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TauEffPlotterMM.py
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TauEffPlotterMM.py
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'''
Base class to do WH plotting.
Author: Evan K. Friis, UW
Takes as input a set of ROOT [files] with analysis histgrams, and the corresponding
lumicalc.sum [lumifiles] that hve the effective lumi for each sample.
If [blind] is true, data in the p1p2p3 region will not be plotted.
'''
import rootpy.plotting.views as views
import rootpy.plotting as plotting
#from rootpy.tree import TreeChain
import rootpy.io
from FinalStateAnalysis.PlotTools.Plotter import Plotter
from FinalStateAnalysis.PlotTools.PoissonView import PoissonView
from FinalStateAnalysis.PlotTools.HistToTGRaphErrors import HistToTGRaphErrors, HistStackToTGRaphErrors
from FinalStateAnalysis.PlotTools.InflateErrorView import InflateErrorView
from FinalStateAnalysis.MetaData.data_styles import data_styles
import FinalStateAnalysis.Utilities.prettyjson as prettyjson
from TauEffPlotterBase import TauEffPlotterBase, remove_name_entry
import sys
import os
import glob
import pprint
import ROOT
import fnmatch
import math
ROOT.gROOT.SetBatch(True)
ROOT.gStyle.SetOptTitle(0)
def quad(*xs):
return math.sqrt(sum(x*x for x in xs))
class TauEffPlotterMM(TauEffPlotterBase):
def __init__(self):
super(TauEffPlotterMM, self).__init__('MM')
self.sample_mapping['Zjets_M50'] = 'zmm'
def get_qcd_estimation(self):
qcd_reg = 'h2Tau/ss'
#MC ZJets view
neg_zjet = views.ScaleView(self.get_view('Zjets*'),-1)
neg_zjet = views.SubdirectoryView(neg_zjet,qcd_reg)
#DATA WJets estimation
neg_wjet = views.ScaleView(self.get_view('WplusJets*'),-1)
neg_wjet = views.SubdirectoryView(neg_wjet,qcd_reg)
#Data view
data_view= views.SubdirectoryView(self.get_view('data'),qcd_reg)
qcd_est = views.SumView(data_view, neg_zjet)
qcd_est = views.SumView(qcd_est , neg_wjet)
qcd_est = views.StyleView(qcd_est, **remove_name_entry(data_styles['QCD*']))
qcd_est = views.TitleView(qcd_est, 'QCD')
return qcd_est
def make_folder_views(self, folder, rebin):
iso_name = folder.split('/')[0]
zjets_mc = self.get_view_dir('Zjets*' , rebin, folder)
data = self.get_view_dir('data' , rebin, folder)
ttbar = self.get_view_dir('TTplusJets*', rebin, folder)
wjet_mc = self.get_view_dir('WplusJets*' , rebin, folder)
diboson = views.TitleView(
views.StyleView(
views.SumView(
self.get_view_dir('WZ*' , rebin, folder),
self.get_view_dir('WW*' , rebin, folder),
self.get_view_dir('ZZ*' , rebin, folder)
),
**remove_name_entry(data_styles['WZ*'])
),
'diboson'
)
#makes QCD Estimation view
qcd_est = self.rebin_view(self.get_qcd_estimation(), rebin)
return {
'Z_jets' : zjets_mc,
'ttbar' : ttbar,
'diboson' : diboson,
'WJets' : wjet_mc,
'QCD' : qcd_est,
'data' : data,
}
def plot_with_estimate(self, folder, variable, rebin=1, xaxis='', leftside=True,
xrange=None, show_error=True, logscale=False, yrange=None):
folder_views = self.make_folder_views(folder, rebin)
zjets_mc = folder_views['Z_jets' ]
ttbar = folder_views['ttbar' ]
diboson = folder_views['diboson']
wjet_mc = folder_views['WJets' ]
qcd_est = folder_views['QCD' ]
data = folder_views['data' ]
stack = views.StackView(qcd_est, wjet_mc, ttbar, diboson, zjets_mc).Get(variable)
stack.Draw()
stack.GetHistogram().GetXaxis().SetTitle(xaxis)
if xrange:
stack.GetXaxis().SetRangeUser(xrange[0], xrange[1])
if yrange:
stack.SetMinimum(yrange[0])
stack.SetMaximum(yrange[1])
#stack.GetYaxis().SetRangeUser(yrange[0], yrange[1])
stack.Draw()
self.keep.append(stack)
#print os.path.join(folder,variable)
