def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, TH1F, gStyle
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
gStyle.SetOptStat(0000000)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
500)
hs = THStack()
hs1 = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
hData_N2 = infile.Get("Data_N2")
hBkg_N2 = infile.Get("Background_N2")
ratio_data = infile.Get("Data_N%d%s" % (N, suffix))
ratio_data.Sumw2()
ratio_data.Divide(hData_N2, hBkg_N2)
ref_N2 = infile.Get("ReferenceTemplateN2_0")
ref_N3 = infile.Get("ReferenceTemplateN3_0")
ratio_fits = infile.Get("ReferenceTemplateN2_0")
ratio_fits.Sumw2()
ratio_fits.Divide(ref_N2, ref_N3)
legend = TLegend(0.3026613, 0.6919492, 0.6094355, 0.8816102)
legend.SetTextSize(0.041)
#was 0.02966102
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("Multiplicity, N = %d" % N)
else:
legend.SetHeader("Multiplicity, N #geq %d" % N)
legend.AddEntry(ratio_data, "Data/Background", "p")
legend.AddEntry(ratio_fits, "Fit-0 (N=2)/Fit-0 (N=3)", "l")
legend_sm = TLegend(0.6271774, 0.6769492, 0.8308065, 0.8171186)
legend_sm.SetTextSize(0.041)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(2)
h.SetLineStyle(i + 2)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
#legend.AddEntry(h, bh_legend, "l")
if isExclusive:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs1.Add(h, "hist")
#legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
#TH1F *ratio_data
ratio_fits.SetLineColor(4)
ratio_fits.SetMarkerStyle(0)
ratio_fits.SetLineWidth(2)
#hs1.SetMinimum(1e-1)
ratio_fits.Draw("linee1")
ratio_data.Draw("same")
#hs.Draw("samenostack")
#c.SetLogy(1)
ratio_fits.GetXaxis().SetTitle("S_{T} (GeV)")
ratio_fits.GetYaxis().SetTitle("Arbitrary Units")
ratio_fits.GetYaxis().SetTitleOffset(1.1)
ratio_fits.GetYaxis().SetTitleSize(0.045)
ratio_fits.GetYaxis().SetLabelSize(0.045)
ratio_fits.GetXaxis().SetTitleSize(0.045)
ratio_fits.GetXaxis().SetLabelSize(0.045)
ratio_fits.GetXaxis().Draw()
ibin = 0
if isExclusive:
ratio_fits.GetXaxis().SetRangeUser(config.fit_range[0],
config.fit_range[1] + 330)
ibin = hData.FindBin(config.fit_range[0])
else:
ratio_fits.GetXaxis().SetRangeUser(config.norm_range[0],
config.norm_range[1] + 330)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
#gBkg.Draw("LX")
#hData.GetXaxis().SetNdivisions(510)
#hData.Draw("esame")
ratio_fits.SetTitle("")
ratio_fits.SetMinimum(0)
ratio_fits.SetMaximum(3)
legend.Draw("plain")
#if isExclusive:
# legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.45, 0.90, 0.60, 0.93, "brNDC")
else:
cmslabel = TPaveText(0.45, 0.90, 0.60, 0.93, "brNDC")
cmslabel.AddText(config.cmsTitle)
#cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.SetTextSize(0.041)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
if isExclusive:
c.Print("ST_Residuals_Mul%d.pdf" % N)
c.Print("ST_Residuals_Mul%d.png" % N)
else:
c.Print("ST_Mul%dup.pdf" % N)
c.Print("ST_Mul%dup.png" % N)
c.Update()
raw_input("Press Enter to continue...")
getFloat(getLowerBin(iEta), 'p')) * 0.25
if printError and (iEn == "1_5" or iEn == '5_10'
or iEn == '10_15' or iEn == '15_20'):
y1 = (getFloat(getUpperBin(iEn)) +
getFloat(getLowerBin(iEn))) / 2 - (
getFloat(getUpperBin(iEn)) -
getFloat(getLowerBin(iEn))) * 0.75
else:
y1 = (getFloat(getUpperBin(iEn)) +
getFloat(getLowerBin(iEn))) / 2 - (
getFloat(getUpperBin(iEn)) -
getFloat(getLowerBin(iEn))) * 0.25
y2 = (getFloat(getUpperBin(iEn)) + getFloat(getLowerBin(iEn))
) / 2 + (getFloat(getUpperBin(iEn)) -
getFloat(getLowerBin(iEn))) * 0.25
score_print = TPaveText(x1, y1, x2, y2)
if [iEn, iEta] not in lowStatBins:
if printError: #we print the error
for iLine in lineQte:
index1_a = iLine.find(' ')
index1_b = iLine.find(' ', index1_a + 1)
index1_c = iLine.find(' ', index1_b + 1)
index1_d = iLine.find(' ', index1_c + 1)
ETrange = iLine[0:index1_a]
ETArange = iLine[index1_a + 1:index1_b]
if iEn == ETrange and iEta == ETArange:
score_print.AddText('#pm {a}'.format(a=round(
float(iLine[index1_c + 1:index1_d]), 1)))
score_print.SetFillColorAlpha(0, 0)
def plot_fit_results(histograms, category, channel):
global variable, translate_options, b_tag_bin, save_path
#ROOT.TH1.SetDefaultSumw2(False)
ROOT.gROOT.SetBatch(True)
ROOT.gROOT.ProcessLine('gErrorIgnoreLevel = 1001;')
plotting.setStyle()
gStyle.SetTitleYOffset(1.4)
ROOT.gROOT.ForceStyle()
for variable_bin in variable_bins_ROOT[variable]:
path = save_path + '/' + variable + '/' + category + '/fit_results/'
make_folder_if_not_exists(path)
plotname = path + channel + '_bin_' + variable_bin + '.png'
# check if template plots exist already
if os.path.isfile(plotname):
continue
canvas = Canvas(width=700, height=500)
canvas.SetLeftMargin(0.15)
canvas.SetBottomMargin(0.15)
canvas.SetTopMargin(0.05)
canvas.SetRightMargin(0.05)
legend = plotting.create_legend(x0=0.7, y1=0.8)
h_data = histograms[variable_bin]['data']
h_signal = histograms[variable_bin]['signal']
h_background = histograms[variable_bin]['background']
h_data.GetXaxis().SetTitle('Lepton #eta')
h_data.GetYaxis().SetTitle('Number of Events')
h_data.GetXaxis().SetTitleSize(0.05)
h_data.GetYaxis().SetTitleSize(0.05)
h_data.SetMinimum(0)
h_data.SetMarkerSize(1)
h_data.SetMarkerStyle(20)
gStyle.SetEndErrorSize(20)
h_data.Draw('P')
h_signal.SetFillColor(kRed + 1)
h_background.SetFillColor(kGreen - 3)
h_signal.SetLineWidth(2)
h_background.SetLineWidth(2)
h_signal.SetFillStyle(1001)
h_background.SetFillStyle(1001)
mcStack = THStack("MC", "MC")
mcStack.Add(h_background)
mcStack.Add(h_signal)
mcStack.Draw('hist same')
h_data.Draw('error P same')
legend.AddEntry(h_data, 'data', 'P')
legend.AddEntry(h_signal, 'signal', 'F')
legend.AddEntry(h_background, 'background', 'F')
legend.Draw()
mytext = TPaveText(0.5, 0.97, 1, 1.01, "NDC")
channelLabel = TPaveText(0.18, 0.97, 0.5, 1.01, "NDC")
if channel == 'electron':
channelLabel.AddText("e, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
elif channel == 'muon':
channelLabel.AddText("#mu, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
else:
channelLabel.AddText("combined, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
mytext.AddText(
"CMS Preliminary, L = %.1f fb^{-1} at #sqrt{s} = 8 TeV" % (5.8))
mytext.SetFillStyle(0)
mytext.SetBorderSize(0)
mytext.SetTextFont(42)
mytext.SetTextAlign(13)
channelLabel.SetFillStyle(0)
channelLabel.SetBorderSize(0)
channelLabel.SetTextFont(42)
channelLabel.SetTextAlign(13)
mytext.Draw()
channelLabel.Draw()
canvas.Modified()
canvas.Update()
canvas.SaveAs(plotname)
canvas.SaveAs(plotname.replace('png', 'pdf'))
#gROOT.Reset()
c1 = TCanvas('c1', 'Tree Data Structure', 200, 10, 750, 940)
c1.Range(0, -0.1, 1, 1.15)
gBenchmark.Start('tree')
branchcolor = 26
leafcolor = 30
basketcolor = 42
offsetcolor = 43
#title = TPaveLabel(.3,1.05,.8,1.13,c1.GetTitle())
title = TPaveLabel(.3, 1.05, .8, 1.13, 'Tree Data Structure')
title.SetFillColor(16)
title.Draw()
tree = TPaveText(.01, .75, .15, 1.00)
tree.SetFillColor(18)
tree.SetTextAlign(12)
tnt = tree.AddText('Tree')
tnt.SetTextAlign(22)
tnt.SetTextSize(0.030)
tree.AddText('fScanField')
tree.AddText('fMaxEventLoop')
tree.AddText('fMaxVirtualSize')
tree.AddText('fEntries')
tree.AddText('fDimension')
tree.AddText('fSelectedRows')
tree.Draw()
farm = TPavesText(.01, 1.02, .15, 1.1, 9, 'tr')
tfarm = farm.AddText('CHAIN')
tfarm.SetTextSize(0.024)
def Measure_Integral(Fname1, Fname2, Title, XaxisT, low, high, freq, RootName):
FNumber = int((high - low) / freq)
LINK = [3]
# LINK=[15,16,17,18,19]
LINKkChannel = [0, 1, 2, 3, 4, 5]
# LINKkChannel=[0]
for linkChannel in LINKkChannel:
for link in LINK:
xIntegral = array("d", xrange(0, FNumber))
yIntegral = array("d", xrange(0, FNumber))
yIntegralErrUp = array("d", xrange(0, FNumber))
yIntegralErrDown = array("d", xrange(0, FNumber))
xIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMS = array("d", xrange(0, FNumber))
yIntegral_RMSErrUp = array("d", xrange(0, FNumber))
yIntegral_RMSErrDown = array("d", xrange(0, FNumber))
xRatio = array("d", xrange(0, FNumber))
yRatio = array("d", xrange(0, FNumber))
xSingleEv = array("d", xrange(0, 40))
ySingleEv = array("d", xrange(0, 40))
num = -1
for iAmp in range(low, high, freq):
num += 1
Fname = Fname1 + str(iAmp) + Fname2
f = open(Fname)
data = getData(f)
M = TH1F(Fname, Fname, 200, 0.4, 1.4)
HistoSergey = TH1F(Fname, Fname, 200, -10, 200)
M.SetDefaultSumw2()
x = array("d", xrange(0, 1001))
y = array("d", xrange(0, 1001))
for event in xrange(0, 9):
for BX in xrange(0, 40):
xSingleEv[BX] = BX
ySingleEv[BX] = data[event][link][BX][linkChannel]
if BX < 16: HistoSergey.Fill(ySingleEv[BX])
if ySingleEv[BX] <= 0: ySingleEv[BX] = 0.1
if ySingleEv[BX] < 0.1: print "--->", ySingleEv[BX]
scanvas = MakeCanvas("mm", "nn", 800, 800)
scanvas.SetLogy()
GrSingleEv = TGraph(len(xSingleEv), xSingleEv, ySingleEv)
# SFit=TF1("fit", "gaus", 19,23)
# SFit.SetParameter(0, 250)
# SFit.SetParameter(1, 20.9)
# SFit.SetParLimits(1, 20, 22)
# SFit.SetParameter(2, 1)
GrSingleEv.GetXaxis().SetRangeUser(0, 40)
GrSingleEv.GetYaxis().SetRangeUser(0.05, 100000)
GrSingleEv.Draw("AC*")
# GrSingleEv.Fit("fit","R0")
# SFit.Draw("same")
# FitParam=SFit.GetParameters()
# print "Gaus fit param 1, 2, 3= " , round(FitParam[0],4), round(FitParam[1],4), round(FitParam[2],4)
fitInfo = TPaveText(.20, 0.7, .60, 0.9, "NDC")
fitInfo.SetBorderSize(0)
fitInfo.SetFillStyle(0)
fitInfo.SetTextAlign(12)
fitInfo.SetTextSize(0.03)
fitInfo.SetTextColor(1)
fitInfo.SetTextFont(62)
fitInfo.AddText("eventNumber_" + str(event) + "_link" +
str(link) + "_ch_" + str(linkChannel))
fitInfo.Draw()
scanvas.SaveAs("PLOT/singleEv_" + str(iAmp) + "_" +
str(event) + RootName + "_link" +
str(link) + "_ch_" + str(linkChannel) +
".pdf")
sergeycanvas = MakeCanvas("mm", "nn", 800, 800)
HistoSergey.Draw()
sergeycanvas.SaveAs("SergeyHisto" + RootName + "_link" +
str(link) + "_ch_" + str(linkChannel) +
".pdf")
"MPV results;Relative i#eta;Relative i#phi;Rec. E / GeV", 7, -3.5,
3.5, 7, -3.5, 3.5, 20, 0, 4)
for i, scenario in enumerate(scenarioNameList):
canvasList.append(
TCanvas("canvasLandau" + str(i), "Canvas Landau" + str(i), 900, 900))
canvasList[-1].Divide(5, 5)
for j, nameTrunk in enumerate(nameTrunkList):
canvasList[i].cd(j + 1)
localHist = file.Get(nameTrunk + scenario)
if (localHist):
localHist.GetXaxis().SetRangeUser(-.1, 5)
histoList.append(localHist)
localHist.Draw()
localHist.SetStats(0)
paveText = TPaveText(0.4, 0.6, 0.9, 0.9, 'NDC')
paveText.AddText('%s: %.2f' % ('Mean', localHist.GetMean()))
if (localHist.GetEntries() > 3):
localFit = TF1('fit' + str(i * len(nameTrunkList) + j),
"landau")
localFit.SetParameter(1, 0.8)
localFit.SetParameter(2, 0.15)
if (j == int(len(nameTrunkList) / 2)):
localHist.Fit(localFit, "Q", "", 0.2, 3)
else:
localHist.Fit(localFit, "Q", "", 0.2, 3)
if (i == 2):
localI = j % 5
h3D.Fill(localI - 2, 2 - j / 5, localFit.GetParameter(1))
if (localFit.GetNDF() < 4):
lowStatisticsList.append([localI - 2, 2 - j / 5])
pad3.GetFrame().SetFillColor(38)
pad3.GetFrame().SetBorderSize(8)
ntuple.SetMarkerColor(1)
ntuple.Draw('py:px','pz>1')
ntuple.SetMarkerColor(2)
ntuple.Draw('py:px','pz<1','same')
c1.Update()
