def MCPlot(datasetsMgr, json):
Verbose("Creating MC plot")
# Create the MC Plot with selected normalization ("normalizeToOne", "normalizeByCrossSection", "normalizeToLumi")
ylabel_ = json["ylabel"]
if json["normalization"]=="normalizeToLumi":
kwargs = {}
p = plots.MCPlot(datasetsMgr, json["histogram"], normalizeToLumi=opts.intLumi, **kwargs)
elif json["normalization"]=="normalizeToOne":
ylabel_ = ylabel_.replace(json["ylabel"].split(" /")[0], "Arbitrary Units")
kwargs = {json["normalization"]: True}
p = plots.MCPlot(datasetsMgr, json["histogram"], **kwargs)
else:
raise Exception("Invalid normalization \"%s\"" % (json["normalization"]) )
# Label size (optional. Commonly Used in counters)
xlabelSize = None
if "xlabelsize" in json:
xlabelSize = json["xlabelsize"]
ylabelSize = None
if "ylabelsize" in json:
ylabelSize = json["ylabelsize"]
# Draw a customised plot
saveName = os.path.join(json["saveDir"], json["title"])
plots.drawPlot(p,
saveName,
xlabel = json["xlabel"],
ylabel = ylabel_,
rebinX = json["rebinX"],
rebinY = json["rebinY"],
stackMCHistograms = json["stackMCHistograms"]=="True",
addMCUncertainty = json["addMCUncertainty"]=="True" and json["normalization"]!="normalizeToOne",
addLuminosityText = json["addLuminosityText"]=="True",
addCmsText = json["addCmsText"]=="True",
cmsExtraText = json["cmsExtraText"],
opts = json["opts"],
log = json["logY"]=="True",
errorBarsX = json["errorBarsX"]=="True",
moveLegend = json["moveLegend"],
# cutLine = json["cutValue"], #cannot have this and "cutBox" defined
cutBox = {"cutValue": json["cutValue"], "fillColor": json["cutFillColour"], "box": json["cutBox"]=="True", "line": json["cutLine"]=="True", "greaterThan": json["cutGreaterThan"]=="True"},
xlabelsize = xlabelSize,
ylabelsize = ylabelSize,
)
# Remove legend?
if json["removeLegend"] == "True":
p.removeLegend()
# Additional text
histograms.addText(json["extraText"].get("x"), json["extraText"].get("y"), json["extraText"].get("text"), json["extraText"].get("size") )
# Save in all formats chosen by user
saveFormats = json["saveFormats"]
for i, ext in enumerate(saveFormats):
Print("%s" % saveName + ext, i==0)
p.saveAs(saveName, formats=saveFormats)
return
def PlotHisto(dsetsMgr, h, histoType):
kwargs = {}
hList = getHistoList(dsetsMgr, h)
if 1:
p = plots.PlotSameBase(dsetsMgr,
h,
normalizeToOne=False,
saveFormats=[],
**kwargs)
else:
p = plots.MCPlot(dsetsMgr,
h,
normalizeToLumi=opts.intLumi,
saveFormats=[],
**kwargs)
p = plots.PlotSameBase(dsetsMgr, h, saveFormats=[], **kwargs)
p = plots.MCPlot(dsetsMgr,
h,
normalizeToOne=True,
saveFormats=[],
**kwargs)
# Set default styles (Called by default in MCPlot)
p._setLegendStyles()
p._setLegendLabels()
p._setPlotStyles()
# Customise legend
for d in dsetsMgr.getAllDatasetNames():
if "TH2" not in histoType:
if "pCalo" in h:
p.histoMgr.setHistoLegendStyle(d, "LP")
p.histoMgr.setHistoDrawStyle(d, "AP")
# Draw a customised plot
kwargs = GetHistoKwargs(h, opts)
plots.drawPlot(p, h, **kwargs)
# Add text
ptSlice = h.rsplit("_")[-1].replace("GE",
"#geq ").replace("to", " to ").replace(
"Pt", "p_{T} = ")
ptSlice += " GeV"
histograms.addText(0.20, 0.865, ptSlice, 18)
