def latexfitresults( filename, namemap, region='3jL', sample='', resultName="RooExpandedFitResult_afterFit", dataname='obsData', doAsym=True):
"""
Method-1: set all parameters constant, except for the one you're interested in,
calculate the systematic/error propagated due to that parameter
@param filename The filename containing afterFit workspace
@param namemap Defines whether any systematics need to be grouped in calculation (by default not defined, hence each parameter gets used one by one)
@param resultname The name of fit result (typically='RooExpandedFitResult_afterFit' or 'RooExpandedFitResult_beforeFit'
@param region The region to be used for systematics breakdown calculation
@param sample The sample to be used insted of total pdf (default='' not defined, hence total pdf used)
@param dataname The name of dataset (default='obsData')
@param doAsym Calculates asymmetric errors taken from MINOS (default=True)
"""
"""
pick up workspace from file
"""
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename,workspacename)
if w==None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
"""
pick up RooExpandedFitResult from workspace with name resultName (either before or after fit)
"""
result = w.obj(resultName)
if result==None:
print "ERROR : Cannot open fit result ", resultName
sys.exit(1)
"""
load workspace snapshot related to resultName (=set all parameters to values after fit)
"""
snapshot = 'snapshot_paramsVals_' + resultName
w.loadSnapshot(snapshot)
"""
pick up dataset from workspace
"""
data_set = w.data(dataname)
if data_set==None:
print "ERROR : Cannot open dataset : ", "data_set"
sys.exit(1)
"""
pick up channel category (RooCategory) from workspace
"""
regionCat = w.obj("channelCat")
data_set.table(regionCat).Print("v");
"""
find full (long) name list of region (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
"""
regionFullName = Util.GetFullRegionName(regionCat, region);
"""
set a boolean whether we're looking at a sample or the full (multi-sample) pdf/model
"""
chosenSample = False
if sample is not '':
chosenSample = True
"""
define regSys set, for all names/numbers to be saved in
"""
regSys = {}
"""
define channelCat call for this region and reduce the dataset to this category/region
"""
regionCatStr = 'channelCat==channelCat::' + regionFullName.Data()
dataRegion = data_set.reduce(regionCatStr)
"""
retrieve and save number of observed (=data) events in region
"""
nobsRegion = 0.
if dataRegion:
nobsRegion = dataRegion.sumEntries()
else:
print " ERROR : dataset-category dataRegion not found"
"""
if looking at a sample, there is no equivalent N_obs (only for the full model)
"""
if chosenSample:
regSys['sqrtnobsa'] = 0.
else:
regSys['sqrtnobsa'] = TMath.Sqrt(nobsRegion)
"""
get the pdf for the total model or just for the sample in region
"""
if chosenSample:
pdfInRegion=getPdfInRegions(w,sample,region)
else:
rawPdfInRegion = Util.GetRegionPdf(w, region)
varInRegion = Util.GetRegionVar(w, region)
prodList = rawPdfInRegion.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varInRegion));
pdfInRegion = rrspdfInt
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
if not pdfInRegion:
if chosenSample:
print " \n Warning, could not find pdf in region = ",region, " for sample = ",sample
else:
print " \n Warning, could not find pdf in region = ",region
"""
calculate fitted pdf number of events and full error
"""
nFittedInRegion=pdfInRegion.getVal()
regSys['sqrtnfitted'] = TMath.Sqrt(nFittedInRegion)
regSys['nfitted'] = nFittedInRegion
pdfFittedErrInRegion = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['totsyserr'] = pdfFittedErrInRegion
"""
calculate error per (floating) parameter in fitresult
get a list of floating parameters to loop over
"""
fpf = result.floatParsFinal()
"""
set all floating parameters constant
"""
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
"""
if several systematatic/parameters are pre-defined in namemap, they will be floated together
or in other words, one will get the error due to all pre-defined systematics
"""
"""
else, float each parameter one by one and calculate the error due to it
"""
if len(namemap)>0:
for key in namemap.keys():
print namemap[key]
for parname in namemap[key]:
par = w.var(parname)
par.setConstant(False)
pass
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_'+key] = sysError
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
pass
else:
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant(False)
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_'+parname] = sysError
par.setConstant()
return regSys
def latexfitresults(filename,regionList,sampleList,exactRegionNames=False,dataname='obsData',showSum=False, doAsym=True, blinded=False):
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename,'w')
if w==None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
resultAfterFit = w.obj('RooExpandedFitResult_afterFit')
if resultAfterFit==None:
print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit"
sys.exit(1)
resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit')
if resultBeforeFit==None:
print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit"
sys.exit(1)
data_set = w.data(dataname)
if data_set==None:
print "ERROR : Cannot open dataset : ", "data_set"+suffix
sys.exit(1)
regionCat = w.obj("channelCat")
data_set.table(regionCat).Print("v");
regionFullNameList = [ Util.GetFullRegionName(regionCat, region) for region in regionList]
print regionFullNameList
######
snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit'
w.loadSnapshot(snapshot)
if not w.loadSnapshot(snapshot):
print "ERROR : Cannot load snapshot : ", snapshot
sys.exit(1)
tablenumbers = {}
# SUM ALL REGIONS
sumName = ""
for index, reg in enumerate(regionList):
if index == 0:
sumName = reg
else:
sumName = sumName + " + " + reg
regionListWithSum = list(regionList)
if showSum:
regionListWithSum.append(sumName)
tablenumbers['names'] = regionListWithSum
regionCatList = [ 'channelCat==channelCat::' +region.Data() for region in regionFullNameList]
regionDatasetList = [data_set.reduce(regioncat) for regioncat in regionCatList]
for index, data in enumerate(regionDatasetList):
data.SetName("data_" + regionList[index])
data.SetTitle("data_" + regionList[index])
nobs_regionList = [ data.sumEntries() for data in regionDatasetList]
#SUM
sumNobs = 0.
for nobs in nobs_regionList:
sumNobs += nobs
## print " \n XXX nobs = ", nobs, " sumNobs = ", sumNobs
if showSum:
nobs_regionList.append(sumNobs)
tablenumbers['nobs'] = nobs_regionList
######
######
###### FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT
######
######
# total pdf, not splitting in components
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList]
rrspdfinRegionList = []
for index,pdf in enumerate(pdfinRegionList):
# pdf.Print("t")
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
# if "BG" in prodList[idx].GetName():
# prodList[idx].Print("t")
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]));
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
nFittedInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfFittedErrInRegionList = [ Util.GetPropagatedError(pdf, resultAfterFit, doAsym) for pdf in rrspdfinRegionList]
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition( "pdf_AllRegions_AFTER", "pdf_AllRegions_AFTER", RooArgList(pdfInAllRegions))
pdfSumInAllRegions.Print()
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultAfterFit, doAsym)
nFittedInRegionList.append(nPdfSumVal)
pdfFittedErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList
tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList
if blinded:
nobs_regionList = [ data.sumEntries() for data in regionDatasetList]
nobs_regionList[-1] = -1
tablenumbers['nobs'] = nobs_regionList
# components
for isam, sample in enumerate(sampleList):
sampleName=getName(sample)
nSampleInRegionVal = []
nSampleInRegionError = []
sampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
sampleInRegion=getPdfInRegions(w,sample,region)
#sampleInRegion = Util.GetComponent(w,sample,region,exactRegionNames)
sampleInRegionVal = 0.
sampleInRegionError = 0.
