Пример #1
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 def conclude(self,pars) :
     from core import plotter
     org = self.organizer(pars)
     org.mergeSamples(targetSpec = {"name":"qcd_py6", "color":r.kBlue}, allWithPrefix="v12_qcd_py6")
     org.scale(100)
     plotter.plotter( org,
                      psFileName = self.psFileName(org.tag),
                      blackList = ["lumiHisto","xsHisto","xsPostWeightsHisto","nJobsHisto"],
                      ).plotAll()
Пример #2
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 def conclude(self,pars) :
     #make a pdf file with plots from the histograms created above
     org = self.organizer(pars)
     org.scale()
     plotter.plotter( org,
                      psFileName = self.psFileName(org.tag),
                      samplesForRatios = ("Example_Skimmed_900_GeV_Data","Example_Skimmed_900_GeV_MC"),
                      sampleLabelsForRatios = ("data","sim"),
                      ).plotAll()
Пример #3
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 def conclude(self,pars) :
     from core import plotter
     org = self.organizer(pars)
     org.mergeSamples(targetSpec = {"name":"qcd_mg", "color":r.kBlue}, allWithPrefix="qcd_mg")
     org.mergeSamples(targetSpec = {"name":"qcd_py6", "color":r.kRed}, allWithPrefix="qcd_py6")
     org.scale()
     plotter.plotter( org,
                      psFileName = self.psFileName(org.tag),
                      blackList = ["lumiHisto","xsHisto","xsPostWeightsHisto","nJobsHisto","genpthat"],
                      detailedCalculables = True,
                      ).plotAll()
Пример #4
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    def conclude(self, conf) :
        org = self.organizer(conf)

        ##for skimming only
        #utils.printSkimResults(org)            

        lineWidth = 3; goptions = "hist"
        org.mergeSamples(targetSpec = {"name":"2011 Data", "color":r.kBlack, "markerStyle":20}, allWithPrefix="DoubleMu.Run2011")
        org.mergeSamples(targetSpec = {"name":"t#bar{t}",  "color":r.kOrange, "lineWidth":lineWidth, "goptions":goptions}, allWithPrefix="tt")
        org.mergeSamples(targetSpec = {"name":"DY->ll",    "color":r.kBlue,   "lineWidth":lineWidth, "goptions":goptions}, allWithPrefix="dyll")
        org.mergeSamples(targetSpec = {"name":"W + jets",  "color":r.kRed,    "lineWidth":lineWidth, "goptions":goptions}, allWithPrefix="w_jets")
        org.mergeSamples(targetSpec = {"name":"s.m.",      "color":r.kGreen,  "lineWidth":lineWidth, "goptions":goptions},
                         sources = ["t#bar{t}", "DY->ll", "W + jets"], keepSources = True)
        
        org.scale() if not self.parameters()["tanBeta"] else org.scale(100.0)
            
        #plot
        pl = plotter.plotter(org,
                             psFileName = self.psFileName(org.tag),
                             samplesForRatios = ("2011 Data","DY->ll"),
                             sampleLabelsForRatios = ("data","DY"),
                             showStatBox = True,
                             #doLog = False,
                             linYAfter = ("value", "0.40<=xcak5JetMhtOverHtPat"),
                             pegMinimum = 0.1,
                             blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                             )
        pl.plotAll()
Пример #5
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    def conclude(self,pars) :
        from core.plotter import plotter
        org = self.organizer(pars)
        org.mergeSamples(targetSpec = {"name":"SingleMu","color":r.kBlack,"markerStyle":20}, allWithPrefix="SingleMu")
        org.mergeSamples(targetSpec = {"name":"qcd", "color":r.kBlue}, allWithPrefix="qcd")
        org.mergeSamples(targetSpec = {"name":"w_jets","color":r.kRed}, allWithPrefix="w_jets")
        org.mergeSamples(targetSpec = {"name":"t#bar{t}","color":r.kViolet}, allWithPrefix="tt_tauola_fj_mg")
        #org.scaleOneRaw([ss['name'] for ss in org.samples].index('w_jets'), 0.6)
        org.mergeSamples(targetSpec = {"name":"s.m.", "color":r.kGreen+3}, keepSources = True, sources = ['qcd','w_jets','t#bar{t}'], force = True)
        org.scale()

