def drawFilledBox(ieta, iphi, canvas):
canvas.cd()
box = TBox(ieta - 0.5, iphi - 0.5, ieta + 0.5, iphi + 0.5)
box.SetLineColor(ROOT.kBlack)
box.SetFillStyle(3013)
box.SetFillColor(ROOT.kBlack)
box.Draw()
return box
def draw(plot, channel='MuMu', plotprefix=None, SetLogy=0):
# print plot
Stack.STAT_ERRORS = True
blindxmin = None
blindxmax = None
titles = xtitles
if channel == 'TauEle':
titles = xtitles_TauEle
xtitle = titles.get(plot.varName, None)
if xtitle is None:
xtitle = ''
global can, pad, padr, ratio
if pad is None:
can, pad, padr = buildCanvas()
pad.cd()
pad.SetLogy(SetLogy)
plot.DrawStack('HIST')
h = plot.supportHist
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
gevperbin = h.GetXaxis().GetBinWidth(1)
h.GetYaxis().SetTitle('Events')
h.GetYaxis().SetTitleOffset(1.4)
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = False
ratio.DrawRatioStack('HIST', ymin=0.4, ymax=1.6)
hr = ratio.stack.totalHist
# hr.weighted.Fit('pol1')
hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitle('Exp./Obs.')
hr.GetYaxis().SetTitleSize(0.1)
hr.GetYaxis().SetTitleOffset(0.5)
hr.GetXaxis().SetTitle('{xtitle}'.format(xtitle=xtitle))
hr.GetXaxis().SetTitleSize(0.13)
hr.GetXaxis().SetTitleOffset(0.9)
rls = 0.075
hr.GetYaxis().SetLabelSize(rls)
hr.GetXaxis().SetLabelSize(rls)
hr.GetYaxis().SetRangeUser(0.5, 1.5)
padr.Update()
# blinding
if plot.blindminx:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(plot.blindminx, 0, plot.blindmaxx, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
# import pdb; pdb.set_trace()
keeper.append(box)
print channel
if channel == 'MuMu': CMSPrelim(plot, pad, '#mu#mu')
can.cd()
if plotprefix == None: plotname = plot.varName
else: plotname = plotprefix + '_' + plot.varName
can.SaveAs(plotname + '.png')
pad.SetLogy(0)
def draw_box(boxList,xl,xr,yl,yr,opacity=1,color=1,style=1001,lstyle=1,lw=3):
from ROOT import TBox
b=TBox(xl,yl,xr,yr)
b.SetBit(ROOT.kCanDelete)
b.SetFillStyle(style)
b.SetFillColorAlpha(color, opacity)
b.SetLineColor(color)
b.SetLineWidth(lw)
b.SetLineStyle(lstyle)
b.Draw()
boxList.append(b)
def drawHoBoxes(canvas):
canvas.cd()
boxes = []
for i in range(1, 6):
for j in range(1, 6):
box = TBox(-2.5 + i - 1, -2.5 + j - 1, -2.5 + i, -2.5 + j)
box.SetFillStyle(0)
box.SetLineColor(ROOT.kBlack)
box.SetLineWidth(2)
box.Draw()
boxes.append(box)
return boxes
def drawHcalBoxesHcalCoords(canvas): canvas.cd() boxes = [] for i in range(-15,15): for j in range(0,72): box = TBox(i,j,(i+1),(j+1)) box.SetFillStyle(0) box.SetLineColor(colorRwthMagenta) box.SetLineWidth(2) box.Draw() boxes.append(box) return boxes
def drawHoBoxes(canvas): canvas.cd() boxes = [] for i in range(-1,2): for j in range(-1,2): box = TBox(i*0.087 - 0.0435,j*0.087 - 0.0435,(i*0.087+0.0435),(j*0.087+0.0435)) box.SetFillStyle(0) box.SetLineColor(colorRwthMagenta) box.SetLineWidth(3) box.Draw() boxes.append(box) return boxes
def drawHoBoxes(canvas):
canvas.cd()
boxes = []
for i in range(1, 8):
for j in range(1, 8):
box = TBox(-0.3045 + (i - 1) * 0.087, -0.3045 + (j - 1) * 0.087,
-0.3045 + i * 0.087, -0.3045 + j * 0.087)
box.SetFillStyle(0)
box.SetLineColor(ROOT.kBlack)
box.SetLineWidth(2)
box.Draw()
boxes.append(box)
return boxes
def drawOfficial(plot, doBlind=False, channel='TauMu', plotprefix = None, ymin = 0.1):
global ocan
print plot
Stack.STAT_ERRORS = False
blindxmin = None
blindxmax = None
doBlind = (plot.varName == 'svfitMass') and doBlind
if doBlind:
blindxmin = 100
blindxmax = 160
plot.Blind(blindxmin, blindxmax, False)
titles = xtitles
if channel=='TauEle':
titles = xtitles_TauEle
xtitle = titles.get( plot.varName, None )
if xtitle is None:
xtitle = ''
global ocan
if ocan is None:
ocan = buildCanvasOfficial()
ocan.cd()
plot.DrawStack('HIST', ymin=ymin)
h = plot.supportHist
h.GetXaxis().SetTitle('{xtitle}'.format(xtitle=xtitle))
# blinding
if plot.blindminx:
ocan.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox( plot.blindminx, 0, plot.blindmaxx, max )
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
# import pdb; pdb.set_trace()
keeper.append(box)
year, lumi, energy = datasetInfo( plot )
datasetStr = "CMS Preliminary, #sqrt{{s}} = {energy} TeV, L = {lumi:3.2f} fb^{{-1}}".format(energy=energy, lumi=lumi)
if channel == 'TauMu' : a,b = CMSPrelimOfficial( datasetStr, '#tau_{#mu}#tau_{h}',0.15,0.835)
elif channel == 'TauEle' : a,b = CMSPrelimOfficial( datasetStr, '#tau_{e}#tau_{h}', 0.15, 0.835)
a.Draw()
b.Draw()
save.extend([a,b])
ocan.Modified()
ocan.Update()
ocan.cd()
if plotprefix == None : plotname = plot.varName
else : plotname = plotprefix + '_' + plot.varName
ocan.SaveAs( plotname + '.png')
ocan.SetLogy()
ocan.SaveAs( plotname + '_log.png')
ocan.SetLogy(0)
def drawBox(x1, y1, x2, y2, t=""):
box = TBox(x1, y1, x2, y2)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
if not t == "":
text = TLatex()
text.SetTextColor(1)
text.SetTextFont(42)
text.SetTextAlign(23)
text.SetTextSize(0.04)
text.DrawLatex((x1 + x2) / 2., y2 / 1.15, t)
text.Draw()
return box
def makeTimeVsEtaPlot(self, source, title=""):
canvas = TCanvas(source)
if title == "":
title = source
hist = TH2D(source, title + ";i#eta;Time / ns;#", 33, -16.5, 16.5, 201,
-100.5, 100.5)
graph = self.fileHandler.getGraph('graphs/timingSupport_' + source)
fillGraphIn2DHist(graph, hist)
hist.SetStats(0)
hist.Draw('colz')
canvas.Update()
setupAxes(hist)
label = self.drawLabel()
canvas.Update()
fractionGraph, counterDict = self.printFractionsPerIEta(graph)
self.debug('Integral of plot %20s: %d' % (source, hist.Integral()))
medianTofZero = (counterDict[9]['median'] +
counterDict[11]['median']) / 2.