if not sampleInRegion==None:
sampleInRegion.Print()
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, doAsym)
sampleInAllRegions.add(sampleInRegion)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =",region, "\n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
if showSum:
sampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_FITTED"), (sampleName+"_AllRegions_FITTED"), RooArgList(sampleInAllRegions))
sampleSumInAllRegions.Print()
nSampleSumVal = sampleSumInAllRegions.getVal()
nSampleSumError = Util.GetPropagatedError(sampleSumInAllRegions, resultAfterFit, doAsym)
nSampleInRegionVal.append(nSampleSumVal)
nSampleInRegionError.append(nSampleSumError)
tablenumbers['Fitted_events_'+sampleName] = nSampleInRegionVal
tablenumbers['Fitted_err_'+sampleName] = nSampleInRegionError
print tablenumbers
######
######
###### FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORE__ THE FIT
######
######
# FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS BEFORE THE FIT
w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit')
# check if any of the initial scaling factors is != 1
_result = w.obj('RooExpandedFitResult_beforeFit')
_muFacs = _result.floatParsFinal()
for i in range(len(_muFacs)):
if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0:
print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (_muFacs[i].GetName(), _muFacs[i].getVal())
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList]
rrspdfinRegionList = []
for index,pdf in enumerate(pdfinRegionList):
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
prodList[idx].Print()
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
nExpInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfExpErrInRegionList = [ Util.GetPropagatedError(pdf, resultBeforeFit, doAsym) for pdf in rrspdfinRegionList]
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition( "pdf_AllRegions_BEFORE", "pdf_AllRegions_BEFORE", RooArgList(pdfInAllRegions))
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultBeforeFit, doAsym)
nExpInRegionList.append(nPdfSumVal)
pdfExpErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList
tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList
for isam, sample in enumerate(sampleList):
sampleName=getName(sample)
nMCSampleInRegionVal = []
nMCSampleInRegionError = []
MCSampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
MCSampleInRegion = getPdfInRegions(w,sample,region)
#MCSampleInRegion = Util.GetComponent(w,sample,region,exactRegionNames)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
if not MCSampleInRegion==None:
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, doAsym)
MCSampleInAllRegions.add(MCSampleInRegion)
else:
print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=",region
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
if showSum:
MCSampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_MC"), (sampleName+"_AllRegions_MC"), RooArgList(MCSampleInAllRegions))
nMCSampleSumVal = MCSampleSumInAllRegions.getVal()
nMCSampleSumError = Util.GetPropagatedError(MCSampleSumInAllRegions, resultBeforeFit, doAsym)
nMCSampleInRegionVal.append(nMCSampleSumVal)
nMCSampleInRegionError.append(nMCSampleSumError)
tablenumbers['MC_exp_events_'+sampleName] = nMCSampleInRegionVal
tablenumbers['MC_exp_err_'+sampleName] = nMCSampleInRegionError
# sorted(tablenumbers, key=lambda sample: sample[1]) # sort by age
map_listofkeys = tablenumbers.keys()
map_listofkeys.sort()
for name in map_listofkeys:
if tablenumbers.has_key(name) :
print name, ": ", tablenumbers[name]
###
return tablenumbers
def latexfitresults(filename,
namemap,
region='3jL',
sample='',
resultName="RooExpandedFitResult_afterFit",
dataname='obsData',
doAsym=True,
SRName=""):
"""
Method-1: set all parameters constant, except for the one you're interested in,
calculate the systematic/error propagated due to that parameter
@param filename The filename containing afterFit workspace
@param namemap Defines whether any systematics need to be grouped in calculation (by default not defined, hence each parameter gets used one by one)
@param resultname The name of fit result (typically='RooExpandedFitResult_afterFit' or 'RooExpandedFitResult_beforeFit'
@param region The region to be used for systematics breakdown calculation
@param sample The sample to be used insted of total pdf (default='' not defined, hence total pdf used)
@param dataname The name of dataset (default='obsData')
@param doAsym Calculates asymmetric errors taken from MINOS (default=True)
"""
"""
pick up workspace from file
"""
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename, workspacename)
if w == None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
"""
pick up RooExpandedFitResult from workspace with name resultName (either before or after fit)
"""
result = w.obj(resultName)
if result == None:
print "ERROR : Cannot open fit result ", resultName
sys.exit(1)
"""
load workspace snapshot related to resultName (=set all parameters to values after fit)
"""
snapshot = 'snapshot_paramsVals_' + resultName
w.loadSnapshot(snapshot)
"""
pick up dataset from workspace
"""
data_set = w.data(dataname)
if data_set == None:
print "ERROR : Cannot open dataset : ", "data_set"
sys.exit(1)
"""
pick up channel category (RooCategory) from workspace
"""
regionCat = w.obj("channelCat")
data_set.table(regionCat).Print("v")
"""
find full (long) name list of region (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
"""
regionFullName = Util.GetFullRegionName(regionCat, region)
"""
set a boolean whether we're looking at a sample or the full (multi-sample) pdf/model
"""
chosenSample = False
if sample is not '':
chosenSample = True
"""
define regSys set, for all names/numbers to be saved in
"""
regSys = {}
"""
define channelCat call for this region and reduce the dataset to this category/region
"""
regionCatStr = 'channelCat==channelCat::' + regionFullName.Data()
dataRegion = data_set.reduce(regionCatStr)
"""
retrieve and save number of observed (=data) events in region
"""
nobsRegion = 0.
if dataRegion:
nobsRegion = dataRegion.sumEntries()
else:
print " ERROR : dataset-category dataRegion not found"
"""
if looking at a sample, there is no equivalent N_obs (only for the full model)
"""
if chosenSample:
regSys['sqrtnobsa'] = 0.
