def runCombineForAsymptotic(self, quietStatus=False):
if not quietStatus:
print "Running Combine for asymptotic limits, saving results to %s" % self.dirname
f = open(os.path.join(self.dirname, "configuration.json"), "wb")
json.dump(self.configuration, f, sort_keys=True, indent=2)
f.close()
self._results = commonLimitTools.ResultContainer(
self.opts.unblinded, self.dirname)
mass_point_counter = 1
for mass in self.massPoints:
print "Processing mass point %s (point %d/%d)..." % (
mass, mass_point_counter, len(self.massPoints))
myResult = self.clsType.runCombine(mass)
if myResult.failed:
if not quietStatus:
print "Fit failed for mass point %s, skipping ..." % mass
else:
self._results.append(myResult)
if not quietStatus:
print "Processed successfully mass point %s, the result is %s" % (
mass, self._results.getResultString(mass))
mass_point_counter += 1
if not quietStatus:
print ""
print "\033[92mSummary of the results:\033[00m"
self._results.print2()
fname = self._results.saveJson()
print "Wrote results to %s" % fname
def runCombine(self, mass):
result = commonLimitTools.Result(mass)
if self.opts.limit:
if self.opts.unblinded:
self._runObservedAndExpected(result, mass)
else:
self._runBlinded(result, mass)
else:
print "Skipping limit for mass:", mass
self._runMLFit(mass)
self._runSignificance(mass)
return result
def runCombineForAsymptotic(self, quietStatus=False):
if not quietStatus:
print "Running Combine for asymptotic limits, saving results to %s" % self.dirname
f = open(os.path.join(self.dirname, "configuration.json"), "wb")
json.dump(self.configuration, f, sort_keys=True, indent=2)
f.close()
self._results = commonLimitTools.ResultContainer(
self.opts.unblinded, self.dirname)
for mass in self.massPoints:
myResult = self.clsType.runCombine(mass)
if myResult.failed:
if not quietStatus:
print "Fit failed for mass point %s, skipping ..." % mass
else:
self._results.append(myResult)
if not quietStatus:
print "Processed successfully mass point %s" % mass
if not quietStatus:
print
self._results.print2()
fname = self._results.saveJson()
print "Wrote results to %s" % fname
def analyseTaskDir(taskDir, scenarioData, scenario, massWhiteList, massPoints):
myScenario = None
myTanbeta = None
mySplit = taskDir.split("_")
myScenario = mySplit[2]
if myScenario != scenario:
# Scenario not requested, do not consider it
return
myTanbeta = mySplit[4].replace("tanbetascan", "")
myList = os.listdir(taskDir)
for item in myList:
if item.startswith("higgsCombineobs_") and item.endswith(".root"):
mySplit = item.split(".")
myMass = mySplit[len(mySplit) - 2].replace("mH", "")
if len(massWhiteList) > 0:
if not myMass in massWhiteList:
continue
if not myMass in massPoints:
massPoints.append(myMass)
# Read result
myResult = commonLimitTools.Result(myMass)
myStatus = CombineTools.parseResultFromCombineOutput(
taskDir, myResult, myMass)
if myStatus != 6: # 1 obs + 5 exp values
# Combine failed
myResult.failed = True
# Store result
myKey = tbtools.constructResultKey(myMass, myTanbeta)
if myKey in scenarioData.keys():
raise Exception(
"Duplicate results for scenario=%s mass=%s tanbeta=%s! Remove wrong ones and then rerun!"
% (myScenario, myMass, myTanbeta))
scenarioData[myKey] = {}
scenarioData[myKey]["combineResult"] = myResult
print "Result found for scenario=%s mass=%s tanbeta=%s" % (
myScenario, myMass, myTanbeta)
def main(opts):
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(opts.gridx)
style.setGridY(opts.gridy)
style.setLogX(opts.logx)
style.setLogY(opts.logy)
# Create legend and set style
histograms.createLegend.moveDefaults(dx=-0.1, dh=-0.15)
histograms.uncertaintyMode.set(histograms.Uncertainty.StatOnly)
styles.ratioLineStyle.append(styles.StyleLine(lineColor=13))
# Define some variables
nameList = []
allShapeNuisances = []
signalTable = {}
myDatacardPattern = ""
myRootfilePattern = ""
# Find out the mass points
if opts.cardPattern == None:
mySettings = limitTools.GeneralSettings(".", [])
myDatacardPattern = mySettings.getDatacardPattern(
limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = mySettings.getRootfilePattern(
limitTools.LimitProcessType.TAUJETS)
else:
myDatacardPattern = opts.cardPattern.replace("MMM", "M%s").replace(
"MM", "%s")
myRootfilePattern = opts.rootfilePattern.replace("MMM", "M%s").replace(
"MM", "%s")
# Get mass points to consider
massPoints = DatacardReader.getMassPointsForDatacardPattern(
".", myDatacardPattern)
Print(
"The following masses will be considered: %s" %
(ShellStyles.HighlightAltStyle() + ", ".join(massPoints) +
ShellStyles.NormalStyle()), True)
# For-loop: All mass points
for i, m in enumerate(massPoints, 1):
# Obtain luminosity from the datacard
myLuminosity = float(
limitTools.readLuminosityFromDatacard(".", myDatacardPattern % m))
# Do the plots
doPlot(opts, int(m), nameList, allShapeNuisances, myLuminosity,
myDatacardPattern, myRootfilePattern, signalTable)
# Print signal table
Print("Max contracted uncertainty for signal:", True)
table = []
align = "{:>15} {:>15} {:>15}"
hLine = "=" * 50
table.append(hLine)
table.append(align.format("Systematic", "Minimum", "Maximum"))
table.append(hLine)
# For-loop: All signal
for i, k in enumerate(signalTable.keys(), 1):
# Print("Key = %s" % (k), False)
minVal = "%.3f" % (signalTable[k]["min"])
maxVal = "%.3f" % (signalTable[k]["max"])
msg = align.format(k, minVal, maxVal)
table.append(msg)
table.append(hLine)
for row in table:
Print(row, False)
msg = "All results under directory %s" % (
ShellStyles.SuccessStyle() + opts.dirName + ShellStyles.NormalStyle())
Print(msg, True)
return
def main(opts):
# Check that input arguments are sufficient
if opts.settings == None:
raise Exception(
ErrorLabel() +
"Please provide input parameter file with -x or --params !")
