# Logging
import StopsDilepton.tools.logger as logger
logger = logger.get_logger('INFO', logFile = None )
histos = {}
for m in ['doubleMu', 'doubleEle', 'muEle']:
plot_path = "png25ns_2l_mAODv2_2100_noPU_new/%s_offZ_standard_isOS-leadingLepIsTight-njet2-nbtag1-met80-metSig5-dPhiJet0-dPhiJet1/" % m
for fh in ["leadingLepIso"]:
for swap in ["L1", "L2"]:
for fs in ["mm","me","em","ee"]:
ofile = os.path.join(plot_directory, plot_path, "dl_mt2ll_%s_swap%s_%s.pkl"%(fh, swap, fs))
if os.path.isfile(ofile):
logger.info( "Loading %s", ofile )
histos["%s_mt2ll_%s_swap%s_%s"%(m, fh, swap, fs)] = pickle.load( file( ofile) )
else:
logger.warning( "File not found: %s", ofile)
def transpose(l):
return list(map(list, zip(*l)))
def add_histos( l ):
res = l[0].Clone()
for h in l[1:]: res.Add(h)
return res
for name, fss in [
['doubleMu', ['mm']],
['muEle', ['me', 'em']],
['doubleEle', ['ee']]
]:
to_be_added = []
else:
sig, fac = s, 1
try:
stack.append([eval(sig)])
if hasattr(stack[-1][0], "scale"):
stack[-1][0].scale *= fac
elif fac != 1:
stack[-1][0].scale = fac
else:
pass
if fac != 1:
stack[-1][0].name += " x" + str(fac)
logger.info("Adding sample %s with factor %3.2f", sig, fac)
except NameError:
logger.warning("Could not add signal %s", s)
sequence = []
rev = reversed if args.reversed else lambda x: x
for i_comb in rev(range(len(cuts) + 1)):
#for i_comb in [len(cuts)]:
for comb in itertools.combinations(cuts, i_comb):
if not args.noData:
data_sample.setSelectionString([dataFilterCut, trigger])
for sample in mc:
sample.setSelectionString([mcFilterCut, trigger])
presel = preselection + list(comb)
sig, fac = split[0], int(split[1])
else:
sig, fac = s, 1
try:
stack.append( [eval(sig)] )
if hasattr(stack[-1][0], "scale"):
stack[-1][0].scale*=fac
elif fac!=1:
stack[-1][0].scale = fac
else: pass
if fac!=1:
stack[-1][0].name+=" x"+str(fac)
logger.info( "Adding sample %s with factor %3.2f", sig, fac)
except NameError:
logger.warning( "Could not add signal %s", s)
sequence = []
#if args.zMode == 'onZ':
#
# def makeUParaUPerp( data ):
#
# qx = data.dl_pt*cos(data.dl_phi)
# qy = data.dl_pt*sin(data.dl_phi)
#
# ux = -data.met_pt*cos(data.met_phi) - qx
# uy = -data.met_pt*sin(data.met_phi) - qy
# data.upara = (ux*qx+uy*qy)/data.dl_pt
# data.uperp = (ux*qy-uy*qx)/data.dl_pt
#
# sequence.append( makeUParaUPerp )
else:
sig, fac = s, 1
try:
stack.append([eval(sig)])
if hasattr(stack[-1][0], "scale"):
stack[-1][0].scale *= fac
elif fac != 1:
stack[-1][0].scale = fac
else:
pass
if fac != 1:
stack[-1][0].name += " x" + str(fac)
logger.info("Adding sample %s with factor %3.2f", sig, fac)
except NameError:
logger.warning("Could not add signal %s", s)
def fromTau(gen_lepton):
return gen_lepton['n_tau'] > 0
def prompt(gen_lepton):
return not fromTau(
gen_lepton) and gen_lepton['n_B'] == 0 and gen_lepton['n_D'] == 0
def nonPrompt(gen_lepton):
return not fromTau(gen_lepton) and not (gen_lepton['n_B'] == 0
and gen_lepton['n_D'] == 0)
raise ValueError( "Need at least one sample. Got %r",samples )
lumiScaleFactor = xSection*targetLumi/float(sample.normalization) if xSection is not None else None
from StopsDilepton.tools.puReweighting import getReweightingFunction
puRW = getReweightingFunction(data="PU_2100_XSecCentral", mc="Fall15")
puRWDown = getReweightingFunction(data="PU_2100_XSecDown", mc="Fall15")
puRWUp = getReweightingFunction(data="PU_2100_XSecUp", mc="Fall15")
# output directory
outDir = os.path.join(options.targetDir, options.processingEra, "gen", sample.name)
if os.path.exists(outDir) and options.overwrite:
if options.nJobs > 1:
logger.warning( "NOT removing directory %s because nJobs = %i", outDir, options.nJobs )
else:
logger.info( "Output directory %s exists. Deleting.", outDir )
shutil.rmtree(outDir)
try: #Avoid trouble with race conditions in multithreading
os.makedirs(outDir)
