def plot_calibrations(group_data, voltage, cal_pars_list, stacked=False):
group_name = str(group_data[0].run_number)
run = group_data[2]
name = str(run.run_number)
hists_and_lines = []
for cal_pars in cal_pars_list:
pars = parameters.gain_pars[cal_pars]
run.calibrate_energies(voltage, pars)
hist = make_hist(name, run.calibrated_energies, 0, 3500)
K_line = TLine(1460.820, 0, 1460.820, 1000000)
K_line.SetLineColor(632)
Tl_line = TLine(2614.511, 0, 2614.511, 1000000)
Tl_line.SetLineColor(632)
hists_and_lines.append([hist, K_line, Tl_line])
if stacked:
print('Plotting stacked calibrated histograms.')
run_canvas = TCanvas()
run_canvas.SetLogy()
colors = [808, 397, 436, 424, 628, 852, 800, 863, 403, 797]
color_index = 0
hs = THStack('hs', 'Group %s Histograms' % group_name)
for entry in hists_and_lines:
title = str(run.run_number)
entry[0].SetLineColor(colors[color_index])
color_index += 1
hs.Add(entry[0])
hs.Draw('nostack')
K_line = TLine(1460.820, 0, 1460.820, 1000000)
K_line.SetLineColor(632)
K_line.Draw()
Tl_line = TLine(2614.511, 0, 2614.511, 1000000)
Tl_line.SetLineColor(632)
Tl_line.Draw()
run_canvas.BuildLegend()
path = 'output/group_' + str(group_data[0].run_number) + '/'
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf['))
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf'))
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf]'))
else:
print('Plotting calibrated energy histogram.')
run_canvas = TCanvas("run_canvas", "run canvas")
run_canvas.Divide(3, int(len(cal_pars_list) / 2))
canvas_index = 1
for entry in hists_and_lines:
pad = run_canvas.cd(canvas_index)
pad.SetLogy()
entry[0].Draw()
entry[1].Draw()
entry[2].Draw()
pad.Update()
canvas_index += 1
path = 'output/group_' + group_name + '/'
run_canvas.Print((path + name + '_calibrated_histograms.pdf['))
run_canvas.Print((path + name + '_calibrated_histograms.pdf'))
run_canvas.Print((path + name + '_calibrated_histograms.pdf]'))
def saveTuplePlot2D(events,
inHisto1,
inHisto2,
nBinsX,
minX,
maxX,
nBinsY,
minY,
maxY,
mincut,
maxcut,
outfile,
canvas,
XaxisTitle="",
YaxisTitle="",
plotTitle="",
stats=0,
logY=0):
events.Draw("{0}:{1}>>histo({2},{3},{4},{5},{6},{7})".format(
inHisto2, inHisto1, nBinsX, minX, maxX, nBinsY, minY, maxY))
histo = ROOT.gROOT.FindObject("histo")
histo.SetTitle(plotTitle)
histo.GetXaxis().SetTitle(XaxisTitle)
histo.GetYaxis().SetTitle(YaxisTitle)
histo.SetStats(stats)
histo.Draw("COLZ")
minline = TLine(minX, mincut, maxX, mincut)
minline.SetLineColor(2)
minline.Draw("same")
maxline = TLine(minX, maxcut, maxX, maxcut)
maxline.SetLineColor(2)
maxline.Draw("same")
canvas.SetLogy(logY)
canvas.Print(outfile + ".pdf")
del histo
def DrawScat2XLine(graph, title, fname, ycoord1, ycoord2): #, grid):
c = TCanvas("c", "c", 800, 600)
graph.SetTitle(title)
graph.GetXaxis().SetTitleSize(.04)
graph.GetYaxis().SetTitleSize(.04)
graph.GetXaxis().SetTitleOffset(1.2)
graph.GetYaxis().SetTitleOffset(1.25)
graph.GetXaxis().CenterTitle(1)
graph.GetYaxis().CenterTitle(1)
graph.GetYaxis().SetMaxDigits(4)
graph.SetMarkerStyle(20) # Full circle
graph.Draw()
gPad.Update()
line1 = TLine(gPad.GetUxmin(), ycoord1, gPad.GetUxmax(), ycoord1)
line2 = TLine(gPad.GetUxmin(), ycoord2, gPad.GetUxmax(), ycoord2)
# print(gPad.GetUymin(),gPad.GetUymax())
line1.SetLineStyle(2)
line1.SetLineColor(2)
line1.SetLineWidth(3)
line2.SetLineStyle(2)
line2.SetLineColor(2)
line2.SetLineWidth(3)
graph.Draw("AP")
line1.Draw("same")
line2.Draw("same")
c.SaveAs(fname + ".C")
c.SaveAs(fname + ".pdf")
return
def drawCut(hist):
#drawCut(80, 140, 0., hist['BkgSum'].GetMaximum())
line1 = TLine(80, 0, 80, hist['BkgSum'].GetMaximum())
line1.SetLineWidth(2)
line1.SetLineStyle(7)
line1.SetLineColor(1)
line1.Draw()
line2 = TLine(140, 0, 140, hist['BkgSum'].GetMaximum())
line2.SetLineWidth(2)
line2.SetLineStyle(7)
line2.SetLineColor(1)
line2.Draw()
line1 = TLine(0.841, 0, 0.841, 15)
line1.SetLineWidth(2)
line1.SetLineStyle(7)
line1.SetLineColor(1)
line1.Draw()
line1 = TLine(100, 0, 100, hist['BkgSum'].GetMaximum())
line1.SetLineWidth(2)
line1.SetLineStyle(7)
line1.SetLineColor(1)
line1.Draw()
def draw2d(hist, xtitle, ytitle, number=False, nxbins=0, nybins=0):
"""Draw 2D histogram."""
