def common1(x) :
x._lumi = {
"mumu" : 1.139e+04,
"muon" : 1.139e+04,
"mcPhot": 1.157e+04,
"phot" : 1.157e+04,
"mcHad" : 5.125e+03,
"had" : 5.125e+03,
"mcMuon": 1.139e+04,
"mcMumu": 1.139e+04,
}
x._triggerEfficiencies = {
"hadBulk": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.950, 0.960, 0.960, 0.970, 0.970, 0.970, 0.980, 0.980, 0.980, 0.980),
}
x._htBinLowerEdges = ( 275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0, 975.0, 1.075e+03, )
x._htMaxForPlot = 1.175e+03
x._htMeans = ( 298.0, 348.0, 416.0, 517.0, 617.0, 719.0, 819.0, 1044., 0.0, 0.0, )
x._observations["nPhot"] = tuple([None, None]+list(x._observations["nPhot"][2:]))
uncs = {"btagUncert": 0.035, "lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10} # SMS other than T1, T2
uncs["btagUncert"] = 0.12 #T1, T2, cMSSM tb10 only
return quadSum(uncs.values())
def common(x) :
common1(x)
systBins = tuple([0,1,2,3,4,5,6,7])
name = x.__class__.__name__
if "le3j" in name :
#1 0.0285990260695
#2 0.0394980874076
#3 0.0517572718323
#4 0.114466557069
#5 0.114466557069
#6 0.157579928392
#7 0.157579928392
#8 0.162175909759
systMagnitudes = (0.03, 0.04, 0.05, 0.11, 0.11, 0.16, 0.16, 0.16)
x._triggerEfficiencies["had"] = (0.895, 0.931, 0.955, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
#1 0.0270903404576
#2 0.0445712283046
#3 0.0609088639964
#4 0.127681484932
#5 0.127681484932
#6 0.127681484932
#7 0.127681484932
#8 0.195374362475
systMagnitudes = (0.03, 0.04, 0.06, 0.13, 0.13, 0.13, 0.13, 0.20)
x._triggerEfficiencies["had"] = (0.9450, 0.980, 0.971, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
else:
systMagnitudes = (0.03, 0.04, 0.06, 0.13, 0.13, 0.16, 0.16, 0.16)
x._triggerEfficiencies["had"] = (0.925, 0.955, 0.962, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
x._mergeBins = None
systBins = systBins
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
systMagnitudes = systMagnitudes
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0,1,2,3,4,5,6,7])
name = x.__class__.__name__
if "le3j" in name :
#1 0.0320545873444
#2 0.0375287336067
#3 0.0743096750102
#4 0.111494351721
#5 0.111494351721
#6 0.111494351721
#7 0.111494351721
#8 0.160744491715
systMagnitudes = (0.03, 0.04, 0.07, 0.11, 0.11, 0.11,0.11,0.16)
x._triggerEfficiencies["had"] = (0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
#1 0.0459013308391
#2 0.0459013308391
#3 0.0874046062946
#4 0.0874046062946
#5 0.119191173705
#6 0.119191173705
#7 0.158743032363
#8 0.158743032363
systMagnitudes = (0.05, 0.05, 0.09, 0.09, 0.12, 0.12,0.16,0.16)
x._triggerEfficiencies["had"] = (0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
else:
systMagnitudes = (0.05, 0.05, 0.09, 0.11, 0.11, 0.11, 0.11, 0.16)
x._triggerEfficiencies["had"] = (0.99, 1.00, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self) :
self._htBinLowerEdges = (250.0, 300.0, 350.0, 450.0)
self._mergeBins = None
self._htMaxForPlot = 600.0
self._htMeans = (265.0, 315.0, 375.0, 475.0) #place-holder values
self._lumi = {
"had": 35.0,
"hadBulk": 35.0,
"muon": 35.0,
"mcMuon": 35.0,
"mcTtw": 35.0,
"phot": 35.0,
"mcPhot": 35.0,
"mcZinv": 35.0,
}
self._triggerEfficiencies = {
"hadBulk":(1.0, 1.0, 1.0, 1.0),
"had": ( 1.0, 1.0, 1.0, 1.0),
"phot": ( 1.0, 1.0, 1.0, 1.0),
"muon": ( 1.0, 1.0, 1.0, 1.0),
}
self._observations = {
"nHadBulk": (844459, 331948, 225649, 110034),
"nHad": ( 33, 11, 8, 5),
"nPhot": ( 24, 4, 6, 1),
"nMuon": ( 13, 5, 5, 2),
}
self._mcExpectationsBeforeTrigger = {
"mcMuon": ( 12.2, 5.2, 4.1, 1.9 ),
"mcTtw": ( 10.5, 4.47, 3.415, 1.692),
"mcPhot": ( 22.4, 7.0, 4.4, 2.1 ),
"mcZinv": ( 8.1, 3.9, 2.586, 1.492),
}
self._mcStatError = {}
self._fixedParameters = {
"sigmaLumiLike": 0.04,
"sigmaPhotZ": [0.40],
"sigmaMuonW": [0.30],
"k_qcd_nom":2.96e-2, #2011
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2]) #2011
}
self._systBins = {
"sigmaPhotZ": (0, 0, 0, 0),
"sigmaMuonW": (0, 0, 0, 0),
}
def common(x):
common1(x)
systBins = tuple([0] * 2 + [1] * 3 + [2] * 1 + [3] * 2 + [4] * 3)
# systBins = tuple([0,1,2,3,3,4,4,5,5,6,6])
name = x.__class__.__name__
if "le3j" in name:
systMagnitudes = (0.05, 0.05, 0.10, 0.20, 0.30) # tmp
# systMagnitudes = (0.05, 0.05, 0.05, 0.10, 0.10, 0.20, 0.30) # tmp
x._triggerEfficiencies["had"] = (0.816, 0.901, 0.988, 0.994, 1.000,
.994, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08,
3.29919975E08, 2.74138825E08,
8.507427E07, 2.8887025E07, 1.09110E07,
4.6215E06, 2.07715E06, 1.031125E06,
1.20755E06)
elif "ge4j" in name:
systMagnitudes = (0.05, 0.10, 0.10, 0.20, 0.30) # dtmp
#systMagnitudes = (0.05, 0.05, 0.05, 0.10, 0.10, 0.20, 0.30) # tmp
x._triggerEfficiencies["had"] = (0.665, 0.666, 0.971, 0.988, 1.000,
1.000, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07,
4.8204025E07, 3.35079E07, 1.582655E07,
7.279475E06, 3.46345E06, 1.732725E06,
8.9562E05, 1.142775E06)
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.25, )
systBins = (0, 0, 0, 0)
else:
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2 + [6]*2)
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["muon"] = (0.875, 0.878, 0.879, 0.881, 0.882, 0.884, 0.885, 0.886, 0.888, 0.887, 0.884)
x._triggerEfficiencies["mumu"] = (0.985, 0.985, 0.986, 0.986, 0.986, 0.986, 0.987, 0.986, 0.987, 0.987, 0.987)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["muon"] = (0.881, 0.882, 0.884, 0.886, 0.888, 0.889, 0.890, 0.891, 0.890, 0.890, 0.896)
x._triggerEfficiencies["mumu"] = (0.984, 0.984, 0.986, 0.985, 0.986, 0.986, 0.986, 0.986, 0.986, 0.988, 0.987)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15,)
systBins = (0, 0, 0, 0)
elif "2b" in name or "3b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2)# + [6]*2)
systMagnitudes = systMagnitudes[:-1]
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2 + [6]*2)
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["muon"] = (0.875, 0.878, 0.879, 0.881, 0.882, 0.884, 0.885, 0.886, 0.888, 0.887, 0.884)
x._triggerEfficiencies["mumu"] = (0.985, 0.985, 0.986, 0.986, 0.986, 0.986, 0.987, 0.986, 0.987, 0.987, 0.987)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["muon"] = (0.881, 0.882, 0.884, 0.886, 0.888, 0.889, 0.890, 0.891, 0.890, 0.890, 0.896)
x._triggerEfficiencies["mumu"] = (0.984, 0.984, 0.986, 0.985, 0.986, 0.986, 0.986, 0.986, 0.986, 0.988, 0.987)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15,)
systBins = (0, 0, 0, 0)
elif "2b" in name or "3b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2)# + [6]*2)
systMagnitudes = systMagnitudes[:-1]
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
#systBins = tuple([0]*4+[1]*2+[2]*2)
systBins = tuple([0,1]+[2]*2+[3]*2+[4]*2)
name = x.__class__.__name__
if "ge2j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._observations["nHadBulk"] = (630453600, 286166200, 209611400, 69777150, 26101500, 20182300, 4745175, 4776350) #v1 zm
#x._observations["nHadBulk"] = (653500000, 294800000, 214600000, 72190000, 26470000, 10860000, 4741000, 4718000) #v2 db
#x._triggerEfficiencies["had"] = (0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["had"] = (0.855, 0.983, 0.992, 1.000, 0.995, 1.000, 1.000, 1.000)
elif "le3j" in name :
#systMagnitudes = (0.10, 0.20, 0.20)
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.20)
#x._triggerEfficiencies["had"] = (0.891, 0.987, 0.990, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["had"] = (0.898, 0.987, 0.992, 1.000, 0.991, 1.000, 1.000, 1.000)
#x._observations["nHadBulk"] = (487992800, 202369400, 134976100, 36965375, 12292400, 8301900, 1925125, 1768325) #v1 zm
x._observations["nHadBulk"] = (559500000, 252400000, 180600000, 51650000, 17060000, 6499000, 2674000, 2501000) #v2 db
elif "ge4j" in name :
#systMagnitudes = (0.10, 0.20, 0.30)
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._triggerEfficiencies["had"] = (0.837, 0.982, 0.997, 1.000, 1.000, 1.000, 1.000, 1.000)
x._triggerEfficiencies["had"] = (0.670, 0.965, 0.993, 1.000, 1.000, 1.000, 1.000, 1.000)
#x._observations["nHadBulk"] = (142460800, 83796800, 74635300, 32811775, 13809100, 11880400, 2820050, 3008025) #v1 zm
x._observations["nHadBulk"] = ( 93940000, 42330000, 33950000, 20540000, 9410000, 4363000, 2067000, 2217000) #v2 db
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25,)
systBins = (0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x):
common1(x)
systBins = tuple([0, 1] + [2] * 2 + [3] * 2 + [4] * 2)
name = x.__class__.__name__
if "ge2j" in name:
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._observations["nHadBulk"] = (630453600, 286166200, 209611400, 69777150, 26101500, 20182300, 4745175, 4776350) #v1 zm
#x._observations["nHadBulk"] = (653500000, 294800000, 214600000, 72190000, 26470000, 10860000, 4741000, 4718000) #v2 db
x._triggerEfficiencies["had"] = (0.870, 0.986, 0.994, 1.000, 1.000,
1.000, 1.000, 1.000)
elif "le3j" in name:
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.20)
x._triggerEfficiencies["had"] = (0.891, 0.987, 0.990, 1.000, 1.000,
1.000, 1.000, 1.000)
#x._observations["nHadBulk"] = (487992800, 202369400, 134976100, 36965375, 12292400, 8301900, 1925125, 1768325) #v1 zm
x._observations["nHadBulk"] = (559500000, 252400000, 180600000,
51650000, 17060000, 6499000, 2674000,
2501000) #v2 db
elif "ge4j" in name:
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
x._triggerEfficiencies["had"] = (0.837, 0.982, 0.997, 1.000, 1.000,
1.000, 1.000, 1.000)
#x._observations["nHadBulk"] = (142460800, 83796800, 74635300, 32811775, 13809100, 11880400, 2820050, 3008025) #v1 zm
x._observations["nHadBulk"] = (93940000, 42330000, 33950000, 20540000,
9410000, 4363000, 2067000, 2217000
) #v2 db
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25, )
systBins = (0, 0, 0)
else:
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
}
def common(x):
lumiLikeValue = common1(x)
