitle(
"p_{T}^{recoil} [GeV]")
if ("recoilPt" in histName):
ratioHists[iDir - 1].GetXaxis().SetRangeUser(300, 3000)
ratioHists[iDir - 1].GetXaxis().SetTitle(
"p_{T}^{recoil} [GeV]")
# if( "jetBeta" in histName):
# ratioHists[iDir-1].SetMaximum(1)
# ratioHists[iDir-1].SetMinimum(-1)
ratioHists[0].Draw("p")
oneLine.Draw("same")
for iDir in range(1, len(nomDirs)):
ratioHists[iDir - 1].Draw("psame")
c1.cd()
leg.Draw()
AtlasStyle.ATLAS_LABEL(0.2, 0.88, 1, " Preliminary")
AtlasStyle.myText(0.2, 0.82, 1, "#sqrt{s} = 13 TeV, 3.3 fb^{-1}")
AtlasStyle.myText(0.2, 0.76, 1, "Multijet Events")
typeText = "anti-k_{t} R = 0.4"
if "_LC_" in dataFile:
typeText += ", LC+JES (in-situ)"
else:
typeText += ", EM+JES (in-situ)"
AtlasStyle.myText(0.2, 0.7, 1, typeText)
AtlasStyle.myText(0.2, 0.64, 1, "#left|#eta^{lead jet}#right| < 1.2")
# AtlasStyle.myText(0.1,0.75,1, "m_{jj} Correction")
if "MJB" in histName:
pad1.SetLogx()
if ratio:
pad2.SetLogx()
else:
pad1.SetLogx(0)
if ratio:
pad2.SetLogx(0)
#if "Pt" in histName or "alpha" in histName:
pad1.SetLogy()
c1.SaveAs(outDir + nomHist.GetName() + "_logy.png")
c1.SaveAs(outDir + "/eps/" + nomHist.GetName() + "_logy.eps")
pad1.SetLogy(0)
c1.SaveAs((outDir + nomHist.GetName() + ".png"))
c1.SaveAs((outDir + "/eps/" + nomHist.GetName() + ".eps"))
c1.SaveAs((outDir + "/eps/" + nomHist.GetName() + ".pdf"))
c1.Clear()
for inFile in inFiles:
inFile.Close()
def plotMJBvEta(file, binnings):
if not "MJB" in file:
print "Error: plotMJBvEta.py must run on a file with \"MJB\", but was given", file
print "Exiting..."
return
binnings = binnings.split(',')
for iBinning in range(len(binnings)):
if not binnings[iBinning][0] == '_':
binnings[iBinning] = '_' + binnings[iBinning]
print "Binnings are ", binnings
outDir = file[:-5] + '/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotMJBvEta/"
if not os.path.exists(outDir):
os.mkdir(outDir)
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFile = TFile.Open(file, "READ")
keyList = [key.GetName()
for key in inFile.GetListOfKeys()] #List of top level objects
dirList = [key for key in keyList
if "Iteration" in key] #List of all directories
#nomDir = [dir for dir in dirList if "NoCorr" in dir]
nomDir = [dir for dir in dirList if "Nominal" in dir]
if (not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDir = inFile.Get(nomDir[0])
c1 = TCanvas()
histList = [
key.GetName() for key in nomDir.GetListOfKeys()
if "MJB" in key.GetName()
]
for binning in binnings:
leg = TLegend(0.80, 0.15, 0.97, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.85, 1)
pad1.Draw()
pad1.cd()
hists = []
counter = 0
for histName in histList:
if not binning in histName:
continue
counter += 1
hists.append(nomDir.Get(histName))
hists[-1].SetMarkerColor(
gStyle.GetColorPalette(70 * (len(hists) - 1)))
hists[-1].SetLineColor(
gStyle.GetColorPalette(70 * (len(hists) - 1)))
hists[-1].GetYaxis().SetRangeUser(0.9, 1.1)
hists[-1].GetXaxis().SetMoreLogLabels(True)
if ("DoubleMJB" in histName):
hists[-1].GetXaxis().SetRangeUser(300, 2000)
if (counter == 1):
if type(hists[-1]) == TGraph:
hists[-1].Draw("apXl")
else:
hists[-1].Draw()
leg.AddEntry(hists[-1], "Nominal", "l")
else:
if type(hists[-1]) == TGraph:
hists[-1].Draw("same pXl")
else:
hists[-1].Draw("same")
leg.AddEntry(hists[-1], "Eta " + str(counter), "l")
c1.cd()
leg.Draw()
pad1.SetLogx()
c1.SaveAs(outDir + "/MJBvEta" + binning + ".png", "png")
pad1.Clear()
c1.Clear()
inFile.Close()
def plotActualSysRatios(file):
outDir = file[:-5] + '/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotActualSysRatios/"