logger.info( "Created output directory %s.", outDir )
except:
pass
new_variables = [ 'weight/F']
read_variables = []
read_variables+= [Variable.fromString('nTrueInt/F')]
# reading gen particles for top pt reweighting
read_variables.append( Variable.fromString('ngenPartAll/I') )
if not '_reHadd_' in f:
to_skip = False
for skip in options.skip:
if skip in f:
logger.info("Found skip string %s in %s. Skipping.",
skip, f)
to_skip = True
break
if to_skip: continue
isOK = checkRootFile( full_filename, checkForObjects = [options.treeName]) \
if options.treeName is not None else checkRootFile( full_filename )
if isOK:
rootFiles.append(f)
else:
logger.warning(
"File %s does not look OK. Checked for tree: %r",
full_filename, options.treeName)
else:
logger.info("Found '_reHadd_' in file %s in %s. Skipping.",
full_filename, dirName)
job = []
jobsize = 0
for fname in rootFiles:
filename, file_extension = os.path.splitext(fname)
n_str = filename.split('_')[-1]
if n_str.isdigit():
full_filename = os.path.join(dirName, fname)
jobsize += os.path.getsize(full_filename)
job.append(full_filename)
if jobsize > 1024**3 * options.sizeGB:
jobs.append(job)
#Calculating systematics
h_summed = {k: plot_mc[k].histos_added[0][0].Clone() for k in plot_mc.keys()}
#Normalize systematic shapes
for k in h_summed.keys():
if k is None: continue
try:
bin_low = h_summed[None].FindBin(x_norm[0])
bin_high = h_summed[None].FindBin(x_norm[1])
# if 'njet' in plot_mc[k].name.lower(): print "before", k,h_summed[k], bin_low, bin_high, h_summed[k].Integral(bin_low, bin_high), [ h_summed[k][i] for i in range(10) ]
h_summed[k].Scale(
h_summed[None].Integral(bin_low, bin_high) / h_summed[k].Integral(bin_low, bin_high)
)
# if 'njet' in plot_mc[k].name.lower(): print "after", k,h_summed[k], bin_low, bin_high, h_summed[k].Integral(bin_low, bin_high), [ h_summed[k][i] for i in range(10) ]
except ZeroDivisionError:
logger.warning( "Found zero for variation %s of variable %s", k, plot_mc[k].name )
h_rel_err = h_summed[None].Clone()
h_rel_err.Reset()
h_sys = {}
for k, s1, s2 in sys_pairs:
h_sys[k] = h_summed[s1].Clone()
h_sys[k].Scale(-1)
h_sys[k].Add(h_summed[s2])
# h_sys[k].Divide(h_summed[None])
h_rel_err = h_summed[None].Clone()
h_rel_err.Reset()
lumiScaleFactor = xSection * targetLumi / float(
sample.normalization) if xSection is not None else None
from StopsDilepton.tools.puReweighting import getReweightingFunction
puRW = getReweightingFunction(data="PU_2100_XSecCentral", mc="Fall15")
puRWDown = getReweightingFunction(data="PU_2100_XSecDown", mc="Fall15")
puRWUp = getReweightingFunction(data="PU_2100_XSecUp", mc="Fall15")
# output directory
outDir = os.path.join(options.targetDir, options.processingEra, "gen",
sample.name)
if os.path.exists(outDir) and options.overwrite:
if options.nJobs > 1:
logger.warning("NOT removing directory %s because nJobs = %i", outDir,
options.nJobs)
else:
logger.info("Output directory %s exists. Deleting.", outDir)
shutil.rmtree(outDir)
try: #Avoid trouble with race conditions in multithreading
os.makedirs(outDir)
logger.info("Created output directory %s.", outDir)
except:
pass
new_variables = ['weight/F']
read_variables = []
read_variables += [Variable.fromString('nTrueInt/F')]
# reading gen particles for top pt reweighting
read_variables.append(Variable.fromString('ngenPartAll/I'))
if f.endswith('.root'):
full_filename = os.path.join(dirName, f)
if not '_reHadd_' in f:
to_skip = False
for skip in options.skip:
if skip in f:
logger.info( "Found skip string %s in %s. Skipping.", skip, f )
to_skip = True
break
if to_skip: continue
isOK = checkRootFile( full_filename, checkForObjects = [options.treeName]) \
if options.treeName is not None else checkRootFile( full_filename )
if isOK:
rootFiles.append( f )
else:
logger.warning( "File %s does not look OK. Checked for tree: %r", full_filename, options.treeName )
else:
logger.info( "Found '_reHadd_' in file %s in %s. Skipping.", full_filename, dirName )
job = []
jobsize = 0
for fname in rootFiles:
filename, file_extension = os.path.splitext(fname)
n_str = filename.split('_')[-1]
if n_str.isdigit():
full_filename = os.path.join(dirName, fname)
jobsize += os.path.getsize( full_filename )
job.append( full_filename )
if jobsize>1024**3*options.sizeGB:
jobs.append(job)
job = []
jobsize = 0
sig, fac = split[0], int(split[1])
else:
sig, fac = s, 1
try:
stack.append( [eval(sig)] )
if hasattr(stack[-1][0], "scale"):
stack[-1][0].scale*=fac
elif fac!=1:
stack[-1][0].scale = fac
else: pass
if fac!=1:
stack[-1][0].name+=" x"+str(fac)
logger.info( "Adding sample %s with factor %3.2f", sig, fac)
except NameError:
logger.warning( "Could not add signal %s", s)
def fromTau( gen_lepton ):
return gen_lepton['n_tau']>0
def prompt( gen_lepton ):
return not fromTau( gen_lepton) and gen_lepton['n_B']==0 and gen_lepton['n_D']==0
def nonPrompt( gen_lepton ):
return not fromTau( gen_lepton) and not ( gen_lepton['n_B']==0 and gen_lepton['n_D']==0 )
gen_ttbar_sequence = []
# Match l1 and l2
def matchLeptons( data ):
# Get Gen leptons
gen_leps = getCollection(data, "GenLep", ["pt", "eta", "phi", "n_t", "n_W", "n_B", "n_D", "n_tau", "pdgId"], "nGenLep" )
non_prompt = filter(lambda l: nonPrompt(l), gen_leps )
logger.info( "MET %3.2f genMET %3.2f pt(neutrinos from W) %s pt(neutrinos from tau from W) %s pt(other neutrinos) %s", \
reader.data.met_pt, reader.data.met_genPt, str_neutrinos_fromW, str_neutrinos_fromTau, str_neutrinos_other )
# Missing energy related
met_pt = reader.data.met_pt
met_phi = reader.data.met_phi
met_genPt = reader.data.met_genPt
met_genPhi = reader.data.met_genPhi
delta_met = sqrt( ( met_pt*cos(met_phi)-met_genPt*cos(met_genPhi) )**2 + ( met_pt*sin(met_phi)-met_genPt*sin(met_genPhi) )**2 )
mt2Calc.reset()
mt2Calc.setMet( met_pt, met_phi )
mt2Calc.setLeptons( reader.data.l1_pt, reader.data.l1_eta, reader.data.l1_phi, reader.data.l2_pt, reader.data.l2_eta, reader.data.l2_phi )
if not mt2Calc.mt2ll() != reader.data.dl_mt2ll:
logger.warning( "MT2 inconsistency!" )
mt2Calc.setMet( met_genPt, met_genPhi )
mt2ll_genMet = mt2Calc.mt2ll()
if mt2ll_genMet<140:
logger.info(bold("MET mismeasurement"))
jets = [ getObjDict(cmg_reader.data, "Jet_", ["pt","eta","phi","mcPt","id"], i) for i in range(cmg_reader.data.nJet) ]
dx, dy = 0., 0.
for j in jets:
if j['mcPt']>0:
dx+=(j['pt']-j['mcPt'])*cos(j['phi'])
dy+=(j['pt']-j['mcPt'])*cos(j['phi'])
if abs(j['pt'] - j['mcPt'])>50:
logger.info( "Mismeasured jet pt %3.2f mcPt %3.2f diff %3.2f, eta %3.2f phi %3.2f id %i", j['pt'], j['mcPt'], j['pt']-j['mcPt'], j['eta'], j['phi'], j['id'] )
corr_pt = localJetResponse.corrected_jet_pt(j['pt'], j['eta'], j['phi'])
local_mism = corr_pt - j['pt']
k: plot_mc[k].histos_added[0][0].Clone()
for k in plot_mc.keys()
}
#Normalize systematic shapes
for k in h_summed.keys():
if k is None: continue
try:
bin_low = h_summed[None].FindBin(x_norm[0])
bin_high = h_summed[None].FindBin(x_norm[1])
# if 'njet' in plot_mc[k].name.lower(): print "before", k,h_summed[k], bin_low, bin_high, h_summed[k].Integral(bin_low, bin_high), [ h_summed[k][i] for i in range(10) ]
h_summed[k].Scale(h_summed[None].Integral(bin_low, bin_high) /
h_summed[k].Integral(bin_low, bin_high))
# if 'njet' in plot_mc[k].name.lower(): print "after", k,h_summed[k], bin_low, bin_high, h_summed[k].Integral(bin_low, bin_high), [ h_summed[k][i] for i in range(10) ]
except ZeroDivisionError:
logger.warning("Found zero for variation %s of variable %s", k,
plot_mc[k].name)
h_rel_err = h_summed[None].Clone()
h_rel_err.Reset()
h_sys = {}
for k, s1, s2 in sys_pairs:
h_sys[k] = h_summed[s1].Clone()
h_sys[k].Scale(-1)
h_sys[k].Add(h_summed[s2])
# h_sys[k].Divide(h_summed[None])
h_rel_err = h_summed[None].Clone()
h_rel_err.Reset()
# Adding in quadrature
