def doPlot(mass, name, nuisance, thetas):
f = ROOT.TFile.Open("lands_histograms_hplushadronic_m%d.root" % mass)
h = f.Get(name)
hUp = f.Get("%s_%dUp" % (name, nuisance))
hDown = f.Get("%s_%dDown" % (name, nuisance))
shapes = []
ll = {}
for i, theta in enumerate(thetas):
morphed = doShape(h, hUp, hDown, theta)
shapes.append(histograms.Histo(morphed, "Theta%d" % i, drawStyle="HIST", legendStyle="l"))
ll["Theta%d" % i] = "#theta=%.2f (%.1f)" % (theta, _integral(morphed))
plot = plots.PlotBase(shapes)
plot.histoMgr.forEachHisto(styles.generator())
plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().SetLineWidth(3))
plot.histoMgr.setHistoLegendLabelMany(ll)
plot.setLegend(histograms.createLegend())
plot.createFrame("shape_theta_%s_syst%d_m%d" % (name, nuisance, mass))
plot.frame.GetXaxis().SetTitle("m_{T} (GeV)")
plot.frame.GetYaxis().SetTitle("Rate")
plot.draw()
x = 0.6
size = 20
histograms.addText(x, 0.70, "Sample %s" % name, size=size)
histograms.addText(x, 0.65, "Nuisance %d" % nuisance, size=size)
histograms.addText(x, 0.60, "m_{H^{+}}=%d GeV" % mass, size=size)
plot.save()
f.Close()
def rtauGen(h, name, rebin=2, ratio=False, defaultStyles=True):
if defaultStyles:
h.setDefaultStyles()
h.histoMgr.forEachHisto(styles.generator())
h.histoMgr.forEachHisto(lambda h: h.getRootHisto().Rebin(rebin))
xlabel = "PF E_{T}^{miss} (GeV)"
ylabel = "Events / %.2f" % h.binWidth()
if "LeptonsInMt" in name:
xlabel = "m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})"
ylabel = "Events / %.0f GeV/c^{2}" % h.binWidth()
if "NoLeptonsRealTau" in name:
xlabel = "m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})"
ylabel = "Events / %.0f GeV/c^{2}" % h.binWidth()
if "Mass" in name:
xlabel = "m_{T}(#tau jet, E_{T}^{miss}) (GeV/c^{2})"
ylabel = "Events / %.0f GeV/c^{2}" % h.binWidth()
kwargs = {"ymin": 0.1, "ymax": 1000}
if "LeptonsInMt" in name:
kwargs = {"ymin": 0., "xmax": 300}
if "NoLeptonsRealTau" in name:
kwargs = {"ymin": 0., "xmax": 300}
if "Rtau" in name:
kwargs = {"ymin": 0.0001, "xmax": 1.1}
kwargs = {"ymin": 0.1, "xmax": 1.1}
h.getPad().SetLogy(True)
# kwargs["opts"] = {"ymin": 0, "xmax": 14, "ymaxfactor": 1.1}}
if ratio:
kwargs["opts2"] = {"ymin": 0.5, "ymax": 1.5}
kwargs["createRatio"] = True
# name = name+"_log"
h.createFrame(name, **kwargs)
# histograms.addText(0.65, 0.7, "BR(t #rightarrow bH^{#pm})=0.05", 20)
h.getPad().SetLogy(True)
leg = histograms.createLegend(0.6, 0.75, 0.8, 0.9)
if "LeptonsInMt" in name:
h.getPad().SetLogy(False)
leg = histograms.moveLegend(leg, dx=-0.18)
histograms.addText(0.5, 0.65, "TailKiller cut: Tight", 20)
h.setLegend(leg)
plots._legendLabels["MetNoJetInHole"] = "Jets outside dead cells"
plots._legendLabels["MetJetInHole"] = "Jets within dead cells"
histograms.addText(300, 300, "p_{T}^{jet} > 50 GeV/c", 20)
kwargs["opts2"] = {"ymin": 0.5, "ymax": 1.5}
kwargs["createRatio"] = True
