def Create_Legend(x1,
y1,
x2,
y2,
font=42,
text_size=0.045,
fill=0,
border_size=1,
entry_sep=0,
margin=0.3,
show_stats=False,
ncols=1):
leg = TLegend(x1, y1, x2, y2)
leg.SetTextFont(font)
leg.SetTextSize(text_size)
leg.SetFillColor(fill)
leg.SetBorderSize(border_size)
leg.SetEntrySeparation(entry_sep)
leg.SetMargin(margin)
leg.SetNColumns(ncols)
if show_stats:
leg.SetNColumns(2)
## Creating headers for the legend
leg.AddEntry(0, "", "")
# leg.AddEntry( 0, "#bf{Mean}", "")
leg.AddEntry(0, "#bf{RMSE}", "")
return leg
def SetLegendRatio(self): legr = TLegend(self.legratx0, self.legraty0, self.legratx1, self.legraty1) legr.SetTextSize(self.legratTextSize) legr.SetBorderSize(0) legr.SetFillColor(10) legr.SetNColumns(self.legratNcol) return legr
def doSuperTGraph( data, canvas, obj):
xmin=-1.8
xmax=1.8
gStyle.SetOptFit(0)
gStyle.SetOptStat(0)
gROOT.SetBatch(1)
color=[601,417,920,633,910,433,400,619,1,922]
mg = TMultiGraph();
leg = TLegend(0.58,0.75,0.89,0.89);
i=0
for ivar in data['var']:
if not os.path.exists(data['fold']+"/"+ivar+"_ll.root"):
continue
print '>>> Opening File :' , data['fold']+"/"+ivar+"_ll.root"
inFile = TFile.Open ( data['fold']+"/"+ivar+"_ll.root" ," READ ")
c1 = inFile.Get(canvas);
gr = c1.GetListOfPrimitives().FindObject(obj)
xaxis = gr.GetXaxis().GetTitle()
yaxis = gr.GetYaxis().GetTitle()
gr.SetLineColor(color[i])
mg.Add(gr)
leg.AddEntry(gr,ivar,"l")
i=i+1
print i
c = TCanvas()
c.cd()
c.SetGrid()
mg.Draw("al")
line1 = TF1("line1","pol0",-100,100)
line1.FixParameter(0,1.)
line1.SetLineWidth(2)
line1.SetLineStyle(2)
line1.SetLineColor(2)
line1.Draw("same")
line2 = TF1("line2","pol0",-100,100)
line2.FixParameter(0,3.84)
line2.SetLineWidth(2)
line2.SetLineStyle(2)
line2.SetLineColor(2)
line2.Draw("same")
mg.SetTitle(";" +xaxis+";" +yaxis)
mg.GetYaxis().SetRangeUser(0,10)
leg.SetNColumns(2)
leg.SetBorderSize(0)
leg.Draw("same")
c.SaveAs(data['fold']+"combined10.png")
c.SaveAs(data['fold']+"combined10.pdf")
c.SaveAs(data['fold']+"combined10.root")
def SetLegend(self):
leg = TLegend(self.legx0, self.legy0, self.legx1, self.legy1)
leg.SetTextSize(self.legTextSize)
leg.SetBorderSize(0)
leg.SetFillColor(10)
leg.SetNColumns(self.legNcol)
return leg
def make_photon_fraction_plot(f_base, f_nightly, result_file):
"""
This functions created a photon validation plot with efficiencies
and fractions
:param f_base TFile with the baseline histograms:
:param f_nightly TFile with the nightly histograms:
"""
for histo in get_key_names(f_nightly, 'truthPhotonConvRecoConvEfficiency'):
variable_name = histo.split("_", 1)[1]
c1 = TCanvas()
leg = TLegend(0.1, 0.75, 0.9, 0.9)
leg.SetNColumns(2)
for i, folder in enumerate(photon_fraction_list):
baseline = f_base.Get(folder['name'] + '/' + folder['name'] + "_" +
variable_name)
baseline.SetDirectory(0)
nightly = f_nightly.Get(folder['name'] + '/' + folder['name'] +
"_" + variable_name)
nightly.SetDirectory(0)
baseline.SetMinimum(
min(baseline.GetMinimum(), baseline.GetMinimum()) * 0.7)
baseline.SetMaximum(
max(baseline.GetMaximum(), baseline.GetMaximum()) * 1.3)
baseline.GetYaxis().SetTitle("Efficiency and fraction")
baseline.SetLineColor(folder['color'])
nightly.SetLineColor(folder['color'])
baseline.SetMarkerColor(folder['color'])
nightly.SetMarkerColor(folder['color'])
baseline.SetMarkerStyle(1)
nightly.SetMarkerStyle(20)
leg.AddEntry(nightly, folder['title'], "p")
if i == 0:
baseline.Draw("hist ")
else:
baseline.Draw("same hist")
nightly.Draw("p same")
leg.Draw()
c1.Update()
result_file.cd()
c1.SaveAs("ConvertionEff_" + variable_name + ".png")
c1.Write("ConvertionEff_" + variable_name)
def draw_nice_legend(x=[0.7, 0.92], y=[0.7, 0.92], tit="", columns=1):