else:
regSys['sqrtnobsa'] = TMath.Sqrt(nobsRegion)
"""
get the pdf for the total model or just for the sample in region
"""
if chosenSample:
pdfInRegion = getPdfInRegions(w, sample, region)
else:
rawPdfInRegion = Util.GetRegionPdf(w, region)
varInRegion = Util.GetRegionVar(w, region)
prodList = rawPdfInRegion.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(
RooArgSet(varInRegion))
pdfInRegion = rrspdfInt
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(
), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
if not pdfInRegion:
if chosenSample:
print " \n Warning, could not find pdf in region = ", region, " for sample = ", sample
else:
print " \n Warning, could not find pdf in region = ", region
"""
calculate fitted pdf number of events and full error
"""
nFittedInRegion = pdfInRegion.getVal()
regSys['sqrtnfitted'] = TMath.Sqrt(nFittedInRegion)
regSys['nfitted'] = nFittedInRegion
pdfFittedErrInRegion = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['totsyserr'] = pdfFittedErrInRegion
"""
MakePlots
"""
makeNicePlots(result, w, SRName)
"""
calculate error per (floating) parameter in fitresult
get a list of floating parameters to loop over
"""
fpf = result.floatParsFinal()
"""
set all floating parameters constant
"""
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
"""
if several systematatic/parameters are pre-defined in namemap, they will be floated together
or in other words, one will get the error due to all pre-defined systematics
"""
"""
else, float each parameter one by one and calculate the error due to it
"""
if len(namemap) > 0:
for key in namemap.keys():
print namemap[key]
for parname in namemap[key]:
par = w.var(parname)
par.setConstant(False)
pass
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_' + key] = sysError
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
pass
else:
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant(False)
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_' + parname] = sysError
par.setConstant()
print parname, par.getVal(), par.getError()
return regSys
def latexfitresults(filename,
regionList,
sampleList,
dataname='obsData',
showSum=False,
doAsym=True,
blinded=False,
splitBins=False):
"""
Calculate before/after-fit yields in all channels given
@param filename The filename containing afterFit workspace
@param regionList A list of regions to be considered
@param sampleList A list of samples to be considered
@param dataname The name of dataset (default='obsData')
@param showSum Calculates sum of all regions if set to true (default=False)
@param doAsym Calculates asymmetric errors taken from MINOS (default=True)
@param blinded Observed event count will not be shown if set to True (default=False)
@param splitBins Calculates bin-by-bin yields for all regions if set to True (default=False)
"""
"""
pick up workspace from file
"""
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename, 'w')
if w == None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
"""
pick up after-fit RooExpandedFitResult from workspace
"""
resultAfterFit = w.obj('RooExpandedFitResult_afterFit')
if resultAfterFit == None:
print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit"
sys.exit(1)
"""
pick up before-fit RooExpandedFitResult from workspace
"""
resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit')
if resultBeforeFit == None:
print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit"
sys.exit(1)
"""
pick up dataset from workspace
"""
data_set = w.data(dataname)
if data_set == None:
print "ERROR : Cannot open dataset : ", "data_set" + suffix
sys.exit(1)
"""
pick up channel category (RooCategory) from workspace
"""
regionCat = w.obj("channelCat")
if not blinded:
data_set.table(regionCat).Print("v")
"""
find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
"""
regionFullNameList = [
Util.GetFullRegionName(regionCat, region) for region in regionList
]
"""
load afterFit workspace snapshot (=set all parameters to values after fit)
"""
snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit'
w.loadSnapshot(snapshot)
if not w.loadSnapshot(snapshot):
print "ERROR : Cannot load snapshot : ", snapshot
sys.exit(1)
"""
define set, for all names/yields to be saved in
"""
tablenumbers = {}
"""
if showSum=True define names for sum of all regions and add to regionList
"""
sumName = ""
for index, reg in enumerate(regionList):
if index == 0:
sumName = reg
else:
sumName = sumName + " + " + reg
regionListWithSum = list(regionList)
if showSum:
regionListWithSum.append(sumName)
tablenumbers['names'] = regionListWithSum
"""
make a list of channelCat calls for every region
"""
regionCatList = [
'channelCat==channelCat::' + region.Data()
for region in regionFullNameList
]
"""
retrieve number of observed (=data) events per region
"""
regionDatasetList = [
data_set.reduce(regioncat) for regioncat in regionCatList
]
for index, data in enumerate(regionDatasetList):
data.SetName("data_" + regionList[index])
data.SetTitle("data_" + regionList[index])
nobs_regionList = [data.sumEntries() for data in regionDatasetList]
"""
if showSum=True calculate the total number of observed events in all regions
"""
sumNobs = 0.
for nobs in nobs_regionList:
sumNobs += nobs
if showSum:
nobs_regionList.append(sumNobs)
tablenumbers['nobs'] = nobs_regionList
"""
FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT
"""
"""
get a list of pdf's and variables per region
"""
pdfinRegionList = [Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [Util.GetRegionVar(w, region) for region in regionList]
"""
if splitBins=True get the list of Nbins, binMax and binMin; make a list of new region names for each bin
"""
varNbinsInRegionList = []
varBinLowInRegionList = []
varBinHighInRegionList = []
rangeNameBinsInRegionList = []
if splitBins:
varNbinsInRegionList = [
Util.GetRegionVar(w, region).getBinning().numBins()
for region in regionList
]
varBinLowInRegionList = [[
Util.GetRegionVar(w, region).getBinning(
(region + "binning")).binLow(ibin)
for ibin in range(0, varNbinsInRegionList[idx])
] for idx, region in enumerate(regionList)]
varBinHighInRegionList = [[
Util.GetRegionVar(w, region).getBinning(
(region + "binning")).binHigh(ibin)
for ibin in range(0, varNbinsInRegionList[idx])
] for idx, region in enumerate(regionList)]
rangeNameBinsInRegionList = [[
regionList[idx] + "_bin" + str(ibin)
for ibin in range(0, varNbinsInRegionList[idx])
] for idx, region in enumerate(regionList)]
for index, region in enumerate(regionList):
if varNbinsInRegionList[index] == 1:
print " \n YieldsTable.py: WARNING: you have called -P (= per-bin yields) but this region ", region, " has only 1 bin \n"
"""
if splitBins=True reshuffle the regionName list; each region name is followed by names of each bin (i.e. regionNameList=['SR3J','SR3J_bin1','SR3j_bin2','SR4J','SR4J_bin1'])
"""
regionListWithBins = []
if splitBins:
for index, region in enumerate(regionList):
regionListWithBins.append(region)
for ibin in range(0, varNbinsInRegionList[index]):
regionListWithBins.append(
rangeNameBinsInRegionList[index][ibin])
tablenumbers['names'] = regionListWithBins
"""
calculate number of observed(=data) events per bin
"""
nobs_regionListWithBins = []
if splitBins:
binFuncInRegionList = [
RooBinningCategory("bin_" + region, "bin_" + region,
varinRegionList[index])
for index, region in enumerate(regionList)
]
for index, data in enumerate(regionDatasetList):
data.addColumn(binFuncInRegionList[index])
if not blinded:
data.table(binFuncInRegionList[index]).Print("v")
nobs_regionListWithBins.append(data.sumEntries())
for ibin in range(0, varNbinsInRegionList[index]):
nobs_regionListWithBins.append(
(data.reduce(binFuncInRegionList[index].GetName() + "==" +
binFuncInRegionList[index].GetName() + "::" +
varinRegionList[index].GetName() + "_bin" +
str(ibin))).sumEntries())
tablenumbers['nobs'] = nobs_regionListWithBins
"""
if blinded=True, set all numbers of observed events to -1
"""
if blinded:
for index, nobs in enumerate(nobs_regionListWithBins):
nobs_regionListWithBins[index] = -1
tablenumbers['nobs'] = nobs_regionListWithBins
"""
get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
"""
rrspdfinRegionList = []
for index, pdf in enumerate(pdfinRegionList):
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(
RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
if splitBins:
origMin = varinRegionList[index].getMin()
origMax = varinRegionList[index].getMax()
for ibin in range(0, varNbinsInRegionList[index]):
rangeName = rangeNameBinsInRegionList[index][ibin]
varinRegionList[index].setRange(
rangeName, varBinLowInRegionList[index][ibin],
varBinHighInRegionList[index][ibin])
rrspdfInt = prodList[idx].createIntegral(
RooArgSet(varinRegionList[index]), rangeName)
rrspdfinRegionList.append(rrspdfInt)
varinRegionList[index].setRange(origMin, origMax)
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(
), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
"""
calculate total pdf number of fitted events and error
"""
nFittedInRegionList = [
pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)
]
pdfFittedErrInRegionList = [
Util.GetPropagatedError(pdf, resultAfterFit, doAsym)
for pdf in rrspdfinRegionList
]
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition("pdf_AllRegions_AFTER",
"pdf_AllRegions_AFTER",
RooArgList(pdfInAllRegions))
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions,
resultAfterFit, doAsym)
nFittedInRegionList.append(nPdfSumVal)
pdfFittedErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList
tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList
"""
calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
"""
for isam, sample in enumerate(sampleList):
sampleName = getName(sample)
nSampleInRegionVal = []
nSampleInRegionError = []
sampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
sampleInRegion = getPdfInRegions(w, sample, region)
sampleInRegionVal = 0.