        kwargs = { "blackList":["lumiHisto","xsHisto","nJobsHisto","muonTriggerWeightPF"],
                   "samplesForRatios":("SingleMu","s.m.") if "s.m." in [ss['name'] for ss in org.samples] else ("","")}

        plotter(org, psFileName = self.psFileName(org.tag+'_log'),   doLog = True,  **kwargs).plotAll()
        plotter(org, psFileName = self.psFileName(org.tag+'_nolog'), doLog = False, **kwargs).plotAll()
Пример #6
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 def conclude(self,conf) :
     org = self.organizer(conf)
     #org.mergeSamples(targetSpec = {"name":"SingleMu", "color":r.kBlack}, allWithPrefix="SingleMu")
     #org.scale()
     
     from core.plotter import plotter
     plotter(org,
             psFileName = self.psFileName(org.tag),
             #samplesForRatios = ("2010 Data","standard_model"),
             #sampleLabelsForRatios = ("data","s.m."),
             #whiteList = ["lowestUnPrescaledTrigger"],
             #doLog = False,
             #compactOutput = True,
             #noSci = True,
             #pegMinimum = 0.1,
             blackList = ["lumiHisto","xsHisto","nJobsHisto"],
             ).plotAll()
Пример #7
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 def plotMeldScale(self) :
     if not hasattr(self,"orgMelded") : print "run meldScale() before plotMeldScale()"; return
     melded = copy.deepcopy(self.orgMelded)
     for ss in filter(lambda ss: 'tt_tauola_fj' in ss['name'], melded.samples) : melded.drop(ss['name'])
     pl = plotter.plotter(melded, psFileName = self.psFileName(melded.tag),
                          doLog = False,
                          blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                          rowColors = self.rowcolors,
                          samplesForRatios = ("top.Data 2011","S.M."),
                          sampleLabelsForRatios = ('data','s.m.')
                          ).plotAll()
Пример #8
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    def makeIndividualPlots(self, org) :
        #plot all
        pl = plotter.plotter(org,
                             psFileName = self.psFileName(org.tag),
                             showStatBox = False,
                             doLog = False,
                             anMode = True,
                             )
        pl.individualPlots(plotSpecs = [{"plotName":"xcak5JetAlphaTFewBinsPat",
                                         "stepName" :"alphaHistogrammer",
                                         "stepDesc" :"xcak5JetPat",
                                         "newTitle":";#alpha_{T};events / bin"},

                                        #{"plotName":"xcak5JetAlphaTRoughPat",
                                        # "stepName" :"variablePtGreaterFilter",
                                        # "stepDesc" :"xcak5JetSumP4Pat.pt()>=140.0 GeV",
                                        # "newTitle":";#alpha_{T};events / bin / 35 pb^{-1}"},

                                        {"plotName":"xcak5JetIndicesPat",
                                         "stepName" :"histogrammer",
                                         "stepDesc" :"(lambda x:len(x))(xcak5JetIndicesPat)",
                                         "newTitle":";N_{jets};events / bin"},
                                        
                                        #{"plotName":"photonPat1MinDRToJet",
                                        # "stepName" :"passFilter",
                                        # "stepDesc" :"singlePhotonPlots2",
                                        # "newTitle":";#DeltaR(photon, nearest jet);events / bin / 35 pb^{-1}",
                                        # "reBinFactor":3},
                                        #
                                        #{"plotName":"photonPat1SeedTime",
                                        # "stepName" :"passFilter",
                                        # "stepDesc" :"singlePhotonPlots2",
                                        # "newTitle":";time of photon seed crystal hit (ns);events / bin / 35 pb^{-1}",
                                        # "sampleWhiteList": ["2010 Data"]},
                                        #
                                        #{"plotName":"photonPat1sigmaIetaIetaBarrel",
                                        # "stepName" :"passFilter",
                                        # "stepDesc" :"singlePhotonPlots2",
                                        # "newTitle":";#sigma_{i#eta i#eta};events / bin / 35 pb^{-1}"},
                                        