tsize = 0.045
lines = []
xmin, xmax = hist.GetXaxis().GetXmin(), hist.GetXaxis().GetXmax()
ymin, ymax = hist.GetYaxis().GetXmin(), hist.GetYaxis().GetXmax()
canvas = TCanvas('canvas', 'canvas', 100, 100, 900, 800)
canvas.SetMargin(0.11, 0.16, 0.10, 0.02) # LRBT
canvas.SetLogz()
hist.GetXaxis().SetTitle(xtitle)
hist.GetYaxis().SetTitle(ytitle)
hist.GetZaxis().SetTitle("Events")
hist.GetXaxis().SetTitleSize(tsize)
hist.GetYaxis().SetTitleSize(tsize)
hist.GetZaxis().SetTitleSize(tsize)
hist.GetXaxis().SetLabelSize(0.9 * tsize)
hist.GetYaxis().SetLabelSize(0.9 * tsize)
hist.GetZaxis().SetLabelSize(0.9 * tsize)
hist.GetXaxis().SetTitleOffset(1.04)
hist.GetYaxis().SetTitleOffset(1.14)
hist.GetZaxis().SetTitleOffset(1.08)
hist.Draw('COLZ')
if number:
latex = TLatex()
latex.SetTextSize(0.8 * tsize)
latex.SetTextAlign(22)
latex.SetTextFont(62)
latex.SetTextColor(kRed)
for ix in range(1, hist.GetXaxis().GetNbins() + 1):
x = hist.GetXaxis().GetBinCenter(ix)
for iy in range(1, hist.GetYaxis().GetNbins() + 1):
y = hist.GetYaxis().GetBinCenter(iy)
latex.DrawLatex(x, y, str(Unroll.GetBin(x, y)))
if nxbins > 0: # divide with nlines
for i in range(1, nxbins):
x = xmin + (xmax - xmin) * i / nxbins
line = TLine(x, ymin, x, ymax)
line.SetLineColor(kRed)
line.SetLineStyle(kDashed)
line.SetLineWidth(1)
line.Draw()
lines.append(line)
if nybins > 0: # divide with nlines
for i in range(1, nybins):
y = ymin + (ymax - ymin) * i / nybins
line = TLine(xmin, y, xmax, y)
line.SetLineColor(kRed)
line.SetLineStyle(kDashed)
line.SetLineWidth(2)
line.Draw()
lines.append(line)
canvas.RedrawAxis()
canvas.SaveAs(hist.GetName() + ".png")
#canvas.SaveAs(hist.GetName()+".pdf")
canvas.Close()
def makePlot(mds, ds, pdf):
""" Mass fit plot """
frame = mds.frame()
ds.plotOn(frame, DataError(RooAbsData.SumW2), MarkerSize(1))
pdf.plotOn(frame, LineWidth(2))
# pull histogram
pullHist = frame.pullHist()
pullFrame = mds.frame(Title(''))
pullFrame.addPlotable(pullHist, 'P')
pullFrame.GetYaxis().SetRangeUser(-5, 5)
canvas = TCanvas('m(Ds)', 'm(Ds)', 600, 700)
canvas.cd()
pad1 = TPad('pad1', 'pad1', .01, .20, .99, .99)
pad2 = TPad('pad2', 'pad2', .01, .01, .99, .20)
pad1.Draw()
pad2.Draw()
pad1.cd()
pad1.SetLeftMargin(0.15)
pad1.SetFillColor(0)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleOffset(0.85)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(1.6)
frame.Draw()
pad2.cd()
pad2.SetLeftMargin(0.15)
pad2.SetFillColor(0)
pullFrame.SetMarkerSize(0.05)
pullFrame.Draw()
mdsRange = fitRange()['mDs']
lineUp = TLine(mdsRange[0], 3, mdsRange[1], 3)
lineUp.SetLineColor(kBlue)
lineUp.SetLineStyle(2)
lineUp.Draw()
lineCe = TLine(mdsRange[0], 0, mdsRange[1], 0)
lineCe.SetLineColor(kBlue)
lineCe.SetLineStyle(1)
lineCe.SetLineWidth(2)
lineCe.Draw()
lineD0 = TLine(mdsRange[0], -3, mdsRange[0], -3)
lineD0.SetLineColor(kBlue)
lineD0.SetLineStyle(2)
lineD0.Draw()
canvas.Update()
def plot_event_selection(canvas, histos, save_name, label):
canvas.Clear()
canvas.Divide(2, 1)
histos['histos_w_in_ctof'].SetLineColor(1)
histos['histos_w_pass_angle_in_ctof'].SetLineColor(1)
histos['histos_w_pass_angle_in_ctof'].SetFillColorAlpha(64, 1.0)
histos['histos_angle_ep'].SetLineColor(1)
