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]*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:]])