# if ratio:
# h.createFrameFraction(name, opts=opts, opts2=opts2)
# h.setLegend(leg)
common(h, xlabel, ylabel)
def doPlot(legList, graphList, saveName, **kwargs):
# Definitions
hgList = []
lList = {}
# For-loop: All TGraphs
for i, g in enumerate(graphList, 0):
if opts.boldText:
gName = legList[i]
else:
gName = "#font[42]{%s}" % legList[i]
hg = histograms.HistoGraph(graphList[i],
gName,
drawStyle="L",
legendStyle="l")
hgList.append(hg)
# Create a plot-base object
Verbose("Creating the plot-base object", True)
# plot = plots.PlotBase(hgList, saveFormats=[])
hgList.insert(0, hgList.pop(opts.refIndex))
plot = plots.ComparisonManyPlot(hgList[0], hgList[1:], saveFormats=[])
#plot = plots.ComparisonManyPlot(hgList[-1], hgList[:-1], saveFormats=[])
# Apply histo style
Verbose("Applying the histogram styles (generator)", True)
plot.histoMgr.forEachHisto(styles.generator())
# plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().SetMarkerSize(1.2))
# plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().SetLineWidth(3))
def sty(h):
r = h.getRootHisto()
r.SetLineWidth(3)
r.SetMarkerSize(1.2)
return
# Apply style and set label
Verbose("Applying the histogram styles (forEachHisto)", True)
plot.histoMgr.forEachHisto(sty)
if opts.plotType != "var":
plot.setLegendHeader("Sequential Model (Keras)")
# Draw the plot
Verbose("Drawing the plot", True)
plots.drawPlot(plot, saveName, **kwargs)
if opts.removeLegend:
plot.removeLegend()
# Save plots and return
Verbose("Saving the plot as %s" % (saveName), True)
SavePlot(plot, opts.saveDir, saveName, opts.saveFormats)
Verbose(
"Plots saved under directory %s" %
(sh_s + aux.convertToURL(opts.saveDir, opts.url) + sh_n), True)
return
def doPlot2(limits, legendLabels, name):
graphs = [
histograms.HistoGraph(limits[0].expectedGraph(), "Expected", drawStyle="L"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=1), "Expected1", drawStyle="F", legendStyle="fl"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=2), "Expected2", drawStyle="F", legendStyle="fl"),
]
graphs[0].getRootHisto().SetLineStyle(1)
plot = plots.PlotBase(graphs)
ll = {
"Expected": None,
"Expected1": "%s exp. median #pm 1#sigma" % legendLabels[0],
"Expected2": "%s exp. median #pm 2#sigma" % legendLabels[0],
}
stGen = styles.generator()
for i in xrange(1, len(limits)):
gr = histograms.HistoGraph(limits[i].expectedGraph(), "Exp%d"%i, drawStyle="L")
stGen(gr)
gr.getRootHisto().SetLineWidth(3)
gr.getRootHisto().SetLineStyle(1)
plot.histoMgr.insertHisto(len(plot.histoMgr)-2, gr, legendIndex=len(plot.histoMgr))
ll["Exp%d"%i] = "%s exp. median" % legendLabels[i]
plot.histoMgr.setHistoLegendLabelMany(ll)
legend = histograms.moveLegend(histograms.createLegend(0.48, 0.75, 0.85, 0.92), dx=-0.02)
if len(limits[0].getFinalstates()) > 1:
legend = histograms.moveLegend(legend, dy=-0.1)
plot.setLegend(legend)
plot.createFrame(name+"_limits", opts={"ymin": 0, "ymax": limits[0].getFinalstateYmaxBR()})