histos['histos_angle_ep_pass_w_in_ctof'].SetLineColor(1)
histos['histos_angle_ep_pass_w_in_ctof'].SetFillColorAlpha(64, 1.0)
histos['histos_w_in_ctof'].SetMinimum(0)
histos['histos_w_pass_angle_in_ctof'].SetMinimum(0)
# Fix missing bins
histos['histos_w_in_ctof'].GetXaxis().SetRangeUser(0.7, 1.3)
histos['histos_w_pass_angle_in_ctof'].GetXaxis().SetRangeUser(0.7, 1.3)
wleft = TLine(0.8, histos['histos_w_in_ctof'].GetMinimum(), 0.8,
0.8 * histos['histos_w_in_ctof'].GetMaximum())
wright = TLine(1.08, histos['histos_w_in_ctof'].GetMinimum(), 1.08,
0.8 * histos['histos_w_in_ctof'].GetMaximum())
wleft.SetLineColor(99)
wleft.SetLineWidth(1)
wright.SetLineColor(99)
wright.SetLineWidth(1)
canvas.cd(1)
histos['histos_w_in_ctof'].Draw()
histos['histos_w_pass_angle_in_ctof'].Draw('same')
wleft.Draw()
wright.Draw()
label.DrawLatex(0.1, 0.925, 'Electron (forward) and Proton (central)')
label.DrawLatex(0.5, 0.015, 'W (GeV/c^{2})')
label.DrawLatex(0.67, 0.86, '#color[64]{#phi_{ep} > 174}')
canvas.cd(2)
histos['histos_angle_ep'].Draw()
histos['histos_angle_ep_pass_w_in_ctof'].Draw('same')
left = TLine(174, 0.0, 174, 0.8 * histos['histos_angle_ep'].GetMaximum())
left.SetLineColor(99)
left.SetLineWidth(1)
left.Draw()
label.DrawLatex(0.1, 0.925, 'Electron (forward) and Proton (central)')
label.DrawLatex(0.5, 0.015, '#phi_{ep}')
label.DrawLatex(0.57, 0.86, '#color[64]{W \in [0.8, 1.08]}')
canvas.Print(save_name)
def addLinesOfCenter(x, y):
line = TLine(0, y, x, y)
line1 = TLine(x, 0, x, y)
line.SetLineColor(2)
line1.SetLineColor(2)
#line1.Draw('same')
#line.Draw('same')
lines = []
lines.append(line1)
lines.append(line)
return lines
def addCuts(histdict, outdir):
c_2D = TCanvas('c_2D', 'ISR photons theta versus Energy', 700, 500)
c_2D.cd(1)
histdict["h_ISR_Theta_vs_E"].Draw("colz")
f1 = TF1("cutThetaPos", "1.48", -1., 200)
f1.SetLineStyle(7)
f1.SetLineColor(2)
f1.Draw("same")
f2 = TF1("cutThetaNeg", "-1.48", -1., 200)
f2.SetLineStyle(7)
f2.SetLineColor(2)
f2.Draw("same")
# gPad.DrawFrame(0, -3.5, 150, 3.5)
cutE = TLine(0.2, -3.5, 0.2, 3.5)
cutE.SetLineColor(2)
cutE.SetLineStyle(7)
cutE.Draw("same")
outfilename = "{}.root".format(outdir)
outfile = TFile(outfilename, "UPDATE")
c_2D.Write("", TObject.kOverwrite)
outfile.Write()
outfile.Close()
def drawLine(xlow, ylow, xup, yup, lineWidth, lineStyle, lineColor):
L1 = TLine(xlow, ylow, xup, yup)
L1.SetLineWidth(lineWidth)
L1.SetLineColor(lineColor)
L1.SetLineStyle(lineStyle)
L1.Draw("same")
return L1
def overlayProfile(l_prof, l_axis, l_histo, l_legend, l_text, l_legInfo, saveAs, saveString):
aString, xLabel, yLabel, xOffset, yOffset, aLabSize, aTextSize = l_axis
hString, c_x, c_y, yMin, yMax, hBins, hFile = l_histo
lString, l_x1, l_y1, l_x2, l_y2, l_textSize = l_legend
t_str, plotText, t_textSize, t_alignment, t_start, t_gap, t_x = l_text
l_bins = PythonUtils.makeListFromString(hBins, ';')
gROOT.SetBatch(1)
c = TCanvas('c', 'c', int(c_x), int(c_y))
gStyle.SetOptStat(0)
c.SetTicks(1, 1)
for i in xrange(len(l_prof)):
if i == 0:
l_prof[i].Draw('eps')
setupAxes(l_prof[i], xLabel, yLabel, xOffset, yOffset,
aTextSize, l_bins[0], l_bins[len(l_bins) -1], 1)
