def PlotTemplates(datasetsMgr, histoName, analysisType="Inverted"):
Verbose("Plotting EWK Vs QCD unity-normalised histograms")
# Create comparison plot
p1 = plots.ComparisonPlot(
getHisto(datasetsMgr, "Data", histoName, "Baseline"),
getHisto(datasetsMgr, "Data", histoName, "Inverted")
)
p1.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
defaultFolder = "ForFakeBMeasurement"
genuineBFolder = defaultFolder + "EWKGenuineB"
fakeBFolder = defaultFolder + "EWKFakeB"
histoNameNew = histoName.replace( defaultFolder, genuineBFolder)
p2 = plots.ComparisonPlot(
getHisto(datasetsMgr, "EWK", histoNameNew, "Baseline"),
getHisto(datasetsMgr, "EWK", histoNameNew, "Inverted")
)
p2.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
# Get EWKGenuineB histos
EWKGenuineB_baseline = p2.histoMgr.getHisto("Baseline-EWK").getRootHisto().Clone("Baseline-EWKGenuineB")
EWKGenuineB_inverted = p2.histoMgr.getHisto("Inverted-EWK").getRootHisto().Clone("Inverted-EWKGenuineB")
# Get FakeB histos
FakeB_baseline = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone("Baseline-FakeB")
FakeB_baseline.Add(EWKGenuineB_baseline, -1)
FakeB_inverted = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone("Inverted-FakeB")
FakeB_inverted.Add(EWKGenuineB_inverted, -1)
# Normalize histograms to unit area
EWKGenuineB_baseline.Scale(1.0/EWKGenuineB_baseline.Integral())
EWKGenuineB_inverted.Scale(1.0/EWKGenuineB_inverted.Integral())
FakeB_baseline.Scale(1.0/FakeB_baseline.Integral())
FakeB_inverted.Scale(1.0/FakeB_inverted.Integral())
# Create the final plot object
comparisonList = [EWKGenuineB_baseline]
p = plots.ComparisonManyPlot(FakeB_inverted, comparisonList, saveFormats=[])
p.setLuminosity(GetLumi(datasetsMgr))
# Apply styles
p.histoMgr.forHisto("Baseline-EWKGenuineB", styles.getBaselineStyle() )
p.histoMgr.forHisto("Inverted-FakeB" , styles.getInvertedStyle() )
# Set draw style
p.histoMgr.setHistoDrawStyle("Baseline-EWKGenuineB", "AP")
p.histoMgr.setHistoDrawStyle("Inverted-FakeB" , "HIST")
# Set legend style
p.histoMgr.setHistoLegendStyle("Baseline-EWKGenuineB", "LP")
p.histoMgr.setHistoLegendStyle("Inverted-FakeB" , "LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany({
"Baseline-EWKGenuineB": "GenuineB (EWK)", # (Baseline)
"Inverted-FakeB" : "FakeB", # (Inverted)
})
# Append analysisType to histogram name
saveName = histoName
# Draw the histograms #alex
plots.drawPlot(p, saveName, **GetHistoKwargs(histoName) ) #the "**" unpacks the kwargs_
# _kwargs = {"lessThan": True}
# p.addCutBoxAndLine(cutValue=200, fillColor=ROOT.kRed, box=False, line=True, ***_kwargs)
# Add text
text = opts.optMode.replace("OptChiSqrCutValue", "#chi^{2} #leq ")
histograms.addText(0.21, 0.85, text)
# Save plot in all formats
saveDir = os.path.join(opts.saveDir, "Templates", opts.optMode)
SavePlot(p, saveName, saveDir, saveFormats = [".C", ".png", ".pdf"])
return
def BaselineVsInvertedComparison(datasetsMgr, histoName):
p1 = plots.ComparisonPlot(*getHistos(datasetsMgr, "Data", "topSelection_Baseline/%s" % histoName, "topSelection_Inverted/%s" % histoName))
p1.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
p2 = plots.ComparisonPlot(*getHistos(datasetsMgr, "EWK", "topSelection_Baseline/%s" % histoName, "topSelection_Inverted/%s" % histoName) )