# Remove legend?
if kwargs["removeLegend"]:
p.removeLegend()
# Save in all formats chosen by user
aux.SavePlot(p, opts.saveDir, h, opts.saveFormats, opts.url)
return
def MCPlot(datasetsMgr, json):
Verbose("Creating MC plot")
# Create the MC Plot with selected normalization ("normalizeToOne", "normalizeByCrossSection", "normalizeToLumi")
ylabel_ = json["ylabel"]
if json["normalization"] == "normalizeToLumi":
kwargs = {}
p = plots.MCPlot(datasetsMgr,
json["histogram"],
normalizeToLumi=opts.intLumi,
**kwargs)
elif json["normalization"] == "normalizeToOne":
ylabel_ = ylabel_.replace(json["ylabel"].split(" /")[0],
"Arbitrary Units")
kwargs = {json["normalization"]: True}
p = plots.MCPlot(datasetsMgr, json["histogram"], **kwargs)
else:
raise Exception("Invalid normalization \"%s\"" %
(json["normalization"]))
'''
if json["normalizationToOne"]=="True":
ylabel_ = ylabel_.replace(json["ylabel"].split(" /")[0], "Arbitrary Units")
kwargs = {json["normalizationToOne"]: True}
p = plots.MCPlot(datasetsMgr, json["histogram"], **kwargs)
else:
raise Exception("Invalid normalization \"%s\"" % (json["normalization"]) )
'''
# Label size (optional. Commonly Used in counters)
xlabelSize = None
if "xlabelsize" in json:
xlabelSize = json["xlabelsize"]
ylabelSize = None
if "ylabelsize" in json:
ylabelSize = json["ylabelsize"]
# Set universal histo styles
if ("drawStyle" in json):
p.histoMgr.setHistoDrawStyleAll(json["drawStyle"])
if ("legendStyle" in json):
p.histoMgr.setHistoLegendStyleAll(json["legendStyle"])
# For-loop: All histos
for index, h in enumerate(p.histoMgr.getHistos()):
if index == 0:
continue
else:
p.histoMgr.setHistoDrawStyle(h.getName(), "AP")
p.histoMgr.setHistoLegendStyle(h.getName(), "AP")
# Set default dataset style to all histos
for index, h in enumerate(p.histoMgr.getHistos()):
plots._plotStyles[p.histoMgr.getHistos()
[index].getDataset().getName()].apply(
p.histoMgr.getHistos()[index].getRootHisto())
# Draw a customised plot
saveDir = "/afs/cern.ch/user/m/mtoumazo/public/html/hltaus/TkCalo/"
saveName = os.path.join(saveDir, json["saveName"])
plots.drawPlot(
p,
saveName,
xlabel=json["xlabel"],
ylabel=ylabel_,
rebinX=json["rebinX"],
rebinY=json["rebinY"],
stackMCHistograms=json["stackMCHistograms"] == "True",
addMCUncertainty=json["addMCUncertainty"] == "True"
and json["normalization"] != "normalizeToOne",
addLuminosityText=json["addLuminosityText"] == "True",
addCmsText=json["addCmsText"] == "True",
cmsExtraText=json["cmsExtraText"],
opts=json["opts"],
log=json["logY"] == "True",
errorBarsX=json["errorBarsX"] == "True",
moveLegend=json["moveLegend"],
# cutLine = json["cutValue"], #cannot have this and "cutBox" defined
cutBox={
"cutValue": json["cutValue"],
"fillColor": json["cutFillColour"],
"box": json["cutBox"] == "True",
"line": json["cutLine"] == "True",
"greaterThan": json["cutGreaterThan"] == "True"
},
xlabelsize=xlabelSize,
ylabelsize=ylabelSize,
)