#
# Display a 3-D scatter plot of 3 columns. Superimpose a different selection.
pad4.cd()
ntuple.Draw('pz:py:px','(pz<10 && pz>6)+(pz<4 && pz>3)')
ntuple.SetMarkerColor(4)
ntuple.Draw('pz:py:px','pz<6 && pz>4','same')
ntuple.SetMarkerColor(5)
ntuple.Draw('pz:py:px','pz<4 && pz>3','same')
l4 = TPaveText(-0.9,0.5,0.9,0.95)
l4.SetFillColor(42)
l4.SetTextAlign(12)
l4.AddText('You can interactively rotate this view in 2 ways:')
l4.AddText(' - With the RotateCube in clicking in this pad')
l4.AddText(' - Selecting View with x3d in the View menu')
l4.Draw()
#
# done
c1.cd()
c1.Update()
gStyle.SetStatColor(19)
gBenchmark.Show('ntuple1')
def plotR2(h5, seql, poll):
norm = 50000
for var in range(0, NVARS):
if var == PHI or var == ALPHA: continue
for pobs in range(0, NPOBS):
if pobs == A: continue
for seq in seql:
outdir_seq = os.path.join(outdir_q2w, SEQ_NAME[seq])
if not os.path.isdir(outdir_seq): os.makedirs(outdir_seq)
cname = ('R2_%s_1%s') % (POBS_NAME[pobs], VARS_NAME[var])
l = TLine(0, 0, 180, 0)
cR2 = TCanvas(cname, cname) #"RvVar", "RvVar")
hR2 = {}
#pltnum=0
for pol in poll:
outdir_pol = os.path.join(outdir_seq, POLS_NAME[pol])
if not os.path.isdir(outdir_pol): os.makedirs(outdir_pol)
if pol != AVG:
hR2[(pol)] = h5[(seq, pol, pobs)].Projection(var)
hR2[(pol)].Scale(1 / math.pi)
hR2[(pol)].Scale(1 / norm)
hR2[(pol)].SetLineColor(
gROOT.ProcessLine("%s" % POLS_COLOR[pol]))
hR2[(pol)].SetMarkerStyle(
gROOT.ProcessLine("kFullCircle"))
elif pol == AVG:
hR2[(AVG)] = hR2[(POS)].Clone("avg")
hR2[(AVG)].Add(hR2[(NEG)])
hR2[(AVG)].Scale(0.5)
if pobs == D:
hR2[(AVG)].SetMinimum(-0.003)
hR2[(AVG)].SetMaximum(0.003)
#Make Titles nice
hR2[(pol)].SetTitle("")
#hR2[(NEG)].SetTitle("")
#hR2[(AVG)].SetTitle("")
#cR2 = {}
#l = TLine(0,0,180,0)
#cname = ('R2%sV%s')%(VARS_NAME[var],VARS_NAME[var])
#if pltnum==0:
hR2[(pol)].Draw("ep")
#else:
# hR2[(pol)].Draw("ep same")
# hR2[(NEG)].Draw("ep same")
#hR2[(AVG)].Draw("ep same")
l.Draw("same")
pt = TPaveText(0.3, 0.85, 0.7, 1.0, "NDC")
q2wt = pt.AddText('[Q^{2}][W] = %s' % q2wdir.GetName())
q2wt.SetTextColor(gROOT.ProcessLine("kBlue"))
vart = pt.AddText(
("%s,%s: %s^{%s} vs. %s") %
(SEQ_NAME[seq], POLS_NAME[pol], POBS_NAME[pobs],
VARS_TITLE[0][var], VARS_TITLE[0][var]))
vart.SetTextSize(0.05)
pt.Draw()
csavename = ('%s/%s') % (outdir_pol, cR2.GetName())
cR2.SaveAs(('%s.png') % (csavename))
print('>>>convert %s.png %s.pdf') % (csavename, csavename)
rc = subprocess.call([
'convert',
'%s.png' % csavename,
'%s.pdf' % csavename
])
if rc != 0: print '.png to .pdf failed for %s' % csavename
h_N2_status.Draw()
c1.Print(outputdir + "N2_status.png")
h_N2_mass.Draw()
c1.Print(outputdir + "N2_mass.png")
h_N2_Pt.Draw()
c1.Print(outputdir + "N2_Pt.png")
h_N2_Eta.Draw()
c1.Print(outputdir + "N2_Eta.png")
h_N2_Phi.Draw()
c1.Print(outputdir + "N2_Phi.png")
fit = h_N2_lifetime_labframe.Fit("expo", "S")
par = [fit.Get().Parameter(i) for i in range(2)]
lifetimeoutput = "Mean Lifetime = " + str(1 / -par[1]) + " ps"
t = TPaveText()
t.SetTextFont(10)
t.AddText(lifetimeoutput)
h_N2_lifetime_labframe.Draw()
t.Draw()
c1.Print(outputdir + "N2_lifetime_labframe.png")
fit = h_N2_lifetime_restframe.Fit("expo", "S")
par = [fit.Get().Parameter(i) for i in range(2)]
lifetimeoutput = "Mean Lifetime = " + str(1 / -par[1]) + " ps"
t = TPaveText()
t.SetTextFont(10)
t.AddText(lifetimeoutput)
h_N2_lifetime_restframe.Draw()
t.Draw()
c1.Print(outputdir + "N2_lifetime_restframe.png")
fit = h_N2_ctau_labframe.Fit("expo", "S")
def fit_hist(histo,
cent_class,
pt_range,
ct_range,
nsigma=3,
model="pol2",
fixsigma=-1,
sigma_limits=None,
mode=3,
split=''):
# canvas for plotting the invariant mass distribution
cv = TCanvas(f'cv_{histo.GetName()}')
# define the number of parameters depending on the bkg model
if 'pol' in str(model):
n_bkgpars = int(model[3]) + 1
elif 'expo' in str(model):
n_bkgpars = 2
else:
print(f'Unsupported model {model}')
# define the fit function bkg_model + gauss
fit_tpl = TF1('fitTpl', f'{model}(0)+gausn({n_bkgpars})', 0, 5)
# redefine parameter names for the bkg_model
for i in range(n_bkgpars):
fit_tpl.SetParName(i, f'B_{i}')
# define parameter names for the signal fit
fit_tpl.SetParName(n_bkgpars, 'N_{sig}')
fit_tpl.SetParName(n_bkgpars + 1, '#mu')
fit_tpl.SetParName(n_bkgpars + 2, '#sigma')
# define parameter values and limits
fit_tpl.SetParameter(n_bkgpars, 40)
fit_tpl.SetParLimits(n_bkgpars, 0.001, 10000)
fit_tpl.SetParameter(n_bkgpars + 1, 2.991)
fit_tpl.SetParLimits(n_bkgpars + 1, 2.986, 3)
# define signal and bkg_model TF1 separately
sigTpl = TF1('fitTpl', 'gausn(0)', 0, 5)
bkg_tpl = TF1('fitTpl', f'{model}(0)', 0, 5)
# plotting stuff for fit_tpl
fit_tpl.SetNpx(300)
fit_tpl.SetLineWidth(2)
fit_tpl.SetLineColor(2)
# plotting stuff for bkg model
bkg_tpl.SetNpx(300)
bkg_tpl.SetLineWidth(2)
bkg_tpl.SetLineStyle(2)
bkg_tpl.SetLineColor(2)
# define limits for the sigma if provided
if sigma_limits != None:
fit_tpl.SetParameter(n_bkgpars + 2,
0.5 * (sigma_limits[0] + sigma_limits[1]))
fit_tpl.SetParLimits(n_bkgpars + 2, sigma_limits[0], sigma_limits[1])
# if the mc sigma is provided set the sigma to that value
elif fixsigma > 0:
fit_tpl.FixParameter(n_bkgpars + 2, fixsigma)
# otherwise set sigma limits reasonably
else:
fit_tpl.SetParameter(n_bkgpars + 2, 0.002)
fit_tpl.SetParLimits(n_bkgpars + 2, 0.001, 0.003)
########################################
# plotting the fits
if mode == 2:
ax_titles = ';m (^{3}He + #pi) (GeV/#it{c})^{2};Counts' + f' / {round(1000 * histo.GetBinWidth(1), 2)} MeV'
if mode == 3:
ax_titles = ';m (d + p + #pi) (GeV/#it{c})^{2};Counts' + f' / {round(1000 * histo.GetBinWidth(1), 2)} MeV'
# invariant mass distribution histo and fit
histo.UseCurrentStyle()
histo.SetLineColor(1)
histo.SetMarkerStyle(20)
histo.SetMarkerColor(1)
histo.SetTitle(ax_titles)
histo.SetMaximum(1.5 * histo.GetMaximum())
histo.Fit(fit_tpl, "QRL", "", 2.96, 3.04)
histo.Fit(fit_tpl, "QRL", "", 2.96, 3.04)
histo.SetDrawOption("e")
histo.GetXaxis().SetRangeUser(2.96, 3.04)
# represent the bkg_model separately
bkg_tpl.SetParameters(fit_tpl.GetParameters())
bkg_tpl.SetLineColor(600)
bkg_tpl.SetLineStyle(2)
bkg_tpl.Draw("same")
# represent the signal model separately
sigTpl.SetParameter(0, fit_tpl.GetParameter(n_bkgpars))
sigTpl.SetParameter(1, fit_tpl.GetParameter(n_bkgpars + 1))
sigTpl.SetParameter(2, fit_tpl.GetParameter(n_bkgpars + 2))
sigTpl.SetLineColor(600)
# sigTpl.Draw("same")
# get the fit parameters
mu = fit_tpl.GetParameter(n_bkgpars + 1)
muErr = fit_tpl.GetParError(n_bkgpars + 1)
sigma = fit_tpl.GetParameter(n_bkgpars + 2)
sigmaErr = fit_tpl.GetParError(n_bkgpars + 2)
signal = fit_tpl.GetParameter(n_bkgpars) / histo.GetBinWidth(1)
errsignal = fit_tpl.GetParError(n_bkgpars) / histo.GetBinWidth(1)
bkg = bkg_tpl.Integral(mu - nsigma * sigma,
mu + nsigma * sigma) / histo.GetBinWidth(1)
if bkg > 0:
errbkg = math.sqrt(bkg)
else:
errbkg = 0
# compute the significance
if signal + bkg > 0:
signif = signal / math.sqrt(signal + bkg)
deriv_sig = 1 / math.sqrt(signal + bkg) - signif / (2 * (signal + bkg))
deriv_bkg = -signal / (2 * (math.pow(signal + bkg, 1.5)))
errsignif = math.sqrt((errsignal * deriv_sig)**2 +
(errbkg * deriv_bkg)**2)
else:
signif = 0
errsignif = 0
# print fit info on the canvas
pinfo2 = TPaveText(0.5, 0.5, 0.91, 0.9, "NDC")
pinfo2.SetBorderSize(0)
pinfo2.SetFillStyle(0)
pinfo2.SetTextAlign(30 + 3)
pinfo2.SetTextFont(42)
string = f'ALICE Internal, Pb-Pb 2018 {cent_class[0]}-{cent_class[1]}%'
pinfo2.AddText(string)
decay_label = {
"": [
'{}^{3}_{#Lambda}H#rightarrow ^{3}He#pi^{-} + c.c.',
'{}^{3}_{#Lambda}H#rightarrow dp#pi^{-} + c.c.'
