def backgroundsWithRooMultiPdf():
modelGroupToUse = modelGroupForMultiPdf
pathToDir = os.path.join(backgroundfitswithroomultipdfDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
counter = 0;
for model in modelGroupToUse.models:
model.color = colors[counter]
counter += 1
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125), ws, data,
modelGroupToUse.models, settings, pathToDir=pathToDir,
groupName=modelGroupToUse.name)
def signalFitInterpolations():
pathToDir = os.path.join(singalfitinterpolationsDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
funcs.signalFitInterpolation(
category,
ws, [
(vbf120, tripleGaus120, diMuonMass120),
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
def signalFitInterpolations():
pathToDir = os.path.join(singalfitinterpolationsDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
funcs.signalFitInterpolation(category, ws,
[
(vbf120, tripleGaus120, diMuonMass120),
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
def backgroundFits():
pathToDir = os.path.join(backgroundfitsDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
for modelGroup in backgroundModelGroups:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
modelsToUse = modelGroup.models
counter = 0;
for m in modelsToUse:
m.color = colors[counter]
counter+=1
funcs.backgroundFits(
(category, diMuonMass125), ws, data, modelsToUse,
settings,
pathToDir=pathToDir,groupName=modelGroup.name)
def backgroundsWithRooMultiPdf():
modelGroupToUse = modelGroupForMultiPdf
pathToDir = os.path.join(backgroundfitswithroomultipdfDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
counter = 0
for model in modelGroupToUse.models:
model.color = colors[counter]
counter += 1
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125),
ws,
data,
modelGroupToUse.models,
settings,
pathToDir=pathToDir,
groupName=modelGroupToUse.name)
def ftest():
pathToDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(pathToDir)
fTestResults = {}
for category in categoriesToUse:
fTestResults[category] = {}
for modelGroup in orderedModelGroups:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
counter = 0;
for m in modelGroup.models:
m.color = colors[counter]
counter+=1
modelToBeUsed, values = funcs.ftestPerFamily(
(category, diMuonMass125), ws, data, modelGroup,
settings, pathToDir=pathToDir)
fTestResults[category][modelGroup.name] = values
funcs.plotFTestResults(fTestResults, pathToDir=pathToDir)
def backgroundFits():
pathToDir = os.path.join(backgroundfitsDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
for modelGroup in backgroundModelGroups:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
modelsToUse = modelGroup.models
counter = 0
for m in modelsToUse:
m.color = colors[counter]
counter += 1
funcs.backgroundFits((category, diMuonMass125),
ws,
data,
modelsToUse,
settings,
pathToDir=pathToDir,
groupName=modelGroup.name)
def signalFits():
pathToDir = os.path.join(signalfitsDir, args.outDirName)
aux.mkdir(pathToDir)
initialValuesFromTH1 = True
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
for modelToUse in [singleGaus125, doubleGaus125, tripleGaus125]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass125), ws, vbf125, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125), ws, glu125, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125), ws, wm125, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125), ws, wp125, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125), ws, zh125, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
aux.buildMassVariable(ws, **diMuonMass120)
for modelToUse in [singleGaus120, doubleGaus120, tripleGaus120]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass120), ws, vbf120, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120), ws, glu120, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120), ws, wm120, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120), ws, wp120, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120), ws, zh120, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
