import ROOT
import collections

ana_tex = "ttV"

### variable list
variables = {
    "z_pt":{"name":"z_pt","title":"p_{T}^{Z} [GeV]","bin":200,"xmin":0,"xmax":1000},
    "z_m":{"name":"z_m","title":"m_{Z} [GeV]","bin":50,"xmin":0,"xmax":500},
    "l1_pt":{"name":"l1_pt","title":"p_{T}^{l, 1} [GeV]","bin":250,"xmin":0,"xmax":1000},
    "l2_pt":{"name":"l2_pt","title":"p_{T}^{l, 2} [GeV]","bin":250,"xmin":0,"xmax":1000},
    "met":{"name":"met_pt","title":"E_{T}^{miss}","bin":100,"xmin":0,"xmax":500},
    "nljets":{"name":"nljets","title":"N_{light}","bin":10,"xmin":0,"xmax":10},
    "nbjets":{"name":"nbjets","title":"N_{b-jets}","bin":10,"xmin":0,"xmax":10},
    "njets":{"name":"njets","title":"N_{jets}","bin":10,"xmin":0,"xmax":10},

}


colors = {}
colors['ttV'] = ROOT.kRed
colors['V+jets'] = ROOT.kGreen+2

signal_groups = collections.OrderedDict()
signal_groups['ttV'] = ['pp_ttv01j_5f']


background_groups = collections.OrderedDict()
background_groups['V+jets'] = ['pp_v0123j_5f']

# global parameters
intLumi = 3.0e+07
delphesVersion = '3.4.2'

uncertainties = []
uncertainties.append([0., 0.])
uncertainties.append([0.02, 0.0])
uncertainties.append([0.02, 0.02])
uncertainties.append([0.02, 0.10])

# the first time needs to be set to True
runFull = True

# base pre-selections
selbase = 'l1_pt > 20. && l2_pt > 20.'

# add mass-dependent list of event selections here if needed...

selections = collections.OrderedDict()
selections['ttV'] = []
selections['ttV'].append(selbase)
selections['ttV'].append(selbase + '&& njets>3')
selections['ttV'].append(selbase + '&& nbjets>0 && njets>3')

b0d7bc8759f9b5bad77f0c98155dba11831938bb
<mask token>

<mask token>
uncertainties.append([0.0, 0.0])
uncertainties.append([0.02, 0.0])
uncertainties.append([0.02, 0.02])
uncertainties.append([0.02, 0.1])
<mask token>
selections['ttV'].append(selbase)
selections['ttV'].append(selbase + '&& njets>3')
selections['ttV'].append(selbase + '&& nbjets>0 && njets>3')

<mask token>
ana_tex = 'ttV'
variables = {'z_pt': {'name': 'z_pt', 'title': 'p_{T}^{Z} [GeV]', 'bin': 
    200, 'xmin': 0, 'xmax': 1000}, 'z_m': {'name': 'z_m', 'title':
    'm_{Z} [GeV]', 'bin': 50, 'xmin': 0, 'xmax': 500}, 'l1_pt': {'name':
    'l1_pt', 'title': 'p_{T}^{l, 1} [GeV]', 'bin': 250, 'xmin': 0, 'xmax': 
    1000}, 'l2_pt': {'name': 'l2_pt', 'title': 'p_{T}^{l, 2} [GeV]', 'bin':
    250, 'xmin': 0, 'xmax': 1000}, 'met': {'name': 'met_pt', 'title':
    'E_{T}^{miss}', 'bin': 100, 'xmin': 0, 'xmax': 500}, 'nljets': {'name':
    'nljets', 'title': 'N_{light}', 'bin': 10, 'xmin': 0, 'xmax': 10},
    'nbjets': {'name': 'nbjets', 'title': 'N_{b-jets}', 'bin': 10, 'xmin': 
    0, 'xmax': 10}, 'njets': {'name': 'njets', 'title': 'N_{jets}', 'bin': 
    10, 'xmin': 0, 'xmax': 10}}
colors = {}
colors['ttV'] = ROOT.kRed
colors['V+jets'] = ROOT.kGreen + 2
signal_groups = collections.OrderedDict()
signal_groups['ttV'] = ['pp_ttv01j_5f']
background_groups = collections.OrderedDict()
background_groups['V+jets'] = ['pp_v0123j_5f']
intLumi = 30000000.0
delphesVersion = '3.4.2'
uncertainties = []
uncertainties.append([0.0, 0.0])
uncertainties.append([0.02, 0.0])
uncertainties.append([0.02, 0.02])
uncertainties.append([0.02, 0.1])
runFull = True
selbase = 'l1_pt > 20. && l2_pt > 20.'
selections = collections.OrderedDict()
selections['ttV'] = []
selections['ttV'].append(selbase)
selections['ttV'].append(selbase + '&& njets>3')
selections['ttV'].append(selbase + '&& nbjets>0 && njets>3')