sampleInRegionError = 0.
if not sampleInRegion == None:
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(
sampleInRegion, resultAfterFit, doAsym)
sampleInAllRegions.add(sampleInRegion)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =", region, "\n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
"""
if splitBins=True calculate numbers of fitted events plus error per bin
"""
if splitBins:
origMin = varinRegionList[ireg].getMin()
origMax = varinRegionList[ireg].getMax()
for ibin in range(0, varNbinsInRegionList[ireg]):
rangeName = rangeNameBinsInRegionList[ireg][ibin]
sampleInRegion = getPdfInRegionsWithRangeName(
w, sample, region, rangeName)
sampleInRegionVal = 0.
sampleInRegionError = 0.
if not sampleInRegion == None:
varinRegionList[ireg].setRange(
rangeName, varBinLowInRegionList[ireg][ibin],
varBinHighInRegionList[ireg][ibin])
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(
sampleInRegion, resultAfterFit, doAsym)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=", region, " bin=", ibin, " \n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
varinRegionList[ireg].setRange(origMin, origMax)
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
sampleSumInAllRegions = RooAddition(
(sampleName + "_AllRegions_FITTED"),
(sampleName + "_AllRegions_FITTED"),
RooArgList(sampleInAllRegions))
nSampleSumVal = sampleSumInAllRegions.getVal()
nSampleSumError = Util.GetPropagatedError(sampleSumInAllRegions,
resultAfterFit, doAsym)
nSampleInRegionVal.append(nSampleSumVal)
nSampleInRegionError.append(nSampleSumError)
tablenumbers['Fitted_events_' + sampleName] = nSampleInRegionVal
tablenumbers['Fitted_err_' + sampleName] = nSampleInRegionError
print "\n starting BEFORE-FIT calculations \n"
"""
FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT
"""
"""
load beforeFit workspace snapshot (=set all parameters to values before fit)
"""
w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit')
"""
check if any of the initial scaling factors is != 1
"""
_result = w.obj('RooExpandedFitResult_beforeFit')
_muFacs = _result.floatParsFinal()
for i in range(len(_muFacs)):
if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0:
print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (
_muFacs[i].GetName(), _muFacs[i].getVal())
"""
get a list of pdf's and variables per region
"""
pdfinRegionList = [Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [Util.GetRegionVar(w, region) for region in regionList]
"""
get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
"""
rrspdfinRegionList = []
for index, pdf in enumerate(pdfinRegionList):
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(
RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
if splitBins:
origMin = varinRegionList[index].getMin()
origMax = varinRegionList[index].getMax()
for ibin in range(0, varNbinsInRegionList[index]):
rangeName = rangeNameBinsInRegionList[index][ibin]
varinRegionList[index].setRange(
rangeName, varBinLowInRegionList[index][ibin],
varBinHighInRegionList[index][ibin])
rrspdfInt = prodList[idx].createIntegral(
RooArgSet(varinRegionList[index]), rangeName)
rrspdfinRegionList.append(rrspdfInt)
varinRegionList[index].setRange(origMin, origMax)
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(
), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
"""
calculate total pdf number of expected events and error
"""
nExpInRegionList = [
pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)
]
pdfExpErrInRegionList = [
Util.GetPropagatedError(pdf, resultBeforeFit, doAsym)
for pdf in rrspdfinRegionList
]
"""
if showSum=True calculate the total number of expected events in all regions
"""
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition("pdf_AllRegions_BEFORE",
"pdf_AllRegions_BEFORE",
RooArgList(pdfInAllRegions))
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions,
resultBeforeFit, doAsym)
nExpInRegionList.append(nPdfSumVal)
pdfExpErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList
tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList
"""
calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
"""
for isam, sample in enumerate(sampleList):
sampleName = getName(sample)
nMCSampleInRegionVal = []
nMCSampleInRegionError = []
MCSampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
MCSampleInRegion = getPdfInRegions(w, sample, region)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
if not MCSampleInRegion == None:
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(
MCSampleInRegion, resultBeforeFit, doAsym)
MCSampleInAllRegions.add(MCSampleInRegion)
else:
print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=", region
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
"""
if splitBins=True calculate numbers of fitted events plus error per bin
"""
if splitBins:
origMin = varinRegionList[ireg].getMin()
origMax = varinRegionList[ireg].getMax()
for ibin in range(0, varNbinsInRegionList[ireg]):
rangeName = rangeNameBinsInRegionList[ireg][ibin]
MCSampleInRegion = getPdfInRegionsWithRangeName(
w, sample, region, rangeName)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
if not MCSampleInRegion == None:
varinRegionList[ireg].setRange(
rangeName, varBinLowInRegionList[ireg][ibin],
varBinHighInRegionList[ireg][ibin])
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(
MCSampleInRegion, resultBeforeFit, doAsym)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=", region, " bin=", ibin, " \n"
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
varinRegionList[ireg].setRange(origMin, origMax)
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
MCSampleSumInAllRegions = RooAddition(
(sampleName + "_AllRegions_MC"),
(sampleName + "_AllRegions_MC"),
RooArgList(MCSampleInAllRegions))
nMCSampleSumVal = MCSampleSumInAllRegions.getVal()
nMCSampleSumError = Util.GetPropagatedError(
MCSampleSumInAllRegions, resultBeforeFit, doAsym)
nMCSampleInRegionVal.append(nMCSampleSumVal)
nMCSampleInRegionError.append(nMCSampleSumError)
tablenumbers['MC_exp_events_' + sampleName] = nMCSampleInRegionVal
tablenumbers['MC_exp_err_' + sampleName] = nMCSampleInRegionError
"""
sort the tablenumbers set
"""
map_listofkeys = tablenumbers.keys()
map_listofkeys.sort()
"""
print the sorted tablenumbers set
"""
for name in map_listofkeys:
if tablenumbers.has_key(name):
print name, ": ", tablenumbers[name]
return tablenumbers
def latexfitresults(filename,regionList,sampleList,dataname='obsData',showSum=False, doAsym=True, blinded=False, splitBins=False):
"""
Calculate before/after-fit yields in all channels given
@param filename The filename containing afterFit workspace
@param regionList A list of regions to be considered
@param sampleList A list of samples to be considered
@param dataname The name of dataset (default='obsData')
@param showSum Calculates sum of all regions if set to true (default=False)
@param doAsym Calculates asymmetric errors taken from MINOS (default=True)
@param blinded Observed event count will not be shown if set to True (default=False)
@param splitBins Calculates bin-by-bin yields for all regions if set to True (default=False)
"""
"""
pick up workspace from file
"""
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename,'w')
if w==None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
"""
pick up after-fit RooExpandedFitResult from workspace
"""
resultAfterFit = w.obj('RooExpandedFitResult_afterFit')
if resultAfterFit==None:
print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit"
sys.exit(1)
"""
pick up before-fit RooExpandedFitResult from workspace
"""
resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit')
if resultBeforeFit==None:
print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit"
sys.exit(1)
"""
pick up dataset from workspace
"""
data_set = w.data(dataname)
if data_set==None:
print "ERROR : Cannot open dataset : ", "data_set"+suffix
sys.exit(1)
"""
pick up channel category (RooCategory) from workspace
"""
regionCat = w.obj("channelCat")
if not blinded:
data_set.table(regionCat).Print("v")
"""
find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
"""
regionFullNameList = [ Util.GetFullRegionName(regionCat, region) for region in regionList]
"""
load afterFit workspace snapshot (=set all parameters to values after fit)
"""
snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit'
w.loadSnapshot(snapshot)
if not w.loadSnapshot(snapshot):
print "ERROR : Cannot load snapshot : ", snapshot
sys.exit(1)
"""
define set, for all names/yields to be saved in
"""
tablenumbers = {}
"""
if showSum=True define names for sum of all regions and add to regionList
"""
sumName = ""
for index, reg in enumerate(regionList):
if index == 0:
sumName = reg
else:
sumName = sumName + " + " + reg
regionListWithSum = list(regionList)
if showSum:
regionListWithSum.append(sumName)
tablenumbers['names'] = regionListWithSum
"""
make a list of channelCat calls for every region
"""
regionCatList = [ 'channelCat==channelCat::' +region.Data() for region in regionFullNameList]
"""
retrieve number of observed (=data) events per region
"""
print regionCatList
srindex = regionFullNameList.index("SR_cuts")
regionDatasetList = [data_set.reduce(regioncat) for regioncat in regionCatList]
for index, data in enumerate(regionDatasetList):
print "data," , data, data.GetName()
data.SetName("data_" + regionList[index])
data.SetTitle("data_" + regionList[index])
nobs_regionList = [ data.sumEntries() for data in regionDatasetList]
if blinded : nobs_regionList[srindex] = -1
"""
if showSum=True calculate the total number of observed events in all regions
"""
sumNobs = 0.