aux.buildMassVariable(ws, **diMuonMass130)
for modelToUse in [singleGaus130, doubleGaus130, tripleGaus130]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass130), ws, vbf130, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130), ws, glu130, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130), ws, wm130, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130), ws, wp130, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130), ws, zh130, modelToUse, settings, pathToDir=pathToDir, initialValuesFromTH1=initialValuesFromTH1)
def ftest():
pathToDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(pathToDir)
fTestResults = {}
for category in categoriesToUse:
fTestResults[category] = {}
for modelGroup in orderedModelGroups:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
counter = 0
for m in modelGroup.models:
m.color = colors[counter]
counter += 1
modelToBeUsed, values = funcs.ftestPerFamily(
(category, diMuonMass125),
ws,
data,
modelGroup,
settings,
pathToDir=pathToDir)
fTestResults[category][modelGroup.name] = values
funcs.plotFTestResults(fTestResults, pathToDir=pathToDir)
def signalFitInterpolationsWithSpline():
pathToDir = os.path.join(signalfitinterpolationswithsplineDir,
args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
print "*" * 80
print "Generating Single Gaus Splines"
print "*" * 80
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(vbf120, singleGaus120, diMuonMass120),
(vbf125, singleGaus125, diMuonMass125),
(vbf130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(glu120, singleGaus120, diMuonMass120),
(glu125, singleGaus125, diMuonMass125),
(glu130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wp120, singleGaus120, diMuonMass120),
(wp125, singleGaus125, diMuonMass125),
(wp130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wm120, singleGaus120, diMuonMass120),
(wm125, singleGaus125, diMuonMass125),
(wm130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(zh120, singleGaus120, diMuonMass120),
(zh125, singleGaus125, diMuonMass125),
(zh130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
print "*" * 80
print "Generating Double Gaus Splines"
print "*" * 80
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(vbf120, doubleGaus120, diMuonMass120),
(vbf125, doubleGaus125, diMuonMass125),
(vbf130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(glu120, doubleGaus120, diMuonMass120),
(glu125, doubleGaus125, diMuonMass125),
(glu130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wp120, doubleGaus120, diMuonMass120),
(wp125, doubleGaus125, diMuonMass125),
(wp130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wm120, doubleGaus120, diMuonMass120),
(wm125, doubleGaus125, diMuonMass125),
(wm130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(zh120, doubleGaus120, diMuonMass120),
(zh125, doubleGaus125, diMuonMass125),
(zh130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
print "*" * 80
print "Generating Triple Gaus Splines"
print "*" * 80
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(vbf120, tripleGaus120, diMuonMass120),
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(glu120, tripleGaus120, diMuonMass120),
(glu125, tripleGaus125, diMuonMass125),
(glu130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wp120, tripleGaus120, diMuonMass120),
(wp125, tripleGaus125, diMuonMass125),
(wp130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wm120, tripleGaus120, diMuonMass120),
(wm125, tripleGaus125, diMuonMass125),
(wm130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
funcs.signalFitInterpolationWithSpline(
category,
ws, [
(zh120, tripleGaus120, diMuonMass120),
(zh125, tripleGaus125, diMuonMass125),
(zh130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir)
def datacardsSingleGaus():
physGroupToUse = physGroupTest
orderedGroupsToUse = orderedGroupsTest
workspaceName = "higgs"
signalSplinesDir = os.path.join(signalfitinterpolationswithsplineDir,