],
"_matter": [
'{}^{3}_{#Lambda}H#rightarrow ^{3}He#pi^{-}',
'{}^{3}_{#Lambda}H#rightarrow dp#pi^{-}'
],
"_antimatter": [
'{}^{3}_{#bar{#Lambda}}#bar{H}#rightarrow ^{3}#bar{He}#pi^{+}',
'{}^{3}_{#Lambda}H#rightarrow #bar{d}#bar{p}#pi^{+}'
],
}
string = decay_label[split][
mode -
2] + ', %i #leq #it{ct} < %i cm %i #leq #it{p}_{T} < %i GeV/#it{c} ' % (
ct_range[0], ct_range[1], pt_range[0], pt_range[1])
pinfo2.AddText(string)
string = f'Significance ({nsigma:.0f}#sigma) {signif:.1f} #pm {errsignif:.1f} '
pinfo2.AddText(string)
string = f'S ({nsigma:.0f}#sigma) {signal:.0f} #pm {errsignal:.0f}'
pinfo2.AddText(string)
string = f'B ({nsigma:.0f}#sigma) {bkg:.0f} #pm {errbkg:.0f}'
pinfo2.AddText(string)
if bkg > 0:
ratio = signal / bkg
string = f'S/B ({nsigma:.0f}#sigma) {ratio:.4f}'
pinfo2.AddText(string)
pinfo2.Draw()
gStyle.SetOptStat(0)
st = histo.FindObject('stats')
if isinstance(st, TPaveStats):
st.SetX1NDC(0.12)
st.SetY1NDC(0.62)
st.SetX2NDC(0.40)
st.SetY2NDC(0.90)
st.SetOptStat(0)
histo.Write()
cv.Write()
return (signal, errsignal, signif, errsignif, mu, muErr, sigma, sigmaErr)
return (signal, errsignal, signif, errsignif, sigma, sigmaErr)
def main():
from optparse import OptionParser
parser = OptionParser()
parser.add_option("-i", "--inputfile", dest="inputfile")
parser.add_option("-N", "--multiplicity", dest="N", type="int", default=3)
parser.add_option("-x", "--exclusive", action="store_true",\
dest="isExclusive", default=False)
parser.add_option("-l", "--label", dest="label", type="string", default="")
(options, args) = parser.parse_args()
N = options.N
isExclusive = options.isExclusive
label_text = options.label
if isExclusive and not (N == 2 or N == 3):
parser.error("Exclusive plot only for N =2 or 3")
import configurations as config
from ROOT import TFile, TCanvas, THStack, TLegend, TPaveText, gStyle
from ModelParser import ModelKey
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadRightMargin(0.05)
suffix = ""
if not isExclusive:
suffix = "up"
sm_files = []
for model in config.sm_models:
f = TFile("%s/%s.root" % (config.sm_dir, model), "READ")
sm_files.append(f)
bh_weights = []
bh_files = []
from BHXsec import BHXsec
xsec = BHXsec()
for model in config.bh_showcase:
f = TFile("%s/%s.root" % (config.bh_dir, model), "READ")
bh_files.append(f)
h = f.Get("plotsNoCut/ST")
nEvents = h.GetEntries()
bh_weights.append(
xsec.get(model) / nEvents * config.integrated_luminosity)
c = TCanvas("ST_Mul%d%s" % (N, suffix), "ST_Mul%d%s" % (N, suffix), 500,
500)
hs = THStack()
infile = TFile(options.inputfile, "READ")
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
gBkg = infile.Get("BackgroundGraph_N%d%s" % (N, suffix))
hData = infile.Get("Data_N%d%s" % (N, suffix))
hBkg = infile.Get("Background_N%d%s" % (N, suffix))
hBkg.SetMarkerSize(0)
hBkg_ = hBkg.Clone("BkgLine")
hBkg.SetFillColor(33)
hBkg.SetLineColor(33)
hBkg_.SetLineWidth(3)
hBkg_.SetLineColor(862)
hs.Add(hBkg, "e3")
legend = TLegend(0.3326613, 0.6419492, 0.9294355, 0.9216102)
legend.SetTextSize(0.02966102)
legend.SetTextFont(42)
legend.SetFillColor(0)
legend.SetLineColor(0)
if isExclusive:
legend.SetHeader("N = %d" % N)
else:
legend.SetHeader("N #geq %d" % N)
legend.AddEntry(hData, "Data", "p")
legend.AddEntry(hBkg_, "Background", "l")
legend.AddEntry(hBkg, "Uncertainty", "f")
legend_sm = TLegend(0.6471774, 0.7669492, 0.8508065, 0.8771186)
legend_sm.SetTextSize(0.02966102)
legend_sm.SetTextFont(42)
legend_sm.SetFillColor(0)
legend_sm.SetLineColor(0)
for i, f in enumerate(bh_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(bh_weights[i])
# Add background
for ibin in range(h.GetNbinsX()):
h.SetBinContent(ibin+1,\
h.GetBinContent(ibin+1)\
+ hBkg.GetBinContent(ibin+1))
h.SetLineWidth(2)
h.SetLineStyle(i + 2)
hs.Add(h, "hist")
model = ModelKey(config.bh_showcase[i])
bh_legend = "M_{D} = %.1f TeV, M_{BH}^{ min} = %.1f TeV, n = %d" % (\
model.parameter["MD"],
model.parameter["M"],
model.parameter["n"])
legend.AddEntry(h, bh_legend, "l")
# if isExclusive:
for i, f in enumerate(sm_files):
h = f.Get("plotsN%d%s/ST" % (N, suffix))
h.Rebin(config.rebin)
h.Scale(config.integrated_luminosity)
h.SetFillColor(config.sm_colors[i])
h.SetLineColor(config.sm_colors[i])
hs.Add(h, "hist")
legend_sm.AddEntry(h, config.sm_models[i], "f")
#hs.Add(hData, "e")
hs.Draw("nostack")
c.SetLogy(1)
hs.GetXaxis().SetTitle("S_{T} (GeV)")
hs.GetYaxis().SetTitle(hData.GetYaxis().GetTitle())
hs.GetYaxis().SetTitleOffset(1.2)
ibin = 0
if isExclusive:
hs.GetXaxis().SetRangeUser(config.fit_range[0], config.maxST)
ibin = hData.FindBin(config.fit_range[0])
else:
hs.GetXaxis().SetRangeUser(config.norm_range[0], config.maxST)
ibin = hData.FindBin(config.norm_range[0])
from Styles import formatUncertainty
formatUncertainty(gBkg)
gBkg.Draw("LX")
hData.Draw("esame")
hs.SetMinimum(5e-2)
if isExclusive:
hs.SetMaximum(hData.GetBinContent(ibin) * 20)
else:
#hs.SetMaximum(4e4)
hs.SetMaximum(hData.GetBinContent(ibin) * 20)
legend.Draw("plain")
if isExclusive:
legend_sm.Draw("plain")
if isExclusive:
cmslabel = TPaveText(0.5544355, 0.5127119, 0.8991935, 0.6292373,
"brNDC")
else:
cmslabel = TPaveText(0.1955645, 0.1631356, 0.5403226, 0.279661,
"brNDC")
cmslabel.AddText(config.cmsTitle)
cmslabel.AddText(config.cmsSubtitle)
cmslabel.SetFillColor(0)
cmslabel.Draw("plain")
label = TPaveText(0.8891129, 0.8644068, 0.9435484, 0.9258475, "brNDC")
label.SetFillColor(0)
label.SetTextSize(0.0529661)
label.AddText(label_text)
label.Draw("plain")
c.Update()
raw_input("Press Enter to continue...")
# # The function "ls()" lists the directory contents of this file # fill.ls() # # Get object "sqroot" from the file. # sqroot = gROOT.FindObject( 'sqroot' ) sqroot.Print() # # Now fit histogram h1f with the function sqroot # h1f = gROOT.FindObject( 'h1f' ) h1f.SetFillColor( 45 ) h1f.Fit( 'sqroot' ) # We now annotate the picture by creating a PaveText object # and displaying the list of commands in this macro # fitlabel = TPaveText( 0.6, 0.3, 0.9, 0.80, 'NDC' ) fitlabel.SetTextAlign( 12 ) fitlabel.SetFillColor( 42 ) fitlabel.ReadFile(path.join(str(gROOT.GetTutorialDir()), 'pyroot', 'fit1_py.py')) fitlabel.Draw() c1.Update() gBenchmark.Show( 'fit1' )
def main():
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(11)
hh=TH2D('hh',';X;Y',22,-10.5,11.5,22,-10.5,11.5)
hi=TH2I('hi',';X;Y',22,-10.5,11.5,22,-10.5,11.5)
setupHists([hh,hi])
xax,yax=hh.GetXaxis(),hh.GetYaxis()
hh.Draw('COLZ')
hi.Draw('TEXTSAME')
gPad.SetLogz()
gPad.SetGrid(1,1)
gPad.SetLeftMargin(0.09)
gPad.SetRightMargin(0.11)
#tt2=TPaveText(0.7,0.96,0.9,0.99,'NDC')
ttM=TPaveText(-3+0.05, 7-4.45, 4.0, 8-4.51)
tt2=TPaveText(-3+0.05, 7-5.45, 4.0, 8-5.51)
ttX=TPaveText(-2, 7-8.00, 3, 8-8.00)
ttY=TPaveText(-2, 7-9.00, 3, 8-9.00)
ttZ=TPaveText(-2, 6-8.80, 3, 8-9.30)
ttZ.AddText("positive = beam top/right")
ttime=TPaveText(-10,-12.5,10,-11.8)
tchan=TPaveText(0,0,0.9,1)
setupPaveTexts([tt2,ttM,ttime,tchan,ttX,ttY,ttZ])
ttM.SetTextColor(2)
ttM.SetFillStyle(0)
ttZ.SetFillStyle(0)
tt2.SetFillStyle(0)
tarrow=TText(-0.9,0.7,'Beam Right')
tarrow.SetTextSizePixels(15)
arrow=TArrow(-1.4,0.5,2.4,0.5,0.02,'|>')
arrow.SetAngle(40)
arrow.SetFillColor(1)
arrow.SetLineWidth(2)
tt=TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.04)
tt.DrawText(12.4,0,'kHz')
tt.SetTextAngle(0)
tt.SetTextColor(1)
tt.DrawTextNDC(0.3,0.92,'FTC FADC SCALERS')
bb=TBox()
bb.SetFillStyle(1001)
bb.SetFillColor(0)
bb.SetLineWidth(1)
bb.SetLineColor(1)
bb.DrawBox(-3.47,-1.47,4.47,2.46)
bb.DrawBox(-1.47,-3.47,2.49,4.47)
bb.DrawBox(-2.47,-2.47,3.49,3.47)
cc.cd()
for xx in [ttM,tt2,ttime,arrow,tarrow,ttX,ttY,ttZ]: xx.Draw()
cc2.cd()
tchan.Draw('NDC')
cc.cd()
gPad.SetEditable(0)
while True:
for ch in ECAL.chans:
loadPV(ch)
ch=ch.vals
xx,yy=ch['X'],ch['Y']
#if (ch['PVVAL']>10):
# print xx,yy,ch['PVVAL']
# swap x to make it downstream view:
xx=-xx
#after, fix the fact x=0 / y=0 don't exists
if xx<0: xx+=1
if yy<0: yy+=1
hh.SetBinContent(xax.FindBin(xx),yax.FindBin(yy),ch['PVVAL'])
hi.SetBinContent(xax.FindBin(xx),yax.FindBin(yy),ch['PVVAL'])
for xx in [ttime,tt2,ttM,ttX,ttY]: xx.Clear()
[total,maximum,top,bottom,left,right]=calcRates(ECAL.chans)
tt2.AddText('Total: %.1f MHz'%(total/1000))
ttM.AddText('Max: %.0f kHz'%(maximum))
if total>1e2:
xasy = (right-left)/total
yasy = (top-bottom)/total
ttX.AddText('X-Asy: %+.1f%%'%(100*xasy))
ttY.AddText('Y-Asy: %+.1f%%'%(100*yasy))
else:
ttX.AddText('X-Asy: N/A')
ttY.AddText('Y-Asy: N/A')
ttime.AddText(makeTime())
if not gPad: sys.exit()
if gPad.GetEvent()==11:
xy=pix2xy(gPad)
ee=ECAL.findChannelXY(xy[0],xy[1])
if ee:
tchan.Clear()
tchan.AddText(printChannel(ee))
cc2.Modified()
cc2.Update()
elif gPad.GetEvent()==12:
tchan.Clear()
cc2.Modified()
cc2.Update()
cc.Modified()
cc.Update()
time.sleep(2)
parser = OptionParser()
parser.add_option('--plotDir',
metavar='P',
type='string',
action='store',
default='Summer2018Plots',
dest='plotDir',
help='output directory of plots')
(options, args) = parser.parse_args()
outDir = options.plotDir
execfile("input.py")
c1 = TCanvas('c1', 'c1', 1800, 1000)
pt1 = TPaveText(.05, .05, .15, .95)
pt2 = TPaveText(0.15, 0.05, 0.23, 0.95)
pt3 = TPaveText(0.23, 0.05, 0.31, 0.95)
pt4 = TPaveText(0.31, 0.05, 0.39, 0.95)
pt5 = TPaveText(0.39, 0.05, 0.47, 0.95)
pt6 = TPaveText(0.47, 0.05, 0.55, 0.95)
pt7 = TPaveText(0.55, 0.05, 0.63, 0.95)
pt8 = TPaveText(0.63, 0.05, 0.71, 0.95)
pt9 = TPaveText(0.71, 0.05, 0.79, 0.95)
pt10 = TPaveText(0.79, 0.05, 0.87, 0.95)
pt11 = TPaveText(0.87, 0.05, 0.95, 0.95)
pt1.AddText("Sample")
pt1.AddLine(0.0, 0.1, 1.0, 0.1)
pt1.AddText("DYToLL")
pt1.AddLine(0.0, 0.2, 1.00, .200)
def plotEfficiency(self, doFit = False):
if hasattr(self, "Denominator") and hasattr(self, "Numerator"):
if self._rebinFactor != 1:
self.Denominator["hist"].Rebin(self._rebinFactor)
self.Numerator["hist"].Rebin(self._rebinFactor)
for ibin in range(-1, self.Numerator["hist"].GetNbinsX()+1):
if self.Numerator["hist"].GetBinContent(ibin+1) > self.Denominator["hist"].GetBinContent(ibin+1):
print('Fixing bad bin:', (ibin+1))
self.Numerator["hist"].SetBinContent(ibin+1, self.Denominator["hist"].GetBinContent(ibin+1))
self.Numerator["hist"].SetBinError(ibin+1, self.Denominator["hist"].GetBinError(ibin+1))
efficiencyGraph = TGraphAsymmErrors(self.Numerator["hist"], self.Denominator["hist"], "cp")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
pt_cmsPrelim.AddText("CMS Preliminary")
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText(self._luminosityLabel)
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.0349127)
pt_leg.SetTextAlign(12)
if self._leg == "METLeg":
legLabel = ""
for filt in self._metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + self._metHLTFilters[-1]
pt_leg.AddText(legLabel)
pt_leg.AddText(self._datasetLabel)
if self._leg == "TrackLeg":
pt_leg.AddText(self._path + "*")
pt_leg.AddText(self._datasetLabel)
legLabel = ""
for filt in self._metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + self._metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if self._leg == "METPath":