for nobs in nobs_regionList:
sumNobs += nobs
if showSum:
nobs_regionList.append(sumNobs)
tablenumbers['nobs'] = nobs_regionList
"""
FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT
"""
"""
get a list of pdf's and variables per region
"""
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList]
"""
if splitBins=True get the list of Nbins, binMax and binMin; make a list of new region names for each bin
"""
varNbinsInRegionList = []
varBinLowInRegionList = []
varBinHighInRegionList = []
rangeNameBinsInRegionList = []
if splitBins:
varNbinsInRegionList = [Util.GetRegionVar(w, region).getBinning().numBins() for region in regionList]
varBinLowInRegionList = [[Util.GetRegionVar(w, region).getBinning((region+"binning")).binLow(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)]
varBinHighInRegionList = [[Util.GetRegionVar(w, region).getBinning((region+"binning")).binHigh(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)]
rangeNameBinsInRegionList = [[regionList[idx]+"_bin"+str(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)]
for index,region in enumerate(regionList):
if varNbinsInRegionList[index]==1:
print " \n YieldsTable.py: WARNING: you have called -P (= per-bin yields) but this region ", region, " has only 1 bin \n"
"""
if splitBins=True reshuffle the regionName list; each region name is followed by names of each bin (i.e. regionNameList=['SR3J','SR3J_bin1','SR3j_bin2','SR4J','SR4J_bin1'])
"""
regionListWithBins = []
if splitBins:
for index,region in enumerate(regionList):
regionListWithBins.append(region)
for ibin in range(0,varNbinsInRegionList[index]):
regionListWithBins.append(rangeNameBinsInRegionList[index][ibin])
tablenumbers['names'] = regionListWithBins
"""
calculate number of observed(=data) events per bin
"""
nobs_regionListWithBins = []
if splitBins:
binFuncInRegionList = [RooBinningCategory("bin_"+region,"bin_"+region,varinRegionList[index]) for index,region in enumerate(regionList)]
for index, data in enumerate(regionDatasetList):
data.addColumn(binFuncInRegionList[index])
if not blinded:
data.table(binFuncInRegionList[index]).Print("v")
nobs_regionListWithBins.append(data.sumEntries())
for ibin in range(0,varNbinsInRegionList[index]):
nobs_regionListWithBins.append((data.reduce(binFuncInRegionList[index].GetName()+"=="+binFuncInRegionList[index].GetName()+"::"+varinRegionList[index].GetName()+"_bin"+str(ibin))).sumEntries())
tablenumbers['nobs'] = nobs_regionListWithBins
"""
if blinded=True, set all numbers of observed events to -1
"""
if blinded and splitBins:
for index, nobs in enumerate(nobs_regionListWithBins):
nobs_regionListWithBins[index] = -1
tablenumbers['nobs'] = nobs_regionListWithBins
"""
get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
"""
rrspdfinRegionList = []
for index,pdf in enumerate(pdfinRegionList):
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
if splitBins:
origMin = varinRegionList[index].getMin()
origMax = varinRegionList[index].getMax()
for ibin in range(0,varNbinsInRegionList[index]):
rangeName = rangeNameBinsInRegionList[index][ibin]
varinRegionList[index].setRange(rangeName,varBinLowInRegionList[index][ibin],varBinHighInRegionList[index][ibin])
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]),rangeName)
rrspdfinRegionList.append(rrspdfInt)
varinRegionList[index].setRange(origMin,origMax)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
"""
calculate total pdf number of fitted events and error
"""
nFittedInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfFittedErrInRegionList = [ Util.GetPropagatedError(pdf, resultAfterFit, doAsym) for pdf in rrspdfinRegionList]
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition( "pdf_AllRegions_AFTER", "pdf_AllRegions_AFTER", RooArgList(pdfInAllRegions))
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultAfterFit, doAsym)
nFittedInRegionList.append(nPdfSumVal)
pdfFittedErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList
tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList
"""
calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
"""
for isam, sample in enumerate(sampleList):
sampleName=getName(sample)
nSampleInRegionVal = []
nSampleInRegionError = []
sampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
sampleInRegion=getPdfInRegions(w,sample,region)
sampleInRegionVal = 0.
sampleInRegionError = 0.
if not sampleInRegion==None:
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, doAsym)
sampleInAllRegions.add(sampleInRegion)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =",region, "\n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
"""
if splitBins=True calculate numbers of fitted events plus error per bin
"""
if splitBins:
origMin = varinRegionList[ireg].getMin()
origMax = varinRegionList[ireg].getMax()
for ibin in range(0,varNbinsInRegionList[ireg]):
rangeName = rangeNameBinsInRegionList[ireg][ibin]
sampleInRegion=getPdfInRegionsWithRangeName(w,sample,region,rangeName)
sampleInRegionVal = 0.
sampleInRegionError = 0.