args.outDirName)
backgroundsDir = os.path.join(backgroundfitswithroomultipdfDir,
args.outDirName)
datacardsDir = os.path.join(datacardsworkspacesDir, args.outDirName)
fffTestDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(signalSplinesDir)
aux.mkdir(backgroundsDir)
aux.mkdir(datacardsDir)
aux.mkdir(fffTestDir)
fTestResults = {}
for category in categoriesToUse:
fTestResults[category] = {}
workspaceFileName = "workspace__{category}__{signalModelId}.root".format(
category=names2RepsToUse[category],
signalModelId=singleGaus120.modelId)
ws = R.RooWorkspace(workspaceName)
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
#
# create the RooDataHist and import it into the Workspace here explicitly
#
fdata = R.TFile(data.pathToFile)
hdata_name = category + "/DiMuonMass"
if settings.useInputFileUF:
hdata_name = "net_histos/" + category + "_Net_Data"
hdata = fdata.Get(hdata_name)
rdata = aux.buildRooHist(
ws, hdata,
"data_obs_{category}".format(category=names2RepsToUse[category]))
getattr(ws, "import")(rdata, R.RooFit.RecycleConflictNodes())
fdata.Close()
#
# Create the Signal Models
#
print "*" * 80
print "Generating Single Gaus Splines"
print "*" * 80
vbfmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(vbf120, singleGaus120, diMuonMass120),
(vbf125, singleGaus125, diMuonMass125),
(vbf130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
glumodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(glu120, singleGaus120, diMuonMass120),
(glu125, singleGaus125, diMuonMass125),
(glu130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
wpmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wp120, singleGaus120, diMuonMass120),
(wp125, singleGaus125, diMuonMass125),
(wp130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
wmmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wm120, singleGaus120, diMuonMass120),
(wm125, singleGaus125, diMuonMass125),
(wm130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
zhmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(zh120, singleGaus120, diMuonMass120),
(zh125, singleGaus125, diMuonMass125),
(zh130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
#
# Perform the F-Test and select the proper order of the
#
selectedOrderedModels = []
for modelGroup in orderedGroupsToUse:
counter = 0
for m in modelGroup.models:
m.color = colors[counter]
counter += 1
selectedModel, values = funcs.ftestPerFamily(
(category, diMuonMass125),
ws,
data,
modelGroup,
settings,
pathToDir=fffTestDir)
if selectedModel is not None:
selectedOrderedModels.append(selectedModel)
fTestResults[category][modelGroup.name] = values
#
# Create the Background Model
#
totalModelGroup = ModelGroup(
"bkgModels", physGroupTest.models + selectedOrderedModels)
counter = 0
for model in totalModelGroup.models:
model.color = colors[counter]
counter += 1
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125),
ws,
data,
totalModelGroup.models,
settings,
pathToDir=backgroundsDir,
groupName=totalModelGroup.name)
#
# Signal and Background Models are ready and are in the Workspace
# create the datacard for this category
#
funcs.datacardAnalytic(category,
ws,
data,
[vbfmodel, glumodel, wpmodel, wmmodel, zhmodel],
ws.pdf("multipdf_{category}".format(
category=names2RepsToUse[category])),
settings,
pathToDir=datacardsDir,
workspaceFileName=workspaceFileName,
workspaceName=workspaceName,
withSystematics=args.withSystematics)
#
# save the Workspacee
#
print "*" * 80
print "*** Final RooWorkspace contents ***"
print "*" * 80
ws.Print("v")
ws.SaveAs(os.path.join(datacardsDir, workspaceFileName))
#
# plot all the F-Test Results
#
funcs.plotFTestResults(fTestResults, pathToDir=fffTestDir)
def datacardsTripleGaus():
physGroupToUse = physGroupTest # The physics derived background fit functions (non ordered)
orderedGroupsToUse = orderedGroupsTest # The ordered background fits (berenstein, sumexp, etc)
# book keeping, set up output dirs for signal, bkg, datacards, and workspaces
workspaceName = "higgs"
