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 draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig, lower1sig, upper2sig, lower2sig): channel = np.array( [3. * nchannels - 1.5 - 3. * i for i in range(0, nchannels)]) ey = np.array([0.8 for i in range(0, nchannels)]) zero = np.zeros(nchannels) gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig, upper1sig, ey, ey) gexpect1sig.SetFillColor(kGreen) gexpect1sig.SetLineWidth(2) gexpect1sig.SetLineStyle(2) gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig, upper2sig, ey, ey) gexpect2sig.SetFillColor(kYellow) gexpect2sig.SetLineWidth(2) gexpect2sig.SetLineStyle(2) gexpect2sig.Draw("2") gexpect1sig.Draw("2") gobs = TGraphErrors(nchannels, obs, channel, zero, ey) gobs.SetMarkerStyle(21) gobs.SetMarkerSize(1.5) gobs.SetLineWidth(2) gobs.Draw("pz") # dashed line at median expected limits l = TLine() l.SetLineStyle(2) l.SetLineWidth(2) for bin in range(nchannels): l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin], channel[bin] + ey[bin]) # line to separate individual and combined limits l.SetLineStyle(1) l.SetLineWidth(1) l.DrawLine(xmin, 0, xmax, 0) # legend x1 = gStyle.GetPadLeftMargin() + 0.01 y2 = 1 - gStyle.GetPadTopMargin() - 0.01 leg = TLegend(x1, y2 - 0.17, x1 + 0.25, y2) leg.SetFillColor(4000) leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL") leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL") leg.AddEntry(gobs, "Observed", "pl") leg.Draw() return gobs, gexpect1sig, gexpect2sig, leg
def draw_limits_per_category(nchannels, xmin, xmax, obs, expect, upper1sig, lower1sig, upper2sig, lower2sig): channel = np.array( [nchannels - 1.5 - float(i) for i in range(0, nchannels)]) ey = np.full(nchannels, 0.494) zero = np.zeros(nchannels) gexpect1sig = TGraphAsymmErrors(nchannels, expect, channel, lower1sig, upper1sig, ey, ey) gexpect1sig.SetFillColor(kGreen) gexpect1sig.SetLineWidth(2) gexpect1sig.SetLineStyle(2) gexpect2sig = TGraphAsymmErrors(nchannels, expect, channel, lower2sig, upper2sig, ey, ey) gexpect2sig.SetFillColor(kYellow) gexpect2sig.SetLineWidth(2) gexpect2sig.SetLineStyle(2) gexpect2sig.Draw("2") gexpect1sig.Draw("2") gobs = TGraphErrors(nchannels, obs, channel, zero, ey) gobs.SetMarkerStyle(21) gobs.SetMarkerSize(1.5) gobs.SetLineWidth(2) #gobs.Draw("pz") # dashed line at median expected limits l = TLine() l.SetLineStyle(2) l.SetLineWidth(2) for bin in range(nchannels): l.DrawLine(expect[bin], channel[bin] - ey[bin], expect[bin], channel[bin] + ey[bin]) # line to separate individual and combined limits l.SetLineStyle(1) l.SetLineWidth(1) l.DrawLine(xmin, 0, xmax, 0) # legend leg = TLegend(0.75, 0.75, 0.95, 0.9) leg.SetFillColor(4000) leg.AddEntry(gexpect1sig, "Expected #pm1#sigma", "FL") leg.AddEntry(gexpect2sig, "Expected #pm2#sigma", "FL") #leg.AddEntry( gobs, "Observed", "pl" ) leg.Draw() return gobs, gexpect1sig, gexpect2sig, leg
def 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 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 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): 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
exh_c = np.array(LC_dict['tpr_e_h']) eyh_c = np.array(LC_dict['fpr_e_h']) # somehow if you call one of the variables before the Draw() method the graph won't work properly gr = GAE(n_bins, x, y, exl, exh, eyl, eyh) gr_s = GAE(n_bins, x, y, exl, exh, eyl, eyh) gr_LC = GAE(1, x_c, y_c, exl_c, exh_c, eyl_c, eyh_c) gr_c = gr.Clone() gr_sc = gr_s.Clone() gr.SetTitle('ROC(zoomed in)') #gr.SetMarkerColor(8) #gr.SetMarkerStyle(21) gr.SetFillColor(632 - 9) gr_s.SetTitle('ROC') gr_s.SetFillColor(632 - 9) gr_sc.SetLineColor(4) c1.cd(1) gr.GetXaxis().SetRangeUser(0, 0.5) gr.GetYaxis().SetRangeUser(0.00001, 0.01) gr_c.GetXaxis().SetRangeUser(0, 0.5) gr_c.GetXaxis().SetRangeUser(0.00001, 0.01) gr_LC.GetXaxis().SetRangeUser(0, 0.5) gr_LC.GetYaxis().SetRangeUser(0.00001, 0.01) gr_c.SetLineColor(4)
def limit(): method = '' channel = "bb" particleP = "Z'" particle = channel multF = ZPTOBB THEORY = ['A1', 'B3'] suffix = "_" + BTAGGING if ISMC: suffix += "_MC" if SY: suffix += "_comb" #if method=="cls": suffix="_CLs" if SY: filename = "./combine/limits/MANtag_study/" + BTAGGING + "/combined_run2/" + YEAR + "_M%d.txt" else: filename = "./combine/limits/MANtag_study/" + BTAGGING + "/" + YEAR + "_M%d.txt" if CATEGORY != "": filename = filename.replace( BTAGGING + "/", BTAGGING + "/single_category/" + CATEGORY + "_") suffix += "_" + CATEGORY if ISMC: filename = filename.replace(".txt", "_MC.txt") mass, val = fillValues(filename) #print "mass =",mass #print "val =", val Obs0s = TGraph() Exp0s = TGraph() Exp1s = TGraphAsymmErrors() Exp2s = TGraphAsymmErrors() Sign = TGraph() pVal = TGraph() Best = TGraphAsymmErrors() Theory = {} for i, m in enumerate(mass): if not m in val: print "Key Error:", m, "not in value map" continue n = Exp0s.GetN() Obs0s.SetPoint(n, m, val[m][0] * multF) Exp0s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF, val[m][4] * multF - val[m][3] * multF) Exp2s.SetPoint(n, m, val[m][3] * multF) Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF, val[m][5] * multF - val[m][3] * multF) if len(val[m]) > 6: Sign.SetPoint(n, m, val[m][6]) if len(val[m]) > 7: pVal.SetPoint(n, m, val[m][7]) if len(val[m]) > 8: Best.SetPoint(n, m, val[m][8]) if len(val[m]) > 10: Best.SetPointError(n, 0., 0., abs(val[m][9]), val[m][10]) for t in THEORY: Theory[t] = TGraphAsymmErrors() addXZH = True for m in sorted(HVT[t]['W']['XS'].keys()): if m < mass[0] or m > mass[-1]: continue if m > 4500: continue ## for now because I don't have the higher mass xs FIXME XsZ, XsZ_Up, XsZ_Down = 0., 0., 0. if addXZH: XsZ = 1000. * HVT[t]['Z']['XS'][ m] * 0.12 #temporary BR value set to 0.12 FIXME XsZ_Up = XsZ * (1. + math.hypot(HVT[t]['Z']['QCD'][m][0] - 1., HVT[t]['Z']['PDF'][m][0] - 1.)) XsZ_Down = XsZ * (1. - math.hypot(1. - HVT[t]['Z']['QCD'][m][0], 1. - HVT[t]['Z']['PDF'][m][0])) n = Theory[t].GetN() Theory[t].SetPoint(n, m, XsZ) Theory[t].SetPointError(n, 0., 0., (XsZ - XsZ_Down), (XsZ_Up - XsZ)) Theory[t].SetLineColor(theoryLineColor[t]) Theory[t].SetFillColor(theoryFillColor[t]) Theory[t].SetFillStyle(theoryFillStyle[t]) Theory[t].SetLineWidth(2) #Theory[t].SetLineStyle(7) Exp2s.SetLineWidth(2) Exp2s.SetLineStyle(1) Obs0s.SetLineWidth(3) Obs0s.SetMarkerStyle(0) Obs0s.SetLineColor(1) Exp0s.SetLineStyle(2) Exp0s.SetLineWidth(3) Exp1s.SetFillColor(417) #kGreen+1 Exp1s.SetLineColor(417) #kGreen+1 Exp2s.SetFillColor(800) #kOrange Exp2s.SetLineColor(800) #kOrange Exp2s.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25) Exp2s.GetXaxis().SetNoExponent(True) Exp2s.GetXaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetTitle("#sigma(" + particleP + ") #bf{#it{#Beta}}(" + particleP + " #rightarrow " + particle + ") (fb)") Exp2s.GetYaxis().SetTitleOffset(1.5) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetMoreLogLabels() Sign.SetLineWidth(2) Sign.SetLineColor(629) Sign.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1) Sign.GetYaxis().SetTitle("Significance") pVal.SetLineWidth(2) pVal.SetLineColor(629) pVal.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1) pVal.GetYaxis().SetTitle("local p-Value") Best.SetLineWidth(2) Best.SetLineColor(629) Best.SetFillColor(629) Best.SetFillStyle(3003) Best.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1) Best.GetYaxis().SetTitle("Best Fit (pb)") c1 = TCanvas("c1", "Exclusion Limits", 800, 600) c1.cd() #SetPad(c1.GetPad(0)) c1.GetPad(0).SetTopMargin(0.06) c1.GetPad(0).SetRightMargin(0.05) c1.GetPad(0).SetLeftMargin(0.12) c1.GetPad(0).SetTicks(1, 1) #c1.GetPad(0).SetGridx() #c1.GetPad(0).SetGridy() c1.GetPad(0).SetLogy() Exp2s.Draw("A3") Exp1s.Draw("SAME, 3") for t in THEORY: Theory[t].Draw("SAME, L3") Theory[t].Draw("SAME, L3X0Y0") Exp0s.Draw("SAME, L") if not options.blind: Obs0s.Draw("SAME, L") #setHistStyle(Exp2s) Exp2s.GetXaxis().SetTitleSize(0.050) Exp2s.GetYaxis().SetTitleSize(0.050) Exp2s.GetXaxis().SetLabelSize(0.045) Exp2s.GetYaxis().SetLabelSize(0.045) Exp2s.GetXaxis().SetTitleOffset(0.90) Exp2s.GetYaxis().SetTitleOffset(1.25) Exp2s.GetYaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetRangeUser(0.1, 5.e3) #else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2) #Exp2s.GetXaxis().SetRangeUser(mass[0], min(mass[-1], MAXIMUM[channel] if channel in MAXIMUM else 1.e6)) Exp2s.GetXaxis().SetRangeUser(SIGNALS[0], SIGNALS[-1]) #drawAnalysis(channel) drawAnalysis("") #drawRegion(channel, True) drawRegion("", True) #drawCMS(LUMI, "Simulation Preliminary") #Preliminary drawCMS(LUMI, "Work in Progress", suppressCMS=True) # legend top = 0.9 nitems = 4 + len(THEORY) leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.98, top) #leg = TLegend(0.45, top-nitems*0.3/5., 0.98, top) leg.SetBorderSize(0) leg.SetFillStyle(0) #1001 leg.SetFillColor(0) leg.SetHeader("95% CL upper limits") leg.AddEntry(Obs0s, "Observed", "l") leg.AddEntry(Exp0s, "Expected", "l") leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f") leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f") for t in THEORY: leg.AddEntry(Theory[t], theoryLabel[t], "fl") leg.Draw() latex = TLatex() latex.SetNDC() latex.SetTextSize(0.045) latex.SetTextFont(42) #latex.DrawLatex(0.66, leg.GetY1()-0.045, particleP+" #rightarrow "+particle+"h") leg2 = TLegend(0.12, 0.225 - 2 * 0.25 / 5., 0.65, 0.225) leg2.SetBorderSize(0) leg2.SetFillStyle(0) #1001 leg2.SetFillColor(0) c1.GetPad(0).RedrawAxis() leg2.Draw() if not options.blind: Obs0s.Draw("SAME, L") c1.GetPad(0).Update() if not gROOT.IsBatch(): raw_input("Press Enter to continue...") c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR + suffix + ".png") c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR + suffix + ".pdf") if 'ah' in channel or 'sl' in channel: c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR + suffix + ".C") c1.Print("combine/plotsLimit/ExclusionLimits/MANtag_study/" + YEAR + suffix + ".root") for t in THEORY: print "Model", t, ":", for m in range(mass[0], mass[-1], 1): if not (Theory[t].Eval(m) > Obs0s.Eval(m)) == ( Theory[t].Eval(m + 1) > Obs0s.Eval(m + 1)): print m, print "" return