                                        #{"plotName":"photonPat1combinedIsolation",
                                        # "stepName" :"passFilter",
                                        # "stepDesc" :"singlePhotonPlots2",
                                        # "onlyDumpToFile":True},

                                        ],
                           newSampleNames = {"qcd_mg_nVtx": "Madgraph QCD",
                                             "g_jets_mg_nVtx": "Madgraph #gamma + jets",
                                             "2011 Data": "Data",
                                             "standard_model_nVtx": "Standard Model",
                                             },
                           preliminary = True,
                           )
Пример #9
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    def conclude(self,pars) :
        org = self.organizer(pars)
        org.mergeSamples(targetSpec = {"name":"Data 2011", "color":r.kBlack, "markerStyle":20}, allWithPrefix="SingleMu")
        org.mergeSamples(targetSpec = {"name":"qcd_py6", "color":r.kBlue}, allWithPrefix="qcd_py6")
        org.mergeSamples(targetSpec = {"name":"t#bar{t}", "color":r.kViolet}, sources=["tt_tauola_fj.wNonQQbar.tw.nvr","tt_tauola_fj.wTopAsymP00.tw.nvr"], keepSources = True)
        org.mergeSamples(targetSpec = {"name":"t#bar{t}.q#bar{q}.N30", "color":r.kRed}, sources = ["tt_tauola_fj.wTopAsymN30.tw.nvr","tt_tauola_fj.wNonQQbar.tw.nvr"][:1])
        org.mergeSamples(targetSpec = {"name":"t#bar{t}.q#bar{q}.P30", "color":r.kGreen}, sources = ["tt_tauola_fj.wTopAsymP30.tw.nvr","tt_tauola_fj.wNonQQbar.tw.nvr"][:1])
        org.mergeSamples(targetSpec = {"name":"standard_model", "color":r.kGreen+2}, sources = ["qcd_py6","t#bar{t}","w_jets_fj_mg.tw.nvr"], keepSources = True)
        #for ss in filter(lambda ss: 'tt_tauola' in ss['name'],org.samples) : org.drop(ss['name'])

        orgpdf = copy.deepcopy(org)
        orgpdf.scale( toPdf = True )
        org.scale( lumiToUseInAbsenceOfData = 1.1e3 )

        names = [ss["name"] for ss in org.samples]
        kwargs = {"detailedCalculables": False,
                  "blackList":["lumiHisto","xsHisto","nJobsHisto"],
                  "samplesForRatios" : next(iter(filter(lambda x: x[0] in names and x[1] in names, [("Data 2011","standard_model")])), ("","")),
                  "sampleLabelsForRatios" : ("data","s.m."),
                  "detailedCalculables" : True,
                  "rowColors" : self.rowcolors,
                  }
        
        plotter.plotter(org, psFileName = self.psFileName(org.tag+"_log"),  doLog = True, pegMinimum = 0.01, **kwargs ).plotAll()
        plotter.plotter(org, psFileName = self.psFileName(org.tag+"_nolog"), doLog = False, **kwargs ).plotAll()

        kwargs["samplesForRatios"] = ("","")
        kwargs["dependence2D"] = True
        plotter.plotter(orgpdf, psFileName = self.psFileName(org.tag+"_pdf"), doLog = False, **kwargs ).plotAll()
Пример #10
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    def conclude(self,pars) :
        org = self.organizer(pars)
        org.scale(toPdf=True)