global nice_legends
leg = TLegend(x[0], y[0], x[1], y[1], tit)
leg.SetLineColor(0)
leg.SetNColumns(columns)
nice_legends.append(leg)
leg.Draw()
return leg
def drawNorm():
hists = allHists()
os.mkdir("plots/%s_norm" % region)
for variable in variables:
hist_data = hists[region + "_" + variable + "_data"]
hist_signal = hists[region + "_" + variable + "_tth"]
mchists = {}
for i in processes:
if i != 'data' and i != 'tth':
temp = hists[region + "_" + variable + "_" + i]
mchists[i] = temp
hs = makeStack(mchists)
h_bkg = hs.GetStack().Last().Clone("h_bkg")
c = createCanvas()
XTitle, YTitle = (titles[variable[0:len(variable) - 2]])[0], (
titles_norm[variable[0:len(variable) - 2]])[1]
leg = TLegend(0.60, 0.70, 0.90, 0.90)
leg.SetNColumns(2)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.AddEntry(hist_data, "data", "pe")
leg.AddEntry(hist_signal, "tth", "l")
#normalize individual hist
mchists_norm = {}
for i in mchists:
mchists[i].Scale(1. / h_bkg.Integral())
mchists_norm[i] = mchists[i]
hs_norm = makeStack(mchists_norm)
for i in mchists:
leg.AddEntry(mchists_norm[i], i, "f")
leg.AddEntry(h_bkg, "uncertainty", 'f')
#draw
hs_norm.SetTitle("")
hs_norm.SetMaximum(3 *
hist_data.GetBinContent(hist_data.GetMaximumBin()) /
hist_data.Integral())
hs_norm.Draw("hist")
hs_norm.GetYaxis().SetTitleSize(0.06)
hs_norm.GetYaxis().SetTitleOffset(1)
hs_norm.GetYaxis().SetTitle(YTitle)
hs_norm.GetXaxis().SetTitle(XTitle)
#hs_norm.GetXaxis().SetTitleSize(0.)
#hs_norm.GetXaxis().SetLabelSize(0.)
h_bkg.SetFillStyle(3253)
h_bkg.SetFillColor(13)
h_bkg.SetLineColor(13)
h_bkg.DrawNormalized("E2 same")
hist_data.SetMarkerStyle(20)
hist_data.SetMarkerSize(0.8)
#hist_data.SetLineColor(kBlack)
hist_data.DrawNormalized("e x0 same")
hist_signal.SetLineColor(kRed)
hist_signal.SetLineStyle(kDashed)
hist_signal.DrawNormalized("hist same")
createLabels()
leg.Draw("same")
c.SaveAs("plots/%s_norm/%s.pdf" % (region, variable))
def doSuperTGraphAll( file_list, canvas, obj, output):
gStyle.SetOptFit(0)
gStyle.SetOptStat(0)
gROOT.SetBatch(1)
mg = TMultiGraph();
leg = TLegend(0.58,0.75,0.89,0.89);
for iFile in file_list:
if not os.path.exists(iFile['path']):
print '>>> This File does not exist --> '+iFile['path']+'... check path ... '
continue
print '>>> Opening File :' , iFile['path']
inFile = TFile.Open ( iFile['path'] ," READ ")
c1 = inFile.Get(canvas);
gr = c1.GetListOfPrimitives().FindObject(obj)
xaxis = gr.GetXaxis().GetTitle()
yaxis = gr.GetYaxis().GetTitle()
gr.SetLineColor(iFile['color'])
mg.Add(gr)
leg.AddEntry(gr,iFile['legend'],"l")
c = TCanvas()
c.cd()
c.SetGrid()
mg.Draw("al")
line1 = TF1("line1","pol0",-100,100)
line1.FixParameter(0,1.)
line1.SetLineWidth(2)
line1.SetLineStyle(2)
line1.SetLineColor(2)
line1.Draw("same")
line2 = TF1("line2","pol0",-100,100)
line2.FixParameter(0,3.84)
line2.SetLineWidth(2)
line2.SetLineStyle(2)
line2.SetLineColor(2)
line2.Draw("same")
mg.SetTitle(";" +xaxis+";" +yaxis)
mg.GetYaxis().SetRangeUser(0,10)
leg.SetNColumns(2)
leg.SetBorderSize(0)
leg.Draw("same")
c.SaveAs(output+"10.png")
c.SaveAs(output+"10.pdf")
c.SaveAs(output+"10.root")
def Draw(self):
canvas=TCanvas(self.name+'canvas','')
canvas.Print('picture/'+self.name+'.pdf[')
j=0
text_name=''
textvalue=''
if(self.ValueName1=='colrow'):
text_name='(col, row)'
else:
text_name=self.ValueName1
text2_name=''
text2value=''
if(self.ValueName2=='colrow'):
#text2_name='#splitline{pixel coordinates}{(col,row)}'
text2_name='pixel(column,row)'
else:
text2_name=self.ValueName2
for graph_list_1 in self.graph_list:
legend=TLegend(self.legend_xl,self.legend_yb,self.legend_xr,self.legend_yt,text2_name)
legend.SetNColumns(self.legend_Col)
legend.SetBorderSize(self.legend_Border)