def makePlot(finname,foutname,plottitle='',masstitle='',scale=False): xsecs = resonantXsecs if 'resonant' in finname else fcncXsecs points = {} if BLIND: cls = [2.5, 16, 50, 84, 97.5] else: cls = [2.5, 16, 50, 84, 97.5,'Observed'] xaxis = [] for cl in cls: points[cl] = [] xsec=1 for l in open(finname): try: if l.strip()[0]=='#': continue if 'MASS' in l: if scale: xsec = xsecs[int(l.split()[1])] if VERBOSE: print '' stdout.write('$%6s$ & $%7.3g$'%(l.split()[1],xsec/(0.667))) xaxis.append(float(l.split()[1])) else: cl,val = parseLine(l) points[cl].append(val/xsec) if VERBOSE and (cl==50 or cl=='Observed'): stdout.write(' & $%10.4g$'%(val/xsec)) except: pass if VERBOSE: print '' N = len(xaxis) up1Sigma=[]; up2Sigma=[] down1Sigma=[]; down2Sigma=[] for iM in xrange(N): up1Sigma.append(points[84][iM]-points[50][iM]) up2Sigma.append(points[97.5][iM]-points[50][iM]) down1Sigma.append(-points[16][iM]+points[50][iM]) down2Sigma.append(-points[2.5][iM]+points[50][iM]) up1Sigma = array('f',up1Sigma) up2Sigma = array('f',up2Sigma) down1Sigma = array('f',down1Sigma) down2Sigma = array('f',down2Sigma) cent = array('f',points[50]) if not BLIND: obs = array('f',points['Observed']) xarray = array('f',xaxis) xsecarray = array('f',[xsecs[xx] for xx in xaxis]) xsecarrayLow = array('f',[0.0625*xsecs[xx] for xx in xaxis]) onearray = array('f',[1 for xx in xaxis]) graphXsec = TGraph(N,xarray,xsecarray) graphXsecLow = TGraph(N,xarray,xsecarrayLow) graphOne = TGraph(N,xarray,onearray) zeros = array('f',[0 for i in xrange(N)]) graphCent = TGraph(N,xarray,cent) if not BLIND: graphObs = TGraph(N,xarray,obs) graph1Sigma = TGraphAsymmErrors(N,xarray,cent,zeros,zeros,down1Sigma,up1Sigma) graph2Sigma = TGraphAsymmErrors(N,xarray,cent,zeros,zeros,down2Sigma,up2Sigma) c = TCanvas('c','c',700,600) c.SetLogy() c.SetLeftMargin(.15) graph2Sigma.GetXaxis().SetTitle(masstitle+' [GeV]') if scale: graph2Sigma.GetYaxis().SetTitle('Upper limit [#sigma/#sigma_{theory}]') else: graph2Sigma.GetYaxis().SetTitle("Upper limit [#sigma] [pb]") graph2Sigma.SetLineColor(5) graph1Sigma.SetLineColor(3) graph2Sigma.SetFillColor(5) graph1Sigma.SetFillColor(3) graph2Sigma.SetMinimum(0.5*min(points[2.5])) if scale: graph2Sigma.SetMaximum(10*max(max(points[97.5]),max(xsecarray),4)) else: graph2Sigma.SetMaximum(10*max(max(points[97.5]),max(xsecarray))) graphCent.SetLineWidth(2) graphCent.SetLineStyle(2) if not BLIND: graphObs.SetLineColor(1) graphObs.SetLineWidth(3) graph1Sigma.SetLineStyle(0) graph2Sigma.SetLineStyle(0) leg = TLegend(0.55,0.7,0.9,0.9) leg.AddEntry(graphCent,'Expected','L') if not BLIND: leg.AddEntry(graphObs,'Observed','L') leg.AddEntry(graph1Sigma,'1 #sigma','F') leg.AddEntry(graph2Sigma,'2 #sigma','F') leg.SetFillStyle(0) leg.SetBorderSize(0) graph2Sigma.Draw('A3') graph1Sigma.Draw('3 same') graphCent.Draw('same L') if not BLIND: graphObs.Draw('same L') if scale: graphOne.SetLineColor(2) graphOne.SetLineWidth(2) graphOne.SetLineStyle(2) graphOne.Draw('same L') else: graphXsec.SetLineColor(2) graphXsecLow.SetLineColor(4) subscript = 'SR' if 'Resonant' in plottitle else 'FC' if 'Resonant' in plottitle: leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=0.1}{m_{#chi}=100 GeV}'%(subscript,subscript),'l') else: leg.AddEntry(graphXsec,'Theory a_{%s}=b_{%s}=0.1'%(subscript,subscript),'l') # leg.AddEntry(graphXsecLow,'Theory a_{%s}=b_{%s}=0.025'%(subscript,subscript),'l') for g in [graphXsec]: g.SetLineWidth(2) g.SetLineStyle(2) g.Draw('same L') leg.Draw() label = TLatex() label.SetNDC() label.SetTextFont(62) label.SetTextAlign(11) label.DrawLatex(0.19,0.85,"CMS") label.SetTextFont(52) label.DrawLatex(0.28,0.85,"Preliminary") label.SetTextFont(42) label.SetTextSize(0.6*c.GetTopMargin()) label.DrawLatex(0.19,0.77,plottitle) if scale: if 'Resonant' in plottitle: label.DrawLatex(0.19,0.7,"a_{SR} = b_{SR} = 0.1") label.DrawLatex(0.19,0.64,"m_{#chi}=100 GeV") else: label.DrawLatex(0.19,0.7,"a_{FC} = b_{FC} = 0.1") label.SetTextSize(0.5*c.GetTopMargin()) label.SetTextFont(42) label.SetTextAlign(31) # align right label.DrawLatex(0.9, 0.94,"%.1f fb^{-1} (13 TeV)"%(plotConfig.lumi)) c.SaveAs(foutname+'.pdf') c.SaveAs(foutname+'.png')
def limit(method, channel): particle = channel[1:2] particleP = particle + "'" if channel.startswith('X') else channel[0] THEORY = ['A1', 'B3'] if channel.startswith('X') else [] suffix = "" if method == "hvt": suffix = "_HVT" if method == "cls": suffix = "_CLs" if method == "monoH": suffix = "_monoH" filename = "./combine/" + method + "/" + channel + "_M%d.txt" mass, val = fillValues(filename) Obs0s = TGraph() Exp0s = TGraph() Exp1s = TGraphAsymmErrors() Exp2s = TGraphAsymmErrors() Sign = TGraph() pVal = TGraph() Best = TGraphAsymmErrors() Theory = {} for i, m in enumerate(mass): if not m in val: print "Key Error:", m, "not in value map" continue n = Exp0s.GetN() Obs0s.SetPoint(n, m, val[m][0]) Exp0s.SetPoint(n, m, val[m][3]) Exp1s.SetPoint(n, m, val[m][3]) Exp1s.SetPointError(n, 0., 0., val[m][3] - val[m][2], val[m][4] - val[m][3]) Exp2s.SetPoint(n, m, val[m][3]) Exp2s.SetPointError(n, 0., 0., val[m][3] - val[m][1], val[m][5] - val[m][3]) if len(val[m]) > 6: Sign.SetPoint(n, m, val[m][6]) if len(val[m]) > 7: pVal.SetPoint(n, m, val[m][7]) if len(val[m]) > 8: Best.SetPoint(n, m, val[m][8]) if len(val[m]) > 10: Best.SetPointError(n, 0., 0., abs(val[m][9]), val[m][10]) for t in THEORY: Theory[t] = TGraphAsymmErrors() for m in sorted(HVT[t]['Z']['XS'].keys()): if m < mass[0] or m > mass[-1]: continue XsW, XsW_Up, XsW_Down, XsZ, XsZ_Up, XsZ_Down = 0., 0., 0., 0., 0., 0. XsZ = 1000. * HVT[t]['Z']['XS'][m] * HVT[t]['Z']['BR'][m] XsZ_Up = XsZ * (1. + math.hypot(HVT[t]['Z']['QCD'][m][0] - 1., HVT[t]['Z']['PDF'][m][0] - 1.)) XsZ_Down = XsZ * (1. - math.hypot(1. - HVT[t]['Z']['QCD'][m][0], 1. - HVT[t]['Z']['PDF'][m][0])) n = Theory[t].GetN() Theory[t].SetPoint(n, m, XsW + XsZ) Theory[t].SetPointError(n, 0., 0., (XsW - XsW_Down) + (XsZ - XsZ_Down), (XsW_Up - XsW) + (XsZ_Up - XsZ)) Theory[t].SetLineColor(theoryLineColor[t]) Theory[t].SetFillColor(theoryFillColor[t]) Theory[t].SetFillStyle(theoryFillStyle[t]) Theory[t].SetLineWidth(2) #Theory[t].SetLineStyle(7) Exp2s.SetLineWidth(2) Exp2s.SetLineStyle(1) Obs0s.SetLineWidth(3) Obs0s.SetMarkerStyle(0) Obs0s.SetLineColor(1) Exp0s.SetLineStyle(2) Exp0s.SetLineWidth(3) Exp1s.SetFillColor(417) #kGreen+1 Exp1s.SetLineColor(417) #kGreen+1 Exp2s.SetFillColor(800) #kOrange Exp2s.SetLineColor(800) #kOrange Exp2s.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25) Exp2s.GetXaxis().SetNoExponent(True) Exp2s.GetXaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetTitle("#sigma(" + particleP + ") #bf{#it{#Beta}}(" + particleP + " #rightarrow " + particle + "h) (fb)") Exp2s.GetYaxis().SetTitleOffset(1.5) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetMoreLogLabels() Sign.SetLineWidth(2) Sign.SetLineColor(629) Sign.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1) Sign.GetYaxis().SetTitle("Significance") pVal.SetLineWidth(2) pVal.SetLineColor(629) pVal.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1) pVal.GetYaxis().SetTitle("local p-Value") Best.SetLineWidth(2) Best.SetLineColor(629) Best.SetFillColor(629) Best.SetFillStyle(3003) Best.GetXaxis().SetTitle("m_{" + particleP + "} (GeV)") Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1) Best.GetYaxis().SetTitle("Best Fit (pb)") c1 = TCanvas("c1", "Exclusion Limits", 800, 600) c1.cd() #SetPad(c1.GetPad(0)) c1.GetPad(0).SetTopMargin(0.06) c1.GetPad(0).SetRightMargin(0.05) c1.GetPad(0).SetLeftMargin(0.12) c1.GetPad(0).SetTicks(1, 1) #c1.GetPad(0).SetGridx() #c1.GetPad(0).SetGridy() c1.GetPad(0).SetLogy() Exp2s.Draw("A3") Exp1s.Draw("SAME, 3") for t in THEORY: Theory[t].Draw("SAME, L3") Theory[t].Draw("SAME, L3X0Y0") Exp0s.Draw("SAME, L") if not options.blind: Obs0s.Draw("SAME, L") #setHistStyle(Exp2s) Exp2s.GetXaxis().SetTitleSize(0.050) Exp2s.GetYaxis().SetTitleSize(0.050) Exp2s.GetXaxis().SetLabelSize(0.045) Exp2s.GetYaxis().SetLabelSize(0.045) Exp2s.GetXaxis().SetTitleOffset(0.90) Exp2s.GetYaxis().SetTitleOffset(1.25) Exp2s.GetYaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetRangeUser(0.01, 5.e3) #else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2) Exp2s.GetXaxis().SetRangeUser( mass[0], min(mass[-1], MAXIMUM[channel] if channel in MAXIMUM else 1.e6)) drawAnalysis(channel) drawRegion(channel, True) drawCMS(LUMI, YEAR, "Preliminary") #Preliminary # legend top = 0.9 nitems = 4 + len(THEORY) leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.98, top) leg.SetBorderSize(0) leg.SetFillStyle(0) #1001 leg.SetFillColor(0) leg.SetHeader("95% CL upper limits") leg.AddEntry(Obs0s, "Observed", "l") leg.AddEntry(Exp0s, "Expected", "l") leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f") leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f") for t in THEORY: leg.AddEntry(Theory[t], theoryLabel[t], "fl") leg.Draw() latex = TLatex() latex.SetNDC() latex.SetTextSize(0.045) latex.SetTextFont(42) #latex.DrawLatex(0.66, leg.GetY1()-0.045, particleP+" #rightarrow "+particle+"h") leg2 = TLegend(0.12, 0.225 - 2 * 0.25 / 5., 0.65, 0.225) leg2.SetBorderSize(0) leg2.SetFillStyle(0) #1001 leg2.SetFillColor(0) c1.GetPad(0).RedrawAxis() """ if True and channel.endswith('sl'): mass, val = fillValues("./combine/alpha/X"+particle+"Hbonly_M%d.txt") Exp, Obs = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(mass): if not m in val: continue Exp.SetPoint(Exp.GetN(), m, val[m][3]) Obs.SetPoint(Obs.GetN(), m, val[m][0]) Exp.SetLineWidth(3) Exp.SetLineColor(602) #602 Exp.SetLineStyle(5) Obs.SetLineWidth(3) Obs.SetLineColor(602) Exp.Draw("SAME, L") Obs.Draw("SAME, L") mass15, val15 = fillValues("./combine/Vh_2015/X"+particle+"h_M%d.txt") Exp15, Obs15 = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(mass15): if not m in val: continue Exp15.SetPoint(Exp15.GetN(), m, val15[m][3]*multF*Theory['B3'].GetY()[i]*(0.625 if particle=='V' and m>3000 else 1.)) Obs15.SetPoint(Obs15.GetN(), m, val15[m][0]*multF*Theory['B3'].GetY()[i]*(0.625 if particle=='V' and m>3000 else 1.)) Exp15.SetLineWidth(3) Exp15.SetLineColor(856) #602 Exp15.SetLineStyle(6) Obs15.SetLineWidth(3) Obs15.SetLineColor(856) Exp15.Draw("SAME, L") #Obs15.Draw("SAME, L") leg2.AddEntry(Exp, "1+2 b-tag", "l") """ if True and channel == 'AZh': massLL, valLL = fillValues("./combine/AZh/AZhll_M%d.txt") ExpLL, ObsLL = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(massLL): if not m in val: continue ExpLL.SetPoint(ExpLL.GetN(), m, valLL[m][3] * multF) ObsLL.SetPoint(ObsLL.GetN(), m, valLL[m][0] * multF) ExpLL.SetLineWidth(3) ExpLL.SetLineColor(833) #602 ExpLL.SetLineStyle(5) ObsLL.SetLineWidth(3) ObsLL.SetLineColor(833) ExpLL.Draw("SAME, L") #ObsLL.Draw("SAME, L") massNN, valNN = fillValues("./combine/AZh/AZhnn_M%d.txt") ExpNN, ObsNN = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(massNN): if not m in val: continue ExpNN.SetPoint(ExpNN.GetN(), m, valNN[m][3] * multF) ObsNN.SetPoint(ObsNN.GetN(), m, valNN[m][0] * multF) ExpNN.SetLineWidth(3) ExpNN.SetLineColor(855) #602 ExpNN.SetLineStyle(6) ObsNN.SetLineWidth(3) ObsNN.SetLineColor(855) ExpNN.Draw("SAME, L") #ObsNN.Draw("SAME, L") leg2.AddEntry(ExpLL, "Expected, A #rightarrow Zh #rightarrow llb#bar{b}", "l") leg2.AddEntry(ExpNN, "Expected, A #rightarrow Zh #rightarrow #nu#nub#bar{b}", "l") if method == 'combo': massAH, valAH = fillValues("./combine/dijet/X" + particle + "Hah_M%d.txt") ExpAH = TGraphAsymmErrors() for i, m in enumerate(massAH): if not m in val: continue ExpAH.SetPoint(ExpAH.GetN(), m, valAH[m][3] * multF) ExpAH.SetLineWidth(2) ExpAH.SetLineColor(602) #602 ExpAH.SetLineStyle(4) ExpAH.Draw("SAME, L") massSL, valSL = fillValues("./combine/alpha/X" + particle + "Hsl_M%d.txt") ExpSL = TGraphAsymmErrors() for i, m in enumerate(massSL): if not m in val: continue ExpSL.SetPoint(ExpSL.GetN(), m, valSL[m][3] * multF) ExpSL.SetLineWidth(3) ExpSL.SetLineColor(860 - 9) #602 ExpSL.SetLineStyle(7) ExpSL.Draw("SAME, L") leg2.AddEntry(ExpAH, "B2G-17-002", "l") leg2.AddEntry(ExpSL, "B2G-17-004", "l") leg2.Draw() if not options.blind: Obs0s.Draw("SAME, L") c1.GetPad(0).Update() if not gROOT.IsBatch(): raw_input("Press Enter to continue...") c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".png") c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".pdf") if 'ah' in channel or 'sl' in channel: c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".C") c1.Print("plotsLimit/Exclusion/" + channel + suffix + ".root") for t in THEORY: print "Model", t, ":", for m in range(mass[0], mass[-1], 1): if not (Theory[t].Eval(m) > Obs0s.Eval(m)) == ( Theory[t].Eval(m + 1) > Obs0s.Eval(m + 1)): print m, print "" print "p1s[", for i in range(Exp0s.GetN()): print Exp0s.GetY()[i] + Exp1s.GetErrorYhigh(i), ",", print "]," print "m1s[", for i in range(Exp0s.GetN()): print Exp0s.GetY()[i] - Exp1s.GetErrorYlow(i), ",", print "]," print "[", for i in range(Exp0s.GetN()): print Exp0s.GetY()[i], ",", print "]" #if not 'ah' in channel and not 'sl' in channel: return # ---------- Significance ---------- c2 = TCanvas("c2", "Significance", 800, 600) c2.cd() c2.GetPad(0).SetTopMargin(0.06) c2.GetPad(0).SetRightMargin(0.05) c2.GetPad(0).SetTicks(1, 1) c2.GetPad(0).SetGridx() c2.GetPad(0).SetGridy() Sign.GetYaxis().SetRangeUser(0., 5.) Sign.Draw("AL3") drawCMS(LUMI, YEAR, "Preliminary") drawAnalysis(channel[1:3]) c2.Print("plotsLimit/Significance/" + channel + suffix + ".png") c2.Print("plotsLimit/Significance/" + channel + suffix + ".pdf") # c2.Print("plotsLimit/Significance/"+channel+suffix+".root") # c2.Print("plotsLimit/Significance/"+channel+suffix+".C") # ---------- p-Value ---------- c3 = TCanvas("c3", "p-Value", 800, 600) c3.cd() c3.GetPad(0).SetTopMargin(0.06) c3.GetPad(0).SetRightMargin(0.05) c3.GetPad(0).SetTicks(1, 1) c3.GetPad(0).SetGridx() c3.GetPad(0).SetGridy() c3.GetPad(0).SetLogy() pVal.Draw("AL3") pVal.GetYaxis().SetRangeUser(2.e-7, 0.5) ci = [ 1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303, 0.000000001973 ] line = TLine() line.SetLineColor(922) line.SetLineStyle(7) text = TLatex() text.SetTextColor(922) text.SetTextSize(0.025) text.SetTextAlign(12) for i in range(1, len(ci) - 1): line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i] / 2, pVal.GetXaxis().GetXmax(), ci[i] / 2) text.DrawLatex(pVal.GetXaxis().GetXmax() * 1.01, ci[i] / 2, "%d #sigma" % i) drawCMS(LUMI, YEAR, "Preliminary") drawAnalysis(channel[1:3]) c3.Print("plotsLimit/pValue/" + channel + suffix + ".png") c3.Print("plotsLimit/pValue/" + channel + suffix + ".pdf") # c3.Print("plotsLimit/pValue/"+channel+suffix+".root") # c3.Print("plotsLimit/pValue/"+channel+suffix+".C") # --------- Best Fit ---------- c4 = TCanvas("c4", "Best Fit", 800, 600) c4.cd() c4.GetPad(0).SetTopMargin(0.06) c4.GetPad(0).SetRightMargin(0.05) c4.GetPad(0).SetTicks(1, 1) c4.GetPad(0).SetGridx() c4.GetPad(0).SetGridy() Best.Draw("AL3") drawCMS(LUMI, YEAR, "Preliminary") drawAnalysis(channel[1:3]) c4.Print("plotsLimit/BestFit/" + channel + suffix + ".png") c4.Print("plotsLimit/BestFit/" + channel + suffix + ".pdf") # c4.Print("plotsLimit/BestFit/"+channel+suffix+".root") # c4.Print("plotsLimit/BestFit/"+channel+suffix+".C") if not gROOT.IsBatch(): raw_input("Press Enter to continue...") if 'ah' in channel: outFile = TFile("bands.root", "RECREATE") outFile.cd() pVal.Write("graph") Best.Write("best") outFile.Close()
0, ] * len(brazil_data)) rms = array("d", list(map(itemgetter(2), brazil_data))) rms2 = array("d", [2 * r for r in rms]) low_2sigma = array("d", list(map(itemgetter(3), brazil_data))) low_1sigma = array("d", list(map(itemgetter(4), brazil_data))) high_1sigma = array("d", list(map(itemgetter(5), brazil_data))) high_2sigma = array("d", list(map(itemgetter(6), brazil_data))) mg = TMultiGraph() #mg.SetTitle(title) mg.SetTitle(job_id) brazil_yellow = TGraphAsymmErrors(len(brazil_data), x, mean, xerr, xerr, low_2sigma, high_2sigma) brazil_yellow.SetFillColor(5) brazil_yellow.SetFillStyle(1001) brazil_yellow.SetLineColor(3) brazil_yellow.SetLineWidth(10) brazil_yellow.SetMarkerColor(3) brazil_green = TGraphAsymmErrors(len(brazil_data), x, mean, xerr, xerr, low_1sigma, high_1sigma) brazil_green.SetFillColor(3) brazil_green.SetFillStyle(1001) brazil_green.SetLineColor(3) brazil_green.SetLineWidth(3) mg.Add(brazil_yellow) mg.Add(brazil_green) mg.Draw("a3")
def make1DLimitPlot(xtitle, xvals, obs, exp, exp1plus, exp1minus, exp2plus, exp2minus, theory): gStyle.SetOptTitle(0) axisTitleSize = 0.041 axisTitleOffset = 1.2 axisTitleSizeRatioX = 0.18 axisLabelSizeRatioX = 0.12 axisTitleOffsetRatioX = 0.94 axisTitleSizeRatioY = 0.15 axisLabelSizeRatioY = 0.108 axisTitleOffsetRatioY = 0.32 leftMargin = 0.15 rightMargin = 0.12 topMargin = 0.05 bottomMargin = 0.14 bottomMargin2 = 0.22 #c1 = TCanvas() #'c1', '', 200, 10, 700, 500 ) c1 = TCanvas( "c1", "c2", 200, 10, 700, 600 ) c1.SetHighLightColor(2) c1.SetFillColor(0) c1.SetBorderMode(0) c1.SetBorderSize(2) c1.SetLeftMargin(leftMargin) c1.SetRightMargin(rightMargin) c1.SetTopMargin(topMargin) c1.SetBottomMargin(bottomMargin) c1.SetFrameBorderMode(0) c1.SetFrameBorderMode(0) c1.SetLogy(1) #c1.SetLogx(1) c1.SetTickx(1) c1.SetTicky(1) #c1.SetGridx(True); #c1.SetGridy(True); if "c#tau" in xtitle: c1.SetLogx(1); exp2sigma_xsec = TGraphAsymmErrors(len(xvals), array('d', xvals), array('d', exp), \ array('d', [0]), array('d', [0]), array('d', exp2minus), array('d', exp2plus)) exp2sigma_xsec.Sort() exp2sigma_xsec.Draw('A3') exp2sigma_xsec.SetFillStyle(1001); exp2sigma_xsec.SetFillColor(kOrange); exp2sigma_xsec.SetLineColor(kOrange); exp2sigma_xsec.GetYaxis().SetRangeUser(0.001,100); exp2sigma_xsec.GetXaxis().SetLimits(0.8*min(xvals),1.1*max(xvals)); #exp2sigma_xsec.GetXaxis().SetTitle('m_{1} [GeV]') #exp2sigma_xsec.GetXaxis().SetTitle('c#tau [cm]') exp2sigma_xsec.GetXaxis().SetTitle(xtitle) exp2sigma_xsec.GetXaxis().SetTitleOffset(axisTitleOffset) exp2sigma_xsec.GetYaxis().SetTitle('95% C.L. #sigma(pp #rightarrow #chi_{1} #chi_{1} #mu^{+} #mu^{-}) [pb]') exp2sigma_xsec.GetYaxis().SetTitleOffset(axisTitleOffset+0.1) exp1sigma_xsec = TGraphAsymmErrors(len(xvals), array('d', xvals), array('d', exp), \ array('d', [0]), array('d', [0]), array('d', exp1minus), array('d', exp1plus)) exp1sigma_xsec.Sort() exp1sigma_xsec.SetFillStyle(1001); exp1sigma_xsec.SetFillColor(kGreen+1); exp1sigma_xsec.SetLineColor(kGreen+1); exp1sigma_xsec.Draw('3 SAME') exp_xsec = TGraph(len(xvals), array('d', xvals), array('d', exp)) exp_xsec.Sort() exp_xsec.SetLineWidth(2) exp_xsec.SetLineStyle(1) exp_xsec.SetLineColor(kRed) exp_xsec.Draw('C SAME') obs_xsec = TGraph(len(xvals), array('d', xvals), array('d', obs)) obs_xsec.Sort() obs_xsec.SetLineWidth(3) obs_xsec.SetLineColor(kBlack) obs_xsec.SetMarkerColor(kBlack) obs_xsec.SetMarkerStyle(20) obs_xsec.SetMarkerSize(1) obs_xsec.Draw('PC SAME') theory_xsec = TGraph(len(xvals), array('d', xvals), array('d', theory)) theory_xsec.Sort() theory_xsec.SetLineWidth(2) theory_xsec.SetLineStyle(8) theory_xsec.SetLineColor(kBlue) theory_xsec.Draw('C SAME') leg = TLegend(0.50,0.70,0.8,0.90); leg.SetBorderSize(0); leg.SetFillStyle(0); leg.AddEntry(theory_xsec, "Theory", "l"); leg.AddEntry(obs_xsec, "Observed Limit", "pl"); leg.AddEntry(exp_xsec, "Expected Limit", "l"); leg.AddEntry(exp1sigma_xsec, "#pm 1 std. dev.", "f"); leg.AddEntry(exp2sigma_xsec, "#pm 2 std. dev.", "f"); leg.Draw() drawCMSLogo(c1, 13, 122450) # TCanvas.Update() draws the frame, after which one can change it # c1.Update() # c1.Modified() # c1.Update() c1.RedrawAxis() c1.Draw() wait(True)