l_prof[i].SetMinimum(float(yMin))
l_prof[i].SetMaximum(float(yMax))
l_prof[i].SetTitle('')
hLine = TLine(l_prof[i].GetXaxis().GetXmin(), 1, l_prof[i].GetXaxis().GetXmax(), 1)
hLine.SetLineWidth(2)
hLine.SetLineColor(1)
hLine.SetLineStyle(2)
hLine.Draw('same')
else:
l_prof[i].Draw('eps same')
setupTextOnPlot(plotText, t_textSize, t_alignment, t_x, t_start, t_gap)
setupLegend(l_legInfo, l_x1, l_y1, l_x2, l_y2, l_textSize)
savePlots(c, saveString, saveAs)
def CheckToysTempFiles(sample='tW', histo='dnn'):
path = baseoutpath%(year, ms, ml)
f = TFile.Open(path+sample+ ('.root' if not sample.endswith('.root') else ''))
hnom = f.Get(histo)
nom = hnom.Integral()
h = TH1F('h', 'h', 20, 0.24, 0.26)
for i in range(nToys):
ht = f.Get(histo+'_NormToy%i'%i)
h.Fill(ht.Integral())
c = TCanvas('c', 'c', 10, 10, 1200, 800)
h.SetStats(0)
h.SetTitle('')
h.GetXaxis().SetTitle("Yield %s"%sample)
h.GetYaxis().SetTitle("Number of toys")
h.SetLineWidth(2); h.SetLineColor(kOrange+1)
h.SetFillColor(0)
h.Draw('hist')
l = TLine(nom, 0, nom, h.GetMaximum())
l.SetLineColor(kGray+3); l.SetLineWidth(2); l.SetLineStyle(2)
l.Draw("same")
name = 'toys_%s_%s'%(sample, histo)
for form in ['png', 'pdf']: c.SaveAs(webpath+name+'.'+form)
def myLineBoxTextBorder(x, y, lcolor, lstyle, bcolor, bstyle, bsize, tsize, text):
l = TLatex()
l.SetTextAlign(12)
l.SetTextSize(tsize/2.5)
l.SetNDC()
l.DrawLatex(x,y,text)
yl1 = y-0.25*bsize
yl2 = y+0.25*bsize
xl1 = x-0.25*bsize-0.4*bsize
xl2 = x+0.25*bsize-0.4*bsize
#print("line = ",xl1,yl1,xl2,yl2)
mline = TLine(xl1,yl1,xl2,yl2)
mline.SetLineColor(lcolor)
mline.SetLineStyle(lstyle)
mline.SetLineWidth(2)
y_new=(yl1+yl2)/2.
mline.DrawLineNDC(xl1,y_new,xl2,y_new)
yb1 = y-0.15*bsize
yb2 = y+0.15*bsize
xb1 = x-0.25*bsize-0.4*bsize
xb2 = x+0.25*bsize-0.4*bsize
#print("box = ",xb1,yb1,xb2,yb2)
mbox = TPave(xb1,yb1,xb2,yb2,1,"NDC")
mbox.SetLineWidth(2)
mbox.SetLineColor(1)
mbox.SetFillColor(bcolor)
mbox.SetFillStyle(bstyle)
mbox.Draw("l")
return mbox
def drawLine(x1, y1, x2, y2, color=1):
line = TLine(x1, y1, x2, y2)
line.SetLineStyle(2)
line.SetLineWidth(2)
line.SetLineColor(color)
line.Draw()
return line
def addLine(self, x1, y1, x2, y2, color, thickness=0.):
line = TLine(x1, y1, x2, y2)
line.SetLineColor(color)
line.SetLineStyle(2)
if thickness:
line.SetLineWidth(thickness)
self.lines.append(line)
def write_spikeroothistogram(vectorspikes, histogramtitle, ytitle,
rootdirectory, deltatime):
"""Function to perform ROOT histograms"""
#Set ROOT histograms
TH1Hist = TH1F(histogramtitle, "", 3, 0, 3)
vectorspikes = [x[5:len(x)] for x in vectorspikes]
#Fill histograms in for loop
for entry in range(len(vectorspikes)):
TH1Hist.Fill(vectorspikes[entry], 1. / (deltatime / 60))
#Draw + DrawOptions histograms
c = TCanvas()
c.SetName(histogramtitle + "_canvas")
Style = gStyle
Style.SetLineWidth(1) #TH1Hist
Style.SetOptStat(0) #Show statistics
gROOT.ForceStyle()
TH1Hist.SetCanExtend(TH1.kAllAxes)
TH1Hist.SetFillColor(38)
TH1Hist.LabelsDeflate()
TH1Hist.SetMinimum(0)
TH1Hist.SetMaximum(2)
YAxis = TH1Hist.GetYaxis()
YAxis.SetTitle(ytitle)
rootdirectory.WriteTObject(TH1Hist)
line = TLine(0., 1.0, len(set(vectorspikes)), 1.0)
line.SetLineStyle(2)