plot.frame.GetXaxis().SetTitle(limit.mHplus())
plot.frame.GetYaxis().SetTitle(limit.BRlimit)
plot.draw()
plot.setLuminosity(limits[0].getLuminosity())
plot.addStandardTexts(cmsTextPosition="outframe")
size = 20
x = 0.2
histograms.addText(x, 0.88, limit.process, size=size)
histograms.addText(x, 0.84, limits[0].getFinalstateText(), size=size)
histograms.addText(x, 0.79, limit.BRassumption, size=size)
plot.save()
def doPlot(mass, name, nuisance, thetas):
f = ROOT.TFile.Open("lands_histograms_hplushadronic_m%d.root" % mass)
h = f.Get(name)
hUp = f.Get("%s_%dUp" % (name, nuisance))
hDown = f.Get("%s_%dDown" % (name, nuisance))
shapes = []
ll = {}
for i, theta in enumerate(thetas):
morphed = doShape(h, hUp, hDown, theta)
shapes.append(
histograms.Histo(morphed,
"Theta%d" % i,
drawStyle="HIST",
legendStyle="l"))
ll["Theta%d" % i] = "#theta=%.2f (%.1f)" % (theta, _integral(morphed))
plot = plots.PlotBase(shapes)
plot.histoMgr.forEachHisto(styles.generator())
plot.histoMgr.forEachHisto(lambda h: h.getRootHisto().SetLineWidth(3))
plot.histoMgr.setHistoLegendLabelMany(ll)
plot.setLegend(histograms.createLegend())
plot.createFrame("shape_theta_%s_syst%d_m%d" % (name, nuisance, mass))
plot.frame.GetXaxis().SetTitle("m_{T} (GeV)")
plot.frame.GetYaxis().SetTitle("Rate")
plot.draw()
x = 0.6
size = 20
histograms.addText(x, 0.70, "Sample %s" % name, size=size)
histograms.addText(x, 0.65, "Nuisance %d" % nuisance, size=size)
histograms.addText(x, 0.60, "m_{H^{+}}=%d GeV" % mass, size=size)
plot.save()
f.Close()
def doLimitError(limits, unblindedStatus):
expRelErrors = []
expLabels = {}
obsRelErrors = []
obsLabels = {}
order = [0, 1, -1, 2, -2]
expErrors = [limits.expectedErrorGraph(sigma=s) for s in order]
if expErrors[0] != None:
exps = [limits.expectedGraph(sigma=s) for s in order]
expRelErrors = [(limit.divideGraph(expErrors[i], exps[i]), "ExpRelErr%d"%i) for i in xrange(len(exps))]
expLabels = {
"ExpRelErr0": "Expected median",
"ExpRelErr1": "Expected +1#sigma",
"ExpRelErr2": "Expected -1#sigma",
"ExpRelErr3": "Expected +2#sigma",
"ExpRelErr4": "Expected -2#sigma",
}
if unblindedStatus:
obsErr = limits.observedErrorGraph()
if obsErr != None:
obs = limits.observedGraph()
if obs != None:
obsRelErrors = [(limit.divideGraph(obsErr, obs), "ObsRelErr")]
obsLabels = {"ObsRelErr": "Observed"}
if len(expRelErrors) == 0 and len(obsRelErrors) == 0:
return
# Create the plot
plot = plots.PlotBase()
if len(expRelErrors) > 0:
plot.histoMgr.extendHistos([histograms.HistoGraph(x[0], x[1], drawStyle="PL", legendStyle="lp") for x in expRelErrors])
plot.histoMgr.forEachHisto(styles.generator())
def sty(h):
r = h.getRootHisto()
r.SetLineStyle(1)
r.SetLineWidth(3)
r.SetMarkerSize(1.4)
plot.histoMgr.forEachHisto(sty)
plot.histoMgr.setHistoLegendLabelMany(expLabels)
if unblindedStatus:
if len(obsRelErrors) > 0:
obsRelErrors[0][0].SetMarkerSize(1.4)