# Remove legend?
if json["removeLegend"] == "True":
p.removeLegend()
# Additional text
histograms.addText(json["extraText"].get("x"), json["extraText"].get("y"),
json["extraText"].get("text"),
json["extraText"].get("size"))
# Save in all formats chosen by user
saveFormats = [".pdf"]
for i, ext in enumerate(saveFormats):
saveNameURL = saveName + ext
saveNameURL = saveNameURL.replace(
"/afs/cern.ch/user/m/mtoumazo/public/html/hltaus/",
"https://cmsdoc.cern.ch/~mtoumazo/hltaus/")
if opts.url:
Print(saveNameURL, 1)
else:
Print(saveName + ext, 1)
p.saveAs(saveName, formats=saveFormats)
return
def Plot2dHistograms(datasetsMgr, dsetName, histoName, index):
msg = "%s%s (%s)%s" % (ShellStyles.SuccessStyle(), histoName, dsetName, ShellStyles.NormalStyle() )
aux.PrintFlushed(msg, index==1)
# Custom Filtering of datasets
dsetsMgr = datasetsMgr.deepCopy()
if opts.verbose:
dsetsMgr.PrintInfo()
# Get Histogram name and its kwargs
saveName = histoName.rsplit("/")[-1] + "_" + dsetName.split("_")[0] + dsetName.split("_")[-1]
kwargs_ = GetHistoKwargs(saveName, opts)
for i, d in enumerate(dsetsMgr.getAllDatasetNames(), 0):
if d == dsetName:
continue
else:
# Remove dataset from manager but do NOT close the file!
dsetsMgr.remove(d, close=False)
# Sanity check
nDatasets = len(dsetsMgr.getAllDatasets())
if nDatasets > 1:
raise Exception("More than 1 datasets detected in the dataset manager! Can only support 1 dataset. Please use the -i option to choose exactly 1 dataset'")
# Get the reference histo and the list of histos to compare
datasets0 = dsetsMgr.getAllDatasets()[0].getName()
histoList = [getHisto(dsetsMgr, datasets0, histoName)]
# Create the 2d plot
Verbose("Creating the 2d plot", True)
if opts.normalizeToLumi:
p = plots.MCPlot(dsetsMgr, histoName, normalizeToLumi=opts.intLumi, saveFormats=[])
elif opts.normalizeByCrossSection:
p = plots.MCPlot(dsetsMgr, histoName, normalizeByCrossSection=True, saveFormats=[], **{})
elif opts.normalizeToOne:
p = plots.MCPlot(dsetsMgr, histoName, normalizeToOne=True, saveFormats=[], **{})
else:
raise Exception("One of the options --normalizeToOne, --normalizeByCrossSection, --normalizeToLumi must be enabled (set to \"True\").")
Verbose("Setting universal histo styles", True)
p.histoMgr.setHistoDrawStyleAll("COLZ")
#p.histoMgr.setHistoLegendStyleAll("L")
Verbose("Customising histograms", True)
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().GetZaxis().SetTitleOffset(1.3)) #fixme
Verbose("Setting plot styles to histograms", True)
for index, h in enumerate(p.histoMgr.getHistos()):
plots._plotStyles[p.histoMgr.getHistos()[index].getDataset().getName()].apply(p.histoMgr.getHistos()[index].getRootHisto())
Verbose("Drawing the plot", True)
plots.drawPlot(p, saveName, **kwargs_) #the "**" unpacks the kwargs_ dictionary
# Add fit line for shrinking cone?
const= 0.0
coeff= 0.0
step = 1
xmin = 0
xmax = 0
if "GenP_VisEt_Vs" in histoName:
const= 3.5
coeff= 1.0
step = 100
xmin = 0
xmax = 30
if "GenP_PtLdg_Vs" in histoName:
const= 2.5 #2.0
coeff= 1.0
step = 100
xmin = 0
xmax = 30
if "VtxIso_Vs_RelIso" in histoName:
const= -0.5
coeff= 0.3 #0.4
step = 100
xmin = 0
xmax = 0#3
if "GenP_VisEt_Vs" in histoName or "GenP_PtLdg_Vs" in histoName:
gr = getCustomTGraph(histoName, const, coeff, xmin, xmax, step)
gr.SetLineWidth(3)
gr.Draw("L same")
Verbose("Removing the legend", True)
p.removeLegend()
Verbose("Adding text on canvas", True)
histograms.addText(0.22, 0.89, plots._legendLabels[datasets0], 18)
#histograms.addText(0.5, 0.89, plots._legendLabels[datasets0], 18)
Verbose("Saving the canvas", True)
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, opts.url)
return