signalSplinesDir = os.path.join(signalfitinterpolationswithsplineDir,
args.outDirName)
backgroundsDir = os.path.join(backgroundfitswithroomultipdfDir,
args.outDirName)
datacardsDir = os.path.join(datacardsworkspacesDir, args.outDirName)
fffTestDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(signalSplinesDir)
aux.mkdir(backgroundsDir)
aux.mkdir(datacardsDir)
aux.mkdir(fffTestDir)
fTestResults = {}
# run over every category and fit the signal and background and make the workspaces
for category in categoriesToUse:
fTestResults[category] = {}
# Create workspace for category
# use the representation of the name rather than the complicated name, should set up reps in config file
workspaceFileName = "workspace__{category}__{signalModelId}.root".format(
category=names2RepsToUse[category],
signalModelId=tripleGaus120.modelId)
ws = R.RooWorkspace(workspaceName)
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
#
# Create the RooDataHist and import it into the Workspace
#
fdata = R.TFile(data.pathToFile)
hdata_name = category + "/DiMuonMass"
if settings.useInputFileUF:
hdata_name = "net_histos/" + category + "_Net_Data"
# Get data histogram from the input file for the category
# Turn it into a roo data histogram to use with roofit
hdata = fdata.Get(hdata_name)
rdata = aux.buildRooHist(
ws, hdata,
"data_obs_{category}".format(category=names2RepsToUse[category]))
getattr(ws, "import")(rdata, R.RooFit.RecycleConflictNodes())
fdata.Close()
#
# Create the Signal Models
#
print "*" * 80
print "Generating Triple Gaus Splines"
print "*" * 80
# vbf120, tripleGaus120, diMuonMass120 imported from config file
# vbf120 is of defs.MC('NoCats', inputFileUF, vbf120MC, color=R.kRed)
# vbf120MC = samp.mcMoriond2017datasets_1['VBF_120']
# tripleGaus120 = models.TripleGaus(tripleGaus120_initialValues)
# diMuonMass120 = {name: DiMuonMass, central: 120, min:110, max:160, fitmin:110, fitmax:130}
vbfmodel = funcs.signalFitInterpolationWithSpline(
category,
ws,
[
(vbf120, tripleGaus120,
diMuonMass120), # (mc sample, fit, fit window)
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
glumodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(glu120, tripleGaus120, diMuonMass120),
(glu125, tripleGaus125, diMuonMass125),
(glu130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
wpmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wp120, tripleGaus120, diMuonMass120),
(wp125, tripleGaus125, diMuonMass125),
(wp130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
wmmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(wm120, tripleGaus120, diMuonMass120),
(wm125, tripleGaus125, diMuonMass125),
(wm130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
zhmodel = funcs.signalFitInterpolationWithSpline(
category,
ws, [
(zh120, tripleGaus120, diMuonMass120),
(zh125, tripleGaus125, diMuonMass125),
(zh130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir)
#
# Perform the F-Test and select the proper order of the
#
selectedOrderedModels = [
] # ordered models for this category that passed the f-test
for modelGroup in orderedGroupsToUse: # ModelGroup has a name for the group and a list of models
counter = 0
for m in modelGroup.models:
m.color = colors[counter]
counter += 1
# return the model with the order that passes the ftest
# e.g. berenstein6 for berensten model group or sumExp3 for sum exp model group
# ftestPerFamily imported from Modeling/higgs2/generatingFunctions.py
selectedModel, values = funcs.ftestPerFamily(
(category, diMuonMass125),
ws,
data,
modelGroup,
settings,
pathToDir=fffTestDir,
unblind=args.unblind)
if selectedModel is not None:
selectedOrderedModels.append(selectedModel)
# Save ftest results for each category,modelgroup
fTestResults[category][modelGroup.name] = values
#
# Create the Background Model
#
totalModelGroup = ModelGroup(
"bkgModels", physGroupTest.models + selectedOrderedModels)
counter = 0
for model in totalModelGroup.models:
model.color = colors[counter]