# Load settings
print "Loading settings:", opts.settings
if not os.path.exists(opts.settings):
raise Exception(ErrorLabel() +
"Cannot find settings file '%s'!" % opts.settings)
os.system("python %s" %
opts.settings) # Catch any errors in the input datacard
config = aux.load_module(opts.settings)
checkSettings(config)
os.system("cp %s ." % opts.settings)
myFitSettingsList = config.fitSettings[:]
# Copy unfitted cards for provenance information if necessary
if not os.path.exists(_myOriginalDir):
os.mkdir(_myOriginalDir)
os.system("mv *.txt %s/." % _myOriginalDir)
os.system("mv *.root %s/." % _myOriginalDir)
print "Moved original datacards as provenance info to %s" % _myOriginalDir
else:
items = glob.glob("*.txt")
if len(items):
os.system("rm *.txt")
items = glob.glob("*.root")
if len(items):
os.system("rm *.root")
# Find datacards
myLimitSettings = limitTools.GeneralSettings(_myOriginalDir, [])
massPoints = myLimitSettings.getMassPoints(
limitTools.LimitProcessType.TAUJETS)
myDatacardPattern = myLimitSettings.getDatacardPattern(
limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = myLimitSettings.getRootfilePattern(
limitTools.LimitProcessType.TAUJETS)
# Loop over mass points
myDrawPlotsStatus = True
myShapeSensitivityTestStatus = False
myShapeSensitivityTestLabel = ""
for m in massPoints:
myHistogramCache = []
# Obtain luminosity
myLuminosity = float(
limitTools.readLuminosityFromDatacard(_myOriginalDir, "%s" %
myDatacardPattern % m))
# Obtain root file
myRootFile = ROOT.TFile.Open("%s/%s" %
(_myOriginalDir, myRootfilePattern % m))
# Obtain datacard
myOriginalCardFile = open("%s/%s" %
(_myOriginalDir, myDatacardPattern % m))
myOriginalCardLines = myOriginalCardFile.readlines()
myOriginalCardFile.close()
# Obtain column and nuisance info
myColumnNames = parseColumnNames(myOriginalCardLines)
myNuisanceInfo = parseNuisanceNames(myOriginalCardLines, myColumnNames)
myFitParNuisanceInfo = None
# Treat observation
hObs = getAndRebinRateHisto("data_obs", myRootFile,
config.finalBinning["shape"])
myPath = os.getcwd()
if "SignalInjection" in myPath:
for k in range(0, hObs.GetNbinsX() + 1):
hObs.SetBinContent(k, round(hObs.GetBinContent(k)))
for n in myNuisanceInfo:
if n["name"] == "observation":
n["value"] = hObs.Integral()
if "SHAPETEST" in myPath:
hObs.Reset()
myShapeSensitivityTestStatus = True
mySplit = myPath.split("_")
for i in range(0, len(mySplit)):
if mySplit[i] == "SHAPETEST":
myShapeSensitivityTestLabel = "_".join(
map(str, mySplit[i + 1:len(mySplit)]))
myShapeSensitivityTestLabel = myShapeSensitivityTestLabel.replace(
"UP", "Up").replace("DOWN", "Down")
myHistogramCache.append(hObs)
# Loop over column names
for c in myColumnNames:
print HighlightStyle() + "Processing column %s for mass %s" % (
c, m) + NormalStyle()
if _isSignal(c) or c in config.Blacklist:
print "... skipping fit (signal or blacklist)"
# Obtain and rebin rate histo
hRate = getAndRebinRateHisto(c, myRootFile,
config.finalBinning["shape"])
if _isSignal(c):
hRate.Scale(opts.lumiProjection)
else:
hRate.Scale(opts.lumiProjection * opts.bkgxsecProjection)
myHistogramCache.append(hRate.Clone())
# Update rate
for n in myNuisanceInfo:
if n["name"] == "rate":
n[c] = "%f" % hRate.Integral()
# Obtain and rebin nuisance histos
hNuisances = getAndRebinNuisanceHistos(
c, myRootFile, myNuisanceInfo,
config.finalBinning["shape"])
for h in hNuisances:
if _isSignal(c):
h.Scale(opts.lumiProjection)
else:
h.Scale(opts.lumiProjection * opts.bkgxsecProjection)
myHistogramCache.extend(hNuisances)
# Treat QCD shape uncertainty separately (for testing only; one should use the tail fit for QCD)
#hNuisances = getAndRebinQCDShapeNuisanceHistos(c, myRootFile, hRate, myNuisanceInfo, config.finalBinning["shape"])
#myHistogramCache.extend(hNuisances)
# Create bin-by-bin stat. histograms for fitted distribution and update the nuisance table
myStatHistograms = addBinByBinStatUncert(config,
c,
hRate,
myColumnNames,
myNuisanceInfo,
isSignal=True)
myHistogramCache.extend(myStatHistograms)
if myShapeSensitivityTestStatus and not _isSignal(c):
hObs.Add(hRate) # Add the fitted histogram
# Add the nuisance with proper binning
for h in hNuisances:
if myShapeSensitivityTestLabel in h.GetName():
hObs.Add(h)
hObs.Add(hRate, -1.0)
else:
# Not signal or blacklist, do fit
hFineBinning = myRootFile.Get(c + "_fineBinning")
for i in range(1, hFineBinning.GetNbinsX() + 1):
hFineBinning.SetBinContent(
i,
hFineBinning.GetBinContent(i) * opts.lumiProjection *
opts.bkgxsecProjection)
hFineBinning.SetBinError(
i,
hFineBinning.GetBinError(i) / math.sqrt(
opts.lumiProjection * opts.bkgxsecProjection))
if hFineBinning == None:
raise Exception(ErrorLabel() +
"Cannot find histogram '%s'!" %
(c + "_fineBinning"))
hOriginalShape = myRootFile.Get(c)
hOriginalShape.SetName(hOriginalShape.GetName() + "Original")
for i in range(1, hOriginalShape.GetNbinsX() + 1):
hOriginalShape.SetBinContent(
i,
hOriginalShape.GetBinContent(i) * opts.lumiProjection *
opts.bkgxsecProjection)
hOriginalShape.SetBinError(
i,
hOriginalShape.GetBinError(i) / math.sqrt(
opts.lumiProjection * opts.bkgxsecProjection))
if hOriginalShape == None:
raise Exception(ErrorLabel() +
"Cannot find histogram '%s'!" % (c))
# Proceed
myFitSettings = None
for s in myFitSettingsList:
if s["id"] in c:
myFitSettings = s
print "... using fitfunc: %s and range %d-%d" % (
s["fitfunc"], s["fitmin"], s["fitmax"])
if myFitSettings == None:
raise Exception(
"Could not determine fit function for column '%s'!" %
c)
myFitter = TailFitter.TailFitter(hFineBinning,
c,
myFitSettings["fitfunc"],
myFitSettings["fitmin"],
myFitSettings["fitmax"],
myFitSettings["applyFrom"],
doPlots=myDrawPlotsStatus,
luminosity=myLuminosity)
# Obtain fitted rate with final binning
myFittedRateHistograms = myFitter.getFittedRateHistogram(
hFineBinning, config.finalBinning["shape"],
myFitSettings["applyFrom"])
myHistogramCache.extend(myFittedRateHistograms)
# Update rate
for n in myNuisanceInfo:
if n["name"] == "rate":
n[c] = "%f" % myFittedRateHistograms[0].Integral()
print "... Updated rate because of fitting %.1f -> %.1f (diff=%f)" % (
hFineBinning.Integral(),
myFittedRateHistograms[0].Integral(),
myFittedRateHistograms[0].Integral() /
hFineBinning.Integral())
# Update all those shape nuisances (update histograms only, no need to touch nuisance table)
for n in myNuisanceInfo:
if n["name"] != "observation" and n[
"distribution"] == "shape" and n[c] == "1":
#print "... Updating shape nuisance '%s' tail"%n["name"]
myUpdatedNuisanceHistograms = updateNuisanceTail(
opts, hOriginalShape, myFittedRateHistograms[0],
myRootFile, "%s_%s" % (c, n["name"]))
myHistogramCache.extend(myUpdatedNuisanceHistograms)
if myShapeSensitivityTestStatus:
# Check if the nuisance histograms exist for this column
myHistoName = "%s_%s" % (
c, myShapeSensitivityTestLabel.replace(
"Up", "").replace("Down", ""))
myList = updateNuisanceTail(opts,
hOriginalShape,
myFittedRateHistograms[0],
myRootFile,
myHistoName,
skipNotFoundTest=True)
#print "DEBUG",myHistoName,len(myList)
if len(myList) > 0:
# Add the nuisance with proper binning
if "Up" in myShapeSensitivityTestLabel:
hObs.Add(myList[0])
#print "DEBUG: Added nuisance",myShapeSensitivityTestLabel,myList[0].GetName(),myList[0].Integral()
elif "Down" in myShapeSensitivityTestLabel:
hObs.Add(myList[1])
#print "DEBUG: Added nuisance",myShapeSensitivityTestLabel,myList[1].GetName(),myList[1].Integral()
else:
raise Exception() # Should not happen
else:
hObs.Add(myFittedRateHistograms[0]
) # Add the fitted histogram
#print "DEBUG: Added",myFittedRateHistograms[0].Integral()
print "Updated shape nuisance tails (rel.uncert. kept constant, but central value changed to the fitted one)"
# Obtain fit uncertainty histograms and add them to cache
(huplist, hdownlist) = myFitter.calculateVariationHistograms(
config.finalBinning["shape"], myFitSettings["applyFrom"])
# Plot if requested
if myDrawPlotsStatus:
myArray = array.array("d", config.finalBinning["shape"])
hFinalBinning = hFineBinning.Rebin(
len(myArray) - 1, "", myArray)
myFitter.makeVariationPlotDetailed(
"", hFinalBinning, myFittedRateHistograms[0], huplist,
hdownlist)
(hupTotal,
hdownTotal) = myFitter.calculateTotalVariationHistograms(
myFittedRateHistograms[0], huplist, hdownlist)
myFitter.makeVariationPlotSimple("", hFinalBinning,
myFittedRateHistograms[0],
hupTotal, hdownTotal,
s["fitmin"])
# print total uncertainty
print "*** Syst. uncert. from fit: +", 1.0 - hupTotal.Integral(
) / myFittedRateHistograms[0].Integral(
), "-", 1.0 - hdownTotal.Integral(
) / myFittedRateHistograms[0].Integral()
hFinalBinning.Delete()
# Treat blancs (norm == 0)
for i in range(0, len(huplist)):
if huplist[i].Integral() == 0:
for k in range(0, huplist[i].GetNbinsX() + 2):
huplist[i].SetBinContent(
k, myFittedRateHistograms[0].GetBinContent(k))
if hdownlist[i].Integral() == 0:
for k in range(0, hdownlist[i].GetNbinsX() + 2):
hdownlist[i].SetBinContent(
k, myFittedRateHistograms[0].GetBinContent(k))
if config.applyFitUncertaintyAsBinByBinUncertainty:
# Add fit uncertainty as bin-by-bin type uncertainty
(hupTotal,
hdownTotal) = myFitter.calculateTotalVariationHistograms(
myFittedRateHistograms[0], huplist, hdownlist)
(myBinByBinUpHistograms, myBinByBinDownHistograms
) = createBinnedFitUncertaintyHistograms(
myFittedRateHistograms[0], hupTotal, hdownTotal,
myFitSettings["applyFrom"], opts)
if not opts.noFitUncert:
myHistogramCache.extend(myBinByBinUpHistograms)
myHistogramCache.extend(myBinByBinDownHistograms)
# Add fit parameter nuisances to nuisance table
for hup in myBinByBinUpHistograms:
addNuisanceForIndividualColumn(
myColumnNames, myNuisanceInfo, c,
hup.GetTitle().replace("%s_%s" % (c, c), c))
else:
# Add fit uncertainty as nuisances parameters
if not opts.noFitUncert:
myHistogramCache.extend(huplist)
myHistogramCache.extend(hdownlist)
# Add fit parameter nuisances to nuisance table
for hup in huplist:
addNuisanceForIndividualColumn(
myColumnNames, myNuisanceInfo, c,
hup.GetTitle())
# Create bin-by-bin stat. histograms for fitted distribution and update the nuisance table
myStatHistograms = addBinByBinStatUncert(
config,
c,
myFittedRateHistograms[0],
myColumnNames,
myNuisanceInfo,
0.0,
myFitSettings["applyFrom"],
isSignal=False)
myHistogramCache.extend(myStatHistograms)
# Clear memory
hFineBinning.Delete()
hOriginalShape.Delete()
for h in myHistogramCache:
h.SetDirectory(None)
myRootFile.Close()
myDrawPlotsStatus = False
myObsIntegral = hObs.Integral()
# Print summary info
printSummaryInfo(myColumnNames, myNuisanceInfo, myHistogramCache, hObs,
m, myLuminosity, opts)
# Histogram cache contains now all root files and nuisance table is now up to date
# Create new root file and write
myRootFilename = myRootfilePattern % m
myRootFile = ROOT.TFile.Open(myRootFilename, "RECREATE")
if myRootFile == None:
raise Exception(ErrorLabel() + " Cannot open file '" +
myRootFilename + "' for output!")