tofFunction = TF1(
'f',
'4*sqrt(1+ 1/(tan(2*atan(exp(-x*0.087/2.)))**2))/300000000.*1e9 - 13.3 + [0]',
-10, 10)
tofFunction.SetParameter(0, medianTofZero)
tofFunction.Draw('same')
###
# Draw Boxes for the Intervals
###
intervalBoxes = []
for index, item in enumerate(counterDict):
iEta = index - 10
# Skip iEta 0
if iEta == 0:
continue
box = TBox(iEta - 0.5, item['median'] - 12.5, iEta + 0.5,
item['median'] + 12.5)
box.SetFillStyle(0)
box.SetLineColor(colorRwthMagenta)
box.SetLineWidth(2)
box.Draw()
intervalBoxes.append(box)
return canvas, hist, label, fractionGraph, intervalBoxes, tofFunction
def plot3x3MatchQualityCodesVsPt(self):
c = TCanvas('cMatchQC3x3', 'Match QC 3x3', 0, 0, 900, 700)
c.SetLogz()
hist = self.fileHandler.getHistogram(
'qualityCode/L1Muon3x3Match_QcVsPt')
hist.SetStats(0)
hist.Scale(1, 'width')
hist.Draw('colz')
c.Update()
setupPalette(hist)
c.Update()
label = self.drawLabel()
c.Update()
box = TBox(0, 6.5, 180, 7.5)
box.SetLineColor(3)
box.SetLineWidth(2)
box.Draw()
c.Update()
return hist, c, label, box
tpc_xy.SetLineStyle(2)
tpc_xy.SetFillStyle(0)
tpc_xy.SetFillStyle(0)
tpc_xy.SetLineWidth(3)
h_xy.Draw("col")
h_xy.GetYaxis().SetTitleOffset(1.3)
#h_xy_corr.Draw("col")
h_xy_corr.GetYaxis().SetTitleOffset(1.3)
preliminary = TPaveText(0.48, 0.74, 0.81, 0.84, "NDC")
preliminary.SetShadowColor(0)
preliminary.SetBorderSize(0)
preliminary.SetFillStyle(0)
preliminary.AddText("MicroBooNE Preliminary")
#preliminary.Draw()
tpc_xy.Draw()
g_end.Draw("P")
g.Draw("P")
f3.SetLineStyle(1)
f3.Draw("cont2same")
c_spacecharge.Update()
c_spacecharge.SaveAs(output + "/spacecharge_" + algo + ".pdf")
c_yz = TCanvas("c_yz")
h_yz.Draw()
#h_yz_mc.Draw("same")
#h_yz_corr.Draw("same")
h_yz_mc.SetMarkerColor(kRed + 1)
h_yz_corr.SetMarkerColor(kBlue + 1)
c_yz.Update()
def massrap_matching(blinded):
c = Canvas("c")
c.cd()
c.SetTicks(1,1)
gr = ROOT.TGraphErrors('gr')
gr.SetName('gr')
count_20, count_5, count_3, count_2, x, y = 0, 0, 0, 0, ROOT.Double(0), ROOT.Double(0)
for i, year in enumerate(years):
g = getGraph(year)
n_gr = gr.GetN() if i > 0 else 0
for j in range(g.GetN()):
g.GetPoint(j,x,y)
#print 'm:', x, 'y:', y
ex = g.GetErrorX(j)
ey = g.GetErrorY(j)
gr.SetPoint(n_gr+j,x,y)
gr.SetPointError(n_gr+j,ex,ey)
if abs(x) < 20 and abs(y) < 20: count_20 += 1
if abs(x) < 5 and abs(y) < 5: count_5 += 1
if abs(x) < 3 and abs(y) < 3: count_3 += 1
if abs(x) < 2 and abs(y) < 2: count_2 += 1
print 'Total events:', gr.GetN(), '20sig:', count_20, '5sig:', count_5, '3sig:', count_3, '2sig:', count_2
gr.SetLineColor(ROOT.kBlack)
gr.SetTitle('')
gr.GetXaxis().SetTitle("(m_{pp}-m_{#gamma#gamma})/#sigma(m_{pp}-m_{#gamma#gamma})")
gr.GetYaxis().SetTitle("(y_{pp} - y_{#gamma#gamma})/#sigma(y_{pp} - y_{#gamma#gamma})")
gr.GetXaxis().SetLimits(-20,20)
gr.GetYaxis().SetRangeUser(-20,20)
gr.SetMarkerSize(0.5)
gr.SetMarkerStyle(24)
gr.Draw("AP")
b3 = TBox(-5, -5, 5, 5)
b3.SetLineColor(ROOT.kRed)
b3.SetFillStyle(0)
#b3.Draw()
b2 = TBox(-3, -3, 3, 3)
if not blinded: b2.SetFillStyle(3001) # transparent
b2.SetFillColor(5)
b2.SetLineColor(1)
b2.Draw()
b1 = TBox(-2, -2, 2, 2)
if not blinded: b1.SetFillStyle(3001) # transparent
b1.SetFillColor(3)
b1.SetLineColor(1)
b1.Draw()
legend = TLegend(0.7,0.8,0.9,0.9)
legend.AddEntry(b1,"2#sigma matching",'f')
legend.AddEntry(b2,"3#sigma matching",'f')
#legend.AddEntry(b3,"5#sigma matching",'l')
legend.Draw()
c.Update()
pLabel = prelimLabel()
pLabel.Draw()
sLabel = selectionLabel("#xi^{#pm}_{#gamma#gamma} #in PPS")
#sLabel = selectionLabel("Reverse acop. selection")
sLabel.Draw()
lLabel = lumiLabel()
lLabel.Draw()
s_blind = '_blinded' if blinded else ''
c.SaveAs("plots/matching/massrap_matching_"+s_years+"_multiRP%s.%s" % (s_blind,extension))
def draw(plot,
do_ratio=True,
channel='e#mu#mu',
plot_dir='/plots/',
plot_name=None,
SetLogy=0,
blindxmin=None,
blindxmax=None,
unit=None):
print plot
Stack.STAT_ERRORS = True
can = pad = padr = None
if do_ratio:
can, pad, padr = HistDrawer.buildCanvas()
else:
can = HistDrawer.buildCanvasSingle()
pad.cd()
pad.SetLogy(SetLogy)
plot.DrawStack('HIST', print_norm=plot.name == '_norm_',
ymin=0.1) # magic word to print integrals in legend
h = plot.supportHist
h.GetXaxis().SetLabelColor(1)
# h.GetXaxis().SetLabelSize(1)
unitsperbin = h.GetXaxis().GetBinWidth(1)
ytitle = 'Events'
if unit:
round_to_n = lambda x, n: round(
x, -int(floor(log10(abs(x)))) + (n - 1))
ytitle += round_to_n(unitsperbin, 3)
h.GetYaxis().SetTitle('Events')
h.GetYaxis().SetTitleOffset(1.0)
h.GetXaxis().SetTitleOffset(2.0)
if do_ratio:
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = False
if blindxmin or blindxmax:
if not blindxmin:
blindxmin = 0
if not blindxmax:
blindxmax = plot.stack.totalHist.GetXaxis().GetXmax()
if do_ratio:
ratio.Blind(blindxmin, blindxmax, True)
plot.Blind(blindxmin, blindxmax, False)
if do_ratio:
ratio.DrawDataOverMCMinus1(-0.5, 0.5)
hr = ratio.dataOverMCHist
# Gymnastics to get same label sizes etc in ratio and main plot
ytp_ratio = 2.