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
name = x.__class__.__name__
if "ge2j" in name:
systMagnitudes = (0.10, 0.20, 0.60)
x._observations["nHadBulk"] = (630453600, 286166200, 209611400,
69777150, 26101500, 20182300, 4745175,
4776350, 0, 0)
elif "le3j" in name:
systMagnitudes = (0.15, 0.30, 0.50)
x._observations["nHadBulk"] = (487992800, 202369400, 134976100,
36965375, 12292400, 8301900, 1925125,
1768325, 0, 0)
elif "ge4j" in name:
systMagnitudes = (0.25, 0.35, 0.70)
x._observations["nHadBulk"] = (142460800, 83796800, 74635300, 32811775,
13809100, 11880400, 2820050, 3008025, 0,
0)
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25, )
systBins = (0, 0, 0)
else:
if "0b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 7, 7)
else:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 7, 7)
#x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 6, 6, 6)
#systBins = tuple([0]*4+[1]*2+[2]*1)
x._systBins = {
"sigmaLumiLike": [0] * len(systBins),
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0]*4 + [1]*4 + [2]*3)
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.1, 0.2, 0.3)
x._triggerEfficiencies["had"] = (1., 1., 1., 1., 1.,1., 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.1, 0.2, 0.3)
x._triggerEfficiencies["had"] = (1., 1., 1., 1., 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.1,)
systBins = (0, 0, 0, 0)
elif "2b" in name or "3b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8)
systBins = tuple([0]*4 + [1]*4 + [2]*1)
#systMagnitudes = systMagnitudes[:-1]
systMagnitudes = (0.1, 0.2, 0.3)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
#systBins = tuple([0]*4+[1]*2+[2]*2)
#systBins = tuple([0,1]+[2]*2+[3]*2+[4]*2)
systBins = tuple([0] + [1]*3 + [2]*1 + [3]*2 + [4])
name = x.__class__.__name__
if "ge2j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._observations["nHadBulk"] = (653500000, 294800000, 214600000, 72190000, 26470000, 10860000, 4741000, 4718000) #v2 db
x._triggerEfficiencies["had"] = (0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
elif "le3j" in name :
#systMagnitudes = (0.10, 0.20, 0.20)
#systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.20)
systMagnitudes = (0.05, 0.05, 0.10, 0.20, 0.30) # tmp
x._triggerEfficiencies["had"] = (0.891, 0.987, 0.990, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (559500000, 252400000, 180600000, 51650000, 17060000, 6499000, 2674000, 2501000)
elif "ge4j" in name :
#systMagnitudes = (0.10, 0.20, 0.30)
#systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
systMagnitudes = (0.05, 0.10, 0.10, 0.20, 0.30) # dtmp
x._triggerEfficiencies["had"] = (0.837, 0.982, 0.997, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = ( 93940000, 42330000, 33950000, 20540000, 9410000, 4363000, 2067000, 2217000)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25,)
systBins = (0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
}
def common(x) :
lumiLikeValue = common1(x)
#systBins = tuple([0]*4+[1]*2+[2]*2)
systBins = tuple([0,1]+[2]*2+[3]*2+[4]*2)
name = x.__class__.__name__
if "ge2j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._observations["nHadBulk"] = (630453600, 286166200, 209611400, 69777150, 26101500, 20182300, 4745175, 4776350, 0, 0)
x._triggerEfficiencies["had"] = (0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
elif "le3j" in name :
#systMagnitudes = (0.10, 0.20, 0.20)
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.20)
x._observations["nHadBulk"] = (487992800, 202369400, 134976100, 36965375, 12292400, 8301900, 1925125, 1768325, 0, 0)
x._triggerEfficiencies["had"] = (0.891, 0.987, 0.990, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
elif "ge4j" in name :
#systMagnitudes = (0.10, 0.20, 0.30)
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
x._triggerEfficiencies["had"] = (0.837, 0.982, 0.997, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (142460800, 83796800, 74635300, 32811775, 13809100, 11880400, 2820050, 3008025, 0, 0)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25,)
systBins = (0, 0, 0)
else :
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 7, 7)
x._systBins = {
"sigmaLumiLike": [0]*len(systBins),
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
}
def common(x, systMode = 124) :
x._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
x._htMaxForPlot = 975.0
x._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02)
x._mergeBins = None
x._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
x._lumi = {
"had": 4.98e+03,
"hadBulk": 4.98e+03,
"muon": 4.98e+03,
"mcMuon": 4.98e+03,
"mcTtw": 4.98e+03,
"phot": 4.98e+03*4529./4650,
"mcGjets": 4.98e+03*4529./4650,
"mcZinv": 4.98e+03*4529./4650,
"mumu": 4.98e+03,
"mcMumu": 4.98e+03,
}
x._triggerEfficiencies = {
"hadBulk": ( 0.88, 0.91, 0.96, 1.00, 1.00, 1.00, 1.00, 1.00),
"had": ( 0.83, 0.96, 0.99, 1.00, 1.00, 1.00, 1.00, 1.00),
"muon": ( 0.83, 0.96, 0.913, 0.913, 0.913, 0.913, 0.913, 0.913),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.83, 0.96, 0.95, 0.95, 0.96, 0.96, 0.96, 0.97),
}
x._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
x._mcExtraBeforeTrigger = {}
x._mcExtraBeforeTrigger["mcHad"] =\
tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(x._mcExpectationsBeforeTrigger["mcTtw"], x._mcExpectationsBeforeTrigger["mcZinv"])])
x._mcStatError["mcHadErr"] =\
tuple([quadSum([a,b]) for a,b in zip(x._mcStatError["mcTtwErr"], x._mcStatError["mcZinvErr"])])
x._observations["nHadBulk"] = ( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06)
syst.load(x, mode = systMode)
def common(x, systMode=3):
x._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0,
875.0)
x._htMaxForPlot = 975.0
x._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02)
x._mergeBins = None
x._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
x._triggerEfficiencies = {
"hadBulk": (0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
x._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
x._mcExtraBeforeTrigger = {}
x._mcExtraBeforeTrigger["mcHad"] =\
tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(x._mcExpectationsBeforeTrigger["mcTtw"], x._mcExpectationsBeforeTrigger["mcZinv"])])
x._mcStatError["mcHadErr"] =\
tuple([quadSum([a,b]) for a,b in zip(x._mcStatError["mcTtwErr"], x._mcStatError["mcZinvErr"])])
x._observations["nHadBulk"] = (2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07,
9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06)
syst.load(x, mode=systMode)
def common(x) :
common1(x)
systBins = tuple([0, 1, 2] + [3]*2 + [4]*2 + [5]*4) # tmp
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.20) # tmp
x._triggerEfficiencies["had"] = (0.816, 0.901, 0.988, 0.994, 1.000, .994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.30) # dtmp
x._triggerEfficiencies["had"] = (0.665, 0.666, 0.971, 0.988, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.25,)
systBins = (0, 0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2 + [6])
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.06, 0.06, 0.08, 0.13, 0.18, 0.20, 0.20)
x._triggerEfficiencies["had"] = (0.952, 0.979, 0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.06, 0.11, 0.11, 0.19, 0.19, 0.25, 0.25)
x._triggerEfficiencies["had"] = (0.900, 0.956, 0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
# if "ge4b" in name :
# x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
# systMagnitudes = (0.15,)
# systBins = (0, 0, 0, 0)
# else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x):
common1(x)
systBins = tuple([0, 1, 2] + [3] * 2 + [4] * 2 + [5] * 4) # tmp
name = x.__class__.__name__
if "le3j" in name:
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.20) # tmp
x._observations["nHadBulk"] = (559500000, 559500000, 252400000,
180600000, 51650000, 17060000, 6499000,
2674000, 2501000, 2501000, 2501000
) # tmp
elif "ge4j" in name:
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.30) # tmp
x._observations["nHadBulk"] = (93940000, 93940000, 42330000, 33950000,
20540000, 9410000, 4363000, 2067000,
2217000, 2217000, 2217000) # tmp
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.25, )
systBins = (0, 0, 0, 0)
else:
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def common(x) :
common1(x)
systBins = tuple([0,1]+[2]*2+[3]*2+[4]*2)
name = x.__class__.__name__
if "ge2j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
#x._observations["nHadBulk"] = (653500000, 294800000, 214600000, 72190000, 26470000, 10860000, 4741000, 4718000) #v2 db
x._triggerEfficiencies["had"] = (0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
elif "le3j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.20)
x._triggerEfficiencies["had"] = (0.891, 0.987, 0.990, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (559500000, 252400000, 180600000, 51650000, 17060000, 6499000, 2674000, 2501000) #v2 db
elif "ge4j" in name :
systMagnitudes = (0.10, 0.10, 0.20, 0.20, 0.30)
x._triggerEfficiencies["had"] = (0.837, 0.982, 0.997, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = ( 93940000, 42330000, 33950000, 20540000, 9410000, 4363000, 2067000, 2217000) #v2 db
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 2, 2, 2, 2, 2)
systMagnitudes = (0.25,)
systBins = (0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
}
def common(x) :
x._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
x._htMaxForPlot = 975.0
x._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02)
x._mergeBins = None
x._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
x._lumi = {
"had" : 4980.0,
"mcHad" : 4980.0,
"muon" : 4980.0,
"mcMuon" : 4980.0,
"mumu" : 4980.0,
"mcMumu" : 4980.0,
"phot" : 4850.0,
"mcPhot" : 4850.0,
}
x._triggerEfficiencies = {
"hadBulk": ( 0.88, 0.91, 0.96, 1.00, 1.00, 1.00, 1.00, 1.00),
"had": ( 0.83, 0.96, 0.99, 1.00, 1.00, 1.00, 1.00, 1.00),