for h in myHistogramCache:
h.SetDirectory(myRootFile)
myRootFile.Write()
myRootFile.Close()
# Create new datacard file and write
myOutput = createDatacardOutput(myOriginalCardLines, myColumnNames,
myNuisanceInfo, opts, myObsIntegral)
myFilename = myDatacardPattern % m
myFile = open(myFilename, "w")
myFile.write(myOutput)
myFile.close()
print "... Generated datacard files %s and %s" % (myFilename,
myRootFilename)
if "%s_error" % item in masspoints[k]["expected"]:
a = float(masspoints[k]["expected"]["%s_error" % item])
b = float(masspoints[k]["expected"][item])
r = 0.0
if b > 0:
r = a / b
line += " %9.4f" % (r)
else:
line += " n.a."
print line
myFile.close()
if __name__ == "__main__":
parser = commonLimitTools.createOptionParser(lepDefault=None,
lhcDefault=False,
lhcasyDefault=False,
fullOptions=False)
parser.add_option("--printonly",
dest="printonly",
action="store_true",
default=False,
help="Print only the ready results")
parser.add_option("--combination",
dest="combination",
action="store_true",
default=False,
help="Run combination instead of only taunu fully hadr.")
opts = commonLimitTools.parseOptionParser(parser)
# Obtain directory list
myDirs = opts.dirs[:]
if not os.path.exists(_dirname):
os.mkdir(_dirname)
# Apply TDR style
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.1, dh=-0.15)
histograms.uncertaintyMode.set(histograms.Uncertainty.StatOnly)
styles.ratioLineStyle.append(styles.StyleLine(lineColor=13))
# Find out the mass points
nameList = []
allShapeNuisances = []
signalTable = {}
myDatacardPattern = ""
myRootfilePattern = ""
if opts.cardPattern == None:
mySettings = limitTools.GeneralSettings(".",[])
myDatacardPattern = mySettings.getDatacardPattern(limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = mySettings.getRootfilePattern(limitTools.LimitProcessType.TAUJETS)
else:
myDatacardPattern = opts.cardPattern.replace("MMM","M%s").replace("MM","%s")
myRootfilePattern = opts.rootfilePattern.replace("MMM","M%s").replace("MM","%s")
massPoints = DatacardReader.getMassPointsForDatacardPattern(".", myDatacardPattern)
print "The following masses are considered:",massPoints
for m in massPoints:
# Obtain luminosity from datacard
myLuminosity = float(limitTools.readLuminosityFromDatacard(".",myDatacardPattern%m))
# Do plots
doPlot(opts,int(m),nameList,allShapeNuisances,myLuminosity,myDatacardPattern,myRootfilePattern,signalTable)
# Print signal table
print "Max contracted uncertainty for signal:"
for k in signalTable.keys():
def main(opts):
# Check that input arguments are sufficient
if opts.settings == None:
raise Exception(ErrorLabel()+"Please provide input parameter file with -x or --params !")
# Load settings
print "Loading settings:",opts.settings
if not os.path.exists(opts.settings):
raise Exception(ErrorLabel()+"Cannot find settings file '%s'!"%opts.settings)
os.system("python %s"%opts.settings) # Catch any errors in the input datacard
config = aux.load_module(opts.settings)
checkSettings(config)
os.system("cp %s ."%opts.settings)
myFitSettingsList = config.fitSettings[:]
# Copy unfitted cards for provenance information if necessary
if not os.path.exists(_myOriginalDir):
os.mkdir(_myOriginalDir)
os.system("mv *.txt %s/."%_myOriginalDir)
os.system("mv *.root %s/."%_myOriginalDir)
print "Moved original datacards as provenance info to %s"%_myOriginalDir
else:
items = glob.glob("*.txt")
if len(items):
os.system("rm *.txt")
items = glob.glob("*.root")
if len(items):
os.system("rm *.root")
# Find datacards
myLimitSettings = limitTools.GeneralSettings(_myOriginalDir,[])
massPoints = myLimitSettings.getMassPoints(limitTools.LimitProcessType.TAUJETS)
myDatacardPattern = myLimitSettings.getDatacardPattern(limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = myLimitSettings.getRootfilePattern(limitTools.LimitProcessType.TAUJETS)
# Loop over mass points
myDrawPlotsStatus = True
myShapeSensitivityTestStatus = False
myShapeSensitivityTestLabel = ""
for m in massPoints:
myHistogramCache = []
# Obtain luminosity
myLuminosity = float(limitTools.readLuminosityFromDatacard(_myOriginalDir, "%s"%myDatacardPattern%m))
# Obtain root file
myRootFile = ROOT.TFile.Open("%s/%s"%(_myOriginalDir, myRootfilePattern%m))
# Obtain datacard
myOriginalCardFile = open("%s/%s"%(_myOriginalDir, myDatacardPattern%m))
myOriginalCardLines = myOriginalCardFile.readlines()
myOriginalCardFile.close()
# Obtain column and nuisance info
myColumnNames = parseColumnNames(myOriginalCardLines)
myNuisanceInfo = parseNuisanceNames(myOriginalCardLines, myColumnNames)
myFitParNuisanceInfo = None
# Treat observation
hObs = getAndRebinRateHisto("data_obs", myRootFile, config.finalBinning["shape"])
myPath = os.getcwd()
if "SignalInjection" in myPath:
for k in range (0, hObs.GetNbinsX()+1):
hObs.SetBinContent(k, round(hObs.GetBinContent(k)))
for n in myNuisanceInfo:
if n["name"] == "observation":
n["value"] = hObs.Integral()
if "SHAPETEST" in myPath:
hObs.Reset()
myShapeSensitivityTestStatus = True
mySplit = myPath.split("_")
for i in range(0,len(mySplit)):
if mySplit[i] == "SHAPETEST":
myShapeSensitivityTestLabel = "_".join(map(str,mySplit[i+1:len(mySplit)]))
myShapeSensitivityTestLabel = myShapeSensitivityTestLabel.replace("UP","Up").replace("DOWN","Down")
myHistogramCache.append(hObs)
# Loop over column names
for c in myColumnNames:
print HighlightStyle()+"Processing column %s for mass %s"%(c,m)+NormalStyle()
if _isSignal(c) or c in config.Blacklist:
print "... skipping fit (signal or blacklist)"
# Obtain and rebin rate histo
hRate = getAndRebinRateHisto(c, myRootFile, config.finalBinning["shape"])
if _isSignal(c):
hRate.Scale(opts.lumiProjection)
else:
hRate.Scale(opts.lumiProjection*opts.bkgxsecProjection)
myHistogramCache.append(hRate.Clone())
# Update rate
for n in myNuisanceInfo:
if n["name"] == "rate":
n[c] = "%f"%hRate.Integral()
# Obtain and rebin nuisance histos
hNuisances = getAndRebinNuisanceHistos(c, myRootFile, myNuisanceInfo, config.finalBinning["shape"])
for h in hNuisances:
if _isSignal(c):
h.Scale(opts.lumiProjection)
else:
h.Scale(opts.lumiProjection*opts.bkgxsecProjection)
myHistogramCache.extend(hNuisances)
# Treat QCD shape uncertainty separately (for testing only; one should use the tail fit for QCD)
#hNuisances = getAndRebinQCDShapeNuisanceHistos(c, myRootFile, hRate, myNuisanceInfo, config.finalBinning["shape"])
#myHistogramCache.extend(hNuisances)
# Create bin-by-bin stat. histograms for fitted distribution and update the nuisance table
myStatHistograms = addBinByBinStatUncert(config, c, hRate, myColumnNames, myNuisanceInfo, isSignal=True)
myHistogramCache.extend(myStatHistograms)
if myShapeSensitivityTestStatus and not _isSignal(c):
hObs.Add(hRate) # Add the fitted histogram
