def __init__(self,
opts,
config,
dirname,
luminosity,
observation,
datasetGroups,
verbose=False):
self._validateDatacard(config)
self._config = config
self._verbose = verbose
self._opts = opts
self._dirname = dirname
self._luminosity = luminosity
self._observation = observation
self._datasetGroups = datasetGroups
# Define label options
myStyle = tdrstyle.TDRStyle()
myStyle.setOptStat(False)
plots._legendLabels["MCStatError"] = "Bkg. stat."
plots._legendLabels["MCStatSystError"] = "Bkg. stat.#oplussyst."
plots._legendLabels["BackgroundStatError"] = "Bkg. stat. unc"
plots._legendLabels[
"BackgroundStatSystError"] = "Bkg. stat.#oplussyst. unc."
# Make control plots
self.Verbose(
ShellStyles.HighlightStyle() + "Generating control plots" +
ShellStyles.NormalStyle(), True)
# Definitions
massPoints = []
massPoints.extend(self._config.MassPoints)
if self._config.OptionDoWithoutSignal:
massPoints.append(-1) # for plotting with no signal
nMasses = len(massPoints)
nPlots = len(self._config.ControlPlots)
counter = 0
# For-loop: All mass points
for m in massPoints:
# Initialize flow plot
selectionFlow = SelectionFlowPlotMaker(self._opts, self._config, m)
# For-loop: All control plots
for i in range(0, nPlots):
counter += 1
# Skip if control plot does not exist
if observation.getControlPlotByIndex(i) == None:
continue
# Get the control plot
myCtrlPlot = self._config.ControlPlots[i]
# The case m < 0 is for plotting hitograms without any signal
if m > 0:
# saveName = "%s/DataDrivenCtrlPlot_M%d_%02d_%s" % (self._dirname, m, i, myCtrlPlot.title)
saveName = "%s/DataDrivenCtrlPlot_M%d_%s" % (
self._dirname, m, myCtrlPlot.title)
msg = "Control Plot %d/%d (m=%s GeV)" % (counter, nMasses *
nPlots, str(m))
else:
# saveName = "%s/DataDrivenCtrlPlot_%02d_%s" % (self._dirname, i, myCtrlPlot.title)
saveName = "%s/DataDrivenCtrlPlot_%s" % (self._dirname,
myCtrlPlot.title)
msg = "Control Plot %d/%d (no signal)" % (counter,
nMasses * nPlots)
# Inform the user of progress
self.PrintFlushed(
ShellStyles.AltStyle() + msg + ShellStyles.NormalStyle(),
counter == 1)
if counter == len(massPoints) * nPlots:
print
# Initialize histograms
hData = None
hSignal = None
hFakeB = None
hQCDMC = None
myStackList = []
# For-loop: All dataset columns (to find histograms)
for c in self._datasetGroups:
self.Verbose(
"Dataset is %s for plot %s" %
(myCtrlPlot.title, c.getLabel()), False)
# Skip plot?
bDoPlot = (m < 0 or c.isActiveForMass(
m, self._config)) and not c.typeIsEmptyColumn(
) and not c.getControlPlotByIndex(i) == None
if not bDoPlot:
continue
# Clone histo
h = c.getControlPlotByIndex(i)["shape"].Clone()
if c.typeIsSignal():
self.Verbose(
"Scaling histogram labelled \"%s\" with BR=%.2f" %
(c.getLabel(), self._config.OptionBr), False)
h.Scale(self._config.OptionBr)
if hSignal == None:
hSignal = h.Clone()
else:
hSignal.Add(h)
elif c.typeIsFakeB():
if hFakeB == None:
hFakeB = h.Clone()
else:
hFakeB.Add(h)
elif c.typeIsQCDMC():
if hQCD == None:
hQCDMC = h.Clone()
else:
hQCDMC.Add(h)
elif c.typeIsEWKMC() or c.typeIsGenuineB():
myHisto = histograms.Histo(h, c._datasetMgrColumn)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.append(myHisto)