if not os.path.exists(outDir):
os.mkdir(outDir)
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFile = TFile.Open(file, "READ")
keyList = [key.GetName()
for key in inFile.GetListOfKeys()] #List of top level objects
dirList = [key for key in keyList
if "Iteration" in key] #List of all directories
#nomDir = [dir for dir in dirList if "NoCorr" in dir]
nomDir = [dir for dir in dirList if "Nominal" in dir]
if (not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDir = inFile.Get(nomDir[0])
c1 = TCanvas()
##################### Plot Systematic Difference #################################
sysDirNameList = [
dirName for dirName in dirList if not "Nominal" in dirName
]
sysDirList = []
for sysDirName in sysDirNameList:
sysDirList.append(inFile.Get(sysDirName))
## This removes extra MJB systematics
MJBsToUse = [
"a40", "a20", "b15", "b05", "pta90", "pta70", "ptt30", "ptt20"
]
sysDirList = [
sysDir for sysDir in sysDirList
if (not "MJB" in sysDir.GetName() or any(MJBtouse in sysDir.GetName()
for MJBtouse in MJBsToUse))
]
sysDirList = [
sysDir for sysDir in sysDirList if not "Nominal" in sysDir.GetName()
]
## Combine systematics in types ##
#sysTypesToUse = ["Zjet_dPhi","Zjet_MC","Zjet_MuScale","Zjet_MuSmearID","Zjet_MuSmearMS","Zjet_KTerm","Zjet_Veto","Zjet_Stat1","Zjet_Stat2","Zjet_Stat3","Zjet_Stat4","Zjet_Stat5","Zjet_Stat6","Zjet_Stat7","Zjet_Stat8","Zjet_Stat9","Zjet_Stat10","Zjet_Stat11","Zjet_Stat12","Zjet_Stat13"]
#sysTypesToUse = ["Gjet_dPhi","Gjet_Generator","Gjet_OOC","Gjet_Purity","Gjet_Veto","Gjet_Stat1","Gjet_Stat2","Gjet_Stat3","Gjet_Stat4","Gjet_Stat5","Gjet_Stat6","Gjet_Stat7","Gjet_Stat8","Gjet_Stat9","Gjet_Stat10","Gjet_Stat11","Gjet_Stat12","Gjet_Stat13","Gjet_Stat14","Gjet_Stat15"]
sysTypesToUse = [
"Zjet", "Gjet", "Flavor", "EtaIntercalibration", "PunchThrough",
"Pileup", "MCType", "MJB"
]
#sysTypesToUse = ["Zjet_Jvt", "Zjet_ElecESZee", "Zjet_ElecEsmear", "Gjet_Jvt", "Gjet_GamESZee", "LAr_Esmear"]
# sysTypesToUse = ["MJB_a", "MJB_b", "MJB_ptt", "MJB_pta", "MCType"]
# SingleParticle, RelativeNonClosure, Pileup, BJES, PunchThrough
sysTypes = []
for sysType in sysTypesToUse:
if any(sysType in sysDir for sysDir in sysDirNameList):
sysTypes.append(sysType)
if len(sysTypes) == 0:
print "Error, found no systematics!!"
exit(1)
if len(sysTypes) > 1:
sysTypes.append("All")
if "All" in sysTypes:
colorOffset = 240. / (len(sysTypes) - 1)
else:
colorOffset = 240. / len(sysTypes)
#print "Plotting systematic differences "
#print sysTypes
histList = [key.GetName() for key in sysDirList[0].GetListOfKeys()]
for histName in histList:
if "prof_" in histName or "ptSlice" in histName:
continue
nomHist = sysDirList[0].Get(histName)
nomHist.SetName(nomHist.GetName())
if not type(nomHist) == TH1F and not type(
nomHist) == TH1D: #Can't draw bands if not 1D
continue
## Get list of systematic histograms ##
fullHistList = []
for thisSysDir in sysDirList:
fullHistList.append(thisSysDir.Get(histName))
fullHistList[-1].SetDirectory(0)
### Setup Plot ###
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.Draw()
pad1.cd()
## An empty histogram for plot settings ##
settingsHist = nomHist.Clone()
for iBin in range(1, settingsHist.GetNbinsX() + 1):
settingsHist.SetBinContent(iBin, 0.)
settingsHist.SetBinError(iBin, 0.)
settingsHist.GetYaxis().SetTitle("Rel. Uncert. " +
nomHist.GetYaxis().GetTitle())
#settingsHist.GetYaxis().SetTitle( "Rel. Uncert. on "+settingsHist.GetYaxis().GetTitle())
settingsHist.SetLineColor(kWhite)
settingsHist.SetMarkerColor(kWhite)
settingsHist.GetYaxis().SetRangeUser(-1., 2.)
