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 plot_sector_beam(canvas, histos, title_formatter, label, save_name):
canvas.Clear()
canvas.Divide(3, 2)
vert = TLine(0, -1.2, 0, 1.2)
hori = TLine(-1.2, 0, 1.2, 0)
vert.SetLineStyle(8)
vert.SetLineStyle(1)
vert.SetLineWidth(1)
hori.SetLineStyle(8)
hori.SetLineStyle(1)
hori.SetLineWidth(1)
xtitle = '#Delta E_{beam} (#theta_{e}, p_{e})'
ytitle = '#Delta E_{beam} (#theta_{e}, #theta_{p})'
for i in range(1, 7):
canvas.cd(i)
histos[title_formatter.format(i)].GetXaxis().SetRangeUser(-1.2, 1.2)
histos[title_formatter.format(i)].GetYaxis().SetRangeUser(-1.2, 1.2)
histos[title_formatter.format(i)].Draw('colz')
vert.Draw()
hori.Draw()
label.DrawLatex(0.1, 0.925, '#Delta E_{beam} = E_{beam} - E_{pred}')
label.DrawLatex(0.5, 0.015, xtitle)
label.SetTextAngle(90)
label.DrawLatex(0.045, 0.5, ytitle)
label.SetTextAngle(0)
canvas.Print(save_name)
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 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 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 draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig,
lower1sig, upper2sig, lower2sig):
channel = np.array(
[3. * nchannels - 1.5 - 3. * i for i in range(0, nchannels)])
ey = np.array([0.8 for i in range(0, nchannels)])
zero = np.zeros(nchannels)
gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig,
upper1sig, ey, ey)
gexpect1sig.SetFillColor(kGreen)
gexpect1sig.SetLineWidth(2)
gexpect1sig.SetLineStyle(2)
gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig,
upper2sig, ey, ey)
gexpect2sig.SetFillColor(kYellow)
gexpect2sig.SetLineWidth(2)
gexpect2sig.SetLineStyle(2)
gexpect2sig.Draw("2")
gexpect1sig.Draw("2")
gobs = TGraphErrors(nchannels, obs, channel, zero, ey)
gobs.SetMarkerStyle(21)
gobs.SetMarkerSize(1.5)
gobs.SetLineWidth(2)
gobs.Draw("pz")
# dashed line at median expected limits
l = TLine()
l.SetLineStyle(2)
l.SetLineWidth(2)
for bin in range(nchannels):
l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin],
channel[bin] + ey[bin])
# line to separate individual and combined limits
l.SetLineStyle(1)
l.SetLineWidth(1)
l.DrawLine(xmin, 0, xmax, 0)
# legend
x1 = gStyle.GetPadLeftMargin() + 0.01
y2 = 1 - gStyle.GetPadTopMargin() - 0.01
leg = TLegend(x1, y2 - 0.17, x1 + 0.25, y2)
leg.SetFillColor(4000)
leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL")
leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL")
leg.AddEntry(gobs, "Observed", "pl")
leg.Draw()
return gobs, gexpect1sig, gexpect2sig, leg
def draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig,
lower1sig, upper2sig, lower2sig):
channel = np.array(
[nchannels - 1.5 - float(i) for i in range(0, nchannels)])
ey = np.full(nchannels, 0.494)
zero = np.zeros(nchannels)
gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig,
upper1sig, ey, ey)
gexpect1sig.SetFillColor(kGreen)
gexpect1sig.SetLineWidth(2)
gexpect1sig.SetLineStyle(2)
gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig,
upper2sig, ey, ey)
gexpect2sig.SetFillColor(kYellow)
gexpect2sig.SetLineWidth(2)
gexpect2sig.SetLineStyle(2)
gexpect2sig.Draw("2")
gexpect1sig.Draw("2")
gobs = TGraphErrors(nchannels, obs, channel, zero, ey)
gobs.SetMarkerStyle(21)
gobs.SetMarkerSize(1.5)
gobs.SetLineWidth(2)
#gobs.Draw("pz")
# dashed line at median expected limits
l = TLine()
l.SetLineStyle(2)
l.SetLineWidth(2)
for bin in range(nchannels):
l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin],
channel[bin] + ey[bin])
# line to separate individual and combined limits
l.SetLineStyle(1)
l.SetLineWidth(1)
l.DrawLine(xmin, 0, xmax, 0)
# legend
leg = TLegend(0.75, 0.75, 0.95, 0.9)
leg.SetFillColor(4000)
leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL")
leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL")
#leg.AddEntry( gobs, "Observed", "pl" )
leg.Draw()
return gobs, gexpect1sig, gexpect2sig, leg
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 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 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 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(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 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 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 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 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 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 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 addLine(self, x1, y1, x2, y2, arrow="", arrowsize=0.1):
if arrow == "":
tl = TLine(x1, y1, x2, y2)
elif arrow == "<->":
tl = TArrow(x1, y1, x2, y2, arrowsize, "<|>")
elif arrow == "->":
print x2, y2, arrowsize
tl = TArrow(x1, y1, x2, y2, arrowsize, "|>")
tl.SetAngle(40)
tl.SetLineWidth(1)
tl.SetFillColor(1)
tl.Draw("same")
self.tlines.append(tl)
return tl
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
def Plot2DHist( th2, slope, offset, x_points, y_points, error_points, outname, xlabel='',
etBinIdx=None, etaBinIdx=None, etBins=None,etaBins=None):
from ROOT import TCanvas, gStyle, TLegend, kRed, kBlue, kBlack,TLine,kBird, kOrange,kGray
from ROOT import TGraphErrors,TF1,TColor
import array
def AddTopLabels(can, etlist = None, etalist = None, etidx = None, etaidx = None, logger=None):
extraText = [GetAtlasInternalText()]
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')
extraText.append(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')
extraText.append(binEta)
DrawText(can,extraText,.14,.68,.35,.93,totalentries=4)
gStyle.SetPalette(kBird)
drawopt='lpE2'
canvas = TCanvas('canvas','canvas',500, 500)
canvas.SetRightMargin(0.15)
th2.GetXaxis().SetTitle('Neural Network output (Discriminant)')
th2.GetYaxis().SetTitle(xlabel)
th2.GetZaxis().SetTitle('Count')
th2.Draw('colz')
canvas.SetLogz()
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.SetLineWidth(1)
g.SetLineColor(kBlue)
g.SetMarkerColor(kBlue)
g.Draw("P same")
line = TLine(slope*th2.GetYaxis().GetXmin()+offset,th2.GetYaxis().GetXmin(), slope*th2.GetYaxis().GetXmax()+offset, th2.GetYaxis().GetXmax())
line.SetLineColor(kBlack)
line.SetLineWidth(2)
line.Draw()
AddTopLabels( canvas, etlist=etBins,etalist=etaBins,etidx=etBinIdx,etaidx=etaBinIdx)
FormatCanvasAxes(canvas, XLabelSize=16, YLabelSize=16, XTitleOffset=0.87, ZLabelSize=14,ZTitleSize=14, YTitleOffset=0.87, ZTitleOffset=1.1)
SetAxisLabels(canvas,'Neural Network output (Discriminant)',xlabel)
canvas.SaveAs(outname+'.pdf')
canvas.SaveAs(outname+'.C')
return outname+'.pdf'
def plot_phi_vz(canvas, histos, label, save_name):
canvas.Clear()
# Start by styling the histograms
histos['histos_phi_electron_delta_vz'].Draw('colz')
line = TLine(-30, 0, 330, 0)
line.SetLineColor(1)
line.SetLineWidth(1)
line.Draw()
label.DrawLatex(0.45, 0.02, '#phi_{e}')
#label.DrawLatex(0.35, 0.925, 'Elastic Vertex Difference')
label.SetTextAngle(90)
label.DrawLatex(0.04, 0.35, '#Delta v_{z} = v_{z} (e) - v_{z} (p) (cm)')
label.SetTextAngle(0)
canvas.Print(save_name)
def myLineText(x, y, lsize, lcolor, lstyle, tsize, text):
l = TLatex()
l.SetTextAlign(12)
l.SetTextSize(tsize)
l.SetNDC()
l.DrawLatex(x,y,text)
y1 = y-0.25*lsize
y2 = y+0.25*lsize
x2 = x-0.3*lsize
x1 = x2-lsize
mline = TLine()
mline.SetLineWidth(2)
mline.SetLineColor(lcolor)
mline.SetLineStyle(lstyle)
y_new=(y1+y2)/2.