# FIXME: what's this exactly?
if len(
myStackList
) < 1 or self._config.OptionFakeBMeasurementSource != "DataDriven":
continue
# Stack all the histograms
if hFakeB != None:
myHisto = histograms.Histo(hFakeB,
"FakeB",
legendLabel=_legendLabelFakeB)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.insert(0, myHisto)
elif hQCDMC != None:
myHisto = histograms.Histo(hQCDMC,
"QCDMC",
legendLabel=_legendLabelQCDMC)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.insert(0, myHisto)
hData = observation.getControlPlotByIndex(i)["shape"].Clone()
hDataUnblinded = hData.Clone()
# Apply blinding & Get blinding string
myBlindingString = self._applyBlinding(myCtrlPlot, myStackList,
hData, hSignal)
# Data
myDataHisto = histograms.Histo(hData, "Data")
myDataHisto.setIsDataMC(isData=True, isMC=False)
myStackList.insert(0, myDataHisto)
# Add signal
if m > 0:
#mySignalLabel = "HplusTB_M%d" % m
mySignalLabel = "ChargedHiggs_HplusTB_HplusToTB_M_%d" % (m)
myHisto = histograms.Histo(hSignal, mySignalLabel)
myHisto.setIsDataMC(isData=False, isMC=True)
myStackList.insert(1, myHisto)
# Add data to selection flow plot
selectionFlow.addColumn(myCtrlPlot.flowPlotCaption,
hDataUnblinded, myStackList[1:])
# Make plot
myStackPlot = None
myParams = myCtrlPlot.details.copy()
myStackPlot = plots.DataMCPlot2(myStackList)
myStackPlot.setLuminosity(self._luminosity)
myStackPlot.setEnergy("%d" % self._config.OptionSqrtS)
myStackPlot.setDefaultStyles()
# Tweak paramaters
if not "unit" in myParams.keys():
myParams["unit"] = ""
if myParams["unit"] != "":
myParams["xlabel"] = "%s (%s)" % (myParams["xlabel"],
myParams["unit"])
# Apply various settings to my parameters
self._setBlingingString(myBlindingString, myParams)
self._setYlabelWidthSuffix(hData, myParams)
self._setLegendPosition(myParams)
self._setRatioLegendPosition(myParams)
# Remove non-dientified keywords
del myParams["unit"]
# Ratio axis
if not "opts2" in myParams.keys():
myParams["opts2"] = {"ymin": 0.3, "ymax": 1.7}
# Make sure BR is indicated if anyting else but BR=1.0
if m > 0 and self._config.OptionBr != 1.0:
myStackPlot.histoMgr.setHistoLegendLabelMany({
#mySignalLabel: "H^{+} m_{H^{+}}=%d GeV (x %s)" % (m, self._config.OptionBr)
mySignalLabel:
"m_{H^{+}}=%d GeV (x %s)" % (m, self._config.OptionBr)
})
# Do plotting
drawPlot(myStackPlot, saveName, **myParams)
# Do selection flow plot
selectionFlow.makePlot(self._dirname, m,
len(self._config.ControlPlots),
self._luminosity)
return
import HiggsAnalysis.NtupleAnalysis.tools.statisticalFunctions as statisticalFunctions
import HiggsAnalysis.NtupleAnalysis.tools.plots as plots
import HiggsAnalysis.NtupleAnalysis.tools.histograms as histograms
import HiggsAnalysis.NtupleAnalysis.tools.styles as styles
import HiggsAnalysis.NtupleAnalysis.tools.ShellStyles as ShellStyles
import HiggsAnalysis.NtupleAnalysis.tools.aux as aux
#================================================================================================
# Shell Type
#================================================================================================
sh_e = ShellStyles.ErrorStyle()
sh_s = ShellStyles.SuccessStyle()
sh_h = ShellStyles.HighlightStyle()
sh_a = ShellStyles.HighlightAltStyle()
sh_l = ShellStyles.AltStyle()
sh_t = ShellStyles.NoteStyle()
sh_n = ShellStyles.NormalStyle()
sh_w = ShellStyles.WarningStyle()
#================================================================================================
# Function definitions
#================================================================================================
def cleanGraph(graph, massPoint):
'''
Remove mass points lower than 100
\param graph TGraph to operate
\param minX Minimum value of mass hypotheses to keep