if ("MJB" in histName):
settingsHist.GetXaxis().SetRangeUser(300, 3000)
settingsHist.GetXaxis().SetMoreLogLabels(True)
settingsHist.GetYaxis().SetRangeUser(-0.03, 0.03)
settingsHist.Draw()
sysHistList = []
for iTopSys, topSysName in enumerate(sysTypes):
if topSysName == 'All':
subHistList = [
thisHist
for thisDir, thisHist in zip(sysDirList, fullHistList)
if any(otherTopName in thisDir.GetName()
for otherTopName in sysTypes)
]
else:
subHistList = [
thisHist
for thisDir, thisHist in zip(sysDirList, fullHistList)
if topSysName in thisDir.GetName()
]
sysHistUp, sysHistDn = getCombinedSysHist(nomHist, subHistList,
topSysName)
if topSysName == 'All':
color = kBlack
else:
color = gStyle.GetColorPalette(int(colorOffset *
(iTopSys + 1)))
sysHistUp.SetLineColor(color)
sysHistUp.SetMarkerColor(color)
sysHistUp.SetMarkerSize(0.8)
sysHistDn.SetLineColor(color)
sysHistDn.SetMarkerColor(color)
sysHistDn.SetMarkerSize(0.8)
sysHistUp.Draw("same hist lp")
sysHistDn.Draw("same hist lp")
if (topSysName == "EtaIntercalibration"):
leg.AddEntry(sysHistUp, "#eta-inter", "lp")
elif (topSysName == "PunchThrough"):
leg.AddEntry(sysHistUp, "PunchTh", "lp")
else:
leg.AddEntry(sysHistUp, topSysName, "lp")
# Save them in a list
sysHistList.append(sysHistUp)
sysHistList.append(sysHistDn)
c1.cd()
leg.Draw()
if ("MJB" in histName):
pad1.SetLogx()
c1.SaveAs(outDir + nomHist.GetName() + "_fracDiff.png")
c1.Clear()
inFile.Close()
def plotNominal(file, f_plotSys, f_addGagik):
outDir = file[:-5]+'/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotNominal/"
if not os.path.exists(outDir):
os.mkdir(outDir)
if not os.path.exists(outDir+'/eps'):
os.mkdir(outDir+'/eps')
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFile = TFile.Open(file, "READ");
keyList = [key.GetName() for key in inFile.GetListOfKeys()] #List of top level objects
dirList = [key for key in keyList if "Iteration" in key] #List of all directories
#nomDir = [dir for dir in dirList if "NoCorr" in dir]
nomDir = [dir for dir in dirList if "Nominal" in dir]
if( not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDir = inFile.Get( nomDir[0] )
c1 = TCanvas()
##################### Plot All Nominal With Systematic Bands #################################
print "Plotting nominal hists "
if(f_plotSys):
sysDirNameList = [dir for dir in dirList if not "Nominal" in dir]
sysDirList = []
for sysDirName in sysDirNameList:
sysDirList.append( inFile.Get(sysDirName) )
## Combine systematics in types ##
#sysTypes = ["MJB_a", "MJB_b", "MJB_ptt", "MJB_pta", "Flavor", "EtaIntercalibration"]
sysTypes = ["ZJ", "GJ", "MJB", "Flavor", "EtaIntercalibration", "All"]
if "All" in sysTypes:
colorOffset = 240./(len(sysTypes)-1)
else:
colorOffset = 240./len(sysTypes)
histList = [key.GetName() for key in nomDir.GetListOfKeys()]
for histName in histList:
if "prof_" in histName or "ptSlice" in histName:
continue
nomHist = nomDir.Get( histName )
nomHist.SetName(nomHist.GetName())
if not type(nomHist) == TH1F and not type(nomHist) == TH1D and not type(nomHist) == TGraphErrors: #Can't draw bands if not 1D
continue
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.Draw()
pad1.cd()
leg.AddEntry( nomHist, "Nominal", "lp" )
#nomHist.SetMinimum(0.9)
if( "Pt" in histName or "Energy" in histName):
nomHist.GetXaxis().SetRange(nomHist.FindFirstBinAbove(0), nomHist.FindLastBinAbove(0)+1 )
nomHist.SetMaximum(1.5*nomHist.GetMaximum())
nomHist.SetMinimum(0.0001)
if( "MJB" in histName) :
nomHist.GetXaxis().SetRangeUser( 300, 2500 )
nomHist.SetMaximum(1.1)
nomHist.SetMinimum(0.9)
nomHist.GetXaxis().SetMoreLogLabels(True)
# nomHist.SetMarkerSize(.75)
if( "recoilPt" in histName):
nomHist.GetYaxis().SetTitle("Entries / GeV")
nomHist.GetXaxis().SetRangeUser( 500, 3100 )
if( "recoilPt" in histName):
for iBin in range(1, nomHist.GetNbinsX()+1):
nomHist.SetBinContent(iBin, nomHist.GetBinContent(iBin)/ nomHist.GetBinWidth(iBin))
nomHist.Draw()
if not type(nomHist) == TGraphErrors:
nomHist.Draw("p")
else:
nomHist.SetMarkerStyle(33)
nomHist.SetMarkerSize(1.5)
nomHist.SetLineWidth(4)
nomHist.Draw("ap")
if(f_plotSys):