if not sampleInRegion==None:
varinRegionList[ireg].setRange(rangeName,varBinLowInRegionList[ireg][ibin],varBinHighInRegionList[ireg][ibin])
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, doAsym)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=",region, " bin=",ibin, " \n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
varinRegionList[ireg].setRange(origMin,origMax)
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
sampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_FITTED"), (sampleName+"_AllRegions_FITTED"), RooArgList(sampleInAllRegions))
nSampleSumVal = sampleSumInAllRegions.getVal()
nSampleSumError = Util.GetPropagatedError(sampleSumInAllRegions, resultAfterFit, doAsym)
nSampleInRegionVal.append(nSampleSumVal)
nSampleInRegionError.append(nSampleSumError)
tablenumbers['Fitted_events_'+sampleName] = nSampleInRegionVal
tablenumbers['Fitted_err_'+sampleName] = nSampleInRegionError
print "\n starting BEFORE-FIT calculations \n"
"""
FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT
"""
"""
load beforeFit workspace snapshot (=set all parameters to values before fit)
"""
w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit')
"""
check if any of the initial scaling factors is != 1
"""
_result = w.obj('RooExpandedFitResult_beforeFit')
_muFacs = _result.floatParsFinal()
for i in range(len(_muFacs)):
if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0:
print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (_muFacs[i].GetName(), _muFacs[i].getVal())
"""
get a list of pdf's and variables per region
"""
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList]
varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList]
"""
get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
"""
rrspdfinRegionList = []
for index,pdf in enumerate(pdfinRegionList):
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
if splitBins:
origMin = varinRegionList[index].getMin()
origMax = varinRegionList[index].getMax()
for ibin in range(0,varNbinsInRegionList[index]):
rangeName = rangeNameBinsInRegionList[index][ibin]
varinRegionList[index].setRange(rangeName,varBinLowInRegionList[index][ibin],varBinHighInRegionList[index][ibin])
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]),rangeName)
rrspdfinRegionList.append(rrspdfInt)
varinRegionList[index].setRange(origMin,origMax)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
"""
calculate total pdf number of expected events and error
"""
nExpInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfExpErrInRegionList = [ Util.GetPropagatedError(pdf, resultBeforeFit, doAsym) for pdf in rrspdfinRegionList]
"""
if showSum=True calculate the total number of expected events in all regions
"""
if showSum:
pdfInAllRegions = RooArgSet()
for index, pdf in enumerate(rrspdfinRegionList):
pdfInAllRegions.add(pdf)
pdfSumInAllRegions = RooAddition( "pdf_AllRegions_BEFORE", "pdf_AllRegions_BEFORE", RooArgList(pdfInAllRegions))
nPdfSumVal = pdfSumInAllRegions.getVal()
nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultBeforeFit, doAsym)
nExpInRegionList.append(nPdfSumVal)
pdfExpErrInRegionList.append(nPdfSumError)
tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList
tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList
"""
calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
"""
for isam, sample in enumerate(sampleList):
sampleName=getName(sample)
nMCSampleInRegionVal = []
nMCSampleInRegionError = []
MCSampleInAllRegions = RooArgSet()
for ireg, region in enumerate(regionList):
MCSampleInRegion = getPdfInRegions(w,sample,region)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
if not MCSampleInRegion==None:
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, doAsym)
MCSampleInAllRegions.add(MCSampleInRegion)
else:
print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=",region
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
"""
if splitBins=True calculate numbers of fitted events plus error per bin
"""
if splitBins:
origMin = varinRegionList[ireg].getMin()
origMax = varinRegionList[ireg].getMax()
for ibin in range(0,varNbinsInRegionList[ireg]):
rangeName = rangeNameBinsInRegionList[ireg][ibin]
MCSampleInRegion=getPdfInRegionsWithRangeName(w,sample,region,rangeName)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
if not MCSampleInRegion==None:
varinRegionList[ireg].setRange(rangeName,varBinLowInRegionList[ireg][ibin],varBinHighInRegionList[ireg][ibin])
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, doAsym)
else:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=",region, " bin=",ibin, " \n"
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
varinRegionList[ireg].setRange(origMin,origMax)
"""
if showSum=True calculate the total number of fitted events in all regions
"""
if showSum:
MCSampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_MC"), (sampleName+"_AllRegions_MC"), RooArgList(MCSampleInAllRegions))
nMCSampleSumVal = MCSampleSumInAllRegions.getVal()
nMCSampleSumError = Util.GetPropagatedError(MCSampleSumInAllRegions, resultBeforeFit, doAsym)
nMCSampleInRegionVal.append(nMCSampleSumVal)
nMCSampleInRegionError.append(nMCSampleSumError)
tablenumbers['MC_exp_events_'+sampleName] = nMCSampleInRegionVal
tablenumbers['MC_exp_err_'+sampleName] = nMCSampleInRegionError
"""
sort the tablenumbers set
"""
map_listofkeys = tablenumbers.keys()
map_listofkeys.sort()
"""
print the sorted tablenumbers set
"""
for name in map_listofkeys:
if tablenumbers.has_key(name) :
print name, ": ", tablenumbers[name]
return tablenumbers
def latexfitresults(filename, region, sample, resultName, dataname, doAsym):
"""
Method: set all parameters constant, except for the one you're interested in,
calculate the systematic/error propagated due to that parameter
filename: The filename containing afterFit workspace
resultname: The name of fit result (typically='RooExpandedFitResult_afterFit' or 'RooExpandedFitResult_beforeFit'
region: The region to be used for systematics breakdown calculation
sample: The sample to be used insted of total pdf (default='' not defined, hence total pdf used)
dataname: The name of dataset (default='obsData')
doAsym: Calculates asymmetric errors taken from MINOS (default=True)
"""
#pick up workspace from file
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename,workspacename)
if w is None:
print "ERROR : Cannot open workspace:", workspacename
sys.exit(1)
#pickup RooExpandedFitResult from workspace with name resultName (either before or after fit)
result = w.obj(resultName)
if result is None:
print "ERROR : Cannot open fit result", resultName
sys.exit(1)
# load workspace snapshot related to resultName (=set all parameters to values after fit)
snapshot = 'snapshot_paramsVals_' + resultName
w.loadSnapshot(snapshot)
# pick up dataset from workspace
data_set = w.data(dataname)
if data_set is None:
print "ERROR : Cannot open dataset: ", "data_set"
sys.exit(1)
#pick up channel category (RooCategory) from workspace
region_cat = w.obj("channelCat")
data_set.table(region_cat).Print("v");
# find full (long) name list of region (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
region_full_name = Util.GetFullRegionName(region_cat, region);
# set a boolean whether we're looking at a sample or the full (multi-sample) pdf/model
chosen_sample = bool(sample)
# define regSys set, for all names/numbers to be saved in
reg_sys = {}
# define channelCat call for this region and reduce the dataset to this category/region
region_cat_str = 'channelCat==channelCat::' + region_full_name.Data()
data_region = data_set.reduce(region_cat_str)
# retrieve and save number of observed (=data) events in region
nobs_region = 0.
if data_region:
nobs_region = data_region.sumEntries()
else:
print " ERROR : dataset-category dataRegion not found"
# if looking at a sample, there is no equivalent N_obs (only for the full model)
if chosen_sample:
reg_sys['sqrtnobsa'] = 0.