i=1
for pixel_graph in graph_list_1:
graph=pixel_graph.CreateGraph()
graph.SetLineColor(i)
graph.SetMarkerColor(i)
graph.SetMarkerStyle(8)
if(self.ValueName2=='colrow'):
text2value='('+str(int(self.Value3List[j][i-1]/1000))+', '+str(self.Value3List[j][i-1]%1000)+')'
else:
text2value=str(self.Value3List[j][i-1])
legend.AddEntry(graph,text2value,'lp')
canvas.cd()
if i == 1 :
#graph.Draw("APL")
graph.Draw("AP")
else :
#graph.Draw("PL")
graph.Draw("P")
i=i+1
legend.Draw('same')
if(self.ValueName1=='colrow'):
textvalue='('+str(int(self.Value1List[j]/1000))+', '+str(self.Value1List[j]%1000)+')'
else:
textvalue=str(self.Value1List[j])
text=ROOT.TText(0.18,0.83,text_name+'='+textvalue)
text.SetTextFont(62)
text.SetNDC(1)
text.Draw()
canvas.Print('picture/'+self.name+'.pdf')
j=j+1
canvas.Print('picture/'+self.name+'.pdf]')
def makeLowerLegend(obs_over_pred, relative_bkg_stat_unc,
relative_bkg_total_unc):
legend = TLegend(0.18, 0.85, 0.94, 0.98, '', 'brNDC')
legend.SetNColumns(3)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.AddEntry(relative_bkg_stat_unc, 'Stat. pred. unc.', 'f')
legend.AddEntry(relative_bkg_total_unc, 'Total pred. unc.', 'f')
legend.AddEntry(obs_over_pred, 'Obs./Pred.', 'pe12')
return legend
def correctedCrossSectionsPlot(crossings, shapes, overDiff):
uncorrected = {41: (3.2575816286, 0.00514858611944), \
281: (3.26316215713, 0.00468789412223), \
872: (3.27340775031, 0.00484925398906), \
1783: (3.24986926821, 0.00460908436455), \
2063: (3.26363843728, 0.0044071069983)}
multi = TMultiGraph('sigmavis', '')
graphs = []
n = len(shapes) + 1
for i, shape in enumerate([''] + list(shapes)):
xval = array('d',
[a + 0.08 * (i - 0.5 * n) for a in range(len(crossings))])
xerr = array('d', len(crossings) * [0])
yval = array('d', [uncorrected[int(bx)][0] for bx in crossings])
yerr = array('d', [uncorrected[int(bx)][1] for bx in crossings])
if shape:
for j, bx in enumerate(crossings):
yval[j] *= 1 + overDiff[shape][bx]
yerr[j] *= 1 + overDiff[shape][bx]
graph = TGraphErrors(len(crossings), xval, yval, xerr, yerr)
graph.SetName('ge' + shape)
graph.SetMarkerStyle(20)
graph.SetMarkerColor(1 + i)
multi.Add(graph)
graphs.append(graph)
gStyle.SetOptStat(0)
hist = TH2F('hist', '', len(crossings), -0.5,
len(crossings) - 0.5, 100, 3.23, 3.33)
for i, bx in enumerate(crossings):
hist.GetXaxis().SetBinLabel(i + 1, bx)
canvas = TCanvas('c_' + multi.GetName(), '', 600, 600)
hist.Draw('AXIS')
multi.Draw('P')
canvas.Update()
hist.GetXaxis().SetLabelSize(0.035)
hist.GetXaxis().SetNdivisions(len(crossings), False)
hist.GetYaxis().SetTitle('#sigma_{vis} [b]')
hist.GetYaxis().SetLabelSize(0.025)
hist.GetYaxis().SetTitleOffset(1.3)
leg = TLegend(0.15, 0.82, 0.85, 0.85)
leg.SetNColumns(len(shapes) + 1)
leg.SetBorderSize(0)
for i, shape in enumerate([''] + list(shapes)):
entry = leg.AddEntry('ge' + shape, shapeNames[shape], 'P')
entry.SetMarkerStyle(20)
entry.SetMarkerColor(1 + i)
leg.Draw()
drawCMS()
canvas.Modified()
canvas.Update()
canvas.SaveAs('summaryPlots/' + canvas.GetName() + '.pdf')
canvas.SaveAs('summaryPlots/' + canvas.GetName() + '.C')
def myLegend(coordinate=[0.48, 0.55, 0.97, 0.87], ncol=1):
co = coordinate
leg = TLegend(co[0], co[1], co[2], co[3])
leg.SetNColumns(ncol)
leg.SetBorderSize(0)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.035)
return leg
def SetLegend(coordinate_=[.15, .7, .47, .87], ncol=1):
c_ = coordinate_
legend = TLegend(c_[0], c_[1], c_[2], c_[3])
legend.SetBorderSize(0)
legend.SetNColumns(ncol)
legend.SetLineColor(1)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.05)
return legend
def create_legend(self, models):
"""Add a legend with the model names to the plot."""