## Get list of systematic histograms ##
fullHistList = []
for thisSysDir in sysDirList:
fullHistList.append( thisSysDir.Get(histName) )
fullHistList[-1].SetDirectory(0)
## Add systematic bands ##
sysHistList = []
for iTopSys, topSysName in enumerate(sysTypes):
if topSysName == 'All':
subHistList = [thisHist for thisName, thisHist in zip(sysDirNameList, fullHistList) if any(otherTopName in thisName for otherTopName in sysTypes) ]
else:
subHistList = [thisHist for thisName, thisHist in zip(sysDirNameList, fullHistList) if topSysName in thisName]
sysHistUp, sysHistDn = plotSysRatios.getCombinedSysHist(nomHist, subHistList, topSysName)
for iBin in range(1, nomHist.GetNbinsX()+1):
sysHistUp.SetBinContent( iBin, nomHist.GetBinContent(iBin)*(1.+sysHistUp.GetBinContent(iBin)) )
sysHistDn.SetBinContent( iBin, nomHist.GetBinContent(iBin)*(1.+sysHistDn.GetBinContent(iBin)) )
if topSysName == 'All':
color = kBlack
else:
color = gStyle.GetColorPalette(int(colorOffset*(iTopSys+1)))
sysHistUp.SetLineColor(color)
sysHistUp.SetMarkerColor(color)
sysHistUp.SetMarkerSize(1.5)
sysHistUp.SetMarkerStyle(34)
sysHistDn.SetLineColor(color)
sysHistDn.SetMarkerColor(color)
sysHistDn.SetMarkerSize(1.5)
sysHistDn.SetMarkerStyle(34)
if( "Pt" in histName or "Energy" in histName):
sysHistUp.GetXaxis().SetRange(sysHistUp.FindFirstBinAbove(0), sysHistUp.FindLastBinAbove(0)+1)
sysHistDn.GetXaxis().SetRange(sysHistDn.FindFirstBinAbove(0), sysHistDn.FindLastBinAbove(0)+1)
if not type(nomHist) == TGraphErrors:
sysHistUp.Draw("same hist l")
sysHistDn.Draw("same hist l")
else:
sysHistUp.SetMarkerStyle(4)
sysHistUp.SetMarkerSize(1.2)
sysHistUp.Draw("same l")
sysHistDn.SetMarkerStyle(4)
sysHistDn.SetMarkerSize(1.2)
sysHistDn.Draw("same l")
if( topSysName == "EtaIntercalibration"):
leg.AddEntry( sysHistUp, "EIC", "lp")
else:
leg.AddEntry( sysHistUp, topSysName, "lp")
# Save them in a list
sysHistList.append( sysHistUp )
sysHistList.append( sysHistDn )
# ### Add MC for Data MJB! ###
# if( "data" in file and "MJB" in histName ):
# filePath = os.path.dirname( file )
# if( "initial" in file):
# mcFile = glob.glob( filePath+"/*mc14*MJB_initial.root")
# elif( "final" in file):
# mcFile = glob.glob( filePath+"/*mc14*MJB_final.root")
# if len(mcFile) == 1:
# mcFile = TFile.Open(mcFile[0], "READ")
# mcKeyList = [key.GetName() for key in mcFile.GetListOfKeys()] #List of top level objects
# mcDirList = [key for key in mcKeyList if "Iteration" in key] #List of all directories
# #mcDir = [dir for dir in dirList if "NoCorr" in dir]
# mcDir = [dir for dir in dirList if "Nominal" in dir]
# if len(mcDir) == 1:
# mcDir = mcFile.Get( mcDir[0] )
# mcHist = mcDir.Get(histName)
# mcHist.SetMarkerColor(kRed)
# mcHist.SetLineColor(kRed)
# mcHist.SetMarkerStyle(33)
# mcHist.SetMarkerSize(1.3)
# mcHist.Draw("same p")
# leg.AddEntry(mcHist, "MC", "lp")
#
# ### Add Gagik for DoubleMJB! ###
# if( f_addGagik ):
# if( "DoubleMJB" in histName ):
# filePath = os.path.dirname( file )
# gagikFile = TFile.Open(filePath+"/ThirdCycle.EM4.sherpa.1.v11.root", "READ")
# gagikHist = gagikFile.Get("g_DoMC_fmean_vs_recoil")
# gagikHist.SetMarkerColor(kRed)
# gagikHist.SetLineColor(kRed)
# gagikHist.SetMarkerStyle(33)
# gagikHist.SetMarkerSize(1.3)
# gagikHist.Draw("same p")
# leg.AddEntry(gagikHist, "8 TeV", "lp")
#
nomHist.Draw("same p")
c1.cd()
leg.Draw()
AtlasStyle.ATLAS_LABEL(0.2,0.88, 1," Internal")
AtlasStyle.myText(0.2,0.82,1, "#sqrt{s} = 13 TeV, 3.3 fb^{-1}")
if "Pt" in histName or "alpha" in histName:
pad1.SetLogy()
c1.SaveAs(outDir+nomHist.GetName()+"_logy.png" )
c1.SaveAs(outDir+'/eps/'+nomHist.GetName()+"_logy.eps" )
pad1.SetLogy(0)
if "MJB" in histName:
pad1.SetLogx()
c1.SaveAs((outDir+nomHist.GetName()+".png") )
c1.SaveAs((outDir+'/eps/'+nomHist.GetName()+".eps") )
c1.Clear()
inFile.Close()
def draw_cross_section_limit(tree, mass_g, flavor_of_sample='MET_TLJets'):
AtlasStyle.SetAtlasStyle()
entries = tree.GetEntries()
current_delta_mass = 0
upper_limits = []
dM = []
index = -1
for entry in range(entries):
tree.GetEntry(entry)
if tree.mGluino == mass_g:
if current_delta_mass != tree.deltaM:
print('*** {0}, {1}'.format(tree.mGluino, tree.deltaM))
upper_limits.append(TGraphErrors())
dM.append(int(tree.deltaM))
index += 1
point = 0
current_delta_mass = tree.deltaM
#if current_delta_mass < 100:
# continue
upper_limits[index].SetPoint(point, tree.ctau * 1e3, tree.xsUL)
upper_limits[index].SetPointError(
point, 0, tree.xsUL * tree.effRelStatErr +
tree.xsUL * tree.effRelSystErr)
point += 1
print(tree.ctau, tree.xsUL)
canvas = TCanvas('c', 'c', 1000, 800)
canvas.SetLogx()
canvas.SetLogy()
#upper_limits[0].SetMinimum(0.8)
#upper_limits[0].SetMinimum(0.05)
#upper_limits[0].SetMaximum(30000)
#upper_limits[0].GetXaxis().SetRangeUser(0.9, 310)
#upper_limits[0].GetXaxis().SetTitle('c#tau [mm]')
#upper_limits[0].GetYaxis().SetTitle('Cross Section [fb]')
#upper_limits[0].Draw('A3')
#if mass_g == 1400:
# upper_limits[1].RemovePoint(0)
#upper_limits[0].RemovePoint(2)
#upper_limits[1].RemovePoint(0)
h_xs = TH1F('xs', ';c#tau [mm]; Cross Section [fb]', 1000, 0.9, 310)
h_xs_line = TH1F('xs_line', ';c#tau [mm]; Cross Section [fb]', 1000, 0.9,
310)
print(mc.mass_xs_err[mass_g]['xs'] * 1e3)
for bin in range(1, 1000 + 1):
h_xs.SetBinContent(bin, mc.mass_xs_err[mass_g]['xs'] * 1e3)
h_xs_line.SetBinContent(bin, mc.mass_xs_err[mass_g]['xs'] * 1e3)
h_xs.SetBinError(
bin, mc.mass_xs_err[mass_g]['xs'] * 1e3 *
mc.mass_xs_err[mass_g]['xs_err'] * 0.01)
h_xs.SetMarkerSize(0)
h_xs.SetFillStyle(3001)
h_xs.SetFillColor(kGray + 2)
#h_xs.SetMinimum(0.8)
h_xs.SetMinimum(0.05)
h_xs.SetMaximum(30000)
#h_xs.Draw('same,e2')
h_xs.Draw('e2')
h_xs_line.SetLineColor(kGray + 3)
h_xs_line.SetLineStyle(2)
h_xs_line.Draw('same')
legend = TLegend(0.60, 0.75, 0.83, 0.90)
for ii, upper_limit in enumerate(upper_limits):
#upper_limit.RemovePoint(0)
upper_limit.SetMarkerSize(0)
upper_limit.SetFillStyle(3001)
index = ii
if dM[ii] == 130:
index = 1
elif dM[ii] == 80:
index = 2
continue
elif dM[ii] == 50:
index = 3
elif dM[ii] == 30:
index = 4
upper_limit.SetFillColor(BasicConfig.colors[index + 1])
upper_limit.SetLineColor(BasicConfig.colors[index + 1])
upper_limit.Draw('3,same')
#upper_limit.Draw('c,same')
#if dM[ii] > 100:
# #legend.AddEntry(upper_limit, 'M_{#tilde{g}} = '+str(mass_g)+' GeV, #DeltaM = '+str(dM[ii])+' GeV', 'lf')
# legend.AddEntry(upper_limit, '#DeltaM = '+str(dM[ii])+' GeV', 'lf')
legend.AddEntry(upper_limit, '#DeltaM = ' + str(dM[ii]) + ' GeV', 'lf')
utils.decorate_legend(legend)
legend.Draw()
AtlasStyle.ATLASLabel(0.19, 0.87, 'Work in Progress')
AtlasStyle.myText(0.20, 0.79, kBlack,
'#sqrt{s} = 13 TeV, #int L dt = 30 fb^{-1}', 0.035)
AtlasStyle.myText(
0.20, 0.73, kBlack,
'Split-SUSY Model, M_{#tilde{g}} = ' + str(mass_g) + ' GeV', 0.032)
#AtlasStyle.myText(0.20, 0.67, kBlack, 'M_{#tilde{g}} = '+str(mass_g)+' GeV', 0.035)
utils.save_as(
canvas, BasicConfig.plotdir + 'xs_limit_mGluino' + str(mass_g) +
flavor_of_sample)
def draw_cross_section_limit_dM(tree, dM, flavor_of_sample='MET_TLJets'):
AtlasStyle.SetAtlasStyle()
entries = tree.GetEntries()
current_mass = 0
upper_limits = []
mass_g = []
index = -1
point = 0
for entry in range(entries):
tree.GetEntry(entry)
if tree.deltaM == dM or (dM == 'large'
and tree.mGluino - tree.deltaM == 100):
if current_mass != tree.mGluino:
print('*** {0}, {1}'.format(tree.mGluino, tree.deltaM))
upper_limits.append(TGraphErrors())
mass_g.append(int(tree.mGluino))
index += 1
point = 0
current_mass = tree.mGluino
upper_limits[index].SetPoint(point, tree.ctau * 1e3, tree.xsUL)
#upper_limits[index].SetPointError(point, 0, tree.xsUL*tree.effRelStatErr+tree.xsUL*tree.effRelSystErr)
point += 1
print(tree.ctau, tree.xsUL)
canvas = TCanvas('c', 'c', 1000, 800)
canvas.SetLogx()
canvas.SetLogy()
h_xs = TH1F('xs', ';c#tau [mm]; Cross Section [fb]', 1000, 0.9, 310)
h_xs.GetYaxis().SetRangeUser(0.1, 100)
h_xs.Draw()
#h_xs_line = TH1F('xs_line', ';c#tau [mm]; Cross Section [fb]', 1000, 0.9, 310)
#print(mc.mass_xs_err[mass_g]['xs'] * 1e3)
legend = TLegend(0.60, 0.75, 0.83, 0.90)
for ii, upper_limit in enumerate(upper_limits):
#upper_limit.RemovePoint(0)
upper_limit.SetMarkerSize(0)
upper_limit.SetFillStyle(3001)
index = ii
#if dM[ii] == 130:
# index = 1
#elif dM[ii] == 80:
# index = 2
# continue
#elif dM[ii] == 50:
# index = 3
#elif dM[ii] == 30:
# index = 4
#print(upper_limit)
upper_limit.SetFillColor(BasicConfig.colors[index + 1])
upper_limit.SetLineColor(BasicConfig.colors[index + 1])
upper_limit.Draw('lp,same')
#upper_limit.Draw('c,same')
#if dM[ii] > 100:
# #legend.AddEntry(upper_limit, 'M_{#tilde{g}} = '+str(mass_g)+' GeV, #DeltaM = '+str(dM[ii])+' GeV', 'lf')
# legend.AddEntry(upper_limit, '#DeltaM = '+str(dM[ii])+' GeV', 'lf')
#legend.AddEntry(upper_limit, '#DeltaM = '+str(dM[ii])+' GeV', 'lf')
legend.AddEntry(upper_limit, 'Mass G = ' + str(mass_g[ii]) + ' GeV',
'lf')
utils.decorate_legend(legend)
legend.Draw()
AtlasStyle.ATLASLabel(0.19, 0.87, 'Work in Progress')
AtlasStyle.myText(0.20, 0.79, kBlack,
'#sqrt{s} = 13 TeV, #int L dt = 30 fb^{-1}', 0.035)
#AtlasStyle.myText(0.20, 0.73, kBlack, 'Split-SUSY Model, M_{#tilde{g}} = '+str(mass_g)+' GeV', 0.032)
#AtlasStyle.myText(0.20, 0.67, kBlack, 'M_{#tilde{g}} = '+str(mass_g)+' GeV', 0.035)
#if dM == 'large' and tree.mGluino - tree.deltaM == 100:
# print('test')
utils.save_as(
canvas, BasicConfig.plotdir + 'xs_limit_large_dM_' + flavor_of_sample)
def plotSL(file, binning):
if not "appended.root" in file:
print "Error: plotSL.py must run on a file ending in \"appended.root\", but was given", file
print "Exiting..."
return
if not binning[0] == '_':
binning = '_'+binning
outDir = file[:-5]+'/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotSL/"
if not os.path.exists(outDir):
os.mkdir(outDir)
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
inFile = TFile.Open(file, "READ");
keyList = [key.GetName() for key in inFile.GetListOfKeys()] #List of top level objects
dirList = [key for key in keyList if "Iteration" in key] #List of all directories
#nomDir = [dir for dir in dirList if "NoCorr" in dir]
nomDir = [dir for dir in dirList if "Nominal" in dir]
if( not len(nomDir) == 1):
print "Error, nominal directories are ", nomDir
return
else:
nomDir = inFile.Get( nomDir[0] )
c1 = TCanvas()
#################### New Sampling Layer Histograms ##########################
numSamples = 24
sampleName = ["PreSamplerB", "EMB1", "EMB2", "EMB3", "PreSamplerE", "EME1", "EME2", "HEC0", "HEC1", "HEC2", "HEC3", "TileBar0", "TileBar1", "TileBar2", "TileGap1", "TileGap2", "TileGap3", "TileExt0", "TileExt1", "TileExt2", "FCAL0", "FCAL1", "FCAL2", "MINIFCAL0", "MINIFCAL1", "MINIFCAL2", "MINIFCAL3"]
print "Plotting new hists for "
for dir in dirList:
print " ", dir
if not os.path.exists(outDir+dir):
os.mkdir( outDir+dir )
thisDir = inFile.Get( dir )
thisSample = []
leg = TLegend(0.80, 0.15, 0.97, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.85, 1)
pad1.Draw()
pad1.cd()
## Draw a ghost copy for it's axis first ##
thisSample.append(thisDir.Get("prof_recoilPt_SamplingLayerPercent0"+binning) )
thisSample[-1].Add( thisSample[-1], -1.)
#for iBin in range(1, thisSample[-1].GetNbinsX()+1):
# thisSample[-1].SetBinError(iBin, 0.)
#if("NoCorr" in dir):
if("Nominal" in dir):
thisSample[-1].GetYaxis().SetTitle("Percent of Recoil Energy per Layer")
thisSample[-1].GetYaxis().SetRangeUser(0.004, 0.5)
elif ("NoCorr" in dir):
thisSample[-1].GetYaxis().SetTitle("Rel. Uncert. in % Recoil E per Layer")
thisSample[-1].GetYaxis().SetRangeUser(-0.3, 0.3)
else:
thisSample[-1].GetYaxis().SetTitle("Rel. Uncert. in % Recoil E per Layer")
thisSample[-1].GetYaxis().SetRangeUser(-0.1, 0.1)
thisSample[-1].SetMarkerSize(0.)
thisSample[-1].Draw()
for iSample in range(0, numSamples):
thisSample.append( thisDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning) )
#thisSample[-1].GetXaxis().SetRangeUser(200., 2000.)
thisSample[-1].SetLineColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerSize(0.5)
if(iSample%3 == 0):
thisSample[-1].SetLineStyle(1)
elif(iSample%3==1):
thisSample[-1].SetLineStyle(9)
thisSample[-1].SetLineWidth(3)
else:
thisSample[-1].SetLineStyle(2)
#if( not "NoCorr" in dir):
if( not "Nominal" in dir):
nomSample = nomDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning)
thisSample[-1].Add(nomSample, -1.)