"muon": ( 0.83, 0.96, 0.913, 0.913, 0.913, 0.913, 0.913, 0.913),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.83, 0.96, 0.95, 0.95, 0.96, 0.96, 0.96, 0.97),
}
x._mcExtraBeforeTrigger = {}
x._mcExtraBeforeTrigger["mcHad"] =\
tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(x._mcExpectationsBeforeTrigger["mcTtw"], x._mcExpectationsBeforeTrigger["mcZinv"])])
x._mcStatError["mcHadErr"] =\
tuple([quadSum([a,b]) for a,b in zip(x._mcStatError["mcTtwErr"], x._mcStatError["mcZinvErr"])])
x._observations["nHadBulk"] = ( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06)
syst.load(x, mode = 124)
def common(x) :
common1(x)
systBins = tuple([0, 1, 2] + [3]*2 + [4]*2 + [5]*4) # tmp
name = x.__class__.__name__
if "le3j" in name :
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.20) # tmp
x._observations["nHadBulk"] = (559500000, 559500000, 252400000, 180600000, 51650000,
17060000, 6499000, 2674000, 2501000, 2501000, 2501000) # tmp
elif "ge4j" in name :
systMagnitudes = (0.10, 0.10, 0.10, 0.20, 0.20, 0.30) # tmp
x._observations["nHadBulk"] = (93940000, 93940000, 42330000, 33950000, 20540000,
9410000, 4363000, 2067000, 2217000, 2217000, 2217000) # tmp
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.25,)
systBins = (0, 0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 2919.0, 1166.0, 769.0, 255.0, 91.0, 31.0, 10.0, 4.0, ) ,
"nMuon" : ( 949.0, 444.0, 1707.0, 748.0, 305.0, 148.0, 81.0, 87.0, ) ,
"nMumu" : ( 95.0, 53.0, 216.0, 86.0, 48.0, 23.0, 5.0, 11.0, ) ,
"nPhot" : excl(( None, None, 1642-221, 596-84, 221-37, 91-16, 32-7, 14-2), isExcl), #>=0 b-tag minus >=1 b-tag
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl(( None, None, 2.00e+3 - 2.3e2, 7.1e+2 - 82, 2.7e+2 - 35, 92-15, 34-6, 14-3), isExcl), #>=0 b-tag minus >=1 b-tag
"mcTtw" : ( 1620.0, 601.5, 375.3, 128.7, 44.36, 17.35, 5.84, 4.109, ) ,
"mcZinv" : ( 1515.0, 635.8, 475.6, 165.3, 63.21, 21.3, 9.142, 6.196, ) ,
"mcMumu" : ( 110.6, 65.92, 255.8, 120.0, 53.79, 24.3, 13.31, 10.74, ) ,
"mcMuon" : ( 1145.0, 532.1, 1886.0, 857.3, 371.9, 179.5, 85.31, 104.5, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 0.04e+3, 0.2e+2, 0.1e+2, 8, 5, 3), #>=0 b-tag
"mcTtwErr" : ( 66.98, 40.54, 4.864, 2.85, 1.656, 1.151, 0.5746, 0.4422, ) ,
"mcZinvErr" : ( 9.983, 6.39, 5.518, 3.25, 2.01, 1.167, 0.7642, 0.6292, ) ,
"mcMuonErr" : ( 55.42, 38.09, 11.08, 7.601, 4.916, 3.504, 2.212, 2.589, ) ,
"mcMumuErr" : ( 6.532, 5.065, 10.01, 6.854, 4.576, 3.086, 2.29, 2.037, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4980.0,
"mcHad": 4980.0,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
160.0,
68.0,
52.0,
19.0,
11.0,
7.0,
0.0,
2.0,
),
"nMuon": (
116.0,
49.0,
264.0,
152.0,
63.0,
26.0,
10.0,
14.0,
),
"nMumu": (
4.0,
3.0,
8.0,
7.0,
5.0,
2.0,
0.0,
0.0,
),
"nPhot":
excl((None, None, 20, 10, 6, 4, 0, 0), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 25, 9, 3, 3, 0.9, 0.9), isExcl),
"mcTtw": (
155.0,
61.11,
53.4,
24.68,
8.047,
5.922,
0.7604,
0.723,
),
"mcHad": (
175.2,
69.75,
60.04,
26.96,
9.038,
6.249,
0.8612,
0.7922,
),
"mcZinv": (
20.27,
8.638,
6.646,
2.277,
0.9903,
0.3273,
0.1008,
0.06919,
),
"mcMumu": (
3.653,
3.054,
8.842,
2.67,
1.225,
0.4837,
0.1596,
0.1389,
),
"mcMuon": (
147.4,
67.01,
279.3,
151.4,
75.46,
29.22,
15.05,
14.54,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 4, 2, 1, 1, 0.9, 0.9),
"mcTtwErr": (
6.284,
4.11,
2.959,
2.085,
1.224,
1.522,
0.3988,
0.3478,
),
"mcZinvErr": (
0.9973,
0.6455,
0.5708,
0.2959,
0.2137,
0.0947,
0.03249,
0.01663,
),
"mcMuonErr": (
7.866,
5.03,
7.422,
5.702,
4.649,
2.438,
1.74,
1.738,
),
"mcMumuErr": (
0.8408,
3.323,
1.448,
0.6659,
0.3875,
0.3398,
0.1987,
0.04303,
),
"mcHadErr": (
6.363,
4.161,
3.013,
2.106,
1.242,
1.525,
0.4001,
0.3482,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def load(data = None, mode = None) :
# lumiLikeValue = quadSum({"lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10}.values())
# SMS other than T1, T2
lumiLikeValue = quadSum({"btagUncert": 0.035, "lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10}.values())
#T1, T2, cMSSM tb10 only
# lumiLikeValue = quadSum({"btagUncert": 0.12, "lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10}.values())
if mode==-1 :
systBins = tuple([0]*8)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*nSyst),
"sigmaPhotZ": tuple([0.40]*nSyst),
"sigmaMuonW": tuple([0.30]*nSyst),
"sigmaMumuZ": tuple([0.20]*nSyst),
}
if mode==1 :
systBins = tuple([0]*8)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*nSyst),
"sigmaPhotZ": tuple([0.20]*nSyst),
"sigmaMuonW": tuple([0.20]*nSyst),
"sigmaMumuZ": tuple([0.20]*nSyst),
"k_qcd_nom" : 2.89e-2,
"k_qcd_unc_inp" : 0.76e-2,
}
if mode==2 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*nSyst),
"sigmaPhotZ": tuple([1.00,1.00,1.00]),
"sigmaMuonW": tuple([1.00,1.00,1.00]),
"sigmaMumuZ": tuple([1.00,1.00,1.00]),
"k_qcd_nom" : 2.89e-2,
"k_qcd_unc_inp" : 0.76e-2,
}
if mode==3 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.20, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom" : 2.89e-2,
"k_qcd_unc_inp" : 0.76e-2,
}
if mode==4 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.20, 0.40, 0.60]),
"sigmaMuonW": tuple([0.20, 0.40, 0.60]),
"sigmaMumuZ": tuple([0.20, 0.40, 0.60]),
"k_qcd_nom" : 2.89e-2,
"k_qcd_unc_inp" : 0.76e-2,
}
if mode==124 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom" : 2.89e-2,
"k_qcd_unc_inp" : 0.76e-2,
}
if mode==1240 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom" : 2.96e-2,
"k_qcd_unc_inp" : quadSum([0.61e-2, 0.463e-2])
}
if mode==12400 :
systBins = tuple([0]*4+[1]*2+[2]*2+[3]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*10,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40, 0.40]),
"k_qcd_nom" : 2.96e-2,
"k_qcd_unc_inp" : quadSum([0.61e-2, 0.463e-2])
}
if mode==237 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": tuple([0.20, 0.30, 0.70]),
"sigmaMuonW": tuple([0.20, 0.30, 0.70]),
"sigmaMumuZ": tuple([0.20, 0.30, 0.70]),
"k_qcd_nom" : 2.96e-2,
"k_qcd_unc_inp" : quadSum([0.61e-2, 0.463e-2])
}
if type(mode)==tuple and len(mode)==1 :
systBins = tuple([0]*3)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*3,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
if type(mode)==tuple and len(mode)==3 :
systBins = tuple([0]*4+[1]*2+[2]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
if type(mode)==tuple and len(mode)==4 :
systBins = tuple([0]*4+[1]*2+[2]*2+[3]*2)
nSyst = 1+max(systBins)
data._systBins = {
"sigmaLumiLike": [0]*10,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue]*1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 10.0, 8.0, 8.0, 1.0, 0.0, 0.0, 0.0, 0.0, ) ,
"nMuon" : ( 9.0, 6.0, 22.0, 16.0, 13.0, 3.0, 1.0, 4.0, ) ,
"nMumu" : ( 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, ) ,
"nPhot" : (None, None, 1, 0, 0, 0, 0, 0, ),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets" : excl( ( None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0 ), isExcl),
"mcTtw" : ( 14.98, 4.788, 4.243, 2.604, 0.5211, 0.3001, 0.01408, 0.06082, ) ,
"mcZinv" : ( 1.079, 0.5188, 0.316, 0.1634, 0.0, 0.09114, 0.0, 0.0, ) ,
"mcMumu" : ( 0.01635, 0.0, 0.6904, 0.0, 0.002354, 0.0, 0.0, 0.0, ) ,
"mcMuon" : ( 13.1, 4.235, 26.51, 15.14, 8.438, 2.703, 1.364, 1.872, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
"mcTtwErr" : ( 1.686, 0.9518, 0.8906, 0.6971, 0.2472, 0.2281, 0.05278, 0.05092, ) ,
"mcZinvErr" : ( 0.2626, 0.1821, 0.1421, 0.1022, 0.0, 0.07631, 0.0, 0.0, ) ,
"mcMuonErr" : ( 1.593, 0.8971, 2.259, 1.693, 1.274, 0.7076, 0.5003, 0.5946, ) ,
"mcMumuErr" : ( 0.01389, 0.0, 0.3678, 0.0, 0.003354, 0.0, 0.0, 0.0, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 2.919e+03, 1.166e+03, 769.0, 255.0, 91.0, 31.0, 10.0, 4.0, ) ,
"nMuon" : ( 949.0, 444.0, 1.707e+03, 748.0, 305.0, 148.0, 81.0, 87.0, ) ,
"nMumu" : ( 95.0, 53.0, 216.0, 86.0, 48.0, 23.0, 5.0, 11.0, ) ,
"nPhot" : excl(( None, None, 1642-221, 596-84, 221-37, 91-16, 32-7, 14-2), isExcl), #>=0 b-tag minus >=1 b-tag
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl(( None, None, 2.00e+3 - 2.3e2, 7.1e+2 - 82, 2.7e+2 - 35, 92-15, 34-6, 14-3), isExcl), #>=0 b-tag minus >=1 b-tag
"mcTtw" : ( 1.618e+03, 601.0, 375.0, 128.5, 44.18, 17.49, 5.826, 4.086, ) ,
"mcZinv" : ( 1.506e+03, 631.7, 472.2, 163.9, 62.67, 21.12, 9.074, 6.161, ) ,
"mcMumu" : ( 110.2, 65.53, 254.2, 119.1, 53.41, 24.7, 13.21, 10.71, ) ,
"mcMuon" : ( 1.149e+03, 531.9, 1.887e+03, 856.5, 371.8, 179.7, 85.12, 104.5, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 0.04e+3, 0.2e+2, 0.1e+2, 8, 5, 3), #>=0 b-tag
"mcTtwErr" : ( 77.06, 56.91, 5.603, 3.397, 2.109, 1.531, 0.6946, 0.4814, ) ,
"mcZinvErr" : ( 12.1, 7.488, 6.895, 3.962, 2.47, 1.435, 0.8611, 0.6675, ) ,
"mcMuonErr" : ( 64.94, 44.18, 13.23, 8.922, 5.857, 4.717, 2.586, 2.933, ) ,
"mcMumuErr" : ( 7.134, 5.709, 11.16, 7.936, 5.165, 3.397, 3.467, 2.115, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def common(x):
common1(x)
systBins = tuple([0] * 1 + [1] * 1 + [2] * 1 + [3] * 2 + [4] * 2 +
[5] * 2 + [6] * 2)
name = x.__class__.__name__
m400_25_xs = 0.35683
if "0b_ge4j" in name:
effHad = [
2.41e-05, 2.32e-04, 1.20e-03, 2.44e-03, 1.79e-03, 7.53e-04,
2.86e-04, 9.22e-05, 3.56e-05, 2.37e-05, 1.24e-06
]
elif "0b_le3j" in name:
effHad = [
2.85e-03, 3.08e-03, 2.66e-03, 1.89e-03, 4.47e-04, 1.18e-04,
6.22e-06, 1.91e-05, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "1b_ge4j" in name:
effHad = [
1.18e-05, 8.18e-04, 2.31e-03, 5.33e-03, 4.31e-03, 2.00e-03,
9.10e-04, 4.26e-04, 1.89e-04, 5.05e-05, 5.80e-05
]
elif "1b_le3j" in name:
effHad = [
3.80e-03, 4.61e-03, 3.99e-03, 3.26e-03, 8.30e-04, 1.86e-04,
6.00e-05, 2.62e-05, 8.70e-06, 0.00e+00, 0.00e+00
]
elif "2b_ge4j" in name:
effHad = [
6.79e-06, 4.74e-04, 1.36e-03, 3.07e-03, 2.50e-03, 1.34e-03,
5.32e-04, 1.24e-04, 1.01e-04, 4.20e-05, 1.40e-05
]
elif "2b_le3j" in name:
effHad = [
8.06e-04, 1.58e-03, 1.69e-03, 1.17e-03, 4.38e-04, 8.09e-05,
2.29e-05, 1.11e-05, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "3b_ge4j" in name:
effHad = [
5.25e-06, 4.22e-05, 1.55e-04, 3.42e-04, 3.46e-04, 2.74e-04,
7.05e-05, 2.99e-06, 2.97e-05, 9.30e-06, 1.71e-05
]
elif "3b_le3j" in name:
effHad = [
1.08e-05, 1.32e-04, 7.88e-05, 5.68e-05, 3.07e-05, 0.00e+00,
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "ge4b_ge4j" in name:
effHad = [
0.00e+00, 0.00e+00, 0.00e+00, 2.19e-05, 0.0, 0.0, 0.0, 0.0, 0.0,
0.0, 0.0
]
if "le3j" in name:
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998,
0.994, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08,
3.29919975E08, 2.74138825E08,
8.507427E07, 2.8887025E07, 1.09110E07,
4.6215E06, 2.07715E06, 1.031125E06,
1.20755E06)
elif "ge4j" in name:
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000,
1.000, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07,
4.8204025E07, 3.35079E07, 1.582655E07,
7.279475E06, 3.46345E06, 1.732725E06,
8.9562E05, 1.142775E06)
x._observations["nHad"] = [
m + (y * m400_25_xs * x._lumi["had"] * z) for m, y, z in zip(
x._observations["nHad"], effHad, x._triggerEfficiencies["had"])
]
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15, )
systBins = (0, 0, 0, 0)
elif "2b" in name or "3b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8)
systBins = tuple([0] * 1 + [1] * 1 + [2] * 1 + [3] * 2 + [4] * 2 +
[5] * 2) # + [6]*2)
systMagnitudes = systMagnitudes[:-1]
else:
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4980.0,
"mcHad": 4980.0,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
10.0,
8.0,
8.0,
1.0,
0.0,
0.0,
0.0,
0.0,
),
"nMuon": (
9.0,
6.0,
22.0,
16.0,
13.0,
3.0,
1.0,
4.0,
),
"nMumu": (
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
),
"nPhot": (
None,
None,
1,
0,
0,
0,
0,
0,
),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0), isExcl),
"mcTtw": (
12.19,
4.937,
5.071,
3.389,
1.284,
1.069,
0.1327,
0.1261,
),
"mcHad": (
12.79,
5.185,
5.254,
3.464,
1.33,
1.086,
0.1341,
0.1268,
),
"mcZinv": (
0.5948,
0.2481,
0.1827,
0.0749,
0.04606,
0.0175,
0.001412,
0.0006948,
),
"mcMumu": (
0.1406,
0.1691,
0.219,
0.1262,
0.06499,
0.01896,
0.006603,
0.00577,
),
"mcMuon": (
11.52,
4.897,
22.5,
15.88,
9.567,
3.794,
2.272,
2.899,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
"mcTtwErr": (
0.3381,
0.2371,
0.2062,
0.1853,
0.1327,
0.1531,
0.04772,
0.03737,
),
"mcZinvErr": (
0.03363,
0.02136,
0.0182,
0.01237,
0.01112,
0.007328,
0.000951,
0.0,
),
"mcMuonErr": (
0.409,
0.2464,
0.4792,
0.4196,
0.4401,
0.1948,
0.1632,
0.2102,
),
"mcMumuErr": (
0.03021,
0.1489,
0.0364,
0.02794,
0.02174,
0.001646,
0.005925,
0.0007417,
),
"mcHadErr": (
0.3398,
0.2381,
0.207,
0.1857,
0.1331,
0.1533,
0.04773,
0.03737,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 10.0, 8.0, 8.0, 1.0, 0.0, 0.0, 0.0, 0.0, ) ,
"nMuon" : ( 9.0, 6.0, 22.0, 16.0, 13.0, 3.0, 1.0, 4.0, ) ,
"nMumu" : ( 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, ) ,
"nPhot" : (None, None, 1, 0, 0, 0, 0, 0, ),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets" : excl( ( None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0 ), isExcl),
"mcTtw" : ( 14.52, 4.638, 4.115, 2.576, 0.5129, 0.3197, 0.01486, 0.06064, ) ,
"mcZinv" : ( 1.12, 0.5603, 0.3348, 0.1535, 0.0, 0.09399, 0.0, 0.0, ) ,
"mcMumu" : ( 0.01747, 0.0, 0.6829, 0.0, 0.002146, 0.0, 0.0, 0.0, ) ,
"mcMuon" : ( 12.86, 3.949, 25.7, 14.56, 8.121, 2.634, 1.318, 1.882, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
"mcTtwErr" : ( 1.916, 0.9796, 1.01, 0.8368, 0.3255, 0.2741, 0.01486, 0.06064, ) ,
"mcZinvErr" : ( 0.4274, 0.224, 0.185, 0.1305, 0.0, 0.09399, 0.0, 0.0, ) ,
"mcMuonErr" : ( 2.82, 0.9221, 2.876, 2.613, 1.296, 0.7105, 0.5531, 0.6301, ) ,
"mcMumuErr" : ( 0.01747, 0.0, 0.5021, 0.0, 0.002146, 0.0, 0.0, 0.0, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4980.0,
"mcHad": 4980.0,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
784.0,
370.0,
274.0,
91.0,
31.0,
13.0,
4.0,
2.0,
),
"nMuon": (
472.0,
201.0,
854.0,
456.0,
192.0,
77.0,
33.0,
44.0,
),
"nMumu": (
19.0,
12.0,
43.0,
27.0,
15.0,
9.0,
1.0,
6.0,
),
"nPhot":
excl((None, None, 221, 84, 37, 16, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcTtw": (
698.3,
284.4,
218.9,
92.54,
30.06,
17.33,
3.097,
2.524,
),
"mcHad": (
907.4,
377.5,
287.7,
119.1,
40.77,
21.26,
4.607,
3.637,
),
"mcZinv": (
209.1,
93.05,
68.81,
26.54,
10.71,
3.922,
1.51,
1.113,
),
"mcMumu": (
23.44,
12.51,
44.0,
20.28,
10.85,
4.672,
1.366,
2.242,
),
"mcMuon": (
624.9,
275.1,
999.8,
519.4,
245.3,
103.6,
50.46,
56.0,
),
"mcGjets": excl((None, None, 2.3e2, 82, 35, 15, 6, 3), isExcl),
}
self._mcStatError = {
"mcTtwErr": (
18.44,
10.6,
10.3,
8.983,
3.923,
3.152,
0.834,
0.5653,
),
"mcZinvErr": (
3.039,
1.953,
1.403,
0.9799,
0.5521,
0.3154,
0.1016,
0.1242,
),
"mcMuonErr": (
18.5,
11.38,
17.6,
14.3,
11.82,
9.903,
4.868,
4.607,
),
"mcMumuErr": (
2.813,
3.887,
3.442,
1.983,
1.17,
1.398,
0.2344,
1.85,
),
"mcHadErr": (
18.69,
10.78,
10.4,
9.037,
3.962,
3.168,
0.8402,
0.5788,
),
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 2),
}
#self._mcStatError["mcHadErr"] = tuple([quadSum([ttwErr, zinvErr]) for ttwErr,zinvErr in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
160.0,
68.0,
52.0,
19.0,
11.0,
7.0,
0.0,
2.0,
),
"nMuon": (
116.0,
49.0,
264.0,
152.0,
63.0,
26.0,
10.0,
14.0,
),
"nMumu": (
4.0,
3.0,
8.0,
7.0,
5.0,
2.0,
0.0,
0.0,
),
"nPhot":
excl((None, None, 20, 10, 6, 4, 0, 0), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 25, 9, 3, 3, 0.9, 0.9), isExcl),
"mcTtw": (
175.1,
66.39,
47.32,
25.34,
8.707,
3.847,
0.6063,
1.139,
),
"mcZinv": (
19.65,
8.831,
8.274,
2.933,
1.212,
0.3464,
0.07716,
0.0,
),
"mcMumu": (
3.129,
4.635,
9.793,
3.514,
0.8206,
0.8718,
0.02835,
0.06183,
),
"mcMuon": (
143.6,
63.06,
266.1,
148.0,
71.06,
29.65,
13.31,
14.37,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 4, 2, 1, 1, 0.9, 0.9),
"mcTtwErr": (
19.57,
6.858,
3.872,
3.303,
1.522,
1.051,
0.3245,
0.4657,
),
"mcZinvErr": (
1.3,
0.8569,
0.9101,
0.5128,
0.3125,
0.1548,
0.06877,
0.0,
),
"mcMuonErr": (
9.917,
6.535,
7.99,
5.874,
5.027,
2.564,
1.638,
1.913,
),
"mcMumuErr": (
0.8724,
4.205,
1.809,
0.8998,
0.3605,
0.5523,
0.02013,
0.06183,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def load(data=None, mode=None):
# lumiLikeValue = quadSum({"lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10}.values())
# SMS other than T1, T2
lumiLikeValue = quadSum({
"btagUncert": 0.035,
"lumi": 0.06,
"deadEcal": 0.03,
"lepVetoes": 0.025,
"jesjer": 0.025,
"pdf": 0.10
}.values())
#T1, T2, cMSSM tb10 only
# lumiLikeValue = quadSum({"btagUncert": 0.12, "lumi": 0.06, "deadEcal": 0.03, "lepVetoes": 0.025, "jesjer": 0.025, "pdf": 0.10}.values())
if mode == -1:
systBins = tuple([0] * 8)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * nSyst),
"sigmaPhotZ": tuple([0.40] * nSyst),
"sigmaMuonW": tuple([0.30] * nSyst),
"sigmaMumuZ": tuple([0.20] * nSyst),
}
if mode == 1:
systBins = tuple([0] * 8)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * nSyst),
"sigmaPhotZ": tuple([0.20] * nSyst),
"sigmaMuonW": tuple([0.20] * nSyst),
"sigmaMumuZ": tuple([0.20] * nSyst),
"k_qcd_nom": 2.89e-2,
"k_qcd_unc_inp": 0.76e-2,
}
if mode == 2:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": systBins,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * nSyst),
"sigmaPhotZ": tuple([1.00, 1.00, 1.00]),
"sigmaMuonW": tuple([1.00, 1.00, 1.00]),
"sigmaMumuZ": tuple([1.00, 1.00, 1.00]),
"k_qcd_nom": 2.89e-2,
"k_qcd_unc_inp": 0.76e-2,
}
if mode == 3:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.20, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom": 2.89e-2,
"k_qcd_unc_inp": 0.76e-2,
}
if mode == 4:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.20, 0.40, 0.60]),
"sigmaMuonW": tuple([0.20, 0.40, 0.60]),
"sigmaMumuZ": tuple([0.20, 0.40, 0.60]),
"k_qcd_nom": 2.89e-2,
"k_qcd_unc_inp": 0.76e-2,
}
if mode == 124:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom": 2.89e-2,
"k_qcd_unc_inp": 0.76e-2,
}
if mode == 1240:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40]),
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
}
if mode == 12400:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2 + [3] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 10,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.10, 0.20, 0.40, 0.40]),
"sigmaMuonW": tuple([0.10, 0.20, 0.40, 0.40]),
"sigmaMumuZ": tuple([0.10, 0.20, 0.40, 0.40]),
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
}
if mode == 237:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": tuple([0.20, 0.30, 0.70]),
"sigmaMuonW": tuple([0.20, 0.30, 0.70]),
"sigmaMumuZ": tuple([0.20, 0.30, 0.70]),
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
}
if type(mode) == tuple and len(mode) == 1:
systBins = tuple([0] * 3)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 3,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
if type(mode) == tuple and len(mode) == 3:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 8,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
if type(mode) == tuple and len(mode) == 4:
systBins = tuple([0] * 4 + [1] * 2 + [2] * 2 + [3] * 2)
nSyst = 1 + max(systBins)
data._systBins = {
"sigmaLumiLike": [0] * 10,
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
data._fixedParameters = {
"sigmaLumiLike": tuple([lumiLikeValue] * 1),
"sigmaPhotZ": mode,
"sigmaMuonW": mode,
"sigmaMumuZ": mode,
}
def common(x) :
common1(x)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2 + [6]*2)
name = x.__class__.__name__
dm10_250_xs = 5.6
if "0b_ge4j" in name:
effHad = [1.73e-06, 4.85e-05, 1.20e-04, 1.90e-04, 2.15e-04, 1.15e-04, 7.62e-05, 5.74e-05, 2.65e-05, 1.97e-05, 2.04e-05]
elif "0b_le3j" in name:
effHad = [3.73e-03, 2.01e-03, 1.51e-03, 1.52e-03, 7.07e-04, 2.77e-04, 1.42e-04, 3.34e-05, 2.57e-05, 1.42e-05, 7.89e-06]
elif "1b_ge4j" in name:
effHad = [0.00e+00, 7.14e-06, 2.37e-05, 2.19e-05, 2.29e-05, 1.21e-05, 3.77e-06, 1.01e-05, 2.50e-06, 2.86e-06, 2.69e-06]
elif "1b_le3j" in name:
effHad = [2.77e-04, 1.78e-04, 1.13e-04, 1.41e-04, 5.05e-05, 3.50e-05, 1.03e-05, 2.17e-06, 1.34e-06, 0.00e+00, 0.00e+00]
elif "2b_ge4j" in name:
effHad = [0.00e+00, 3.85e-06, 1.60e-06, 2.96e-06, 2.38e-06, 4.12e-06, 1.38e-06, 1.60e-06, 1.13e-06, 0.00e+00, 0.00e+00]
elif "2b_le3j" in name:
effHad = [1.26e-05, 1.39e-05, 1.41e-05, 1.29e-05, 4.91e-06, 1.47e-06, 2.77e-06, 7.31e-07, 0.00e+00, 0.00e+00, 0.00e+00]
elif "3b_ge4j" in name:
effHad = [0.00e+00, 0.00e+00, 0.00e+00, 1.14e-06, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00]
elif "3b_le3j" in name:
effHad = [0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00]
elif "4b_ge4j" in name:
effHad = [0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00]
if "le3j" in name :
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
x._observations["nHad"] = [m+(y*dm10_250_xs*x._lumi["had"]*z) for m,y,z in zip(x._observations["nHad"],effHad, x._triggerEfficiencies["had"])]
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15,)
systBins = (0, 0, 0, 0)
elif "2b" in name or "3b" in name:
x._mergeBins = (0, 1, 2, 3, 4, 5, 6, 7, 8, 8, 8)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2)# + [6]*2)
systMagnitudes = systMagnitudes[:-1]
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
2.919e+03,
1.166e+03,
769.0,
255.0,
91.0,
31.0,
10.0,
4.0,
),
"nMuon": (
949.0,
444.0,
1.707e+03,
748.0,
305.0,
148.0,
81.0,
87.0,
),
"nMumu": (
95.0,
53.0,
216.0,
86.0,
48.0,
23.0,
5.0,
11.0,
),
"nPhot":
excl((None, None, 1642 - 221, 596 - 84, 221 - 37, 91 - 16, 32 - 7,
14 - 2), isExcl), #>=0 b-tag minus >=1 b-tag
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 2.00e+3 - 2.3e2, 7.1e+2 - 82, 2.7e+2 - 35,
92 - 15, 34 - 6, 14 - 3),
isExcl), #>=0 b-tag minus >=1 b-tag
"mcTtw": (
1.618e+03,
601.0,
375.0,
128.5,
44.18,
17.49,
5.826,
4.086,
),
"mcZinv": (
1.506e+03,
631.7,
472.2,
163.9,
62.67,
21.12,
9.074,
6.161,
),
"mcMumu": (
110.2,
65.53,
254.2,
119.1,
53.41,
24.7,
13.21,
10.71,
),
"mcMuon": (
1.149e+03,
531.9,
1.887e+03,
856.5,
371.8,
179.7,
85.12,
104.5,
),
}
self._mcStatError = {
"mcGjetsErr":
(None, None, 0.04e+3, 0.2e+2, 0.1e+2, 8, 5, 3), #>=0 b-tag
"mcTtwErr": (
77.06,
56.91,
5.603,
3.397,
2.109,
1.531,
0.6946,
0.4814,
),
"mcZinvErr": (
12.1,
7.488,
6.895,
3.962,
2.47,
1.435,
0.8611,
0.6675,
),
"mcMuonErr": (
64.94,
44.18,
13.23,
8.922,
5.857,
4.717,
2.586,
2.933,
),
"mcMumuErr": (
7.134,
5.709,
11.16,
7.936,
5.165,
3.397,
3.467,
2.115,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
784.0,
370.0,
274.0,
91.0,
31.0,
13.0,
4.0,
2.0,
),
"nMuon": (
472.0,
201.0,
854.0,
456.0,
192.0,
77.0,
33.0,
44.0,
),
"nMumu": (
19.0,
12.0,
43.0,
27.0,
15.0,
9.0,
1.0,
6.0,
),
"nPhot":
excl((None, None, 221, 84, 37, 16, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcTtw": (
622.3,
270.4,
196.2,
78.23,
26.14,
14.22,
2.697,
2.0,
),
"mcZinv": (
197.7,
85.56,
59.23,
24.97,
9.424,
3.213,
1.108,
0.88,
),
"mcMumu": (
22.95,
11.73,
39.17,
18.13,
10.1,
3.987,
1.275,
2.198,
),
"mcMuon": (
547.1,
237.9,
885.3,
455.5,
217.6,
94.22,
43.29,
46.07,
),
"mcGjets": excl((None, None, 2.3e2, 82, 35, 15, 6, 3), isExcl),
}
self._mcStatError = {
"mcTtwErr": (
30.58,
23.3,
6.743,
4.835,
2.515,
2.472,
0.6185,
0.5275,
),
"mcZinvErr": (
4.567,
2.765,
2.291,
1.944,
0.8916,
0.523,
0.3206,
0.2947,
),
"mcMuonErr": (
25.72,
16.52,
13.56,
9.95,
7.581,
4.92,
2.962,
2.998,
),
"mcMumuErr": (
3.111,
4.605,
4.095,
2.679,
2.103,
1.22,
0.6464,
0.9855,
),
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 2),
}
#self._mcStatError["mcHadErr"] = tuple([quadSum([ttwErr, zinvErr]) for ttwErr,zinvErr in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def common(x) :
common1(x)
systBins = tuple([0]*1 + [1]*1 + [2]*1 + [3]*2 + [4]*2 + [5]*2 + [6]*2)
name = x.__class__.__name__
m400_25_xs = 0.35683
if "0b_ge4j" in name:
effHad = [2.41e-05, 2.32e-04, 1.20e-03, 2.44e-03, 1.79e-03, 7.53e-04, 2.86e-04, 9.22e-05, 3.56e-05, 2.37e-05, 1.24e-06]
elif "0b_le3j" in name:
effHad = [2.85e-03, 3.08e-03, 2.66e-03, 1.89e-03, 4.47e-04, 1.18e-04, 6.22e-06, 1.91e-05, 0.00e+00, 0.00e+00, 0.00e+00]
elif "1b_ge4j" in name:
effHad = [1.18e-05, 8.18e-04, 2.31e-03, 5.33e-03, 4.31e-03, 2.00e-03, 9.10e-04, 4.26e-04, 1.89e-04, 5.05e-05, 5.80e-05]
elif "1b_le3j" in name:
effHad = [3.80e-03, 4.61e-03, 3.99e-03, 3.26e-03, 8.30e-04, 1.86e-04, 6.00e-05, 2.62e-05, 8.70e-06, 0.00e+00, 0.00e+00]
elif "2b_ge4j" in name:
effHad = [6.79e-06, 4.74e-04, 1.36e-03, 3.07e-03, 2.50e-03, 1.34e-03, 5.32e-04, 1.24e-04, 1.01e-04, 4.20e-05, 1.40e-05]
elif "2b_le3j" in name:
effHad = [8.06e-04, 1.58e-03, 1.69e-03, 1.17e-03, 4.38e-04, 8.09e-05, 2.29e-05, 1.11e-05, 0.00e+00, 0.00e+00, 0.00e+00]
elif "3b_ge4j" in name:
effHad = [5.25e-06, 4.22e-05, 1.55e-04, 3.42e-04, 3.46e-04, 2.74e-04, 7.05e-05, 2.99e-06, 2.97e-05, 9.30e-06, 1.71e-05]
elif "3b_le3j" in name:
effHad = [1.08e-05, 1.32e-04, 7.88e-05, 5.68e-05, 3.07e-05, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00]
elif "ge4b_ge4j" in name:
effHad = [0.00e+00, 0.00e+00, 0.00e+00, 2.19e-05, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]
if "le3j" in name :
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08, 3.29919975E08, 2.74138825E08, 8.507427E07,
2.8887025E07, 1.09110E07, 4.6215E06, 2.07715E06, 1.031125E06, 1.20755E06)
elif "ge4j" in name :
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07, 4.8204025E07, 3.35079E07,
1.582655E07, 7.279475E06, 3.46345E06, 1.732725E06, 8.9562E05, 1.142775E06)
x._observations["nHad"] = [m+(y*m400_25_xs*x._lumi["had"]*z) for m,y,z in zip(x._observations["nHad"],effHad, x._triggerEfficiencies["had"])]
if "ge4b" in name :
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15,)
systBins = (0, 0, 0, 0)
else :
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom":2.96e-2,
"k_qcd_unc_inp":quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 160.0, 68.0, 52.0, 19.0, 11.0, 7.0, 0.0, 2.0, ) ,
"nMuon" : ( 116.0, 49.0, 264.0, 152.0, 63.0, 26.0, 10.0, 14.0, ) ,
"nMumu" : ( 4.0, 3.0, 8.0, 7.0, 5.0, 2.0, 0.0, 0.0, ) ,
"nPhot": excl(( None, None, 20, 10, 6, 4, 0, 0), isExcl),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets" : excl( ( None, None, 25, 9, 3, 3, 0.9, 0.9 ), isExcl),
"mcTtw" : ( 175.1, 66.39, 47.32, 25.34, 8.707, 3.847, 0.6063, 1.139, ) ,
"mcZinv" : ( 19.65, 8.831, 8.274, 2.933, 1.212, 0.3464, 0.07716, 0.0, ) ,
"mcMumu" : ( 3.129, 4.635, 9.793, 3.514, 0.8206, 0.8718, 0.02835, 0.06183, ) ,
"mcMuon" : ( 143.6, 63.06, 266.1, 148.0, 71.06, 29.65, 13.31, 14.37, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 4, 2, 1, 1, 0.9, 0.9),
"mcTtwErr" : ( 19.57, 6.858, 3.872, 3.303, 1.522, 1.051, 0.3245, 0.4657, ) ,
"mcZinvErr" : ( 1.3, 0.8569, 0.9101, 0.5128, 0.3125, 0.1548, 0.06877, 0.0, ) ,
"mcMuonErr" : ( 9.917, 6.535, 7.99, 5.874, 5.027, 2.564, 1.638, 1.913, ) ,
"mcMumuErr" : ( 0.8724, 4.205, 1.809, 0.8998, 0.3605, 0.5523, 0.02013, 0.06183, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4980.0,
"mcHad": 4980.0,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
2919.0,
1166.0,
769.0,
255.0,
91.0,
31.0,
10.0,
4.0,
),
"nMuon": (
949.0,
444.0,
1707.0,
748.0,
305.0,
148.0,
81.0,
87.0,
),
"nMumu": (
95.0,
53.0,
216.0,
86.0,
48.0,
23.0,
5.0,
11.0,
),
"nPhot":
excl((None, None, 1642 - 221, 596 - 84, 221 - 37, 91 - 16, 32 - 7,
14 - 2), isExcl), #>=0 b-tag minus >=1 b-tag
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 2.00e+3 - 2.3e2, 7.1e+2 - 82, 2.7e+2 - 35,
92 - 15, 34 - 6, 14 - 3),
isExcl), #>=0 b-tag minus >=1 b-tag
"mcTtw": (
1653.0,
634.6,
396.1,
135.3,
46.53,
16.7,
6.068,
3.879,
),
"mcHad": (
3185.0,
1300.0,
897.0,
312.2,
114.3,
39.14,
15.51,
10.3,
),
"mcZinv": (
1532.0,
665.5,
500.9,
176.9,
67.75,
22.44,
9.445,
6.426,
),
"mcMumu": (
119.4,
69.96,
275.5,
128.8,
56.63,
25.53,
14.72,
11.63,
),
"mcMuon": (
1198.0,
563.9,
1978.0,
902.0,
393.8,
188.4,
90.65,
109.2,
),
}
self._mcStatError = {
"mcGjetsErr":
(None, None, 0.04e+3, 0.2e+2, 0.1e+2, 8, 5, 3), #>=0 b-tag
"mcTtwErr": (
74.89,
55.58,
5.17,
3.189,
2.002,
1.131,
0.5627,
0.4215,
),
"mcZinvErr": (
12.05,
7.545,
6.928,
4.141,
2.51,
1.409,
0.8549,
0.6651,
),
"mcMuonErr": (
63.0,
43.93,
11.85,
8.155,
5.251,
3.741,
2.362,
2.685,
),
"mcMumuErr": (
7.301,
5.831,
11.62,
8.069,
5.133,
3.373,
3.591,
2.181,
),
"mcHadErr": (
75.85,
56.09,
8.645,
5.226,
3.211,
1.807,
1.023,
0.7874,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 784.0, 370.0, 274.0, 91.0, 31.0, 13.0, 4.0, 2.0, ) ,
"nMuon" : ( 472.0, 201.0, 854.0, 456.0, 192.0, 77.0, 33.0, 44.0, ) ,
"nMumu" : ( 19.0, 12.0, 43.0, 27.0, 15.0, 9.0, 1.0, 6.0, ) ,
"nPhot": excl(( None, None, 221, 84, 37, 16, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcTtw" : ( 622.3, 270.4, 196.2, 78.23, 26.14, 14.22, 2.697, 2.0, ) ,
"mcZinv" : ( 197.7, 85.56, 59.23, 24.97, 9.424, 3.213, 1.108, 0.88, ) ,
"mcMumu" : ( 22.95, 11.73, 39.17, 18.13, 10.1, 3.987, 1.275, 2.198, ) ,
"mcMuon" : ( 547.1, 237.9, 885.3, 455.5, 217.6, 94.22, 43.29, 46.07, ) ,
"mcGjets": excl( ( None, None, 2.3e2, 82, 35, 15, 6, 3 ), isExcl),
}
self._mcStatError = {
"mcTtwErr" : ( 30.58, 23.3, 6.743, 4.835, 2.515, 2.472, 0.6185, 0.5275, ) ,
"mcZinvErr" : ( 4.567, 2.765, 2.291, 1.944, 0.8916, 0.523, 0.3206, 0.2947, ) ,
"mcMuonErr" : ( 25.72, 16.52, 13.56, 9.95, 7.581, 4.92, 2.962, 2.998, ) ,
"mcMumuErr" : ( 3.111, 4.605, 4.095, 2.679, 2.103, 1.22, 0.6464, 0.9855, ) ,
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 2),
}
#self._mcStatError["mcHadErr"] = tuple([quadSum([ttwErr, zinvErr]) for ttwErr,zinvErr in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
614.0,
294.0,
214.0,
71.0,
20.0,