# Add the nuisance with proper binning
for h in hNuisances:
if myShapeSensitivityTestLabel in h.GetName():
hObs.Add(h)
hObs.Add(hRate, -1.0)
else:
# Not signal or blacklist, do fit
hFineBinning = myRootFile.Get(c+"_fineBinning")
for i in range(1, hFineBinning.GetNbinsX()+1):
hFineBinning.SetBinContent(i, hFineBinning.GetBinContent(i)*opts.lumiProjection*opts.bkgxsecProjection)
hFineBinning.SetBinError(i, hFineBinning.GetBinError(i)/math.sqrt(opts.lumiProjection*opts.bkgxsecProjection))
if hFineBinning == None:
raise Exception(ErrorLabel()+"Cannot find histogram '%s'!"%(c+"_fineBinning"))
hOriginalShape = myRootFile.Get(c)
hOriginalShape.SetName(hOriginalShape.GetName()+"Original")
for i in range(1, hOriginalShape.GetNbinsX()+1):
hOriginalShape.SetBinContent(i, hOriginalShape.GetBinContent(i)*opts.lumiProjection*opts.bkgxsecProjection)
hOriginalShape.SetBinError(i, hOriginalShape.GetBinError(i)/math.sqrt(opts.lumiProjection*opts.bkgxsecProjection))
if hOriginalShape == None:
raise Exception(ErrorLabel()+"Cannot find histogram '%s'!"%(c))
# Proceed
myFitSettings = None
for s in myFitSettingsList:
if s["id"] in c:
myFitSettings = s
print "... using fitfunc: %s and range %d-%d"%(s["fitfunc"],s["fitmin"],s["fitmax"])
if myFitSettings == None:
raise Exception("Could not determine fit function for column '%s'!"%c)
myFitter = TailFitter.TailFitter(hFineBinning, c, myFitSettings["fitfunc"], myFitSettings["fitmin"], myFitSettings["fitmax"], myFitSettings["applyFrom"], doPlots=myDrawPlotsStatus, luminosity=myLuminosity)
# Obtain fitted rate with final binning
myFittedRateHistograms = myFitter.getFittedRateHistogram(hFineBinning, config.finalBinning["shape"], myFitSettings["applyFrom"])
myHistogramCache.extend(myFittedRateHistograms)
# Update rate
for n in myNuisanceInfo:
if n["name"] == "rate":
n[c] = "%f"%myFittedRateHistograms[0].Integral()
print "... Updated rate because of fitting %.1f -> %.1f (diff=%f)"%(hFineBinning.Integral(), myFittedRateHistograms[0].Integral(), myFittedRateHistograms[0].Integral()/hFineBinning.Integral())
# Update all those shape nuisances (update histograms only, no need to touch nuisance table)
for n in myNuisanceInfo:
if n["name"] != "observation" and n["distribution"] == "shape" and n[c] == "1":
#print "... Updating shape nuisance '%s' tail"%n["name"]
myUpdatedNuisanceHistograms = updateNuisanceTail(opts, hOriginalShape, myFittedRateHistograms[0], myRootFile, "%s_%s"%(c,n["name"]))
myHistogramCache.extend(myUpdatedNuisanceHistograms)
if myShapeSensitivityTestStatus:
# Check if the nuisance histograms exist for this column
myHistoName = "%s_%s"%(c,myShapeSensitivityTestLabel.replace("Up","").replace("Down",""))
myList = updateNuisanceTail(opts, hOriginalShape, myFittedRateHistograms[0], myRootFile, myHistoName, skipNotFoundTest=True)
#print "DEBUG",myHistoName,len(myList)
if len(myList) > 0:
# Add the nuisance with proper binning
if "Up" in myShapeSensitivityTestLabel:
hObs.Add(myList[0])
#print "DEBUG: Added nuisance",myShapeSensitivityTestLabel,myList[0].GetName(),myList[0].Integral()
elif "Down" in myShapeSensitivityTestLabel:
hObs.Add(myList[1])
#print "DEBUG: Added nuisance",myShapeSensitivityTestLabel,myList[1].GetName(),myList[1].Integral()
else:
raise Exception() # Should not happen
else:
hObs.Add(myFittedRateHistograms[0]) # Add the fitted histogram
#print "DEBUG: Added",myFittedRateHistograms[0].Integral()
print "Updated shape nuisance tails (rel.uncert. kept constant, but central value changed to the fitted one)"
# Obtain fit uncertainty histograms and add them to cache
(huplist, hdownlist) = myFitter.calculateVariationHistograms(config.finalBinning["shape"], myFitSettings["applyFrom"])
# Plot if requested
if myDrawPlotsStatus:
myArray = array.array("d",config.finalBinning["shape"])
hFinalBinning = hFineBinning.Rebin(len(myArray)-1, "", myArray)
myFitter.makeVariationPlotWithSeparateUncertainties("", hFinalBinning, myFittedRateHistograms[0], huplist, hdownlist, myFitSettings["applyFrom"])
(hupTotal, hdownTotal) = myFitter.calculateTotalVariationHistograms(myFittedRateHistograms[0], huplist, hdownlist)
myFitter.makeVariationPlotWithTotalUncertainties("", hFinalBinning, myFittedRateHistograms[0], hupTotal, hdownTotal, myFitSettings["applyFrom"])
# print total uncertainty
print "*** Syst. uncert. from fit: +",1.0-hupTotal.Integral()/myFittedRateHistograms[0].Integral(), "-", 1.0-hdownTotal.Integral()/myFittedRateHistograms[0].Integral()
hFinalBinning.Delete()
# Treat blancs (norm == 0)
for i in range(0, len(huplist)):
if huplist[i].Integral() == 0:
for k in range(0, huplist[i].GetNbinsX()+2):
huplist[i].SetBinContent(k, myFittedRateHistograms[0].GetBinContent(k))
if hdownlist[i].Integral() == 0:
for k in range(0, hdownlist[i].GetNbinsX()+2):
hdownlist[i].SetBinContent(k, myFittedRateHistograms[0].GetBinContent(k))
if config.applyFitUncertaintyAsBinByBinUncertainty:
# Add fit uncertainty as bin-by-bin type uncertainty
(hupTotal, hdownTotal) = myFitter.calculateTotalVariationHistograms(myFittedRateHistograms[0], huplist, hdownlist)
(myBinByBinUpHistograms, myBinByBinDownHistograms) = createBinnedFitUncertaintyHistograms(myFittedRateHistograms[0], hupTotal, hdownTotal, myFitSettings["applyFrom"], opts)
if not opts.noFitUncert:
myHistogramCache.extend(myBinByBinUpHistograms)
myHistogramCache.extend(myBinByBinDownHistograms)
# Add fit parameter nuisances to nuisance table
for hup in myBinByBinUpHistograms:
addNuisanceForIndividualColumn(myColumnNames,myNuisanceInfo,c,hup.GetTitle().replace("%s_%s"%(c,c),c))
else:
# Add fit uncertainty as nuisances parameters
if not opts.noFitUncert:
myHistogramCache.extend(huplist)
myHistogramCache.extend(hdownlist)
# Add fit parameter nuisances to nuisance table
for hup in huplist:
addNuisanceForIndividualColumn(myColumnNames,myNuisanceInfo,c,hup.GetTitle())
# Create bin-by-bin stat. histograms for fitted distribution and update the nuisance table
myStatHistograms = addBinByBinStatUncert(config, c, myFittedRateHistograms[0], myColumnNames, myNuisanceInfo, 0.0, myFitSettings["applyFrom"], isSignal=False)
myHistogramCache.extend(myStatHistograms)
# Clear memory
hFineBinning.Delete()
hOriginalShape.Delete()
for h in myHistogramCache:
h.SetDirectory(None)
myRootFile.Close()
myDrawPlotsStatus = False
myObsIntegral = hObs.Integral()
# Print summary info
printSummaryInfo(myColumnNames, myNuisanceInfo, myHistogramCache, hObs, m, myLuminosity, opts)
# Histogram cache contains now all root files and nuisance table is now up to date
# Create new root file and write
myRootFilename = myRootfilePattern%m
myRootFile = ROOT.TFile.Open(myRootFilename, "RECREATE")
if myRootFile == None:
raise Exception(ErrorLabel()+" Cannot open file '"+myRootFilename+"' for output!")
