#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
#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")))
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()