        self.signalChi2(org,("tt_tauola_fj_mg.wTopAsymN30","tt_tauola_fj_mg.wTopAsymP30"), org.keysMatching(["genTopBeta",
                                                                                                             "genTopDeltaAbsYttbar",
                                                                                                             "genTopTrue",
                                                                                                             "genTopMez"
                                                                                                             ]))
        from core import plotter
        pl = plotter.plotter(org,
                             psFileName = self.psFileName(org.tag),
                             doLog = False,
                             pegMinimum = 0.1,
                             blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                             ).plotAll()
Пример #11
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    def meldQCDpartitions(self) :
        samples = {"top_muon_pf" : ["qcd_py6fjmu"],
                   "Wlv_muon_pf" : [],
                   "QCD_muon_pf" : ["qcd_py6fjmu","SingleMu"]}
        organizers = [organizer.organizer(tag, [s for s in self.sampleSpecs(tag) if any(item in s['name'] for item in samples[tag])])
                      for tag in [p['tag'] for p in self.readyConfs]]
        if not organizers : return
        for org in organizers :
            org.mergeSamples(targetSpec = {"name":"Data 2011", "color":r.kBlack, "markerStyle":20}, allWithPrefix="SingleMu")
            org.mergeSamples(targetSpec = {"name":"qcd_py6mu", "color":r.kRed if "QCD" in org.tag else r.kBlue, "markerStyle": 22}, allWithPrefix="qcd_py6fjmu")
            org.scale(toPdf=True)

        melded = organizer.organizer.meld("qcdPartitions",filter(lambda o: o.samples, organizers))
        pl = plotter.plotter(melded,
                             psFileName = self.psFileName(melded.tag),
                             doLog = False,
                             blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                             ).plotAll()
Пример #12
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 def makeStandardPlots(self, org) :
     #plot
     pl = plotter.plotter(org,
                          psFileName = self.psFileName(org.tag),
                          samplesForRatios = ("2011 Data","Standard Model "),
                          sampleLabelsForRatios = ("data","s.m."),
                          printRatios = True,
                          showStatBox = not self.ra1Cosmetics(),
                          rowColors = [r.kBlack, r.kViolet+4],
                          #whiteList = ["lowestUnPrescaledTrigger"],
                          #doLog = False,
                          #compactOutput = True,
                          #noSci = True,
                          #latexYieldTable = True,
                          linYAfter = ("variableGreaterFilter", "xcak5JetAlphaTEtPat>=0.550 "),
                          pegMinimum = 0.1,
                          blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                          )
     pl.plotAll()
Пример #13
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 def makeStandardPlots(self, org) :
     #plot
     pl = plotter.plotter(org,
                          psFileName = self.psFileName(org.tag),
                          samplesForRatios = ("2011 Data","standard_model" if not self.ra1Cosmetics() else "Standard Model "),
                          sampleLabelsForRatios = ("data","s.m."),
                          #samplesForRatios = ("calo_325_scaled.xcak5JetnJetsWeightPat", "calo_325_scaled"),
                          #sampleLabelsForRatios = ("3jet","Njet"),
                          showStatBox = not self.ra1Cosmetics(),
                          #whiteList = ["lowestUnPrescaledTrigger"],
                          #doLog = False,
                          #compactOutput = True,
                          #noSci = True,
                          #latexYieldTable = True,
                          linYAfter = ("variableGreaterFilter", "xcak5JetAlphaTEtPat>=0.550 "),
                          pegMinimum = 0.1,
                          blackList = ["lumiHisto","xsHisto","nJobsHisto"],
                          )
     pl.plotAll()
Пример #14
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    def conclude(self,pars) :
        import re
        org = self.organizer(pars)
        black = sum([[hist for hist in step if re.match(r"HLT_Mu\d*_v\d*_p\d*",hist)] for step in org.steps],[])

        
        args = {"blackList":["lumiHisto","xsHisto","nJobsHisto"] + black,
                "detailedCalculables" : True }

        from core.plotter import plotter
        plotter(org, psFileName = self.psFileName(org.tag+"unmerged"), **args ).plotAll()
        plotter(org, psFileName = self.psFileName(org.tag+"unmerged_nolog"), doLog=False, **args ).plotAll()
        org.mergeSamples(targetSpec = {"name":"SingleMu","color":r.kRed}, allWithPrefix="SingleMu")
        plotter(org, psFileName = self.psFileName(org.tag), **args ).plotAll()
        self.printPrescales(org)
Пример #15
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    def makeStandardPlots(self, org) :
        names = [ss["name"] for ss in org.samples]
        samplesForRatios = filter(lambda x: x[0] in names and x[1] in names,
                                  [("2011 Data","standard_model_nVtx"),
                                   (".2011 Data",".standard_model_nVtx"),
                                   ("g.2011 Data","g.standard_model_nVtx"),
                                   ("2011 Data","standard_model"),
                                   ("2011 Data","standard_model_py6"),
                                   ("2010 Data","sm_2010")])