l = TLegend(0.15, 0.77, 0.85, 0.83)
l.SetNColumns(3)
l.SetBorderSize(0)
for mod, gr, mark, clr in zip(models, self._multi.GetListOfGraphs(),
self.markers, self.colors):
gr.SetMarkerStyle(mark)
gr.SetMarkerColor(clr)
entry = l.AddEntry(gr.GetName(), mod, 'P')
entry.SetMarkerStyle(mark)
entry.SetMarkerColor(clr)
self.add(l)
return l
def makeUpperLegend(data,
processCollection,
bkg_total,
legend_names=None,
draw_signal=False,
signal_legend_names=None):
legend = TLegend(0.25, 0.73, 0.87, 0.92, '', 'brNDC')
legend.SetNColumns(3) if draw_signal else legend.SetNColumns(2)
legend.SetFillStyle(0) #avoid box
legend.SetBorderSize(0)
legend.AddEntry(data, 'Data', 'pe1')
for p in processCollection:
if p.isSignal(): continue
addProcessToLegend(legend, p, 'f', legend_names)
legend.AddEntry(bkg_total, 'Total bkg. unc.', 'f')
if draw_signal:
for s in processCollection.signals():
addProcessToLegend(legend, s, 'l', signal_legend_names)
return legend
def drawHisto(h1, h2, name, var):
#gStyle.SetOptStat(0000)
name = os.path.join('inVarPlots/', name)
h1.SetMarkerStyle(20)
h1.SetMarkerColor(kBlue)
h1.SetLineColor(kBlue)
h1.SetLineWidth(2)
h2.SetMarkerStyle(20)
h2.SetMarkerColor(kRed)
h2.SetLineColor(kRed)
h2.SetLineWidth(2)
h1.GetXaxis().SetTitle(var)
h1.Scale(41.5)
if h1.Integral() != 0 and h2.Integral() != 0:
h2.Scale(h1.Integral() / h2.Integral())
h2.GetXaxis().SetTitle(var)
leg = TLegend(0.455, 0.85, 0.76, 0.89, "", "brNDC")
leg.SetBorderSize(0)
leg.SetTextSize(0.035)
leg.SetFillColor(0)
leg.SetNColumns(2)
leg.AddEntry(h1, "w/ weights", "L")
leg.AddEntry(h2, "w/o weights", "L")
maximum = h1.GetMaximum()
if h2.GetMaximum() >= maximum:
maximum = h2.GetMaximum()
maximum *= 1.01
h2.GetYaxis().SetRangeUser(0., maximum)
c = TCanvas()
h2.Draw("HIST")
h1.Draw("HIST,same")
leg.Draw("same")
c.SaveAs(name + ".png", "png")
c.SaveAs(name + ".pdf", "pdf")
h2.GetYaxis().SetRangeUser(0.001, maximum * 5.)
c.SetLogy()
h2.Draw("HIST")
h1.Draw("HIST,same")
leg.Draw("same")
c.SaveAs(name + "_log.png", "png")
c.SaveAs(name + "_log.pdf", "pdf")
def setup_canvas(hist_name):
canvas = TCanvas(hist_name, hist_name, 0, 0, 800, 800)
canvas.SetMargin(0.13, 0.05, 0.12, 0.05)
canvas.SetTicks(1, 1)
leg = TLegend(0.3, 0.15, 0.75, 0.4)
leg.SetNColumns(3)
leg.SetBorderSize(0)
leg.SetTextSize(0.03)
leg.SetTextFont(42)
leg.SetMargin(0.2)
leg.SetHeader("Train setup: #it{N}_{ev}^{training}, #it{n}_{#it{#varphi}}" +\
" #times #it{n}_{#it{r}} #times #it{n}_{#it{z}}", "C")
return canvas, leg
def makeDiscr(discr_dict,
outfile,
xtitle="discriminator",
nbins=30,
x_min=0,
x_max=1):
c = ROOT.TCanvas("c", "c", 800, 500)
ROOT.gStyle.SetOptStat(0)
ROOT.gPad.SetMargin(0.15, 0.1, 0.2, 0.1)
#ROOT.gPad.SetLogy(1)
#ROOT.gPad.SetGrid(1,1)
ROOT.gStyle.SetGridColor(17)
l = TLegend(0.17, 0.75, 0.88, 0.88)
l.SetTextSize(0.055)
l.SetBorderSize(0)
l.SetFillStyle(0)
l.SetNColumns(2)
colors = [2, 4, 8, ROOT.kCyan + 2]
counter = 0
for leg, discr in discr_dict.iteritems():
a = Hist(nbins, x_min, x_max)
#fill_hist_with_ndarray(a, discr)
a.fill_array(discr)
a.SetLineColor(colors[counter])
a.SetLineWidth(2)
a.GetXaxis().SetTitle(xtitle)
a.GetXaxis().SetLabelSize(0.05)
a.GetXaxis().SetTitleSize(0.05)
a.GetXaxis().SetTitleOffset(1.45)
a.GetYaxis().SetTitle("a.u.")