xtp_ratio = 2.
# hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitleSize(h.GetYaxis().GetTitleSize() * xtp_ratio)
hr.GetXaxis().SetTitleSize(h.GetXaxis().GetTitleSize() * ytp_ratio)
hr.GetYaxis().SetTitleOffset(h.GetYaxis().GetTitleOffset() /
xtp_ratio)
hr.GetXaxis().SetTitleOffset(h.GetXaxis().GetTitleOffset() /
ytp_ratio)
hr.GetYaxis().SetLabelSize(h.GetYaxis().GetLabelSize() * xtp_ratio)
hr.GetXaxis().SetLabelSize(h.GetXaxis().GetLabelSize() * ytp_ratio)
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
padr.Update()
# blinding
if blindxmin or blindxmax:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(blindxmin, 0, blindxmax, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
HistDrawer.keeper.append(box)
HistDrawer.CMSPrelim(plot, pad, channel, legend=plot.legendPos)
can.cd()
plotname = plot_dir + '/'
ensureDir(plot_dir)
plotname += plot_name if plot_name else plot.name
can.SaveAs(plotname + '.png')
can.SaveAs(plotname + '.pdf')
can.SaveAs(plotname + '.root')
# Also save with log y
h.GetYaxis().SetRangeUser(pad.GetUymax() * 5. / 1000000.,
pad.GetUymax() * 5.)
pad.SetLogy(True)
can.SaveAs(plotname + '_log.png')
can.SaveAs(plotname + '_log.pdf')
pad.SetLogy(0)
def plot_rocs(plotObjects, kwargs):
from ROOT import kCyan, kRed, kGreen, kBlue, kBlack, kMagenta, kGray, kWhite, kYellow
Colors = [kBlue, kRed, kMagenta, kBlack, kCyan, kGreen]
from RingerCore import StdPair as std_pair
from util import line, minmax
dset = kwargs['set']
ref = kwargs['reference']
refVal = kwargs['refVal']
eps = kwargs['eps']
savename = kwargs['cname'] + '.pdf'
#Some protection
if not ('operation' in dset or 'tst' in dset):
raise ValueError('Option set must be: tst (test) or val (validation)')
if not ('SP' in ref or 'Pd' in ref or 'Pf' in ref):
raise ValueError('Option reference must be: SP, Pd or Pf')
#Create dict to hold all list plots
curves = dict()
#list of dicts to dict of lists
for name in plotObjects.keys():
curves[name] = plotObjects.tolist(name)
paintIdx = kwargs['paintListIdx'] # [best, worst]
paintCurves = [
std_pair(plotObjects.index_correction(paintIdx[0]), kBlack),
std_pair(plotObjects.index_correction(paintIdx[1]), kRed)
]
curves['roc'] = curves['roc_' + dset]
#Start to build all ROOT objects
from ROOT import TCanvas, gROOT, kTRUE
gROOT.SetBatch(kTRUE)
canvas = TCanvas('canvas', 'canvas', 1600, 1300)
x_limits = [0.00, 0.40]
y_limits = [0.6, 1.03]
#create dummy graph
dummy = curves['roc'][0]
dummy.SetTitle('Receive Operation Curve')
dummy.GetXaxis().SetTitle('False Alarm')
dummy.GetYaxis().SetTitle('Detection')
dummy.GetHistogram().SetAxisRange(y_limits[0], y_limits[1], 'Y')
dummy.GetHistogram().SetAxisRange(x_limits[0], x_limits[1], 'X')
dummy.Draw('AL')
corredor = None
target = None
from ROOT import TBox
if ref == 'Pf':
corredor = TBox(refVal - eps, y_limits[0], refVal + eps, y_limits[1])
target = line(refVal, y_limits[0], refVal, y_limits[1], kBlack, 2, 1,
'')
elif ref == 'Pd':
corredor = TBox(x_limits[0], refVal - eps, x_limits[1], refVal + eps)
target = line(x_limits[0], refVal, x_limits[1], refVal, kBlack, 2, 1,
'')
if ref != 'SP':
corredor.SetFillColor(kYellow - 9)
corredor.Draw('same')
target.Draw('same')
canvas.Modified()
canvas.Update()
#Plot curves
for c in curves['roc']:
c.SetLineColor(kGray + 1)
#c.SetMarkerStyle(7)
#c.SetMarkerColor(kBlue)
c.SetLineWidth(1)
c.SetLineStyle(3)
#c.Draw('PLsame')
c.Draw('same')
marker = list()
#Paint a specifical curve
for pair in paintCurves:
curves['roc'][pair.first].SetLineWidth(1)
curves['roc'][pair.first].SetLineStyle(1)
#curves['roc'][pair.first].SetMarkerStyle(7)
#curves['roc'][pair.first].SetMarkerColor(kBlue)
curves['roc'][pair.first].SetLineColor(pair.second)
#curves['roc'][pair.first].Draw('PLsame')
curves['roc'][pair.first].Draw('same')
if ref == 'SP':
faVec = curves['roc'][pair.first].GetX()
detVec = curves['roc'][pair.first].GetY()
from RingerCore import calcSP
spVec = [
calcSP(detVec[i], 1 - faVec[i])
for i in range(curves['roc'][pair.first].GetN())
]
imax = spVec.index(max(spVec))
from ROOT import TMarker
marker.append(TMarker(faVec[imax], detVec[imax], 4))
marker[-1].SetMarkerColor(pair.second)
marker[-1].Draw('same')
#Update Canvas
canvas.Modified()
canvas.Update()
canvas.SaveAs(savename)
del canvas
return savename
def draw(plot,
do_ratio=True,
channel='#mu#tau_{h}',
plot_dir='plots',
plot_name=None,
SetLogy=0,
blindxmin=None,
blindxmax=None,
unit=None):
print plot
Stack.STAT_ERRORS = True
can = pad = padr = None
if do_ratio:
can, pad, padr = HistDrawer.buildCanvas()
else:
can = HistDrawer.buildCanvasSingle()
pad.cd()
pad.SetLogy(SetLogy)
# print "about to DrawStack"
# plot.DrawNormalized()
# plot.DrawNormalizedRatioStack('HIST', ymin=0.1)
# , dataAsPoisson=True
plot.DrawStack(
'HIST',
print_norm=plot.name == '_norm_',
ymin=0.1,
scale_signal='') # magic word to print integrals in legend
h = plot.supportHist
h.GetXaxis().SetLabelColor(1)
# h.GetXaxis().SetLabelSize(1)
unitsperbin = h.GetXaxis().GetBinWidth(1)
ytitle = 'Events'
if unit:
round_to_n = lambda x, n: round(
x, -int(floor(log10(abs(x)))) + (n - 1))
ytitle += round_to_n(unitsperbin, 3)
h.GetYaxis().SetTitle('Events')
# if axis labels and title overlap, change offset here
h.GetYaxis().SetTitleOffset(1.3)
h.GetXaxis().SetTitleOffset(2.0)
if do_ratio:
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = False
if blindxmin or blindxmax:
if not blindxmin:
blindxmin = 0
if not blindxmax:
blindxmax = plot.GetXaxis().GetXmax()
if do_ratio:
ratio.Blind(blindxmin, blindxmax, True)
plot.Blind(blindxmin, blindxmax, False)
if do_ratio:
ratio.DrawDataOverMCMinus1(-0.5, 0.5)
hr = ratio.dataOverMCHist
# Gymnastics to get same label sizes etc in ratio and main plot
ytp_ratio = 2.
