def getGraph(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(
self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match" % (
len(self.__x), len(self.__y), len(
self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [
float(i) for i in self.__getStyleOption("legendPosition").split()
]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s" %
(self.__title, self.__xTitle, self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d", [0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__yErrLow, self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__ySysErrLow, self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
result.Add(sysGraph, "[]")
result.Add(graph, "P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s" % (self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
def bestfit():
xmin = -10
xmax = 6
c, h = draw_canvas_histo(
xmin, xmax, "Best fit #mu = #sigma/#sigma_{SM} at m_{H} = 125 GeV")
# line at SM expectation of mu = 1
l = TLine()
l.SetLineStyle(2)
l.DrawLine(1.0, -1.0, 1.0, -1.0 + nchannels)
mu = np.array([-0.4, -4.734, -2.014])
upper = np.array([2.12, 3.688, 1.80])
lower = np.array([2.08, 3.754, 1.8224])
channel = np.array([1.5, 0.5, -0.5])
zero = np.zeros(nchannels)
gmu = TGraphAsymmErrors(nchannels, mu, channel, lower, upper, zero, zero)
gmu.SetMarkerStyle(21)
gmu.SetMarkerSize(1.5)
gmu.SetLineColor(2)
gmu.SetLineWidth(2)
gmu.Draw("pz")
#draw_disclaimer()
c.RedrawAxis()
c.Modified()
c.Update()
c.SaveAs("bestfit.pdf")
def getGraphSimple(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
graph.SetDrawOption("AP")
return (graph, legend)
def convertToPoisson(h):
graph = TGraphAsymmErrors()
q = (1-0.6827)/2.
for i in range(1,h.GetNbinsX()+1):
x=h.GetXaxis().GetBinCenter(i)
xLow =h.GetXaxis().GetBinLowEdge(i)
xHigh =h.GetXaxis().GetBinUpEdge(i)
y=h.GetBinContent(i)
yLow=0
yHigh=0
if y !=0.0:
yLow = y-Math.chisquared_quantile_c(1-q,2*y)/2.
yHigh = Math.chisquared_quantile_c(q,2*(y+1))/2.-y
graph.SetPoint(i-1,x,y)
graph.SetPointEYlow(i-1,yLow)
graph.SetPointEYhigh(i-1,yHigh)
graph.SetPointEXlow(i-1,0.0)
graph.SetPointEXhigh(i-1,0.0)
graph.SetMarkerStyle(20)
graph.SetLineWidth(2)
graph.SetMarkerSize(1.)
graph.SetMarkerColor(kBlack)
return graph
def makeResidHist(data, bkg):
pulls = TGraphAsymmErrors(data.GetN())
pulls.SetName("Pulls")
pulls.SetLineWidth(data.GetLineWidth())
pulls.SetLineStyle(data.GetLineStyle())
pulls.SetLineColor(data.GetLineColor())
pulls.SetMarkerSize(data.GetMarkerSize())
pulls.SetMarkerStyle(data.GetMarkerStyle())
pulls.SetMarkerColor(data.GetMarkerColor())
pulls.SetFillStyle(data.GetFillStyle())
pulls.SetFillColor(data.GetFillColor())
# Add histograms, calculate Poisson confidence interval on sum value
for i in range(data.GetN()):
x = data.GetX()[i]
dyl = data.GetErrorYlow(i)
dyh = data.GetErrorYhigh(i)
yy = data.GetY()[i] - bkg.Interpolate(x) #bkg.GetBinContent(i+1)
norm = dyl if yy > 0. else dyh
if norm == 0.:
yy, dyh, dyl = 0., 0., 0.
else:
yy /= norm
dyh /= norm
dyl /= norm
pulls.SetPoint(i, x, yy)
pulls.SetPointEYhigh(i, dyh)
pulls.SetPointEYlow(i, dyl)
return pulls
def convertHistToGraph(hist, useGarwood=False):
alpha = 1 - 0.6827
graph = TGraphAsymmErrors(hist.GetNbinsX())
if useGarwood:
lastEvent = False
for i in reversed(range(hist.GetNbinsX())):
N = hist.GetBinContent(i + 1)
if not lastEvent and N > 0: lastEvent = True
if lastEvent and N <= 0.: N = 1.e-6
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
graph.SetPointError(i, 0., 0., N - L, U - N)
else:
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
hist.GetBinContent(i + 1))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetBinError(i + 1),
hist.GetBinError(i + 1))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def ratioplot():
# create required parts
leg = getLegend()
latex = getLatex()
c = TCanvas()
c.SetLogy()
#Draw input histograms
hists = ['h_frac_recoil_', 'h_full_recoil_']
label = ['recoil with MET triggers', 'recoil without MET triggers']
combineHist(hists, label, leg)
#leg.Draw()
#c.SaveAs("Combinehists_D.pdf")
ratio = []
h1 = f.Get('h_frac_recoil_')
#h1=setHistStyle(h1,bins)
h2 = f.Get('h_full_recoil_')
#h2=setHistStyle(h2,bins)
h3 = createRatio(h1, h2)
gr = TGraphAsymmErrors(h1, h2)
gr.GetXaxis().SetRangeUser(0, 1500)
gr.GetYaxis().SetRangeUser(0, 1.2)
gr.SetMarkerStyle(20)
gr.SetMarkerSize(0.5)
gr.SetLineColor(1)
gr.GetYaxis().SetTitle("Trigger Efficiency")
gr.GetXaxis().SetTitle("Recoil [GeV]")
gr.SetTitle("")
# print ("ratio",ratio )
# c, pad1, pad2 = createCanvasPads()
#
# # draw everything
# pad1.cd()
# h1.Draw()
# h2.Draw("same")
# to avoid clipping the bottom zero, redraw a small axis
# h1.GetYaxis().SetLabelSize(0.0)
# axis = TGaxis(-5, 20, -5, 220, 20, 220, 510, "")
# axis.SetLabelFont(43)
# axis.SetLabelSize(15)
# axis.Draw()
# pad2.cd()
gr.Draw()
latex.DrawLatex(0.41, 0.93, "Trigger Efficincy in MET Run2017E")
xmin = 0.0
line = TLine(max(xmin, gr.GetXaxis().GetXmin()), 1, 1500, 1)
line.SetLineColor(1)
line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw()
#h3.Draw('pl')
c.SaveAs("test.pdf")
def makeEffPlotsVars(tree,
varx,
vary,
sel,
nbinx,
xmin,
xmax,
nbiny,
ymin,
ymax,
xtitle,
ytitle,
leglabel=None,
header='',
addon='',
option='pt',
marker=20):
binning = [20, 30, 40, 50, 60, 70, 80, 100, 150, 200]
c = TCanvas()
if option == 'pt':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(binning) - 1, array('d', binning))
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(binning) - 1, array('d', binning))
elif option == 'eta':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon, nbinx, xmin, xmax)
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon, nbinx, xmin,
xmax)
elif option == 'nvtx':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(vbinning) - 1, array('d', vbinning))
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(vbinning) - 1, array('d', vbinning))
tree.Draw(varx + ' >> ' + _hist_.GetName(), sel)
tree.Draw(varx + ' >> ' + _ahist_.GetName(), sel + ' && ' + vary)
g_efficiency = TGraphAsymmErrors()
g_efficiency.BayesDivide(_ahist_, _hist_)
g_efficiency.GetXaxis().SetTitle(xtitle)
g_efficiency.GetYaxis().SetTitle('efficiency')
g_efficiency.GetYaxis().SetNdivisions(507)
g_efficiency.SetLineWidth(3)
g_efficiency.SetName(header)
g_efficiency.SetMinimum(0.)
g_efficiency.GetYaxis().SetTitleOffset(1.3)
g_efficiency.SetMarkerStyle(marker)
g_efficiency.SetMarkerSize(1)
g_efficiency.Draw('ap')
# save(c, 'plots/' + addon)
return copy.deepcopy(g_efficiency)
def getDataPoissonErrors(hist,
kPoisson=False,
drawZeroBins=False,
drawXbars=False,
centerBin=True):
'''Make data poisson errors for a histogram with two different methods:
- TH1.kPoisson
- chi-squared quantile
'''
# https://github.com/DESY-CMS-SUS/cmgtools-lite/blob/8_0_25/TTHAnalysis/python/plotter/mcPlots.py#L70-L102
# https://github.com/DESY-CMS-SUS/cmgtools-lite/blob/8_0_25/TTHAnalysis/python/plotter/susy-1lep/RcsDevel/plotDataPredictWithSyst.py#L12-L21
if kPoisson: hist.SetBinErrorOption(TH1D.kPoisson)
Nbins = hist.GetNbinsX()
xaxis = hist.GetXaxis()
alpha = (1 - 0.6827) / 2.
graph = TGraphAsymmErrors(Nbins)
graph.SetName(hist.GetName() + "_graph")
graph.SetTitle(hist.GetTitle())
for i in xrange(1, Nbins + 1):
N = hist.GetBinContent(i)
if N <= 0 and not drawZeroBins: continue
dN = hist.GetBinError(i)
yscale = 1
if centerBin:
x = xaxis.GetBinCenter(i)
else:
x = xaxis.GetBinLowEdge(i)
if N > 0 and dN > 0 and abs(dN**2 / N -
1) > 1e-4: # check is error is Poisson
yscale = (dN**2 / N)
N = (N / dN)**2
if kPoisson:
EYlow = hist.GetBinErrorLow(i)
EYup = hist.GetBinErrorUp(i)
else:
EYlow = (N - Math.chisquared_quantile_c(1 - alpha, 2 * N) /
2.) if N > 0 else 0
EYup = Math.chisquared_quantile_c(alpha, 2 * (N + 1)) / 2. - N
y = yscale * N
EXup = xaxis.GetBinUpEdge(i) - x if drawXbars else 0
EXlow = x - xaxis.GetBinLowEdge(i) if drawXbars else 0
graph.SetPoint(i - 1, x, y)
graph.SetPointError(i - 1, EXlow, EXup, EYlow, EYup)
#print ">>> getDataPoissonErrors - bin %2d: (x,y) = ( %3.1f - %4.2f + %4.2f, %4.2f - %4.2f + %4.2f )"%(i,x,EXlow,EXup,y,EYlow,EYup)
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineColor(hist.GetLineColor())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetMarkerStyle(hist.GetMarkerStyle())
return graph
def makeEffPlotsVars(tree,
varx,
vary,
sel,
nbinx,
xmin,
xmax,
nbiny,
ymin,
ymax,
xtitle,
ytitle,
leglabel=None,
header='',
addon='',
option='pt',
marker=20,
col=1):
binning = [20, 200] if args.onebin else [
20, 30, 40, 50, 60, 70, 80, 100, 150, 200
]
if option == 'pt':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(binning) - 1, array('d', binning))
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(binning) - 1, array('d', binning))
elif option == 'eta':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon, nbinx, xmin, xmax)
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon, nbinx, xmin,
xmax)
tree.Draw(varx + ' >> ' + _hist_.GetName(), sel)
tree.Draw(varx + ' >> ' + _ahist_.GetName(), sel + ' && ' + vary)
g_efficiency = TGraphAsymmErrors()
g_efficiency.Divide(_ahist_, _hist_, "cl=0.683 b(1,1) mode")
g_efficiency.GetXaxis().SetTitle(xtitle)
g_efficiency.GetYaxis().SetTitle('efficiency')
g_efficiency.GetYaxis().SetNdivisions(507)
g_efficiency.SetLineWidth(3)
g_efficiency.SetName(header)
g_efficiency.SetMinimum(0.)