else:
reg_sys['sqrtnobsa'] = ROOT.TMath.Sqrt(nobs_region)
# get the pdf for the total model or just for the sample in region
if chosen_sample:
pdf_in_region = getPdfInRegions(w, sample, region)
else:
raw_pdf_in_region = Util.GetRegionPdf(w, region)
var_in_region = Util.GetRegionVar(w, region)
prod_list = raw_pdf_in_region.pdfList()
foundRRS = 0
for idx in xrange(prod_list.getSize()):
if prod_list[idx].InheritsFrom("RooRealSumPdf"):
rrspdf_int = prod_list[idx].createIntegral(ROOT.RooArgSet(var_in_region));
pdf_in_region = rrspdf_int
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
if not pdf_in_region:
if chosenSample:
print " \n Warning, could not find pdf in region = ",region, " for sample = ",sample
else:
print " \n Warning, could not find pdf in region = ",region
# calculate fitted pdf number of events and full error
n_fitted_in_region = pdf_in_region.getVal()
reg_sys['sqrtnfitted'] = ROOT.TMath.Sqrt(n_fitted_in_region)
reg_sys['nfitted'] = n_fitted_in_region
pdf_fitted_err_in_region = Util.GetPropagatedError(pdf_in_region, result, doAsym)
reg_sys['totsyserr'] = pdf_fitted_err_in_region
# calculate error per (floating) parameter in fitresult
# get a list of floating parameters to loop over
fpf = result.floatParsFinal()
# set all floating parameters constant
for idx in xrange(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant(True)
for idx in xrange(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant(False)
reg_sys['syserr_'+parname] = Util.GetPropagatedError(pdf_in_region, result, doAsym)
par.setConstant(True)
return reg_sys
def latexfitresults( filename, namemap, region='3jL', sample='', resultName="RooExpandedFitResult_afterFit", dataname='obsData', doAsym=True):
#Method-1: set all parameters constant, except for the one you're interested in,
# calculate the error propagated due to that parameter
workspacename = 'w'
w = Util.GetWorkspaceFromFile(filename,workspacename)
if w==None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
result = w.obj(resultName)
if result==None:
print "ERROR : Cannot open fit result ", resultName
sys.exit(1)
snapshot = 'snapshot_paramsVals_' + resultName
w.loadSnapshot(snapshot)
data_set = w.data(dataname)
if data_set==None:
print "ERROR : Cannot open dataset : ", "data_set"
sys.exit(1)
regionCat = w.obj("channelCat")
data_set.table(regionCat).Print("v");
regionFullName = Util.GetFullRegionName(regionCat, region);
chosenSample = False
if sample is not '':
chosenSample = True
######################################################
regSys = {}
regionCatStr = 'channelCat==channelCat::' + regionFullName.Data()
dataRegion = data_set.reduce(regionCatStr)
nobsRegion = 0.
if dataRegion:
nobsRegion = dataRegion.sumEntries()
else:
print " ERROR : dataset-category dataRegion not found"
if chosenSample:
regSys['sqrtnobsa'] = 0.
else:
regSys['sqrtnobsa'] = TMath.Sqrt(nobsRegion)
####
if chosenSample:
pdfInRegion=getPdfInRegions(w,sample,region)
else:
rawPdfInRegion = Util.GetRegionPdf(w, region)
varInRegion = Util.GetRegionVar(w, region)
prodList = rawPdfInRegion.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(RooArgSet(varInRegion));
pdfInRegion = rrspdfInt
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
if not pdfInRegion:
if chosenSample:
print " \n Warning, could not find pdf in region = ",region, " for sample = ",sample
else:
print " \n Warning, could not find pdf in region = ",region
nFittedInRegion=pdfInRegion.getVal()
regSys['sqrtnfitted'] = TMath.Sqrt(nFittedInRegion)
regSys['nfitted'] = nFittedInRegion
pdfFittedErrInRegion = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['totsyserr'] = pdfFittedErrInRegion
# calculate error per parameter on fitresult
fpf = result.floatParsFinal()
# set all floating parameters constant
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
if len(namemap)>0:
#pre-defined systematics, optionally merged
for key in namemap.keys():
print namemap[key]
#
for parname in namemap[key]:
par = w.var(parname)
par.setConstant(False)
pass
#
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_'+key] = sysError
#
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant()
pass
else:
#all systematics, one-by-one
for idx in range(fpf.getSize()):
parname = fpf[idx].GetName()
par = w.var(parname)
par.setConstant(False)
sysError = Util.GetPropagatedError(pdfInRegion, result, doAsym)
regSys['syserr_'+parname] = sysError
par.setConstant()
return regSys
def latexfitresults(filename, region_list, sample_list):
f = ROOT.TFile.Open(filename)
w = f.Get('w')
if w is None:
print "ERROR : Cannot open workspace : w"
sys.exit(1)
resultAfterFit = w.obj('RooExpandedFitResult_afterFit')
if resultAfterFit is None:
print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit"
sys.exit(1)
resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit')
if resultBeforeFit is None:
print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit"
sys.exit(1)
# pick up dataset from workspace
data_set = w.data('obsData')
# pick up channel category (RooCategory) from workspace
regionCat = w.obj("channelCat")
# if not blinded:
# data_set.table(regionCat).Print("v")
# find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
regionFullNameList = [ Util.GetFullRegionName(regionCat, region) for region in region_list ]
# load afterFit workspace snapshot (=set all parameters to values after fit)
snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit'
w.loadSnapshot(snapshot)
if not w.loadSnapshot(snapshot):
print "ERROR : Cannot load snapshot : ", snapshot
sys.exit(1)
# define set, for all names/yields to be saved in
tablenumbers = {}
tablenumbers['names'] = region_list
# make a list of channelCat calls for every region
regionCatList = [ 'channelCat==channelCat::' + region.Data() for region in regionFullNameList]
# retrieve number of observed (=data) events per region
regionDatasetList = [data_set.reduce(regioncat) for regioncat in regionCatList]
for index, data in enumerate(regionDatasetList):
data.SetName("data_" + region_list[index])
data.SetTitle("data_" + region_list[index])
nobs_regionList = [ data.sumEntries() for data in regionDatasetList]
tablenumbers['nobs'] = nobs_regionList
# FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT
#get a list of pdf's and variables per region
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in region_list]
varinRegionList = [ Util.GetRegionVar(w, region) for region in region_list]
# if splitBins=True get the list of Nbins, binMax and binMin; make a list of new region names for each bin
varNbinsInRegionList = []
varBinLowInRegionList = []
varBinHighInRegionList = []
rangeNameBinsInRegionList = []
# if blinded=True, set all numbers of observed events to -1
# if blinded:
# for index, nobs in enumerate(nobs_regionListWithBins):
# nobs_regionListWithBins[index] = -1
# tablenumbers['nobs'] = nobs_regionListWithBins
# get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
rrspdfinRegionList = []
for index, pdf in enumerate(pdfinRegionList):
if not pdf:
print "WARNING: pdf is NULL for index {0}".format(index)
continue
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(ROOT.RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
# calculate total pdf number of fitted events and error
nFittedInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfFittedErrInRegionList = [ Util.GetPropagatedError(pdf, resultAfterFit, True) for pdf in rrspdfinRegionList]
tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList
tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList
# calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
for isam, sample in enumerate(sample_list):
sampleName = getName(sample)
nSampleInRegionVal = []
nSampleInRegionError = []
sampleInAllRegions = ROOT.RooArgSet()
for ireg, region in enumerate(region_list):
sampleInRegion = getPdfInRegions(w, sample, region)
sampleInRegionVal = 0.
sampleInRegionError = 0.