line.SetLineColor(2)
TH1Hist.Draw("histo")
line.Draw()
rootdirectory.WriteTObject(c)
def overlayAndRatio(canvas, min_ratio, max_ratio, h1, h2):
canvas.ResetAttPad()
canvas.Clear()
pad = TPad("main", "main", 0, 0.3, 1, 1)
pad.SetBottomMargin(0.05)
pad.Draw()
pad.cd()
h1.Draw()
h2.SetLineColor(kOrange + 10)
h2.Draw('SAME')
canvas.cd()
ratio = TPad("ratio", "ratio", 0, 0.05, 1, 0.3)
ratio.SetTopMargin(0.05)
ratio.Draw()
ratio.cd()
if isinstance(h1, TProfile) and isinstance(h2, TProfile):
h1_p = h1.ProjectionX()
h2_p = h2.ProjectionX()
h1_p.Divide(h2_p)
h1_p.SetMaximum(max_ratio)
h1_p.SetMinimum(min_ratio)
h1_p.SetMarkerStyle(kFullCircle)
h1_p.SetMarkerSize(0.6)
h1_p.SetTitle('')
h1_p.GetXaxis().SetLabelFont(42)
h1_p.GetXaxis().SetLabelSize(0.1)
h1_p.GetYaxis().SetLabelFont(42)
h1_p.GetYaxis().SetLabelSize(0.1)
h1_p.GetYaxis().SetNdivisions(505)
equality = TLine()
h1_p.Draw("SAME HIST P")
equality.SetLineColor(kOrange + 10)
equality.DrawLine(h1_p.GetXaxis().GetXmin(), 1,
h1_p.GetXaxis().GetXmax(), 1)
def plot_GOF(hist, obs, critical, p_value, alpha="0.05"):
# canvas
canv = TCanvas("canv", "canv", 600, 600)
canv.SetBottomMargin(0.10)
canv.SetLeftMargin(0.15)
canv.SetRightMargin(0.12)
# histograms
hist.SetMarkerColor(0)
hist.SetTitle("GOF test - toys {}".format(int(hist.GetEntries())))
hist.GetXaxis().SetTitleFont(43)
hist.GetYaxis().SetTitleFont(43)
hist.GetXaxis().SetTitleSize(20)
hist.GetYaxis().SetTitleSize(20)
hist.GetXaxis().SetTitleOffset(0.8)
hist.GetYaxis().SetTitleOffset(1.5)
hist.GetXaxis().SetTitle("Statistics")
hist.GetYaxis().SetTitle("Probability")
hist.Draw("hist")
up = hist.GetMaximum()
hist.GetYaxis().SetRangeUser(0, 1.2 * up)
# lines
c_line = TLine(critical, 0, critical, 1.2 * up)
c_line.SetLineColor(2)
c_line.SetLineWidth(4)
c_line.SetLineStyle(2)
c_line.Draw("L same")
obs_line = TLine(obs, 0, obs, 1.2 * up)
obs_line.SetLineColor(1)
obs_line.SetLineWidth(4)
obs_line.Draw("L same")
# legend
leg = TLegend(0.6, 0.65, .95, .95)
leg.SetFillColor(0)
leg.SetShadowColor(0)
leg.SetLineColor(0)
leg.SetTextFont(43)
leg.SetTextSize(18)
leg.AddEntry(c_line, "alpha = {}".format(alpha), 'L')
leg.AddEntry(obs_line, "data (p-value={0:.2f})".format(p_value), 'L')
leg.AddEntry(hist, "toys", "L")
leg.Draw("same")
# save canvas
canv.SaveAs("{}.pdf".format(saveout))
canv.SaveAs("{}.png".format(saveout))
canv.SaveAs("{}.root".format(saveout))
return canv
def GetLine(x1,y1,x2,y2,color,style,width, text=''): from ROOT import TLine l = TLine(x1,y1,x2,y2) l.SetNDC(False) l.SetLineColor(color) l.SetLineWidth(width) l.SetLineStyle(style) return l
def MakeCutPlot(c,cal,var,eb,elo,ehi,vb,vlo,vhi,d2Cut,d1Cut,outPlot,fastMode):
""" Creates a channel-specific energy calibration plot. """
# Calculate cut vals (assumes plot range is correct)
h1 = wl.H1D(cal,vb,vlo,vhi,var,d1Cut)
h1Sum = h1.Integral()
if h1Sum == 0:
print "Error: Failed %s, histogram sum is 0 so cannot normalize, setting to [0,0,0,0,0]"%(var)
return 0,0,0,0,0
h1.Scale(1/h1Sum)
try:
cut99,cut95,cut01,cut05,cut90 = wl.GetIntegralPoints(h1)
except:
print "Error: Failed %s using cut %s, setting to [0,0,0,0,0]"%(var,d1Cut)
return 0,0,0,0,0
if fastMode:
print "Returning fastMode output: ", cut99,cut95,cut01,cut05,cut90
return cut99,cut95,cut01,cut05,cut90
# Generate the plot for inspection.
c.cd(2)
gPad.SetLogy(0)
h1.GetXaxis().SetRangeUser(cut01-abs(0.25*cut01), cut99 + abs(0.25*cut99) )
h1.SetTitle("")
h1.GetXaxis().SetTitle(var)
h1.Draw("hist")
c.cd(1)
gPad.SetLogy(0)
cal.Draw("%s:trapENFCal>>b(%d,%d,%d,%d,%.3E,%.3E)"%(var,eb+10,elo-5,ehi+5,vb,cut01-abs(0.25*cut01),cut99+abs(0.25*cut99)) ,d2Cut)
l1, l2, l3 = TLine(), TLine(), TLine()
l1.SetLineColor(ROOT.kGreen)
l2.SetLineColor(ROOT.kRed)
l3.SetLineColor(ROOT.kMagenta)
l1.DrawLine(elo-5, cut99, ehi+5, cut99)
l2.DrawLine(elo-5, cut95, ehi+5, cut95)
l2.DrawLine(elo-5, cut05, ehi+5, cut05)
l1.DrawLine(elo-5, cut01, ehi+5, cut01)
c.cd(3)
x_h1, y_h1 = wl.npTH1D(h1)
int_h1 = wl.integFunc(y_h1)
g2 = TGraph(len(x_h1), x_h1, int_h1)
g2.GetXaxis().SetRangeUser(cut01-abs(0.3*cut01), cut99 + abs(0.3*cut99) )
g2.SetTitle("")
g2.GetXaxis().SetTitle(var)
g2.GetYaxis().SetTitle("Percentile")
g2.Draw("ACP")
l1.DrawLine(cut99, 0, cut99, 1)
l2.DrawLine(cut95, 0, cut95, 1)
l1.DrawLine(cut01, 0, cut01, 1)
l2.DrawLine(cut05, 0, cut05, 1)
c.Print(outPlot)
return cut99,cut95,cut01,cut05,cut90
def draw_line(lineList,x1,x2,y1,y2,width=1,style=1,color=1):
from ROOT import TLine
l=TLine(x1,y1,x2,y2)
l.SetBit(ROOT.kCanDelete)
l.SetLineWidth(width)
l.SetLineStyle(style)
l.SetLineColor(color)
l.Draw()
lineList.append(l)
def col_lin(col, w=4, st=rt.kSolid):
#create line of a given color
lin = TLine()
lin.SetLineColor(col)
lin.SetLineWidth(w)
lin.SetLineStyle(st)
return lin
def ratioplot():
# create required parts
leg = getLegend()
latex = getLatex()
c = TCanvas()
c.SetLogy()
#Draw input histograms
hists = ['h_frac_recoil_', 'h_full_recoil_']
label = ['recoil with MET triggers', 'recoil without MET triggers']
combineHist(hists, label, leg)
#leg.Draw()
#c.SaveAs("Combinehists_D.pdf")
ratio = []
h1 = f.Get('h_frac_recoil_')
#h1=setHistStyle(h1,bins)
h2 = f.Get('h_full_recoil_')
#h2=setHistStyle(h2,bins)
h3 = createRatio(h1, h2)
gr = TGraphAsymmErrors(h1, h2)
gr.GetXaxis().SetRangeUser(0, 1500)
gr.GetYaxis().SetRangeUser(0, 1.2)
gr.SetMarkerStyle(20)
gr.SetMarkerSize(0.5)
gr.SetLineColor(1)
gr.GetYaxis().SetTitle("Trigger Efficiency")
gr.GetXaxis().SetTitle("Recoil [GeV]")
gr.SetTitle("")
# print ("ratio",ratio )
# c, pad1, pad2 = createCanvasPads()
#
# # draw everything
# pad1.cd()
# h1.Draw()
# h2.Draw("same")
# to avoid clipping the bottom zero, redraw a small axis
# h1.GetYaxis().SetLabelSize(0.0)
# axis = TGaxis(-5, 20, -5, 220, 20, 220, 510, "")
# axis.SetLabelFont(43)
# axis.SetLabelSize(15)
# axis.Draw()
# pad2.cd()
gr.Draw()
latex.DrawLatex(0.41, 0.93, "Trigger Efficincy in MET Run2017E")
xmin = 0.0
line = TLine(max(xmin, gr.GetXaxis().GetXmin()), 1, 1500, 1)
line.SetLineColor(1)
line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw()
#h3.Draw('pl')
c.SaveAs("test.pdf")
def plotGraph(self, x='vv', y='acc'):
'''
Plot a graph with specified quantities on x and y axes , and saves the graph
'''
if (x not in self.quantities.keys()) or (y not in self.quantities.keys()):
raise RuntimeError('selected quantities not available, available quantities are: \n{}'.format(self.quantities.keys()))
xq = self.quantities[x]
yq = self.quantities[y]
#graph = TGraphAsymmErrors()
#graph = TGraph()
graph = TGraphErrors()
for i,s in enumerate(self.samples):
graph.SetPoint(i,getattr(s, xq.name), getattr(s, yq.name) )
#if xq.err:
# graph.SetPointEXhigh(i, getattr(s, xq.name+'_errup')) # errup errdn
# graph.SetPointEXlow (i, getattr(s, xq.name+'_errdn'))
if yq.err:
graph.SetPointError(i, 0, getattr(s, yq.name+'_errup'))
# graph.SetPointEYhigh(i, getattr(s, yq.name+'_errup'))
# graph.SetPointEYlow (i, getattr(s, yq.name+'_errdn'))
c = TCanvas()
graph.SetLineWidth(2)
graph.SetMarkerStyle(22)
graph.SetTitle(';{x};{y}'.format(y=yq.title,x=xq.title))
graph.Draw('APLE')
if yq.forceRange:
graph.SetMinimum(yq.Range[0])
graph.SetMaximum(yq.Range[1])
gPad.Modified()
gPad.Update()
if yq.name=='expNevts':
line = TLine(gPad.GetUxmin(),3,gPad.GetUxmax(),3)
line.SetLineColor(ROOT.kBlue)
line.Draw('same')
#graph.SetMinimum(0.01)
#graph.SetMaximum(1E06)
if xq.log: c.SetLogx()
if yq.log: c.SetLogy()
c.SetGridx()
c.SetGridy()
c.SaveAs('./plots/{}{}/{}_{}VS{}.pdf'.format(self.label,suffix,self.name,yq.name,xq.name))
c.SaveAs('./plots/{}{}/{}_{}VS{}.C'.format(self.label,suffix,self.name,yq.name,xq.name))
c.SaveAs('./plots/{}{}/{}_{}VS{}.png'.format(self.label,suffix,self.name,yq.name,xq.name))