g_efficiency.GetYaxis().SetTitleOffset(1.3)
g_efficiency.SetMarkerStyle(marker)
g_efficiency.SetMarkerSize(1)
g_efficiency.SetMarkerColor(col)
g_efficiency.SetLineColor(col)
g_efficiency.Draw('ap')
# save(c, 'plots/' + addon)
return g_efficiency
def fixData(hist, useGarwood=True, cutGrass=False, maxPoisson=False):
if hist == None: return
varBins = False
data = TGraphAsymmErrors()
alpha = 1 - 0.6827
for i in list(reversed(range(0, hist.GetNbinsX()))):
#print "bin", i, "x:", hist.GetX()[i], "y:", hist.GetY()[i]
# X error bars to 0 - do not move this, otherwise the first bin will disappear, thanks Wouter and Rene!
N = max(hist.GetBinContent(i + 1), 0.) # Avoid unphysical bins
data.SetPoint(i, hist.GetXaxis().GetBinCenter(i + 1), N)
if not varBins:
data.SetPointEXlow(i, 0)
data.SetPointEXhigh(i, 0)
# Garwood confidence intervals
if (useGarwood):
L = ROOT.Math.gamma_quantile(alpha / 2, N, 1.) if N > 0 else 0.
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
# maximum between Poisson and Sumw2 error bars
EL = N - L if not maxPoisson else max(N -
L, hist.GetBinErrorLow(i))
EU = U - N if not maxPoisson else max(U -
N, hist.GetBinErrorHigh(i))
data.SetPointEYlow(i, EL)
data.SetPointEYhigh(i, EU)
else:
data.SetPointEYlow(i, math.sqrt(N))
data.SetPointEYhigh(i, math.sqrt(N))
# Cut grass
if cutGrass and data.GetY()[i] > 0.: cutGrass = False
# Treatment for 0 bins
# if abs(hist.GetY()[i])<=1.e-6:
# if cutGrass: hist.SetPointError(i, hist.GetErrorXlow(i), hist.GetErrorXhigh(i), 1.e-6, 1.e-6, )
# if (hist.GetX()[i]>65 and hist.GetX()[i]<135 and hist.GetY()[i]==0): hist.SetPointError(i, hist.GetErrorXlow(i), hist.GetErrorXhigh(i), 1.e-6, 1.e-6, )
# hist.SetPoint(i, hist.GetX()[i], -1.e-4)
# X error bars
#if hist.GetErrorXlow(i)<1.e-4:
# binwidth = hist.GetX()[1]-hist.GetX()[0]
# hist.SetPointEXlow(i, binwidth/2.)
# hist.SetPointEXhigh(i, binwidth/2.)
data.SetMarkerColor(hist.GetMarkerColor())
data.SetMarkerStyle(hist.GetMarkerStyle())
data.SetMarkerSize(hist.GetMarkerSize())
#data.SetLineSize(hist.GetLineSize())
return data
def convertHistToGraph(hist):
graph = TGraphAsymmErrors(hist.GetNbinsX())
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i), hist.GetBinContent(i))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetBinError(i), hist.GetBinError(i))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def histToGraph(hist, name='', keepErrors=True, poissonErrors=True):
## Helper method to convert a histogram to a corresponding graph
# @hist TH1 object
# @name name of the graph (default is name of histogram)
# @keepErrors decide if the y-errors should be propagated to the graph
# @poissonErrors decide if the y-errors should be calculated as Poisson errors
# @return graph
if not name:
name = 'g%s' % (hist.GetName())
from ROOT import TGraphAsymmErrors
nBins = hist.GetNbinsX()
graph = TGraphAsymmErrors(nBins)
graph.SetNameTitle(name, hist.GetTitle())
xAxis = hist.GetXaxis()
for i in xrange(nBins):
xVal = xAxis.GetBinCenter(i + 1)
yVal = hist.GetBinContent(i + 1)
graph.SetPoint(i, xVal, yVal)
graph.SetPointEXlow(i, abs(xVal - xAxis.GetBinLowEdge(i + 1)))
graph.SetPointEXhigh(i, abs(xVal - xAxis.GetBinUpEdge(i + 1)))
if keepErrors:
if poissonErrors:
lo, hi = calculatePoissonErrors(yVal)
graph.SetPointEYlow(i, lo)
graph.SetPointEYhigh(i, hi)
else:
graph.SetPointEYlow(i, hist.GetBinErrorLow(i + 1))
graph.SetPointEYhigh(i, hist.GetBinErrorUp(i + 1))
# copy the style
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetLineWidth(hist.GetLineWidth())
graph.SetFillColor(hist.GetFillColor())
graph.SetFillStyle(hist.GetFillStyle())
return graph
def makeEffPlotsVars(tree,
varx,
numeratorAddSelection,
baseSelection,
binning,
xtitle='',
header='',
addon='',
marker=20,
col=1):
_denomHist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(binning) - 1, binning)
_nominatorHist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(binning) - 1, binning)
tree.Draw(varx + ' >> ' + _denomHist_.GetName(), baseSelection)
tree.Draw(varx + ' >> ' + _nominatorHist_.GetName(),
baseSelection + ' && ' + numeratorAddSelection)
g_eff = TGraphAsymmErrors()
g_eff.Divide(_nominatorHist_, _denomHist_, "cl=0.683 b(1,1) mode")
g_eff.GetXaxis().SetTitle(xtitle)
g_eff.GetYaxis().SetTitle('efficiency')
g_eff.GetYaxis().SetNdivisions(507)
g_eff.SetLineWidth(3)
g_eff.SetName(header)
g_eff.SetMinimum(0.)
g_eff.GetYaxis().SetTitleOffset(1.3)
g_eff.SetMarkerStyle(marker)
g_eff.SetMarkerSize(1)
g_eff.SetMarkerColor(col)
g_eff.SetLineColor(col)
g_eff.Draw('ap')
return g_eff
def fixPlots_withErrors(middleGraph):
thisBandsGraph = TGraphAsymmErrors()
thisBandsGraph.SetName(middleGraph.GetName())
thisBandsGraph.SetMarkerStyle(middleGraph.GetMarkerStyle())
thisBandsGraph.SetMarkerSize(middleGraph.GetMarkerSize())
thisBandsGraph.SetMarkerColor(middleGraph.GetMarkerColor())
thisBandsGraph.SetLineColor(middleGraph.GetLineColor())
for iPoint in xrange(0, middleGraph.GetN()):
# Retrieve middle graph for (x,y) coordinates
dataPointX = Double(0)
dataPointY = Double(0)
dataErrorX = Double(0)
middleGraph.GetPoint(iPoint, dataPointX, dataPointY)
dataErrorX = middleGraph.GetErrorX(iPoint)
dataErrorY = middleGraph.GetErrorY(iPoint)
dataPointY = fabs(dataPointY - 1)
if (iPoint < middleGraph.GetN()):
#if(dataPointY != 0 and iPoint < middleGraph.GetN()):
print "fixPlots:", dataPointX
thisBandsGraph.SetPoint(iPoint, dataPointX, dataPointY)
thisBandsGraph.SetPointError(iPoint, dataErrorX, dataErrorX,
dataErrorY, dataErrorY)
#if (dataPointY == 0) :
#thisBandsGraph.SetPoint(iPoint, dataPointX, dataPointY)
#thisBandsGraph.SetPointError(iPoint, dataErrorX, dataErrorX, dataErrorY, dataErrorY)
return thisBandsGraph
#print threshold_scan
##Prepare the canvas to plot the scan for SL1_L1
can_scan_SL1_L1 = TCanvas("can_scan_SL1_L1","can_scan_SL1_L1", 1000, 800)
can_scan_SL1_L1.SetGrid()
can_scan_SL1_L1.cd()
##Prepare summary TGraph
graph = TGraphAsymmErrors()
n=0
for a in sorted(threshold_scan):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph.SetPoint(n,int(a),float(threshold_scan[a]))
n = n+1
graph.SetMarkerSize(1.)