a.GetYaxis().SetTickSize(0)
a.GetYaxis().SetLabelSize(0)
a.GetYaxis().SetTitleSize(0.06)
a.GetYaxis().SetTitleOffset(0.9)
a.Scale(1. / a.Integral())
#a.GetYaxis().SetRangeUser(0.00001,100)
a.GetYaxis().SetRangeUser(0, 0.2)
if counter == 0: a.draw("hist")
else: a.draw("same hist")
l.AddEntry(a, leg, "l")
counter += 1
l.Draw("same")
c.SaveAs(outfile)
def makeUpperLegend(data, processCollection, bkg_total, legend_names=None):
legend = TLegend(0.20, 0.73, 0.92, 0.90, '', 'brNDC')
legend.SetNColumns(3)
legend.SetFillStyle(0) #avoid box
legend.SetBorderSize(0)
legend.AddEntry(data, 'Total bkg', 'pe1')
for p in processCollection:
if p.isSignal(): continue
name = p.name()
if legend_names is not None:
try:
name = legend_names[p.name()]
except KeyError:
pass
legend.AddEntry(p.nominal(), name, 'f')
legend.AddEntry(bkg_total, 'Total bkg. unc.', 'f')
return legend
def main(directories):
hists = []
for directory in directories:
#basename = os.path.basename(root_file_name)
#print '--> processing %s' % basename
hist = get_hist_from_files(directory)
hists.append(hist)
# end loop over hists
canvas = TCanvas('canvas', '')
canvas.SetLogy(1)
legend = TLegend(0.1, 0.9, 0.9, 0.99)
legend.SetNColumns(2)
hist_zero = hists[0]
hist_zero.Draw('hist')
max = hist_zero.GetMaximum()
for i_hist in range(len(hists)):
hist = hists[i_hist]
hist.SetLineColor(i_hist + 1)
hist.Draw('hist same')
legend.AddEntry(hist, hist.GetName(), 'l')
legend.Draw()
hist_zero.SetMinimum(max / 1e4)
canvas.Update()
canvas.Print('mageSpectra.pdf')
raw_input('--> enter to continue')
return
hist_zero.SetAxisRange(2030, 2040)
hist_zero.SetMinimum(0)
canvas.SetLogy(0)
canvas.Update()
canvas.Print('mageSpectra_zoom.pdf')
raw_input('--> enter to continue')
def compare(objs, add_leg_title=True, normalize=True):
print("Comparing")
cols = ['#e41a1c', '#377eb8', '#4daf4a']
colors = {}
drawn = {}
for i in objs:
print("Entry", len(colors), i)
colors[i] = TColor.GetColor(cols[len(colors)])
# Drawing objects
for i in objs:
for j in objs[i]:
obj = objs[i][j]
opt = ""
if drawn.setdefault(j, None) is None:
drawn[j] = [TCanvas(j, j)]
else:
opt += "same"
drawn[j][0].cd()
print("Drawing", obj, "with opt", opt, "on canvas", gPad.GetName())
obj.SetLineColor(colors[i])
obj.SetBit(TH1.kNoTitle)
obj.SetBit(TH1.kNoStats)
obj.SetTitle(i)
if normalize:
drawn[j].append(obj.DrawNormalized(opt))
else:
drawn[j].append(obj.DrawClone(opt))
for i in drawn:
d = drawn[i]
can = d[0]
can.cd()
gPad.SetLogy()
leg = TLegend(.1, .9, .9, .99, can.GetName())
leg.SetNColumns(2)
d.append(leg)
for j in can.GetListOfPrimitives():
leg.AddEntry(j)
leg.Draw()
return drawn
def efficiencytracking(var):
# plots the efficiency vs pT, eta and phi for all the species(it extracts the
# Efficiency from qa - tracking - efficiency if you have ran with-- make - eff)
hadron_list = [
"pion",
"proton",
"kaon",
"electron",
"muon",
]
color_list = [1, 2, 4, 6, 8]
marker_list = [20, 21, 22, 34, 45]
fileo2 = TFile("../codeHF/AnalysisResults_O2.root")
c1 = TCanvas("c1", "Efficiency")
gStyle.SetOptStat(0)
gStyle.SetErrorX(0)
gStyle.SetFrameLineWidth(2)
gStyle.SetTitleSize(0.045, "x")
gStyle.SetTitleSize(0.045, "y")
gStyle.SetMarkerSize(1)
gStyle.SetLabelOffset(0.015, "x")
gStyle.SetLabelOffset(0.02, "y")
gStyle.SetTickLength(-0.02, "x")
gStyle.SetTickLength(-0.02, "y")
gStyle.SetTitleOffset(1.1, "x")
gStyle.SetTitleOffset(1.0, "y")
c1.SetCanvasSize(800, 600)
c1.cd()
c1.SetGridy()
c1.SetGridx()
eff_list = []
if var == "Pt":
hempty = TH1F("hempty", ";Transverse Momentum(GeV/c);Efficiency", 100,
0.05, 10)
gPad.SetLogx()
elif var == "Eta":
hempty = TH1F("hempty", ";Pseudorapidity;Efficiency", 100, -4.0, 4.0)
elif var == "Phi":
hempty = TH1F("hempty", ";Azimuthal angle(rad);Efficiency", 100, 0.0,
6.0)
hempty.GetYaxis().CenterTitle()
hempty.GetXaxis().CenterTitle()
hempty.GetXaxis().SetNoExponent()
hempty.GetXaxis().SetMoreLogLabels(1)
hempty.Draw()
leg = TLegend(0.55, 0.15, 0.89, 0.35, "P")
leg.SetNColumns(2)
leg.SetHeader("Minimum bias KrKr #sqrt{s} = 6.46TeV", "C")
leg.SetFillColor(0)
for i, had in enumerate(hadron_list):
leff = fileo2.Get("qa-tracking-efficiency-%s/Efficiency" % had)
if var == "Pt":
eff = leff.At(0)
elif var == "Eta":
eff = leff.At(1)
elif var == "Phi":
eff = leff.At(2)
gPad.Update()
eff.Paint("p")
gr = eff.GetPaintedGraph().Clone()
for j in range(0, gr.GetN()):
gr.GetEXlow()[j] = 0
gr.GetEXhigh()[j] = 0
gr.SetLineColor(color_list[i])