p2.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
# Get Data histos
baseline_Data = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone("Baseline-Data")
inverted_Data = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone("Inverted-Data")
# Get EWK histos
baseline_EWK = p2.histoMgr.getHisto("Baseline-EWK").getRootHisto().Clone("Baseline-EWK")
inverted_EWK = p2.histoMgr.getHisto("Inverted-EWK").getRootHisto().Clone("Inverted-EWK")
# Create QCD histos: QCD = Data-EWK
baseline_QCD = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone("Baseline-QCD")
baseline_QCD.Add(baseline_EWK, -1)
inverted_QCD = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone("Inverted-QCD")
inverted_QCD.Add(inverted_EWK, -1)
# Normalize histograms to unit area
baseline_QCD.Scale(1.0/baseline_QCD.Integral())
inverted_QCD.Scale(1.0/inverted_QCD.Integral())
# Create the final plot object
p = plots.ComparisonManyPlot(baseline_QCD, [inverted_QCD], saveFormats=[]) #[".C", ".png", ".pdf"])
p.setLuminosity(GetLumi(datasetsMgr))
# Apply styles
p.histoMgr.forHisto("Baseline-QCD" , styles.getBaselineStyle() )
p.histoMgr.forHisto("Inverted-QCD" , styles.getInvertedStyle() )
# Set draw style
p.histoMgr.setHistoDrawStyle("Baseline-QCD", "AP")
p.histoMgr.setHistoLegendStyle("Baseline-QCD", "LP")
p.histoMgr.setHistoDrawStyle("Inverted-QCD", "HIST")
p.histoMgr.setHistoLegendStyle("Inverted-QCD", "F")
# p.histoMgr.setHistoLegendStyleAll("LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany({
"Baseline-QCD" : "Baseline (QCD)",
"Inverted-QCD" : "Inverted (QCD)",
})
# Draw the histograms
_rebinX = 1
_cutBox = None
_opts = {"ymin": 8e-5, "ymaxfactor": 2.0}
if "Pt_" in histoName:
_format = "%0.f GeV/c"
if "tetrajet" in histoName.lower():
_rebinX = 2
if "ChiSqr" in histoName:
_format = "%0.1f"
_rebinX = 10
if "After" in histoName:
_rebinX = 1
_opts["xmax"] = 20.0
if "Mass" in histoName:
_format = "%0.0f GeV/c^{2}"
_rebinX = 2
if "tetrajet" in histoName.lower():
_rebinX = 5
_opts["xmax"] = 3000.0
if "BDisc" in histoName:
_format = "%0.2f"
_rebinX = 2
_opts["xmax"] = 1.01
if "Eta" in histoName:
_format = "%0.2f"
if "trijet" in histoName.lower():
_cutBox = {"cutValue": 173.21, "fillColor": 16, "box": False, "line": True, "greaterThan": True}
if "dijet" in histoName.lower():
_cutBox = {"cutValue": 80.399, "fillColor": 16, "box": False, "line": True, "greaterThan": True}
if "TetrajetMass" in histoName:
_opts = {"ymin": 8e-5, "ymaxfactor": 2.0, "xmax": 3000.0}
plots.drawPlot(p, histoName,
ylabel = "Arbitrary Units / %s" % (_format),
log = True,
rebinX = _rebinX, cmsExtraText = "Preliminary",
createLegend = {"x1": 0.62, "y1": 0.78, "x2": 0.92, "y2": 0.92},
opts = _opts,
opts2 = {"ymin": 0.6, "ymax": 1.4},
ratio = True,
ratioInvert = False,
ratioYlabel = "Ratio",
cutBox = _cutBox,
)
# Save plot in all formats
SavePlot(p, histoName, os.path.join(opts.saveDir, "BaselineVsInverted") )
return
def BaselineVsInvertedPlots(datasetsMgr, histoName, analysisType="Inverted"):
# Sanity check
IsBaselineOrInverted(analysisType)
# Get the Data (Inclusive)
p1 = plots.ComparisonPlot(*getHistos(datasetsMgr, "Data", histoName, analysisType))