graph.SetMarkerStyle(21)
graph.SetMarkerColor(862)
graph.SetFillColor(868)
graph.SetFillStyle(3844)
graph.SetLineColor(868)
graph.SetLineWidth(2)
graph.SetLineStyle(2)
graph.GetXaxis().SetTitle("threshold [mV]")
graph.GetYaxis().SetTitleOffset(1.2)
graph.GetYaxis().SetTitle("rate [kHz]")
graph.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextColor(1)
def plotQIcalibration(results, outDir = "results", currentMode = ""):
gROOT.SetBatch(True)
calibGraphs = []
gStyle.SetMarkerColor(kBlue)
gStyle.SetLineColor(kBlack)
#for ch in xrange(1, len(results)+1): # Number of channels
for ch in sorted(results.keys()):
gr = TGraphAsymmErrors()
gr.SetMarkerStyle(22)
gr.SetMarkerSize(1.2)
gr.SetName("Channel_%d_Charge_vs_DAC" % ch)
gr.SetTitle("Channel %d Charge vs DAC value%s" % (ch, " %s current mode" % currentMode if currentMode in ["low", "high"] else ""))
res = results[ch]
for i, dacVal in enumerate(sorted(res.keys())):
mean = res[dacVal]["mean"] * 25.e6 # Convert to fC
err = res[dacVal]["std"] * 25.e6
# Index of new point
np = gr.GetN()
# Set value and error
gr.SetPoint(np, dacVal, mean)
gr.SetPointError(np, 0., 0., err, err)
calibGraphs.append((gr,ch))
if outDir[-1] == "/": outDir = outDir[:-1]
os.system("mkdir -p %s/calibGraphs" % outDir )
c1 = TCanvas('c1','c1', 1200, 800)
c1.SetLeftMargin(0.15);
c1.SetRightMargin(0.25)
c1.SetBottomMargin(0.25);
pad1=TPad('p1','p1',0.,0.,1.0,1.0)
pad1.Draw()
outF = TFile.Open(outDir + "/calibration.root", "RECREATE")
fitParams = {} # Converted to charge by * 25ns
for i,(gr,ch) in enumerate(calibGraphs):
gr.Fit('pol1', "Q") # Q: Quiet mode
f = gr.GetFunction("pol1")
p0 = f.GetParameter(0)
p0_err = f.GetParError(0)
p1 = f.GetParameter(1)
p1_err = f.GetParError(1)
fitline = "offset %g #pm %g slope %g #pm %g" % (p0, p0_err, p1, p1_err)
# Convert to fC
fitParams[ch] = {"slope":(p1), "offset":(p0)}
#fitParams[(i+1)] = {"slope":(p1), "offset":(p0)}
gr.GetXaxis().SetTitle("DAC value")
gr.GetYaxis().SetTitle("Charge [fC]")
if currentMode == "low":
gr.GetYaxis().SetTitleOffset(1.37)
pad1.cd()
gr.Draw("AP")
gr.Write()
txt=TLatex()
txt.SetNDC(True)
txt.SetTextFont(43)
txt.SetTextSize(20)
txt.SetTextAlign(12)
txt.DrawLatex(0.40,0.87, fitline)
Quiet(c1.SaveAs)(outDir + "/calibGraphs/channel_%d.png" % (i+1))
# for g in adcGraphs:
#
# g.Write()
# for g in chargeGraphs:
# g.Write()
#outF.Write()
outF.Close()
return fitParams
def draw(hist, data, back, sign, snorm=1, ratio=0, poisson=False, log=False):
# If not present, create BkgSum
if not 'BkgSum' in hist.keys():
hist['BkgSum'] = hist['data_obs'].Clone(
"BkgSum") if 'data_obs' in hist else hist[back[0]].Clone("BkgSum")
hist['BkgSum'].Reset("MICES")
for i, s in enumerate(back):
hist['BkgSum'].Add(hist[s])
hist['BkgSum'].SetMarkerStyle(0)
# Some style
for i, s in enumerate(data):
hist[s].SetMarkerStyle(21)
hist[s].SetMarkerSize(1.25)
for i, s in enumerate(sign):
hist[s].SetLineWidth(3)
for i, s in enumerate(data + back + sign + ['BkgSum']):
addOverflow(hist[s], False) # Add overflow
# Set Poisson error bars
#if len(data) > 0: hist['data_obs'].SetBinErrorOption(1) # doesn't work
# Poisson error bars for data
if poisson:
alpha = 1 - 0.6827
hist['data_obs'].SetBinErrorOption(TH1.kPoisson)
data_graph = TGraphAsymmErrors(hist['data_obs'].GetNbinsX())
data_graph.SetMarkerStyle(hist['data_obs'].GetMarkerStyle())
data_graph.SetMarkerSize(hist['data_obs'].GetMarkerSize())
res_graph = data_graph.Clone()
for i in range(hist['data_obs'].GetNbinsX()):
N = hist['data_obs'].GetBinContent(i + 1)
B = hist['BkgSum'].GetBinContent(i + 1)
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
data_graph.SetPoint(
i, hist['data_obs'].GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
data_graph.SetPointError(
i, hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2., N - L,
U - N)
res_graph.SetPoint(i,
hist['data_obs'].GetXaxis().GetBinCenter(i + 1),
N / B if not B == 0 and not N == 0 else -1.e99)
res_graph.SetPointError(
i, hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
(N - L) / B if not B == 0 else -1.e99,
(U - N) / B if not B == 0 else -1.e99)
# Create stack
bkg = THStack("Bkg",
";" + hist['BkgSum'].GetXaxis().GetTitle() + ";Events")
for i, s in enumerate(back):
bkg.Add(hist[s])
# Legend
n = len([x for x in data + back + ['BkgSum'] + sign if samples[x]['plot']])
for i, s in enumerate(sign):
if 'sublabel' in samples[s]: n += 1
if 'subsublabel' in samples[s]: n += 1
#leg = TLegend(0.68, 0.9-0.05*n, 0.93, 0.9)
leg = TLegend(0.68 - 0.05, 0.9 - 0.05 * n, 0.93, 0.9) #DCMS
leg.SetTextSize(0.03) #DCMS
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("Signal x-sec=%.0f pb" % (1 * snorm))
if len(data) > 0:
leg.AddEntry(hist[data[0]], samples[data[0]]['label'], "ple1")
for i, s in reversed(list(enumerate(['BkgSum'] + back))):
leg.AddEntry(hist[s], samples[s]['label'], "f")
for i, s in enumerate(sign):
leg.AddEntry(hist[s], samples[s]['label'], "f")
# --- Display ---
c1 = TCanvas("c1",
hist.values()[-1].GetXaxis().GetTitle(), 1000,
800 if ratio else 700)
if ratio:
c1.Divide(1, 2)
setTopPad(c1.GetPad(1), ratio)
setBotPad(c1.GetPad(2), ratio)
c1.cd(1)
c1.GetPad(bool(ratio)).SetTopMargin(0.06)
c1.GetPad(bool(ratio)).SetRightMargin(0.05)
c1.GetPad(bool(ratio)).SetTicks(1, 1)
if log:
c1.GetPad(bool(ratio)).SetLogy()
#c1.GetPad(bool(ratio)).SetLogx()
# Draw
bkg.Draw("HIST") # stack
hist['BkgSum'].Draw("SAME, E2") # sum of bkg
if poisson: data_graph.Draw("SAME, PE")
elif len(data) > 0: hist['data_obs'].Draw("SAME, PE")
for i, s in enumerate(sign):
if samples[s]['plot']:
hist[s].DrawNormalized("SAME, HIST",
hist[s].Integral() * snorm) # signals
bkg.GetYaxis().SetTitleOffset(bkg.GetYaxis().GetTitleOffset() * 1.075)
# Determine range
if 'data_obs' in hist:
bkg.SetMaximum((2.5 if log else 1.2) * max(
bkg.GetMaximum(),
hist['data_obs'].GetBinContent(hist['data_obs'].GetMaximumBin()) +
hist['data_obs'].GetBinError(hist['data_obs'].GetMaximumBin())))
bkg.SetMinimum(
max(
min(
hist['BkgSum'].GetBinContent(hist['BkgSum'].GetMinimumBin(
)), hist['data_obs'].GetMinimum()), 5.e-1) if log else 0.)
else:
bkg.SetMaximum(bkg.GetMaximum() * (2.5 if log else 1.2))
bkg.SetMinimum(5.e-1 if log else 0.)
