Example #1
0
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):

    print 'fitting', str(mass)
    plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
    #    plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
    plotter.addCorrectionFactor('genWeight', 'tree')
    #    plotter.addCorrectionFactor('xsec','tree')
    plotter.addCorrectionFactor('puWeight', 'tree')

    fitter = Fitter(['MVV', 'MJJ'])
    fitter.signal2D('model', ['MVV', 'MJJ'])
    fitter.w.var("MH").setVal(mass)
    histo = plotter.drawTH2(options.mjj + ':' + options.mvv, options.cut, "1",
                            500, 0, 6000, 100, options.minMJJ, options.maxMJJ)

    fitter.importBinnedData(histo, ['MVV', 'MJJ'], 'data')
    fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])
    fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])

    fitter.projection("model", "data", "MVV", "debugVV_" + str(mass) + ".root")
    fitter.projection("model", "data", "MJJ", "debugJJ_" + str(mass) + ".root")

    for var, graph in graphs.iteritems():
        value, error = fitter.fetch(var)
        graph.SetPoint(N, mass, value)
        graph.SetPointError(N, 0.0, error)

    N = N + 1
Example #2
0
#Now we have the samples: Sort the masses and run the fits
N = 0
for mass in sorted(samples.keys()):

    print 'fitting', str(mass)
    plotter = TreePlotter(args[0] + '/' + samples[mass] + '.root', 'tree')
    plotter.setupFromFile(args[0] + '/' + samples[mass] + '.pck')
    plotter.addCorrectionFactor('genWeight', 'tree')
    plotter.addCorrectionFactor('xsec', 'tree')
    plotter.addCorrectionFactor('puWeight', 'tree')

    fitter = Fitter(['m', 'M'])
    fitter.signal2D('model', options.boson)
    fitter.w.var("MH").setVal(mass)

    histo = plotter.drawTH2(options.mjj + ":" + options.mvv, options.cutShape,
                            "1", 500, 0, 13000, 120, 25, 165)
    histoYield = plotter.drawTH2(options.mjj + ":" + options.mvv,
                                 options.cutYield, "1", 130, 0, 13000, 100, 25,
                                 165)
    fitter.importBinnedData(histo, ['M', 'm'], 'data')
    fitter.fit('model', 'data', [ROOT.RooFit.SumW2Error(0)])

    #create the yield
    #    fitter.w.var('m').setMax(options.maxMJJ)
    #    fitter.w.var('m').setMin(options.minMJJ)
    #    integral = fitter.w.pdf("model").createIntegral(ROOT.RooArgSet(fitter.w.var("m"),fitter.w.var("M")))

    #    analysisIntegral=integral.getVal()
    #    fitter.w.var('m').setMin(25)
    #    fitter.w.var('m').setMax(165)
    #    integral = fitter.w.pdf("model").createIntegral(ROOT.RooArgSet(fitter.w.var("m"),fitter.w.var("M")))
Example #3
0
        continue

    print 'fitting',str(mass) 
    plotter=TreePlotter(args[0]+'/'+samples[mass]+'.root','tree')
    plotter.setupFromFile(args[0]+'/'+samples[mass]+'.pck')
    plotter.addCorrectionFactor('genWeight','tree')
    plotter.addCorrectionFactor('xsec','tree')
    plotter.addCorrectionFactor('puWeight','tree')
        
        
    fitter=Fitter(['m','M'])
    fitter.signal2D('model',options.boson)
    fitter.w.var("MH").setVal(mass)


    histo = plotter.drawTH2(options.mjj+":"+options.mvv,options.cutShape,"1",500,0,13000,120,60,140)
    histoYield = plotter.drawTH2(options.mjj+":"+options.mvv,options.cutYield,"1",130,0,13000,100,25,165)
    fitter.importBinnedData(histo,['M','m'],'data')
    fitter.fit('model','data',[ROOT.RooFit.SumW2Error(1)])

    #create the yield
    fitter.w.var('m').setMax(options.maxMJJ)
    fitter.w.var('m').setMin(options.minMJJ)
    integral = fitter.w.pdf("model").createIntegral(ROOT.RooArgSet(fitter.w.var("m"),fitter.w.var("M")))

    analysisIntegral=integral.getVal()
    fitter.w.var('m').setMin(40)
    fitter.w.var('m').setMax(120)
    integral = fitter.w.pdf("model").createIntegral(ROOT.RooArgSet(fitter.w.var("m"),fitter.w.var("M")))
    fitRangeIntegral=integral.getVal()