xtp_ratio = 2.
# hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitleSize(h.GetYaxis().GetTitleSize() * xtp_ratio)
hr.GetXaxis().SetTitleSize(h.GetXaxis().GetTitleSize() * ytp_ratio)
hr.GetYaxis().SetTitleOffset(h.GetYaxis().GetTitleOffset() /
xtp_ratio)
hr.GetXaxis().SetTitleOffset(h.GetXaxis().GetTitleOffset() /
ytp_ratio)
hr.GetYaxis().SetLabelSize(h.GetYaxis().GetLabelSize() * xtp_ratio)
hr.GetXaxis().SetLabelSize(h.GetXaxis().GetLabelSize() * ytp_ratio)
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
padr.Update()
# blinding
if blindxmin or blindxmax:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(blindxmin, 0, blindxmax, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
HistDrawer.keeper.append(box)
HistDrawer.CMSPrelim(plot, pad, channel, legend=plot.legendPos)
can.cd()
plotname = plot_dir + '/'
ensureDir(plot_dir)
plotname += plot_name if plot_name else plot.name
can.SaveAs(plotname + '.png')
can.SaveAs(plotname + '.pdf')
# Also save with log y
if plot.legendPos == 'right':
h.GetYaxis().SetRangeUser(0.1001, pad.GetUymax() * 5.)
else:
# minimum is set to 2 orders of magnitude lower than maximum
minRange = pow(10, floor(log10(pad.GetUymax() / 100.)))
h.GetYaxis().SetRangeUser(minRange + minRange * 1e-4,
pad.GetUymax() * 5.e3)
pad.SetLogy(True)
can.SaveAs(plotname + '_log.png')
can.SaveAs(plotname + '_log.pdf')
pad.SetLogy(0)
return ratio
null = TPad("null","",0,0,1,1)
null.SetFillStyle(0)
null.SetFrameFillStyle(0)
null.Draw()
null.cd()
null.Range(x1-LM,yf-BM,x2+RM,y2+TM)
tri=TPolyLine(3,xx,yy)
tri.SetFillColor(0)
box1=TBox(-0.2,-0.2,1.05,0)
box2=TBox(-0.2,-0.2,0,1.05)
box1.SetFillColor(0)
box2.SetFillColor(0)
#p.Draw('atext')
tri.Draw('f')
box1.Draw('f')
box2.Draw('f')
tri.Draw('f')
if tipo in ['obs','exp']:
bm = c.GetBottomMargin()
lm = c.GetLeftMargin()
rm = c.GetRightMargin()
to = c.GetTopMargin()
x1 = p.GetXaxis().GetXmin()
yf = p.GetYaxis().GetXmin()
x2 = p.GetXaxis().GetXmax()
y2 = p.GetYaxis().GetXmax()
Xa = (x2-x1)/(1-lm-rm)-(x2-x1)
Ya = (y2-yf)/(1-bm-to)-(y2-yf)
def draw(plot,
do_ratio=True,
channel='TauMu',
plot_dir='plots',
plot_name=None,
SetLogy=0,
mssm=False,
blindxmin=None,
blindxmax=None,
unit=None):
print plot
Stack.STAT_ERRORS = True
can = pad = padr = None
if do_ratio:
can, pad, padr = HistDrawer.buildCanvas()
else:
can = HistDrawer.buildCanvasSingle()
pad.cd()
pad.SetLogy(SetLogy)
plot.DrawStack('HIST')
h = plot.supportHist
h.GetXaxis().SetLabelColor(1)
# h.GetXaxis().SetLabelSize(1)
unitsperbin = h.GetXaxis().GetBinWidth(1)
ytitle = 'Events'
if unit:
round_to_n = lambda x, n: round(
x, -int(floor(log10(abs(x)))) + (n - 1))
ytitle += round_to_n(unitsperbin, 3)
h.GetYaxis().SetTitle('Events')
h.GetYaxis().SetTitleOffset(1.0)
h.GetXaxis().SetTitleOffset(2.0)
if do_ratio:
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = False
if blindxmin or blindxmax:
if not blindxmin:
blindxmin = 0
if not blindxmax:
blindxmax = plot.GetXaxis().GetXmax()
if do_ratio:
ratio.Blind(blindxmin, blindxmax, True)
plot.Blind(blindxmin, blindxmax, False)
if do_ratio:
ratio.DrawDataOverMCMinus1(-0.5, 0.5)
hr = ratio.dataOverMCHist
# ytp_ratio = float(pad.YtoPixel(0.)/padr.YtoPixel(0))
# print 'YTP ratio', ytp_ratio
# xtp_ratio = float(pad.XtoPixel(0.)/padr.XtoPixel(0))
# print 'XTP ratio', xtp_ratio
ytp_ratio = 2.
xtp_ratio = 2.
# hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitleSize(h.GetYaxis().GetTitleSize() * xtp_ratio)
hr.GetXaxis().SetTitleSize(h.GetXaxis().GetTitleSize() * ytp_ratio)
hr.GetYaxis().SetTitleOffset(h.GetYaxis().GetTitleOffset() /
xtp_ratio)
hr.GetXaxis().SetTitleOffset(h.GetXaxis().GetTitleOffset() /
ytp_ratio)
hr.GetYaxis().SetLabelSize(h.GetYaxis().GetLabelSize() * xtp_ratio)
hr.GetXaxis().SetLabelSize(h.GetXaxis().GetLabelSize() * ytp_ratio)
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
padr.Update()
# blinding
if blindxmin or blindxmax:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(blindxmin, 0, blindxmax, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
HistDrawer.keeper.append(box)
print channel
if channel == 'TauMu':
HistDrawer.CMSPrelim(plot,
pad,
'#tau_{#mu}#tau_{h}',
legend=plot.legendPos)
elif channel == 'TauEle':
HistDrawer.CMSPrelim(plot,
pad,
'#tau_{e}#tau_{h}',
legend=plot.legendPos)
can.cd()
plotname = plot_dir + '/'
ensureDir(plot_dir)
plotname += plot_name if plot_name else plot.name
can.SaveAs(plotname + '.png')
pad.SetLogy(0)
return ratio
ihMinTHalf_y = SensClass.GetTHalf(ihMaxMbb_meV * CLHEP.meV, isotope,
nmeModel, ga) / CLHEP.year
ihMaxTHalf_y = SensClass.GetTHalf(ihMinMbb_meV * CLHEP.meV, isotope,
nmeModel, ga) / CLHEP.year
ihMaxMaxTHalf_y = SensClass.GetTHalf(ihMinMinMbb_meV * CLHEP.meV, isotope,
nmeModel, ga) / CLHEP.year
bInvHierOut = TBox(expMin_ty, ihMinMinTHalf_y, 0.98 * expMax_ty,
ihMaxMaxTHalf_y)
bInvHierIn = TBox(expMin_ty, ihMinTHalf_y, 0.98 * expMax_ty, ihMaxTHalf_y)
if options.useShellModel: ihText += "(SM"
else: ihText += "(QRPA"
ihText += ", g_{A}=" + str(ga) + ")"
lInvHier = TLatex(2. * expMin_ty, math.sqrt(ihMinTHalf_y * ihMaxTHalf_y),
ihText)
bInvHierOut.SetFillColor(TColor.GetColor(0.8, 1.0, 0.8))
bInvHierOut.Draw()
bInvHierIn.SetFillColor(TColor.GetColor(0.7, 0.95, 0.7))
bInvHierIn.Draw()
lInvHier.SetTextAlign(12)
lInvHier.SetTextColor(TColor.GetColor(0.1, 0.4, 0.1))
lInvHier.SetTextSize(0.04)
lInvHier.Draw()
if drawKKDC:
hvkkTHalfLo_y = (2.23 - 3. * 0.31) * 1e25
hvkkTHalfHi_y = (2.23 + 3. * 0.44) * 1e25
hvkkMbbLo_meV = SensClass.GetMbb(hvkkTHalfHi_y * CLHEP.year, isotope,
nmeModel, ga) / (1.e-3 * CLHEP.eV)
hvkkMbbHi_meV = SensClass.GetMbb(hvkkTHalfLo_y * CLHEP.year, isotope,
nmeModel, ga) / (1.e-3 * CLHEP.eV)
hvkkBox = TBox(expMin_ty, hvkkMbbLo_meV, 0.98 * expMax_ty, hvkkMbbHi_meV)
def oneDim_matching(blinded):
c1 = Canvas("c1")
c2 = Canvas("c2")
h_mass = ROOT.TH1F('h_mass', '', 40, -20, 20)
h_rap = ROOT.TH1F('h_rap', '', 40, -20, 20)
x, y = ROOT.Double(0), ROOT.Double(0)
for i, year in enumerate(years):
g = getGraph(year)
for j in range(g.GetN()):
g.GetPoint(j,x,y)
ex = g.GetErrorX(j)
ey = g.GetErrorY(j)
h_mass.Fill(x)
h_rap.Fill(y)
c1.cd()
c1.SetTicks(1,1)
h_mass.GetXaxis().SetTitle('(m_{pp}-m_{#gamma#gamma})/#sigma(m_{pp}-m_{#gamma#gamma}}')
h_mass.GetYaxis().SetTitle('Events')
h_mass.SetMarkerStyle(24)
h_mass.SetLineColor( ROOT.kBlack )
h_mass.Sumw2()
min, max = h_mass.GetMinimum(), h_mass.GetMaximum()+3
h_mass.SetMaximum(max)
h_mass.Draw('p')
'''
l1 = TLine(-2,h_mass.GetMinimum(),-2,max)
l1.SetLineColor( ROOT.kRed+1 )
l1.SetLineStyle(2)
l1.SetLineWidth(2)
l2 = TLine(2,h_mass.GetMinimum(),2,max)
l2.SetLineColor( ROOT.kRed+1 )
l2.SetLineStyle(2)
l2.SetLineWidth(2)
l3 = TLine(-3,h_mass.GetMinimum(),-3,max)
l3.SetLineColor( ROOT.kRed+1 )
l3.SetLineStyle(1)
l3.SetLineWidth(2)
l4 = TLine(3,h_mass.GetMinimum(),3,max)
l4.SetLineColor( ROOT.kRed+1 )
l4.SetLineStyle(1)
l4.SetLineWidth(2)
'''
b2 = TBox(-3, min, 3, max-0.05)
if not blinded: b2.SetFillStyle(3001) # transparent
b2.SetFillColor(5)
b2.SetLineColor(1)
b2.Draw()
b1 = TBox(-2, min, 2, max-0.05)
if not blinded: b1.SetFillStyle(3001) # transparent
b1.SetFillColor(3)
b1.SetLineColor(1)
b1.Draw()
pLabel, sLabel, lLabel = prelimLabel(), selectionLabel("#xi^{#pm}_{#gamma#gamma} #in PPS"), lumiLabel()
pLabel.Draw(), sLabel.Draw(), lLabel.Draw()
legend = TLegend(0.7,0.8,0.9,0.9)
legend.AddEntry(b1,"2#sigma matching",'f')
legend.AddEntry(b2,"3#sigma matching",'f')
legend.Draw()
c1.SaveAs('plots/matching/h_mass_1d.%s' % extension)
c2.cd()
c2.SetTicks(1,1)
h_rap.GetXaxis().SetTitle('(y_{pp}-y_{#gamma#gamma})/#sigma(y_{pp}-y_{#gamma#gamma}}')
h_rap.GetYaxis().SetTitle('Events')
h_rap.SetMarkerStyle(24)
h_rap.SetLineColor( ROOT.kBlack )
h_rap.Sumw2()
h_rap.SetMaximum(max)
h_rap.Draw('p')
b2.Draw()
b1.Draw()
pLabel, sLabel, lLabel = prelimLabel(), selectionLabel("#xi^{#pm}_{#gamma#gamma} #in PPS"), lumiLabel()
pLabel.Draw(), sLabel.Draw(), lLabel.Draw()
legend = TLegend(0.7,0.8,0.9,0.9)
legend.AddEntry(b1,"2#sigma matching",'f')
legend.AddEntry(b2,"3#sigma matching",'f')
legend.Draw()
c2.SaveAs('plots/matching/h_rap_1d.%s' % extension)
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...")