counter += 1
# Multipdf for background with physics based models and the ftest passed ordered models
# !!! DOES NOT use modelGroupForMultiPdf from config file !!!
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125),
ws,
data,
totalModelGroup.models,
settings,
pathToDir=backgroundsDir,
groupName=totalModelGroup.name,
unblind=args.unblind)
#
# Signal and Background Models are ready and are in the Workspace
# create the datacard for this category
#
funcs.datacardAnalytic(category,
ws,
data,
[vbfmodel, glumodel, wpmodel, wmmodel, zhmodel],
ws.pdf("multipdf_{category}".format(
category=names2RepsToUse[category])),
settings,
pathToDir=datacardsDir,
workspaceFileName=workspaceFileName,
workspaceName=workspaceName,
withSystematics=args.withSystematics)
#
# save the Workspacee
#
ws.SaveAs(os.path.join(datacardsDir, workspaceFileName))
#
# plot all the F-test results
#
funcs.plotFTestResults(fTestResults, pathToDir=fffTestDir)
def datacardsSingleGaus():
physGroupToUse = physGroupTest
orderedGroupsToUse = orderedGroupsTest
workspaceName = "higgs"
signalSplinesDir = os.path.join(signalfitinterpolationswithsplineDir, args.outDirName)
backgroundsDir = os.path.join(backgroundfitswithroomultipdfDir, args.outDirName)
datacardsDir = os.path.join(datacardsworkspacesDir, args.outDirName)
fffTestDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(signalSplinesDir); aux.mkdir(backgroundsDir); aux.mkdir(datacardsDir)
aux.mkdir(fffTestDir)
fTestResults = {}
for category in categoriesToUse:
fTestResults[category] = {}
workspaceFileName = "workspace__{category}__{signalModelId}.root".format(
category=names2RepsToUse[category], signalModelId = singleGaus120.modelId)
ws = R.RooWorkspace(workspaceName)
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
#
# create the RooDataHist and import it into the Workspace here explicitly
#
fdata = R.TFile(data.pathToFile)
hdata_name = category + "/DiMuonMass"
if settings.useInputFileUF:
hdata_name = "net_histos/"+category+"_Net_Data"
hdata = fdata.Get(hdata_name)
rdata = aux.buildRooHist(ws, hdata,
"data_obs_{category}".format(category=names2RepsToUse[category]))
getattr(ws, "import")(rdata, R.RooFit.RecycleConflictNodes())
fdata.Close()
#
# Create the Signal Models
#
print "*"*80
print "Generating Single Gaus Splines"
print "*"*80
vbfmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(vbf120, singleGaus120, diMuonMass120),
(vbf125, singleGaus125, diMuonMass125),
(vbf130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
glumodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(glu120, singleGaus120, diMuonMass120),
(glu125, singleGaus125, diMuonMass125),
(glu130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
wpmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(wp120, singleGaus120, diMuonMass120),
(wp125, singleGaus125, diMuonMass125),
(wp130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
wmmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(wm120, singleGaus120, diMuonMass120),
(wm125, singleGaus125, diMuonMass125),
(wm130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
zhmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(zh120, singleGaus120, diMuonMass120),
(zh125, singleGaus125, diMuonMass125),
(zh130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
#
# Perform the F-Test and select the proper order of the
#
selectedOrderedModels = []
for modelGroup in orderedGroupsToUse:
counter = 0;
for m in modelGroup.models:
m.color = colors[counter]
counter+=1
selectedModel, values = funcs.ftestPerFamily(
(category, diMuonMass125), ws, data, modelGroup,
settings, pathToDir=fffTestDir)
if selectedModel is not None:
selectedOrderedModels.append(selectedModel)
fTestResults[category][modelGroup.name] = values
#
# Create the Background Model
#
totalModelGroup = ModelGroup("bkgModels",
physGroupTest.models + selectedOrderedModels)
counter = 0
for model in totalModelGroup.models:
model.color = colors[counter]
counter += 1
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125), ws, data,
totalModelGroup.models, settings,
pathToDir=backgroundsDir,
groupName=totalModelGroup.name)
#
# Signal and Background Models are ready and are in the Workspace
# create the datacard for this category
#
funcs.datacardAnalytic(category, ws, data,
[vbfmodel, glumodel, wpmodel, wmmodel, zhmodel],
ws.pdf("multipdf_{category}".format(category=names2RepsToUse[category])),
settings,
pathToDir=datacardsDir,
workspaceFileName=workspaceFileName,
workspaceName=workspaceName,
withSystematics=args.withSystematics
)