p1.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
# Get the EWK (GenuineB)
defaultFolder = "ForFakeBMeasurement"
genuineBFolder = defaultFolder + "EWKGenuineB"
fakeBFolder = defaultFolder + "EWKFakeB"
histoNameNew = histoName.replace( defaultFolder, genuineBFolder)
p2 = plots.ComparisonPlot(*getHistos(datasetsMgr, "EWK", histoNameNew, analysisType) )
p2.histoMgr.normalizeMCToLuminosity(datasetsMgr.getDataset("Data").getLuminosity())
# Get Data histos
baseline_Data = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone("Baseline-Data")
inverted_Data = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone("Inverted-Data")
# Get EWK histos
baseline_EWKGenuineB = p2.histoMgr.getHisto("Baseline-EWK").getRootHisto().Clone("Baseline-EWKGenuineB")
inverted_EWKGenuineB = p2.histoMgr.getHisto("Inverted-EWK").getRootHisto().Clone("Inverted-EWKGenuineB")
# Get FakeB (Baseline): FakeB = Data-EWKGenuineB
baseline_FakeB = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone("Baseline-FakeB")
baseline_FakeB.Add(baseline_EWKGenuineB, -1)
# Get FakeB (Inverted): FakeB = Data-EWKGenuineB
inverted_FakeB = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone("Inverted-FakeB")
inverted_FakeB.Add(inverted_EWKGenuineB, -1)
# Normalize histograms to unit area
baseline_FakeB.Scale(1.0/baseline_FakeB.Integral())
inverted_FakeB.Scale(1.0/inverted_FakeB.Integral())
# Create the final plot object
p = plots.ComparisonManyPlot(baseline_FakeB, [inverted_FakeB], saveFormats=[]) #[".C", ".png", ".pdf"])
p.setLuminosity(GetLumi(datasetsMgr))
# Apply styles
p.histoMgr.forHisto("Baseline-FakeB" , styles.getBaselineStyle() )
p.histoMgr.forHisto("Inverted-FakeB" , styles.getInvertedStyle() )
# Set draw style
p.histoMgr.setHistoDrawStyle("Baseline-FakeB", "AP")
p.histoMgr.setHistoDrawStyle("Inverted-FakeB", "HIST")
# Set legend style
p.histoMgr.setHistoLegendStyle("Baseline-FakeB", "LP")
p.histoMgr.setHistoLegendStyle("Inverted-FakeB", "F")
# p.histoMgr.setHistoLegendStyleAll("LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany({
"Baseline-FakeB" : "FakeB (Baseline)",
"Inverted-FakeB" : "FakeB (Inverted)",
})
# Draw the histograms
_cutBox = None
_rebinX = 1
_opts = {"ymin": 1e-4, "ymaxfactor": 2.0}
_format = "%0.0f"
_xlabel = None
if "dijetm" in histoName.lower():
_rebinX = 2
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jj} (%s)" % (_units)
_cutBox = {"cutValue": 80.399, "fillColor": 16, "box": False, "line": True, "greaterThan": True}
_opts["xmax"] = 400.0
if "trijetm" in histoName.lower():
_rebinX = 5
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjb} (%s)" % _units
_cutBox = {"cutValue": 173.21, "fillColor": 16, "box": False, "line": True, "greaterThan": True}
_opts["xmax"] = 1500.0
if "pt" in histoName.lower():
_rebinX = 2
_format = "%0.0f GeV/c"
if "eta" in histoName.lower():
_format = "%0.2f"
_cutBox = {"cutValue": 0., "fillColor": 16, "box": False, "line": True, "greaterThan": True}
_opts["xmin"] = -3.0
_opts["xmax"] = +3.0
if "deltaeta" in histoName.lower():
_format = "%0.2f"
_opts["xmin"] = 0.0
_opts["xmax"] = 6.0
if "bdisc" in histoName.lower():
_format = "%0.2f"
if "tetrajetm" in histoName.lower():
_rebinX = 10
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjjb} (%s)" % (_units)