thisSample[-1].Divide(nomSample)
# for iBin in range(1, thisSample[-1].GetNbinsX()+1):
# thisSample[-1].SetBinError(iBin, 0.)
#if("NoCorr" in dir):
if("Nominal" in dir):
thisSample[-1].GetYaxis().SetTitle("Percent of Recoil Energy per Layer")
thisSample[-1].GetYaxis().SetRangeUser(0.004, 0.5)
elif ("NoCorr" in dir):
thisSample[-1].GetYaxis().SetTitle("Rel. Uncert. in % Recoil E per Layer")
thisSample[-1].GetYaxis().SetRangeUser(-0.3, 0.3)
else:
thisSample[-1].GetYaxis().SetTitle("Rel. Uncert. in % Recoil E per Layer")
thisSample[-1].GetYaxis().SetRangeUser(-0.1, 0.1)
leg.AddEntry(thisSample[-1], sampleName[iSample], "l")
#if( "NoCorr" in dir):
if( "Nominal" in dir):
thisSample[-1].Draw("same hist pe")
else:
thisSample[-1].Draw("same hist l")
c1.cd()
leg.Draw()
c1.SaveAs(outDir+dir+"/SamplingEnergy_all"+binning+".png")
#if( "NoCorr" in dir):
if( "Nominal" in dir):
pad1.SetLogy()
c1.SaveAs(outDir+dir+"/SamplingEnergy_all"+binning+"_logy.png")
pad1.SetLogy(0)
c1.Clear()
inFile.Close()
def plotSLDataMCRatio(dataFile, mcFile, binning):
if not "appended.root" in mcFile or not "appended.root" in dataFile:
print "Error: plotSL.py must run on two files ending in \"appended.root\", but was given", mcFile, "and", dataFile
print "Exiting..."
return
if not binning[0] == '_':
binning = '_'+binning
outDir = dataFile[:-5]+'/'
if not os.path.exists(outDir):
os.mkdir(outDir)
outDir += "plotSLDataMCRatio/"
if not os.path.exists(outDir):
os.mkdir(outDir)
AtlasStyle.SetAtlasStyle()
gROOT.ProcessLine("gErrorIgnoreLevel = 2000") #Ignore TCanvas::Print info
mcFile = TFile.Open(mcFile, "READ");
mcKeyList = [key.GetName() for key in mcFile.GetListOfKeys()] #List of top level objects
#mcDir = [key for key in mcKeyList if "Iteration" in key and "NoCorr" in key] #List of all directories
mcDir = [key for key in mcKeyList if "Iteration" in key and "Nominal" in key] #List of all directories
mcDir = mcFile.Get( mcDir[0] )
dataFile = TFile.Open(dataFile, "READ");
dataKeyList = [key.GetName() for key in dataFile.GetListOfKeys()] #List of top level objects
#dataDir = [key for key in dataKeyList if "Iteration" in key and "NoCorr" in key] #List of all directories
dataDir = [key for key in dataKeyList if "Iteration" in key and "Nominal" in key] #List of all directories
dataDir = dataFile.Get( dataDir[0] )
c1 = TCanvas()
numSamples = 24
sampleName = ["PreSamplerB", "EMB1", "EMB2", "EMB3", "PreSamplerE", "EME1", "EME2", "HEC0", "HEC1", "HEC2", "HEC3", "TileBar0", "TileBar1", "TileBar2", "TileGap1", "TileGap2", "TileGap3", "TileExt0", "TileExt1", "TileExt2", "FCAL0", "FCAL1", "FCAL2", "MINIFCAL0", "MINIFCAL1", "MINIFCAL2", "MINIFCAL3"]
sampleSubset = [0, 1, 2, 3, 11, 12, 13]
#################### New Histograms ##########################
print "Plotting sampling layer energy ratio "
thisSample = []
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.SetRightMargin(0.1)
pad1.Draw()
pad1.cd()
## Draw a ghost copy for it's axis first ##
thisSample.append(mcDir.Get("prof_recoilPt_SamplingLayerPercent0"+binning) )
#thisSample[-1].Add(thisSample[-1], -1.)
thisSample[-1].GetYaxis().SetTitle( "Rel. Uncert. of Recoil Energy per Layer" )
thisSample[-1].GetYaxis().SetRangeUser(-0.2,0.2)
thisSample[-1].SetLineColor(kWhite)
thisSample[-1].SetMarkerColor(kWhite)
thisSample[-1].Draw("hist l")
for iSample in range(0, numSamples):
thisSample.append( mcDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning) )
thisSample[-1].SetName(thisSample[-1].GetName()+str(iSample))
dataSample = dataDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning)
thisSample[-1].Add(dataSample, -1.)
thisSample[-1].Divide(dataSample)
thisSample[-1].GetYaxis().SetRangeUser(-0.2,0.2)
#thisSample[-1].GetXaxis().SetRangeUser(200., 2000.)
thisSample[-1].SetLineColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerSize(0.5)
if(iSample%3 == 0):
thisSample[-1].SetLineStyle(1)
elif(iSample%3==1):
thisSample[-1].SetLineStyle(9)
thisSample[-1].SetLineWidth(3)
else:
thisSample[-1].SetLineStyle(2)
leg.AddEntry(thisSample[-1], sampleName[iSample], "l")
thisSample[-1].Draw("same hist l")
c1.cd()
leg.Draw()
c1.SaveAs(outDir+"Frac_SamplingEnergy_all"+binning+".png")
# pad1.SetLogy()
# c1.SaveAs(outDir+"SamplingEnergy_all"+binning+"_logy.png")
# pad1.SetLogy(0)
c1.Clear()
###### Do straight difference ##########
thisSample = []
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.Draw()
pad1.cd()
## Draw a ghost copy for it's axis first ##
thisSample.append(mcDir.Get("prof_recoilPt_SamplingLayerPercent0"+binning) )
thisSample[-1].Add(thisSample[-1], -1.)