import ROOT
import collections
ana_tex = 'ttV'
variables = {'z_pt': {'name': 'z_pt', 'title': 'p_{T}^{Z} [GeV]', 'bin': 
    200, 'xmin': 0, 'xmax': 1000}, 'z_m': {'name': 'z_m', 'title':
    'm_{Z} [GeV]', 'bin': 50, 'xmin': 0, 'xmax': 500}, 'l1_pt': {'name':
    'l1_pt', 'title': 'p_{T}^{l, 1} [GeV]', 'bin': 250, 'xmin': 0, 'xmax': 
    1000}, 'l2_pt': {'name': 'l2_pt', 'title': 'p_{T}^{l, 2} [GeV]', 'bin':
    250, 'xmin': 0, 'xmax': 1000}, 'met': {'name': 'met_pt', 'title':
    'E_{T}^{miss}', 'bin': 100, 'xmin': 0, 'xmax': 500}, 'nljets': {'name':
    'nljets', 'title': 'N_{light}', 'bin': 10, 'xmin': 0, 'xmax': 10},
    'nbjets': {'name': 'nbjets', 'title': 'N_{b-jets}', 'bin': 10, 'xmin': 
    0, 'xmax': 10}, 'njets': {'name': 'njets', 'title': 'N_{jets}', 'bin': 
    10, 'xmin': 0, 'xmax': 10}}
colors = {}
colors['ttV'] = ROOT.kRed
colors['V+jets'] = ROOT.kGreen + 2
signal_groups = collections.OrderedDict()
signal_groups['ttV'] = ['pp_ttv01j_5f']
background_groups = collections.OrderedDict()
background_groups['V+jets'] = ['pp_v0123j_5f']
intLumi = 30000000.0
delphesVersion = '3.4.2'
uncertainties = []
uncertainties.append([0.0, 0.0])
uncertainties.append([0.02, 0.0])
uncertainties.append([0.02, 0.02])
uncertainties.append([0.02, 0.1])
runFull = True
selbase = 'l1_pt > 20. && l2_pt > 20.'
selections = collections.OrderedDict()
selections['ttV'] = []
selections['ttV'].append(selbase)
selections['ttV'].append(selbase + '&& njets>3')
selections['ttV'].append(selbase + '&& nbjets>0 && njets>3')

import ROOT
import collections

ana_tex = "ttV"

### variable list
variables = {
    "z_pt":{"name":"z_pt","title":"p_{T}^{Z} [GeV]","bin":200,"xmin":0,"xmax":1000},
    "z_m":{"name":"z_m","title":"m_{Z} [GeV]","bin":50,"xmin":0,"xmax":500},
    "l1_pt":{"name":"l1_pt","title":"p_{T}^{l, 1} [GeV]","bin":250,"xmin":0,"xmax":1000},
    "l2_pt":{"name":"l2_pt","title":"p_{T}^{l, 2} [GeV]","bin":250,"xmin":0,"xmax":1000},
    "met":{"name":"met_pt","title":"E_{T}^{miss}","bin":100,"xmin":0,"xmax":500},
    "nljets":{"name":"nljets","title":"N_{light}","bin":10,"xmin":0,"xmax":10},
    "nbjets":{"name":"nbjets","title":"N_{b-jets}","bin":10,"xmin":0,"xmax":10},
    "njets":{"name":"njets","title":"N_{jets}","bin":10,"xmin":0,"xmax":10},

}


colors = {}
colors['ttV'] = ROOT.kRed
colors['V+jets'] = ROOT.kGreen+2

signal_groups = collections.OrderedDict()
signal_groups['ttV'] = ['pp_ttv01j_5f']


background_groups = collections.OrderedDict()
background_groups['V+jets'] = ['pp_v0123j_5f']

# global parameters
intLumi = 3.0e+07
delphesVersion = '3.4.2'

uncertainties = []
uncertainties.append([0., 0.])
uncertainties.append([0.02, 0.0])
uncertainties.append([0.02, 0.02])
uncertainties.append([0.02, 0.10])

# the first time needs to be set to True
runFull = True

# base pre-selections
selbase = 'l1_pt > 20. && l2_pt > 20.'

# add mass-dependent list of event selections here if needed...

selections = collections.OrderedDict()
selections['ttV'] = []
selections['ttV'].append(selbase)
selections['ttV'].append(selbase + '&& njets>3')
selections['ttV'].append(selbase + '&& nbjets>0 && njets>3')