try: ##if sampleInRegion is not None:
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, True)
sampleInAllRegions.add(sampleInRegion)
except:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =", region, "\n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
tablenumbers['Fitted_events_'+sampleName] = nSampleInRegionVal
tablenumbers['Fitted_err_'+sampleName] = nSampleInRegionError
# FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT
#load beforeFit workspace snapshot (=set all parameters to values before fit)
w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit')
# check if any of the initial scaling factors is != 1
_result = w.obj('RooExpandedFitResult_beforeFit')
_muFacs = _result.floatParsFinal()
for i in xrange(len(_muFacs)):
if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0:
print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (_muFacs[i].GetName(), _muFacs[i].getVal())
# get a list of pdf's and variables per region
pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in region_list]
varinRegionList = [ Util.GetRegionVar(w, region) for region in region_list]
# get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
rrspdfinRegionList = []
for index,pdf in enumerate(pdfinRegionList):
if not pdf:
print "WARNING: pdf is NULL for index {0}".format(index)
continue
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(ROOT.RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS >1 or foundRRS==0:
print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
# calculate total pdf number of expected events and error
nExpInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)]
pdfExpErrInRegionList = [ Util.GetPropagatedError(pdf, resultBeforeFit, True) for pdf in rrspdfinRegionList]
tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList
tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList
# calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
for isam, sample in enumerate(sample_list):
sampleName = getName(sample)
nMCSampleInRegionVal = []
nMCSampleInRegionError = []
MCSampleInAllRegions = ROOT.RooArgSet()
for ireg, region in enumerate(region_list):
MCSampleInRegion = getPdfInRegions(w,sample,region)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
try:
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, True)
MCSampleInAllRegions.add(MCSampleInRegion)
except:
print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=",region
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
tablenumbers['MC_exp_events_'+sampleName] = nMCSampleInRegionVal
tablenumbers['MC_exp_err_'+sampleName] = nMCSampleInRegionError
# sort the tablenumbers set
map_listofkeys = tablenumbers.keys()
map_listofkeys.sort()
return tablenumbers
def latexfitresults(filename, region_list, sample_list):
f = ROOT.TFile.Open(filename)
w = f.Get('w')
doAsym = True
if w is None:
print "ERROR : Cannot open workspace : w"
sys.exit(1)
resultAfterFit = w.obj('RooExpandedFitResult_afterFit')
if resultAfterFit is None:
print(
"ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit"
)
sys.exit(1)
resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit')
if resultBeforeFit is None:
print(
"ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit"
)
sys.exit(1)
# pick up dataset from workspace
data_set = w.data('obsData')
# pick up channel category (RooCategory) from workspace
regionCat = w.obj("channelCat")
# find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50)
regionFullNameList = [
Util.GetFullRegionName(regionCat, region) for region in region_list
]
# load afterFit workspace snapshot (=set all parameters to values after fit)
snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit'
w.loadSnapshot(snapshot)
if not w.loadSnapshot(snapshot):
print "ERROR : Cannot load snapshot : ", snapshot
sys.exit(1)
# define set, for all names/yields to be saved in
tablenumbers = dict()
tablenumbers['names'] = region_list
# make a list of channelCat calls for every region
regionCatList = [
'channelCat==channelCat::' + region.Data()
for region in regionFullNameList
]
# retrieve number of observed (=data) events per region
regionDatasetList = [
data_set.reduce(regioncat) for regioncat in regionCatList
]
for index, data in enumerate(regionDatasetList):
data.SetName("data_" + region_list[index])
data.SetTitle("data_" + region_list[index])
nobs_regionList = [data.sumEntries() for data in regionDatasetList]
tablenumbers['nobs'] = nobs_regionList
# FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT
#get a list of pdf's and variables per region
pdfinRegionList = [Util.GetRegionPdf(w, region) for region in region_list]
varinRegionList = [Util.GetRegionVar(w, region) for region in region_list]
varNbinsInRegionList = []
varBinLowInRegionList = []
varBinHighInRegionList = []
rangeNameBinsInRegionList = []
# get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
rrspdfinRegionList = []
for index, pdf in enumerate(pdfinRegionList):
if not pdf:
print "WARNING: pdf is NULL for index {0}".format(index)
continue
prodList = pdf.pdfList()
foundRRS = 0
for idx in range(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(
ROOT.RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(
), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
# calculate total pdf number of fitted events and error
nFittedInRegionList = [
pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)
]
pdfFittedErrInRegionList = [
Util.GetPropagatedError(pdf, resultAfterFit, doAsym)
for pdf in rrspdfinRegionList
]
tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList
tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList
# calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
for isam, sample in enumerate(sample_list):
sampleName = getName(sample)
nSampleInRegionVal = []
nSampleInRegionError = []
sampleInAllRegions = ROOT.RooArgSet()
for ireg, region in enumerate(region_list):
sampleInRegion = getPdfInRegions(w, sample, region)
sampleInRegionVal = 0.
sampleInRegionError = 0.
try:
sampleInRegionVal = sampleInRegion.getVal()
sampleInRegionError = Util.GetPropagatedError(
sampleInRegion, resultAfterFit, doAsym)
sampleInAllRegions.add(sampleInRegion)
except:
print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =", region, "\n"
nSampleInRegionVal.append(sampleInRegionVal)
nSampleInRegionError.append(sampleInRegionError)
tablenumbers['Fitted_events_' + sampleName] = nSampleInRegionVal
tablenumbers['Fitted_err_' + sampleName] = nSampleInRegionError
# FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT
#load beforeFit workspace snapshot (=set all parameters to values before fit)
w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit')
# check if any of the initial scaling factors is != 1
_result = w.obj('RooExpandedFitResult_beforeFit')
_muFacs = _result.floatParsFinal()
for i in xrange(len(_muFacs)):
if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0:
print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (
_muFacs[i].GetName(), _muFacs[i].getVal())
# get a list of pdf's and variables per region
pdfinRegionList = [Util.GetRegionPdf(w, region) for region in region_list]
varinRegionList = [Util.GetRegionVar(w, region) for region in region_list]
# get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples)
rrspdfinRegionList = []
for index, pdf in enumerate(pdfinRegionList):
if not pdf:
print "WARNING: pdf is NULL for index {0}".format(index)
continue
prodList = pdf.pdfList()
foundRRS = 0
for idx in xrange(prodList.getSize()):
if prodList[idx].InheritsFrom("RooRealSumPdf"):
rrspdfInt = prodList[idx].createIntegral(
ROOT.RooArgSet(varinRegionList[index]))
rrspdfinRegionList.append(rrspdfInt)
foundRRS += 1
if foundRRS > 1 or foundRRS == 0:
print " \n\n WARNING: ", pdf.GetName(
), " has ", foundRRS, " instances of RooRealSumPdf"
print pdf.GetName(), " component list:", prodList.Print("v")
# calculate total pdf number of expected events and error
nExpInRegionList = [
pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)
]
pdfExpErrInRegionList = [
Util.GetPropagatedError(pdf, resultBeforeFit, doAsym)
for pdf in rrspdfinRegionList
]
tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList
tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList
# calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf
for isam, sample in enumerate(sample_list):
sampleName = getName(sample)
nMCSampleInRegionVal = []
nMCSampleInRegionError = []
MCSampleInAllRegions = ROOT.RooArgSet()
for ireg, region in enumerate(region_list):
MCSampleInRegion = getPdfInRegions(w, sample, region)
MCSampleInRegionVal = 0.
MCSampleInRegionError = 0.
try:
MCSampleInRegionVal = MCSampleInRegion.getVal()
MCSampleInRegionError = Util.GetPropagatedError(
MCSampleInRegion, resultBeforeFit, doAsym)
MCSampleInAllRegions.add(MCSampleInRegion)
except:
print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=", region
nMCSampleInRegionVal.append(MCSampleInRegionVal)
nMCSampleInRegionError.append(MCSampleInRegionError)
tablenumbers['MC_exp_events_' + sampleName] = nMCSampleInRegionVal
tablenumbers['MC_exp_err_' + sampleName] = nMCSampleInRegionError
# sort the tablenumbers set
map_listofkeys = tablenumbers.keys()
map_listofkeys.sort()
f.Close()
return tablenumbers