6.0,
4.0,
0.0,
),
"nMuon": (
347.0,
146.0,
568.0,
288.0,
116.0,
48.0,
22.0,
26.0,
),
"nMumu": (
15.0,
9.0,
34.0,
20.0,
10.0,
7.0,
0.0,
6.0,
),
"nPhot":
excl((None, None, 200, 74, 31, 12, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl((None, None, 2.0e2, 72, 31, 12, 6, 3),
isExcl), #>=1 b-tag
"mcTtw": (
432.6,
199.4,
144.7,
50.31,
16.92,
10.06,
2.075,
0.8008,
),
"mcZinv": (
176.9,
76.16,
50.62,
21.88,
8.212,
2.772,
1.031,
0.88,
),
"mcMumu": (
19.81,
7.089,
28.69,
14.62,
9.282,
3.116,
1.247,
2.136,
),
"mcMuon": (
390.6,
170.9,
593.4,
292.8,
138.5,
61.94,
28.65,
29.81,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 1),
"mcTtwErr": (
23.42,
22.25,
5.427,
3.43,
1.976,
2.221,
0.5263,
0.2402,
),
"mcZinvErr": (
4.357,
2.619,
2.095,
1.87,
0.835,
0.4906,
0.3131,
0.2947,
),
"mcMuonErr": (
23.57,
15.14,
10.57,
7.595,
5.525,
4.138,
2.405,
2.22,
),
"mcMumuErr": (
2.986,
1.878,
3.64,
2.524,
2.072,
1.088,
0.6461,
0.9835,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 614.0, 294.0, 214.0, 71.0, 20.0, 6.0, 4.0, 0.0, ) ,
"nMuon" : ( 347.0, 146.0, 568.0, 288.0, 116.0, 48.0, 22.0, 26.0, ) ,
"nMumu" : ( 15.0, 9.0, 34.0, 20.0, 10.0, 7.0, 0.0, 6.0, ) ,
"nPhot": excl(( None, None, 200, 74, 31, 12, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl( ( None, None, 2.0e2, 72, 31, 12, 6, 3 ), isExcl), #>=1 b-tag
"mcTtw" : ( 432.6, 199.4, 144.7, 50.31, 16.92, 10.06, 2.075, 0.8008, ) ,
"mcZinv" : ( 176.9, 76.16, 50.62, 21.88, 8.212, 2.772, 1.031, 0.88, ) ,
"mcMumu" : ( 19.81, 7.089, 28.69, 14.62, 9.282, 3.116, 1.247, 2.136, ) ,
"mcMuon" : ( 390.6, 170.9, 593.4, 292.8, 138.5, 61.94, 28.65, 29.81, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 10, 7, 5, 3, 2, 1),
"mcTtwErr" : ( 23.42, 22.25, 5.427, 3.43, 1.976, 2.221, 0.5263, 0.2402, ) ,
"mcZinvErr" : ( 4.357, 2.619, 2.095, 1.87, 0.835, 0.4906, 0.3131, 0.2947, ) ,
"mcMuonErr" : ( 23.57, 15.14, 10.57, 7.595, 5.525, 4.138, 2.405, 2.22, ) ,
"mcMumuErr" : ( 2.986, 1.878, 3.64, 2.524, 2.072, 1.088, 0.6461, 0.9835, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4980.0,
"mcHad": 4980.0,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
614.0,
294.0,
214.0,
71.0,
20.0,
6.0,
4.0,
0.0,
),
"nMuon": (
347.0,
146.0,
568.0,
288.0,
116.0,
48.0,
22.0,
26.0,
),
"nMumu": (
15.0,
9.0,
34.0,
20.0,
10.0,
7.0,
0.0,
6.0,
),
"nPhot":
excl((None, None, 200, 74, 31, 12, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl((None, None, 2.0e2, 72, 31, 12, 6, 3),
isExcl), #>=1 b-tag
"mcTtw": (
531.0,
218.4,
160.4,
64.47,
20.73,
10.34,
2.204,
1.674,
),
"mcHad": (
719.2,
302.6,
222.4,
88.66,
30.4,
13.92,
3.612,
2.717,
),
"mcZinv": (
188.2,
84.16,
61.98,
24.19,
9.67,
3.577,
1.408,
1.043,
),
"mcMumu": (
19.64,
9.278,
34.94,
17.49,
9.56,
4.171,
1.199,
2.097,
),
"mcMuon": (
465.9,
203.2,
698.0,
352.2,
160.4,
70.58,
33.13,
38.57,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 1),
"mcTtwErr": (
17.34,
9.773,
9.865,
8.736,
3.725,
2.756,
0.7309,
0.4441,
),
"mcZinvErr": (
2.871,
1.843,
1.281,
0.934,
0.5089,
0.3007,
0.09626,
0.123,
),
"mcMuonErr": (
16.74,
10.21,
15.95,
13.11,
10.86,
9.597,
4.544,
4.261,
),
"mcMumuErr": (
2.684,
2.012,
3.122,
1.868,
1.104,
1.356,
0.1242,
1.849,
),
"mcHadErr": (
17.57,
9.945,
9.948,
8.786,
3.76,
2.773,
0.7372,
0.4608,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def common1(x):
x._lumi = {
"mumu": 1.139e+04,
"muon": 1.139e+04,
"mcPhot": 1.157e+04,
"phot": 1.157e+04,
"mcHad": 5.125e+03,
"had": 5.125e+03,
"mcMuon": 1.139e+04,
"mcMumu": 1.139e+04,
}
x._triggerEfficiencies = {
"hadBulk":
(1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"had":
(0.870, 0.986, 0.994, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon":
(0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880, 0.880),
"phot":
(1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.950, 0.960, 0.960, 0.970, 0.970, 0.970, 0.980, 0.980, 0.980,
0.980),
}
x._htBinLowerEdges = (
275.0,
325.0,
375.0,
475.0,
575.0,
675.0,
775.0,
875.0,
975.0,
1.075e+03,
)
x._htMaxForPlot = 1.175e+03
x._htMeans = (
298.0,
348.0,
416.0,
517.0,
617.0,
719.0,
819.0,
1044.,
0.0,
0.0,
)
x._observations["nPhot"] = tuple([None, None] +
list(x._observations["nPhot"][2:]))
uncs = {
"btagUncert": 0.035,
"lumi": 0.06,
"deadEcal": 0.03,
"lepVetoes": 0.025,
"jesjer": 0.025,
"pdf": 0.10
} # SMS other than T1, T2
uncs["btagUncert"] = 0.12 #T1, T2, cMSSM tb10 only
return quadSum(uncs.values())
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 1, 0, 0, 0, 0, 0, 0, 0)
#self._mergeBins = ( 0, 1, 2, 3, 4, 4, 4, 4)
#self._constantMcRatioAfterHere = ( 1, 0, 0, 0, 0)
#self._mergeBins = ( 0, 1, 2, 2, 2, 2, 2, 2)
#self._constantMcRatioAfterHere = ( 1, 0, 0)
#self._mergeBins = ( 0, 1, 2, 3, 3, 4, 4, 4)
#self._constantMcRatioAfterHere = ( 1, 0, 0, 0, 0)
self._lumi = {
"had": 769.,
"hadBulk": 769.,
"muon": 769.,
"mcMuon": 769.,
"mcTtw": 769.,
"phot": 771.2,
"mcGjets": 771.2,
"mcZinv": 468.8,
"mumu": 697.,
"mcZmumu": 697.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02)
self._observations = {
"nHadBulk":scaled(( 4.118e+07, 1.693e+07, 1.158e+07, 3.664e+06, 1.273e+06, 4.934e+05, 2.072e+05, 1.861e+05), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad51": ( 2.887e+04, 5.499e+03, 1.037e+03, 2.670e+02, 9.200e+01, 2.700e+01, 1.100e+01, 1.100e+01),
"nHad52": ( 6.481e+03, 9.260e+02, 3.570e+02, 1.090e+02, 4.500e+01, 1.300e+01, 5.000e+00, 3.000e+00),
"nHad53": ( 1.809e+03, 4.000e+02, 2.230e+02, 6.900e+01, 3.200e+01, 1.000e+01, 4.000e+00, 2.000e+00),
"nHad55": ( 5.720e+02, 2.370e+02, 1.400e+02, 4.500e+01, 1.800e+01, 3.000e+00, 2.000e+00, 1.000e+00),
"nPhot": excl(( 630, 227, 233, 81, 33, 15, 6, 3), isExcl),
#"nPhot2Jet": excl(( 255, 94, 99, 31, 11, 3, 1, 0), isExcl),
"nMuon": ( 262, 100, 78, 31, 12, 4, 0, 0),
#"nMuon2Jet": ( 86, 23, 25, 10, 2, 0, 0, 0),
"nMumu": excl(( 22, 5, 11, 6, 3, 0, 0, 0), isExcl),
}
self._observations["nHad"] = self._observations["nHad55"]
self._observations["nHadControl_53_55"] = tuple([n53-n55 for n53,n55 in zip(self._observations["nHad53"], self._observations["nHad55"])])
self._observations["nHadControl_52_53"] = tuple([n52-n53 for n52,n53 in zip(self._observations["nHad52"], self._observations["nHad53"])])
self._observations["nHadControl_51_52"] = tuple([n51-n52 for n51,n52 in zip(self._observations["nHad51"], self._observations["nHad52"])])
self._triggerEfficiencies = {
"hadBulk": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
#"had": ( 0.957, 0.986, 0.990, 0.990, 0.990, 0.990, 0.990, 0.990),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
}
for item in ["muon"] :
self._triggerEfficiencies[item] = self._triggerEfficiencies["had"]
#for item in ["hadControl_51_52", "hadControl_52_53", "hadControl_53_55"] :
# self._triggerEfficiencies[item] = self._triggerEfficiencies["had"]
self._mcExpectationsBeforeTrigger = {
"mcMuon": scaled((252.07, 104.36, 67.61, 24.04, 9.39, 4.37, 0.32, 0.22), self.lumi()["muon"]/self.lumi()["mcMuon"]),
#"mcMuon2Jet": scaled(( 86.03, 28.51, 25.63, 2.02, 4.78, 3.29, 0.107, 0), self.lumi()["muon"]/self.lumi()["mcMuon"]),
"mcTtw": scaled((274.87, 104.11, 66.67, 24.58, 4.18, 3.94, 1.92, 0.54), self.lumi()["had" ]/self.lumi()["mcTtw"] ),
"mcGjets": excl(scaled(( 440, 190, 181, 62, 22, 5, 4, 1.5), self.lumi()["phot"]/self.lumi()["mcGjets"]), isExcl),
#"mcPhot2Jet": excl(scaled(( 210, 91, 71, 20, 8, 0.4, 0.4, 0.4), self.lumi()["phot"]/self.lumi()["mcGjets"]), isExcl),
"mcZinv": excl(scaled(( 90, 41, 51, 24, 4, 1, 1, 0), self.lumi()["had"] /self.lumi()["mcZinv"]), isExcl),
"mcZmumu": excl(scaled(( 15, 9, 11, 7, 3, 0.9, 0, 0), self.lumi()["mumu"]/self.lumi()["mcZmumu"]), isExcl),
}
self._mcStatError = {
"mcMuonErr": ( 14.79, 10.39, 8.91, 5.39, 3.244, 2.286, 0.186, 0.152),
#"mcMuon2JetErr": ( 11.59, 7.23, 6.92, 2.84, 2.83, 2.31, 0.11, 0.1),
"mcTtwErr": ( 17.58, 10.41, 8.47, 5.40, 2.32, 2.28, 1.60, 0.24),
"mcGjetsErr": scaled(( 20, 10, 10, 6, 4, 2, 1, 0.9), self.lumi()["phot"]/self.lumi()["mcGjets"]),
#"mcPhot2JetErr": scaled(( 20, 10, 6, 3, 2, 0.4, 0.4, 0.4), self.lumi()["phot"]/self.lumi()["mcGjets"]),
"mcZinvErr": scaled(( 10, 7, 8, 5, 2, 1, 1, 1), self.lumi()["had"] /self.lumi()["mcZinv"]),
"mcZmumuErr": scaled(( 4, 3, 3, 3, 2, 1, 1, 1), self.lumi()["mumu"]/self.lumi()["mcZmumu"]),
}
self._mcStatError["mcHadErr"] = tuple([quadSum([ttwErr, zinvErr]) for ttwErr,zinvErr in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
self._purities = {
"phot": ( 0.92, 0.97, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99),
"mumu": ( 0.89, 0.94, 0.97, 0.97, 0.97, 0.97, 0.97, 0.97),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([ttw+zinv for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcExtraBeforeTrigger["mcPhot"] = tuple([gJet/purity for gJet,purity in zip(self._mcExpectationsBeforeTrigger["mcGjets"], self._purities["phot"])])
syst.load(self, mode = self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 160.0, 68.0, 52.0, 19.0, 11.0, 7.0, 0.0, 2.0, ) ,
"nMuon" : ( 116.0, 49.0, 264.0, 152.0, 63.0, 26.0, 10.0, 14.0, ) ,
"nMumu" : ( 4.0, 3.0, 8.0, 7.0, 5.0, 2.0, 0.0, 0.0, ) ,
"nPhot": excl(( None, None, 20, 10, 6, 4, 0, 0), isExcl),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets" : excl( ( None, None, 25, 9, 3, 3, 0.9, 0.9 ), isExcl),
"mcTtw" : ( 181.1, 69.64, 49.37, 26.42, 8.904, 3.795, 0.6144, 1.183, ) ,
"mcZinv" : ( 19.91, 8.835, 8.185, 2.92, 1.218, 0.3464, 0.07037, 0.0, ) ,
"mcMumu" : ( 3.331, 4.9, 10.42, 3.777, 0.8922, 0.9244, 0.03023, 0.06706, ) ,
"mcMuon" : ( 149.8, 67.0, 281.1, 156.0, 74.87, 31.07, 14.01, 15.05, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 4, 2, 1, 1, 0.9, 0.9),
"mcTtwErr" : ( 12.19, 6.101, 2.981, 2.186, 1.211, 0.8435, 0.3401, 0.4419, ) ,
"mcZinvErr" : ( 1.137, 0.7513, 0.7231, 0.4319, 0.279, 0.1488, 0.06705, 0.0, ) ,
"mcMuonErr" : ( 8.983, 6.111, 7.206, 5.346, 3.707, 2.384, 1.586, 1.637, ) ,