if log:
bkg.GetYaxis().SetNoExponent(bkg.GetMaximum() < 1.e4)
bkg.GetYaxis().SetMoreLogLabels(True)
leg.Draw()
#drawCMS(LUMI, "Preliminary")
#drawRegion(channel)
#drawAnalysis("LL")
setHistStyle(bkg, 1.2 if ratio else 1.1)
setHistStyle(hist['BkgSum'], 1.2 if ratio else 1.1)
if ratio:
c1.cd(2)
err = hist['BkgSum'].Clone("BkgErr;")
err.SetTitle("")
err.GetYaxis().SetTitle("Data / Bkg")
for i in range(1, err.GetNbinsX() + 1):
err.SetBinContent(i, 1)
if hist['BkgSum'].GetBinContent(i) > 0:
err.SetBinError(
i, hist['BkgSum'].GetBinError(i) /
hist['BkgSum'].GetBinContent(i))
setBotStyle(err)
errLine = err.Clone("errLine")
errLine.SetLineWidth(2)
errLine.SetFillStyle(0)
errLine.SetLineColor(2) #L#
errLine.SetLineStyle(2) #L#
#err.GetXaxis().SetLabelOffset(err.GetXaxis().GetLabelOffset()*5)
#err.GetXaxis().SetTitleOffset(err.GetXaxis().GetTitleOffset()*2)
err.Draw("E2")
errLine.Draw("SAME, HIST")
if 'data_obs' in hist:
res = hist['data_obs'].Clone("Residues")
for i in range(0, res.GetNbinsX() + 1):
if hist['BkgSum'].GetBinContent(i) > 0:
res.SetBinContent(
i,
res.GetBinContent(i) / hist['BkgSum'].GetBinContent(i))
res.SetBinError(
i,
res.GetBinError(i) / hist['BkgSum'].GetBinContent(i))
setBotStyle(res)
if poisson: res_graph.Draw("SAME, PE0")
else: res.Draw("SAME, PE0")
if len(err.GetXaxis().GetBinLabel(
1)) == 0: # Bin labels: not a ordinary plot
drawRatio(hist['data_obs'], hist['BkgSum'])
drawKolmogorov(hist['data_obs'], hist['BkgSum'])
else:
res = None
c1.Update()
# return list of objects created by the draw() function
return [
c1, bkg, leg, err if ratio else None, errLine if ratio else None,
res if ratio else None, data_graph if poisson else None,
res_graph if poisson else None
]
def draw(hist, data, back, sign, snorm=1, ratio=0, poisson=True, log=False):
groupList = plt.cfg.getGroupPlot()
# If not present, create BkgSum
#if not 'BkgSum' in hist.keys():
# hist['BkgSum'] = hist['DATA'].Clone("BkgSum") if 'DATA' in hist else hist[back[0]].Clone("BkgSum")
# hist['BkgSum'].Reset("MICES")
# for i, s in enumerate(back): hist['BkgSum'].Add(hist[s].GetPtr())
hist['BkgSum'].SetMarkerStyle(0)
# Some style
for i, s in enumerate(data):
hist[s].SetMarkerStyle(20)
hist[s].SetMarkerSize(1.25)
for i, s in enumerate(sign):
hist[s].SetLineWidth(3)
for i, s in enumerate(data + back + sign + ['BkgSum']):
addOverflow(hist[s], False) # Add overflow
# Set Poisson error bars
#if len(data) > 0: hist['data_obs'].SetBinErrorOption(1) # doesn't work
# Poisson error bars for data
if poisson:
alpha = 1 - 0.6827
hist['DATA'].SetBinErrorOption(TH1.kPoisson)
data_graph = TGraphAsymmErrors(hist['DATA'].GetNbinsX())
data_graph.SetMarkerStyle(hist['DATA'].GetMarkerStyle())
data_graph.SetMarkerSize(hist['DATA'].GetMarkerSize())
res_graph = data_graph.Clone()
for i in range(hist['DATA'].GetNbinsX()):
N = hist['DATA'].GetBinContent(i + 1)
B = hist['BkgSum'].GetBinContent(i + 1)
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
data_graph.SetPoint(i, hist['DATA'].GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
data_graph.SetPointError(
i, hist['DATA'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['DATA'].GetXaxis().GetBinWidth(i + 1) / 2., N - L, U - N)
res_graph.SetPoint(i, hist['DATA'].GetXaxis().GetBinCenter(i + 1),
N / B if not B == 0 and not N == 0 else -1.e99)
res_graph.SetPointError(
i, hist['DATA'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['DATA'].GetXaxis().GetBinWidth(i + 1) / 2.,
(N - L) / B if not B == 0 else -1.e99,
(U - N) / B if not B == 0 else -1.e99)
# Create stack
#bkg = THStack("Bkg", ";"+hist['BkgSum'].GetXaxis().GetTitle()+";Events")
bkg = THStack(
"Bkg", ";" + hist['BkgSum'].GetXaxis().GetTitle() + ";" +
hist['BkgSum'].GetYaxis().GetTitle())
for i, s in enumerate(back):
bkg.Add(hist[s])
# Legend
n = len(
[x for x in data + back + ['BkgSum'] + sign if groupList[x]['plot']])
for i, s in enumerate(sign):
if 'sublabel' in groupList[s]: n += 1
if 'subsublabel' in groupList[s]: n += 1
leg = TLegend(0.7, 0.9 - 0.05 * n, 0.95, 0.9)
#leg.SetNColumns(3)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
if len(data) > 0:
#leg.AddEntry( hist[data[0]] , groupList[data[0]]['label'], "pl")
leg.AddEntry(
hist[data[0]], '%s [%.1f]' %
(groupList[data[0]]['label'], hist[data[0]].Integral()), "pl")
for i, s in reversed(list(enumerate(['BkgSum'] + back))):
leg.AddEntry(hist[s] if s == 'BkgSum' else hist[s],
'%s [%.1f]' % (groupList[s]['label'], hist[s].Integral()),
"f")
for i, s in enumerate(sign):
if groupList[s]['plot']:
#leg.AddEntry( hist[s] if s=='BkgSum' else hist[s] , groupList[s]['label'], "fl")
leg.AddEntry(
hist[s] if s == 'BkgSum' else hist[s],
'%s [%.1f]' % (groupList[s]['label'], hist[s].Integral()),
"fl")
#print samples[s]
if 'sublabel' in groupList[s]:
leg.AddEntry(
hist[s] if s == 'BkgSum' else hist[s],
groupList[s]['sublabel'].replace("m_{#Chi}=1 GeV", ""), "")
if 'subsublabel' in groupList[s]:
leg.AddEntry(
hist[s] if s == 'BkgSum' else hist[s],
groupList[s]['subsublabel'].replace("m_{#Chi}=1 GeV",
""), "")
# --- Display ---
c1 = TCanvas("c1",
hist.values()[-1].GetXaxis().GetTitle(), 800,
800 if ratio else 600)
if ratio:
c1.Divide(1, 2)
setTopPad(c1.GetPad(1), ratio)
setBotPad(c1.GetPad(2), ratio)
c1.cd(1)
c1.GetPad(bool(ratio)).SetTopMargin(0.06)
c1.GetPad(bool(ratio)).SetRightMargin(0.05)
c1.GetPad(bool(ratio)).SetTicks(1, 1)
if log:
c1.GetPad(bool(ratio)).SetLogy()
# Draw
bkg.Draw("HIST") # stack
hist['BkgSum'].Draw("SAME, E2") # sum of bkg
if poisson: data_graph.Draw("SAME, PE")
elif len(data) > 0: hist['DATA'].Draw("SAME, PE")
for i, s in enumerate(sign):
if groupList[s]['plot']:
hist[s].DrawNormalized("SAME, HIST",
hist[s].Integral() * snorm) # signals
#bkg.GetYaxis().SetTitleOffset(bkg.GetYaxis().GetTitleOffset()*1.075) #1.075
if 'DATA' in hist:
#bkg.SetMaximum((3.0 if log else 1.5)*max(bkg.GetMaximum(), hist['DATA'].GetBinContent(hist['DATA'].GetMaximumBin())+hist['DATA'].GetBinError(hist['DATA'].GetMaximumBin())))
bkg.SetMaximum((25.0 if log else 2.0) * max(
bkg.GetMaximum(),
hist['DATA'].GetBinContent(hist['DATA'].GetMaximumBin()) +
hist['DATA'].GetBinError(hist['DATA'].GetMaximumBin())))
bkg.SetMinimum(
max(
min(
hist['BkgSum'].GetBinContent(hist['BkgSum'].GetMinimumBin(
)), hist['DATA'].GetMinimum()), 5.e-1) if log else 0.)
else:
bkg.SetMaximum(bkg.GetMaximum() * (3.0 if log else 1.5)) #2.5 ; 1.2
bkg.SetMinimum(5.e-1 if log else 0.)
if not log:
#bkg.GetYaxis().SetNoExponent(1)
bkg.GetYaxis().SetNoExponent(bkg.GetMaximum() < 1.e4)
# bkg.GetYaxis().SetMoreLogLabels(True)
#set range on stack
bkg.SetMinimum(5.e-1 if log else 1.0)
leg.Draw()
setHistStyle(bkg, 1.2 if ratio else 1.1)
setHistStyle(hist['BkgSum'], 1.2 if ratio else 1.1)
if ratio:
#err.GetXaxis().SetTitleOffset(err.GetXaxis().GetTitleOffset()*1)
c1.cd(2)
err = hist['BkgSum'].Clone("BkgErr;")
err.SetTitle("")
err.GetYaxis().SetTitle("Data / Bkg")
for i in range(1, err.GetNbinsX() + 1):
err.SetBinContent(i, 1)
if hist['BkgSum'].GetBinContent(i) > 0:
err.SetBinError(
i, hist['BkgSum'].GetBinError(i) /
hist['BkgSum'].GetBinContent(i))
setBotStyle(err)
errLine = err.Clone("errLine")
errLine.SetLineWidth(1)
errLine.SetFillStyle(0)
errLine.SetLineColor(1)
#err.GetXaxis().SetLabelOffset(err.GetXaxis().GetLabelOffset()*1)
#err.GetXaxis().SetTitleOffset(err.GetXaxis().GetTitleOffset()*1)
#err.GetYaxis().SetTitleOffset(err.GetYaxis().GetTitleOffset()*1)
err.Draw("E2")
errLine.Draw("SAME, HIST")
if 'DATA' in hist:
res = hist['DATA'].Clone("Residues")
for i in range(0, res.GetNbinsX() + 1):
if hist['BkgSum'].GetBinContent(i) > 0:
res.SetBinContent(
i,
res.GetBinContent(i) / hist['BkgSum'].GetBinContent(i))
res.SetBinError(
i,
res.GetBinError(i) / hist['BkgSum'].GetBinContent(i))
setBotStyle(res)
if poisson: res_graph.Draw("SAME, PE0")
else: res.Draw("SAME, PE0")
if len(err.GetXaxis().GetBinLabel(
1)) == 0: # Bin labels: not a ordinary plot
drawRatio(hist['DATA'], hist['BkgSum'])
drawKolmogorov(hist['DATA'], hist['BkgSum'])
if len(sign) != 0: drawSB(hist['BkgSum'], hist[sign[0]])
#drawRelativeYield( hist['DATA'] , hist['BkgSum'] )
else:
res = None
c1.Update()
# return list of objects created by the draw() function
if not ratio:
return [
c1, bkg, leg, data_graph if poisson else None,
res_graph if poisson else None
]
else:
return [
c1, bkg, leg, err, errLine, res, data_graph if poisson else None,
res_graph if poisson else None
]
def draw(hist,
channel,
data,
back,
sign,
snorm=1,
lumi=-1,
ratio=0,
log=False):
# If not present, create BkgSum
if not 'BkgSum' in hist.keys():
hist['BkgSum'] = hist['data_obs'].Clone(
"BkgSum") if 'data_obs' in hist else hist[back[0]].Clone("BkgSum")
hist['BkgSum'].Reset("MICES")
for i, s in enumerate(back):
hist['BkgSum'].Add(hist[s])
hist['BkgSum'].SetMarkerStyle(0)