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) latex.SetTextColor(1) latex.SetTextFont(42) latex.SetTextAlign(33)
def make_ratioplot(name, ttbar_file=0, qcd_file=0, signal_files=[], histo=0, rebin=1, minx=0, maxx=0, miny=0, maxy=0, logy=False, xtitle='', ytitle='', textsizefactor=1, signal_legend=[], outfile=0, signal_colors=[], signal_zoom=1, qcd_zoom=1, ttbar_zoom=1, ttbar_legend='t#bar{t}', qcd_legend='QCD from MC', dosys=False, docms=True, legendtitle=''): ###canvas setting up canvas = 0 canvas = TCanvas(name, '', 0, 0, 600, 600) canvas.SetLeftMargin(0.15) canvas.SetRightMargin(0.05) canvas.SetTopMargin(0.10) canvas.SetBottomMargin(0.10) charsize = 0.04 offset = 1.9 ###latex label latex = 0 latex = TLatex(0.6, 0.7, '13 TeV, 2.69 fb^{-1}') latex.SetTextSize(charsize) latex.SetNDC(1) latex.SetTextFont(42) ###legend setting up #legend=TLegend(0.0,0.75,0.99,1.04) legend = TLegend(0.4, 0.6, 0.94, 0.95) legend.SetNColumns(2) legend.SetHeader('') legend.SetFillStyle(0) legend.SetBorderSize(0) ###mc stack stack = THStack(name + '_stack', '') qcd_histo = qcd_file.Get(histo).Clone(name + '_make_plot') qcd_histo.Rebin(rebin) ttbar_histo = ttbar_file.Get(histo).Clone() ttbar_histo.Rebin(rebin) ttbar_histo.SetFillColor(kRed - 9) ttbar_histo.SetLineColor(kRed - 9) ttbar_histo.SetMarkerColor(kRed - 9) if ttbar_zoom != 1: ttbar_histo.Scale(ttbar_zoom) legend.AddEntry(ttbar_histo, ttbar_legend, 'f') qcd_histo.SetFillColor(kOrange - 5) qcd_histo.SetLineColor(kOrange - 5) qcd_histo.SetMarkerColor(kOrange - 5) if qcd_zoom != 1: qcd_histo.Scale(qcd_zoom) legend.AddEntry(qcd_histo, qcd_legend, 'f') sum_mc = qcd_histo.Clone(histo + 'tmp') sum_mc.Add(ttbar_histo) stack.Add(ttbar_histo) stack.Add(qcd_histo) sum_mc.SetLineColor(kBlack) sum_mc.SetFillStyle(0) err = TGraphAsymmErrors(sum_mc) legend.AddEntry(err, 'Total uncertainty', 'f') if legendtitle == '': legend.AddEntry(0, "", '') legend.AddEntry(0, "g_{RS} #rightarrow t#bar{t} (2pb)", '') else: legend.AddEntry(0, "", '') legend.AddEntry(0, legendtitle, '') ###signal setting up signal_histos = [] colors = [ kBlack, kRed, kOrange, kBlue, kGreen + 3, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60 ] styles = [ 1, 3, 5, 7, 7, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ] if signal_colors != []: colors = signal_colors for i in range(len(signal_files)): signal_histos.append(signal_files[i].Get(histo).Clone()) signal_histos[i].SetLineWidth(3) signal_histos[i].SetLineStyle(styles[i]) signal_histos[i].SetLineColor(colors[i]) signal_histos[i].SetMarkerColor(colors[i]) signal_histos[i].Rebin(rebin) if signal_zoom != 1: signal_histos[i].Scale(signal_zoom) legend.AddEntry(signal_histos[i], signal_legend[i], 'l') ###mc shape line ttbar_line = 0 ttbar_line = ttbar_histo.Clone() ttbar_line.SetLineColor(kBlack) ttbar_line.SetFillStyle(0) ###mc errors if dosys: sys_diff_qcd = [] sys_diff_ttbar = [] for imtt in range(1, ttbar_histo.GetNbinsX() + 1): sys_diff_qcd.append([]) sys_diff_ttbar.append([]) #adding stat uncertainties <--removed # for imtt in range(1,ttbar_histo.GetNbinsX()+1): # sys_diff_ttbar[imtt-1].append(ttbar_histo.GetBinError(imtt)) # sys_diff_ttbar[imtt-1].append(-ttbar_histo.GetBinError(imtt)) # sys_diff_qcd[imtt-1].append(qcd_histo.GetBinError(imtt)) # sys_diff_qcd[imtt-1].append(-qcd_histo.GetBinError(imtt)) #adding flat uncertainties for imtt in range(1, ttbar_histo.GetNbinsX() + 1): #ttbar for i in [ 2.4, #pdf 10.0, #mu 3.0, #xsec 6.0, #toppt 1.0, #lumi 3.5, #jec 3.0, #jer 10.0, #btag #3.0,#trig 10.0, #toptag 3.0 ]: #pileup sys_diff_ttbar[imtt - 1].append( i / 100.0 * ttbar_histo.GetBinContent(imtt)) sys_diff_ttbar[imtt - 1].append( -i / 100.0 * ttbar_histo.GetBinContent(imtt)) closureunc = 5.0 # if '1b' in histo: # closureunc=5.0 # elif '2b' in histo: # closureunc=10.0 for i in [ 2.0, #modmass closureunc ]: #closure sys_diff_qcd[imtt - 1].append(i / 100.0 * qcd_histo.GetBinContent(imtt)) sys_diff_qcd[imtt - 1].append(-i / 100.0 * qcd_histo.GetBinContent(imtt)) # #3% trigger # sys_diff_ttbar[imtt-1].append(0.03*ttbar_histo.GetBinContent(imtt)) # sys_diff_ttbar[imtt-1].append(-0.03*ttbar_histo.GetBinContent(imtt)) # #2.7% lumi # sys_diff_ttbar[imtt-1].append(0.023*ttbar_histo.GetBinContent(imtt)) # sys_diff_ttbar[imtt-1].append(-0.023*ttbar_histo.GetBinContent(imtt)) # #15% ttbar # #sys_diff_ttbar[imtt-1].append(0.15*ttbar_histo.GetBinContent(imtt)) # #sys_diff_ttbar[imtt-1].append(-0.15*ttbar_histo.GetBinContent(imtt)) # #2.8% QCD # sys_diff_qcd[imtt-1].append(0.028*qcd_histo.GetBinContent(imtt)) # sys_diff_qcd[imtt-1].append(-0.028*qcd_histo.GetBinContent(imtt)) #combining uncertainties sys_tot_ttbar = [] sys_tot_qcd = [] sys_tot = [] sys_global_ttbar = [0.0, 0.0] sys_global_qcd = [0.0, 0.0] nevt_global = [0.0, 0.0, 0.0] for imtt in range(1, ttbar_histo.GetNbinsX() + 1): uperr_qcd = 0 downerr_qcd = 0 uperr_ttbar = 0 downerr_ttbar = 0 for error in sys_diff_ttbar[imtt - 1]: if error < 0: downerr_ttbar = downerr_ttbar + error * error else: uperr_ttbar = uperr_ttbar + error * error for error in sys_diff_qcd[imtt - 1]: if error < 0: downerr_qcd = downerr_qcd + error * error else: uperr_qcd = uperr_qcd + error * error sys_tot_ttbar.append( [math.sqrt(downerr_ttbar), math.sqrt(uperr_ttbar)]) sys_tot_qcd.append([math.sqrt(downerr_qcd), math.sqrt(uperr_qcd)]) sys_tot.append([ math.sqrt(downerr_qcd + downerr_ttbar), math.sqrt(uperr_qcd + uperr_ttbar) ]) sys_global_qcd[0] = sys_global_qcd[0] + downerr_qcd sys_global_qcd[1] = sys_global_qcd[1] + uperr_qcd sys_global_ttbar[0] = sys_global_ttbar[0] + downerr_ttbar sys_global_ttbar[1] = sys_global_ttbar[1] + uperr_ttbar # nevt_global[0]=nevt_global[0]+data_histo.GetBinContent(imtt) nevt_global[1] = nevt_global[1] + qcd_histo.GetBinContent(imtt) nevt_global[2] = nevt_global[2] + ttbar_histo.GetBinContent(imtt) #print 'ttbar+qcd',math.sqrt(uperr_qcd+uperr_ttbar),math.sqrt(downerr_qcd+downerr_ttbar) #print 'qcd',math.sqrt(uperr_qcd),math.sqrt(downerr_qcd) #print 'ttbar',math.sqrt(uperr_ttbar),math.sqrt(downerr_ttbar) err.SetPointEYhigh(imtt - 1, math.sqrt(uperr_qcd + uperr_ttbar)) err.SetPointEYlow(imtt - 1, math.sqrt(downerr_qcd + downerr_ttbar)) sys_global = [0.0, 0.0] sys_global[0] = math.sqrt(sys_global_qcd[0] + sys_global_ttbar[0]) sys_global[1] = math.sqrt(sys_global_qcd[1] + sys_global_ttbar[1]) sys_global_qcd[0] = math.sqrt(sys_global_qcd[0]) sys_global_qcd[1] = math.sqrt(sys_global_qcd[1]) sys_global_ttbar[0] = math.sqrt(sys_global_ttbar[0]) sys_global_ttbar[1] = math.sqrt(sys_global_ttbar[1]) # print name # print "\hline" # print "Multijet QCD & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[1],sys_global_qcd[1],sys_global_qcd[0]) # print "SM ttbar & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[2],sys_global_ttbar[1],sys_global_ttbar[0]) # print "\hline" # print "Total background & $%.0f^{+%.0f}_{-%.0f}$ \\\\" % (nevt_global[1]+nevt_global[2],sys_global[1],sys_global[0]) # print 'DATA & %.0f' %nevt_global[0] err.SetFillStyle(3145) err.SetFillColor(kGray + 1) ###drawing top canvas.cd() stack.Draw('hist') stack.GetXaxis().SetTitle(ttbar_histo.GetXaxis().GetTitle()) stack.GetYaxis().SetTitle(ttbar_histo.GetYaxis().GetTitle()) stack.GetXaxis().SetLabelSize(charsize) stack.GetXaxis().SetTitleSize(charsize) stack.GetYaxis().SetLabelSize(charsize) stack.GetYaxis().SetTitleSize(charsize) stack.GetYaxis().SetTitleOffset(offset) if minx != 0 or maxx != 0: stack.GetXaxis().SetRangeUser(minx, maxx) #else: # stack.GetXaxis().SetRangeUser(0,4000) if miny != 0 or maxy != 0: stack.SetMaximum(maxy) stack.SetMinimum(miny) else: if logy: stack.SetMaximum(stack.GetMaximum() * 10) stack.SetMinimum(0.2) else: stack.SetMaximum(stack.GetMaximum() * 2.0) stack.SetMinimum(0.001) err.Draw('2') sum_mc.Draw('samehist') if ttbar_file != 0: ttbar_line.Draw('samehist') for i in signal_histos: i.Draw('samehist') if logy: canvas.SetLogy() legend.Draw() latex2text = '' if 'ldy_0b' in name: latex2text = '#Deltay < 1; 0 b tag' elif 'ldy_1b' in name: latex2text = '#Deltay < 1; 1 b tag' elif 'ldy_2b' in name: latex2text = '#Deltay < 1; 2 b tag' elif 'hdy_0b' in name: latex2text = '#Deltay > 1; 0 b tag' elif 'hdy_1b' in name: latex2text = '#Deltay > 1; 1 b tag' elif 'hdy_2b' in name: latex2text = '#Deltay > 1; 2 b tag' latex2 = TLatex(0.19, 0.7, latex2text) latex2.SetTextSize(0.03) latex2.SetNDC(1) latex2.SetTextFont(42) latex2.Draw() if docms: if '3000' in name: CMS_lumi.CMS_lumi(canvas, 3, 11) elif '1000' in name: CMS_lumi.CMS_lumi(canvas, 2, 11) elif '300' in name: CMS_lumi.CMS_lumi(canvas, 1, 11) elif '36' in name: CMS_lumi.CMS_lumi(canvas, 0, 11) ###saving canvas.SaveAs('pdf/' + name + '.pdf') if outfile != 0: canvas.Write()