obsRelErrors[0][0].SetMarkerStyle(25)
plot.histoMgr.insertHisto(0, histograms.HistoGraph(obsRelErrors[0][0], obsRelErrors[0][1], drawStyle="PL", legendStyle="lp"))
plot.histoMgr.setHistoLegendLabelMany(obsLabels)
plot.setLegend(histograms.moveLegend(histograms.createLegend(0.48, 0.75, 0.85, 0.92), dx=0.1, dy=-0.1))
if len(limits.mass) == 1:
plot.createFrame("limitsBrRelativeUncertainty", opts={"xmin": limits.mass[0]-5.0, "xmax": limits.mass[0]+5.0, "ymin": 0, "ymaxfactor": 1.5})
else:
plot.createFrame("limitsBrRelativeUncertainty", opts={"ymin": 0, "ymaxfactor": 1.5})
plot.frame.GetXaxis().SetTitle(limit.mHplus())
plot.frame.GetYaxis().SetTitle("Uncertainty/limit")
plot.draw()
plot.setLuminosity(limits.getLuminosity())
plot.addStandardTexts()
size = 20
x = 0.2
histograms.addText(x, 0.88, limit.process, size=size)
histograms.addText(x, 0.84, limits.getFinalstateText(), size=size)
histograms.addText(x, 0.79, limit.BRassumption, size=size)
size = 22
x = 0.55
histograms.addText(x, 0.88, "Toy MC relative", size=size)
histograms.addText(x, 0.84, "statistical uncertainty", size=size)
plot.save()
def doPlot(mass, mu, mul=None):
f = openFile(mass)
tree_obs = f.Get("TESTED_R%s"%mu)
if not tree_obs:
print "Did not find TESTED_R%s TTree in file %s" % (mu, f.GetName())
listMu(mass, f)
f.Close()
return
tree_sb = f.Get("SAMPLING_SB_TESTED_R%s" % mu)
if not tree_sb:
raise Exception("Did not find SAMPLING_SB_TESTED_R%s from file %s" % (mu, f.GetName()))
tree_b = f.Get("SAMPLING_B_TESTED_R%s" % mu)
if not tree_b:
raise Exception("Did not find SAMPLING_B_TESTED_R%s from file %s" % (mu, f.GetName()))
xmin = min(tree_sb.GetMinimum("brT"), tree_b.GetMinimum("brT"))
xmax = max(tree_sb.GetMaximum("brT"), tree_b.GetMaximum("brT"))
obsval = tree_obs.GetMinimum("brT")
# Get the distributions
tree_sb.Draw("brT >>hsb(%d, %f, %f)" % (nbins, xmin, xmax), "", "goff")
h_sb = tree_sb.GetHistogram()
tree_b.Draw("brT >>hb(%d, %f, %f)" % (nbins, xmin, xmax), "", "goff")
h_b = tree_b.GetHistogram()
# Set obsval to bin boundary
obsval_bin = obsval
for bin in xrange(0, h_sb.GetNbinsX()+1):
edge = h_sb.GetBinLowEdge(bin)
if obsval > edge:
obsval_bin = edge
# Normalize the distributions to unit area
dataset._normalizeToOne(h_sb)
dataset._normalizeToOne(h_b)
plot = plots.PlotBase([
histograms.Histo(h_b, "B"),
histograms.Histo(h_sb, "SB")
])
mulegend = mul
if mul == None:
mulegend = mu
plot.histoMgr.setHistoLegendLabelMany({
"B": "f(#tilde{q}_{#mu=%s} | #mu=0, #hat{#bf{#theta}}_{0}^{obs})" % mulegend,
"SB": "f(#tilde{q}_{#mu=%s} | #mu=%s, #hat{#bf{#theta}}_{#mu=%s}^{obs})" % (mulegend, mulegend, mulegend),
})
plot.setLegend(histograms.moveLegend(histograms.createLegend(0.6, 0.8, 0.9, 0.9), dy=0.02, dx=-0.05))
plot.histoMgr.forEachHisto(styles.generator())
fname = "teststat_m%s_mu%s" % (mass, mu)
plot.createFrame(fname.replace(".", "_"), opts={"ymin": 1e-6, "ymaxfactor": 2})