gr.SetMarkerColor(color_list[i])
gr.SetMarkerStyle(marker_list[i])
eff_list.append(gr)
gr.Draw(" same p")
leg.AddEntry(eff_list[i], had, "p")
leg.Draw()
saveCanvas(c1, "efficiency_tracking_%s" % var)
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
text_="",
x_=0.5,
y_=0.5,
legendloc=[0.53, 0.13, 0.93, 0.39]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
#gStyle.SetTitleOffset(1.1,"Y");
#gStyle.SetTitleOffset(0.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
legpos = legendloc
leg = TLegend(legpos[0], legpos[1], legpos[2], legpos[3])
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.049)
from PlotTemplates import myCanvas1D
c = myCanvas1D()
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c1_2 = TPad("c1_2","newpad",0.04,0.13,1,0.994)
#c1_2.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
#c1_2.SetBottomMargin(0.013)
#c1_2.SetLogy(logstatus[1])
#c1_2.SetLogx(logstatus[0])
#c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
#print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
#histList[ii].Scale(1.0/histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(100) #1.4 for log
histList[ih].SetMinimum(0.00001) #1.4 for log
if logstatus[1] is 0:
histList[ih].SetMaximum(1.4) #1.4 for log
histList[ih].SetMinimum(0.001) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(10)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.08)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.14)
#histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetNdivisions(508)
from PlotTemplates import SetCMSAxis
histList[ih] = SetCMSAxis(histList[ih], 1.0, 1.15)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
i = i + 1
'''
pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
text = pt.AddText(0.2,0.5,"CMS Internal")
'''
from PlotTemplates import drawenergy1D
pt_ = drawenergy1D(False)
for ipt in pt_:
ipt.Draw()
'''
if len(text_) >0:
ltx = TLatex()
ltx.SetTextFont(42)
ltx.SetTextSize(0.049)
#text_f = "#font[42]{Phase Scan}"
ltx.DrawTextNDC(x_,y_,text_)
'''
from PlotTemplates import ExtraText
text_ex = ExtraText(text_, x_, y_)
text_ex.Draw()
ExtraText("ECAL Endcaps", 0.4, 0.85)
ltx_ = TLatex()
ltx_.SetTextFont(42)
ltx_.SetTextSize(0.049)
ltx_.DrawLatexNDC(0.32, 0.81, "L1 e-#gamma object p_{T} > 10 GeV")
#text_ex.Draw()
#pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
#text = pt.AddText(0.65,0.5,"Phase Scan data #sqrt{s} = 13 TeV (2018)")
#pt.Draw()
# t2a = TPaveText(0.0877181,0.81,0.9580537,0.89,"brNDC")
# t2a.SetBorderSize(0)
# t2a.SetFillStyle(0)
# t2a.SetTextSize(0.040)
# t2a.SetTextAlign(12)
# t2a.SetTextFont(62)
# histolabel1= str(fileVec[(len(fileVec)-1)])
# text1 = t2a.AddText(0.06,0.5,"CMS Internal")
# t2a.Draw()
leg.SetHeader("Matched TP energy")
leg.Draw()
#
# c.cd()
outputdirname = './'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
ttt = tt + ";" + tx + ";" + sys.argv[2] + " :: " + sys.argv[3]
h0.SetTitle(ttt)
if len(hh) > 2:
ymin = h0.GetMinimum()
ymax = h0.GetMaximum()
max1 = ymax + ymax - ymin
h0.SetMaximum(max1)
h0.Draw("HIST")
leg = TLegend(0.1, 0.55, 0.9, 0.9)
for h in hh:
h.Draw("HISTSAME")
tit = h.GetTitle()
leg.AddEntry(h, tit, "l")
if len(hh) > 2:
if len(hh) > 30:
leg.SetNColumns(4)
elif len(hh) > 20:
leg.SetNColumns(3)
elif len(hh) > 5:
leg.SetNColumns(2)
leg.Draw()
#=== simple diff plot
if cmd == "diff":
h = dp.getDiffPlot(1)
h.Draw('COLZ')
#=== simple diff profile plot
if cmd == "diffprof":
h = dp.getDiffPlot(2)
h.Draw('COLZ')
#bxs += ["%i-%i" % (x , x+24) for x in bx_list]
#bxs += ["%i-%i" % (x+24, x+48) for x in bx_list]
for ilayer, layer in enumerate(layers):
for iplot, plot in enumerate(plots):
print "\nPLOT %i / %i" % (
iplot
+ ilayer * len(plots)
+ 1
, len(layers) * len(plots))
# Do TH2 histos
plotname = 'h_%s_%s' % (plot, layer)
if 'TH2' in plots[plot]['class']:
c2.cd()
legend = TLegend(0.25, 0.72, 0.80, 0.93, "")
legend.SetNColumns(2)
legend.SetFillColor(ROOT.kWhite)
legend.SetLineColor(ROOT.kWhite)
legend.SetShadowColor(ROOT.kWhite)
for irun, run in enumerate(runs):
for ilumisection, lumisection in enumerate(lumisections):
for ibx, bx in enumerate(bxs):
# for ibx, bx in enumerate(bx_list):
for k in keyList:
if plots[plot]['histname'] not in k:
continue
if layer not in k or str(run) not in k:
continue
# if 'LS_%i-%i_%s' % (lumisection[0], lumisection[1], layer) not in k:
if '_%i-%i_%s' % (lumisection[0], lumisection[1], layer) not in k:
continue