thisSample[-1].GetYaxis().SetTitle( "Difference in Recoil Energy per Layer" )
thisSample[-1].GetYaxis().SetRangeUser(-0.1,0.1)
thisSample[-1].SetLineColor(kWhite)
thisSample[-1].SetMarkerColor(kWhite)
thisSample[-1].Draw("hist l")
for iSample in range(0, numSamples):
thisSample.append( mcDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning) )
thisSample[-1].SetName(thisSample[-1].GetName()+str(iSample))
dataSample = dataDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning)
thisSample[-1].Add(dataSample, -1.)
thisSample[-1].GetYaxis().SetRangeUser(-0.1,0.1)
#thisSample[-1].GetXaxis().SetRangeUser(200., 2000.)
thisSample[-1].SetLineColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerSize(0.5)
if(iSample%3 == 0):
thisSample[-1].SetLineStyle(1)
elif(iSample%3==1):
thisSample[-1].SetLineStyle(9)
thisSample[-1].SetLineWidth(3)
else:
thisSample[-1].SetLineStyle(2)
leg.AddEntry(thisSample[-1], sampleName[iSample], "l")
thisSample[-1].Draw("same hist l")
c1.cd()
leg.Draw()
c1.SaveAs(outDir+"Diff_SamplingEnergy_all"+binning+".png")
c1.Clear()
###################################### Subset of sample layers only ###################################################
#################### New Histograms ##########################
print "Plotting sampling layer energy ratio "
thisSample = []
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.SetRightMargin(0.1)
pad1.Draw()
pad1.cd()
## Draw a ghost copy for it's axis first ##
thisSample.append(mcDir.Get("prof_recoilPt_SamplingLayerPercent0"+binning) )
#thisSample[-1].Add(thisSample[-1], -1.)
thisSample[-1].GetYaxis().SetTitle( "Rel. Uncert. of Recoil Energy per Layer" )
thisSample[-1].GetYaxis().SetRangeUser(-0.2,0.2)
thisSample[-1].SetLineColor(kWhite)
thisSample[-1].SetMarkerColor(kWhite)
thisSample[-1].Draw("hist l")
for iSample in sampleSubset:
thisSample.append( mcDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning) )
thisSample[-1].SetName(thisSample[-1].GetName()+str(iSample))
dataSample = dataDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning)
thisSample[-1].Add(dataSample, -1.)
thisSample[-1].Divide(dataSample)
thisSample[-1].GetYaxis().SetRangeUser(-0.2,0.2)
#thisSample[-1].GetXaxis().SetRangeUser(200., 2000.)
thisSample[-1].SetLineColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerSize(0.5)
if(iSample%3 == 0):
thisSample[-1].SetLineStyle(1)
elif(iSample%3==1):
thisSample[-1].SetLineStyle(9)
thisSample[-1].SetLineWidth(3)
else:
thisSample[-1].SetLineStyle(2)
leg.AddEntry(thisSample[-1], sampleName[iSample], "l")
thisSample[-1].Draw("same hist l")
c1.cd()
leg.Draw()
c1.SaveAs(outDir+"Frac_SubsetSamplingEnergy_all"+binning+".png")
# pad1.SetLogy()
# c1.SaveAs(outDir+"SamplingEnergy_all"+binning+"_logy.png")
# pad1.SetLogy(0)
c1.Clear()
###### Do straight difference ##########
thisSample = []
leg = TLegend(0.83, 0.15, 0.99, 0.95)
pad1 = TPad("pad1", "", 0, 0, 0.83, 1)
pad1.Draw()
pad1.cd()
## Draw a ghost copy for it's axis first ##
thisSample.append(mcDir.Get("prof_recoilPt_SamplingLayerPercent0"+binning) )
thisSample[-1].Add(thisSample[-1], -1.)
thisSample[-1].GetYaxis().SetTitle( "Difference in Recoil Energy per Layer" )
thisSample[-1].GetYaxis().SetRangeUser(-0.1,0.1)
thisSample[-1].SetLineColor(kWhite)
thisSample[-1].SetMarkerColor(kWhite)
thisSample[-1].Draw("hist l")
for iSample in sampleSubset:
thisSample.append( mcDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning) )
thisSample[-1].SetName(thisSample[-1].GetName()+str(iSample))
dataSample = dataDir.Get("prof_recoilPt_SamplingLayerPercent"+str(iSample)+binning)
thisSample[-1].Add(dataSample, -1.)
thisSample[-1].GetYaxis().SetRangeUser(-0.1,0.1)
#thisSample[-1].GetXaxis().SetRangeUser(200., 2000.)
thisSample[-1].SetLineColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerColor( gStyle.GetColorPalette(10*iSample+1) )
thisSample[-1].SetMarkerSize(0.5)
if(iSample%3 == 0):
thisSample[-1].SetLineStyle(1)
elif(iSample%3==1):
thisSample[-1].SetLineStyle(9)
thisSample[-1].SetLineWidth(3)
else:
thisSample[-1].SetLineStyle(2)
leg.AddEntry(thisSample[-1], sampleName[iSample], "l")
thisSample[-1].Draw("same hist l")
c1.cd()
leg.Draw()
c1.SaveAs(outDir+"Diff_SubsetSamplingEnergy_all"+binning+".png")
c1.Clear()