        #plot all
        pl = plotter.plotter(org,
                             psFileName = self.psFileName(org.tag),
                             sampleLabelsForRatios = ("data","s.m."),
                             samplesForRatios = next(iter(samplesForRatios), ("","")),
                             blackList = ["lumiHisto","xsHisto","nJobsHisto",
                                          "deltaRGenReco",
                                          "photonMothergenPt", "photonMotherrecoPt", "photonMothermht",
                                          "quarkMothergenPt",  "quarkMotherrecoPt",  "quarkMothermht",
                                          "otherMothergenPt",  "otherMotherrecoPt",  "otherMothermht",
                                          "nGenPhotonsStatus1Photon","photonEtaStatus1Photon","photonPtStatus1Photon",
                                          "photonPhiVsEtaStatus1Photon", "photonIsoStatus1Photon",
                                          "nJetsStatus1Photon", "jetHtStatus1Photon",
                                          "nJetsPlusnPhotonsStatus1Photon", "jetHtPlusPhotonHtStatus1Photon",
                                          ],
                             doLog = False,
                             #latexYieldTable = True,
                             rowColors = [r.kBlack, r.kViolet+4],
                             showErrorsOnDataYields = False,
                             #whiteList = ["xcak5JetIndicesPat",
                             #             #"photonPat1Pt",
                             #             #"photonPat1mhtVsPhotonPt",
                             #             "xcak5JetAlphaTFewBinsPat",
                             #             "xcak5JetAlphaTRoughPat",
                             #             "xcak5JetAlphaTWithPhoton1PtRatherThanMhtPat",
                             #             ],
                             )
        pl.plotAll()
Пример #16
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    def meldNorm(self) :
        meldSamples = {"top_muon_pf" : ["SingleMu","P00","NonQQbar","w_jets"],
                       #"Wlv_muon_pf" : ["w_jets"],
                       "QCD_muon_pf" : ["SingleMu"]}

        organizers = [organizer.organizer(tag, [s for s in self.sampleSpecs(tag) if any(item in s['name'] for item in meldSamples[tag])])
                      for tag in [p['tag'] for p in self.readyConfs if p["tag"] in meldSamples]]
        if not organizers : return
        for org in organizers :
            org.mergeSamples(targetSpec = {"name":"t#bar{t}", "color":r.kViolet}, sources=["tt_tauola_fj.wNonQQbar.nvr","tt_tauola_fj.wTopAsymP00.nvr"])
            org.mergeSamples(targetSpec = {"name":"w_jets", "color":r.kRed}, allWithPrefix = "w_jets")
            org.mergeSamples(targetSpec = {"name":"Data 2011",
                                           "color":r.kBlue if "qcd_" in org.tag else r.kBlack,
                                           "markerStyle":(20 if "top" in org.tag else 1)}, allWithPrefix="SingleMu")
            
        if True :
            templates = []
            dist = "TriDiscriminant"
            for org in organizers :
                before = next(org.indicesOfStep("label","selection complete"))
                distTup = org.steps[next(iter(filter(lambda i: before<i, org.indicesOfStepsWithKey(dist))))][dist]
                for ss,hist in zip(org.samples,distTup) :            
                    contents = [hist.GetBinContent(i) for i in range(hist.GetNbinsX()+2)]
                    if "top" in org.tag and ss["name"] is "Data 2011":  signal = contents
                    else : templates.append(contents)
                    print org.tag, ss["name"]
            from core import fractions
            cs = fractions.componentSolver(signal, templates, 1e4)
            with open("measuredFractions.txt","w") as file : print >> file, cs
            stuff = fractions.drawComponentSolver(cs)
            stuff[0].Print("measuredFractions.eps")
        