for h in myHistogramCache:
h.SetDirectory(myRootFile)
myRootFile.Write()
myRootFile.Close()
# Create new datacard file and write
myOutput = createDatacardOutput(myOriginalCardLines, myColumnNames, myNuisanceInfo, opts, myObsIntegral)
myFilename = myDatacardPattern%m
myFile = open(myFilename, "w")
myFile.write(myOutput)
myFile.close()
print "... Generated datacard files %s and %s"%(myFilename, myRootFilename)
def createOptionParser(lepDefault=None, lhcDefault=None, lhcasyDefault=None):
return commonLimitTools.createOptionParser(lepDefault, lhcDefault,
lhcasyDefault)
settings.getDatacardPattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
rootfilePatterns=[
settings.getRootfilePattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
clsType=combine.LHCTypeAsymptotic(opts),
postfix=pfix)
else:
return False
return True
if __name__ == "__main__":
parser = commonLimitTools.createOptionParser(lepType, lhcType,
lhcTypeAsymptotic)
parser.add_option("--postfix",
dest="postfix",
default="",
help="Postfix to add to output directory name")
opts = commonLimitTools.parseOptionParser(parser)
# General settings
myDirs = opts.dirs[:]
if len(myDirs) == 0:
myDirs.append(".")
for myDir in myDirs:
print "Considering directory:", myDir
settings = commonLimitTools.GeneralSettings(myDir, opts.masspoints)
print "The following masses are considered:", settings.getMassPoints(
if __name__ == "__main__":
def addToDatacards(myDir, massPoints, dataCardList, rootFileList, dataCardPattern, rootFilePattern):
if rootFilePattern != None and "%s" in dataCardPattern:
m = DatacardReader.getMassPointsForDatacardPattern(myDir, dataCardPattern)
if len(m) > 0:
m = DatacardReader.getMassPointsForDatacardPattern(myDir, dataCardPattern, massPoints)
del massPoints[:]
massPoints.extend(m)
dataCardList.append(dataCardPattern)
rootFileList.append(rootFilePattern)
else:
if os.path.exists(dataCardPattern):
dataCardList.append(dataCardPattern)
rootFileList.append(rootFilePattern)
parser = commonLimitTools.createOptionParser(lepType, lhcType, lhcTypeAsymptotic)
opts = commonLimitTools.parseOptionParser(parser)
# General settings
myDirs = opts.dirs[:]
if len(myDirs) == 0:
myDirs.append(".")
for myDir in myDirs:
print "Considering directory:",myDir
datacardPatterns = []
rootFilePatterns = []
myMassPoints = []
if len(opts.masspoints) > 0:
myMassPoints = opts.masspoints[:]
# taunu, tau+jets final state
def _createInjection(self, mass, datacardFiles):
if not self.brlimit:
raise Exception(
"Signal injection supported only for brlimit for now")
if len(datacardFiles) != 1:
raise Exception(
"Signal injection supported only for one datacard for now (got %d)"
% len(datacardFiles))
if len(self.multicrabConfiguration["rootfiles"]) != 1:
raise Exception(
"Signal injection supported only for one root file for now (got %d)"
% len(self.configuration["rootfiles"]))
fileName = "runCombine_LHCasy_SignalInjected_m" + mass
shutil.copy(
os.path.join(os.environ["CMSSW_BASE"], "bin",
os.environ["SCRAM_ARCH"], "combine"), self.dirname)
shutil.copy(
os.path.join(os.environ["CMSSW_BASE"], "bin",
os.environ["SCRAM_ARCH"], "text2workspace.py"),
self.dirname)
shutil.copy(
os.path.join(os.environ["CMSSW_BASE"], "src", "HiggsAnalysis",
"NtupleAnalysis", "scripts",
"combineInjectSignalLight.py"), self.dirname)
tar = tarfile.open(os.path.join(self.dirname, "python.tar.gz"),
mode="w:gz",
dereference=True)
tar.add(os.path.join(os.environ["CMSSW_BASE"], "python"),
arcname="python")
tar.close()
datacard = datacardFiles[0]
rootfile = self.multicrabConfiguration["rootfiles"][0] % mass
rootfileSignal = self.multicrabConfiguration["rootfiles"][
0] % self.opts.injectSignalMass
rfs = ""
if rootfileSignal != rootfile:
rfs = rootfileSignal
command = """
#!/bin/bash
SEED_START=1
NUMBER_OF_ITERATIONS={NTOYS}
if [ $# -ge 1 ]; then
SEED_START=$(($1 * 10000))
fi
tar zxf python.tar.gz
export PYTHONPATH=$PWD/python:$PYTHONPATH
if [ ! -d original ]; then
mkdir original
mv {DATACARD} {ROOTFILE} {ROOTFILESIGNAL_OR_EMPTY} original
fi
function runcombine {{
./combineInjectSignalLight.py --inputDatacard original/{DATACARD} --inputRoot original/{ROOTFILE} --inputRootSignal original/{ROOTFILESIGNAL} --outputDatacard {DATACARD} --outputRoot {ROOTFILE} --brtop {BRTOP} --brh {BRHPLUS} -s $1
./text2workspace.py ./{DATACARD} -P HiggsAnalysis.CombinedLimit.ChargedHiggs:brChargedHiggs -o workspaceM{MASS}.root
# combine -M Asymptotic --picky -v 2 --rAbsAcc 0.00001 --rMin 0 --rMax 1.0 -m {MASS} -n obs_m{MASS} -d workspaceM{MASS}.root
./combine {OPTS} --rMin {RMIN} --rMax {RMAX} -m {MASS} -n inj_m{MASS} -d workspaceM{MASS}.root
mv higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.root higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.seed$1.root
}}
for ((I=0; I<$NUMBER_OF_ITERATIONS; I++)); do
runcombine $(($SEED_START+$I))
done
hadd higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.root higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.seed*.root
""".format(
DATACARD=datacard,
ROOTFILE=rootfile,
ROOTFILESIGNAL=rootfileSignal,
ROOTFILESIGNAL_OR_EMPTY=rfs,
BRTOP=self.opts.injectSignalBRTop,
BRHPLUS=self.opts.injectSignalBRHplus,
NTOYS=self.opts.injectNumberToys,
MASS=mass,
OPTS=self.optionsObservedAndExpected.getValue(mass),
RMIN=self.rMin.getValue(mass),
RMAX=self.rMax.getValue(mass),
)
if "signalInjection" not in self.configuration:
self.configuration["signalInjection"] = {
"mass": self.opts.injectSignalMass,
"brTop": self.opts.injectSignalBRTop,
"brHplus": self.opts.injectSignalBRHplus
}
if not os.path.exists(os.path.join(self.dirname, "limits.json")):
# Insert luminosity to limits.json already here
limits = {
"luminosity":
commonLimitTools.readLuminosityFromDatacard(
self.dirname, datacard)
}
f = open(os.path.join(self.dirname, "limits.json"), "w")
json.dump(limits, f, sort_keys=True, indent=2)
f.close()
aux.writeScript(os.path.join(self.dirname, fileName), command)
self.signalInjectionScripts[mass] = fileName
def main(opts, settings, myDir):
postfix = "taujets"
# lepType = True
# lhcType = True
lhcTypeAsymptotic = True
crabScheduler = "arc"
crabOptions = {
# "GRID": [
# "ce_white_list = jade-cms.hip.fi",
# "ce_white_list = korundi.grid.helsinki.fi",
# ]
}
if settings.isLands():
if opts.lepType:
lands.generateMultiCrab(
opts,
myDir,
massPoints = settings.getMassPoints(commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns = [settings.getDatacardPattern(commonLimitTools.LimitProcessType.TAUJETS)],
rootfilePatterns = [settings.getRootfilePattern(commonLimitTools.LimitProcessType.TAUJETS)],
clsType = lands.LEPType(opts.brlimit,opts.sigmabrlimit,toysPerJob=100,firstSeed=settings.getFirstSeed()),
numberOfJobs = 10,
postfix = postfix+"_lep_toys1k",
crabScheduler=crabScheduler, crabOptions=crabOptions)
elif opts.lhcType:
myVR = None
if opts.brlimit:
if commonLimitTools.isHeavyHiggs(settings.getMassPoints(commonLimitTools.LimitProcessType.TAUJETS)):
raise Exception("Error: --brlimit is not available for heavy H+! Please use --sigmabrlimit !")