if self._path == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
pt_leg.AddText(self._path + "*")
pt_leg.AddText(self._datasetLabel)
lumiLabel = TPaveText(0.66416, 0.937339, 0.962406, 0.992894, "brNDC")
lumiLabel.SetBorderSize(0)
lumiLabel.SetFillStyle(0)
lumiLabel.SetTextFont(42)
lumiLabel.SetTextSize(0.0387597)
lumiLabel.AddText(str (self._luminosityLabel))
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
if self._leg == "METLeg" or self._leg == "METPath":
backgroundHist.GetXaxis().SetTitle(self._metLegAxisTitle)
elif self._leg == "TrackLeg":
backgroundHist.GetXaxis().SetTitle(self._trackLegAxisTitle)
SetStyle(backgroundHist)
SetStyle(efficiencyGraph)
self._canvas.cd()
backgroundHist.Draw()
efficiencyGraph.Draw("P")
pt_cmsPrelim.Draw("same")
pt_lumi.Draw("same")
pt_leg.Draw("same")
oneLine.Draw("same")
if doFit:
(fitFunc, fitText) = self.PlotFit(efficiencyGraph)
fitFunc.Draw("same")
fitText.Draw("same")
if not os.path.exists('plots_' + self.Denominator["sample"]):
os.mkdir('plots_' + self.Denominator["sample"])
if self._leg == "METPath":
self._canvas.SaveAs('plots_' + self.Denominator["sample"] + '/' + self._path + "_Efficiency.pdf")
else:
self._canvas.SaveAs('plots_' + self.Denominator["sample"] + '/' + self._path + "_" + self._leg + ".pdf")
self._fout.cd()
if self._tgraphSuffix is not None:
efficiencyGraph.Write(self._path + "_" + self._leg + "_" + self._tgraphSuffix)
if doFit:
fitFunc.Write(self._path + "_" + self._leg + "_" + self._tgraphSuffix + "_fitResult")
else:
efficiencyGraph.Write(self._path + "_" + self._leg)
if doFit:
fitFunc.Write(self._path + "_" + self._leg + "_fitResult")
else:
print("Denominator and Numerator must be defined for path ", self._path, ", leg ", self._leg)
return 0.0
def make_mutefreq_plot(plotdir, gene_name, positions):
nuke_colors = {
'A': kRed + 1,
'C': kBlue - 7,
'G': kOrange - 3,
'T': kGreen + 2
}
ibin = 0
drawn_name_texts, lines, vlines, texts = {}, {}, {}, {}
for info in positions:
posname = info['name']
# make label below bin
drawn_name_texts[posname] = TPaveText(-0.5 + ibin, -0.1, 0.5 + ibin,
-0.05)
drawn_name_texts[posname].SetBorderSize(0)
drawn_name_texts[posname].SetFillColor(0)
drawn_name_texts[posname].SetFillStyle(0)
drawn_name_texts[posname].AddText(-0.5 + ibin, -0.075,
simplify_state_name(posname))
total = 0.0
lines[posname], vlines[posname], texts[posname] = [], [], []
for nuke, prob in sorted(info['nuke_freqs'].items(),
key=operator.itemgetter(1),
reverse=True):
# horizontal line at height total+prob
lines[posname].append(
TLine(-0.5 + ibin, total + prob, 0.5 + ibin, total + prob))
lines[posname][-1].SetLineWidth(6)
# vertical line from total to total+prob
vlines[posname].append(TLine(ibin, total, ibin, total + prob))
vlines[posname][-1].SetLineWidth(6)
vlines[posname][-1].SetLineColor(nuke_colors[nuke])
# write [ACGT] at midpoint between total and total+prob
midpoint = 0.5 * (prob + 2 * total)
texts[posname].append(
TPaveText(-0.5 + ibin, midpoint - 0.04, 0.5 + ibin,
midpoint + 0.01))
texts[posname][-1].AddText(-0.5 + ibin, midpoint, nuke)
texts[posname][-1].SetBorderSize(0)
texts[posname][-1].SetFillColor(0)
texts[posname][-1].SetFillStyle(0)
total += prob
ibin += 1
cvn = TCanvas('cvn-2', '', 1000, 300)
n_bins = ibin
hframe = TH1D(gene_name + '-emission-frame',
utils.unsanitize_name(gene_name), n_bins, -0.5, n_bins - 0.5)
hframe.SetNdivisions(202, 'y')
hframe.SetNdivisions(0, 'x')
hframe.Draw()
for state_name in lines.keys():
drawn_name_texts[state_name].Draw()
for itrans in range(len(lines[state_name])):
# lines[state_name][itrans].Draw() # hm, maybe don't need the horizontal lines any more
vlines[state_name][itrans].Draw()
# texts[state_name][itrans].Draw() # don't label the bases at the moment, you can tell by the color just fine
cvn.SaveAs(plotdir + '/plots/' + gene_name + '.png')
#gPad.SetRightMargin(0.15)
h_theta_phi.GetZaxis().SetRangeUser(0, 1)
h_theta_phi.GetXaxis().SetRangeUser(60, 120)
h_theta_phi.GetYaxis().SetRangeUser(-90, -45)
h_theta_phi.SetMarkerSize(2.5)
gPad.SetBottomMargin(0.17)
gPad.SetLeftMargin(0.13)
gPad.SetTopMargin(0.15)
gPad.SetRightMargin(0.15)
h_theta_phi.GetYaxis().SetTitleSize(0.07)
h_theta_phi.GetXaxis().SetTitleSize(0.07)
h_theta_phi.GetYaxis().SetTitleOffset(0.8)
pt = TPaveText(0.13, 0.855, 0.42, 0.98, "ndc")
pt.AddText("MicroBooNE")
pt.SetFillColor(0)
pt.SetBorderSize(0)
pt.SetShadowColor(0)
h_theta_phi.Draw("colz texte")
pt.Draw()
h_theta_phi.SaveAs("plots/%s/e_theta_phi_%s.root" %
("data" if data else "mc", algo))
c_theta_phi.SaveAs("plots/%s/e_theta_phi.pdf" % ("data" if data else "mc"))
c_theta_phi.Update()
c_theta_l = TCanvas("c_theta_l", "theta_l")
c_theta_l.cd()
fs.append(f / NN)
f = 0.0
#Average the final 100 values?
avgs.append(np.mean(fs[len(fs) - 100:len(fs)]))
c1 = TCanvas()
tg = TGraph()
for i in xrange(len(avgs)):
tg.SetPoint(i, i, avgs[i])
looks_minos()
tf = TF1("tf", "[0]*exp([1]*x)+[2]", 0, 10)
title = TPaveText(0.5014368, 0.7478814, 0.9022989, 0.8177966, "nbNDC")
title.SetFillColor(0)
title.SetFillStyle(0)
title.SetLineColor(0)
title.AddText("p0 exp(p1*n) + p2")
tg.SetMarkerStyle(6)
tg.Fit("tf")
gStyle.SetOptFit(1111)
tg.SetLineWidth(2)
tg.Draw("AL")
title.Draw("SAMES")
tg.GetYaxis().SetTitle("<#sigma_{x} #sigma_{y}>")
tg.GetXaxis().SetTitle("n")
logging.basicConfig(level=logging.INFO)
assert isfile(args.pulls_file)
import ROOT
from ROOT import TFile, TPaveText, gStyle, gROOT
tfile = TFile(args.pulls_file)
gStyle.SetOptStat(0)
gROOT.SetBatch()
#c1 = TCanvas("c1","Pull Shorter Version",200,10,800,800);
##c1.SetGrid();
#c1.DrawFrame(0.85,0.75,1.15,1.25);
nuisancs = tfile.Get('nuisancs')
nuisancs.Draw()
pt = TPaveText(.5, 1.7, 0.5 + args.label_width, 2.7)
if 'pulls_of_nuisances_both' in args.pulls_file:
pt.AddText("both channels")
elif 'pulls_of_nuisances_mu' in args.pulls_file:
pt.AddText("muon-tau channel")
else:
pt.AddText("electron-tau channel")
pt.Draw("same")
nuisancs.SaveAs(args.pulls_file.replace('.root', '.png'))
def drawhist(isMET, reg, dirPath):
path_before = "analysis_histogram/2018_old/"
path_after = "analysis_histogram/2018_hem_cut_updated/"
if isMET:
openfcomb = TFile(path_before + "combined_data_MET.root")
openfAB = TFile(path_before + "combined_data_MET_AB.root")
openfCD_bfr = TFile(path_before + "combined_data_MET_CD.root")
openfCD = TFile(path_after + "combined_data_MET_CD.root")
h_jet1phi_1b = []
jet1phi_comb_top1b = openfcomb.Get("h_reg_TopmunuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_comb_top1b)
jet1phi_AB_top1b = openfAB.Get("h_reg_TopmunuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_AB_top1b)
jet1phi_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopmunuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_CD_bfr_top1b)
jet1phi_CD_top1b = openfCD.Get("h_reg_TopmunuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_CD_top1b)
h_jet1eta_1b = []
jet1eta_comb_top1b = openfcomb.Get("h_reg_TopmunuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_comb_top1b)
jet1eta_AB_top1b = openfAB.Get("h_reg_TopmunuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_AB_top1b)
jet1eta_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopmunuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_CD_bfr_top1b)
jet1eta_CD_top1b = openfCD.Get("h_reg_TopmunuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_CD_top1b)
#h_MET_1b = []
#MET_comb_top1b = openfcomb.Get("h_reg_TopmunuCR_1b_MET")
#h_MET_1b.append(MET_comb_top1b)
#MET_AB_top1b = openfAB.Get("h_reg_TopmunuCR_1b_MET")
#h_MET_1b.append(MET_AB_top1b)
#MET_CD_top1b = openfCD.Get("h_reg_TopmunuCR_1b_MET")
#h_MET_1b.append(MET_CD_top1b)
h_METphi_1b = []
METphi_comb_top1b = openfcomb.Get("h_reg_TopmunuCR_1b_METPhi")
h_METphi_1b.append(METphi_comb_top1b)
METphi_AB_top1b = openfAB.Get("h_reg_TopmunuCR_1b_METPhi")
h_METphi_1b.append(METphi_AB_top1b)
METphi_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopmunuCR_1b_METPhi")
h_METphi_1b.append(METphi_CD_bfr_top1b)
METphi_CD_top1b = openfCD.Get("h_reg_TopmunuCR_1b_METPhi")
h_METphi_1b.append(METphi_CD_top1b)
h_RecoilPhi_1b = []
RecoilPhi_comb_top1b = openfcomb.Get("h_reg_TopmunuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_comb_top1b)
RecoilPhi_AB_top1b = openfAB.Get("h_reg_TopmunuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_AB_top1b)
RecoilPhi_CD_bfr_top1b = openfCD_bfr.Get(
"h_reg_TopmunuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_CD_bfr_top1b)
RecoilPhi_CD_top1b = openfCD.Get("h_reg_TopmunuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_CD_top1b)
h_jet1phi_2b = []
jet1phi_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_comb_top2b)
jet1phi_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_AB_top2b)
jet1phi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopmunuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_CD_bfr_top2b)
jet1phi_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_CD_top2b)
h_jet2phi_2b = []
jet2phi_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_comb_top2b)
jet2phi_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_AB_top2b)
jet2phi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopmunuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_CD_bfr_top2b)
jet2phi_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_CD_top2b)
h_jet1eta_2b = []
jet1eta_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_comb_top2b)
jet1eta_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_AB_top2b)
jet1eta_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopmunuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_CD_bfr_top2b)
jet1eta_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_CD_top2b)
h_jet2eta_2b = []
jet2eta_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_comb_top2b)
jet2eta_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_AB_top2b)
jet2eta_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopmunuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_CD_bfr_top2b)
jet2eta_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_CD_top2b)
#h_MET_2b = []
#MET_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_MET")
#h_MET_2b.append(MET_comb_top2b)
#MET_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_MET")
#h_MET_2b.append(MET_AB_top2b)
#MET_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_MET")
#h_MET_2b.append(MET_CD_top2b)
h_METphi_2b = []
METphi_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_METPhi")
h_METphi_2b.append(METphi_comb_top2b)
METphi_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_METPhi")
h_METphi_2b.append(METphi_AB_top2b)
METphi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopmunuCR_2b_METPhi")
h_METphi_2b.append(METphi_CD_bfr_top2b)
METphi_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_METPhi")
h_METphi_2b.append(METphi_CD_top2b)
#h_RecoilPhi_2b = []
#RecoilPhi_comb_top2b = openfcomb.Get("h_reg_TopmunuCR_2b_RecoilPhi")
#h_RecoilPhi_2b.append(RecoilPhi_comb_top2b)
#RecoilPhi_AB_top2b = openfAB.Get("h_reg_TopmunuCR_2b_RecoilPhi")
#h_RecoilPhi_2b.append(RecoilPhi_AB_top2b)