plot.frame.GetXaxis().SetTitle("Test statistic #tilde{q}_{#mu}")
plot.frame.GetYaxis().SetTitle("Arbitrary units")
plot.getPad().SetLogy(True)
area_sb = h_sb.Clone("AreaSB")
area_sb.SetFillColor(area_sb.GetLineColor())
area_sb.SetFillStyle(3005)
area_sb.SetLineWidth(0)
area_b = h_b.Clone("AreaB")
area_b.SetFillColor(area_b.GetLineColor())
area_b.SetFillStyle(3004)
area_b.SetLineWidth(0)
for bin in xrange(0, area_sb.GetNbinsX()+1):
if area_sb.GetBinLowEdge(bin) < obsval_bin:
area_sb.SetBinContent(bin, 0)
if area_b.GetBinLowEdge(bin) >= obsval_bin:
area_b.SetBinContent(bin, 0)
plot.appendPlotObject(area_b, "HIST ][")
plot.appendPlotObject(area_sb, "HIST ][")
plot.addCutBoxAndLine(box=False, cutValue=obsval_bin)
plot.draw()
size = 26
histograms.addText(0.35, 0.4, "CL_{s+b}", size=size)
histograms.addText(0.18, 0.4, "1-CL_{b}", size=size)
size = 20
# x = obsval_bin/(plot.frame.GetXaxis().GetXmax() - plot.frame.GetXaxis().GetXmin())+0.02
x = (obsval_bin - plot.getPad().GetX1()) / (plot.getPad().GetX2() - plot.getPad().GetX1())
x += 0.01
histograms.addText(x, 0.88, "Observed", size=size)
histograms.addText(x, 0.85, "value", size=size)
histograms.addText(0.62, 0.78, "m_{H^{+}} = %s %s" % (mass, limit.massUnit()), size=size)
# size = 20
# x = 0.2
# histograms.addText(x, 0.88, brlimit.process, size=size)
# histograms.addText(x, 0.84, brlimit._finalstateLabels["taujets"], size=size)
# histograms.addText(x, 0.79, brlimit.BRassumption, size=size)
plot.save()
f.Close()
def doLimitError(limits, unblindedStatus):
expRelErrors = []
expLabels = {}
obsRelErrors = []
obsLabels = {}
order = [0, 1, -1, 2, -2]
expErrors = [limits.expectedErrorGraph(sigma=s) for s in order]
if expErrors[0] != None:
exps = [limits.expectedGraph(sigma=s) for s in order]
expRelErrors = [(limit.divideGraph(expErrors[i],
exps[i]), "ExpRelErr%d" % i)
for i in xrange(len(exps))]
expLabels = {
"ExpRelErr0": "Expected median",
"ExpRelErr1": "Expected +1#sigma",
"ExpRelErr2": "Expected -1#sigma",
"ExpRelErr3": "Expected +2#sigma",
"ExpRelErr4": "Expected -2#sigma",
}
if unblindedStatus:
obsErr = limits.observedErrorGraph()
if obsErr != None:
obs = limits.observedGraph()
if obs != None:
obsRelErrors = [(limit.divideGraph(obsErr, obs), "ObsRelErr")]
obsLabels = {"ObsRelErr": "Observed"}
if len(expRelErrors) == 0 and len(obsRelErrors) == 0:
return
# Create the plot
plot = plots.PlotBase()
if len(expRelErrors) > 0:
plot.histoMgr.extendHistos([
histograms.HistoGraph(x[0], x[1], drawStyle="PL", legendStyle="lp")
for x in expRelErrors
])
plot.histoMgr.forEachHisto(styles.generator())
def sty(h):
r = h.getRootHisto()
r.SetLineStyle(1)
r.SetLineWidth(3)
r.SetMarkerSize(1.4)
plot.histoMgr.forEachHisto(sty)
plot.histoMgr.setHistoLegendLabelMany(expLabels)
if unblindedStatus:
if len(obsRelErrors) > 0:
obsRelErrors[0][0].SetMarkerSize(1.4)
obsRelErrors[0][0].SetMarkerStyle(25)