myVR = {"default": None,
# Initially obtained from asymp. limit as min/max of +-2 sigma and observed
# After that, with trial and error of hybrid limit (e.g. by looking plot*.gif plots)
# Light H+, values calibrated with 2011A, met>50, loose delta phi
"80": ("0.001", "0.08", "x1.05"),
"90": ("0.001", "0.07", "x1.05"),
"100": ("0.001", "0.06", "x1.05"),
"120": ("0.0005", "0.04", "x1.05"),
"140": ("0.0001", "0.03", "x1.05"),
"150": ("0.0001", "0.025", "x1.03"),
"155": ("0.0001", "0.02", "x1.03"),
"160": ("0.0001", "0.02", "x1.03"),
}
if opts.sigmabrlimit:
myVR = {"default": None,
# Initially obtained from asymp. limit as min/max of +-2 sigma and observed
# After that, with trial and error of hybrid limit (e.g. by looking plot*.gif plots)
# Light H+, values calibrated with 2011A, met>50, loose delta phi
"80": ("1", "20", "x1.05"),
"90": ("1", "20", "x1.05"),
"100": ("0.5", "20", "x1.05"),
"120": ("0.5", "20", "x1.05"),
"140": ("0.5", "10", "x1.05"),
"150": ("0.1", "10", "x1.03"),
"155": ("0.1", "10", "x1.03"),
"160": ("0.1", "10", "x1.03"),
"180": ("0.01", "5", "x1.05"),
"190": ("0.01", "5", "x1.05"),
"200": ("0.01", "5", "x1.05"),
"220": ("0.01", "5", "x1.03"),
"250": ("0.01", "5", "x1.03"),
"300": ("0.01", "5", "x1.03"),
"350": ("0.01", "5", "x1.03"),
"400": ("0.005", "1", "x1.03"),
"500": ("0.005", "1", "x1.03"),
"600": ("0.005", "1", "x1.03"),
}
lands.generateMultiCrab(
opts,
myDir,
massPoints = settings.getMassPoints(commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns = [settings.getDatacardPattern(commonLimitTools.LimitProcessType.TAUJETS)],
rootfilePatterns = [settings.getRootfilePattern(commonLimitTools.LimitProcessType.TAUJETS)],
clsType = lands.LHCType(opts.brlimit,opts.sigmabrlimit,toysCLsb=_ntoysCLsb(),toysCLb=_ntoysCLb(),firstSeed=settings.getFirstSeed(),vR=myVR),
numberOfJobs = _njobs(),
postfix = postfix+"_lhc_jobs160_sb150_b75",
crabScheduler=crabScheduler, crabOptions=crabOptions)
elif opts.lhcTypeAsymptotic:
lands.produceLHCAsymptotic(
opts,
myDir,
massPoints = settings.getMassPoints(commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns = [settings.getDatacardPattern(commonLimitTools.LimitProcessType.TAUJETS)],
rootfilePatterns = [settings.getRootfilePattern(commonLimitTools.LimitProcessType.TAUJETS)],
clsType = lands.LHCTypeAsymptotic(opts.brlimit,opts.sigmabrlimit),
postfix = postfix+"_lhcasy"
)
else:
return False
elif settings.isCombine():
if opts.lepType:
raise Exception("LEP type Hybrid CLs not implemented yet for combine")
elif opts.lhcType:
raise Exception("LHC type Hybrid CLs not implemented yet for combine")
elif opts.lhcTypeAsymptotic:
pfix = postfix #+"_lhcasy"
if opts.postfix != "":
pfix += "_"+opts.postfix
combine.produceLHCAsymptotic(
opts,
myDir,
massPoints = settings.getMassPoints(commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns = [settings.getDatacardPattern(commonLimitTools.LimitProcessType.TAUJETS)],
rootfilePatterns = [settings.getRootfilePattern(commonLimitTools.LimitProcessType.TAUJETS)],
clsType = combine.LHCTypeAsymptotic(opts),
postfix = pfix
)
else:
return False
return True
def parseOptionParser(parser):
commonLimitTools.parseOptionParser(parser)
def createOptionParser(lepDefault=None, lhcDefault=None, lhcasyDefault=None):
return commonLimitTools.createOptionParser(lepDefault, lhcDefault, lhcasyDefault)
def _createInjection(self, mass, datacardFiles):
if not self.brlimit:
raise Exception("Signal injection supported only for brlimit for now")
if len(datacardFiles) != 1:
raise Exception("Signal injection supported only for one datacard for now (got %d)" % len(datacardFiles))
if len(self.multicrabConfiguration["rootfiles"]) != 1:
raise Exception("Signal injection supported only for one root file for now (got %d)" % len(self.configuration["rootfiles"]))
fileName = "runCombine_LHCasy_SignalInjected_m" + mass
shutil.copy(os.path.join(os.environ["CMSSW_BASE"], "bin", os.environ["SCRAM_ARCH"], "combine"), self.dirname)
shutil.copy(os.path.join(os.environ["CMSSW_BASE"], "bin", os.environ["SCRAM_ARCH"], "text2workspace.py"), self.dirname)
shutil.copy(os.path.join(os.environ["CMSSW_BASE"], "src", "HiggsAnalysis", "NtupleAnalysis", "scripts", "combineInjectSignalLight.py"), self.dirname)
tar = tarfile.open(os.path.join(self.dirname, "python.tar.gz"), mode="w:gz", dereference=True)
tar.add(os.path.join(os.environ["CMSSW_BASE"], "python"), arcname="python")
tar.close()
datacard = datacardFiles[0]
rootfile = self.multicrabConfiguration["rootfiles"][0] % mass
rootfileSignal = self.multicrabConfiguration["rootfiles"][0] % self.opts.injectSignalMass
rfs = ""
if rootfileSignal != rootfile:
rfs = rootfileSignal
command = """
#!/bin/bash
SEED_START=1
NUMBER_OF_ITERATIONS={NTOYS}
if [ $# -ge 1 ]; then
SEED_START=$(($1 * 10000))
fi
tar zxf python.tar.gz
export PYTHONPATH=$PWD/python:$PYTHONPATH
if [ ! -d original ]; then
mkdir original
mv {DATACARD} {ROOTFILE} {ROOTFILESIGNAL_OR_EMPTY} original
fi
function runcombine {{
./combineInjectSignalLight.py --inputDatacard original/{DATACARD} --inputRoot original/{ROOTFILE} --inputRootSignal original/{ROOTFILESIGNAL} --outputDatacard {DATACARD} --outputRoot {ROOTFILE} --brtop {BRTOP} --brh {BRHPLUS} -s $1
./text2workspace.py ./{DATACARD} -P HiggsAnalysis.CombinedLimit.ChargedHiggs:brChargedHiggs -o workspaceM{MASS}.root
# combine -M Asymptotic --picky -v 2 --rAbsAcc 0.00001 --rMin 0 --rMax 1.0 -m {MASS} -n obs_m{MASS} -d workspaceM{MASS}.root
./combine {OPTS} --rMin {RMIN} --rMax {RMAX} -m {MASS} -n inj_m{MASS} -d workspaceM{MASS}.root
mv higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.root higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.seed$1.root
}}
for ((I=0; I<$NUMBER_OF_ITERATIONS; I++)); do
runcombine $(($SEED_START+$I))
done
hadd higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.root higgsCombineinj_m{MASS}.Asymptotic.mH{MASS}.seed*.root
""".format(
DATACARD=datacard, ROOTFILE=rootfile, ROOTFILESIGNAL=rootfileSignal, ROOTFILESIGNAL_OR_EMPTY=rfs,
BRTOP=self.opts.injectSignalBRTop, BRHPLUS=self.opts.injectSignalBRHplus,
NTOYS=self.opts.injectNumberToys, MASS=mass,
OPTS=self.optionsObservedAndExpected.getValue(mass),
RMIN=self.rMin.getValue(mass),
RMAX=self.rMax.getValue(mass),
)
if "signalInjection" not in self.configuration:
self.configuration["signalInjection"] = {
"mass": self.opts.injectSignalMass,
"brTop": self.opts.injectSignalBRTop,
"brHplus": self.opts.injectSignalBRHplus
}
if not os.path.exists(os.path.join(self.dirname, "limits.json")):
# Insert luminosity to limits.json already here
limits = {"luminosity": commonLimitTools.readLuminosityFromDatacard(self.dirname, datacard)}
f = open(os.path.join(self.dirname, "limits.json"), "w")
json.dump(limits, f, sort_keys=True, indent=2)
f.close()
aux.writeScript(os.path.join(self.dirname, fileName), command)
self.signalInjectionScripts[mass] = fileName
line += " %9.5f"%(float(masspoints[k]["expected"][item]))
for item in myKeys:
if "%s_error"%item in masspoints[k]["expected"]:
a = float(masspoints[k]["expected"]["%s_error"%item])
b = float(masspoints[k]["expected"][item])
r = 0.0
if b > 0:
r = a/b
line += " %9.4f"%(r)
else:
line += " n.a."