def limit2HDM(): global signals signals = range(800, 2000 + 1, 50) multF = HTOBB THEORY = ['T1', 'T2'] mass, val = fillValues("./combine/AZh/AZh_M%d.txt") Obs0s = TGraph() Exp0s = TGraph() Exp1s = TGraphAsymmErrors() Exp2s = TGraphAsymmErrors() massB, valB = fillValues("./combine/BBAZh/BBAZh_M%d.txt") Obs0sB = TGraph() Exp0sB = TGraph() Exp1sB = TGraphAsymmErrors() Exp2sB = TGraphAsymmErrors() for i, m in enumerate(mass): if not m in val: print "Key Error:", m, "not in value map" continue n = Exp0s.GetN() Obs0s.SetPoint(n, m, val[m][0] * multF) Exp0s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF, val[m][4] * multF - val[m][3] * multF) Exp2s.SetPoint(n, m, val[m][3] * multF) Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF, val[m][5] * multF - val[m][3] * multF) Obs0sB.SetPoint(n, m, valB[m][0] * multF) Exp0sB.SetPoint(n, m, valB[m][3] * multF) Exp1sB.SetPoint(n, m, valB[m][3] * multF) Exp1sB.SetPointError(n, 0., 0., valB[m][3] * multF - valB[m][2] * multF, valB[m][4] * multF - valB[m][3] * multF) Exp2sB.SetPoint(n, m, valB[m][3] * multF) Exp2sB.SetPointError(n, 0., 0., valB[m][3] * multF - valB[m][1] * multF, valB[m][5] * multF - valB[m][3] * multF) col = 629 Exp2s.SetLineWidth(2) Exp2s.SetLineStyle(1) Obs0s.SetLineWidth(3) Obs0s.SetMarkerStyle(0) Obs0s.SetLineColor(1) Exp0s.SetLineStyle(2) Exp0s.SetLineWidth(3) Exp0s.SetLineColor(1) # Exp1s.SetFillColorAlpha(col, 0.4) #kGreen+1 # Exp1s.SetLineColorAlpha(col, 0.4) # Exp2s.SetFillColorAlpha(col, 0.2) #kOrange # Exp2s.SetLineColorAlpha(col, 0.2) Exp1s.SetFillColor(417) Exp1s.SetLineColor(417) Exp2s.SetFillColor(800) Exp2s.SetLineColor(800) colB = 922 Exp2sB.SetLineWidth(2) Obs0sB.SetLineStyle(9) Obs0sB.SetLineWidth(3) Obs0sB.SetMarkerStyle(0) Obs0sB.SetLineColor(colB) Exp0sB.SetLineStyle(8) Exp0sB.SetLineWidth(3) Exp0sB.SetLineColor(colB) Exp1sB.SetFillColorAlpha(colB, 0.4) #kGreen+1 Exp1sB.SetLineColorAlpha(colB, 0.4) Exp2sB.SetFillColorAlpha(colB, 0.2) #kOrange Exp2sB.SetLineColorAlpha(colB, 0.2) Exp2s.GetXaxis().SetTitle("m_{A} (GeV)") Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25) Exp2s.GetXaxis().SetNoExponent(True) Exp2s.GetXaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetTitle( "#sigma(A) #bf{#it{#Beta}}(A #rightarrow Zh) #bf{#it{#Beta}}(h #rightarrow bb) (fb)" ) Exp2s.GetYaxis().SetTitleOffset(1.5) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetMoreLogLabels() Theory = {} #for t in THEORY: # Theory[t] = TGraphAsymmErrors() # for m in sorted(THDM[t]['ggA'].keys()): # if m < mass[0] or m > mass[-1]: continue # Xs, Xs_Up, Xs_Down = 0., 0., 0. # Xs = THDM[t]['ggA'][m] # Xs_Up = Xs*(1.+math.sqrt((THDM['PDF']['ggA'][m][0]-1.)**2 + (THDM['QCD']['ggA'][m][0]-1.)**2)) # Xs_Down = Xs*(1.-math.sqrt((1.-THDM['PDF']['ggA'][m][1])**2 + (1.-THDM['QCD']['ggA'][m][1])**2)) # n = Theory[t].GetN() # Theory[t].SetPoint(n, m, Xs) # Theory[t].SetPointError(n, 0., 0., (Xs-Xs_Down), (Xs_Up-Xs)) # Theory[t].SetLineColor(theoryLineColor[t]) # Theory[t].SetFillColor(theoryFillColor[t]) # Theory[t].SetFillStyle(theoryFillStyle[t]) # Theory[t].SetLineWidth(2) # #Theory[t].SetLineStyle(7) c1 = TCanvas("c1", "Exclusion Limits", 800, 600) c1.cd() #SetPad(c1.GetPad(0)) c1.GetPad(0).SetTopMargin(0.06) c1.GetPad(0).SetRightMargin(0.05) c1.GetPad(0).SetLeftMargin(0.12) c1.GetPad(0).SetTicks(1, 1) c1.GetPad(0).SetLogy() Exp2s.Draw("A3") Exp1s.Draw("SAME, 3") Exp0s.Draw("SAME, L") # Exp2sB.Draw("SAME, 3") # Exp1sB.Draw("SAME, 3") Exp0sB.Draw("SAME, L") if not options.blind: Obs0s.Draw("SAME, L") Obs0sB.Draw("SAME, L") for t in THEORY: Theory[t].Draw("SAME, L3") Theory[t].Draw("SAME, L3X0Y0") #setHistStyle(Exp2s) # Exp2s.GetXaxis().SetTitleSize(0.045) # Exp2s.GetYaxis().SetTitleSize(0.04) # Exp2s.GetXaxis().SetLabelSize(0.04) # Exp2s.GetYaxis().SetLabelSize(0.04) # Exp2s.GetXaxis().SetTitleOffset(1) # Exp2s.GetYaxis().SetTitleOffset(1.25) Exp2s.GetXaxis().SetTitleSize(0.050) Exp2s.GetYaxis().SetTitleSize(0.050) Exp2s.GetXaxis().SetLabelSize(0.045) Exp2s.GetYaxis().SetLabelSize(0.045) Exp2s.GetXaxis().SetTitleOffset(0.90) Exp2s.GetYaxis().SetTitleOffset(1.25) Exp2s.GetYaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetRangeUser(0.5, 1.e3) Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1]) drawAnalysis('AZh') drawRegion('AZHsl', True) drawCMS(LUMI, "") #Preliminary #drawCMS(LUMI, "Work in Progress", suppressCMS=True) # legend leg = TLegend(0.6, 0.90, 0.99, 0.90) leg.SetBorderSize(0) leg.SetFillStyle(0) #1001 leg.SetFillColor(0) leg.SetHeader("95% CL upper limits") leg.AddEntry(None, "gg #rightarrow A #rightarrow Zh", "") #"95% CL upper limits" leg.AddEntry(Obs0s, "Observed", "l") leg.AddEntry(Exp0s, "Expected", "l") leg.AddEntry(Exp1s, "#pm 1 std. deviation", "f") leg.AddEntry(Exp2s, "#pm 2 std. deviation", "f") leg.AddEntry(None, "", "") leg.AddEntry(None, "bbA #rightarrow Zh", "") leg.AddEntry(Obs0sB, "Observed", "l") leg.AddEntry(Exp0sB, "Expected", "l") leg.SetY1(leg.GetY2() - leg.GetNRows() * 0.045) leg.Draw() # latex = TLatex() # latex.SetNDC() # latex.SetTextSize(0.040) # latex.SetTextFont(42) # latex.DrawLatex(0.65, leg.GetY1()-0.045, "cos(#beta-#alpha)=0.25, tan(#beta)=1") # legB = TLegend(0.12, 0.4-4*0.3/5., 0.65, 0.4) legB = TLegend(0.15, 0.27, 0.68, 0.27) legB.SetBorderSize(0) legB.SetFillStyle(0) #1001 legB.SetFillColor(0) for t in THEORY: legB.AddEntry(Theory[t], theoryLabel[t], "fl") legB.AddEntry(None, "cos(#beta-#alpha)=0.25, tan(#beta)=1", "") legB.SetY1(legB.GetY2() - legB.GetNRows() * 0.045) legB.Draw() c1.GetPad(0).RedrawAxis() leg.Draw() c1.Update() if not gROOT.IsBatch(): raw_input("Press Enter to continue...") c1.Print("plotsLimit/Exclusion/THDM.png") c1.Print("plotsLimit/Exclusion/THDM.pdf")
def makeBiasPlot(output, muFile, chan, interference, printStats=False, obs2="", ratioLabel=""): mu = open(muFile, 'r') limits = {} mux = [] muy = [] mu1SigLow = [] mu1SigHigh = [] mu2SigLow = [] mu2SigHigh = [] for entry in mu: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in limits: limits[massPoint] = [] limits[massPoint].append(limitEntry) if printStats: print "len limits:", len(limits) for massPoint in sorted(limits): limits[massPoint].sort() numLimits = len(limits[massPoint]) nrExpts = len(limits[massPoint]) medianNr = int(nrExpts * 0.5) #get indexes: upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5)) lower1Sig = int(nrExpts * (1 - 0.68) * 0.5) upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5)) lower2Sig = int(nrExpts * (1 - 0.95) * 0.5) if printStats: print massPoint, ":", limits[massPoint][lower2Sig], limits[ massPoint][lower1Sig], limits[massPoint][medianNr], limits[ massPoint][upper1Sig], limits[massPoint][upper2Sig] #fill lists: mux.append(massPoint) print massPoint, limits[massPoint][medianNr] muy.append(limits[massPoint][medianNr]) mu1SigLow.append(limits[massPoint][lower1Sig]) mu1SigHigh.append(limits[massPoint][upper1Sig]) mu2SigLow.append(limits[massPoint][lower2Sig]) mu2SigHigh.append(limits[massPoint][upper2Sig]) muX = numpy.array(mux) muY = numpy.array(muy) values2 = [] xPointsForValues2 = [] values = [] xPointsForValues = [] if printStats: print "length of mux: ", len(mux) if printStats: print "length of mu1SigLow: ", len(mu1SigLow) if printStats: print "length of mu1SigHigh: ", len(mu1SigHigh) #Here is some Voodoo via Sam: for x in range(0, len(mux)): values2.append(mu2SigLow[x]) xPointsForValues2.append(mux[x]) for x in range(len(mux) - 1, 0 - 1, -1): values2.append(mu2SigHigh[x]) xPointsForValues2.append(mux[x]) if printStats: print "length of values2: ", len(values2) for x in range(0, len(mux)): values.append(mu1SigLow[x]) xPointsForValues.append(mux[x]) for x in range(len(mux) - 1, 0 - 1, -1): values.append(mu1SigHigh[x]) xPointsForValues.append(mux[x]) if printStats: print "length of values: ", len(values) mu2Sig = numpy.array(values2) xPoints2 = numpy.array(xPointsForValues2) mu1Sig = numpy.array(values) xPoints = numpy.array(xPointsForValues) if printStats: print "xPoints2: ", xPoints2 if printStats: print "mu2Sig: ", mu2Sig if printStats: print "xPoints: ", xPoints if printStats: print "mu1Sig: ", mu1Sig GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, mu2Sig) GraphErr2Sig.SetFillColor(ROOT.kYellow + 1) GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, mu1Sig) GraphErr1Sig.SetFillColor(ROOT.kGreen) cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500) gStyle.SetOptStat(0) plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1) plotPad.Draw() plotPad.cd() muX = numpy.array(mux) muY = numpy.array(muy) GraphMU = TGraph(len(muX), muX, muY) GraphMU.SetLineWidth(3) GraphMU.SetLineStyle(2) GraphMU.SetLineColor(ROOT.kBlue) #Draw the graphs: DummyGraph = TH1F("DummyGraph", "", 100, 10, 40) DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]") DummyGraph.GetYaxis().SetTitle("#hat{#mu}") gStyle.SetOptStat(0) if "Des" in output: DummyGraph.GetXaxis().SetRangeUser(10, 28) else: DummyGraph.GetXaxis().SetRangeUser(10, 40) DummyGraph.SetMinimum(-2) DummyGraph.SetMaximum(10) DummyGraph.GetXaxis().SetLabelSize(0.04) DummyGraph.GetXaxis().SetTitleSize(0.045) DummyGraph.GetXaxis().SetTitleOffset(1.) DummyGraph.GetYaxis().SetLabelSize(0.04) DummyGraph.GetYaxis().SetTitleSize(0.045) DummyGraph.GetYaxis().SetTitleOffset(1.) DummyGraph.Draw() DummyGraph.SetLineColor(ROOT.kWhite) if (FULL): GraphErr2Sig.Draw("F") GraphErr1Sig.Draw("F") GraphMU.Draw("lpsame") else: GraphMU.Draw("lp") plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC") #plCMS.SetTextSize(0.8) plCMS.SetTextAlign(12) plCMS.SetTextFont(62) plCMS.SetFillColor(0) plCMS.SetFillStyle(0) plCMS.SetBorderSize(0) plCMS.Draw() plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC") plPrelim.SetTextSize(0.6) plPrelim.SetTextAlign(12) plPrelim.SetTextFont(52) plPrelim.SetFillColor(0) plPrelim.SetFillStyle(0) plPrelim.SetBorderSize(0) plPrelim.Draw() cCL.SetTickx(1) cCL.SetTicky(1) cCL.RedrawAxis() cCL.Update() #leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC") leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC") # leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC") leg.SetTextSize(0.032) leg.AddEntry(GraphMU, "median value", "l") if (FULL): leg.AddEntry(GraphErr1Sig, "1#sigma quantile", "f") leg.AddEntry(GraphErr2Sig, "2#sigma quantile", "f") leg.SetLineWidth(0) leg.SetLineStyle(0) leg.SetFillStyle(0) leg.SetLineColor(0) leg.Draw("hist") if "Moriond" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "35.9 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") else: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") plLumi.SetTextSize(0.5) plLumi.SetTextFont(42) plLumi.SetFillColor(0) plLumi.SetBorderSize(0) plLumi.Draw() maxX = 40 if "Des" in output: maxX = 28 line = ROOT.TLine(10, 0, maxX, 0) if "mu1" in output: line = ROOT.TLine(10, 1, maxX, 1) line.SetLineStyle(ROOT.kDashed) line.Draw("same") plotPad.RedrawAxis() cCL.Update() printPlots(cCL, output)