# Set Poisson error bars
#if len(data) > 0: hist['data_obs'].SetBinErrorOption(1) # doesn't work
alpha = 1 - 0.6827
hist['data_obs'].SetBinErrorOption(TH1.kPoisson)
data_graph = TGraphAsymmErrors(hist['data_obs'].GetNbinsX())
data_graph.SetMarkerStyle(hist['data_obs'].GetMarkerStyle())
data_graph.SetMarkerSize(hist['data_obs'].GetMarkerSize())
res_graph = data_graph.Clone()
for i in range(hist['data_obs'].GetNbinsX()):
N = hist['data_obs'].GetBinContent(i + 1)
B = hist['BkgSum'].GetBinContent(i + 1)
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
data_graph.SetPoint(i, hist['data_obs'].GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
data_graph.SetPointError(
i, hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2., N - L, U - N)
res_graph.SetPoint(i, hist['data_obs'].GetXaxis().GetBinCenter(i + 1),
N / B if not B == 0 and not N == 0 else -1.e99)
res_graph.SetPointError(
i, hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
hist['data_obs'].GetXaxis().GetBinWidth(i + 1) / 2.,
(N - L) / B if not B == 0 else -1.e99,
(U - N) / B if not B == 0 else -1.e99)
# Create stack
bkg = THStack("Bkg",
";" + hist['BkgSum'].GetXaxis().GetTitle() + ";Events")
for i, s in enumerate(back):
bkg.Add(hist[s])
# Legend
n = len([x for x in data + back + ['BkgSum'] + sign if sample[x]['plot']])
leg = TLegend(0.7, 0.9 - 0.05 * n, 0.95, 0.9)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
if len(data) > 0:
leg.AddEntry(hist[data[0]], sample[data[0]]['label'], "pl")
for i, s in reversed(list(enumerate(['BkgSum'] + back))):
leg.AddEntry(hist[s], sample[s]['label'], "f")
for i, s in enumerate(sign):
if sample[s]['plot']:
leg.AddEntry(hist[s],
sample[s]['label'].replace("m_{#Chi}=1 GeV",
""), "fl")
# --- Display ---
c1 = TCanvas("c1",
hist.values()[0].GetXaxis().GetTitle(), 800,
800 if ratio else 600)
if ratio:
c1.Divide(1, 2)
setTopPad(c1.GetPad(1), ratio)
setBotPad(c1.GetPad(2), ratio)
c1.cd(1)
c1.GetPad(bool(ratio)).SetTopMargin(0.06)
c1.GetPad(bool(ratio)).SetRightMargin(0.05)
c1.GetPad(bool(ratio)).SetTicks(1, 1)
if log:
c1.GetPad(bool(ratio)).SetLogy()
# Draw
bkg.Draw("HIST") # stack
hist['BkgSum'].Draw("SAME, E2") # sum of bkg
#if len(data) > 0: hist['data_obs'].Draw("SAME, PE") # data
data_graph.Draw("SAME, PE")
for i, s in enumerate(sign):
if sample[s]['plot']:
hist[s].DrawNormalized("SAME, HIST",
hist[s].Integral() * snorm) # signals
bkg.GetYaxis().SetTitleOffset(bkg.GetYaxis().GetTitleOffset() * 1.075)
bkg.SetMaximum((2. if log else 1.2) * max(
bkg.GetMaximum(),
hist['data_obs'].GetBinContent(hist['data_obs'].GetMaximumBin()) +
hist['data_obs'].GetBinError(hist['data_obs'].GetMaximumBin())))
bkg.SetMinimum(
max(
min(hist['BkgSum'].GetBinContent(hist['BkgSum'].GetMinimumBin(
)), hist['data_obs'].GetMinimum()), 5.e-1) if log else 0.)
if log:
bkg.GetYaxis().SetNoExponent(bkg.GetMaximum() < 1.e4)
bkg.GetYaxis().SetMoreLogLabels(True)
#if log: bkg.SetMinimum(1)
leg.Draw()
drawCMS(lumi, "Preliminary")
drawRegion(channel)
drawAnalysis(channel)
#if nm1 and not cutValue is None: drawCut(cutValue, bkg.GetMinimum(), bkg.GetMaximum()) #FIXME
if len(sign) > 0:
if channel.startswith('X') and len(sign) > 0:
drawNorm(0.9 - 0.04 * (n + 1),
"#sigma(X) #times B(X #rightarrow Vh) = %.1f pb" % snorm)
#elif "SR" in channel: drawNorm(0.9-0.04*(n+1), "DM+bb/tt, scaled by %.0f" % snorm, "m_{#chi}=1 GeV, scalar mediator")
elif "SR" in channel:
drawNorm(0.9 - 0.04 * (n + 1), "DM+bb/tt, m_{#chi}=1 GeV",
"scalar mediator")
setHistStyle(bkg, 1.2 if ratio else 1.1)
setHistStyle(hist['BkgSum'], 1.2 if ratio else 1.1)
if ratio:
c1.cd(2)
err = hist['BkgSum'].Clone("BkgErr;")
err.SetTitle("")
err.GetYaxis().SetTitle("Data / Bkg")
for i in range(1, err.GetNbinsX() + 1):
err.SetBinContent(i, 1)
if hist['BkgSum'].GetBinContent(i) > 0:
err.SetBinError(
i, hist['BkgSum'].GetBinError(i) /
hist['BkgSum'].GetBinContent(i))
setBotStyle(err)
errLine = err.Clone("errLine")
errLine.SetLineWidth(1)
errLine.SetFillStyle(0)
res = hist['data_obs'].Clone("Residues")
for i in range(0, res.GetNbinsX() + 1):
if hist['BkgSum'].GetBinContent(i) > 0:
res.SetBinContent(
i,
res.GetBinContent(i) / hist['BkgSum'].GetBinContent(i))
res.SetBinError(
i,
res.GetBinError(i) / hist['BkgSum'].GetBinContent(i))
setBotStyle(res)
#err.GetXaxis().SetLabelOffset(err.GetXaxis().GetLabelOffset()*5)
#err.GetXaxis().SetTitleOffset(err.GetXaxis().GetTitleOffset()*2)
err.Draw("E2")
errLine.Draw("SAME, HIST")
if len(data) > 0:
#res.Draw("SAME, PE0")
res_graph.Draw("SAME, PE0")
# if len(err.GetXaxis().GetBinLabel(1))==0: # Bin labels: not a ordinary plot
# drawRatio(hist['data_obs'], hist['BkgSum'])
# drawKolmogorov(hist['data_obs'], hist['BkgSum'])
c1.Update()
# return list of objects created by the draw() function
return [c1, bkg, leg, err, errLine, res, data_graph, res_graph]
def getGraph(self,dset):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
lst = []
for inc in range (0,n):
d={}
d['run']=self.__runs[inc]
d['x']=self.__x[inc]
d['y']=self.__y[inc]
d['yErr']=self.__yErrLow[inc]
d['yTitle']=self.__yTitle
if self.__config.has_option(self.__section,"yMin") and self.__config.has_option(self.__section,"yMax") :
d['ymin']=float(self.__config.get(self.__section,"yMin"))
d['ymax']=float(self.__config.get(self.__section,"yMax"))
else:
d['ymin']=0
d['ymax']=0
lst.append(d)
obj ={}
obj[self.__title]=lst
#finalObj[self.__title]=lst
#finalList.append(finalObj)
# save_path = './JSON_A/'
#completeName = os.path.join(save_path, self.__title+".json")
if not os.path.exists("JSON_RECO"):
os.makedirs("JSON_RECO")
if not os.path.exists("JSON_RECO/"+dset):
os.makedirs("JSON_RECO/"+dset)
with open("./JSON_RECO/"+dset+"/"+self.__title+".json", 'w') as outfile:
json.dump(obj, outfile,indent=4)
print json.dumps(obj,indent=2)
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__ySysErrLow,self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
#TOMAS removed sys error from the plot
#result.Add(sysGraph,"[]")
result.Add(graph,"P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s"%(self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
ey_hi_mu = grMu.GetErrorYhigh(i)
ey_hi_ele = grEle.GetErrorYhigh(i)
if y_mu < 1.e-9 or y_ele < 1.e-9:
ey_hi_ratio = 0.0
else:
ey_hi_ratio = y_ratio * math.hypot(ey_hi_mu / y_mu, ey_hi_ele / y_ele)
grRatio.SetPoint(i, x, y_ratio)
grRatio.SetPointEXlow(i, ex_lo)
grRatio.SetPointEXhigh(i, ex_hi)
grRatio.SetPointEYlow(i, ey_lo_ratio)
grRatio.SetPointEYhigh(i, ey_hi_ratio)
if True:
grRatio.SetMarkerStyle(20)
grRatio.SetMarkerSize(1.5)
grRatio.SetMarkerColor(1)
grRatio.SetLineStyle(1)
grRatio.SetLineColor(1)
grRatio.SetLineWidth(1)
grRatio.GetXaxis().SetLabelSize(0.04)
grRatio.GetXaxis().SetTitleSize(0.04)
grRatio.GetXaxis().SetTitleOffset(1.25)
grRatio.GetYaxis().SetLabelSize(0.04)
grRatio.GetYaxis().SetTitleSize(0.04)
grRatio.GetYaxis().SetTitleOffset(1.5)
# grRatio.GetYaxis().SetRangeUser(ylo, yhi)
emtf2026_rate_err))
print rates
gr_denom = TGraphAsymmErrors(len(rates))
gr_numer = TGraphAsymmErrors(len(rates))
for i, x in enumerate(rates):
pu, emtf_rate, emtf_rate_err, emtf2026_rate, emtf2026_rate_err = x
gr_denom.SetPoint(i, pu, emtf_rate)
gr_denom.SetPointError(i, 0, 0, emtf_rate_err, emtf_rate_err)
gr_numer.SetPoint(i, pu, emtf2026_rate)
gr_numer.SetPointError(i, 0, 0, emtf2026_rate_err, emtf2026_rate_err)
gr_denom.SetMarkerStyle(20)
gr_denom.SetMarkerSize(1.4)
gr_denom.SetMarkerColor(632) # kRed
gr_denom.SetLineWidth(2)
gr_denom.SetLineColor(632) # kRed
gr_numer.SetMarkerStyle(20)
gr_numer.SetMarkerSize(1.4)
gr_numer.SetMarkerColor(600) # kBlue
gr_numer.SetLineWidth(2)
gr_numer.SetLineColor(600) # kBlue
frame = TH1F("frame", "; PU; Trigger rate [kHz]", 100, 0, 350)
frame.SetMinimum(0)
frame.SetMaximum(25)
frame.Draw()
def draw_geff(target_dir,
c_title,
ext,
t,
title,
h_name,
h_bins,
to_draw,
denom_cut,
extra_num_cut,
opt,
color,
marker_st=1,
marker_sz=1):
c = TCanvas("c", "c", 600, 600)
c.Clear()
gPad.SetGrid(1)
gStyle.SetStatStyle(0)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
t.Draw(to_draw + ">>num_" + h_name + h_bins, extra_num_cut + denom_cut,
"goff")
num = TH1F(gDirectory.Get("num_" + h_name))
if not num:
sys.exit('num does not exist')
num = TH1F(num.Clone("eff_" + h_name))
t.Draw(to_draw + ">>denom_" + h_name + h_bins, denom_cut, "goff")
den = TH1F(gDirectory.Get("denom_" + h_name).Clone("denom_" + h_name))
eff = TGraphAsymmErrors(num, den)
if not "same" in opt:
num.Reset()
num.GetYaxis().SetRangeUser(0., 1.05)
num.SetStats(0)
num.SetTitle(title)
num.Draw()
eff.SetLineWidth(2)
eff.SetLineColor(color)
eff.SetMarkerStyle(marker_st)
eff.SetMarkerColor(color)
eff.SetMarkerSize(marker_sz)
eff.Draw(opt + " same")
## Do fit in the flat region
if "eta" in c_title:
xmin = eta_min
xmax = eta_max
else:
xmin = -999.