#RecoilPhi_CD_top2b = openfCD.Get("h_reg_TopmunuCR_2b_RecoilPhi")
#h_RecoilPhi_2b.append(RecoilPhi_CD_top2b)
alllist = []
alllist.append(h_jet1phi_1b)
#alllist.append(h_jet2phi_1b)
alllist.append(h_jet1eta_1b)
#alllist.append(h_jet2eta_1b)
#alllist.append(h_MET_1b)
alllist.append(h_METphi_1b)
alllist.append(h_RecoilPhi_1b)
alllist.append(h_jet1phi_2b)
alllist.append(h_jet2phi_2b)
alllist.append(h_jet1eta_2b)
alllist.append(h_jet2eta_2b)
#alllist.append(h_MET_2b)
alllist.append(h_METphi_2b)
#alllist.append(h_RecoilPhi_2b)
#print "1", alllist, len(alllist)
if not isMET:
openfcomb = TFile(path_before + "combined_data_SE.root")
openfcomb_aftr = TFile(path_after + "combined_data_SE.root")
openfAB = TFile(path_before + "combined_data_SE_AB.root")
openfAB_aftr = TFile(path_after + "combined_data_SE_AB.root")
openfCD_bfr = TFile(path_before + "combined_data_SE_CD.root")
openfCD = TFile(path_after + "combined_data_SE_CD.root")
h_jet1phi_1b = []
jet1phi_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_comb_top1b)
jet1phi_comb_aftr_top1b = openfcomb_aftr.Get(
"h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_comb_aftr_top1b)
jet1phi_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_AB_top1b)
jet1phi_AB_aftr_top1b = openfAB_aftr.Get("h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_AB_aftr_top1b)
jet1phi_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_CD_bfr_top1b)
jet1phi_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_Jet1Phi")
h_jet1phi_1b.append(jet1phi_CD_top1b)
h_jet1eta_1b = []
jet1eta_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_comb_top1b)
jet1eta_comb_aftr_top1b = openfcomb_aftr.Get(
"h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_comb_aftr_top1b)
jet1eta_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_AB_top1b)
jet1eta_AB_aftr_top1b = openfAB_aftr.Get("h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_AB_aftr_top1b)
jet1eta_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_CD_bfr_top1b)
jet1eta_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_Jet1Eta")
h_jet1eta_1b.append(jet1eta_CD_top1b)
h_MET_1b = []
MET_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_comb_top1b)
MET_comb_aftr_top1b = openfcomb_aftr.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_comb_aftr_top1b)
MET_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_AB_top1b)
MET_AB_aftr_top1b = openfAB_aftr.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_AB_aftr_top1b)
MET_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_CD_bfr_top1b)
MET_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_MET")
h_MET_1b.append(MET_CD_top1b)
h_METphi_1b = []
METphi_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_comb_top1b)
METphi_comb_aftr_top1b = openfcomb_aftr.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_comb_aftr_top1b)
METphi_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_AB_top1b)
METphi_AB_aftr_top1b = openfAB_aftr.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_AB_aftr_top1b)
METphi_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_CD_bfr_top1b)
METphi_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_METPhi")
h_METphi_1b.append(METphi_CD_top1b)
h_Recoil_1b = []
Recoil_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_comb_top1b)
Recoil_comb_aftr_top1b = openfcomb_aftr.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_comb_aftr_top1b)
Recoil_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_AB_top1b)
Recoil_AB_aftr_top1b = openfAB_aftr.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_AB_aftr_top1b)
Recoil_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_CD_bfr_top1b)
Recoil_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_Recoil")
h_Recoil_1b.append(Recoil_CD_top1b)
h_RecoilPhi_1b = []
RecoilPhi_comb_top1b = openfcomb.Get("h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_comb_top1b)
RecoilPhi_comb_aftr_top1b = openfcomb_aftr.Get(
"h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_comb_aftr_top1b)
RecoilPhi_AB_top1b = openfAB.Get("h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_AB_top1b)
RecoilPhi_AB_aftr_top1b = openfAB_aftr.Get(
"h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_AB_aftr_top1b)
RecoilPhi_CD_bfr_top1b = openfCD_bfr.Get("h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_CD_bfr_top1b)
RecoilPhi_CD_top1b = openfCD.Get("h_reg_TopenuCR_1b_RecoilPhi")
h_RecoilPhi_1b.append(RecoilPhi_CD_top1b)
h_jet1phi_2b = []
jet1phi_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_comb_top2b)
jet1phi_comb_aftr_top2b = openfcomb_aftr.Get(
"h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_comb_aftr_top2b)
jet1phi_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_AB_top2b)
jet1phi_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_AB_aftr_top2b)
jet1phi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_CD_bfr_top2b)
jet1phi_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_Jet1Phi")
h_jet1phi_2b.append(jet1phi_CD_top2b)
h_jet2phi_2b = []
jet2phi_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_comb_top2b)
jet2phi_comb_aftr_top2b = openfcomb_aftr.Get(
"h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_comb_aftr_top2b)
jet2phi_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_AB_top2b)
jet2phi_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_AB_aftr_top2b)
jet2phi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_CD_bfr_top2b)
jet2phi_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_Jet2Phi")
h_jet2phi_2b.append(jet2phi_CD_top2b)
h_jet1eta_2b = []
jet1eta_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_comb_top2b)
jet1eta_comb_aftr_top2b = openfcomb_aftr.Get(
"h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_comb_aftr_top2b)
jet1eta_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_AB_top2b)
jet1eta_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_AB_aftr_top2b)
jet1eta_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_CD_bfr_top2b)
jet1eta_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_Jet1Eta")
h_jet1eta_2b.append(jet1eta_CD_top2b)
h_jet2eta_2b = []
jet2eta_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_comb_top2b)
jet2eta_comb_aftr_top2b = openfcomb_aftr.Get(
"h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_comb_aftr_top2b)
jet2eta_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_AB_top2b)
jet2eta_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_AB_aftr_top2b)
jet2eta_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_CD_bfr_top2b)
jet2eta_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_Jet2Eta")
h_jet2eta_2b.append(jet2eta_CD_top2b)
h_MET_2b = []
MET_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_comb_top2b)
MET_comb_aftr_top2b = openfcomb_aftr.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_comb_aftr_top2b)
MET_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_AB_top2b)
MET_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_AB_aftr_top2b)
MET_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_CD_bfr_top2b)
MET_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_MET")
h_MET_2b.append(MET_CD_top2b)
h_METphi_2b = []
METphi_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_comb_top2b)
METphi_comb_aftr_top2b = openfcomb_aftr.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_comb_aftr_top2b)
METphi_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_AB_top2b)
METphi_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_AB_aftr_top2b)
METphi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_CD_bfr_top2b)
METphi_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_METPhi")
h_METphi_2b.append(METphi_CD_top2b)
h_Recoil_2b = []
Recoil_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_comb_top2b)
Recoil_comb_aftr_top2b = openfcomb_aftr.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_comb_aftr_top2b)
Recoil_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_AB_top2b)
Recoil_AB_aftr_top2b = openfAB_aftr.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_AB_aftr_top2b)
Recoil_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_CD_bfr_top2b)
Recoil_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_Recoil")
h_Recoil_2b.append(Recoil_CD_top2b)
h_RecoilPhi_2b = []
RecoilPhi_comb_top2b = openfcomb.Get("h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_comb_top2b)
RecoilPhi_comb_aftr_top2b = openfcomb_aftr.Get(
"h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_comb_aftr_top2b)
RecoilPhi_AB_top2b = openfAB.Get("h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_AB_top2b)
RecoilPhi_AB_aftr_top2b = openfAB_aftr.Get(
"h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_AB_aftr_top2b)
RecoilPhi_CD_bfr_top2b = openfCD_bfr.Get("h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_CD_bfr_top2b)
RecoilPhi_CD_top2b = openfCD.Get("h_reg_TopenuCR_2b_RecoilPhi")
h_RecoilPhi_2b.append(RecoilPhi_CD_top2b)
alllist = []
alllist.append(h_jet1phi_1b)
alllist.append(h_jet1eta_1b)
alllist.append(h_MET_1b)
alllist.append(h_METphi_1b)
alllist.append(h_Recoil_1b)
alllist.append(h_RecoilPhi_1b)
alllist.append(h_jet1phi_2b)
alllist.append(h_jet2phi_2b)
alllist.append(h_jet1eta_2b)
alllist.append(h_jet2eta_2b)
alllist.append(h_MET_2b)
alllist.append(h_METphi_2b)
alllist.append(h_Recoil_2b)
alllist.append(h_RecoilPhi_2b)
#print "2", alllist, len(alllist)
effectMET_ABCD_1b = effect(h_Pre=MET_comb_top1b,
h_Post=MET_comb_aftr_top1b)
print "HEM effect on MET of Topenu 1b ABCD:", effectMET_ABCD_1b, "%"
print " "
effectMET_AB_1b = effect(h_Pre=MET_AB_top1b, h_Post=MET_AB_aftr_top1b)
print "HEM effect on MET of Topenu 1b AB:", effectMET_AB_1b, "%"
print " "
effectMET_CD_1b = effect(h_Pre=MET_CD_bfr_top1b, h_Post=MET_CD_top1b)
print "HEM effect on MET of Topenu 1b CD:", effectMET_CD_1b, "%"
print " "
c = PlotTemplates.myCanvas()
gPad.GetUymax()
gPad.SetLogy()
gStyle.SetOptStat(0)
gStyle.SetOptTitle(0)
leg = PlotTemplates.SetLegend(coordinate_=[.37, .76, .78, .9], ncol=2)
leg.SetTextSize(0.017)
xAxisName = [
"Jet1 #phi", "Jet1 #eta", "MET (GeV)", "MET #phi", "Recoil (GeV)",
"Recoil #phi", "Jet1 #phi", "Jet2 #phi", "Jet1 #eta", "Jet2 #eta",
"MET (GeV)", "MET #phi", "Recoil (GeV)", "Recoil #phi"
]
color = [1, 2, 4, 3, 6, 28]
color_bfr = [1, 4, 6]
legendName = [
"2018 ABCD (Before HEM Veto)", "2018 ABCD (After HEM Veto)",
"2018 AB (Before HEM Veto)", "2018 AB (After HEM Veto)",
"2018 CD (Before HEM Veto)", "2018 CD (After HEM Veto)"
]
legendName_bfr = ["2018 ABCD", "2018 AB", "2018 CD"]
for i in range(len(alllist)):
leg.Clear()
if (i == 2) or (i == 4) or (i == 10) or (i == 12):
h = alllist[i]
for j in range(len(h)):
h[j].SetLineWidth(3)
#h[j].SetMarkerStyle(20)
#h[j].SetMarkerSize(0.5)
h[j].SetLineColor(color[j])
#h[j].SetMarkerColor(color[j])
h[j].GetXaxis().SetTitle(xAxisName[i])
h[j].GetYaxis().SetTitle("Events/Bin")
leg.AddEntry(h[j], legendName[j])
#h[j].Draw("histsame")
#leg.Draw()
else:
h = alllist[i]
#print i, "x-axis :", h[0].GetNbinsX(), h[0].GetXaxis().GetBinLowEdge(1)
for j in range(len(h)):