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 makeLimitPlot(output, obs, exp, chan, interference, printStats=False, obs2="", ratioLabel=""): fileObs = open(obs, 'r') fileExp = open(exp, 'r') observedx = [] observedy = [] obsLimits = {} xSecs = getFittedXSecCurve("CI_%s" % interference, 1.3) for entry in fileObs: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) * xSecs.Eval( int(float(entry.split()[0]))) if massPoint not in obsLimits: obsLimits[massPoint] = [] obsLimits[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits) for massPoint in sorted(obsLimits): observedx.append(massPoint) observedy.append(numpy.mean(obsLimits[massPoint])) if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits[massPoint]), " std dev: ", numpy.std( obsLimits[massPoint]), " from: ", obsLimits[massPoint] if not obs2 == "": fileObs2 = open(obs2, 'r') observedx2 = [] observedy2 = [] obsLimits2 = {} for entry in fileObs2: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) * xSecs.Eval( int(float(entry.split()[0]))) if massPoint not in obsLimits2: obsLimits2[massPoint] = [] obsLimits2[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits2) for massPoint in sorted(obsLimits2): observedx2.append(massPoint) observedy2.append(numpy.mean(obsLimits2[massPoint])) if (numpy.std(obsLimits2[massPoint]) / numpy.mean(obsLimits2[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits2[massPoint]), " std dev: ", numpy.std( obsLimits2[massPoint] ), " from: ", obsLimits2[massPoint] limits = {} expectedx = [] expectedy = [] expected1SigLow = [] expected1SigHigh = [] expected2SigLow = [] expected2SigHigh = [] for entry in fileExp: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) * xSecs.Eval( int(float(entry.split()[0]))) if massPoint not in limits: limits[massPoint] = [] limits[massPoint].append(limitEntry) if printStats: print "len limits:", len(limits) for massPoint in sorted(limits): limits[massPoint].sort() numLimits = len(limits[massPoint]) nrExpts = len(limits[massPoint]) medianNr = int(nrExpts * 0.5) #get indexes: upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5)) lower1Sig = int(nrExpts * (1 - 0.68) * 0.5) upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5)) lower2Sig = int(nrExpts * (1 - 0.95) * 0.5) if printStats: print massPoint, ":", limits[massPoint][lower2Sig], limits[ massPoint][lower1Sig], limits[massPoint][medianNr], limits[ massPoint][upper1Sig], limits[massPoint][upper2Sig] #fill lists: expectedx.append(massPoint) print massPoint, limits[massPoint][medianNr] expectedy.append(limits[massPoint][medianNr]) expected1SigLow.append(limits[massPoint][lower1Sig]) expected1SigHigh.append(limits[massPoint][upper1Sig]) expected2SigLow.append(limits[massPoint][lower2Sig]) expected2SigHigh.append(limits[massPoint][upper2Sig]) expX = numpy.array(expectedx) expY = numpy.array(expectedy) values2 = [] xPointsForValues2 = [] values = [] xPointsForValues = [] if printStats: print "length of expectedx: ", len(expectedx) if printStats: print "length of expected1SigLow: ", len(expected1SigLow) if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh) #Here is some Voodoo via Sam: for x in range(0, len(expectedx)): values2.append(expected2SigLow[x]) xPointsForValues2.append(expectedx[x]) for x in range(len(expectedx) - 1, 0 - 1, -1): values2.append(expected2SigHigh[x]) xPointsForValues2.append(expectedx[x]) if printStats: print "length of values2: ", len(values2) for x in range(0, len(expectedx)): values.append(expected1SigLow[x]) xPointsForValues.append(expectedx[x]) for x in range(len(expectedx) - 1, 0 - 1, -1): values.append(expected1SigHigh[x]) xPointsForValues.append(expectedx[x]) if printStats: print "length of values: ", len(values) exp2Sig = numpy.array(values2) xPoints2 = numpy.array(xPointsForValues2) exp1Sig = numpy.array(values) xPoints = numpy.array(xPointsForValues) if printStats: print "xPoints2: ", xPoints2 if printStats: print "exp2Sig: ", exp2Sig if printStats: print "xPoints: ", xPoints if printStats: print "exp1Sig: ", exp1Sig GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig) GraphErr2Sig.SetFillColor(ROOT.kOrange) GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig) GraphErr1Sig.SetFillColor(ROOT.kGreen + 1) cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500) gStyle.SetOptStat(0) if not obs2 == "": plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1) ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3) plotPad.Draw() ratioPad.Draw() plotPad.cd() else: plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1) plotPad.Draw() plotPad.cd() expX = numpy.array(expectedx) expY = numpy.array(expectedy) GraphExp = TGraph(len(expX), expX, expY) GraphExp.SetLineWidth(3) GraphExp.SetLineStyle(2) GraphExp.SetLineColor(ROOT.kBlue) obsX = numpy.array(observedx) obsY = numpy.array(observedy) if printStats: print "obsX: ", obsX if printStats: print "obsY: ", obsY if SMOOTH: smooth_obs = TGraphSmooth("normal") GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY) GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0, 0.005) else: GraphObs = TGraph(len(obsX), obsX, obsY) GraphObs.SetLineWidth(3) if not obs2 == "": ratio = [] ratiox = [] for index, val in enumerate(observedy): mass = observedx[index] foundIndex = -1 for index2, mass2 in enumerate(observedx2): if mass == mass2: foundIndex = index2 if foundIndex > 0: ratio.append(observedy2[foundIndex] / val) ratiox.append(mass) ratioA = numpy.array(ratio) ratioX = numpy.array(ratiox) obsX2 = numpy.array(observedx2) obsY2 = numpy.array(observedy2) ratioGraph = TGraph(len(ratioX), ratioX, ratioA) if printStats: print "obsX2: ", obsX2 if printStats: print "obsY2: ", obsY2 if SMOOTH: smooth_obs2 = TGraphSmooth("normal") GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2) GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear", 0, 0.005) else: GraphObs2 = TGraph(len(obsX2), obsX2, obsY2) GraphObs2.SetLineWidth(3) xSecCurves = [] xSecCurves.append(getFittedXSecCurve("CI_%s" % interference, 1.3)) #Draw the graphs: plotPad.SetLogy() DummyGraph = TH1F("DummyGraph", "", 100, 10, 46) DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]") if chan == "mumu": DummyGraph.GetYaxis().SetTitle( "95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#mu#mu +X) [pb]" ) elif chan == "elel": DummyGraph.GetYaxis().SetTitle( "95% CL limit on #sigma(pp#rightarrow CI+X#rightarrowee +X) [pb]") elif chan == "elmu": DummyGraph.GetYaxis().SetTitle( "95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#font[12]{ll}) [pb]" ) gStyle.SetOptStat(0) DummyGraph.GetXaxis().SetRangeUser(10, 46) DummyGraph.SetMinimum(5e-4) DummyGraph.SetMaximum(1) DummyGraph.GetXaxis().SetLabelSize(0.04) DummyGraph.GetXaxis().SetTitleSize(0.045) DummyGraph.GetXaxis().SetTitleOffset(1.) DummyGraph.GetYaxis().SetLabelSize(0.04) DummyGraph.GetYaxis().SetTitleSize(0.045) DummyGraph.GetYaxis().SetTitleOffset(1.) DummyGraph.Draw() if (FULL): GraphErr2Sig.Draw("F") GraphErr1Sig.Draw("F") GraphExp.Draw("lpsame") else: if obs2 == "": GraphExp.Draw("lp") if not EXPONLY: GraphObs.Draw("plsame") if not obs2 == "": GraphObs2.SetLineColor(ROOT.kRed) GraphObs2.SetLineStyle(ROOT.kDashed) GraphObs2.Draw("plsame") for curve in xSecCurves: print curve.Eval(28) #curve.Draw() curve.Draw("sameR") plCMS = TPaveLabel(.15, .81, .25, .88, "CMS", "NBNDC") #plCMS.SetTextSize(0.8) plCMS.SetTextAlign(12) plCMS.SetTextFont(62) plCMS.SetFillColor(0) plCMS.SetFillStyle(0) plCMS.SetBorderSize(0) plCMS.Draw() plPrelim = TPaveLabel(.15, .76, .275, .82, "Supplementary", "NBNDC") plPrelim.SetTextSize(0.6) plPrelim.SetTextAlign(12) plPrelim.SetTextFont(52) plPrelim.SetFillColor(0) plPrelim.SetFillStyle(0) plPrelim.SetBorderSize(0) #plPrelim.Draw() cCL.SetTickx(1) cCL.SetTicky(1) cCL.RedrawAxis() cCL.Update() #leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC") leg = TLegend(0.440517, 0.523051, 0.834885, 0.878644, "", "brNDC") # leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC") leg.SetTextSize(0.032) if not obs2 == "": if ratioLabel == "": ratioLabel = "Variant/Default" ratioLabels = ratioLabel.split("/") print ratioLabels leg.AddEntry(GraphObs, "%s Observed 95%% CL limit" % ratioLabels[1], "l") leg.AddEntry(GraphObs2, "%s Observed 95%% CL limit" % ratioLabels[0], "l") else: if not EXPONLY: leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l") leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l") if (FULL): leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f") leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f") leg.AddEntry(xSecCurves[0], labels[interference], "l") leg.SetLineWidth(0) leg.SetLineStyle(0) leg.SetFillStyle(0) leg.SetLineColor(0) leg.Draw("hist") if "Moriond" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "35.9 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif "2017" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "42.1 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "41.5 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "41.5 fb^{-1} (13 TeV, ee) + 42.1 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") else: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") plLumi.SetTextSize(0.5) plLumi.SetTextFont(42) plLumi.SetFillColor(0) plLumi.SetBorderSize(0) plLumi.Draw() plotPad.RedrawAxis() if not obs2 == "": ratioPad.cd() line = ROOT.TLine(200, 1, 5500, 1) line.SetLineStyle(ROOT.kDashed) ROOT.gStyle.SetTitleSize(0.12, "Y") ROOT.gStyle.SetTitleYOffset(0.35) ROOT.gStyle.SetNdivisions(000, "Y") ROOT.gStyle.SetNdivisions(408, "Y") ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel) line.Draw("same") ratioGraph.Draw("sameP") cCL.Update() printPlots(cCL, output)