"mcMumuErr" : ( 0.9278, 1.373, 1.7, 0.9549, 0.395, 0.5199, 0.05894, 0.05347, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
160.0,
68.0,
52.0,
19.0,
11.0,
7.0,
0.0,
2.0,
),
"nMuon": (
116.0,
49.0,
264.0,
152.0,
63.0,
26.0,
10.0,
14.0,
),
"nMumu": (
4.0,
3.0,
8.0,
7.0,
5.0,
2.0,
0.0,
0.0,
),
"nPhot":
excl((None, None, 20, 10, 6, 4, 0, 0), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl((None, None, 25, 9, 3, 3, 0.9, 0.9), isExcl),
"mcTtw": (
181.1,
69.64,
49.37,
26.42,
8.904,
3.795,
0.6144,
1.183,
),
"mcZinv": (
19.91,
8.835,
8.185,
2.92,
1.218,
0.3464,
0.07037,
0.0,
),
"mcMumu": (
3.331,
4.9,
10.42,
3.777,
0.8922,
0.9244,
0.03023,
0.06706,
),
"mcMuon": (
149.8,
67.0,
281.1,
156.0,
74.87,
31.07,
14.01,
15.05,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 4, 2, 1, 1, 0.9, 0.9),
"mcTtwErr": (
12.19,
6.101,
2.981,
2.186,
1.211,
0.8435,
0.3401,
0.4419,
),
"mcZinvErr": (
1.137,
0.7513,
0.7231,
0.4319,
0.279,
0.1488,
0.06705,
0.0,
),
"mcMuonErr": (
8.983,
6.111,
7.206,
5.346,
3.707,
2.384,
1.586,
1.637,
),
"mcMumuErr": (
0.9278,
1.373,
1.7,
0.9549,
0.395,
0.5199,
0.05894,
0.05347,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 10.0, 8.0, 8.0, 1.0, 0.0, 0.0, 0.0, 0.0, ) ,
"nMuon" : ( 9.0, 6.0, 22.0, 16.0, 13.0, 3.0, 1.0, 4.0, ) ,
"nMumu" : ( 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0, 0.0, ) ,
"nPhot" : (None, None, 1, 0, 0, 0, 0, 0, ),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
#"mcGjets" : excl( ( None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0 ), isExcl),
"mcGjets" : ( None, None, 0.8, 0.8, 0.3, 0.1, 0.03, 0.03 ),
#"mcTtw" : ( 14.98, 4.788, 4.243, 2.604, 0.5211, 0.3001, 0.01408, 0.06082, ) ,
#"mcTtw" : ( 7.313, 2.8670, 2.720, 1.5100,0.640397,0.469682,0.079102,0.064794,), #March 26 (ttw and zInv)
"mcTtw" : (12.783, 5.0463, 4.925, 3.1325,1.291151,0.975077,0.130844,0.117748,), #March 27 (ttw and zInv)
#"mcZinv" : ( 1.079, 0.5188, 0.316, 0.1634, 0.0, 0.09114, 0.0, 0.0, ) ,
"mcZinv" : ( 1.079, 0.5188, 0.316, 0.1634, 0.1, 0.09114, 0.01, 0.02, ) ,
#"mcZinv" : ( 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 26 ttw has both
#"mcZinv" : ( 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 27 ttw has both
"mcMumu" : ( 0.01635, 0.01, 0.6904, 0.2, 0.06, 0.02, 0.02, 0.02, ) ,
#"mcMuon" : ( 13.1, 4.235, 26.51, 15.14, 8.438, 2.703, 1.364, 1.872, ) ,
#"mcMuon" : ( 6.90, 2.94, 14.25, 9.20, 5.238, 1.988, 1.103, 1.169,), #March 26
"mcMuon" : (10.87, 4.561, 20.81, 14.80, 9.018, 3.533, 2.003, 2.485,), #March 27
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
#"mcTtwErr" : ( 1.686, 0.9518, 0.8906, 0.6971, 0.2472, 0.2281, 0.05278, 0.05092, ) ,
"mcTtwErr" : ( 0.343, 0.2217, 0.1930, 0.1666, 0.1256, 0.1370, 0.04483, 0.034354,), #March 27
#"mcZinvErr" : ( 0.2626, 0.1821, 0.1421, 0.1022, 0.0, 0.07631, 0.0, 0.0, ) ,
"mcZinvErr" : ( 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 27
#"mcMuonErr" : ( 1.593, 0.8971, 2.259, 1.693, 1.274, 0.7076, 0.5003, 0.5946, ) ,
#"mcMuonErr" : ( 0.333, 0.1958, 0.379, 0.328, 0.325, 0.1546, 0.1190, 0.1576,), #March 26
"mcMuonErr" : ( 0.380, 0.2289, 0.442, 0.392, 0.403, 0.1836, 0.1467, 0.1891,), #March 27
"mcMumuErr" : ( 0.01389, 0.0, 0.3678, 0.0, 0.003354, 0.0, 0.0, 0.0, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
2919.0,
1166.0,
769.0,
255.0,
91.0,
31.0,
10.0,
4.0,
),
"nMuon": (
949.0,
444.0,
1707.0,
748.0,
305.0,
148.0,
81.0,
87.0,
),
"nMumu": (
95.0,
53.0,
216.0,
86.0,
48.0,
23.0,
5.0,
11.0,
),
"nPhot":
excl((None, None, 1642 - 221, 596 - 84, 221 - 37, 91 - 16, 32 - 7,
14 - 2), isExcl), #>=0 b-tag minus >=1 b-tag
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 2.00e+3 - 2.3e2, 7.1e+2 - 82, 2.7e+2 - 35,
92 - 15, 34 - 6, 14 - 3),
isExcl), #>=0 b-tag minus >=1 b-tag
"mcTtw": (
1620.0,
601.5,
375.3,
128.7,
44.36,
17.35,
5.84,
4.109,
),
"mcZinv": (
1515.0,
635.8,
475.6,
165.3,
63.21,
21.3,
9.142,
6.196,
),
"mcMumu": (
110.6,
65.92,
255.8,
120.0,
53.79,
24.3,
13.31,
10.74,
),
"mcMuon": (
1145.0,
532.1,
1886.0,
857.3,
371.9,
179.5,
85.31,
104.5,
),
}
self._mcStatError = {
"mcGjetsErr":
(None, None, 0.04e+3, 0.2e+2, 0.1e+2, 8, 5, 3), #>=0 b-tag
"mcTtwErr": (
66.98,
40.54,
4.864,
2.85,
1.656,
1.151,
0.5746,
0.4422,
),
"mcZinvErr": (
9.983,
6.39,
5.518,
3.25,
2.01,
1.167,
0.7642,
0.6292,
),
"mcMuonErr": (
55.42,
38.09,
11.08,
7.601,
4.916,
3.504,
2.212,
2.589,
),
"mcMumuErr": (
6.532,
5.065,
10.01,
6.854,
4.576,
3.086,
2.29,
2.037,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = ( 0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":scaled(( 2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06, 3.954e+06, 1.679e+06, 1.563e+06), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad" : ( 614.0, 294.0, 214.0, 71.0, 20.0, 6.0, 4.0, 0.0, ) ,
"nMuon" : ( 347.0, 146.0, 568.0, 288.0, 116.0, 48.0, 22.0, 26.0, ) ,
"nMumu" : ( 15.0, 9.0, 34.0, 20.0, 10.0, 7.0, 0.0, 6.0, ) ,
"nPhot": excl(( None, None, 200, 74, 31, 12, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk": ( 0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl( ( None, None, 2.0e2, 72, 31, 12, 6, 3 ), isExcl), #>=1 b-tag
"mcTtw" : ( 428.6, 199.0, 143.2, 49.2, 16.34, 9.632, 2.014, 0.7877, ) ,
"mcZinv" : ( 170.1, 72.91, 48.15, 20.86, 7.816, 2.654, 0.9874, 0.8448, ) ,
"mcMumu" : ( 19.41, 6.645, 27.72, 13.81, 8.911, 3.04, 1.211, 2.145, ) ,
"mcMuon" : ( 386.9, 169.7, 582.6, 286.7, 136.0, 60.56, 27.97, 29.74, ) ,
}
self._mcStatError = {
"mcGjetsErr" : ( None, None, 10, 7, 5, 3, 2, 1),
"mcTtwErr" : ( 20.84, 16.65, 4.627, 2.682, 1.532, 1.247, 0.4522, 0.2632, ) ,
"mcZinvErr" : ( 3.357, 2.164, 1.754, 1.154, 0.7066, 0.4118, 0.2512, 0.2323, ) ,
"mcMuonErr" : ( 19.8, 12.09, 9.159, 6.487, 4.503, 2.997, 1.957, 1.934, ) ,
"mcMumuErr" : ( 2.598, 1.604, 3.101, 2.188, 1.8, 0.9922, 0.6249, 0.8243, ) ,
}
self._purities = {
"phot": ( None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([(ttw+zinv if ttw!=None and zinv!=None else None) for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcStatError["mcHadErr"] = tuple([quadSum([x,y]) for x,y in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
syst.load(self, mode = self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
10.0,
8.0,
8.0,
1.0,
0.0,
0.0,
0.0,
0.0,
),
"nMuon": (
9.0,
6.0,
22.0,
16.0,
13.0,
3.0,
1.0,
4.0,
),
"nMumu": (
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
),
"nPhot": (
None,
None,
1,
0,
0,
0,
0,
0,
),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0), isExcl),
#"mcTtw" : ( 14.98, 4.788, 4.243, 2.604, 0.5211, 0.3001, 0.01408, 0.06082, ) ,
#"mcTtw" : ( 7.313, 2.8670, 2.720, 1.5100,0.640397,0.469682,0.079102,0.064794,), #March 26 (ttw and zInv)
"mcTtw": (
12.803,
4.9976,
4.836,
3.0502,
1.256734,
0.951101,
0.128434,
0.117421,
), #March 27 (ttw and zInv)
#"mcZinv" : ( 1.079, 0.5188, 0.316, 0.1634, 0.0, 0.09114, 0.0, 0.0, ) ,
#"mcZinv" : ( 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 26 ttw has both
"mcZinv":
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 27 ttw has both
"mcMumu": (
0.01635,
0.0,
0.6904,
0.0,
0.002354,
0.0,
0.0,
0.0,
),
#"mcMuon" : ( 13.1, 4.235, 26.51, 15.14, 8.438, 2.703, 1.364, 1.872, ) ,
#"mcMuon" : ( 6.90, 2.94, 14.25, 9.20, 5.238, 1.988, 1.103, 1.169,), #March 26
"mcMuon": (
10.97,
4.515,
20.71,
14.59,
8.818,
3.449,
1.960,
2.486,
), #March 27
}
self._mcStatError = {
"mcGjetsErr": (None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
#"mcTtwErr" : ( 1.686, 0.9518, 0.8906, 0.6971, 0.2472, 0.2281, 0.05278, 0.05092, ) ,
"mcTtwErr": (
0.352,
0.2270,
0.1969,
0.1706,
0.1288,
0.1405,
0.04618,
0.035571,
), #March 27
#"mcZinvErr" : ( 0.2626, 0.1821, 0.1421, 0.1022, 0.0, 0.07631, 0.0, 0.0, ) ,
"mcZinvErr": (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), #March 27
#"mcMuonErr" : ( 1.593, 0.8971, 2.259, 1.693, 1.274, 0.7076, 0.5003, 0.5946, ) ,
#"mcMuonErr" : ( 0.333, 0.1958, 0.379, 0.328, 0.325, 0.1546, 0.1190, 0.1576,), #March 26
"mcMuonErr": (
0.394,
0.2327,
0.450,
0.400,
0.411,
0.1874,
0.1498,
0.1982,
), #March 27
"mcMumuErr": (
0.01389,
0.0,
0.3678,
0.0,
0.003354,
0.0,
0.0,
0.0,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def common(x):
common1(x)
systBins = tuple([0] * 1 + [1] * 1 + [2] * 1 + [3] * 2 + [4] * 2 +
[5] * 2 + [6] * 2)
name = x.__class__.__name__
dm10_250_xs = 5.6
if "0b_ge4j" in name:
effHad = [
1.73e-06, 4.85e-05, 1.20e-04, 1.90e-04, 2.15e-04, 1.15e-04,
7.62e-05, 5.74e-05, 2.65e-05, 1.97e-05, 2.04e-05
]
elif "0b_le3j" in name:
effHad = [
3.73e-03, 2.01e-03, 1.51e-03, 1.52e-03, 7.07e-04, 2.77e-04,
1.42e-04, 3.34e-05, 2.57e-05, 1.42e-05, 7.89e-06
]
elif "1b_ge4j" in name:
effHad = [
0.00e+00, 7.14e-06, 2.37e-05, 2.19e-05, 2.29e-05, 1.21e-05,
3.77e-06, 1.01e-05, 2.50e-06, 2.86e-06, 2.69e-06
]
elif "1b_le3j" in name:
effHad = [
2.77e-04, 1.78e-04, 1.13e-04, 1.41e-04, 5.05e-05, 3.50e-05,
1.03e-05, 2.17e-06, 1.34e-06, 0.00e+00, 0.00e+00
]
elif "2b_ge4j" in name:
effHad = [
0.00e+00, 3.85e-06, 1.60e-06, 2.96e-06, 2.38e-06, 4.12e-06,
1.38e-06, 1.60e-06, 1.13e-06, 0.00e+00, 0.00e+00
]
elif "2b_le3j" in name:
effHad = [
1.26e-05, 1.39e-05, 1.41e-05, 1.29e-05, 4.91e-06, 1.47e-06,
2.77e-06, 7.31e-07, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "3b_ge4j" in name:
effHad = [
0.00e+00, 0.00e+00, 0.00e+00, 1.14e-06, 0.00e+00, 0.00e+00,
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "3b_le3j" in name:
effHad = [
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00,
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00
]
elif "4b_ge4j" in name:
effHad = [
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00,
0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00, 0.00e+00
]
if "le3j" in name:
systMagnitudes = (0.04, 0.06, 0.06, 0.08, 0.13, 0.18, 0.20)
x._triggerEfficiencies["had"] = (0.818, 0.952, 0.979, 0.992, 0.998,