plot.histoMgr.insertHisto(
0,
histograms.HistoGraph(obsRelErrors[0][0],
obsRelErrors[0][1],
drawStyle="PL",
legendStyle="lp"))
plot.histoMgr.setHistoLegendLabelMany(obsLabels)
plot.setLegend(
histograms.moveLegend(histograms.createLegend(0.48, 0.75, 0.85, 0.92),
dx=0.1,
dy=-0.1))
if len(limits.mass) == 1:
plot.createFrame("limitsBrRelativeUncertainty",
opts={
"xmin": limits.mass[0] - 5.0,
"xmax": limits.mass[0] + 5.0,
"ymin": 0,
"ymaxfactor": 1.5
})
else:
plot.createFrame("limitsBrRelativeUncertainty",
opts={
"ymin": 0,
"ymaxfactor": 1.5
})
plot.frame.GetXaxis().SetTitle(limit.mHplus())
plot.frame.GetYaxis().SetTitle("Uncertainty/limit")
plot.draw()
plot.setLuminosity(limits.getLuminosity())
plot.addStandardTexts()
size = 20
x = 0.2
histograms.addText(x, 0.88, limit.process, size=size)
histograms.addText(x, 0.84, limits.getFinalstateText(), size=size)
histograms.addText(x, 0.79, limit.BRassumption, size=size)
size = 22
x = 0.55
histograms.addText(x, 0.88, "Toy MC relative", size=size)
histograms.addText(x, 0.84, "statistical uncertainty", size=size)
plot.save()
def doPlotSigmaBands(limits, legendLabels, saveName, _opts={}):
# Define graphs to be used
graphs = [
histograms.HistoGraph(limits[0].expectedGraph(),
"Expected",
drawStyle="L"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=1),
"Expected1",
drawStyle="F",
legendStyle="fl"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=2),
"Expected2",
drawStyle="F",
legendStyle="fl"),
]
# Set line style
graphs[0].getRootHisto().SetLineStyle(ROOT.kSolid)
# Create plot base object
plot = plots.PlotBase(graphs)
ll = {
"Expected": None,
"Expected1": "%s #pm 1#sigma" % legendLabels[0],
"Expected2": "%s #pm 2#sigma" % legendLabels[0],
#"Expected1": "%s exp. median #pm 1#sigma" % legendLabels[0],
#"Expected2": "%s exp. median #pm 2#sigma" % legendLabels[0],
}
stGen = styles.generator()
nLimits = len(limits)
# For-loop: All limits
for i in xrange(1, nLimits):
name = "Exp%d" % i
gr = histograms.HistoGraph(limits[i].expectedGraph(),
name,
drawStyle="L")
stGen(gr)
gr.getRootHisto().SetLineWidth(3)
gr.getRootHisto().SetLineStyle(1)
plot.histoMgr.insertHisto(len(plot.histoMgr) - 2,
gr,
legendIndex=len(plot.histoMgr))
ll[name] = "%s" % legendLabels[i] # "%s exp. median" % legendLabels[i]
# Set histo labels
plot.histoMgr.setHistoLegendLabelMany(ll)
# Create & set legend
nGraphs = len(graphs)
# If sigma bands are drawn each legend entry is plotted twice. Correct this in the count
if "Sigma1" in name or "Sigma2" in name:
nGraphs = nGraphs / 2.0
legend = getLegend(nGraphs + 4, limit, xPosLeg)
plot.setLegend(legend)
# Determine save name, minimum and maximum of y-axis
ymin, ymax, saveName = getYMinMaxAndName(limits, saveName)
if _opts.yMin == -1:
_opts.yMin = ymin
if _opts.yMax == -1:
_opts.yMax = ymax
# Create the frame and set axes titles
plot.createFrame(saveName, opts={"ymin": _opts.yMin, "ymax": _opts.yMax})