self.graphs['{}VS{}'.format(yq.name,xq.name)] = graph
# add the graph container for memory?
graph_saver.append(graph)
def AddBinLines(can, hist, useHistMax=False, horizotalLine=1., lineStyle=2):
tobject_collector = []
from ROOT import TH1, TGraph, THStack, TColor, kGray, kBlue, TLine, kRed
if can.GetPrimitive('pad_top'):
tobject_collector.extend(
AddBinLines(can.GetPrimitive('pad_top'), hist, useHistMax,
horizotalLine))
if can.GetPrimitive('pad_bot'):
# TODO Move this to another function
pad = GetBotPad(can)
tobject_collector.extend(AddBinLines(pad, hist))
if horizotalLine is not None and pad.GetUymax(
) > horizotalLine > pad.GetUymin():
pad.cd()
maxValue = pad.GetUxmax()
minValue = pad.GetUxmin()
l = TLine(minValue, horizotalLine, maxValue, horizotalLine)
l.SetLineColor(kRed)
l.SetLineStyle(2)
l.Draw()
tobject_collector.append(l)
return tobject_collector
can.cd()
#listOfPlottedObjects = [o for o in can.GetListOfPrimitives() if isinstance(o,(TH1, THStack))]
#listOfPlottedObjects += [o.GetHistogram() for o in can.GetListOfPrimitives() if isinstance(o,TGraph)]
#if listOfPlottedObjects:
#maxValue = max([o.GetBinContent(o.GetMaximumBin()) + o.GetBinError(o.GetMaximumBin()) for o in listOfPlottedObjects])
#minValue = min([o.GetBinContent(o.GetMinimumBin()) - o.GetBinError(o.GetMinimumBin()) for o in listOfPlottedObjects])
maxValue = hist.GetBinContent(
hist.GetMaximumBin()) if useHistMax else can.GetUymax()
minValue = can.GetUymin()
for x in range(2, hist.GetXaxis().GetNbins() + 1):
xv = hist.GetBinLowEdge(x)
line = TLine(xv, minValue, xv, maxValue)
line.SetLineColor(17)
line.SetLineStyle(lineStyle)
line.Draw()
tobject_collector.append(line)
return tobject_collector
def evalDiode():
datalist = loadCSVToList('../data/part1/Kennlinie.txt')
data = DataErrors()
U0 = datalist[0][1]
sU0 = 0.05 + 0.01 * U0
for I, u in datalist:
U = u - U0
su = 5 + 0.01 * u
sU = sqrt(su**2 + sU0**2)
data.addPoint(I, U, 0.1, sU)
xmin, xmax = 53, 71.5
c = TCanvas('c_diode', '', 1280, 720)
g = data.makeGraph('g_diode', "Laserstrom I_{L} / mA",
"Photodiodenspannung U_{ph} / mV")
g.GetXaxis().SetRangeUser(-5, 90)
g.SetMinimum(-50)
g.SetMaximum(1400)
g.Draw('APX')
# y=0 line
line = TLine(-5, 0, 90, 0)
line.SetLineColor(OPData.CH2ECOLOR)
line.Draw()
data.filterX(xmin, xmax)
g2 = data.makeGraph('g_diode_2', "Laserstrom I_{L} / mA",
"Photodiodenspannung U_{ph} / mV")
g2.SetMarkerColor(OPData.CH1COLOR)
g2.SetLineColor(OPData.CH1COLOR)
fit = Fitter('fit_diode', '[0] * (x-[1])')
fit.function.SetNpx(1000)
fit.setParam(0, 'a', 1)
fit.setParam(1, 'I_{th}', 50)
fit.fit(g2, 40, 77)
fit.saveData('../fit/part1/kennlinie.txt')
l = TLegend(0.15, 0.55, 0.4, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Laserdiodenkennlinie', 'p')
l.AddEntry(g2, 'Ausschnitt zum Fitten', 'p')
l.AddEntry(fit.function, 'Fit mit U_{ph} = a (I_{ L} - I_{ th} )', 'l')
fit.addParamsToLegend(l, (('%.1f', '%.1f'), ('%.2f', '%.2f')),
chisquareformat='%.2f',
units=['mV/mA', 'mA'])
l.Draw()
g.Draw('P')
g2.Draw('P')
c.Update()
c.Print('../img/part1/diodenkennlinie.pdf', 'pdf')
def plot_sector_page_single(canvas,
histos,
title_formatter,
save_name,
xtitle=None,
ytitle=None,
title=None,
x_range=None,
log=False,
hline=None):
""" Plot one histogram for each sector. """
label = TLatex()
label.SetNDC()
label.SetTextSize(0.045)
canvas.Clear()
canvas.Divide(3, 2)
root_garbage_can = []
for i in range(1, 7):
canvas.cd(i)
if x_range:
histos.get(title_formatter.format(i),
default_histo2d).GetXaxis().SetRangeUser(
x_range[0], x_range[1])
histos.get(title_formatter.format(i), default_histo2d).Draw('colz')
if log:
gPad.SetLogz()
if title:
label.DrawLatex(0.1, 0.925, title)
if xtitle:
label.DrawLatex(0.45, 0.015, xtitle)
if ytitle:
label.SetTextAngle(90)
label.DrawLatex(0.0325, 0.65, ytitle)
label.SetTextAngle(0)
if hline:
xmin = histos.get(title_formatter.format(i)).GetXaxis().GetXmin()
xmax = histos.get(title_formatter.format(i)).GetXaxis().GetXmax()
line = TLine(xmin, hline, xmax, hline)
line.SetLineColor(1)
line.SetLineStyle(1)
line.Draw('same')
root_garbage_can.append(line)
canvas.Print(save_name)
def myMarkerTextSmall2(x, y, lcolor, lstyle, mcolor, mstyle, msize, size,
text):
l = TLatex()
l.SetTextAlign(12)
l.SetTextSize(size / 2.5)
l.SetNDC()
l.DrawLatex(x, y, text)
yb1 = y - 0.15 * size
yb2 = y + 0.15 * size
xb1 = x - 0.28 * size - 0.45 * size
xb2 = x + 0.28 * size - 0.45 * size
print "box = ", xb1, yb1, xb2, yb2
#print "line = ",xl1,yl1,xl2,yl2
mline1 = TLine(xb1, yb1, xb2, yb2)
mline1.SetLineColor(lcolor)
mline1.SetLineStyle(lstyle)
mline1.SetLineWidth(2)
y_new = (yb1 + yb2) / 2.