_opts["xmax"] = 3500.0
plots.drawPlot(p, histoName,
xlabel = _xlabel,
ylabel = "Arbitrary Units / %s" % (_format),
log = True,
rebinX = _rebinX, cmsExtraText = "Preliminary",
createLegend = {"x1": 0.62, "y1": 0.78, "x2": 0.92, "y2": 0.92},
opts = _opts,
opts2 = {"ymin": 0.6, "ymax": 1.4},
ratio = True,
ratioInvert = False,
ratioYlabel = "Ratio",
cutBox = _cutBox,
)
# Save plot in all formats
SavePlot(p, histoName, os.path.join(opts.saveDir, "BaselineVsInverted", opts.optMode) )
return
def PlotBaselineVsInverted(datasetsMgr, hBaseline, hInverted):
# Get the Inclusive (Data, EWK)
p1 = plots.ComparisonPlot(
*getHistos(datasetsMgr, "Data", hBaseline, hInverted))
p1.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
p2 = plots.ComparisonPlot(
*getHistos(datasetsMgr, "EWK", hBaseline, hInverted))
p2.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
if opts.useMC:
p3 = plots.ComparisonPlot(
*getHistos(datasetsMgr, "QCD", hBaseline, hInverted))
p3.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
# Get Baseline histos
baseline_Data = p1.histoMgr.getHisto(
"Baseline-Data").getRootHisto().Clone()
baseline_QCD = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone(
"Baseline-QCD")
baseline_EWK = p2.histoMgr.getHisto("Baseline-EWK").getRootHisto().Clone()
if opts.useMC:
baseline_QCDMC = p3.histoMgr.getHisto(
"Baseline-QCD").getRootHisto().Clone("Baseline-QCDMC")
# Get Inverted histos
inverted_Data = p1.histoMgr.getHisto(
"Inverted-Data").getRootHisto().Clone()
inverted_QCD = p1.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone(
"Inverted-QCD")
inverted_EWK = p2.histoMgr.getHisto("Inverted-EWK").getRootHisto().Clone()
if opts.useMC:
inverted_QCDMC = p3.histoMgr.getHisto(
"Inverted-QCD").getRootHisto().Clone("Inverted-QCDMC")
# Subtract EWK from Data to get QCD
baseline_QCD.Add(baseline_EWK, -1)
inverted_QCD.Add(inverted_EWK, -1)
# Option: Use QCD-MC instead of QCD=Data-EWK
if opts.useMC:
baseline_QCD = baseline_QCDMC
inverted_QCD = inverted_QCDMC
# Normalize histograms to unit area
if opts.normaliseToOne:
baseline_Data.Scale(1.0 / baseline_Data.Integral())
baseline_QCD.Scale(1.0 / baseline_QCD.Integral())
baseline_EWK.Scale(1.0 / baseline_EWK.Integral())
inverted_Data.Scale(1.0 / inverted_Data.Integral())
inverted_QCD.Scale(1.0 / inverted_QCD.Integral())
inverted_EWK.Scale(1.0 / inverted_EWK.Integral())
# Create the final plot object
p = plots.ComparisonManyPlot(baseline_QCD, [inverted_QCD], saveFormats=[])
# Apply styles
if opts.useMC:
p.histoMgr.forHisto("Baseline-QCDMC", styles.getBaselineStyle())
p.histoMgr.forHisto("Inverted-QCDMC", styles.getInvertedStyle())
else:
p.histoMgr.forHisto("Baseline-QCD", styles.getBaselineStyle())
p.histoMgr.forHisto("Inverted-QCD", styles.getInvertedStyle())
# Set draw style
if opts.useMC:
p.histoMgr.setHistoDrawStyle("Baseline-QCDMC", "AP")
p.histoMgr.setHistoDrawStyle("Inverted-QCDMC", "HIST")
else:
p.histoMgr.setHistoDrawStyle("Baseline-QCD", "AP")
p.histoMgr.setHistoDrawStyle("Inverted-QCD", "HIST")
# Set legend style
if opts.useMC:
p.histoMgr.setHistoLegendStyle("Baseline-QCDMC", "LP")
p.histoMgr.setHistoLegendStyle("Inverted-QCDMC", "F")
else:
p.histoMgr.setHistoLegendStyle("Baseline-QCD", "LP")