h[j].Scale(1 / h[j].Integral())
h[j].SetLineWidth(3)
#h[j].SetMarkerStyle(20)
#h[j].SetMarkerSize(0.5)
h[j].SetLineColor(color[j])
#h[j].SetMarkerColor(color[j])
h[j].GetXaxis().SetTitle(xAxisName[i])
h[j].GetYaxis().SetTitle("Events/Bin")
leg.AddEntry(h[j], legendName[j])
#h[j].Draw("histsame")
#leg.Draw()
h[0].Draw("hist")
h[1].Draw("histsame")
h[2].Draw("histsame")
h[3].Draw("histsame")
h[4].Draw("histsame")
h[5].Draw("histsame")
leg.Draw()
energy = PlotTemplates.drawenergy(is2017=False)
for k in energy:
k.Draw()
pavetxt = [
"Top (e#nu) + 1b CR", "Top (e#nu) + 1b CR", "Top (e#nu) + 1b CR",
"Top (e#nu) + 1b CR", "Top (e#nu) + 1b CR", "Top (e#nu) + 1b CR",
"Top (e#nu) + 2b CR", "Top (e#nu) + 2b CR", "Top (e#nu) + 2b CR",
"Top (e#nu) + 2b CR", "Top (e#nu) + 2b CR", "Top (e#nu) + 2b CR",
"Top (e#nu) + 2b CR", "Top (e#nu) + 2b CR"
]
pt = TPaveText(0.2177181, 0.855, 0.4540537, 0.885, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(52)
pt.AddText(pavetxt[i])
pt.Draw()
name = [
"_1b_jet1phi", "_1b_jet1eta", "_1b_MET", "_1b_METphi",
"_1b_Recoil", "_1b_Recoilphi", "_2b_jet1phi", "_2b_jet2phi",
"_2b_jet1eta", "_2b_jet2eta", "_2b_MET", "_2b_METphi",
"_2b_Recoil", "_2b_RecoilPhi"
]
c.Update()
dt = datetime.now()
dt_str = dt.strftime("%Y%m%d_%H%M")
subdirPath = dirPath + "/" + reg + "_" + dt_str
if not (os.path.exists(subdirPath)):
os.mkdir(subdirPath)
dirPDF = subdirPath + "/pdf"
dirPNG = subdirPath + "/png"
if not (os.path.exists(dirPDF)):
os.mkdir(dirPDF)
if not (os.path.exists(dirPNG)):
os.mkdir(dirPNG)
c.SaveAs(dirPDF + "/" + reg + name[i] + "_new.pdf")
c.SaveAs(dirPNG + "/" + reg + name[i] + "_new.png")
def makePlots():
# gROOT.SetStyle('Plain') # white background
# gStyle.SetOptStat(222211)
ROOT.gROOT.ProcessLine('.L ../tdrstyle.C')
ROOT.gROOT.Reset()
ROOT.gROOT.ProcessLine('setTDRStyle()') #Set CMS TDR style
inputFile = TFile(output_name + '.root', 'READ')
histos_SR1 = dict()
histos_SR2 = dict()
histos_LSB = dict()
histos_RSB = dict()
histos_MC = dict()
keys = [
'photon_pt', 'photon_eta', 'dimuon_pt', 'dimuon_rapidity', 'chib_pt'
]
for key in keys:
histos_SR1[key] = inputFile.Get(key + '_SR1')
histos_SR2[key] = inputFile.Get(key + '_SR2')
histos_LSB[key] = inputFile.Get(key + '_LSB')
histos_RSB[key] = inputFile.Get(key + '_RSB')
histos_MC[key] = inputFile.Get(key + '_MC')
titles = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];Entries / 100 MeV',
photon_eta='photon_eta;#eta(#gamma);Entries / 0.05',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];Entries / GeV',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);Entries / 0.1',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];Entries / GeV',
)
titles_chib = dict(
photon_pt='photon E_{T};E_{T}(#gamma) [GeV];A.U.',
photon_eta='photon_eta;#eta(#gamma);A.U.',
dimuon_pt='#Upsilon p_{T};p_{T}(#Upsilon) [GeV];A.U.',
dimuon_rapidity='#Upsilon rapidity(#Upsilon);y(#Upsilon);A.U.',
chib_pt='#chi_{b} p_{T};p_{T}(#chi_{b}) [GeV];A.U.',
)
logY = dict(
photon_pt=0,
photon_eta=0,
dimuon_pt=0,
dimuon_rapidity=0,
chib_pt=0,
)
maxY = dict(
photon_pt=750,
photon_eta=350,
dimuon_pt=800,
dimuon_rapidity=400,
chib_pt=800,
)
integralData1 = histos_SR1[keys[0]].Integral()
integralData2 = histos_SR2[keys[0]].Integral()
integralData = integralData1 + integralData2
for histo in histos_LSB.values() + histos_RSB.values() + histos_MC.values(
):
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
histo.Rebin(3)
for histo in histos_SR1.values() + histos_SR2.values():
histo.Rebin(3)
fBG = 0.48 #0.28
fLSB = 0.5
histos_BG = dict()
for key in keys:
histos_BG[key] = histos_RSB[key].Clone()
histos_BG[key].SetNameTitle(key + '_BG', 'bgd from side-bands')
histos_BG[key].Scale(1 - fLSB)
histos_BG[key].Add(histos_LSB[key], fLSB)
histos_Signal1 = dict()
histos_Signal2 = dict()
histos_Signal = dict()
histos_SR = dict()
for key in keys:
histos_Signal1[key] = histos_SR1[key].Clone()
histos_Signal1[key].SetNameTitle(key + '_signal1', 'Signal1')
histos_Signal1[key].Add(histos_BG[key], -1 * integralData1 * fBG)
histos_Signal2[key] = histos_SR2[key].Clone()
histos_Signal2[key].SetNameTitle(key + '_signal2', 'Signal2')
histos_Signal2[key].Add(histos_BG[key], -1 * integralData2 * fBG)
histos_Signal[key] = histos_Signal1[key].Clone()
histos_Signal[key].Add(histos_Signal2[key])
histos_Signal[key].SetNameTitle(key + '_signal', 'data bkg-subtracted')
histos_SR[key] = histos_SR1[key].Clone()
histos_SR[key].Add(histos_SR2[key])
histos_SR[key].SetNameTitle(key + '_SR', 'data')
for histo in histos_Signal.values() + histos_BG.values():
if (histo.Integral() != 0):
histo.Scale(1. / histo.Integral())
# Normalize SR to their original value, MC to be comparable with signal background-subtracted and background such that Signal+background = SR
for histo in histos_MC.values():
histo.Scale(integralData * (1 - fBG))
for histo in histos_BG.values():
histo.Scale(integralData * fBG)
for histo in histos_LSB.values():
histo.Scale(integralData * fBG * fLSB)
for histo in histos_RSB.values():
histo.Scale(integralData * fBG * (1 - fLSB))
chi2Prob = dict()
kolmogorovProb = dict()
h_ratio = dict()
for key in histos_Signal.keys():
h_ratio[key] = histos_SR[key].Clone()
histo_sum_MC_BG = histos_MC[key].Clone()
histo_sum_MC_BG.Add(histos_BG[key])
h_ratio[key].Divide(histo_sum_MC_BG)
h_ratio[key].SetNameTitle(key + '_ratio', titles[key])
h_ratio[key].SetMarkerStyle(20)
h_ratio[key].SetMarkerSize(1)
h_ratio[key].GetYaxis().SetLabelSize(0.18)
h_ratio[key].GetYaxis().SetTitle('DATA/MC')
h_ratio[key].GetYaxis().SetTitleSize(0.22)
h_ratio[key].GetYaxis().SetTitleOffset(0.2)
h_ratio[key].GetYaxis().SetNdivisions(005)
h_ratio[key].GetXaxis().SetLabelSize(0.16)
h_ratio[key].GetXaxis().SetTitleSize(0.16)
h_ratio[key].SetMaximum(1.5)
h_ratio[key].SetMinimum(0.667)
chi2Prob[key] = histos_SR[key].Chi2Test(
histo_sum_MC_BG) #, 'UW')#, 'NORM')
kolmogorovProb[key] = histos_SR[key].KolmogorovTest(histo_sum_MC_BG)
for histo in histos_SR.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlack)
histo.SetMarkerStyle(20)
for histo in histos_SR1.values() + histos_Signal1.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kBlue)
histo.SetMarkerStyle(22)
for histo in histos_SR2.values() + histos_Signal2.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetMarkerColor(ROOT.kRed)
histo.SetMarkerStyle(23)
for histo in histos_Signal.values():
histo.SetLineColor(ROOT.kBlack)
histo.SetLineWidth(2)
# histo.SetMarkerColor(ROOT.kBlack)
# histo.SetMarkerStyle(21)
for histo in histos_BG.values():
histo.SetLineColor(ROOT.kRed)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kRed)
# histo.SetMarkerColor(ROOT.kRed)
# histo.SetMarkerStyle(22)
# for histo in histos_RSB.values():
# histo.SetLineColor(ROOT.kViolet)
# histo.SetLineWidth(2)
for histo in histos_MC.values():
histo.SetLineColor(ROOT.kBlue)
histo.SetLineWidth(2)
histo.SetFillColor(ROOT.kBlue)
# histo.SetMarkerColor(ROOT.kBlue)
# histo.SetMarkerStyle(20)
outputFile = TFile(output_name + '_plots.root', 'RECREATE')
for histo in histos_Signal.values() + histos_MC.values(
) + histos_BG.values() + histos_SR.values():
histo.Write()
outputFile.Close()
canvas = TCanvas("canvas", "canvas")
canvas.Print(outputFile_name + "[") #apre file .ps
for key in keys:
pad1 = TPad("pad1", "The pad 80% of the height", 0.0, 0.2, 1.0, 1.0)
pad1.cd()
pad1.SetLogy(logY[key])
hs = THStack('hs', titles[key])
#hs.Add(histos_SR[key])
#hs.Add(histos_Signal[key])
hs.Add(histos_BG[key])
hs.Add(histos_MC[key])
#hs.Add(histos_LSB[key])
#hs.Add(histos_RSB[key])
#maxHisto = max(hs.GetMaximum(), histos_SR[key].GetMaximum())
hs.SetMaximum(maxY[key]) #maxHisto)
hs.Draw('HIST')
histos_SR[key].Draw('same')
leg = pad1.BuildLegend(.65, .93, .95, .7)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.Draw("SAME")
pad2 = TPad("pad2", "The pad 20% of the height", 0.0, 0.01, 1.0, 0.2)
pad2.cd()
h_ratio[key].Draw()
xmin = h_ratio[key].GetBinLowEdge(1)
xmax = h_ratio[key].GetBinLowEdge(
h_ratio[key].GetNbinsX()) + h_ratio[key].GetBinWidth(
h_ratio[key].GetNbinsX())
line0 = TLine(xmin, 1, xmax, 1)
line0.SetLineColor(ROOT.kBlue)
line0.SetLineWidth(2)
line0.Draw('same')
canvas.cd()
pad1.Draw()
pad2.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '.root')
# Make comparisison between chib1 and chib2
histos_SR1[key].Scale(1. / histos_SR1[key].Integral())
histos_SR2[key].Scale(1. / histos_SR2[key].Integral())
histos_Signal1[key].Scale(1. / histos_Signal1[key].Integral())
histos_Signal2[key].Scale(1. / histos_Signal2[key].Integral())
# histos_SR1[key].Rebin(3)
# histos_SR2[key].Rebin(3)
# histos_Signal1[key].Rebin(3)
# histos_Signal2[key].Rebin(3)
hsc = THStack('hsc', titles_chib[key])
hsc.Add(histos_Signal1[key])
hsc.Add(histos_Signal2[key])
#hsc.SetMaximum(maxY[key])
hsc.Draw('nostack')
legc = canvas.BuildLegend(.65, .93, .95, .7)
legc.SetFillStyle(0)
legc.SetBorderSize(0)
legc.Draw("SAME")
print 'kolmogorov prob SR ' + key + ' ' + str(
histos_SR1[key].KolmogorovTest(histos_SR2[key]))
print 'kolmogorov prob Signal ' + key + ' ' + str(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]))
cfr = 2 if key not in ['dimuon_pt', 'chib_pt'] else 5
kolmogorovProb_chi = round(
histos_Signal1[key].KolmogorovTest(histos_Signal2[key]), cfr)
pvtxt = TPaveText(.2, .0, 0.5, 0.1, "NDC")
pvtxt.SetFillStyle(0)
pvtxt.SetBorderSize(0)
pvtxt.SetTextSize(0.04)
pvtxt.AddText('Kolmogorov prob = ' + str(kolmogorovProb_chi))
pvtxt.Draw()
canvas.Update()
canvas.Print(outputFile_name)
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.png')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.pdf')
canvas.Print('plots/' + key + '_' + mc_ptSpectrum + '_comparison' +
'.root')
canvas.Clear()
canvas.Print(outputFile_name + "]") #chiude file .ps
for key in keys:
print '\n'
print key + ' Kolmogorov probability: ' + str(chi2Prob[key])
print key + ' chiSqure probability: ' + str(kolmogorovProb[key])
#print 'Kolmogorov probability with sidebands: '+str(histos_MC['dimuon_pt'].KolmogorovTest(histos_LSB['dimuon_pt'])) #
inputFile.Close()
ccos = cos(2 * pi / numberOfPoints * i) + 1
esin = sin(2 * pi / (numberOfCircles * d) * j) + 1
x = j * (csin + esin)
y = j * ccos
z = j
pm3d.SetPoint(i, x, y, z)
# set marker size, color & style
pm3d.SetMarkerSize(1)
pm3d.SetMarkerColor(2 + (d == (j & d)))
pm3d.SetMarkerStyle(3)
# draw
pm3d.Draw()
# save a reference
polymarkers.append(pm3d)
gBenchmark.Show('tornado')
ct = gBenchmark.GetCpuTime('tornado')
timeStr = 'Execution time: %g sec.' % ct
text = TPaveText(0.1, 0.81, 0.9, 0.97)
text.SetFillColor(42)
text.AddText('PyROOT example: tornado.py')
text.AddText(timeStr)
text.Draw()
sky.Update()
]
hist = TH1D(hisName, "", 50, 5.5, 5.7)
plbl0.Draw('lbtkMass>>' + hisName, '&&'.join(myCutLists))
print 'hiiii --- {0}'.format(hist.GetEntries())
print 'hiiii --- ' + '&&'.join(myCutLists)
hist.SetStats(False)
hist.SetTitle(
"#Lambda^{0}_{b}#rightarrow J/#psi p K under cut")
hist.GetXaxis().SetTitle('#Lambda^{0}_{b} Mass (GeV)')
hist.GetYaxis().SetTitle('event/4MeV')
hist.SetMaximum(hist.GetMaximum() * 1.5)
hist.SetMinimum(0.)