xmax = 999.
f1 = TF1("fit1", "pol0", xmin, xmax)
r = eff.Fit("fit1", "RQS")
ptstats = TPaveStats(0.25, 0.35, 0.75, 0.55, "brNDC")
ptstats.SetName("stats")
ptstats.SetBorderSize(0)
ptstats.SetLineWidth(0)
ptstats.SetFillColor(0)
ptstats.SetTextAlign(11)
ptstats.SetTextFont(42)
ptstats.SetTextSize(.05)
ptstats.SetTextColor(kRed)
ptstats.SetOptStat(0)
ptstats.SetOptFit(1111)
chi2 = int(r.Chi2())
ndf = int(r.Ndf())
## prob = r.Prob()
round(2.675, 2)
p0 = f1.GetParameter(0)
p0e = f1.GetParError(0)
ptstats.AddText("#chi^{2} / ndf: %d/%d" % (chi2, ndf))
## ptstats.AddText("Fit probability: %f %" %(prob))
ptstats.AddText("Efficiency: %f #pm %f %%" % (p0, p0e))
ptstats.Draw("same")
pt = TPaveText(0.09899329, 0.9178322, 0.8993289, 0.9737762, "blNDC")
pt.SetName("title")
pt.SetBorderSize(1)
pt.SetFillColor(0)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.AddText(eff.GetTitle())
pt.Draw("same")
c.Modified()
c.SaveAs(target_dir + c_title + ext)
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...")
##Prepare the canvas to plot the HV scan for SL1_L1
can_HV_scan_SL1_L1 = TCanvas("can_HV_scan_SL1_L1", "can_HV_scan_SL1_L1", 1000,
800)
can_HV_scan_SL1_L1.SetGrid()
can_HV_scan_SL1_L1.cd()
##Prepare summary TGraph
graph_HV_L1 = TGraphAsymmErrors()
n = 0
for a in sorted(HV_scan_L1):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph_HV_L1.SetPoint(n, int(a), float(HV_scan_L1[a]))
n = n + 1
graph_HV_L1.SetMarkerSize(1.)
graph_HV_L1.SetMarkerStyle(21)
graph_HV_L1.SetMarkerColor(418)
graph_HV_L1.SetFillColor(868)
graph_HV_L1.SetFillStyle(3844)
graph_HV_L1.SetLineColor(418 - 1)
graph_HV_L1.SetLineWidth(2)
graph_HV_L1.SetLineStyle(2)
graph_HV_L1.GetXaxis().SetTitle("HV [V]")
graph_HV_L1.GetYaxis().SetTitleOffset(1.2)
graph_HV_L1.GetYaxis().SetTitle("efficiency")
graph_HV_L1.GetYaxis().SetRangeUser(0, 1.01)
graph_HV_L1.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
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 nuisance_plot(input_file_, orien_, sticker_, oname_):
pars = get_parameters_from_file(input_file_)
#adjust_parameters(pars)
N = len(pars)
g68 = TGraph(2 * N + 7)
g95 = TGraph(2 * N + 7)
gPR = TGraphAsymmErrors(N)
for i in range(0, N):
x = pars[i].value
y = i + 1.5
xerr = pars[i].error
yerr = 0.
if orien_ == 'h':
x, y = y, x
xerr, yerr = yerr, xerr
gPR.SetPoint(i, x, y)
gPR.SetPointEXlow(i, xerr)
gPR.SetPointEYlow(i, yerr)
gPR.SetPointEXhigh(i, xerr)
gPR.SetPointEYhigh(i, yerr)
for a in range(0, N + 3):
if orien_ == 'h':
g68.SetPoint(a, a, -1)
g95.SetPoint(a, a, -2)
g68.SetPoint(a + 1 + N + 2, N + 2 - a, 1)
g95.SetPoint(a + 1 + N + 2, N + 2 - a, 2)
else:
g68.SetPoint(a, -1, a)
g95.SetPoint(a, -2, a)
g68.SetPoint(a + 1 + N + 2, 1, N + 2 - a)
g95.SetPoint(a + 1 + N + 2, 2, N + 2 - a)
gPR.SetLineStyle(1)
gPR.SetLineWidth(1)
gPR.SetLineColor(1)
gPR.SetMarkerStyle(21)
gPR.SetMarkerSize(1.25)
g68.SetFillColor(kGreen)
g95.SetFillColor(kYellow)
if orien_ == 'h':
text_TL = TPaveText(0.100, 0.925, 0.440, 0.995, 'NDC')
text_TR = TPaveText(0.587, 0.925, 0.999, 0.993, 'NDC')
else:
text_TL = TPaveText(0.370, 0.945, 0.590, 0.995, 'NDC')
text_TR = TPaveText(0.600, 0.945, 0.995, 0.993, 'NDC')
text_TL.AddText(label_TL)
text_TL.SetFillColor(0)
text_TL.SetTextAlign(12)
text_TL.SetTextSize(0.06)
text_TL.SetTextFont(42)
text_TR.AddText(sticker_)
text_TR.SetFillColor(0)
text_TR.SetTextAlign(32)
text_TR.SetTextSize(0.05)
text_TR.SetTextFont(42)
if orien_ == 'h':
c = TCanvas('c', 'c', 1000, 700)
c.SetTopMargin(0.08)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.16)
c.SetLeftMargin(0.11)
else:
c = TCanvas('c', 'c', 700, 1000)
c.SetTopMargin(0.06)
c.SetRightMargin(0.02)
c.SetBottomMargin(0.12)
c.SetLeftMargin(0.35 * 700 / 650)
c.SetTickx()
c.SetTicky()
c.Update()
g95.Draw('AF')
g68.Draw('F')
gPR.Draw('P')
text_TL.Draw('same')
text_TR.Draw('same')
ax_1 = g95.GetHistogram().GetYaxis()
ax_2 = g95.GetHistogram().GetXaxis()
if orien_ == 'h': ax_1, ax_2 = ax_2, ax_1
ax_1.Set(N + 2, 0, N + 2)
ax_1.SetNdivisions(-414)
for i in range(0, N):
ax_1.SetBinLabel(i + 2, pars[i].name)
g95.SetTitle('')
ax_2.SetTitle('post-fit nuisance parameters values')
#ax_2.SetTitle('deviation in units of #sigma')
ax_1.SetTitleSize(0.050)
ax_2.SetTitleSize(0.050)
ax_1.SetTitleOffset(1.4)
ax_2.SetTitleOffset(1.0)
ax_1.SetLabelSize(0.05)
#ax_2.SetLabelSize(0.05)
ax_1.SetRangeUser(0, N + 2)
ax_2.SetRangeUser(-2.4, 2.4)
g95.GetHistogram().Draw('axis,same')
c.SaveAs(oname_ + '.pdf')
c.Close()
def ratioplot():
# create required parts
leg = getLegend()
latex = getLatex()
c = SetCanvas()
#c.SetLogy()
#c = TCanvas()
#c.SetLogy()
h1 = f.Get('h_num_calo_') #'calo',pf
h1 = setHistStyle(h1, bins)
h2 = f.Get('h_den_calo_')
h2 = setHistStyle(h2, bins)
h11 = f2.Get('h_num_calo_')
h11 = setHistStyle(h11, bins)
h21 = f2.Get('h_den_calo_')
h21 = setHistStyle(h21, bins)
gr = TGraphAsymmErrors(30)
#gr.Divide(h1,h2)
gr = TGraphAsymmErrors(h1, h2)
gr2 = TGraphAsymmErrors(h11, h21)
gr2.SetMarkerStyle(20)
gr2.GetXaxis().SetRangeUser(0, 1000)
gr2.SetMarkerSize(1.5)
gr2.SetLineColor(2)
gr2.SetLineWidth(1)
gr2.SetMarkerColor(2)
gr.GetXaxis().SetRangeUser(0, 1000)
# gr.GetYaxis().SetRangeUser(0.0001,1.2)
gr.SetMarkerStyle(20)
gr.SetMarkerSize(1.5)
gr.SetLineColor(1)
gr.SetLineWidth(1)
gr.SetMarkerColor(1)
gr.GetYaxis().SetTitle("Trigger Efficiency")
gr.GetXaxis().SetTitle("MET [GeV]")
gr.SetTitle("")
#base histogram
histogram_base = TH1F("histogram_base", "", 1000, 0, 1000.)