qcd_color, vh_color, diboson_color, singletop_color, ttbar_color,
zll_color, wjets_color, zvv_color
]
print color
legend = TLegend(0.65, 0.7, 0.92, 0.89)
legend.SetTextSize(0.046)
legend.SetBorderSize(0)
legend.SetLineColor(1)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetNColumns(2)
i = 0
for iprocess in processes:
hist_met_ = fin.Get('h_summary_' + iprocess)
hist_met_.Sumw2()
hist_met_.SetDirectory(0)
TH1.AddDirectory(0)
# gStyle.SetPalette(53)
hist_met_.SetFillColor(color[i])
#hist_met_.SetLineColor(color[i])
bkgStack.Add(hist_met_, 'hist')
legend.AddEntry(hist_met_, processesLegend[i], "f")
i = i + 1
c = TCanvas()
def stack_hists(self,
hists_,
title,
variable_name,
input_hist_data,
dodata=0):
c1 = ROOT.TCanvas('c1', ',1000,1000')
p1 = ROOT.TPad('p1', 'p1', 0.0, 0.0, 1.0, 1.0)
p1.Draw()
p1.SetRightMargin(0.1)
p1.SetLeftMargin(0.1)
p1.SetBottomMargin(0.1)
p1.SetTopMargin(0.1)
p1.SetGridx(True)
p1.SetGridy(True)
p1.cd()
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptTitle(0)
hist_count = 0
maxy = 0
legend = TLegend(0.7, 0.7, 0.9, 0.9)
legend.SetNColumns(2)
process_list = OrderedDict([("Conv", 5), ("EWK", 6), ("Fakes", 13),
("Flips", 17), ("Rares", 38), ("TTW", 8),
("TTZ", 9), ("TTWW", 3), ("TTH_hww", 2),
("TTH_hzz", 2), ("TTH_htt", 2),
("TTH_hot", 2), ("TTH_hmm", 2),
("Data", 1)])
stacked_hist = ROOT.THStack()
#binning_ = self.define_binning(input_hist_data.GetName())
for name, hist_ in hists_.iteritems():
print 'name = ', name
for key in process_list:
if key in name:
if key == 'TTW' and 'TTWW' in name:
continue
print 'add %s to legend' % (key)
hist_.SetMarkerColor(process_list[key])
hist_.SetMarkerStyle(20)
hist_.SetLineColor(process_list[key])
hist_.SetFillColor(process_list[key])
hist_.SetFillStyle(3002)
if 'Data' in name:
legend.AddEntry(hist_, key, 'p')
else:
legend.AddEntry(hist_, key, 'f')
if 'Data' in name:
continue
stacked_hist.Add(hist_)
stacked_hist.SetTitle(title)
stacked_hist.SetMaximum(stacked_hist.GetStack().Last().GetMaximum() +
(stacked_hist.GetStack().Last().GetMaximum() /
2))
stacked_hist.SetMinimum(0.)
#input_hist_data = hists_.get(data_hist_name)
maxy = stacked_hist.GetMaximum() * 1.2 if stacked_hist.GetStack().Last(
).GetMaximum() > input_hist_data.GetMaximum(
) else input_hist_data.GetMaximum() * 1.2
histo_title_mc = 'MC'
stacked_hist.Draw('HIST')
stacked_hist.SetTitle(histo_title_mc)
stacked_hist.GetYaxis().SetTitle('Events')
stacked_hist.GetXaxis().SetTitle(variable_name)
stacked_hist.SetMaximum(maxy)
if dodata == 1:
histo_title_data = 'DATA'
input_hist_data.Draw('HISTSAMEEP')
input_hist_data.SetTitle(histo_title_data)
input_hist_data.GetYaxis().SetTitle('Events')
input_hist_data.GetXaxis().SetTitle(variable_name)
input_hist_data.SetMaximum(maxy)
legend.Draw('SAME')
c1.Update()
c1.SaveAs(self.output_fullpath, 'png')
return stacked_hist
h_Night = f2.Get(folder + '/' + histo)
h_Night.SetMarkerStyle(8)
h_Night.SetMarkerSize(0.5)
mainPad.cd()
h_Base.Draw()
h_Night.Draw("same p")
c1.Update()
var_name = histo.split("_", 1)[1]
leg = TLegend(0.330986, 0.884087, 0.879499, 0.97053)
leg.SetHeader(folder + '' + var_name, "C")
leg.SetNColumns(2)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.AddEntry(h_Base, "Baseline", "l")
leg.AddEntry(h_Night, "Nightly", "p")
leg.Draw()
c1.Update()
ratioPad.cd()
h1clone = h_Night.Clone()
h1clone.Sumw2()
h1clone.SetStats(0)
h1clone.Divide(h_Base)
h1clone.SetMarkerColor(1)
def pulls(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
b_pulls = TH1F("b_pulls", ";;Pulls", nbins, 0. - off, nbins - off)
s_pulls = TH1F("s_pulls", ";;Pulls", nbins, 0. + off, nbins + off) #
for i, s in enumerate(content):
l = s.split()
b_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
s_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
b_pulls.SetBinContent(i + 1, float(l[1]))
b_pulls.SetBinError(i + 1, float(l[2]))
s_pulls.SetBinContent(i + 1, float(l[3]))
s_pulls.SetBinError(i + 1, float(l[4]))
b_pulls.SetFillStyle(3005)
b_pulls.SetFillColor(923)
b_pulls.SetLineColor(923)
b_pulls.SetLineWidth(2)
b_pulls.SetMarkerStyle(20)
b_pulls.SetMarkerSize(1.25)
s_pulls.SetLineColor(602)
s_pulls.SetMarkerColor(602)
s_pulls.SetMarkerStyle(24) #24
s_pulls.SetLineWidth(2)
b_pulls.GetYaxis().SetRangeUser(-2.5, 2.5)
canvas = TCanvas("canvas", "Pulls", 1600, 800)
canvas.cd()
canvas.GetPad(0).SetTopMargin(0.06)
canvas.GetPad(0).SetRightMargin(0.05)
canvas.GetPad(0).SetBottomMargin(0.15)
canvas.GetPad(0).SetTicks(1, 1)