p.histoMgr.setHistoLegendStyle("Inverted-QCD", "F")
# Set legend labels
if opts.useMC:
p.histoMgr.setHistoLegendLabelMany({
"Baseline-QCDMC":
"QCD-MC (Baseline)",
"Inverted-QCDMC":
"QCD-MC (Inverted)",
})
else:
p.histoMgr.setHistoLegendLabelMany({
"Baseline-QCD": "QCD (Baseline)",
"Inverted-QCD": "QCD (Inverted)",
})
# Draw the histograms
_cutBox = None
_rebinX = 1
if opts.normaliseToOne:
_opts = {"ymin": 3e-4, "ymaxfactor": 2.0}
else:
_opts = {"ymin": 1e0, "ymaxfactor": 2.0}
_format = "%0.0f"
_xlabel = None
if "dijetm" in hBaseline.lower():
_rebinX = 2
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jj} (%s)" % (_units)
_cutBox = {
"cutValue": 80.399,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 400.0
if "chisqr" in hBaseline.lower():
_rebinX = 1
_units = ""
_format = "%0.1f " + _units
_xlabel = "#chi^{2}"
_cutBox = {
"cutValue": 10.0,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 100.0
if "ldgdijetpt" in hBaseline.lower():
_rebinX = 1
_units = "GeV/c"
_format = "%0.0f " + _units
_xlabel = "p_{T} (%s)" % _units
_cutBox = {
"cutValue": 40.0,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 800.0
if "ldgdijetm" in hBaseline.lower():
_rebinX = 1
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jj} (%s)" % _units
_cutBox = {
"cutValue": 80.385,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 300.0
if "trijetm" in hBaseline.lower():
_rebinX = 4 #5
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjb} (%s)" % _units
_cutBox = {
"cutValue": 173.21,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 1000.0
if "pt" in hBaseline.lower():
_rebinX = 2
_format = "%0.0f GeV/c"
_cutBox = {
"cutValue": 40.,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
ROOT.gStyle.SetNdivisions(8, "X")
_opts["xmax"] = 1000.0
if "eta" in hBaseline.lower():
_format = "%0.2f"
_cutBox = {
"cutValue": 0.,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmin"] = -3.0
_opts["xmax"] = +3.0
if "deltaeta" in hBaseline.lower():
_format = "%0.2f"
_opts["xmin"] = 0.0
_opts["xmax"] = 6.0
if "bdisc" in hBaseline.lower():
_format = "%0.2f"
if "tetrajetm" in hBaseline.lower():
_rebinX = 10 #4
if opts.useMC:
_rebinX = 10
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjbb} (%s)" % (_units)
_opts["xmax"] = 3000.0
#_opts["xmax"] = 3500.0
plots.drawPlot(
p,
hBaseline,
xlabel=_xlabel,
ylabel="Arbitrary Units / %s" % (_format),
log=True,
rebinX=_rebinX,
cmsExtraText="Preliminary",
createLegend={
"x1": 0.62,
"y1": 0.78,
"x2": 0.92,
"y2": 0.92
},
opts=_opts,
opts2={
"ymin": 0.6,
"ymax": 1.4
},
ratio=True,
ratioInvert=False,
ratioYlabel="Ratio",
cutBox=_cutBox,
)
# Save plot in all formats
saveName = hBaseline.replace("/", "_")
saveName = saveName.replace("_Baseline_", "_")
savePath = os.path.join(opts.saveDir, "BaselineVsInverted", opts.optMode)
if opts.useMC:
savePath = os.path.join(opts.saveDir, "BaselineVsInverted", "MC",
opts.optMode)
SavePlot(p, saveName, savePath)
return
def PlotBaselineVsInvertedTemplates(datasetsMgr,
histoName,
addQcdBaseline=False):
Verbose("Plotting EWK Vs QCD unity-normalised histograms")
# Create comparison plot
p1 = plots.ComparisonPlot(
getHisto(datasetsMgr, "Data", "topSelection_Baseline/%s" % histoName,
"Baseline"),