hist.Draw()
hist.Write()
text = TPaveText(0.41, 0.70, 0.85, 0.85, 'NDC')
text.AddText('Total Entries {0}'.format(hist.GetEntries()))
text.SetFillStyle(4000)
text.SetFillColor(4000)
text.Draw('same')
canv.Modified()
canv.SaveAs('{}/h_{}.eps'.format(figFolder, hisName))
canv.SaveAs(pdfFile)
canv.SaveAs(pdfFile + ']')
mySavingROOTFilt.Close()
rootFile.Close()
def main():
if True:
mf=TGMainFrame(gClient.GetRoot(),1500,475)
gvf=TGVerticalFrame(mf,1500,475)
rec=TRootEmbeddedCanvas("ccc",gvf,1500,450)
rec2=TRootEmbeddedCanvas("ccc2",gvf,1500,25)
gvf.AddFrame(rec,TGLayoutHints(ROOT.kLHintsExpandX|ROOT.kLHintsTop))
gvf.AddFrame(rec2,TGLayoutHints(ROOT.kLHintsExpandX|ROOT.kLHintsBottom))
mf.AddFrame(gvf,TGLayoutHints(ROOT.kLHintsExpandX))
cc=rec.GetCanvas()
cc2=rec2.GetCanvas()
mf.SetEditable(0)
mf.SetWindowName('HPS ECAL FADC SCALERS')
mf.MapSubwindows()
mf.Resize(1501,476)# resize to get proper frame placement
mf.MapWindow()
else:
cc=TCanvas('cc','',1500,450)
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(11)
hh=TH2D('hh',';X;Y',46,-22,24,11,-5,6)
hi=TH2I('hi',';X;Y',46,-22,24,11,-5,6)
setupHists([hh,hi])
xax,yax=hh.GetXaxis(),hh.GetYaxis()
hh.Draw('COLZ')
hi.Draw('TEXTSAME')
gPad.SetLogz()
gPad.SetGrid(1,1)
gPad.SetLeftMargin(0.05)
tt1=TPaveText(0.1,0.9,0.3,1.0,'NDC')
tt2=TPaveText(0.7,0.91,0.9,0.99,'NDC')
ttT=TPaveText(-22+13+0.05,6-5,-22+22,7-5-0.05)
ttB=TPaveText(-22+13+0.05,4-5+0.05,-22+22,5-5)
ttM=TPaveText(-22+0+0.05,5-5+0.05,-22+13,6-5.01)
ttime=TPaveText(-10,-6.5,10,-5.8)
tchan=TPaveText(0,0,0.9,1)
setupPaveTexts([tt1,tt2,ttT,ttB,ttM,ttime,tchan])
ttM.SetTextColor(2)
bb=TBox()
bb.SetFillStyle(1001)
bb.SetFillColor(0)
bb.SetLineWidth(1)
bb.SetLineColor(1)
bb.DrawBox(-9+0.05,-1,0,1.97)
bb.DrawBox(-24,0,24.05,0.97)
tarrow=TText(14.5,0.3,'Beam Left')
arrow=TArrow(19,0.5,23,0.5,0.02,'|>')
arrow.SetAngle(40)
arrow.SetFillColor(1)
arrow.SetLineWidth(2)
tt=TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.08)
tt.DrawText(25.4,0,'kHz')
tt.SetTextAngle(0)
tt.SetTextColor(2)
tt.DrawTextNDC(0.3,0.92,'ECAL FADC SCALERS')
cc.cd()
for xx in [tt2,ttT,ttB,ttM,arrow,tarrow,ttime]: xx.Draw()
cc2.cd()
tchan.Draw('NDC')
cc.cd()
ll=TLine()
ll.DrawLine(xax.GetXmin(),yax.GetXmin(),xax.GetXmax(),yax.GetXmin())
ll.DrawLine(xax.GetXmin(),yax.GetXmax(),xax.GetXmax(),yax.GetXmax())
ll.DrawLine(xax.GetXmin(),yax.GetXmin(),xax.GetXmin(),0)
ll.DrawLine(xax.GetXmax(),yax.GetXmin(),xax.GetXmax(),0)
ll.DrawLine(xax.GetXmin(),yax.GetXmax(),xax.GetXmin(),1)
ll.DrawLine(xax.GetXmax(),yax.GetXmax(),xax.GetXmax(),1)
ll.DrawLine(xax.GetXmax(),0,0,0)
ll.DrawLine(xax.GetXmax(),1,0,1)
ll.DrawLine(xax.GetXmin(),0,-9,0)
ll.DrawLine(xax.GetXmin(),1,-9,1)
ll.DrawLine(-9,-1,0,-1)
ll.DrawLine(-9,2,0,2)
ll.DrawLine(-9,1,-9,2)
ll.DrawLine(-9,-1,-9,0)
ll.DrawLine(0,-1,0,0)
ll.DrawLine(0,1,0,2)
gPad.SetEditable(0)
while True:
# try:
zvals=getPVS()
for ii in range(len(zvals)):
hh.SetBinContent(xax.FindBin(XVALS[ii]),yax.FindBin(YVALS[ii]),zvals[ii])
hi.SetBinContent(xax.FindBin(XVALS[ii]),yax.FindBin(YVALS[ii]),zvals[ii])
for xx in [ttime,tt2,ttT,ttB,ttM]: xx.Clear()
[top,bottom,maximum]=calcRates(zvals)
tt2.AddText('Total: %.1f MHz'%((top+bottom)/1000))
ttT.AddText('%.1f MHz'%(top/1000))
ttB.AddText('%.1f MHz'%(bottom/1000))
ttM.AddText('MAX SINGLE CRYSTAL = %.0f kHz'%(maximum))
ttime.AddText(makeTime())
if gPad.GetEvent()==11:
xy=pix2xy(gPad)
ee=ECAL.findChannelXY(xy[0],xy[1])
if ee:
tchan.Clear()
tchan.AddText(printChannel(ee))
cc2.Modified()
cc2.Update()
elif gPad.GetEvent()==12:
tchan.Clear()
cc2.Modified()
cc2.Update()
cc.Modified()
cc.Update()
time.sleep(1)
## \author Wim Lavrijsen
from ROOT import TCanvas, TPaveLabel, TPaveText, TText, TArrow, TLine
from ROOT import gROOT
c1 = TCanvas('c1', 'ROOT FilDir description', 700, 900)
c1.Range(1, 1, 19, 24.5)
title = TPaveLabel(4, 23, 16, 24.2, 'ROOT File/Directory/Key description')
title.SetFillColor(16)
title.Draw()
keycolor = 42
dircolor = 21
objcolor = 46
file = TPaveText(2, 19, 6, 22)
file.SetFillColor(39)
file.Draw()
file.SetTextSize(0.04)
file.AddText('TFile')
file.AddText('Header')
arrow = TArrow(6, 20.5, 17, 20.5, 0.02, '|>')
arrow.SetFillStyle(1001)
arrow.SetLineWidth(2)
arrow.Draw()
free = TPaveText(8, 20, 11, 21)
free.SetFillColor(18)
free.Draw()
free.AddText('First:Last')
free2 = TPaveText(12, 20, 15, 21)
free2.SetFillColor(18)
def compareDatasets(trigger, leg, datasets, lineColors, legendLabels, axisTitle, canvas, dataLumi, metHLTFilters, outputSuffix = None):
inputFiles = [TFile.Open("triggerEfficiency_" + x + ".root") for x in datasets]
efficiencies = [x.Get(trigger + "_" + leg) for x in inputFiles]
for iEff in range(len(efficiencies)):
SetStyle(efficiencies[iEff])
efficiencies[iEff].SetLineColor(lineColors[iEff])
efficiencies[iEff].SetMarkerColor(lineColors[iEff])
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
backgroundHist.GetXaxis().SetTitle(axisTitle)
SetStyle(backgroundHist)
canvas.cd()
backgroundHist.Draw()
for eff in efficiencies:
eff.Draw("CP same")
#oneLine.Draw("same")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
if dataLumi > 0:
pt_cmsPrelim.AddText("CMS Preliminary")
else:
pt_cmsPrelim.AddText("CMS Simulation")
pt_cmsPrelim.Draw("same")
if dataLumi > 0:
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText("{:.2f}".format(dataLumi / 1000.0) + " fb^{-1}, 13 TeV")
pt_lumi.Draw("same")
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.025)
pt_leg.SetTextAlign(12)
if leg == "METLeg":
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1]
pt_leg.AddText(legLabel)
if leg == "TrackLeg":
pt_leg.AddText(trigger + "*")
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if leg == "METPath":
if trigger == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
if len(trigger) > 25 and len(trigger.split("_")) > 2:
firstLine = trigger.split("_")[0] + "_" + trigger.split("_")[1] + "_"
pt_leg.AddText(firstLine)
secondLine = ""
for line in trigger.split("_")[2:-1]:
secondLine += line + "_"
secondLine += trigger.split("_")[-1] + "*"
pt_leg.AddText(secondLine)
else:
pt_leg.AddText(trigger + "*")
pt_leg.Draw("same")
legendLabel = trigger
legend = TLegend(0.65, 0.75, 0.93, 0.88)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
if leg == 'METLeg':
legend.SetHeader('MET Leg')
elif leg == 'TrackLeg':
legend.SetHeader('Track Leg')
for iEff in range(len(efficiencies)):
legend.AddEntry(efficiencies[iEff], legendLabels[iEff], 'P')
legend.Draw("same")
if outputSuffix is not None:
canvas.SaveAs('compareDatasets_' + trigger + '_' + leg + '_' + outputSuffix + '.pdf')
else:
canvas.SaveAs('compareDatasets_' + trigger + '_' + leg + '_.pdf')
for inputFile in inputFiles:
inputFile.Close()
return
def make_template_plots(histograms, category, channel):
global variable, translate_options, b_tag_bin, save_path
ROOT.TH1.SetDefaultSumw2(False)
ROOT.gROOT.SetBatch(True)
ROOT.gROOT.ProcessLine('gErrorIgnoreLevel = 1001;')
plotting.setStyle()
gStyle.SetTitleYOffset(1.4)
ROOT.gROOT.ForceStyle()
for variable_bin in variable_bins_ROOT[variable]:
path = save_path + '/' + variable + '/' + category + '/fit_templates/'
make_folder_if_not_exists(path)
plotname = path + channel + '_templates_bin_' + variable_bin + '.png'
# check if template plots exist already
if os.path.isfile(plotname):
continue
canvas = Canvas(width=700, height=500)
canvas.SetLeftMargin(0.15)
canvas.SetBottomMargin(0.15)
canvas.SetTopMargin(0.05)
canvas.SetRightMargin(0.05)
legend = plotting.create_legend(x0=0.7, y1=0.8)
h_signal = histograms[variable_bin]['signal']
h_VJets = histograms[variable_bin]['V+Jets']
h_QCD = histograms[variable_bin]['QCD']
h_signal.GetXaxis().SetTitle('Lepton #eta')
h_signal.GetYaxis().SetTitle('Normalised Events')
h_signal.GetXaxis().SetTitleSize(0.05)
h_signal.GetYaxis().SetTitleSize(0.05)
h_signal.SetMinimum(0)
h_signal.SetMaximum(0.2)
h_signal.SetLineWidth(2)
h_VJets.SetLineWidth(2)
h_QCD.SetLineWidth(2)
h_signal.SetLineColor(kRed + 1)
h_VJets.SetLineColor(kBlue)
h_QCD.SetLineColor(kYellow)
h_signal.Draw('hist')
h_VJets.Draw('hist same')
h_QCD.Draw('hist same')
legend.AddEntry(h_signal, 'signal', 'l')
legend.AddEntry(h_VJets, 'V+Jets', 'l')
legend.AddEntry(h_QCD, 'QCD', 'l')
legend.Draw()
mytext = TPaveText(0.5, 0.97, 1, 1.01, "NDC")
channelLabel = TPaveText(0.18, 0.97, 0.5, 1.01, "NDC")
if channel == 'electron':
channelLabel.AddText("e, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
elif channel == 'muon':
channelLabel.AddText("#mu, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
else:
channelLabel.AddText("combined, %s, %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin]))
mytext.AddText(
"CMS Preliminary, L = %.1f fb^{-1} at #sqrt{s} = 8 TeV" % (5.8))
mytext.SetFillStyle(0)
mytext.SetBorderSize(0)
mytext.SetTextFont(42)
mytext.SetTextAlign(13)
channelLabel.SetFillStyle(0)
channelLabel.SetBorderSize(0)
channelLabel.SetTextFont(42)
channelLabel.SetTextAlign(13)
mytext.Draw()
channelLabel.Draw()
canvas.Modified()
canvas.Update()
canvas.SaveAs(plotname)
canvas.SaveAs(plotname.replace('png', 'pdf'))
def compare(trigger, leg, data, mc, axisTitle, canvas, dataLumi, metHLTFilters):
dataFile = TFile.Open("triggerEfficiency_" + data + ".root", "read")
mcFile = TFile.Open("triggerEfficiency_" + mc + ".root", "read")
dataEff = dataFile.Get(trigger + "_" + leg)
mcEff = mcFile.Get(trigger + "_" + leg)
SetStyle(dataEff)
SetStyle(mcEff)
mcEff.SetLineColor(600)
mcEff.SetMarkerColor(600)
oneLine = TLine(xlo, 1.0, xhi, 1.0)
oneLine.SetLineWidth(3)
oneLine.SetLineStyle(2)
backgroundHist = TH1D("backgroundHist", "backgroundHist", 1, xlo, xhi)
backgroundHist.GetYaxis().SetTitle("Trigger Efficiency")
backgroundHist.GetYaxis().SetRangeUser(ylo, yhi)
backgroundHist.GetXaxis().SetTitle(axisTitle)
SetStyle(backgroundHist)
canvas.cd()
backgroundHist.Draw()
dataEff.Draw("CP same")
mcEff.Draw("CP same")
#oneLine.Draw("same")
pt_cmsPrelim = TPaveText(0.132832, 0.859453, 0.486216, 0.906716, "brNDC")
pt_cmsPrelim.SetBorderSize(0)
pt_cmsPrelim.SetFillStyle(0)
pt_cmsPrelim.SetTextFont(62)
pt_cmsPrelim.SetTextSize(0.0374065)
pt_cmsPrelim.AddText("CMS Preliminary")
pt_cmsPrelim.Draw("same")
pt_lumi = TPaveText(0.744361, 0.92928, 0.860902, 0.977667, "brNDC")
pt_lumi.SetBorderSize(0)
pt_lumi.SetFillStyle(0)
pt_lumi.SetTextFont(42)
pt_lumi.SetTextSize(0.0374065)
pt_lumi.AddText("{:.2f}".format(dataLumi / 1000.0) + " fb^{-1}, 13 TeV")
pt_lumi.Draw("same")
pt_leg = TPaveText(0.160401, 0.768657, 0.342105, 0.863184, "brNDC")
pt_leg.SetBorderSize(0)
pt_leg.SetFillStyle(0)
pt_leg.SetTextFont(42)
pt_leg.SetTextSize(0.025)
pt_leg.SetTextAlign(12)
if leg == "METLeg":
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1]
pt_leg.AddText(legLabel)
if leg == "TrackLeg":
pt_leg.AddText(trigger + "*")
legLabel = ""
for filt in metHLTFilters[:-1]:
legLabel = legLabel + filt + ", "
legLabel = legLabel + metHLTFilters[-1] + " applied"
pt_leg.AddText(legLabel)
if leg == "METPath":
if trigger == "GrandOr":
pt_leg.AddText("OR of Signal Paths")
else:
if len(trigger) > 25 and len(trigger.split("_")) > 2:
firstLine = trigger.split("_")[0] + "_" + trigger.split("_")[1] + "_"
pt_leg.AddText(firstLine)
secondLine = ""
for line in trigger.split("_")[2:-1]:
secondLine += line + "_"
secondLine += trigger.split("_")[-1] + "*"
pt_leg.AddText(secondLine)
else:
pt_leg.AddText(trigger + "*")
pt_leg.Draw("same")
dataLabel = '2015 data'
if '2016BC' in data:
dataLabel = '2016 B+C data'
if '2016DEFGH' in data:
dataLabel = '2016 D-H data'
if '2017' in data:
dataLabel = '2017 data'
if '2018' in data:
dataLabel = '2018 data'
legendLabel = trigger
legend = TLegend(0.65, 0.75, 0.93, 0.88)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
if leg == 'METLeg':
legend.SetHeader('MET Leg')
elif leg == 'TrackLeg':
legend.SetHeader('Track Leg')
legend.AddEntry(dataEff, dataLabel, 'P')
legend.AddEntry(mcEff, 'W #rightarrow l#nu MC', 'P')
legend.Draw("same")
outputDirectory = 'plots_compare'
if 'BC' in data:
outputDirectory = 'plots_compareBC'
if 'DEFGH' in data:
outputDirectory = 'plots_compareDEFGH'
if not os.path.exists(outputDirectory):
os.mkdir(outputDirectory)
canvas.SaveAs(outputDirectory + '/' + trigger + '_' + leg + '.pdf')
mcFile.Close()
dataFile.Close()
return
def make_plots_ROOT(histograms, category, save_path, histname, channel):
global variable, translateOptions, k_value, b_tag_bin, maximum
ROOT.TH1.SetDefaultSumw2(False)
ROOT.gROOT.SetBatch(True)
ROOT.gROOT.ProcessLine('gErrorIgnoreLevel = 1001;')
plotting.setStyle()
gStyle.SetTitleYOffset(2.)