def makeCombinedEtaPlot(self, tight=False):
hist = self.makeL1TimeVsEtaPlot(('tight_' if tight else '') +
'dtOnly_bxidVsEta')[2]
countsInL1 = []
for x in np.arange(-.95, 1.05, 0.1):
totalCounter = 0
zeroCount = 0
for y in range(-2, 3):
totalCounter += hist.GetBinContent(hist.FindBin(x, y))
if y == 0:
zeroCount = hist.GetBinContent(hist.FindBin(x, y))
countsInL1.append({
'total': totalCounter,
'zero': zeroCount,
'eta': x
})
#Graph for results
graph1 = TEfficiency(hist.GetName(), "", 8, -9.195, -.5)
graph2 = TEfficiency(hist.GetName(), "", 8, .5, 9.195)
for item in countsInL1:
if item['total'] == 0:
continue
print item['total'], item['zero'], item['eta']
if item['eta'] < 0:
graph1.SetTotalEvents(
graph1.FindFixBin(-0.5 + item['eta'] / 0.087),
int(item['total']))
graph1.SetPassedEvents(
graph1.FindFixBin(-0.5 + item['eta'] / 0.087),
int(item['zero']))
else:
graph2.SetTotalEvents(
graph2.FindFixBin(0.5 + item['eta'] / 0.087),
int(item['total']))
graph2.SetPassedEvents(
graph2.FindFixBin(0.5 + item['eta'] / 0.087),
int(item['zero']))
histHo = None
if tight:
histHo = self.plotTightHoTimeVsEta()[3][1]
else:
histHo = self.plotHoTimeVsEta()[3][1]
histHo.SetTitle(('Tight ' if tight else '') + 'Unmatched DT + HO')
canvas = TCanvas(
'combinedPlot' + ('Tight ' if tight else '') + hist.GetName(),
'combinedPlot')
canvas.cd().SetTopMargin(.15)
histHo.Draw('ap')
canvas.Update()
canvas.cd().SetTicks(0, 0)
histHo.SetMarkerStyle(2)
histHo.SetLineColor(colorRwthDarkBlue)
histHo.SetMarkerColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetRangeUser(-12, 12)
histHo.GetPaintedGraph().GetXaxis().SetLabelColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetTitleColor(colorRwthDarkBlue)
histHo.GetPaintedGraph().GetXaxis().SetAxisColor(colorRwthDarkBlue)
yMax = gPad.GetFrame().GetY2()
yMin = gPad.GetFrame().GetY1()
#Print average Fraction excluding iEta +/-2
x = Double(0)
y = Double(0)
mean = 0
var = 0
for i in range(0, histHo.GetPaintedGraph().GetN()):
histHo.GetPaintedGraph().GetPoint(i, x, y)
if abs(x) == 2:
continue
mean += y
var += histHo.GetPaintedGraph().GetErrorY(
i) * histHo.GetPaintedGraph().GetErrorY(i)
mean /= histHo.GetPaintedGraph().GetN() - 2
sigma = sqrt(var / (histHo.GetPaintedGraph().GetN() - 2))
self.debug(
"Average fraction excluding iEta +/- 2 %s: %5.2f%% +/- %5.2f%%" %
('[Tight]' if tight else '', mean * 100, sigma * 100))
nTotal = 0
nPassed = 0
for item in countsInL1:
if fabs(item['eta']) == 2 or fabs(item['eta'] == 0):
continue
nTotal += item['total']
nPassed += item['zero']
#Print again with ClopperPearson uncertainty, the counts are for L1!!!
mean = nPassed / nTotal * 100
sigmaPlus = TEfficiency.ClopperPearson(int(nTotal), int(nPassed), .68,
1) * 100 - mean
sigmaMinus = mean - TEfficiency.ClopperPearson(
int(nTotal), int(nPassed), .68, 0) * 100
#self.debug("Average fraction excluding iEta +/- 2 %s with Clop.Pear.: %5.2f%% +%5.2f%% -%5.2f%%"
# % ('[Tight]' if tight else '',mean,sigmaPlus,sigmaMinus))
#Left axis part
f1 = TF1("f1", "x", -0.87, 0)
A1 = TGaxis(-10, yMax, -0.5, yMax, "f1", 010, "-")
A1.SetLineColor(colorRwthRot)
A1.SetLabelColor(colorRwthRot)
A1.Draw()
#Right axis part
f2 = TF1("f2", "x", 0, 0.87)
A2 = TGaxis(0.5, yMax, 10, yMax, "f2", 010, "-")
A2.SetLineColor(colorRwthRot)
A2.SetLabelColor(colorRwthRot)
A2.Draw()
#Box for shading out 0
box = TBox(-.5, yMin, 0.5, yMax)
box.SetLineColor(colorRwthDarkGray)
box.SetFillColor(colorRwthDarkGray)
box.SetFillStyle(3013)
box.Draw('same')
#Left L1 eta
graph1.SetMarkerColor(colorRwthRot)
graph1.SetLineColor(colorRwthRot)
graph1.SetMarkerStyle(20)
graph1.Draw('same,p')
#Right L1Eta
graph2.SetMarkerColor(colorRwthRot)
graph2.SetLineColor(colorRwthRot)
graph2.SetMarkerStyle(20)
graph2.Draw('same,p')
#Label for extra axis
axisLabel = TPaveText(0.83, 0.85, 0.89, 0.9, "NDC")
axisLabel.AddText('#eta_{L1}')
axisLabel.SetBorderSize(0)
axisLabel.SetFillStyle(0)
axisLabel.SetTextColor(colorRwthRot)
axisLabel.SetTextSize(0.05)
axisLabel.Draw()
#Legend
legend = getLegend(x1=0.1, y1=0.1, x2=0.4, y2=.35)
legend.AddEntry(histHo, 'HO #in #pm12.5 ns', 'pe')
legend.AddEntry(graph1, ('Tight ' if tight else '') + 'L1 BXID = 0',
'pe')
legend.Draw()
canvas.Update()
self.storeCanvas(canvas,
"combinedFractionL1AndHo" +
('Tight' if tight else ''),
drawMark=False)
return histHo, graph1, canvas, A1, f1, A2, f2, box, graph2, axisLabel, legend
pars.varRanges[pars.var[0]][2])
pull1.GetXaxis().SetTitle(fitter.ws.var(vName1).getTitle(True).Data())
pull1.GetYaxis().SetTitle("pull (#sigma)")
blinder = plot1.findObject('TBox')
blinder2 = None
if blinder:
blinder2 = TBox(pars.exclude[pars.var[0]][0],
pull1.GetYaxis().GetXmin(), pars.exclude[pars.var[0]][1],
pull1.GetYaxis().GetXmax())
blinder2.SetFillColor(kBlack)
blinder2.SetFillStyle(1001)
if blinder2:
#blinder2.Print()
blinder2.Draw()
cp1.Update()
if opts.toyOut:
outFile = open(opts.toyOut, 'a', 1)
fitter.ws.loadSnapshot("genPars")
line = '%s %.6g %.6g %.6g '
outFile.write('nll %f covQual %i edm %.4g ' %
(fr.minNll(), fr.covQual(), fr.edm()))
outFile.write('chi2Prob %f ' % (TMath.Prob(chi2, ndf)))
for cycle in range(0, fr.numStatusHistory()):
outFile.write(
'%s %i ' %
(fr.statusLabelHistory(cycle), fr.statusCodeHistory(cycle)))
def draw(plot,
doBlind=True,
channel='TauMu',
plotprefix=None,
SetLogy=0,
mssm=False):
print plot
Stack.STAT_ERRORS = True
blindxmin = None
blindxmax = None
if doBlind:
if plot.varName == 'svfitMass':
blindxmin = 100
if mssm:
blindxmax = 1000.