# Add cut line?
if _opts.cutLine != 999.9:
kwargs = {"greaterThan": True}
plot.addCutBoxAndLine(cutValue=_opts.cutLine,
fillColor=ROOT.kRed,
box=False,
line=True,
**kwargs)
if opts.cutLineY != 999.9:
kwargs = {
"greaterThan": True,
"mainCanvas": True,
"ratioCanvas": False
}
plot.addCutBoxAndLineY(cutValue=_opts.cutLineY,
fillColor=ROOT.kRed,
box=False,
line=True,
**kwargs)
# Set axes titles
plot.frame.GetXaxis().SetTitle(limit.mHplus())
plot.frame.GetYaxis().SetTitle(limit.BRlimit)
# Enable/Disable logscale for axes
ROOT.gPad.SetLogy(_opts.logY)
ROOT.gPad.SetLogx(_opts.logX)
# Draw the plot with standard texts
plot.draw()
plot.addStandardTexts(cmsTextPosition="outframe")
plot.setLuminosity(limits[0].getLuminosity())
addPhysicsText(histograms, limit, x=xPosText)
# Save the plots & return
SavePlot(plot, _opts.saveDir, saveName, [".png"]) #, ".pdf"])
return
def doPlot2(limits, legendLabels, name):
graphs = [
histograms.HistoGraph(limits[0].expectedGraph(),
"Expected",
drawStyle="L"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=1),
"Expected1",
drawStyle="F",
legendStyle="fl"),
histograms.HistoGraph(limits[0].expectedBandGraph(sigma=2),
"Expected2",
drawStyle="F",
legendStyle="fl"),
]
graphs[0].getRootHisto().SetLineStyle(1)
plot = plots.PlotBase(graphs)
ll = {
"Expected": None,
"Expected1": "%s exp. median #pm 1#sigma" % legendLabels[0],
"Expected2": "%s exp. median #pm 2#sigma" % legendLabels[0],
}
stGen = styles.generator()
for i in xrange(1, len(limits)):
gr = histograms.HistoGraph(limits[i].expectedGraph(),
"Exp%d" % i,
drawStyle="L")
stGen(gr)
gr.getRootHisto().SetLineWidth(3)
gr.getRootHisto().SetLineStyle(1)
plot.histoMgr.insertHisto(len(plot.histoMgr) - 2,
gr,
legendIndex=len(plot.histoMgr))
ll["Exp%d" % i] = "%s exp. median" % legendLabels[i]
plot.histoMgr.setHistoLegendLabelMany(ll)
legend = histograms.moveLegend(histograms.createLegend(
0.48, 0.75, 0.85, 0.92),
dx=-0.02)
if len(limits[0].getFinalstates()) > 1:
legend = histograms.moveLegend(legend, dy=-0.1)
plot.setLegend(legend)
plot.createFrame(name + "_limits",
opts={
"ymin": 0,
"ymax": limits[0].getFinalstateYmaxBR()
})
plot.frame.GetXaxis().SetTitle(limit.mHplus())
plot.frame.GetYaxis().SetTitle(limit.BRlimit)
plot.draw()
plot.setLuminosity(limits[0].getLuminosity())
plot.addStandardTexts(cmsTextPosition="outframe")
size = 20
x = 0.2
histograms.addText(x, 0.88, limit.process, size=size)
histograms.addText(x, 0.84, limits[0].getFinalstateText(), size=size)
histograms.addText(x, 0.79, limit.BRassumption, size=size)
plot.save()
def doPlot(mass, mu, mul=None):
f = openFile(mass)
tree_obs = f.Get("TESTED_R%s" % mu)
if not tree_obs:
print "Did not find TESTED_R%s TTree in file %s" % (mu, f.GetName())
listMu(mass, f)
f.Close()
return
tree_sb = f.Get("SAMPLING_SB_TESTED_R%s" % mu)
if not tree_sb:
raise Exception("Did not find SAMPLING_SB_TESTED_R%s from file %s" %
(mu, f.GetName()))