mline.DrawLineNDC(x1,y_new,x2,y_new)
def cut_line(cut_val, yl, hx, logy=False):
#vertical line representing a cut value
if logy == False:
tsel_pos = yl * hx.GetMaximum()
else:
if hx.GetMinimum() > 0.:
tsel_pos = TMath.Log10(hx.GetMinimum()) + yl * (
TMath.Log10(hx.GetMaximum()) - TMath.Log10(hx.GetMinimum()))
else:
tsel_pos = yl * TMath.Log10(hx.GetMaximum())
tsel_pos = TMath.Power(10, tsel_pos)
lin = TLine(cut_val, 0., cut_val, tsel_pos)
lin.SetLineColor(rt.kViolet)
lin.SetLineStyle(rt.kDashed)
lin.SetLineWidth(4)
return lin
def draw(hist, xtitle, nbins=0):
"""Draw 1D histogram."""
tsize = 0.045
lines = []
canvas = TCanvas('canvas', 'canvas', 100, 100, 1200, 800)
canvas.SetMargin(0.09, 0.02, 0.11, 0.02) # LRBT
canvas.SetLogy()
hist.SetMaximum(1.8 * hist.GetMaximum())
hist.SetMinimum(2)
hist.GetXaxis().SetTitle(xtitle)
hist.GetYaxis().SetTitle("Events")
hist.GetXaxis().SetTitleSize(tsize)
hist.GetYaxis().SetTitleSize(tsize)
hist.GetXaxis().SetLabelSize(0.9 * tsize)
hist.GetYaxis().SetLabelSize(0.9 * tsize)
hist.GetXaxis().SetTitleOffset(1.05)
hist.GetYaxis().SetTitleOffset(1.00)
#hist.SetMinimum(ymin)
#hist.SetMaximum(ymax)
hist.SetLineColor(kBlue)
hist.SetLineWidth(2)
#hist.SetMarkerSize(size)
#hist.SetMarkerColor(color)
#hist.SetMarkerStyle(8)
hist.Draw('HIST')
if nbins > 0: # divide with nlines
xmin, xmax = hist.GetXaxis().GetXmin(), hist.GetXaxis().GetXmax()
ymin, ymax = hist.GetMinimum(), hist.GetMaximum()
for i in range(1, nbins):
x = xmin + (xmax - xmin) * i / nbins
line = TLine(x, ymin, x, ymax)
line.SetLineColor(kRed)
line.SetLineStyle(kDashed)
line.SetLineWidth(1)
line.Draw()
lines.append(line)
canvas.SaveAs(hist.GetName() + ".png")
#canvas.SaveAs(hist.GetName()+".pdf")
canvas.Close()
def myBoxText(x,y,boxsize,mcolor,text): tsize=0.06; l=TLatex(); l.SetTextAlign(12); l.SetNDC(); l.DrawLatex(x,y,text); y1=y-0.25*tsize; y2=y+0.25*tsize; x2=x-0.3*tsize; x1=x2-boxsize; mbox= TPave(x1,y1,x2,y2,0,"NDC"); mbox.SetFillColor(mcolor); mbox.SetFillStyle(1001); mbox.Draw(); mline=TLine() mline.SetLineWidth(4) mline.SetLineColor(1) mline.SetLineStyle(1) y=(y1+y2)/2. mline.DrawLineNDC(x1,y,x2,y)
def plotDeltaPhiVsL1Phi(self):
canvas = TCanvas('cDeltaPhiVsL1Phi', 'DeltaPhiVsL1Phi', 1200, 1200)
hist = self.fileHandler.getHistogram(
'correlation/shiftCheckDeltaPhiVsPhi')
hist.GetYaxis().SetRangeUser(-1, 1)
hist.GetXaxis().SetRangeUser(-.5, .5)
hist.GetXaxis().SetTitle('L1 #phi')
hist.GetZaxis().SetTitle('#')
hist.SetStats(0)
hist.SetTitle('#Delta#phi vs. L1#phi')
setupAxes(hist)
hist.Draw('colz')
phiBorderLines = []
HO_BIN = math.pi / 36.
for i in range(-31, 32):
line = TLine(HO_BIN * i - HO_BIN / 2., -.6,
HO_BIN * i - HO_BIN / 2., .6)
line.SetLineWidth(2)
# line.Draw()
phiBorderLines.append(line)
legend = TLegend(0.6, 0.8, 0.9, 0.85)
legend.AddEntry(phiBorderLines[0], "HO Tile center", "e")
#legend.Draw()
label = self.drawLabel()
canvas.Update()
setupPalette(hist)
canvas.Update()
canvas.SaveAs('plots/deltaPhiVsL1Phi.pdf')
return canvas, hist, label, phiBorderLines, legend
