def main():
inputs = effectiveModel.getInputs(options.input)
for i in inputs:
i[2] = unit # This function has to be pickle'able. Lambda functions are not allowed.
x = [bins[0], plotRange[0], plotRange[2]]
y = [bins[1], plotRange[1], plotRange[3]]
h = ROOT.TH2F(
"muTmuW",
"(#mu^{f}_{ggF+ttH},#mu^{f}_{VBF+VH}) plane;#mu^{f}_{ggF+ttH};#mu^{f}_{VBF+VH};-2 ln #Lambda",
x[0], x[1], x[2], y[0], y[1], y[2])
npHistograms = {}
effectiveModel.fillHist(h,
x,
y,
inputs,
options,
npHistograms=npHistograms)
PyROOTUtils.subtractMinFromHist(h)
outF = effectiveModel.outFileName(options.output, options)
fOut = ROOT.TFile.Open(outF, "RECREATE")
h.Write()
for npH in npHistograms.values():
npH.Write()
fOut.Close()
print("Output written to: " + outF)
def main():
f = ROOT.TFile.Open(options.input, "READ")
w = f.Get(options.wsName)
mc = w.obj(options.mcName)
data = w.data(options.dataName)
# prepare model
w.var("mu").setVal(1.0)
w.var("mu").setConstant()
# get nll
nll = getNll(mc.GetPdf(), data)
kGam = [100, plotRange[0], plotRange[2]]
kGlu = [100, plotRange[1], plotRange[3]]
h = ROOT.TH2F(
"kGlukGamma",
"Couplings in (k_{g},k_{#gamma});#kappa_{#gamma};#kappa_{g};-2 ln #Lambda",
kGam[0], kGam[1], kGam[2], kGlu[0], kGlu[1], kGlu[2])
for x in range(kGam[0]):
kGamVal = kGam[1] + (x + 0.5) * (kGam[2] - kGam[1]) / kGam[0]
print("Progress: %.0f%%" % (100.0 * x / kGam[0]))
for y in range(kGlu[0]):
kGluVal = kGlu[1] + (y + 0.5) * (kGlu[2] - kGlu[1]) / kGlu[0]
muTmuW2ph = kGlukGamma.map_2ph(kGamVal, kGluVal)
w.var("muT_2ph").setVal(muTmuW2ph[0])
w.var("muW_2ph").setVal(muTmuW2ph[1])
muTmuW4l = kGlukGamma.map_4l(kGamVal, kGluVal)
w.var("muT_4l").setVal(muTmuW4l[0])
w.var("muW_4l").setVal(muTmuW4l[1])
muTmuWlvlv = kGlukGamma.map_lvlv(kGamVal, kGluVal)
w.var("muT_lvlv").setVal(muTmuWlvlv[0])
w.var("muW_lvlv").setVal(muTmuWlvlv[1])
minimize(nll)
h.SetBinContent(h.FindBin(kGamVal, kGluVal), 2.0 * nll.getVal())
PyROOTUtils.subtractMinFromHist(h)
fOut = ROOT.TFile.Open(options.output, "RECREATE")
h.Write()
fOut.Close()
print("Output written to: " + options.output)
def main():
f = ROOT.TFile.Open( options.input, "READ" )
w = f.Get( options.wsName )
mc = w.obj( options.mcName )
data = w.data( options.dataName )
# prepare model
w.var("mu").setVal( 1.0 )
w.var("mu").setConstant()
# get nll
nll = getNll( mc.GetPdf(), data )
kGam = [100, plotRange[0], plotRange[2]]
kGlu = [100, plotRange[1], plotRange[3]]
h = ROOT.TH2F( "kGlukGamma", "Couplings in (k_{g},k_{#gamma});#kappa_{#gamma};#kappa_{g};-2 ln #Lambda", kGam[0], kGam[1], kGam[2], kGlu[0], kGlu[1], kGlu[2] )
for x in range( kGam[0] ):
kGamVal = kGam[1] + (x+0.5)*(kGam[2]-kGam[1]) / kGam[0]
print( "Progress: %.0f%%" % (100.0*x/kGam[0]) )
for y in range( kGlu[0] ):
kGluVal = kGlu[1] + (y+0.5)*(kGlu[2]-kGlu[1]) / kGlu[0]
muTmuW2ph = kGlukGamma.map_2ph( kGamVal, kGluVal )
w.var("muT_2ph").setVal( muTmuW2ph[0] )
w.var("muW_2ph").setVal( muTmuW2ph[1] )
muTmuW4l = kGlukGamma.map_4l( kGamVal, kGluVal )
w.var("muT_4l").setVal( muTmuW4l[0] )
w.var("muW_4l").setVal( muTmuW4l[1] )
muTmuWlvlv = kGlukGamma.map_lvlv( kGamVal, kGluVal )
w.var("muT_lvlv").setVal( muTmuWlvlv[0] )
w.var("muW_lvlv").setVal( muTmuWlvlv[1] )
minimize( nll )
h.SetBinContent( h.FindBin( kGamVal, kGluVal ), 2.0*nll.getVal() )
PyROOTUtils.subtractMinFromHist( h )
fOut = ROOT.TFile.Open( options.output, "RECREATE" )
h.Write()
fOut.Close()
print( "Output written to: "+options.output )
def main():
inputs = effectiveModel.getInputs( options.input )
for i in inputs: i[2] = unit # This function has to be pickle'able. Lambda functions are not allowed.
x = [bins[0], plotRange[0], plotRange[2]]
y = [bins[1], plotRange[1], plotRange[3]]
h = ROOT.TH2F( "muTmuW", "(#mu^{f}_{ggF+ttH},#mu^{f}_{VBF+VH}) plane;#mu^{f}_{ggF+ttH};#mu^{f}_{VBF+VH};-2 ln #Lambda", x[0], x[1], x[2], y[0], y[1], y[2] )
npHistograms = {}
effectiveModel.fillHist( h,x,y,inputs, options, npHistograms=npHistograms )
PyROOTUtils.subtractMinFromHist( h )
outF = effectiveModel.outFileName( options.output, options )
fOut = ROOT.TFile.Open( outF, "RECREATE" )
h.Write()
for npH in npHistograms.values(): npH.Write()
fOut.Close()
print( "Output written to: "+outF )
def main():
inputs = effectiveModel.getInputs( options.input )
for i in inputs:
if "2ph" in i[2]: i[2] = map_2ph
elif "4l" in i[2]: i[2] = map_4l
elif "lvlv" in i[2]: i[2] = map_lvlv
else:
print( "WARNING: Didn't find functional replacement for "+i[2] )
kGam = [bins[0], plotRange[0], plotRange[2]]
kGlu = [bins[1], plotRange[1], plotRange[3]]
h = ROOT.TH2F( "kGlukGamma", "Couplings in (k_{g},k_{#gamma});#kappa_{#gamma};#kappa_{g};-2 ln #Lambda", kGam[0], kGam[1], kGam[2], kGlu[0], kGlu[1], kGlu[2] )
npHistograms = {}
effectiveModel.fillHist( h,kGam,kGlu,inputs, options, npHistograms=npHistograms )
PyROOTUtils.subtractMinFromHist( h )
outF = effectiveModel.outFileName( options.output, options )
fOut = ROOT.TFile.Open( outF, "RECREATE" )
h.Write()
for npH in npHistograms.values(): npH.Write()
fOut.Close()
print( "Output written to: "+outF )