else:
blindxmax = 160
elif plot.varName == 'visMass':
blindxmin = 70
blindxmax = 100
titles = xtitles
if channel == 'TauEle':
titles = xtitles_TauEle
xtitle = titles.get(plot.varName, None)
if xtitle is None:
xtitle = ''
global can, pad, padr, ratio
#if pad is None:
if not pad:
can, pad, padr = buildCanvas()
pad.cd()
pad.SetLogy(SetLogy)
plot.DrawStack('HIST')
h = plot.supportHist
h.GetXaxis().SetLabelColor(1)
h.GetXaxis().SetLabelSize(1)
gevperbin = h.GetXaxis().GetBinWidth(1)
h.GetYaxis().SetTitle('Events')
h.GetYaxis().SetTitleOffset(1.4)
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = False
if doBlind:
ratio.Blind(blindxmin, blindxmax, True)
plot.Blind(blindxmin, blindxmax, False)
ratio.DrawDataOverMCMinus1(-0.2, 0.2)
hr = ratio.dataOverMCHist
hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitleSize(0.1)
hr.GetYaxis().SetTitleOffset(0.7)
hr.GetXaxis().SetTitle('{xtitle}'.format(xtitle=xtitle))
hr.GetXaxis().SetTitleSize(0.13)
hr.GetXaxis().SetTitleOffset(0.9)
rls = 0.1
hr.GetYaxis().SetLabelSize(rls)
hr.GetXaxis().SetLabelSize(rls)
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
padr.Update()
# blinding
if doBlind:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(blindxmin, 0, blindxmax, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
# import pdb; pdb.set_trace()
keeper.append(box)
print channel
if channel == 'TauMu': CMSPrelim(plot, pad, '#tau_{#mu}#tau_{h}')
elif channel == 'TauEle': CMSPrelim(plot, pad, '#tau_{e}#tau_{h}')
can.cd()
if plotprefix == None: plotname = plot.varName
else: plotname = plotprefix + '_' + plot.varName
can.SaveAs(plotname + '.png')
pad.SetLogy(0)
return ratio
def draw(plot,
do_ratio=True,
channel='e#mu#mu',
plot_dir='/plots/',
plot_name=None,
SetLogy=0,
blindxmin=None,
blindxmax=None,
unit=None,
server='starseeker',
region='DY',
channel_dir='mmm',
dataset='2017'):
print(plot)
Stack.STAT_ERRORS = True
can = pad = padr = None
if do_ratio:
can, pad, padr = HistDrawer.buildCanvas()
pad.cd()
pad.SetLogy(SetLogy)
else:
can = HistDrawer.buildCanvasSingle()
pad = can
pad.cd()
pad.SetLogy(SetLogy)
# plot.DrawStack('HIST', print_norm=plot.name=='_norm_', ymin=0.1) # magic word to print integrals in legend
plot.DrawStack('HIST', print_norm=('_norm_' in plot.name),
ymin=0.1) # magic word to print integrals in legend
h = plot.supportHist
h.GetXaxis().SetLabelColor(1)
# h.GetXaxis().SetLabelSize(1)
unitsperbin = h.GetXaxis().GetBinWidth(1)
ytitle = 'Events'
if unit:
round_to_n = lambda x, n: round(
x, -int(floor(log10(abs(x)))) + (n - 1))
ytitle += round_to_n(unitsperbin, 3)
h.GetYaxis().SetTitle('Events')
h.GetYaxis().SetTitleOffset(1.4)
h.GetXaxis().SetTitleOffset(2.0)
if do_ratio:
padr.cd()
ratio = copy.deepcopy(plot)
ratio.legendOn = True
ratio.STAT_ERRORS = True
if blindxmin or blindxmax:
if not blindxmin:
blindxmin = 0
if not blindxmax:
blindxmax = plot.stack.totalHist.GetXaxis().GetXmax()
if do_ratio:
ratio.Blind(blindxmin, blindxmax, True)
plot.Blind(blindxmin, blindxmax, False)
if do_ratio:
# ratio.DrawDataOverMCMinus1(-0.5, 0.5)
ratio.DrawDataOverMCMinus1(-0.9, 0.9)
hr = ratio.dataOverMCHist
# Gymnastics to get same label sizes etc in ratio and main plot
ytp_ratio = 2.
xtp_ratio = 2.
# hr.GetYaxis().SetNdivisions(4)
hr.GetYaxis().SetTitleSize(h.GetYaxis().GetTitleSize() * xtp_ratio)
hr.GetXaxis().SetTitleSize(h.GetXaxis().GetTitleSize() * ytp_ratio)
hr.GetYaxis().SetTitleOffset(h.GetYaxis().GetTitleOffset() /
xtp_ratio)
hr.GetXaxis().SetTitleOffset(h.GetXaxis().GetTitleOffset() /
ytp_ratio)
hr.GetYaxis().SetLabelSize(h.GetYaxis().GetLabelSize() * xtp_ratio)
hr.GetXaxis().SetLabelSize(h.GetXaxis().GetLabelSize() * ytp_ratio)
h.GetXaxis().SetLabelColor(0)
h.GetXaxis().SetLabelSize(0)
padr.Update()
# blinding
if blindxmin or blindxmax:
pad.cd()
max = plot.stack.totalHist.GetMaximum()
box = TBox(blindxmin, 0, blindxmax, max)
box.SetFillColor(1)
box.SetFillStyle(3004)
box.Draw()
HistDrawer.keeper.append(box)
HistDrawer.CMSPrelim(plot, pad, channel, legend=plot.legendPos)
can.cd()
gErrorIgnoreLevel = kWarning
h.GetYaxis().SetRangeUser(0, pad.GetUymax() * 1.)