getHisto(datasetsMgr, "EWK", "topSelection_Baseline/%s" % histoName,
"Baseline"))
p1.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
p2 = plots.ComparisonPlot(
getHisto(datasetsMgr, "Data", "topSelection_Inverted/%s" % histoName,
"Inverted"),
getHisto(datasetsMgr, "EWK", "topSelection_Inverted/%s" % histoName,
"Inverted"))
p2.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
# Get EWK histos
EWK_baseline = p1.histoMgr.getHisto("Baseline-EWK").getRootHisto().Clone(
"Baseline-EWK")
EWK_inverted = p2.histoMgr.getHisto("Inverted-EWK").getRootHisto().Clone(
"Inverted-EWK")
# Get QCD histos
QCD_baseline = p1.histoMgr.getHisto("Baseline-Data").getRootHisto().Clone(
"Baseline-QCD")
QCD_inverted = p2.histoMgr.getHisto("Inverted-Data").getRootHisto().Clone(
"Inverted-QCD")
# Create QCD histos: QCD = Data-EWK
QCD_baseline.Add(EWK_baseline, -1)
QCD_inverted.Add(EWK_inverted, -1)
# Normalize histograms to unit area
EWK_baseline.Scale(1.0 / EWK_baseline.Integral())
EWK_inverted.Scale(1.0 / EWK_inverted.Integral())
QCD_baseline.Scale(1.0 / QCD_baseline.Integral())
QCD_inverted.Scale(1.0 / QCD_inverted.Integral())
# Create the final plot object
if addQcdBaseline:
compareHistos = [EWK_baseline, QCD_baseline]
else:
compareHistos = [EWK_baseline]
p = plots.ComparisonManyPlot(QCD_inverted, compareHistos, saveFormats=[])
p.setLuminosity(GetLumi(datasetsMgr))
# Apply styles
p.histoMgr.forHisto("Baseline-EWK", styles.getBaselineStyle())
if addQcdBaseline:
p.histoMgr.forHisto("Baseline-QCD", styles.getInvertedLineStyle())
p.histoMgr.forHisto("Inverted-QCD", styles.getInvertedStyle())
# Set draw style
p.histoMgr.setHistoDrawStyle("Baseline-EWK", "AP")
p.histoMgr.setHistoLegendStyle("Baseline-EWK", "LP")
if addQcdBaseline:
p.histoMgr.setHistoDrawStyle("Baseline-QCD", "HIST")
p.histoMgr.setHistoLegendStyle("Baseline-QCD", "FL")
p.histoMgr.setHistoDrawStyle("Inverted-QCD", "AP")
p.histoMgr.setHistoLegendStyle("Inverted-QCD", "LP")
# Set legend labels
if addQcdBaseline:
p.histoMgr.setHistoLegendLabelMany({
"Baseline-EWK": "EWK (Baseline)",
"Baseline-QCD": "QCD (Baseline)",
"Inverted-QCD": "QCD (Inverted)",
})
else:
p.histoMgr.setHistoLegendLabelMany({
"Baseline-EWK": "EWK (Baseline)",
"Inverted-QCD": "QCD (Inverted)",
})
# Append analysisType to histogram name
saveName = histoName
# Draw the histograms #alex
plots.drawPlot(p, saveName,
**GetHistoKwargs(histoName)) #the "**" unpacks the kwargs_
# _kwargs = {"lessThan": True}
# p.addCutBoxAndLine(cutValue=200, fillColor=ROOT.kRed, box=False, line=True, ***_kwargs)
# Add text
text = opts.optMode.replace("OptChiSqrCutValue", "#chi^{2} #leq ")
histograms.addText(0.21, 0.85, text)
# Save plot in all formats
saveDir = os.path.join(opts.saveDir, "Templates", opts.optMode)
SavePlot(p, saveName, saveDir, saveFormats=[".C", ".png", ".pdf"])
return
def BaselineVsInvertedPlots(datasetsMgr, histoName):
# Get the Inclusive (Data, EWK)
p1 = plots.ComparisonPlot(*getHistos(datasetsMgr, histoName, "Baseline"))
p1.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
p2 = plots.ComparisonPlot(*getHistos(datasetsMgr, histoName, "Inverted"))
p2.histoMgr.normalizeMCToLuminosity(
datasetsMgr.getDataset("Data").getLuminosity())
# Get Baseline histos
baseline_Data = p1.histoMgr.getHisto("Data").getRootHisto().Clone(