# box = TBox(950., 105., 2000., 200.)
# box.SetFillStyle(3354)
# #box.SetFillStyle(0)
# box.SetFillColor(1)
# box.SetLineWidth(2)
# box.SetLineStyle(2)
# box.SetLineColor(1)
# box.Draw()
# Draw
b_pulls.Draw("PE1")
#b_pulls.Draw("B")
s_pulls.Draw("SAME, PE1")
leg = TLegend(0.25, 0.95, 0.75, 0.995)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
leg.SetNColumns(2)
leg.AddEntry(b_pulls, "background-only fit", "flp")
leg.AddEntry(s_pulls, "signal+background fit", "lp")
if text: leg.AddEntry(0, text, "")
line = TLine()
line.DrawLine(0., 0., nbins, 0.)
line.SetLineStyle(7)
line.SetLineWidth(2)
line.SetLineColor(417)
line.DrawLine(0., 1., nbins, 1.)
line.DrawLine(0., -1., nbins, -1.)
line.SetLineColor(800)
line.DrawLine(0., 2., nbins, 2.)
line.DrawLine(0., -2., nbins, -2.)
leg.Draw()
# drawCMS(LUMI, "Simulation")
# drawAnalysis("DM")
# drawRegion(channel)
# canvas.Print(outName+".jpg")
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def pullsVertical(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
b_pulls = TH1F("b_pulls", ";;Pulls", nbins, 0. - off, nbins - off)
s_pulls = TH1F("s_pulls", ";;Pulls", nbins, 0. + off, nbins + off) #
for i, s in enumerate(content):
l = s.split()
b_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
s_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
b_pulls.SetBinContent(i + 1, float(l[1]))
b_pulls.SetBinError(i + 1, float(l[2]))
s_pulls.SetBinContent(i + 1, float(l[3]))
s_pulls.SetBinError(i + 1, float(l[4]))
b_pulls.SetFillStyle(3005)
b_pulls.SetFillColor(923)
b_pulls.SetLineColor(923)
b_pulls.SetLineWidth(1)
b_pulls.SetMarkerStyle(20)
b_pulls.SetMarkerSize(1.25)
s_pulls.SetLineColor(602)
s_pulls.SetMarkerColor(602)
s_pulls.SetMarkerStyle(24) #24
s_pulls.SetLineWidth(1)
b_pulls.GetYaxis().SetRangeUser(-2.5, 2.5)
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
B_pulls = TGraphAsymmErrors(nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 600, 150 + nbins * 10) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.GetPad(0).SetTopMargin(0.01)
canvas.GetPad(0).SetRightMargin(0.01)
canvas.GetPad(0).SetBottomMargin(0.05)
canvas.GetPad(0).SetLeftMargin(0.25) #(0.25)#(0.065)
canvas.GetPad(0).SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
if "1034h" in l[0]: l[0] = "CMS_PDF_13TeV"
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0].replace('CMS2016_', '')) #C
#y1 = gStyle.GetPadBottomMargin()
#y2 = 1. - gStyle.GetPadTopMargin()
#h = (y2 - y1) / float(nbins)
#y1 = y1 + float(i) * h
#y2 = y1 + h
#box = TPaveText(0, y1, 1, y2, 'NDC')
#box.SetFillColor(0)
#box.SetTextSize(0.02)
#box.SetBorderSize(0)
#box.SetTextAlign(12)
#box.SetMargin(0.005)
#if i % 2 == 0:
# box.SetFillColor(18)
#box.Draw()
#boxes.append(box)
B_pulls.SetPoint(i + 1, float(l[1]), float(i + 1) - 0.3) #C
B_pulls.SetPointError(i + 1, float(l[2]), float(l[2]), 0., 0.) #C
for i, s in enumerate(content):
l = s.split()
S_pulls.SetPoint(i + 1, float(l[3]), float(i + 1) - 0.7) #C
S_pulls.SetPointError(i + 1, float(l[4]), float(l[4]), 0., 0.) #C
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(-0.01)
h_pulls.GetXaxis().SetTitleOffset(.6)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
B_pulls.SetFillColor(1)
B_pulls.SetLineColor(1)
B_pulls.SetLineStyle(1)
B_pulls.SetLineWidth(2)
B_pulls.SetMarkerColor(1)
B_pulls.SetMarkerStyle(20)
B_pulls.SetMarkerSize(1) #(0.75)
S_pulls.SetFillColor(629)
S_pulls.SetLineColor(629)
S_pulls.SetMarkerColor(629)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
box1.SetFillStyle(3001)
#box1.SetFillStyle(0)
box1.SetFillColor(417)
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(417)
box2 = TBox(-2., 0., 2., nbins)
box2.SetFillStyle(3001)
#box2.SetFillStyle(0)
box2.SetFillColor(800)
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(800)
leg = TLegend(0.1, -0.05, 0.7, 0.08)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
leg.SetNColumns(2)
leg.AddEntry(B_pulls, "B-only fit", "lp")
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
B_pulls.Draw("P6SAME")
S_pulls.Draw("P6SAME")
leg.Draw()
# drawCMS(35867, "Preliminary")
# drawAnalysis("VH")
# drawRegion(outName)
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