print line
myFile.close()
if __name__ == "__main__":
parser = commonLimitTools.createOptionParser(lepDefault=None, lhcDefault=False, lhcasyDefault=False, fullOptions=False)
parser.add_option("--printonly", dest="printonly", action="store_true", default=False, help="Print only the ready results")
parser.add_option("--combination", dest="combination", action="store_true", default=False, help="Run combination instead of only taunu fully hadr.")
opts = commonLimitTools.parseOptionParser(parser)
# Obtain directory list
myDirs = opts.dirs[:]
if len(myDirs) == 0 or (len(myDirs) == 1 and myDirs[0] == "."):
myDirs = []
for dirname, dirnames, filenames in os.walk('.'):
for subdirname in dirnames:
#if "LandSMultiCrab" in subdirname:
if "datacards_" in subdirname:
myDirs.append(os.path.join(dirname, subdirname))
if len(myDirs) == 0:
raise Exception("Error: Could not find any sub directories starting with 'datacards_' below this directory!")
style = tdrstyle.TDRStyle()
histograms.createLegend.moveDefaults(dx=-0.1, dh=-0.15)
histograms.uncertaintyMode.set(histograms.Uncertainty.StatOnly)
styles.ratioLineStyle.append(styles.StyleLine(lineColor=13))
# Find out the mass points
nameList = []
allShapeNuisances = []
signalTable = {}
myDatacardPattern = ""
myRootfilePattern = ""
if opts.cardPattern == None:
mySettings = limitTools.GeneralSettings(".",[])
myDatacardPattern = mySettings.getDatacardPattern(limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = mySettings.getRootfilePattern(limitTools.LimitProcessType.TAUJETS)
else:
myDatacardPattern = opts.cardPattern.replace("MMM","M%s").replace("MM","%s")
myRootfilePattern = opts.rootfilePattern.replace("MMM","M%s").replace("MM","%s")
massPoints = DatacardReader.getMassPointsForDatacardPattern(".", myDatacardPattern)
print "The following masses are considered:",massPoints
for m in massPoints:
# Obtain luminosity from datacard
myLuminosity = float(limitTools.readLuminosityFromDatacard(".",myDatacardPattern%m))
# Do plots
doPlot(opts,int(m),nameList,allShapeNuisances,myLuminosity,myDatacardPattern,myRootfilePattern,signalTable)
# Print signal table
print "Max contracted uncertainty for signal:"
for k in signalTable.keys():
# print "Key: "+str(k)
print "%s, %.3f--%.3f"%(k, signalTable[k]["min"],signalTable[k]["max"])
print "br(tb) uncert: minus: %f-%f, plus %f-%f"%(brTBUncertMinusMin,brTBUncertMinusMax,brTBUncertPlusMin,brTBUncertPlusMax)
print "br(taunu+tb) uncert: minus: %f-%f, plus %f-%f"%(brCombUncertMinusMin,brCombUncertMinusMax,brCombUncertPlusMin,brCombUncertPlusMax)
if __name__ == "__main__":
def addToDatacards(myDir, massPoints, dataCardList, rootFileList, dataCardPattern, rootFilePattern):
m = DatacardReader.getMassPointsForDatacardPattern(myDir, dataCardPattern)
if len(m) > 0:
m = DatacardReader.getMassPointsForDatacardPattern(myDir, dataCardPattern, massPoints)
del massPoints[:]
massPoints.extend(m)
dataCardList.append(dataCardPattern)
rootFileList.append(rootFilePattern)
parser = commonLimitTools.createOptionParser(False, False, True)
parser.add_option("--scen", dest="scenarios", action="append", default=[], help="MSSM scenarios")
parser.add_option("-t", "--tanbeta", dest="tanbeta", action="append", default=[], help="tanbeta values (will scan only these)")
parser.add_option("--tanbetarangemin", dest="tanbetarangemin", action="append", default=[], help="tanbeta values minimum range")
parser.add_option("--tanbetarangemax", dest="tanbetarangemax", action="append", default=[], help="tanbeta values maximum range")
parser.add_option("--evalUuncert", dest="evaluateUncertainties", action="store_true", default=False, help="Make plots of theoretical uncertainties")
parser.add_option("--creategridjobs", dest="creategridjobs", action="store_true", default=False, help="Create crab task dirs for running on grid")
parser.add_option("--gridmassive", dest="gridRunAllMassesInOneJob", action="store_true", default=False, help="Crab jobs run all masses in one job (default=1 job / mass)")
opts = commonLimitTools.parseOptionParser(parser)
if opts.rmin == None:
opts.rmin = "0"
if opts.rmax == None:
opts.rmax = "1" # To facilitate the search for different tan beta values
if opts.creategridjobs:
print "*** Start creating individual crab job directories for grid submission ... ***"
def parseOptionParser(parser):
commonLimitTools.parseOptionParser(parser)
def getCombineResultPassedStatus(opts, brContainer, mHp, tanbeta, resultKey, scen):
reuseStatus = False
if not brContainer.resultExists(mHp, tanbeta):
# Produce cards
myPostFix = "lhcasy_%s_mHp%s_tanbetascan%.1f"%(scen,mHp,tanbeta)
myPostFixAllMasses = "lhcasy_%s_mHpAll_tanbetascan%.1f"%(scen,tanbeta)
myList = os.listdir(".")
myList.sort()
myResultDir = None
myResultFound = False
for item in myList:
if myPostFix in item or myPostFixAllMasses in item:
myResultDir = item
if myResultDir != None:
myList = os.listdir("./%s"%myResultDir)
for item in myList:
if item.startswith("higgsCombineobs_m%s"%mHp):
f = ROOT.TFile.Open(os.path.join(myResultDir, item))
myTree = f.Get("limit")
myValue = array.array('d',[0])
myTree.SetBranchAddress("limit", myValue)
myResult = commonLimitTools.Result(mHp)
if myTree.GetEntries() != 6:
myResult.failed = True
else:
myResult.failed = False
i = 0
while i < myTree.GetEntries():
myTree.GetEvent(i)
if i == 0:
myResult.expectedMinus2Sigma = myValue[0]
elif i == 1:
myResult.expectedMinus1Sigma = myValue[0]
elif i == 2:
myResult.expected = myValue[0]
elif i == 3:
myResult.expectedPlus1Sigma = myValue[0]
elif i == 4:
myResult.expectedPlus2Sigma = myValue[0]
elif i == 5:
myResult.observed = myValue[0]
i += 1
myResultFound = True
brContainer._readFromDatabase(mHp, tanbeta)
brContainer.setCombineResult(mHp, tanbeta, myResult)
f.Close()
if not myResultFound:
massInput = [mHp]
postFixInput = myPostFix
if opts.gridRunAllMassesInOneJob:
if mHp != opts.masspoints[0]:
return None
massInput = opts.masspoints[:]
postFixInput = myPostFixAllMasses
# Result does not exist, let's calculate it
if opts.gridRunAllMassesInOneJob:
for m in opts.masspoints:
brContainer.produceScaledCards(m, tanbeta)
else:
brContainer.produceScaledCards(mHp, tanbeta)
# Run Combine
if "CMSSW_BASE" in os.environ or opts.creategridjobs:
resultContainer = combine.produceLHCAsymptotic(opts, ".", massPoints=massInput,
datacardPatterns = brContainer.getDatacardPatterns(),
rootfilePatterns = brContainer.getRootfilePatterns(),
clsType = combine.LHCTypeAsymptotic(opts),
postfix = postFixInput,
quietStatus = True)
if resultContainer != None and len(resultContainer.results) > 0:
result = resultContainer.results[0]
# Store result
brContainer.setCombineResult(mHp, tanbeta, result)
else:
print "... Skipping combine (assuming debug is intended; to run combine, do first cmsenv) ..."