0.994, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (3.4067318E09, 8.317453E08,
3.29919975E08, 2.74138825E08,
8.507427E07, 2.8887025E07, 1.09110E07,
4.6215E06, 2.07715E06, 1.031125E06,
1.20755E06)
elif "ge4j" in name:
systMagnitudes = (0.06, 0.06, 0.11, 0.11, 0.19, 0.19, 0.25)
x._triggerEfficiencies["had"] = (0.789, 0.900, 0.956, 0.987, 1.000,
1.000, 1.000, 1.000, 1.000, 1.000,
1.000)
x._observations["nHadBulk"] = (6.60088E07, 1.400533E08, 5.2689525E07,
4.8204025E07, 3.35079E07, 1.582655E07,
7.279475E06, 3.46345E06, 1.732725E06,
8.9562E05, 1.142775E06)
x._observations["nHad"] = [
m + (y * dm10_250_xs * x._lumi["had"] * z) for m, y, z in zip(
x._observations["nHad"], effHad, x._triggerEfficiencies["had"])
]
if "ge4b" in name:
x._mergeBins = (0, 1, 2, 3, 3, 3, 3, 3, 3, 3, 3)
systMagnitudes = (0.15, )
systBins = (0, 0, 0, 0)
else:
x._mergeBins = None
x._systBins = {
"sigmaPhotZ": systBins,
"sigmaMuonW": systBins,
"sigmaMumuZ": systBins,
}
x._fixedParameters = {
"sigmaPhotZ": systMagnitudes,
"sigmaMuonW": systMagnitudes,
"sigmaMumuZ": systMagnitudes,
"k_qcd_nom": 2.96e-2,
"k_qcd_unc_inp": quadSum([0.61e-2, 0.463e-2])
#"k_qcd_unc_inp":quadSum([2.5*0.61e-2, 2.5*0.463e-2])
}
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 1, 0, 0, 0)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
10.0,
8.0,
8.0,
1.0,
0.0,
0.0,
0.0,
0.0,
),
"nMuon": (
9.0,
6.0,
22.0,
16.0,
13.0,
3.0,
1.0,
4.0,
),
"nMumu": (
0.0,
0.0,
1.0,
0.0,
0.0,
0.0,
1.0,
0.0,
),
"nPhot": (
None,
None,
1,
0,
0,
0,
0,
0,
),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets":
excl((None, None, 1.0, 0.8, 0.0, 0.0, 0.0, 0.0), isExcl),
"mcTtw": (
14.52,
4.638,
4.115,
2.576,
0.5129,
0.3197,
0.01486,
0.06064,
),
"mcZinv": (
1.12,
0.5603,
0.3348,
0.1535,
0.0,
0.09399,
0.0,
0.0,
),
"mcMumu": (
0.01747,
0.0,
0.6829,
0.0,
0.002146,
0.0,
0.0,
0.0,
),
"mcMuon": (
12.86,
3.949,
25.7,
14.56,
8.121,
2.634,
1.318,
1.882,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 0.8, 0.8, 0.0, 0.0, 0.0, 0.0),
"mcTtwErr": (
1.916,
0.9796,
1.01,
0.8368,
0.3255,
0.2741,
0.01486,
0.06064,
),
"mcZinvErr": (
0.4274,
0.224,
0.185,
0.1305,
0.0,
0.09399,
0.0,
0.0,
),
"mcMuonErr": (
2.82,
0.9221,
2.876,
2.613,
1.296,
0.7105,
0.5531,
0.6301,
),
"mcMumuErr": (
0.01747,
0.0,
0.5021,
0.0,
0.002146,
0.0,
0.0,
0.0,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self):
isExcl = (1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0,
775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._constantMcRatioAfterHere = (0, 0, 0, 0, 0, 0, 0, 1)
self._lumi = {
"had": 4650.,
"hadBulk": 4650.,
"muon": 4650.,
"mcMuon": 4650.,
"mcTtw": 4650.,
"phot": 4529.,
"mcGjets": 4529.,
"mcZinv": 4529.,
"mumu": 4650.,
"mcMumu": 4650.,
}
self._htMeans = (2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02,
7.171e+02, 8.179e+02, 9.188e+02) #old
self._observations = {
"nHadBulk":
scaled((2.792e+08, 1.214e+08, 8.544e+07, 2.842e+07, 9.953e+06,
3.954e+06, 1.679e+06, 1.563e+06),
self.lumi()["had"] / self.lumi()["hadBulk"]),
"nHad": (
614.0,
294.0,
214.0,
71.0,
20.0,
6.0,
4.0,
0.0,
),
"nMuon": (
347.0,
146.0,
568.0,
288.0,
116.0,
48.0,
22.0,
26.0,
),
"nMumu": (
15.0,
9.0,
34.0,
20.0,
10.0,
7.0,
0.0,
6.0,
),
"nPhot":
excl((None, None, 200, 74, 31, 12, 7, 2), isExcl),
}
self._triggerEfficiencies = {
"hadBulk":
(0.878, 0.906, 0.957, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": (0.727, 0.869, 0.943, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
"phot": (1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": (0.727, 0.869, 0.950, 0.950, 0.950, 0.950, 0.950, 0.950),
}
self._mcExpectationsBeforeTrigger = {
"mcGjets": excl((None, None, 2.0e2, 72, 31, 12, 6, 3),
isExcl), #>=1 b-tag
"mcTtw": (
428.6,
199.0,
143.2,
49.2,
16.34,
9.632,
2.014,
0.7877,
),
"mcZinv": (
170.1,
72.91,
48.15,
20.86,
7.816,
2.654,
0.9874,
0.8448,
),
"mcMumu": (
19.41,
6.645,
27.72,
13.81,
8.911,
3.04,
1.211,
2.145,
),
"mcMuon": (
386.9,
169.7,
582.6,
286.7,
136.0,
60.56,
27.97,
29.74,
),
}
self._mcStatError = {
"mcGjetsErr": (None, None, 10, 7, 5, 3, 2, 1),
"mcTtwErr": (
20.84,
16.65,
4.627,
2.682,
1.532,
1.247,
0.4522,
0.2632,
),
"mcZinvErr": (
3.357,
2.164,
1.754,
1.154,
0.7066,
0.4118,
0.2512,
0.2323,
),
"mcMuonErr": (
19.8,
12.09,
9.159,
6.487,
4.503,
2.997,
1.957,
1.934,
),
"mcMumuErr": (
2.598,
1.604,
3.101,
2.188,
1.8,
0.9922,
0.6249,
0.8243,
),
}
self._purities = {
"phot": (None, None, 0.98, 0.99, 0.99, 0.99, 0.99, 0.99),
}
self._mcExtraBeforeTrigger = {}
self._mcExtraBeforeTrigger["mcHad"] = tuple([
(ttw + zinv if ttw != None and zinv != None else None)
for ttw, zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"],
self._mcExpectationsBeforeTrigger["mcZinv"])
])
self._mcStatError["mcHadErr"] = tuple([
quadSum([x, y]) for x, y in zip(self._mcStatError["mcTtwErr"],
self._mcStatError["mcZinvErr"])
])
syst.load(self, mode=self.systMode)
def _fill(self) :
isExcl = ( 1, 1, 0, 0, 0, 0, 0, 1)
self._htBinLowerEdges = (275.0, 325.0, 375.0, 475.0, 575.0, 675.0, 775.0, 875.0)
self._htMaxForPlot = 975.0
self._mergeBins = None
self._lumi = {
"had": 1080.,
"hadBulk": 1080.,
"muon": 1080.,
"mcMuon": 1080.,
"mcTtw": 1080.,
"phot": 1057.,
"mcGjets": 1057.,
"mcZinv": 1057.,
"mumu": 697.,
"mcZmumu": 697.,
}
self._htMeans = ( 2.960e+02, 3.464e+02, 4.128e+02, 5.144e+02, 6.161e+02, 7.171e+02, 8.179e+02, 9.188e+02)
self._sigEffCorr = ( 9.88e-01, 9.84e-01, 9.96e-01, 9.71e-01, 9.60e-01, 9.58e-01, 9.52e-01, 9.35e-01); print "sigEffCorr ignored"
self._observations = {
"nHadBulk":scaled(( 5.733e+07, 2.358e+07, 1.619e+07, 5.116e+06, 1.777e+06, 6.888e+05, 2.900e+05, 2.599e+05), self.lumi()["had"]/self.lumi()["hadBulk"]),
"nHad": ( 7.820e+02, 3.210e+02, 1.960e+02, 6.200e+01, 2.100e+01, 6.000e+00, 3.000e+00, 1.000e+00),
"nPhot": excl(( 849, 307, 321, 111, 44, 20, 8, 4), isExcl),
"nPhot2Jet": excl(( 336, 127, 136, 40, 13, 4, 2, 0), isExcl),
"nMuon": ( 389, 156, 113, 39, 17, 5, 0, 0),
"nMuon2Jet": ( 128, 37, 36, 12, 2, 0, 0, 0),
"nMumu": excl(( 22, 5, 11, 6, 3, 0, 0, 0), isExcl),
}
self._observations["nHad_55"] = self._observations["nHad"]
self._triggerEfficiencies = {
"hadBulk": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
#"had": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"had": ( 0.991, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"muon": ( 0.991, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"mumu": ( 0.991, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
"phot": ( 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000, 1.000),
}
for item in ["hadControl_51_52", "hadControl_52_53", "hadControl_53_55"] :
self._triggerEfficiencies[item] = self._triggerEfficiencies["had"]
self._mcExpectationsBeforeTrigger = {
"mcMuon": scaled((411.20, 179.11, 131.59, 48.68, 13.32, 7.95, 3.20, 0.90), self.lumi()["muon"]/self.lumi()["mcMuon"]),
"mcMuon2Jet": scaled((121.83, 54.43, 45.06, 14.89, 3.69, 0.72, 0.72, 0.00), self.lumi()["muon"]/self.lumi()["mcMuon"]),
"mcMuon2JetSpring11": scaled((139.39, 53.17, 40.62, 2.84, 6.71, 4.63, 0.15, 0.00), self.lumi()["muon"]/self.lumi()["mcMuon"]),
"mcMuon2JetSpring11Re": scaled((113.86, 48.99, 39.57, 3.75, 3.13, 6.61, 0.166, 0.0 ), self.lumi()["muon"]/self.lumi()["mcMuon"]),
"mcTtw": scaled((467.25, 171.16, 116.33, 43.68, 17.50, 5.08, 1.09, 1.81), self.lumi()["had" ]/self.lumi()["mcTtw"] ),
"mcGjets": excl(scaled(( 600, 260, 250, 85, 31, 8, 5, 2), self.lumi()["phot"]/self.lumi()["mcGjets"]), isExcl),
"mcPhot2Jet": excl(scaled(( 290, 124, 98, 26, 10, 0.5, 0.5, 0.5), self.lumi()["phot"]/self.lumi()["mcGjets"]), isExcl),
"mcZinv": excl(scaled(( 210, 90, 110, 50, 8, 3, 3, 0), self.lumi()["had"] /self.lumi()["mcZinv"]), isExcl),
"mcMumu": excl(scaled(( 15, 9, 11, 7, 3, 0.9, 0, 0), self.lumi()["mumu"]/self.lumi()["mcZmumu"]), isExcl),
}
self._mcStatError = {
"mcMuonErr": ( 14.51, 9.57, 8.78, 5.54, 2.92, 2.29, 1.44, 0.73),
"mcMuon2JetErr": ( 9.01, 6.07, 5.54, 3.22, 1.61, 0.72, 0.72, 0.00),
"mcMuon2JetSpring11Err": ( 17.06, 10.50, 9.25, 2.26, 3.88, 3.17, 0.15, 0.00),
"mcMuon2JetSpring11ReErr": ( 14.54, 10.34, 9.42, 3.93, 2.45, 3.51, 0.166, 0.00),
"mcTtwErr": ( 16.00, 9.47, 8.26, 5.06, 3.17, 1.80, 0.73, 1.03),
"mcGjetsErr": scaled(( 20, 10, 10, 8, 5, 2, 2, 1), self.lumi()["phot"]/self.lumi()["mcGjets"]),
"mcPhot2JetErr": scaled(( 40, 10, 8, 4, 3, 0.5, 0.5, 0.5), self.lumi()["phot"]/self.lumi()["mcGjets"]),
"mcZinvErr": scaled(( 20, 20, 20, 10, 5, 3, 3, 3), self.lumi()["had"] /self.lumi()["mcZinv"]),
"mcMumuErr": scaled(( 4, 3, 3, 3, 2, 1, 1, 1), self.lumi()["mumu"]/self.lumi()["mcZmumu"]),
}
self._mcStatError["mcHadErr"] = tuple([quadSum([ttwErr, zinvErr]) for ttwErr,zinvErr in zip(self._mcStatError["mcTtwErr"], self._mcStatError["mcZinvErr"])])
self._purities = {
"phot": ( 0.92, 0.97, 0.99, 0.99, 0.99, 0.99, 0.99, 0.99),
"mumu": ( 0.89, 0.94, 0.97, 0.97, 0.97, 0.97, 0.97, 0.97),
}
self._mcExpectationsBeforeTrigger["mcHad"] = tuple([ttw+zinv for ttw,zinv in zip(self._mcExpectationsBeforeTrigger["mcTtw"], self._mcExpectationsBeforeTrigger["mcZinv"])])
self._mcExpectationsBeforeTrigger["mcPhot"] = tuple([gJet/purity for gJet,purity in zip(self._mcExpectationsBeforeTrigger["mcGjets"], self._purities["phot"])])
syst.load(self, mode = self.systMode)
#remove outdated key
del self._mcExpectationsBeforeTrigger["mcGjets"]
#force constant mc ratios for HT>375
i = 2 #constantMcRatioAfterHere = (0, 0, 1, 0, 0, 0, 0, 0)
phot = self._mcExpectationsBeforeTrigger["mcPhot"]
zinv = self._mcExpectationsBeforeTrigger["mcZinv"]
rFinal = sum(zinv[i:])/sum(phot[i:])
self._mcExpectationsBeforeTrigger["mcZinv"] = zinv[:i]+tuple([x*rFinal for x in phot[i:]])
muon = self._mcExpectationsBeforeTrigger["mcMuon"]
ttw = self._mcExpectationsBeforeTrigger["mcTtw"]
rFinal = sum(ttw[i:])/sum(muon[i:])
self._mcExpectationsBeforeTrigger["mcTtw"] = ttw[:i]+tuple([x*rFinal for x in muon[i:]])