plotname = plot_name if plot_name else plot.name
if ('dz' in plotname) or ('logx' in plotname):
pad.SetLogx(True)
try:
padr.SetLogx(True)
except:
pass
if not os.path.exists(plot_dir + '/pdf/'):
os.mkdir(plot_dir + '/pdf/')
os.mkdir(plot_dir + '/pdf/linear/')
os.mkdir(plot_dir + '/pdf/log/')
if not os.path.exists(plot_dir + '/root/'):
os.mkdir(plot_dir + '/root/')
os.mkdir(plot_dir + '/root/linear/')
os.mkdir(plot_dir + '/root/log')
if not os.path.exists(plot_dir + '/png/'):
os.mkdir(plot_dir + '/png/')
os.mkdir(plot_dir + '/png/linear/')
os.mkdir(plot_dir + '/png/log/')
if not os.path.exists(plot_dir + '/datacards/'):
os.mkdir(plot_dir + '/datacards/')
can.SaveAs(plot_dir + '/pdf/linear/' + plotname + '.pdf')
can.SaveAs(plot_dir + '/root/linear/' + plotname + '.root')
can.SaveAs(plot_dir + '/png/linear/' + plotname + '.png')
if server == "starseeker":
if dataset == '2017':
t3_dir = '/home/dehuazhu/t3work/3_figures/1_DataMC/FinalStates/' + channel_dir + '/' + region.name
if dataset == '2018':
t3_dir = '/home/dehuazhu/t3work/3_figures/1_DataMC/FinalStates/2018/' + channel_dir + '/' + region.name
can.SaveAs(t3_dir + '/pdf/linear/' + plotname + '.pdf')
can.SaveAs(t3_dir + '/root/linear/' + plotname + '.root')
can.SaveAs(t3_dir + '/png/linear/' + plotname + '.png')
# Also save with log y
h.GetYaxis().SetRangeUser(pad.GetUymax() * 5. / 1000000.,
pad.GetUymax() * 1000.)
pad.SetLogy(True)
can.SaveAs(plot_dir + '/png/log/' + plotname + '_log.png')
can.SaveAs(plot_dir + '/root/log/' + plotname + '_log.root')
can.SaveAs(plot_dir + '/pdf/log/' + plotname + '_log.pdf')
if server == "starseeker":
can.SaveAs(t3_dir + '/pdf/log/' + plotname + '_log.pdf')
can.SaveAs(t3_dir + '/root/log/' + plotname + '_log.root')
can.SaveAs(t3_dir + '/png/log/' + plotname + '_log.png')
pad.SetLogy(0)
# if 'dz' in plotname:
if ('dz' in plotname) or ('logx' in plotname):
pad.SetLogx(False)
try:
padr.SetLogx(False)
except:
pass
def pullsVertical_noBonly(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 720, 300 + nbins * 18) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.SetTopMargin(0.01)
canvas.SetRightMargin(0.01)
canvas.SetBottomMargin(0.10)
canvas.SetLeftMargin(0.40)
canvas.SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0])
S_pulls.SetPoint(i, float(l[3]), float(i + 1) - 0.5)
S_pulls.SetPointError(i, float(l[4]), float(l[4]), 0., 0.)
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(0.0)
h_pulls.GetXaxis().SetTitleOffset(0.8)
h_pulls.GetXaxis().SetLabelSize(0.045)
h_pulls.GetXaxis().SetTitleSize(0.050)
h_pulls.GetYaxis().SetLabelSize(0.046)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
S_pulls.SetFillColor(kBlack)
S_pulls.SetLineColor(kBlack)
S_pulls.SetMarkerColor(kBlack)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
#box1.SetFillStyle(3001) # 3001 checkered
#box1.SetFillStyle(0)
box1.SetFillColor(kGreen + 1) # 417
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(kGreen + 1) # 417
box2 = TBox(-2., 0., 2., nbins)
#box2.SetFillStyle(3001) # 3001 checkered
#box2.SetFillStyle(0)
box2.SetFillColor(kOrange) # 800
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(kOrange) # 800
leg = TLegend(0.01, 0.01, 0.3, 0.15)
leg.SetTextSize(0.05)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
#leg.SetNColumns(2)
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
S_pulls.Draw("P6SAME")
leg.Draw()
canvas.RedrawAxis()
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def xi_matching(sector):
c = Canvas("c")
c.cd()
c.SetTicks(1,1)
gr = ROOT.TGraphErrors('gr')
gr_m = ROOT.TGraphErrors('gr_m')
gr.SetName('gr')
gr_m.SetName('gr_m')
x, y = ROOT.Double(0), ROOT.Double(0)
for i, year in enumerate(years):
g = getGraph(year,'xi'+sector)
n_grm = gr_m.GetN() if i > 0 else 0
n_gr = gr.GetN() if i > 0 else 0
for j in range(g.GetN()):
g.GetPoint(j,x,y)
ex = g.GetErrorX(j) # FIXME?
ey = g.GetErrorY(j)
diff = abs(y-x)
if diff < 0.003:
#if diff < 0.02 * x: # only using relative PPS xi error
gr_m.SetPoint(n_grm+j,x,y)
gr_m.SetPointError(n_grm+j,ex,ey)
else:
gr.SetPoint(n_gr+j,x,y)
gr.SetPointError(n_gr+j,ex,ey)
gr.SetMarkerSize(0.6)
gr.SetMarkerStyle(24)
gr_m.SetMarkerSize(0.6)
gr_m.SetMarkerStyle(24)
gr_m.SetMarkerColor(ROOT.kRed)
gr_multi = ROOT.TMultiGraph('gr_multi','')
gr_multi.Add(gr,'AP')
gr_multi.Add(gr_m,'AP')
c.SetGrid()
min, max = 0.0001, 0.25
c.DrawFrame(min,min,max,max)
gr_multi.Draw()
gr_multi.GetXaxis().SetTitleOffset(1.3)
gr_multi.GetYaxis().SetTitleOffset(1.3)
if sector == 'm':
gr_multi.GetXaxis().SetTitle("#xi(p)"+"^{-}")
gr_multi.GetYaxis().SetTitle("#xi(#gamma#gamma)"+"^{-}")
elif sector == 'p':
gr_multi.GetXaxis().SetTitle("#xi(p)"+"^{+}")
gr_multi.GetYaxis().SetTitle("#xi(#gamma#gamma)"+"^{+}")
# Draw y = x line
l = TLine(min, min, max, max)
l.SetLineStyle(2)
l.SetLineWidth(2)
l.Draw()
# Draw shaded region for no acceptance
b = TBox(min, min, 0.015, max)
b.SetFillStyle(3001)
b.SetFillColor(ROOT.kGray)
b.SetLineColor(1)
b.Draw()
# Make legend
legend = TLegend(0.65,0.45,0.8,0.6)
legend.SetBorderSize(0)
legend.SetTextFont(42)
legend.SetTextSize(0.038)
legend.AddEntry(b,"No acceptance",'f')
legend.AddEntry(gr,"Not matching",'p')
legend.AddEntry(gr_m,"Matching at 2#sigma",'p')
legend.Draw()
pLabel, sLabel, lLabel = prelimLabel(), selectionLabel("Tight #xi selection"), lumiLabel()
pLabel.Draw(), sLabel.Draw(), lLabel.Draw()
#c.SaveAs("plots/matching/xi"+sector+"_matching_"+s_years+".pdf")
c.SaveAs("plots/matching/xi%s_matching_%s.%s" % (sector,s_years,extension))