tree_b = f.Get("SAMPLING_B_TESTED_R%s" % mu)
if not tree_b:
raise Exception("Did not find SAMPLING_B_TESTED_R%s from file %s" %
(mu, f.GetName()))
xmin = min(tree_sb.GetMinimum("brT"), tree_b.GetMinimum("brT"))
xmax = max(tree_sb.GetMaximum("brT"), tree_b.GetMaximum("brT"))
obsval = tree_obs.GetMinimum("brT")
# Get the distributions
tree_sb.Draw("brT >>hsb(%d, %f, %f)" % (nbins, xmin, xmax), "", "goff")
h_sb = tree_sb.GetHistogram()
tree_b.Draw("brT >>hb(%d, %f, %f)" % (nbins, xmin, xmax), "", "goff")
h_b = tree_b.GetHistogram()
# Set obsval to bin boundary
obsval_bin = obsval
for bin in xrange(0, h_sb.GetNbinsX() + 1):
edge = h_sb.GetBinLowEdge(bin)
if obsval > edge:
obsval_bin = edge
# Normalize the distributions to unit area
dataset._normalizeToOne(h_sb)
dataset._normalizeToOne(h_b)
plot = plots.PlotBase(
[histograms.Histo(h_b, "B"),
histograms.Histo(h_sb, "SB")])
mulegend = mul
if mul == None:
mulegend = mu
plot.histoMgr.setHistoLegendLabelMany({
"B":
"f(#tilde{q}_{#mu=%s} | #mu=0, #hat{#bf{#theta}}_{0}^{obs})" %
mulegend,
"SB":
"f(#tilde{q}_{#mu=%s} | #mu=%s, #hat{#bf{#theta}}_{#mu=%s}^{obs})" %
(mulegend, mulegend, mulegend),
})
plot.setLegend(
histograms.moveLegend(histograms.createLegend(0.6, 0.8, 0.9, 0.9),
dy=0.02,
dx=-0.05))
plot.histoMgr.forEachHisto(styles.generator())
fname = "teststat_m%s_mu%s" % (mass, mu)
plot.createFrame(fname.replace(".", "_"),
opts={
"ymin": 1e-6,
"ymaxfactor": 2
})
plot.frame.GetXaxis().SetTitle("Test statistic #tilde{q}_{#mu}")
plot.frame.GetYaxis().SetTitle("Arbitrary units")
plot.getPad().SetLogy(True)
area_sb = h_sb.Clone("AreaSB")
area_sb.SetFillColor(area_sb.GetLineColor())
area_sb.SetFillStyle(3005)
area_sb.SetLineWidth(0)
area_b = h_b.Clone("AreaB")
area_b.SetFillColor(area_b.GetLineColor())
area_b.SetFillStyle(3004)
area_b.SetLineWidth(0)
for bin in xrange(0, area_sb.GetNbinsX() + 1):
if area_sb.GetBinLowEdge(bin) < obsval_bin:
area_sb.SetBinContent(bin, 0)
if area_b.GetBinLowEdge(bin) >= obsval_bin:
area_b.SetBinContent(bin, 0)
plot.appendPlotObject(area_b, "HIST ][")
plot.appendPlotObject(area_sb, "HIST ][")
plot.addCutBoxAndLine(box=False, cutValue=obsval_bin)
plot.draw()
size = 26
histograms.addText(0.35, 0.4, "CL_{s+b}", size=size)
histograms.addText(0.18, 0.4, "1-CL_{b}", size=size)
size = 20
# x = obsval_bin/(plot.frame.GetXaxis().GetXmax() - plot.frame.GetXaxis().GetXmin())+0.02
x = (obsval_bin - plot.getPad().GetX1()) / (plot.getPad().GetX2() -
plot.getPad().GetX1())
x += 0.01
histograms.addText(x, 0.88, "Observed", size=size)
histograms.addText(x, 0.85, "value", size=size)
histograms.addText(0.62,
0.78,
"m_{H^{+}} = %s %s" % (mass, limit.massUnit()),
size=size)
# size = 20
# x = 0.2
# histograms.addText(x, 0.88, brlimit.process, size=size)
# histograms.addText(x, 0.84, brlimit._finalstateLabels["taujets"], size=size)
# histograms.addText(x, 0.79, brlimit.BRassumption, size=size)
plot.save()
f.Close()