        for org in organizers : org.scale(toPdf=True)
            
        melded = organizer.organizer.meld(organizers = organizers)
        pl = plotter.plotter(melded, psFileName = self.psFileName(melded.tag),
                             doLog = False, blackList = ["lumiHisto","xsHisto","nJobsHisto"] ).plotAll()
Пример #17
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 def conclude(self, conf) :
     org = self.organizer(conf)
     pl = plotter.plotter(org, psFileName = self.psFileName(org.tag), blackList = ["lumiHisto","xsHisto","nJobsHisto"])
     pl.plotAll()
Пример #18
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 def makeIndividualPlots(self, org) :
     #plot all
     pl = plotter.plotter(org,
                          psFileName = self.psFileName(org.tag),
                          showStatBox = False,
                          doLog = True,
                          pegMinimum = 0.1,                             
                          anMode = True,
                          )
     pl.individualPlots(plotSpecs = [{"plotName":"xcak5JetAlphaTRoughPat",
                                      "stepName" :"alphaHistogrammer",
                                      "stepDesc" :"xcak5JetPat",
                                      "newTitle":";#alpha_{T};events / bin",
                                      "legendCoords": (0.55, 0.60, 0.85, 0.90),
                                      "stampCoords": (0.75, 0.55)
                                      },
                                     {"plotName":"jetMultiplicity",
                                      "stepName":"singleJetHistogrammer",
                                      "stepDesc":"xcak5JetPat through index 2",
                                      "newTitle":";N_{jets};events / bin",
                                      "legendCoords": (0.7, 0.7, 0.92, 0.92),
                                      "stampCoords": (0.5, 0.28),
                                      },
                                     {"plotName":"xcak5JetHtPat",
                                      "stepName":"cleanJetHtMhtHistogrammer",
                                      "stepDesc":"xcak5JetPat",
                                      "newTitle":";H_{T} (GeV);events / bin",
                                      "legendCoords": (0.6, 0.60, 0.92, 0.92),
                                      "stampCoords": (0.45, 0.88)
                                     },
                                     ##after alphaT
                                     {"plotName":"xcak5JetDeltaPhiStarPat",
                                      "stepName":"histogrammer",
                                      "stepDesc" :"(lambda x:x[0][0])(xcak5JetDeltaPhiStarPat)",
                                      "index" : -1,
                                      "newTitle":";#Delta#phi*;events / bin",
                                      "legendCoords": (0.6, 0.6, 0.92, 0.92),
                                      "stampCoords": (0.33, 0.88),
                                      },
                                     {"plotName":"xcak5JetHtPlusMhtRoughPat",
                                      "stepName":"cleanJetHtMhtHistogrammer",
                                      "stepDesc":"xcak5JetPat",
                                      "index":-1,
                                      "newTitle":";M_{eff} (GeV);events / bin",
                                      "legendCoords": (0.7, 0.7, 0.92, 0.92),
                                      "stampCoords": (0.75, 0.4),
                                      },
                                     {"plotName":"xcak5JetIndicesPat",
                                      "stepName":"histogrammer",
                                      "stepDesc" :"(lambda x:len(x))(xcak5JetIndicesPat)",
                                      "index" : -1,
                                      "newTitle":";N_{jets};events / bin",
                                      "legendCoords": (0.6, 0.6, 0.92, 0.92),
                                      "stampCoords": (0.6, 0.38),
                                      }
                                     ],
                        newSampleNames = None,
                        #newSampleNames = {"qcd_mg_nVtx": "Madgraph QCD",
                        #                  "g_jets_mg_nVtx": "Madgraph #gamma + jets",
                        #                  "2011 Data": "Data",
                        #                  "standard_model_nVtx": "Standard Model",
                        #                  },
                        preliminary = True,
                        )