ROOT.gROOT.ForceStyle()
canvas = Canvas(width=700, height=500)
canvas.SetLeftMargin(0.18)
canvas.SetBottomMargin(0.15)
canvas.SetTopMargin(0.05)
canvas.SetRightMargin(0.05)
legend = plotting.create_legend(x0=0.6, y1=0.5)
hist_data = histograms['unfolded']
hist_data.GetXaxis().SetTitle(translate_options[variable] + ' [GeV]')
hist_data.GetYaxis().SetTitle('#frac{1}{#sigma} #frac{d#sigma}{d' +
translate_options[variable] + '} [GeV^{-1}]')
hist_data.GetXaxis().SetTitleSize(0.05)
hist_data.GetYaxis().SetTitleSize(0.05)
hist_data.SetMinimum(0)
hist_data.SetMaximum(maximum[variable])
hist_data.SetMarkerSize(1)
hist_data.SetMarkerStyle(8)
plotAsym = TGraphAsymmErrors(hist_data)
plotStatErr = TGraphAsymmErrors(hist_data)
xsections = read_unfolded_xsections(channel)
bins = variable_bins_ROOT[variable]
assert (len(bins) == len(xsections['central']))
for bin_i in range(len(bins)):
scale = 1 # / width
centralresult = xsections['central'][bin_i]
fit_error = centralresult[1]
uncertainty = calculateTotalUncertainty(xsections, bin_i)
uncertainty_total_plus = uncertainty['Total+'][0]
uncertainty_total_minus = uncertainty['Total-'][0]
uncertainty_total_plus, uncertainty_total_minus = symmetriseErrors(
uncertainty_total_plus, uncertainty_total_minus)
error_up = sqrt(fit_error**2 + uncertainty_total_plus**2) * scale
error_down = sqrt(fit_error**2 + uncertainty_total_minus**2) * scale
plotStatErr.SetPointEYhigh(bin_i, fit_error * scale)
plotStatErr.SetPointEYlow(bin_i, fit_error * scale)
plotAsym.SetPointEYhigh(bin_i, error_up)
plotAsym.SetPointEYlow(bin_i, error_down)
gStyle.SetEndErrorSize(20)
plotAsym.SetLineWidth(2)
plotStatErr.SetLineWidth(2)
hist_data.Draw('P')
plotStatErr.Draw('same P')
plotAsym.Draw('same P Z')
legend.AddEntry(hist_data, 'unfolded', 'P')
hist_measured = histograms['measured']
hist_measured.SetMarkerSize(1)
hist_measured.SetMarkerStyle(20)
hist_measured.SetMarkerColor(2)
#hist_measured.Draw('same P')
#legend.AddEntry(hist_measured, 'measured', 'P')
for key, hist in sorted(histograms.iteritems()):
if not 'unfolded' in key and not 'measured' in key:
hist.SetLineStyle(7)
hist.SetLineWidth(2)
# setting colours
if 'POWHEG' in key or 'matchingdown' in key:
hist.SetLineColor(kBlue)
elif 'MADGRAPH' in key or 'matchingup' in key:
hist.SetLineColor(kRed + 1)
elif 'MCATNLO' in key or 'scaleup' in key:
hist.SetLineColor(kGreen - 3)
elif 'scaledown' in key:
hist.SetLineColor(kMagenta + 3)
hist.Draw('hist same')
legend.AddEntry(hist, translate_options[key], 'l')
legend.Draw()
mytext = TPaveText(0.5, 0.97, 1, 1.01, "NDC")
channelLabel = TPaveText(0.18, 0.97, 0.5, 1.01, "NDC")
if 'electron' in histname:
channelLabel.AddText(
"e, %s, %s, k = %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin], k_value))
elif 'muon' in histname:
channelLabel.AddText(
"#mu, %s, %s, k = %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin], k_value))
else:
channelLabel.AddText(
"combined, %s, %s, k = %s" %
("#geq 4 jets", b_tag_bins_latex[b_tag_bin], k_value))
mytext.AddText("CMS Preliminary, L = %.1f fb^{-1} at #sqrt{s} = 8 TeV" %
(5.8))
mytext.SetFillStyle(0)
mytext.SetBorderSize(0)
mytext.SetTextFont(42)
mytext.SetTextAlign(13)
channelLabel.SetFillStyle(0)
channelLabel.SetBorderSize(0)
channelLabel.SetTextFont(42)
channelLabel.SetTextAlign(13)
mytext.Draw()
channelLabel.Draw()
canvas.Modified()
canvas.Update()
path = save_path + '/' + variable + '/' + category
make_folder_if_not_exists(path)
canvas.SaveAs(path + '/' + histname + '_kv' + str(k_value) + '.png')
canvas.SaveAs(path + '/' + histname + '_kv' + str(k_value) + '.pdf')
def createPlots_(plot, geometry):
"""Cumulative material budget from simulation.
Internal function that will produce a cumulative profile of the
material budget inferred from the simulation starting from the
single detectors that compose the tracker. It will iterate over
all existing detectors contained in the DETECTORS
dictionary. The function will automatically skip non-existent
detectors.
"""
IBs = ["InnerServices", "Phase2PixelBarrel", "TIB", "TIDF", "TIDB"]
theDirname = "Figures"
if plot not in plots.keys():
print("Error: chosen plot name not known %s" % plot)
return
hist_X0_detectors = OrderedDict()
hist_X0_IB = None
hist_X0_elements = OrderedDict()
for subDetector, color in six.iteritems(DETECTORS):
h = get1DHisto_(subDetector, plots[plot].plotNumber, geometry)
if not h:
print('Warning: Skipping %s' % subDetector)
continue
hist_X0_detectors[subDetector] = h
# Merge together the "inner barrel detectors".
if subDetector in IBs:
hist_X0_IB = assignOrAddIfExists_(hist_X0_IB,
hist_X0_detectors[subDetector])
# category profiles
for label, [num, color, leg] in six.iteritems(hist_label_to_num):
if label is 'SUM': continue
hist_label = get1DHisto_(subDetector, num + plots[plot].plotNumber,
geometry)
hist_X0_elements[label] = assignOrAddIfExists_(
hist_X0_elements.setdefault(label, None),
hist_label,
)
hist_X0_elements[label].SetFillColor(color)
cumulative_matbdg = TH1D("CumulativeSimulMatBdg", "CumulativeSimulMatBdg",
hist_X0_IB.GetNbinsX(),
hist_X0_IB.GetXaxis().GetXmin(),
hist_X0_IB.GetXaxis().GetXmax())
cumulative_matbdg.SetDirectory(0)
# colors
for det, color in six.iteritems(DETECTORS):
setColorIfExists_(hist_X0_detectors, det, color)
# First Plot: BeamPipe + Pixel + TIB/TID + TOB + TEC + Outside
# stack
stackTitle_SubDetectors = "Tracker Material Budget;%s;%s" % (
plots[plot].abscissa, plots[plot].ordinate)
stack_X0_SubDetectors = THStack("stack_X0", stackTitle_SubDetectors)
for det, histo in six.iteritems(hist_X0_detectors):
stack_X0_SubDetectors.Add(histo)
cumulative_matbdg.Add(histo, 1)
# canvas
can_SubDetectors = TCanvas("can_SubDetectors", "can_SubDetectors", 800,
800)
can_SubDetectors.Range(0, 0, 25, 25)
can_SubDetectors.SetFillColor(kWhite)
# Draw
stack_X0_SubDetectors.SetMinimum(plots[plot].ymin)
stack_X0_SubDetectors.SetMaximum(plots[plot].ymax)
stack_X0_SubDetectors.Draw("HIST")
stack_X0_SubDetectors.GetXaxis().SetLimits(plots[plot].xmin,
plots[plot].xmax)
# Legenda
theLegend_SubDetectors = TLegend(0.180, 0.8, 0.98, 0.92)
theLegend_SubDetectors.SetNColumns(3)
theLegend_SubDetectors.SetFillColor(0)
theLegend_SubDetectors.SetFillStyle(0)
theLegend_SubDetectors.SetBorderSize(0)
for det, histo in six.iteritems(hist_X0_detectors):
theLegend_SubDetectors.AddEntry(histo, det, "f")
theLegend_SubDetectors.Draw()
# text
text_SubDetectors = TPaveText(0.180, 0.727, 0.402, 0.787, "NDC")
text_SubDetectors.SetFillColor(0)
text_SubDetectors.SetBorderSize(0)
text_SubDetectors.AddText("CMS Simulation")
text_SubDetectors.SetTextAlign(11)
text_SubDetectors.Draw()
# Store
can_SubDetectors.Update()
if not checkFile_(theDirname):
os.mkdir(theDirname)
can_SubDetectors.SaveAs("%s/Tracker_SubDetectors_%s.pdf" %
(theDirname, plot))
can_SubDetectors.SaveAs("%s/Tracker_SubDetectors_%s.root" %
(theDirname, plot))
# Second Plot: BeamPipe + SEN + ELE + CAB + COL + SUP + OTH/AIR +
# Outside stack
stackTitle_Materials = "Tracker Material Budget;%s;%s" % (
plots[plot].abscissa, plots[plot].ordinate)
stack_X0_Materials = THStack("stack_X0", stackTitle_Materials)
stack_X0_Materials.Add(hist_X0_detectors["BeamPipe"])
for label, [num, color, leg] in six.iteritems(hist_label_to_num):
if label is 'SUM':
continue
stack_X0_Materials.Add(hist_X0_elements[label])
# canvas
can_Materials = TCanvas("can_Materials", "can_Materials", 800, 800)
can_Materials.Range(0, 0, 25, 25)
can_Materials.SetFillColor(kWhite)
# Draw
stack_X0_Materials.SetMinimum(plots[plot].ymin)
stack_X0_Materials.SetMaximum(plots[plot].ymax)
stack_X0_Materials.Draw("HIST")
stack_X0_Materials.GetXaxis().SetLimits(plots[plot].xmin, plots[plot].xmax)
# Legenda
theLegend_Materials = TLegend(0.180, 0.8, 0.95, 0.92)
theLegend_Materials.SetNColumns(3)
theLegend_Materials.SetFillColor(0)
theLegend_Materials.SetBorderSize(0)
theLegend_Materials.AddEntry(hist_X0_detectors["BeamPipe"], "Beam Pipe",
"f")
for label, [num, color, leg] in six.iteritems(hist_label_to_num):
if label is 'SUM':
continue
theLegend_Materials.AddEntry(hist_X0_elements[label], leg, "f")
theLegend_Materials.Draw()
# text
text_Materials = TPaveText(0.180, 0.727, 0.402, 0.787, "NDC")
text_Materials.SetFillColor(0)
text_Materials.SetBorderSize(0)
text_Materials.AddText("CMS Simulation")
text_Materials.SetTextAlign(11)
text_Materials.Draw()
# Store
can_Materials.Update()
can_Materials.SaveAs("%s/Tracker_Materials_%s.pdf" % (theDirname, plot))
can_Materials.SaveAs("%s/Tracker_Materials_%s.root" % (theDirname, plot))
return cumulative_matbdg