data_h = data.Get(variable)
data_h.Draw('same')
self.keep.append(data_h)
# Make sure we can see everything
if data_h.GetMaximum() > stack.GetMaximum():
stack.SetMaximum(1.2*data_h.GetMaximum())
if show_error:
stack_sum = sum(stack.GetHists())
stack_sum.SetMarkerSize(0)
stack_sum.SetFillColor(1)
stack_sum.SetFillStyle(3013)
stack_sum.legendstyle = 'f'
self.keep.append(stack_sum)
stack_sum.Draw('pe2,same')
# Add legend
self.add_legend([data_h, stack], leftside, entries=5)
self.add_cms_blurb(self.sqrts)
if logscale:
self.pad.SetLogy()
self.add_ratio_plot(data_h, stack, xrange, 0.2)
def get_signal_views(self, iso_name, variable):
folder = 'h2Tau/os/'
nbins = self.get_view('Zjets*').Get('/'.join([folder,variable])).GetNbinsX()
return self.make_folder_views(folder, nbins)
def map_interesting_directories(self, selection_region, var, himt_region = 'MT70_120'):
ret = {}
for sign in ['os', 'ss']:
ret[sign] = self.map_yields(
os.path.join( selection_region, sign ),
var
)
return ret
def dump_selection_info(self, tauids, var):
ret = {}
for tau_id in tauids:
ret[tau_id] = self.map_interesting_directories(
tau_id,
var
)
return ret
if __name__ <> "__main__":
sys.exit(0)
jobid = os.environ['jobid']
toPlot = {
'nvtx' : { 'xaxis' : 'N_{vtx}' , 'rebin' : 1 , 'leftside' : False},
"m1Pt" : { 'xaxis' : 'p_{#mu_{1} T} (GeV)' , 'rebin' : 2 , 'leftside' : False},
"m2Pt" : { 'xaxis' : 'p_{#mu_{2} T} (GeV)' , 'rebin' : 2 , 'leftside' : False},
"m1AbsEta" : { 'xaxis' : '|#eta|_{#mu_{1}} (GeV)', 'rebin' : 2 , 'leftside' : False, 'xrange' : (0,3)},
"m2AbsEta" : { 'xaxis' : '|#eta|_{#mu_{2}} (GeV)', 'rebin' : 2 , 'leftside' : False, 'xrange' : (0,3)},
"m1_m2_Mass" : { 'xaxis' : 'M_{#mu#mu} (GeV)' , 'rebin' : 1 , 'leftside' : False, 'xrange' : (60,120)},
"nvtx" : { 'xaxis' : 'Number of vertices' , 'rebin' : 1 , 'leftside' : False},
"type1_pfMetEt" : { 'xaxis' : 'Type 1 MET E_{T} (GeV)', 'rebin' : 2, 'leftside' : False, 'xrange' : (0,90)},
"type1_pfMetPhi" : { 'xaxis' : 'Type 1 MET #phi' , 'rebin' : 1, 'leftside' : False, 'xrange' : (-3.5,3.5)},
"MET_Z_perp" : { 'xaxis' : 'Type 1 MET perp. to Z (GeV)', 'rebin' : 2, 'leftside' : False, 'xrange' : (0,80)},
"MET_Z_para" : { 'xaxis' : 'Type 1 MET parallel. to Z (GeV)', 'rebin' : 2, 'leftside' : False, 'xrange' : (0,80)},
}
plotter = TauEffPlotterMM()
print '\n\nPlotting MM\n\n'
folder = 'h2Tau/os'
plotter.set_subdir('signal')
for var, kwargs in toPlot.iteritems():
## plotter.plot_mc_vs_data(folder, var, **kwargs)
## plotter.save('mc_vs_data_%s_%s' % ('signal_region', var) )
plotter.plot_with_estimate(folder, var, **kwargs)
plotter.save('final_%s_%s' % ('signal_region', var) )
if var == "m1_m2_Mass":
kwargs['logscale']=True
kwargs['yrange']=[1,3*10**8]
plotter.plot_with_estimate(folder, var, **kwargs)
plotter.save('final_%s_%s_logscale' % ('signal_region', var) )
del kwargs['logscale']
del kwargs['yrange']
plotter.set_subdir('')
plotter.write_summary('','m1_m2_Mass')
yield_dump = plotter.dump_selection_info(['h2Tau'], 'm1_m2_Mass')
with open('results/%s/plots/mm/yield_dump.json' % jobid, 'w') as jfile:
jfile.write(prettyjson.dumps(yield_dump) )
#Make QCD region plots
folder = folder.replace('os','ss')
plotter.set_subdir('qcd')
for var, kwargs in toPlot.iteritems():
plotter.plot_mc_vs_data(folder, var, **kwargs)
plotter.save('mc_vs_data_%s_%s' % ('qcd_region', var) )
#FIXME: _understand systamtic uncertainties:
# _ask Evan for Zrecoil correction in MVA MET
# _make uncertainties on Zrecoil correction --> propagate to WJets Ztautau QCD ecc...
# _make #evts passing cuts #of MC events passing cuts (+ stat+sys)