#
# save the Workspacee
#
print "*"*80
print "*** Final RooWorkspace contents ***"
print "*"*80
ws.Print("v")
ws.SaveAs(os.path.join(datacardsDir, workspaceFileName))
#
# plot all the F-Test Results
#
funcs.plotFTestResults(fTestResults, pathToDir=fffTestDir)
def datacardsTripleGaus():
physGroupToUse = physGroupTest # The physics derived background fit functions (non ordered)
orderedGroupsToUse = orderedGroupsTest # The ordered background fits (berenstein, sumexp, etc)
# book keeping, set up output dirs for signal, bkg, datacards, and workspaces
workspaceName = "higgs"
signalSplinesDir = os.path.join(signalfitinterpolationswithsplineDir, args.outDirName)
backgroundsDir = os.path.join(backgroundfitswithroomultipdfDir, args.outDirName)
datacardsDir = os.path.join(datacardsworkspacesDir, args.outDirName)
fffTestDir = os.path.join(ftestDir, args.outDirName)
aux.mkdir(signalSplinesDir); aux.mkdir(backgroundsDir); aux.mkdir(datacardsDir)
aux.mkdir(fffTestDir)
fTestResults = {}
# run over every category and fit the signal and background and make the workspaces
for category in categoriesToUse:
fTestResults[category] = {}
# Create workspace for category
# use the representation of the name rather than the complicated name, should set up reps in config file
workspaceFileName = "workspace__{category}__{signalModelId}.root".format(
category=names2RepsToUse[category], signalModelId = tripleGaus120.modelId)
ws = R.RooWorkspace(workspaceName)
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
#
# Create the RooDataHist and import it into the Workspace
#
fdata = R.TFile(data.pathToFile)
hdata_name = category + "/DiMuonMass"
if settings.useInputFileUF:
hdata_name = "net_histos/"+category+"_Net_Data"
# Get data histogram from the input file for the category
# Turn it into a roo data histogram to use with roofit
hdata = fdata.Get(hdata_name)
rdata = aux.buildRooHist(ws, hdata,
"data_obs_{category}".format(category=names2RepsToUse[category]))
getattr(ws, "import")(rdata, R.RooFit.RecycleConflictNodes())
fdata.Close()
#
# Create the Signal Models
#
print "*"*80
print "Generating Triple Gaus Splines"
print "*"*80
# vbf120, tripleGaus120, diMuonMass120 imported from config file
# vbf120 is of defs.MC('NoCats', inputFileUF, vbf120MC, color=R.kRed)
# vbf120MC = samp.mcMoriond2017datasets_1['VBF_120']
# tripleGaus120 = models.TripleGaus(tripleGaus120_initialValues)
# diMuonMass120 = {name: DiMuonMass, central: 120, min:110, max:160, fitmin:110, fitmax:130}
vbfmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(vbf120, tripleGaus120, diMuonMass120), # (mc sample, fit, fit window)
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
glumodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(glu120, tripleGaus120, diMuonMass120),
(glu125, tripleGaus125, diMuonMass125),
(glu130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
wpmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(wp120, tripleGaus120, diMuonMass120),
(wp125, tripleGaus125, diMuonMass125),
(wp130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
wmmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(wm120, tripleGaus120, diMuonMass120),
(wm125, tripleGaus125, diMuonMass125),
(wm130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
zhmodel = funcs.signalFitInterpolationWithSpline(category, ws,
[
(zh120, tripleGaus120, diMuonMass120),
(zh125, tripleGaus125, diMuonMass125),
(zh130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=signalSplinesDir
)
#
# Perform the F-Test and select the proper order of the
#
selectedOrderedModels = [] # ordered models for this category that passed the f-test
for modelGroup in orderedGroupsToUse: # ModelGroup has a name for the group and a list of models
counter = 0;
for m in modelGroup.models:
m.color = colors[counter]
counter+=1
# return the model with the order that passes the ftest
# e.g. berenstein6 for berensten model group or sumExp3 for sum exp model group
# ftestPerFamily imported from Modeling/higgs2/generatingFunctions.py
selectedModel, values = funcs.ftestPerFamily(
(category, diMuonMass125), ws, data, modelGroup,
settings, pathToDir=fffTestDir, unblind=args.unblind)
if selectedModel is not None:
selectedOrderedModels.append(selectedModel)
# Save ftest results for each category,modelgroup
fTestResults[category][modelGroup.name] = values
#
# Create the Background Model
#
totalModelGroup = ModelGroup("bkgModels",
physGroupTest.models + selectedOrderedModels)
counter = 0
for model in totalModelGroup.models:
model.color = colors[counter]