mline1.DrawLineNDC(xb1, y_new, xb2, y_new)
mline2 = TLine(xb1, yb1, xb2, yb2)
mline2.SetLineColor(lcolor)
mline2.SetLineStyle(lstyle)
mline2.SetLineWidth(2)
x_new = (xb1 + xb2) / 2.
mline2.DrawLineNDC(x_new, yb1, x_new, yb2)
marker = TMarker((xb1 + xb2) / 2.0, y, mstyle)
marker.SetNDC()
marker.SetMarkerColor(mcolor)
marker.SetMarkerStyle(mstyle)
marker.SetMarkerSize(msize)
marker.Draw()
return marker
def plot_correction( h2, slope, offset, x_points, y_points, error_points, outname,
xlabel='',
etBinIdx=None,
etaBinIdx=None,
etBins=None,
etaBins=None,
label='Internal',
ref_value=None,
pd_value=None,
palette=kBlackBody):
def toStrBin(etlist = None, etalist = None, etidx = None, etaidx = None):
if etlist and etidx is not None:
etlist=copy(etlist)
if etlist[-1]>9999: etlist[-1]='#infty'
binEt = (str(etlist[etidx]) + ' < E_{T} [GeV] < ' + str(etlist[etidx+1]) if etidx+1 < len(etlist) else
'E_{T} > ' + str(etlist[etidx]) + ' GeV')
return binEt
if etalist and etaidx is not None:
binEta = (str(etalist[etaidx]) + ' < |#eta| < ' + str(etalist[etaidx+1]) if etaidx+1 < len(etalist) else
str(etalist[etaidx]) + ' <|#eta| < 2.47')
return binEta
canvas = TCanvas("canvas","canvas",500,500)
rpl.set_figure(canvas)
gStyle.SetPalette(palette)
canvas.SetRightMargin(0.15)
canvas.SetTopMargin(0.15)
canvas.SetLogz()
h2.GetXaxis().SetTitle('Neural Network output (Discriminant)')
h2.GetYaxis().SetTitle(xlabel)
h2.GetZaxis().SetTitle('Count')
h2.Draw('colz')
g = TGraphErrors(len(x_points), array.array('d',x_points), array.array('d',y_points), array.array('d',error_points), array.array('d',[0]*len(x_points)))
g.SetMarkerColor(kBlue)
g.SetMarkerStyle(8)
g.SetMarkerSize(1)
g.Draw("P same")
line = TLine(slope*h2.GetYaxis().GetXmin()+offset,h2.GetYaxis().GetXmin(), slope*h2.GetYaxis().GetXmax()+offset, h2.GetYaxis().GetXmax())
line.SetLineColor(kBlack)
line.SetLineWidth(2)
line.Draw()
# Add text labels into the canvas
text = toStrBin(etlist=etBins, etidx=etBinIdx)
text+= ', '+toStrBin(etalist=etaBins, etaidx=etaBinIdx)
if ref_value and pd_value:
text+=', P_{D} = %1.2f (%1.2f) [%%]'%(pd_value*100, ref_value*100)
rpl.add_text(0.15, 0.885, text, textsize=.03)
rpl.set_atlas_label(0.15, 0.94, label)
rpl.format_canvas_axes(XLabelSize=16, YLabelSize=16, XTitleOffset=0.87, ZLabelSize=16,ZTitleSize=16, YTitleOffset=0.87, ZTitleOffset=1.1)
canvas.SaveAs(outname)
def BuildTLine(xmin_in, ymin_in, xmax_in, ymax_in, Properties):
xmin = Properties.get('xmin_tline', xmin_in)
xmax = Properties.get('xmax_tline', xmax_in)
ymin = Properties.get('ymin_tline', ymin_in)
ymax = Properties.get('ymax_tline', ymax_in)
linewidth = Properties.get('lineWidth_tline', 1)
linestyle = Properties.get('lineStyle_tline', 1)
linecolor = Properties.get('lineColor_tline', 1)
line = TLine(xmin, ymin, xmax, ymax)
line.SetLineWidth(linewidth)
line.SetLineStyle(linestyle)
line.SetLineColor(linecolor)
return line