else:
reuseStatus = True
#if brContainer.resultExists(mHp, tanbeta):
#myContainer = brContainer
#else:
#raise Exception("No datacards present")
if opts.creategridjobs:
return None
# Print output
s = "- mHp=%s, tanbeta=%.1f, sigmaTheory="%(mHp, tanbeta)
if brContainer.getResult(mHp, tanbeta)["sigmaTheory"] == None:
s += "None"
else:
s += "%.3f"%brContainer.getResult(mHp, tanbeta)["sigmaTheory"]
if brContainer.getFailedStatus(mHp, tanbeta):
s += " sigmaCombine (%s)=failed"%resultKey
else:
s += " sigmaCombine (%s)=%.3f, passed=%d"%(resultKey, brContainer.getCombineResultByKey(mHp, tanbeta, resultKey), brContainer.getPassedStatus(mHp, tanbeta, resultKey))
if not reuseStatus:
print s
# return limit from combine
if brContainer.getFailedStatus(mHp, tanbeta):
return None
return brContainer.getPassedStatus(mHp, tanbeta, resultKey)
def main(opts, settings, myDir):
postfix = "taujets"
# lepType = True
lhcType = True
# lhcTypeAsymptotic = True
crabScheduler = "arc"
crabOptions = {
# "GRID": [
# "ce_white_list = jade-cms.hip.fi",
# "ce_white_list = korundi.grid.helsinki.fi",
# ]
}
if settings.isLands():
if opts.lepType:
lands.generateMultiCrab(
opts,
myDir,
massPoints=settings.getMassPoints(
commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns=[
settings.getDatacardPattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
rootfilePatterns=[
settings.getRootfilePattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
clsType=lands.LEPType(opts.brlimit,
opts.sigmabrlimit,
toysPerJob=100,
firstSeed=settings.getFirstSeed()),
numberOfJobs=10,
postfix=postfix + "_lep_toys1k",
crabScheduler=crabScheduler,
crabOptions=crabOptions)
elif opts.lhcType:
myVR = None
if opts.brlimit:
if commonLimitTools.isHeavyHiggs(
settings.getMassPoints(
commonLimitTools.LimitProcessType.TAUJETS)):
raise Exception(
"Error: --brlimit is not available for heavy H+! Please use --sigmabrlimit !"
)
myVR = {
"default": None,
# Initially obtained from asymp. limit as min/max of +-2 sigma and observed
# After that, with trial and error of hybrid limit (e.g. by looking plot*.gif plots)
# Light H+, values calibrated with 2011A, met>50, loose delta phi
"80": ("0.001", "0.08", "x1.05"),
"90": ("0.001", "0.07", "x1.05"),
"100": ("0.001", "0.06", "x1.05"),
"120": ("0.0005", "0.04", "x1.05"),
"140": ("0.0001", "0.03", "x1.05"),
"150": ("0.0001", "0.025", "x1.03"),
"155": ("0.0001", "0.02", "x1.03"),
"160": ("0.0001", "0.02", "x1.03"),
}
if opts.sigmabrlimit:
myVR = {
"default": None,
# Initially obtained from asymp. limit as min/max of +-2 sigma and observed
# After that, with trial and error of hybrid limit (e.g. by looking plot*.gif plots)
# Light H+, values calibrated with 2011A, met>50, loose delta phi
"80": ("1", "20", "x1.05"),
"90": ("1", "20", "x1.05"),
"100": ("0.5", "20", "x1.05"),
"120": ("0.5", "20", "x1.05"),
"140": ("0.5", "10", "x1.05"),
"150": ("0.1", "10", "x1.03"),
"155": ("0.1", "10", "x1.03"),
"160": ("0.1", "10", "x1.03"),
"180": ("0.01", "5", "x1.05"),
"190": ("0.01", "5", "x1.05"),
"200": ("0.01", "5", "x1.05"),
"220": ("0.01", "5", "x1.03"),
"250": ("0.01", "5", "x1.03"),
"300": ("0.01", "5", "x1.03"),
"350": ("0.01", "5", "x1.03"),
"400": ("0.005", "1", "x1.03"),
"500": ("0.005", "1", "x1.03"),
"600": ("0.005", "1", "x1.03"),
}
lands.generateMultiCrab(
opts,
myDir,
massPoints=settings.getMassPoints(
commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns=[
settings.getDatacardPattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
rootfilePatterns=[
settings.getRootfilePattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
clsType=lands.LHCType(opts.brlimit,
opts.sigmabrlimit,
toysCLsb=_ntoysCLsb(),
toysCLb=_ntoysCLb(),
firstSeed=settings.getFirstSeed(),
vR=myVR),
numberOfJobs=_njobs(),
postfix=postfix + "_lhc_jobs160_sb150_b75",
crabScheduler=crabScheduler,
crabOptions=crabOptions)
elif opts.lhcTypeAsymptotic:
lands.produceLHCAsymptotic(
opts,
myDir,
massPoints=settings.getMassPoints(
commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns=[
settings.getDatacardPattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
rootfilePatterns=[
settings.getRootfilePattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
clsType=lands.LHCTypeAsymptotic(opts.brlimit,
opts.sigmabrlimit),
postfix=postfix + "_lhcasy")
else:
return False
elif settings.isCombine():
if opts.lepType:
raise Exception(
"LEP type Hybrid CLs not implemented yet for combine")
elif opts.lhcType:
raise Exception(
"LHC type Hybrid CLs not implemented yet for combine")
elif opts.lhcTypeAsymptotic:
pfix = postfix + "_lhcasy"
if opts.postfix != "":
pfix += "_" + opts.postfix
combine.produceLHCAsymptotic(
opts,
myDir,
massPoints=settings.getMassPoints(
commonLimitTools.LimitProcessType.TAUJETS),
datacardPatterns=[
settings.getDatacardPattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
rootfilePatterns=[
settings.getRootfilePattern(
commonLimitTools.LimitProcessType.TAUJETS)
],
clsType=combine.LHCTypeAsymptotic(opts),
postfix=pfix)
else:
return False
return True
def parseTextResultsFromFile(brContainer, massWhiteList, scen, resultKeys):
# Read
name = tbtools._resultsPattern % scen
print "Opening file '%s' for input" % (name)
f = open(name)
if f == None:
raise Exception("Error: Could not open result file '%s' for input!" %
name)
lines = f.readlines()
f.close()
# Obtain mass points
myMassPoints = []
if len(massWhiteList) > 0:
myMassPoints = massWhiteList[:]
else:
myLine = 0
while myLine < len(lines):
if lines[myLine].startswith("Tan beta limit scan ("):
s = lines[myLine].replace("Tan beta limit scan (", "").replace(
") for m=", ",").replace(" and key: ",
",").replace("\n", "")
mySplit = s.split(",")
m = mySplit[1]
if not m in myMassPoints:
myMassPoints.append(m)
myLine += 1
myMassPoints.sort()
# Analyse lines
for m in myMassPoints:
for myKey in resultKeys:
myBlockStart = None
myBlockEnd = None
myLine = 0
while myLine < len(lines) and myBlockEnd == None:
if lines[myLine].startswith("Tan beta limit scan (") or lines[
myLine].startswith("Allowed tan beta"):
if myBlockStart == None:
s = lines[myLine].replace(
"Tan beta limit scan (",
"").replace(") for m=",
",").replace(" and key: ",
",").replace("\n", "")
mySplit = s.split(",")
if scen == mySplit[0] and m == mySplit[
1] and myKey == mySplit[2]:
# Entry found, store beginning
myBlockStart = myLine
else:
myBlockEnd = myLine
myLine += 1
if myBlockStart == None or myLine - myBlockStart > 100:
print "... could not find results"
else:
myBlockEnd = myLine
if myBlockEnd != None:
for i in range(myBlockStart + 1, myBlockEnd - 1):
s = lines[i].replace(" tan beta=", "").replace(
" xsecTheor=",
"").replace(" pb, limit(%s)=" % myKey,
",").replace(" pb, passed=", ",")
mySplit = s.split(",")
if len(mySplit) > 1 and s[0] != "#" and not mySplit[2] in [
"failed", "n.a.", ""
] and mySplit[1] != "None":
myTanBeta = mySplit[0]
tanbetakey = tbtools.constructResultKey(m, myTanBeta)
if not brContainer.resultExists(m, myTanBeta):
brContainer._results[tanbetakey] = {}
if mySplit[1] == "None":
brContainer._results[tanbetakey][
"sigmaTheory"] = None
else:
brContainer._results[tanbetakey][
"sigmaTheory"] = float(mySplit[1])
result = commonLimitTools.Result(0)
setattr(result, myKey, float(mySplit[2]))
brContainer.setCombineResult(m, myTanBeta, result)
else:
# Add result key
setattr(
brContainer._results[tanbetakey]
["combineResult"], myKey, float(mySplit[2]))
return myMassPoints