histogram_base.SetTitle("")
histogram_base.SetStats(0)
histogram_base.SetMarkerSize(2)
#histogram_base.SetMinimum(0.0)
histogram_base.SetMaximum(1.2)
histogram_base.GetXaxis().SetTitle("Online E_{T}^{miss} (GeV)")
histogram_base.GetYaxis().SetTitle("Efficiency")
histogram_base = setHistStyle(histogram_base, bins)
histogram_base.Draw("HIST")
# c.SaveAs()
gr.Draw('P same')
gr2.Draw('P same')
latex.DrawLatex(0.49, 0.93, " EGamma Run2018C, 13 TeV")
xmin = 0.0
line = TLine(max(xmin, gr.GetXaxis().GetXmin()), 1, 1000, 1)
line.SetLineColor(1)
line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw()
leg.AddEntry(gr, 'With HBHENoise filter', 'P')
leg.AddEntry(gr2, 'Without HBHENoise filter', 'P')
leg.Draw()
txt = 'Path: HLT_PFMETTypeOne200_HBHE_BeamHaloCleaned'
texcms = AddText(txt)
texcms.Draw("same")
c.SaveAs('testTurnOn_EGamma.png')
def makeplot_single(
h1_sig=None,
h1_bkg=None,
h1_data=None,
sig_legends_=None,
bkg_legends_=None,
sig_colors_=None,
bkg_colors_=None,
hist_name_=None,
sig_scale_=1.0,
dir_name_="plots",
output_name_=None,
extraoptions=None
):
if h1_sig == None or h1_bkg == None:
print("nothing to plot...")
return
os.system("mkdir -p "+dir_name_)
os.system("cp index.php "+dir_name_)
s_color = [632, 617, 839, 800, 1]
b_color = [920, 2007, 2005, 2003, 2001, 2011]
if sig_colors_:
s_color = sig_colors_
if bkg_colors_:
b_color = bkg_colors_
for idx in range(len(h1_sig)):
h1_sig[idx].SetLineWidth(3)
h1_sig[idx].SetLineColor(s_color[idx])
for idx in range(len(h1_bkg)):
h1_bkg[idx].SetLineWidth(2)
h1_bkg[idx].SetLineColor(b_color[idx])
h1_bkg[idx].SetFillColorAlpha(b_color[idx], 1)
if h1_data:
h1_data.SetBinErrorOption(1)
h1_data.SetLineColor(1)
h1_data.SetLineWidth(2)
h1_data.SetMarkerColor(1)
h1_data.SetMarkerStyle(20)
myC = r.TCanvas("myC","myC", 600, 600)
myC.SetTicky(1)
pad1 = r.TPad("pad1","pad1", 0.05, 0.33,0.95, 0.97)
pad1.SetBottomMargin(0.027)
pad1.SetRightMargin( rightMargin )
pad1.SetLeftMargin( leftMargin )
pad2 = r.TPad("pad2","pad2", 0.05, 0.04, 0.95, 0.31)
pad2.SetBottomMargin(0.4)
pad2.SetTopMargin(0.05)
pad2.SetRightMargin( rightMargin )
pad2.SetLeftMargin( leftMargin )
pad2.Draw()
pad1.Draw()
pad1.cd()
for idx in range(len(h1_sig)):
print("before signal scaling",h1_sig[idx].Integral())
h1_sig[idx].Scale(sig_scale_)
print("after signal scaling",h1_sig[idx].Integral())
stack = r.THStack("stack", "stack")
nS = np.zeros(h1_bkg[0].GetNbinsX())
eS = np.zeros(h1_bkg[0].GetNbinsX())
#hist_all is used to make the data/mc ratio. remove signal for the moment due to signal is scaled right now
hist_all = h1_sig[0].Clone("hist_all")
hist_all.Scale(0.0)
hist_s = h1_sig[0].Clone("hist_s")
hist_b = h1_bkg[0].Clone("hist_b")
for idx in range(len(h1_bkg)):
stack.Add(h1_bkg[idx])
for ib in range(h1_bkg[0].GetNbinsX()):
nS[ib] += h1_bkg[idx].GetBinContent(ib+1)
eS[ib] = math.sqrt(eS[ib]*eS[ib] + h1_bkg[idx].GetBinError(ib+1)*h1_bkg[idx].GetBinError(ib+1))
hist_all.Add(h1_bkg[idx])
if idx > 0:
hist_b.Add(h1_bkg[idx])
for idx in range(len(h1_sig)):
print("ggH signal yield: ", hist_s.Integral())
if idx > 0:
hist_temp = h1_sig[idx].Clone(h1_sig[idx].GetName()+"_temp")
#hist_all.Add(hist_temp)
hist_s.Add(h1_sig[idx])
print("all signal yield: ", hist_s.Integral())
stack.SetTitle("")
maxY = 0.0
if "stack_signal" in extraoptions and extraoptions["stack_signal"]:
for idx in range(len(h1_sig)):
h1_sig[idx].SetFillColorAlpha(s_color[idx], 1)
stack.Add(h1_sig[idx])
for ib in range(h1_bkg[0].GetNbinsX()):
nS[ib] += h1_sig[idx].GetBinContent(ib+1)
eS[ib] = math.sqrt(eS[ib]*eS[ib] + h1_sig[idx].GetBinError(ib+1)*h1_sig[idx].GetBinError(ib+1))
if stack.GetMaximum() > maxY:
maxY = stack.GetMaximum()
#if "SR" in h.GetTitle():
stack.Draw("hist")
else:
stack.Draw("hist")
if stack.GetMaximum() > maxY:
maxY = stack.GetMaximum()
for idx in range(len(h1_sig)):
if h1_sig[idx].GetMaximum() > maxY:
maxY = h1_sig[idx].GetMaximum()
if "SR" in h1_bkg[0].GetTitle():
#h1_sig[idx].Draw("samehist")
hist_s.Draw("samehist")
##draw stack total unc on top of total histogram
box = r.TBox(0,0,1,1,)
box.SetFillStyle(3002)
box.SetLineWidth(0)
box.SetFillColor(r.kBlack)
for idx in range(h1_bkg[0].GetNbinsX()):
box.DrawBox(h1_bkg[0].GetBinCenter(idx+1)-0.5*h1_bkg[0].GetBinWidth(idx+1), nS[idx]-eS[idx], h1_bkg[0].GetBinCenter(idx+1)+0.5*h1_bkg[0].GetBinWidth(idx+1), nS[idx]+eS[idx])
if h1_data:
if h1_data.GetMaximum() > maxY:
maxY = h1_data.GetMaximum()+np.sqrt(h1_data.GetMaximum())
#if not "SR" in h1_data.GetTitle() or "fail" in h1_data.GetTitle():
if True:
#print("debug h1_data.GetName()",h1_data.GetName(), h1_data.GetTitle())
TGraph_data = TGraphAsymmErrors(h1_data)
for i in range(TGraph_data.GetN()):
#data point
var_x, var_y = Double(0.), Double(0.)
TGraph_data.GetPoint(i,var_x,var_y)
if np.fabs(var_y) < 1e-5:
TGraph_data.SetPoint(i,var_x,-1.0)
TGraph_data.SetPointEYlow(i,-1)
TGraph_data.SetPointEYhigh(i,-1)
#print("zero bins in the data TGraph: bin",i+1)
else:
TGraph_data.SetPoint(i,var_x,var_y)
err_low = var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y))
TGraph_data.SetPointEYlow(i, var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y)))
TGraph_data.SetPointEYhigh(i, (0.5*TMath.ChisquareQuantile(1.-0.1586555,2.*(var_y+1))) - var_y)
TGraph_data.SetMarkerColor(1)
TGraph_data.SetMarkerSize(1)
TGraph_data.SetMarkerStyle(20)
TGraph_data.Draw("same P")
stack.GetYaxis().SetTitle("Events")
stack.GetYaxis().SetTitleOffset(1.05)
stack.GetYaxis().SetTitleSize(0.08)
stack.GetYaxis().SetLabelSize(0.06)
#stack.GetYaxis().CenterTitle()
stack.GetXaxis().SetLabelSize(0.)
#stack.GetXaxis().SetLabelOffset(0.013)
#if "xaxis_range" in extraoptions:
# stack.GetXaxis().SetRangeUser(float(extraoptions["xaxis_range"][0]),float(extraoptions["xaxis_range"][1]))
leg = r.TLegend(0.2, 0.60, 0.9, 0.88)
leg.SetNColumns(3)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
for idx in range(len(h1_bkg)):
leg.AddEntry(h1_bkg[idx], bkg_legends_[idx], "F")
if "SR" in hist_s.GetTitle():
leg.AddEntry(hist_s, 'HH #times {:1.2}'.format(sig_scale_), "L")
leg.AddEntry(box, "Total unc", "F")
if h1_data:
leg.AddEntry(h1_data, "Data", "ep")
leg.Draw()
pad2.cd()
pad2.SetGridy(1)
ratio = None
ratio_Low = 0.0
ratio_High = 4
if h1_data:
ratio = TGraphAsymmErrors(h1_data)
for i in range(ratio.GetN()):
#bkg prediction
imc = Double(hist_all.GetBinContent(i+1))
#data point
var_x, var_y = Double(0.), Double(0.)