counter += 1
# Multipdf for background with physics based models and the ftest passed ordered models
# !!! DOES NOT use modelGroupForMultiPdf from config file !!!
funcs.backgroundsWithRooMultiPdf((category, diMuonMass125), ws, data,
totalModelGroup.models, settings, pathToDir=backgroundsDir,
groupName=totalModelGroup.name, unblind=args.unblind)
#
# Signal and Background Models are ready and are in the Workspace
# create the datacard for this category
#
funcs.datacardAnalytic(category, ws, data,
[vbfmodel, glumodel, wpmodel, wmmodel, zhmodel],
ws.pdf("multipdf_{category}".format(category=names2RepsToUse[category])),
settings,
pathToDir=datacardsDir,
workspaceFileName=workspaceFileName,
workspaceName=workspaceName,
withSystematics=args.withSystematics
)
#
# save the Workspacee
#
ws.SaveAs(os.path.join(datacardsDir, workspaceFileName))
#
# plot all the F-test results
#
funcs.plotFTestResults(fTestResults, pathToDir=fffTestDir)
def signalFitInterpolationsWithSpline():
pathToDir = os.path.join(signalfitinterpolationswithsplineDir, args.outDirName)
aux.mkdir(pathToDir)
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
aux.buildMH(ws, mhmin=120, mhmax=130)
print "*"*80
print "Generating Single Gaus Splines"
print "*"*80
funcs.signalFitInterpolationWithSpline(category, ws,
[
(vbf120, singleGaus120, diMuonMass120),
(vbf125, singleGaus125, diMuonMass125),
(vbf130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(glu120, singleGaus120, diMuonMass120),
(glu125, singleGaus125, diMuonMass125),
(glu130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wp120, singleGaus120, diMuonMass120),
(wp125, singleGaus125, diMuonMass125),
(wp130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wm120, singleGaus120, diMuonMass120),
(wm125, singleGaus125, diMuonMass125),
(wm130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(zh120, singleGaus120, diMuonMass120),
(zh125, singleGaus125, diMuonMass125),
(zh130, singleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
print "*"*80
print "Generating Double Gaus Splines"
print "*"*80
funcs.signalFitInterpolationWithSpline(category, ws,
[
(vbf120, doubleGaus120, diMuonMass120),
(vbf125, doubleGaus125, diMuonMass125),
(vbf130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(glu120, doubleGaus120, diMuonMass120),
(glu125, doubleGaus125, diMuonMass125),
(glu130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wp120, doubleGaus120, diMuonMass120),
(wp125, doubleGaus125, diMuonMass125),
(wp130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wm120, doubleGaus120, diMuonMass120),
(wm125, doubleGaus125, diMuonMass125),
(wm130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(zh120, doubleGaus120, diMuonMass120),
(zh125, doubleGaus125, diMuonMass125),
(zh130, doubleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
print "*"*80
print "Generating Triple Gaus Splines"
print "*"*80
funcs.signalFitInterpolationWithSpline(category, ws,
[
(vbf120, tripleGaus120, diMuonMass120),
(vbf125, tripleGaus125, diMuonMass125),
(vbf130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(glu120, tripleGaus120, diMuonMass120),
(glu125, tripleGaus125, diMuonMass125),
(glu130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wp120, tripleGaus120, diMuonMass120),
(wp125, tripleGaus125, diMuonMass125),
(wp130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(wm120, tripleGaus120, diMuonMass120),
(wm125, tripleGaus125, diMuonMass125),
(wm130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
funcs.signalFitInterpolationWithSpline(category, ws,
[
(zh120, tripleGaus120, diMuonMass120),
(zh125, tripleGaus125, diMuonMass125),
(zh130, tripleGaus130, diMuonMass130),
],
settings,
pathToDir=pathToDir
)
def signalFits():
pathToDir = os.path.join(signalfitsDir, args.outDirName)