"Baseline-Data")
baseline_QCD = p1.histoMgr.getHisto("Data").getRootHisto().Clone(
"Baseline-QCD")
baseline_EWK = p1.histoMgr.getHisto("EWK").getRootHisto().Clone(
"Baseline-EWK")
# Get Inverted histos
inverted_Data = p2.histoMgr.getHisto("Data").getRootHisto().Clone(
"Inverted-Data")
inverted_QCD = p2.histoMgr.getHisto("Data").getRootHisto().Clone(
"Inverted-QCD")
inverted_EWK = p2.histoMgr.getHisto("EWK").getRootHisto().Clone(
"Inverted-EWK")
# Subtract EWK from Data to get QCD
baseline_QCD.Add(baseline_EWK, -1)
inverted_QCD.Add(inverted_EWK, -1)
# Normalize histograms to unit area
baseline_Data.Scale(1.0 / baseline_Data.Integral())
baseline_QCD.Scale(1.0 / baseline_QCD.Integral())
baseline_EWK.Scale(1.0 / baseline_EWK.Integral())
inverted_Data.Scale(1.0 / inverted_Data.Integral())
inverted_QCD.Scale(1.0 / inverted_QCD.Integral())
inverted_EWK.Scale(1.0 / inverted_EWK.Integral())
# Create the final plot object
p = plots.ComparisonManyPlot(baseline_QCD, [inverted_QCD], saveFormats=[])
#p.setLuminosity(GetLumi(datasetsMgr))
# Apply styles
p.histoMgr.forHisto("Baseline-QCD", styles.getBaselineStyle())
p.histoMgr.forHisto("Inverted-QCD", styles.getInvertedStyle())
# Set draw style
p.histoMgr.setHistoDrawStyle("Baseline-QCD", "AP")
p.histoMgr.setHistoDrawStyle("Inverted-QCD", "HIST")
# Set legend style
p.histoMgr.setHistoLegendStyle("Baseline-QCD", "LP")
p.histoMgr.setHistoLegendStyle("Inverted-QCD", "F")
# p.histoMgr.setHistoLegendStyleAll("LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany({
"Baseline-QCD": "QCD (Baseline)",
"Inverted-QCD": "QCD (Inverted)",
})
# Draw the histograms
_cutBox = None
_rebinX = 1
_opts = {"ymin": 1e-4, "ymaxfactor": 2.0}
_format = "%0.0f"
_xlabel = None
if "dijetm" in histoName.lower():
_rebinX = 2
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jj} (%s)" % (_units)
_cutBox = {
"cutValue": 80.399,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 400.0
if "trijetm" in histoName.lower():
_rebinX = 5
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjb} (%s)" % _units
_cutBox = {
"cutValue": 173.21,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmax"] = 1500.0
if "pt" in histoName.lower():
_rebinX = 2
_format = "%0.0f GeV/c"
if "eta" in histoName.lower():
_format = "%0.2f"
_cutBox = {
"cutValue": 0.,
"fillColor": 16,
"box": False,
"line": True,
"greaterThan": True
}
_opts["xmin"] = -3.0
_opts["xmax"] = +3.0
if "deltaeta" in histoName.lower():
_format = "%0.2f"
_opts["xmin"] = 0.0
_opts["xmax"] = 6.0
if "bdisc" in histoName.lower():
_format = "%0.2f"
if "tetrajetm" in histoName.lower():
_rebinX = 10
_units = "GeV/c^{2}"
_format = "%0.0f " + _units
_xlabel = "m_{jjjb} (%s)" % (_units)
_opts["xmax"] = 3500.0
plots.drawPlot(
p,
histoName,
xlabel=_xlabel,
ylabel="Arbitrary Units / %s" % (_format),
log=True,
rebinX=_rebinX,
cmsExtraText="Preliminary",
createLegend={
"x1": 0.62,
"y1": 0.78,
"x2": 0.92,
"y2": 0.92
},
opts=_opts,
opts2={
"ymin": 0.6,
"ymax": 1.4
},
ratio=True,
ratioInvert=False,
ratioYlabel="Ratio",
cutBox=_cutBox,
)
# Save plot in all formats
SavePlot(p, histoName.replace("<Analysis>_", ""),
os.path.join(opts.saveDir, "BaselineVsInverted", opts.optMode))
return