if not ("SR" in h1_data.GetTitle() and (i>5 and i<9)):
ratio.GetPoint(i,var_x,var_y)
if var_y == 0.:
ratio.SetPoint(i,var_x,-1.0)
ratio.SetPointEYlow(i,-1)
ratio.SetPointEYhigh(i,-1)
continue
ratio.SetPoint(i,var_x,var_y/imc)
err_low = (var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y)))/imc
err_high = ((0.5*TMath.ChisquareQuantile(1.-0.1586555,2.*(var_y+1))) - var_y)/imc
ratio.SetPointEYlow(i, err_low)
ratio.SetPointEYhigh(i, err_high)
ratio.SetMarkerColor(1)
ratio.SetMarkerSize(1)
ratio.SetMarkerStyle(20)
ratio.GetXaxis().SetTitle("j_{2} regressed mass [GeV]")
#myC.Update()
if "ratio_range" in extraoptions:
ratio_Low = extraoptions["ratio_range"][0]
ratio_High = extraoptions["ratio_range"][1]
ratio.GetYaxis().SetTitle("data/mc")
ratio.GetYaxis().SetRangeUser(ratio_Low, ratio_High)
ratio.GetXaxis().SetRangeUser(50, 220)
ratio.SetTitle("")
ratio.Draw("same AP")
pad2.Update()
print(ratio.GetTitle(),ratio.GetName(),"debug")
else:
ratio = h1_sig[0].Clone("ratio")
ratio_High = 0.0
for ibin in range(1,ratio.GetNbinsX()+1):
s = hist_s.GetBinContent(ibin)
b = hist_b.GetBinContent(ibin)
L = 0.0
if b > 0.0:
L = s/math.sqrt(b)
if L > ratio_High:
ratio_High = L
ratio.SetBinContent(ibin, L)
if ratio_High > 1.0:
ratio_High = 1.0
ratio.GetYaxis().SetRangeUser(ratio_Low, ratio_High*1.2)
ratio.GetYaxis().SetTitle("S/#sqrt{B}")
ratio.Draw("samehist")
ratio.SetLineColor(1)
ratio.SetLineWidth(2)
ratio.SetMarkerStyle(20)
ratio.SetMarkerColor(1)
ratio.SetFillColorAlpha(1, 0)
ratio.GetXaxis().SetTitleOffset(0.94)
ratio.GetXaxis().SetTitleSize(0.18)
ratio.GetXaxis().SetLabelSize(0.12)
ratio.GetXaxis().SetLabelOffset(0.013)
ratio.GetYaxis().SetTitleOffset(0.40)
ratio.GetYaxis().SetTitleSize(0.17)
ratio.GetYaxis().SetLabelSize(0.13)
ratio.GetYaxis().SetTickLength(0.01)
ratio.GetYaxis().SetNdivisions(505)
#if "xaxis_range" in extraoptions:
# ratio.GetXaxis().SetRangeUser(float(extraoptions["xaxis_range"][0]),float(extraoptions["xaxis_range"][1]))
#draw stack total unc on the ratio plot to present the background uncertainty
box_ratio = r.TBox(0,0,1,1,)
box_ratio.SetFillStyle(3002)
box_ratio.SetLineWidth(0)
box_ratio.SetFillColor(r.kBlack)
for idx in range(h1_bkg[0].GetNbinsX()):
if np.fabs(nS[idx])> 1e-06:
box_ratio.DrawBox(h1_bkg[0].GetBinCenter(idx+1)-0.5*h1_bkg[0].GetBinWidth(idx+1), (nS[idx]-eS[idx])/nS[idx], h1_bkg[0].GetBinCenter(idx+1)+0.5*h1_bkg[0].GetBinWidth(idx+1), (nS[idx]+eS[idx])/nS[idx])
else:
print("blinded Higgs peak region")
if "xaxis_label" in extraoptions and extraoptions["xaxis_label"] != None:
x_title = extraoptions["xaxis_label"]
ratio.GetXaxis().SetTitle(x_title)
ratio.GetYaxis().CenterTitle()
##########draw CMS preliminary
pad1.cd()
tex1 = r.TLatex(leftMargin, 0.91, "CMS")
tex1.SetNDC()
tex1.SetTextFont(61)
tex1.SetTextSize(0.070)
tex1.SetLineWidth(2)
tex1.Draw()
tex2 = r.TLatex(leftMargin+0.12,0.912,"Internal")
tex2.SetNDC()
tex2.SetTextFont(52)
tex2.SetTextSize(0.055)
tex2.SetLineWidth(2)
tex2.Draw()
lumi_value = 137
if "lumi_value" in extraoptions:
lumi_value = extraoptions["lumi_value"]
tex3 = r.TLatex(0.72,0.912,"%d"%lumi_value+" fb^{-1} (13 TeV)")
tex3.SetNDC()
tex3.SetTextFont(42)
tex3.SetTextSize(0.055)
tex3.SetLineWidth(2)
tex3.Draw()
outFile = dir_name_
if output_name_:
outFile = outFile + "/" +output_name_
else:
outFile = outFile + "/" + hist_name_
#print("maxY = "+str(maxY))
stack.SetMaximum(maxY*1.7)
#print everything into txt file
text_file = open(outFile+"_linY.txt", "w")
text_file.write("bin | x ")
for idx in range(len(h1_bkg)):
text_file.write(" | %21s"%bkg_legends_[idx])
text_file.write(" | %21s"%("total B"))
for idx in range(len(sig_legends_)):
text_file.write(" | %25s"%sig_legends_[idx])
if h1_data:
text_file.write(" | data | data/mc")
text_file.write("\n-------------")
for idx in range(24*(len(h1_bkg) + 1)+ 29*len(sig_legends_)):
text_file.write("-")
if h1_data:
text_file.write("-------")
text_file.write("\n")
for ibin in range(0,h1_sig[0].GetNbinsX()+1):
text_file.write("%3d"%ibin+" ")
text_file.write(" | %6.3f"%h1_data.GetBinCenter(ibin)+" ")
for idx in range(len(h1_bkg)):
text_file.write(" | %7.3f "%h1_bkg[idx].GetBinContent(ibin)+"$\\pm$"+ " %7.3f"%h1_bkg[idx].GetBinError(ibin))
text_file.write(" | %7.3f "%hist_b.GetBinContent(ibin)+"$\\pm$"+ " %7.3f"%hist_b.GetBinError(ibin))
for idx in range(len(sig_legends_)):
text_file.write(" | %9.3f "%h1_sig[idx].GetBinContent(ibin)+"$\\pm$"+ " %9.3f"%h1_sig[idx].GetBinError(ibin))
if h1_data:
text_file.write(" | %d"%h1_data.GetBinContent(ibin) + " | %7.3f "%h1_data.GetBinContent(ibin) +"$\\pm$"+ " %7.3f"%h1_data.GetBinError(ibin))
text_file.write("\n\n")
#print yield table for AN
text_file.write("print yield table for AN\n")
bkg_all = 0
bkg_all_errsq = 0
for idx in range(len(h1_bkg)):
bkg_tmp = h1_bkg[idx].GetBinContent(7)+h1_bkg[idx].GetBinContent(8)+h1_bkg[idx].GetBinContent(9)
bkg_errsq_tmp = h1_bkg[idx].GetBinError(7)*h1_bkg[idx].GetBinError(7)+h1_bkg[idx].GetBinError(8)*h1_bkg[idx].GetBinError(8)+h1_bkg[idx].GetBinError(9)*h1_bkg[idx].GetBinError(9)
bkg_all += bkg_tmp
bkg_all_errsq += bkg_errsq_tmp
text_file.write("%s"%(bkg_legends_[idx])+"& %7.2f"%(bkg_tmp)+"$\\pm$"+ "%7.2f"%np.sqrt(bkg_errsq_tmp)+"\n")
text_file.write("total background & %7.2f"%(bkg_all)+"$\\pm$"+ "%7.2f"%np.sqrt(bkg_all_errsq)+"\n")
text_file.write("\ggHH SM ($\kapl=1$) & %7.2f"%((h1_sig[0].GetBinContent(7)+h1_sig[0].GetBinContent(8)+h1_sig[0].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.1f"%(sig_scale_*np.sqrt(h1_sig[0].GetBinError(7)*h1_sig[0].GetBinError(7)+h1_sig[0].GetBinError(8)*h1_sig[0].GetBinError(8)+h1_sig[0].GetBinError(9)*h1_sig[0].GetBinError(9)))+"\n")
text_file.write("\VBFHH SM ($\kapl=1$) & %7.2f"%((h1_sig[1].GetBinContent(7)+h1_sig[1].GetBinContent(8)+h1_sig[1].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.1f"%(sig_scale_*np.sqrt(h1_sig[1].GetBinError(7)*h1_sig[1].GetBinError(7)+h1_sig[1].GetBinError(8)*h1_sig[1].GetBinError(8)+h1_sig[1].GetBinError(9)*h1_sig[1].GetBinError(9)))+"\n")
text_file.write("HH bin 8 value %s"%h1_sig[0].GetBinContent(8)+"\n")
text_file.write("HH bin 9 value %s"%h1_sig[0].GetBinContent(9)+"\n")
text_file.write("HH bin 7 value %s"%h1_sig[0].GetBinContent(7)+"\n")
text_file.write("HH bin 8 error %s"%h1_sig[0].GetBinError(8)+"\n")
text_file.write("HH bin 9 error %s"%h1_sig[0].GetBinError(9)+"\n")
text_file.write("HH bin 7 error %s"%h1_sig[0].GetBinError(7)+"\n")
text_file.write("total & %7.2f"%(bkg_all+(h1_sig[0].GetBinContent(7)+h1_sig[0].GetBinContent(8)+h1_sig[0].GetBinContent(9)+h1_sig[1].GetBinContent(7)+h1_sig[1].GetBinContent(8)+h1_sig[1].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.2f"%(np.sqrt((h1_sig[0].GetBinError(7)*h1_sig[0].GetBinError(7)+h1_sig[0].GetBinError(8)*h1_sig[0].GetBinError(8)+h1_sig[0].GetBinError(9)*h1_sig[0].GetBinError(9))/(sig_scale_*sig_scale_)+(h1_sig[1].GetBinError(7)*h1_sig[1].GetBinError(7)+h1_sig[1].GetBinError(8)*h1_sig[1].GetBinError(8)+h1_sig[1].GetBinError(9)*h1_sig[1].GetBinError(9))/(sig_scale_*sig_scale_)+bkg_all_errsq))+"\n")
text_file.close()
os.system("cp "+outFile+"_linY.txt "+outFile+"_logY.txt")
pad1.RedrawAxis()
myC.SaveAs(outFile+"_linY.png")
myC.SaveAs(outFile+"_linY.pdf")
myC.SaveAs(outFile+"_linY.C")
pad1.cd()
stack.SetMaximum(maxY*100.0)
stack.SetMinimum(0.5)
pad1.SetLogy()
pad1.RedrawAxis()
myC.SaveAs(outFile+"_logY.png")
myC.SaveAs(outFile+"_logY.pdf")
myC.SaveAs(outFile+"_logY.C")
#save histogram and ratio to root file
outFile_root = r.TFile(outFile+".root", "recreate")
outFile_root.cd()
for idx in range(len(h1_bkg)):
h1_bkg[idx].Write()
for idx in range(len(sig_legends_)):
h1_sig[idx].Write()
if h1_data:
h1_data.Write()
ratio.Write()
#outFile_root.Write()
outFile_root.Close()