aux.mkdir(pathToDir)
initialValuesFromTH1 = True
for category in categoriesToUse:
ws = R.RooWorkspace("higgs")
aux.buildMassVariable(ws, **diMuonMass125)
for modelToUse in [singleGaus125, doubleGaus125, tripleGaus125]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass125),
ws,
vbf125,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125),
ws,
glu125,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125),
ws,
wm125,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125),
ws,
wp125,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass125),
ws,
zh125,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
aux.buildMassVariable(ws, **diMuonMass120)
for modelToUse in [singleGaus120, doubleGaus120, tripleGaus120]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass120),
ws,
vbf120,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120),
ws,
glu120,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120),
ws,
wm120,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120),
ws,
wp120,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass120),
ws,
zh120,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
aux.buildMassVariable(ws, **diMuonMass130)
for modelToUse in [singleGaus130, doubleGaus130, tripleGaus130]:
modelToUse.color = R.kRed
funcs.signalFit((category, diMuonMass130),
ws,
vbf130,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130),
ws,
glu130,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130),
ws,
wm130,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130),
ws,
wp130,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
funcs.signalFit((category, diMuonMass130),
ws,
zh130,
modelToUse,
settings,
pathToDir=pathToDir,
initialValuesFromTH1=initialValuesFromTH1)
#
# close...
#
fdata.Close()
if __name__ == "__main__":
singleGaus = models.SingleGaus(singleGaus_initialValues)
#distributions(("NoCats", "DiMuonMass"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
#distributions(("NoCats", "DiMuonpt"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
#distributions(("NoCats", "Muonpt"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
ws = R.RooWorkspace("higgs")
ws.Print("v")
aux.buildMassVariable(ws, **diMuonMass125)
signalFit(("VBFTight", diMuonMass125),
ws,
vbf,
singleGaus,
pathToDir=signalfitsDir)
signalFit(("ggFTight", diMuonMass125),
ws,
vbf,
singleGaus,
pathToDir=signalfitsDir)
expGaus = models.ExpGaus(expGaus_defaultValues)
expGaus.color = R.kRed
bwzRedux = models.BWZRedux(bwzredux_defaultValues)
bwzRedux.color = R.kBlue
#
# close...
#
fdata.Close()
if __name__=="__main__":
singleGaus = models.SingleGaus(singleGaus_initialValues)
#distributions(("NoCats", "DiMuonMass"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
#distributions(("NoCats", "DiMuonpt"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
#distributions(("NoCats", "Muonpt"), data, [glu, vbf, wm, wp, zh], [wJetsToLNu, wwTo2L2Nu, wzTo3LNu, tt, dy])
ws = R.RooWorkspace("higgs")
ws.Print("v")
aux.buildMassVariable(ws, **diMuonMass125)
signalFit(("VBFTight", diMuonMass125), ws, vbf, singleGaus, pathToDir=signalfitsDir)
signalFit(("ggFTight", diMuonMass125), ws, vbf, singleGaus, pathToDir=signalfitsDir)
expGaus = models.ExpGaus(expGaus_defaultValues)
expGaus.color = R.kRed
bwzRedux = models.BWZRedux(bwzredux_defaultValues)
bwzRedux.color = R.kBlue
bwzGamma = models.BWZGamma(bwzgamma_defaultValues)
bwzGamma.color = R.kGreen
b5 = models.Bernstein(bernstein_defaultValues, degree=6)
b5.color = R.kYellow
sumExp5 = models.SumExponentials(sumExp_defaultValues, degree=5)
sumExp5.color = R.kViolet
backgroundFits(("VBFTight", diMuonMass125), ws, data, [expGaus, bwzRedux, bwzGamma, b5,
sumExp5], pathToDir=backgroundfitsDir, groupName="testGroup")