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) latex.SetTextFont(42) latex.SetTextAlign(33) latex.SetTextSize(0.04)
def limit(channel, signal): multF = 1. # in fb filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt" if (options.mediator == 'SC'): filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt" elif (options.mediator == 'PS'): filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_pseudo" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt" else: print 'WRONG mediator type' mass, val = fillValues(filename) Obs0s = TGraph() Exp0s = TGraph() Exp1s = TGraphAsymmErrors() Exp2s = TGraphAsymmErrors() Sign = TGraph() pVal = TGraph() Best = TGraphAsymmErrors() for i, m in enumerate(mass): if not m in val: print "Key Error:", m, "not in value map" continue n = Exp0s.GetN() Obs0s.SetPoint(n, m, val[m][0] * multF) Exp0s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPoint(n, m, val[m][3] * multF) Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF, val[m][4] * multF - val[m][3] * multF) Exp2s.SetPoint(n, m, val[m][3] * multF) Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF, val[m][5] * multF - val[m][3] * multF) #Sign.SetPoint(n, m, val[m][6]) #pVal.SetPoint(n, m, val[m][7]) #Best.SetPoint(n, m, val[m][8]) #Best.SetPointError(m, 0., 0., abs(val[m][9]), abs(val[m][10])) Exp2s.SetLineWidth(2) Exp2s.SetLineStyle(1) Obs0s.SetLineWidth(3) Obs0s.SetMarkerStyle(0) Obs0s.SetLineColor(1) Exp0s.SetLineStyle(2) Exp0s.SetLineWidth(3) Exp1s.SetFillColor(417) #kGreen+1 Exp1s.SetLineColor(417) #kGreen+1 Exp2s.SetFillColor(800) #kOrange Exp2s.SetLineColor(800) #kOrange Exp2s.GetXaxis().SetTitle("m_{#phi} (GeV)") Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25) Exp2s.GetXaxis().SetNoExponent(True) Exp2s.GetXaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetTitle("#sigma/#sigma_{th}") Exp2s.GetYaxis().SetTitleOffset(1.5) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetMoreLogLabels() Sign.SetLineWidth(2) Sign.SetLineColor(629) Sign.GetXaxis().SetTitle("m_{#phi} (GeV)") Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1) Sign.GetYaxis().SetTitle("Significance") pVal.SetLineWidth(2) pVal.SetLineColor(629) pVal.GetXaxis().SetTitle("m_{#phi} (GeV)") pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1) pVal.GetYaxis().SetTitle("local p-Value") Best.SetLineWidth(2) Best.SetLineColor(629) Best.SetFillColor(629) Best.SetFillStyle(3003) Best.GetXaxis().SetTitle("m_{#phi} (GeV)") Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1) Best.GetYaxis().SetTitle("Best Fit (pb)") c1 = TCanvas("c1", "Exclusion Limits", 800, 600) c1.cd() #SetPad(c1.GetPad(0)) c1.GetPad(0).SetTopMargin(0.06) c1.GetPad(0).SetRightMargin(0.05) c1.GetPad(0).SetTicks(1, 1) #c1.GetPad(0).SetGridx() #c1.GetPad(0).SetGridy() c1.GetPad(0).SetLogx() c1.GetPad(0).SetLogy() Exp2s.Draw("A3") Exp1s.Draw("SAME, 3") Exp0s.Draw("SAME, L") if not options.blind: Obs0s.Draw("SAME, L") #Theory[0].Draw("SAME, L") #Theory[1].Draw("SAME, L") #setHistStyle(Exp2s) Exp2s.GetXaxis().SetTitleSize(0.045) Exp2s.GetXaxis().SetMoreLogLabels(True) Exp2s.GetXaxis().SetNoExponent(True) Exp2s.GetYaxis().SetTitleSize(0.04) Exp2s.GetXaxis().SetLabelSize(0.04) Exp2s.GetYaxis().SetLabelSize(0.04) Exp2s.GetXaxis().SetTitleOffset(1) Exp2s.GetYaxis().SetTitleOffset(1.25) Exp2s.GetYaxis().SetMoreLogLabels(True) Exp2s.GetYaxis().SetNoExponent(True) Exp2s.GetYaxis().SetRangeUser(0.1, 1000.) #else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2) Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1]) drawAnalysis("tDM") drawRegion(channel, True) drawCMS(LUMI, "Preliminary") if True: if (options.mediator == 'SC'): massT, valT = fillValues("./limitOutput_" + options.name + "/" + signal.replace('tttDM', 'tDM') + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt") elif (options.mediator == 'PS'): massT, valT = fillValues("./limitOutput_" + options.name + "/" + signal.replace('tttDM', 'tDM') + "_MChi1_MPhi%d_pseudo" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt") ExpT, ObsT = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(massT): if not m in val: continue ExpT.SetPoint(ExpT.GetN(), m, valT[m][3] * multF) ObsT.SetPoint(ObsT.GetN(), m, valT[m][0] * multF) ExpT.SetLineWidth(3) ExpT.SetLineColor(602) #602 ExpT.SetLineStyle(5) ObsT.SetLineWidth(3) ObsT.SetLineColor(602) ExpT.SetMarkerStyle(21) ObsT.SetMarkerStyle(22) ExpT.SetMarkerColor(602) ObsT.SetMarkerColor(602) ExpT.Draw("SAME, PC") #if not options.blind: ObsT.Draw("SAME, P") if (options.mediator == 'SC'): massTTT, valTTT = fillValues("./limitOutput_" + options.name + "/" + signal.replace('tttDM', 'ttDM') + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt") elif (options.mediator == 'PS'): massTTT, valTTT = fillValues("./limitOutput_" + options.name + "/" + signal.replace('tttDM', 'ttDM') + "_MChi1_MPhi%d_pseudo" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt") ExpTTT, ObsTTT = TGraphAsymmErrors(), TGraphAsymmErrors() for i, m in enumerate(massTTT): if not m in val: continue ExpTTT.SetPoint(ExpTTT.GetN(), m, valTTT[m][3] * multF) ObsTTT.SetPoint(ObsTTT.GetN(), m, valTTT[m][0] * multF) ExpTTT.SetLineWidth(3) ExpTTT.SetLineColor(634) #602 ExpTTT.SetLineStyle(5) ObsTTT.SetLineWidth(3) ObsTTT.SetLineColor(634) ExpTTT.SetMarkerStyle(21) ObsTTT.SetMarkerStyle(22) ExpTTT.SetMarkerColor(634) ObsTTT.SetMarkerColor(634) ExpTTT.Draw("SAME, PC") #if not options.blind: ObsTTT.Draw("SAME, P") # legend top = 0.9 nitems = 4 + 2 leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.95, top) leg.SetBorderSize(0) leg.SetFillStyle(0) #1001 leg.SetFillColor(0) leg.SetHeader("95% CL limits") leg.AddEntry(Obs0s, "Observed", "l") leg.AddEntry(Exp0s, "Expected (t+DM, tt+DM)", "l") leg.AddEntry(Exp1s, "#pm 1 s. d.", "f") leg.AddEntry(Exp2s, "#pm 2 s. d.", "f") if True: leg.AddEntry(ExpT, "Expected (t+DM)", "p") leg.AddEntry(ExpTTT, "Expected (tt+DM)", "p") leg.Draw() c1.GetPad(0).RedrawAxis() c1.GetPad(0).Update() if gROOT.IsBatch(): c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" + options.mediator + "_" + options.bjets + ".png") c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" + options.mediator + "_" + options.bjets + ".pdf") if not gROOT.IsBatch(): raw_input("Press Enter to continue...") # print "p1s[", # for i in range(Exp0s.GetN()): # print Exp0s.GetY()[i]+Exp1s.GetErrorYhigh(i), ",", # print "]," # print "m1s[", # for i in range(Exp0s.GetN()): # print Exp0s.GetY()[i]-Exp1s.GetErrorYlow(i), ",", # print "]," # print "[", # for i in range(Exp0s.GetN()): # print Exp0s.GetY()[i], ",", # print "]" return # ---------- Significance ---------- c2 = TCanvas("c2", "Significance", 800, 600) c2.cd() c2.GetPad(0).SetTopMargin(0.06) c2.GetPad(0).SetRightMargin(0.05) c2.GetPad(0).SetTicks(1, 1) c2.GetPad(0).SetGridx() c2.GetPad(0).SetGridy() Sign.GetYaxis().SetRangeUser(0., 5.) Sign.Draw("AL3") drawCMS(LUMI, "Preliminary") drawAnalysis(channel[1:3]) if gROOT.IsBatch(): c2.Print("plotsLimit_" + options.name + "/Significance/" + channel + "_" + options.mediator + "_" + options.bjets + ".png") c2.Print("plotsLimit_" + options.name + "/Significance/" + channel + "_" + options.mediator + "_" + options.bjets + ".pdf") # c2.Print("plotsLimit/Significance/"+channel+suffix+".root") # c2.Print("plotsLimit/Significance/"+channel+suffix+".C") # ---------- p-Value ---------- c3 = TCanvas("c3", "p-Value", 800, 600) c3.cd() c3.GetPad(0).SetTopMargin(0.06) c3.GetPad(0).SetRightMargin(0.05) c3.GetPad(0).SetTicks(1, 1) c3.GetPad(0).SetGridx() c3.GetPad(0).SetGridy() c3.GetPad(0).SetLogy() pVal.Draw("AL3") pVal.GetYaxis().SetRangeUser(2.e-7, 0.5) ci = [ 1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303, 0.000000001973 ] line = TLine() line.SetLineColor(922) line.SetLineStyle(7) text = TLatex() text.SetTextColor(922) text.SetTextSize(0.025) text.SetTextAlign(12) for i in range(1, len(ci) - 1): line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i] / 2, pVal.GetXaxis().GetXmax(), ci[i] / 2) text.DrawLatex(pVal.GetXaxis().GetXmax() * 1.01, ci[i] / 2, "%d #sigma" % i) drawCMS(LUMI, "Preliminary") drawAnalysis(channel[1:3]) if gROOT.IsBatch(): c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix + "_" + options.mediator + "_" + options.bjets + ".png") c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix + "_" + options.mediator + "_" + options.bjets + ".pdf") # c3.Print("plotsLimit/pValue/"+channel+suffix+".root") # c3.Print("plotsLimit/pValue/"+channel+suffix+".C") # --------- Best Fit ---------- c4 = TCanvas("c4", "Best Fit", 800, 600) c4.cd() c4.GetPad(0).SetTopMargin(0.06) c4.GetPad(0).SetRightMargin(0.05) c4.GetPad(0).SetTicks(1, 1) c4.GetPad(0).SetGridx() c4.GetPad(0).SetGridy() Best.Draw("AL3") drawCMS(LUMI, "Preliminary") drawAnalysis(channel[1:3]) if gROOT.IsBatch(): c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel + suffix + "_" + options.mediator + "_" + options.bjets + ".png") c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel + suffix + "_" + options.mediator + "_" + options.bjets + ".pdf") # c4.Print("plotsLimit/BestFit/"+channel+suffix+".root") # c4.Print("plotsLimit/BestFit/"+channel+suffix+".C") if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def makeLimitPlot(output, obs, exp, chan, printStats=False, obs2="", ratioLabel=""): fileObs = open(obs, 'r') fileExp = open(exp, 'r') observedx = [] observedy = [] obsLimits = {} for entry in fileObs: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in obsLimits: obsLimits[massPoint] = [] obsLimits[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits) for massPoint in sorted(obsLimits): observedx.append(massPoint) observedy.append(numpy.mean(obsLimits[massPoint])) if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits[massPoint]), " std dev: ", numpy.std( obsLimits[massPoint]), " from: ", obsLimits[massPoint] if not obs2 == "": fileObs2 = open(obs2, 'r') observedx2 = [] observedy2 = [] obsLimits2 = {} for entry in fileObs2: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in obsLimits2: obsLimits2[massPoint] = [] obsLimits2[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits2) for massPoint in sorted(obsLimits2): observedx2.append(massPoint) observedy2.append(numpy.mean(obsLimits2[massPoint])) if (numpy.std(obsLimits2[massPoint]) / numpy.mean(obsLimits2[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits2[massPoint]), " std dev: ", numpy.std( obsLimits2[massPoint] ), " from: ", obsLimits2[massPoint] limits = {} expectedx = [] expectedy = [] expected1SigLow = [] expected1SigHigh = [] expected2SigLow = [] expected2SigHigh = [] for entry in fileExp: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in limits: limits[massPoint] = [] limits[massPoint].append(limitEntry) if printStats: print "len limits:", len(limits) for massPoint in sorted(limits): limits[massPoint].sort() numLimits = len(limits[massPoint]) nrExpts = len(limits[massPoint]) medianNr = int(nrExpts * 0.5) #get indexes: upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5)) lower1Sig = int(nrExpts * (1 - 0.68) * 0.5) upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5)) lower2Sig = int(nrExpts * (1 - 0.95) * 0.5) if printStats: print massPoint, ":", limits[massPoint][lower2Sig], limits[ massPoint][lower1Sig], limits[massPoint][medianNr], limits[ massPoint][upper1Sig], limits[massPoint][upper2Sig] #fill lists: expectedx.append(massPoint) expectedy.append(limits[massPoint][medianNr]) expected1SigLow.append(limits[massPoint][lower1Sig]) expected1SigHigh.append(limits[massPoint][upper1Sig]) expected2SigLow.append(limits[massPoint][lower2Sig]) expected2SigHigh.append(limits[massPoint][upper2Sig]) expX = numpy.array(expectedx) expY = numpy.array(expectedy) values2 = [] xPointsForValues2 = [] values = [] xPointsForValues = [] if printStats: print "length of expectedx: ", len(expectedx) if printStats: print "length of expected1SigLow: ", len(expected1SigLow) if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh) #Here is some Voodoo via Sam: for x in range(0, len(expectedx)): values2.append(expected2SigLow[x]) xPointsForValues2.append(expectedx[x]) for x in range(len(expectedx) - 1, 0 - 1, -1): values2.append(expected2SigHigh[x]) xPointsForValues2.append(expectedx[x]) if printStats: print "length of values2: ", len(values2) for x in range(0, len(expectedx)): values.append(expected1SigLow[x]) xPointsForValues.append(expectedx[x]) for x in range(len(expectedx) - 1, 0 - 1, -1): values.append(expected1SigHigh[x]) xPointsForValues.append(expectedx[x]) if printStats: print "length of values: ", len(values) exp2Sig = numpy.array(values2) xPoints2 = numpy.array(xPointsForValues2) exp1Sig = numpy.array(values) xPoints = numpy.array(xPointsForValues) if printStats: print "xPoints2: ", xPoints2 if printStats: print "exp2Sig: ", exp2Sig if printStats: print "xPoints: ", xPoints if printStats: print "exp1Sig: ", exp1Sig GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig) GraphErr2Sig.SetFillColor(ROOT.kYellow + 1) GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig) GraphErr1Sig.SetFillColor(ROOT.kGreen) cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500) gStyle.SetOptStat(0) if not obs2 == "": plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1) ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3) plotPad.Draw() ratioPad.Draw() plotPad.cd() else: plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1) plotPad.Draw() plotPad.cd() expX = numpy.array(expectedx) expY = numpy.array(expectedy) GraphExp = TGraph(len(expX), expX, expY) GraphExp.SetLineWidth(3) GraphExp.SetLineStyle(2) GraphExp.SetLineColor(ROOT.kBlue) obsX = numpy.array(observedx) obsY = numpy.array(observedy) if printStats: print "obsX: ", obsX if printStats: print "obsY: ", obsY if SMOOTH: smooth_obs = TGraphSmooth("normal") GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY) GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0, 0.005) else: GraphObs = TGraph(len(obsX), obsX, obsY) GraphObs.SetLineWidth(3) if not obs2 == "": ratio = [] ratiox = [] for index, val in enumerate(observedy): mass = observedx[index] foundIndex = -1 for index2, mass2 in enumerate(observedx2): if mass == mass2: foundIndex = index2 if foundIndex > 0: ratio.append(observedy2[foundIndex] / val) ratiox.append(mass) ratioA = numpy.array(ratio) ratioX = numpy.array(ratiox) obsX2 = numpy.array(observedx2) obsY2 = numpy.array(observedy2) ratioGraph = TGraph(len(ratioX), ratioX, ratioA) if printStats: print "obsX2: ", obsX2 if printStats: print "obsY2: ", obsY2 if SMOOTH: smooth_obs2 = TGraphSmooth("normal") GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2) GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear", 0, 0.005) else: GraphObs2 = TGraph(len(obsX2), obsX2, obsY2) GraphObs2.SetLineWidth(3) smoother = TGraphSmooth("normal") smoother2 = TGraphSmooth("normal") zprimeX = [] zprimeY = [] fileZPrime = open('tools/xsec_SSM.txt', 'r') for entries in fileZPrime: entry = entries.split() zprimeX.append(float(entry[0])) zprimeY.append(float(entry[1]) * 1.3 / 1928) zpX = numpy.array(zprimeX) zpY = numpy.array(zprimeY) GraphZPrime = TGraph(481, zpX, zpY) GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear") GraphZPrimeSmooth.SetLineWidth(3) GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3) GraphZPrimeSmooth.SetLineStyle(2) zprimePsiX = [] zprimePsiY = [] fileZPrimePsi = open('tools/xsec_PSI.txt', 'r') for entries in fileZPrimePsi: entry = entries.split() zprimePsiX.append(float(entry[0])) zprimePsiY.append(float(entry[1]) * 1.3 / 1928) zpPsiX = numpy.array(zprimePsiX) zpPsiY = numpy.array(zprimePsiY) GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY) GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear") GraphZPrimePsiSmooth.SetLineWidth(3) GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue) #Draw the graphs: plotPad.SetLogy() if "Moriond" in output: DummyGraph = TH1F("DummyGraph", "", 100, 120, 4500) else: DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500) DummyGraph.GetXaxis().SetTitle("M [GeV]") if chan == "mumu": DummyGraph.GetYaxis().SetTitle( "#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)" ) elif chan == "elel": DummyGraph.GetYaxis().SetTitle( "#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)" ) elif chan == "elmu": DummyGraph.GetYaxis().SetTitle( "#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)" ) gStyle.SetOptStat(0) if "Moriond" in output: DummyGraph.GetXaxis().SetRangeUser(120, 4500) else: DummyGraph.GetXaxis().SetRangeUser(400, 4500) DummyGraph.SetMinimum(1e-8) DummyGraph.SetMaximum(4e-4) DummyGraph.GetXaxis().SetLabelSize(0.04) DummyGraph.GetXaxis().SetTitleSize(0.045) DummyGraph.GetXaxis().SetTitleOffset(1.) DummyGraph.GetYaxis().SetLabelSize(0.04) DummyGraph.GetYaxis().SetTitleSize(0.045) DummyGraph.GetYaxis().SetTitleOffset(1.) DummyGraph.Draw() if (FULL): GraphErr2Sig.Draw("F") GraphErr1Sig.Draw("F") GraphExp.Draw("lpsame") else: if obs2 == "": GraphExp.Draw("lp") GraphObs.Draw("plsame") if not obs2 == "": GraphObs2.SetLineColor(ROOT.kRed) GraphObs2.SetLineStyle(ROOT.kDashed) GraphObs2.Draw("plsame") if not SPIN2: GraphZPrimeSmooth.Draw("lsame") GraphZPrimePsiSmooth.Draw("lsame") cCL.SetTickx(1) cCL.SetTicky(1) cCL.RedrawAxis() cCL.Update() #leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC") leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC") # leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC") leg.SetTextSize(0.032) if not obs2 == "": if ratioLabel == "": ratioLabel = "Variant/Default" ratioLabels = ratioLabel.split("/") leg.AddEntry(GraphObs, "% Observed 95% CL limit" % ratioLabel[1], "l") leg.AddEntry(GraphObs2, "%s Observed 95% CL limit" % ratioLabel[0], "l") else: leg.AddEntry(GraphObs, "Observed 95% CL limit", "l") leg.AddEntry(GraphExp, "Expected 95% CL limit, median", "l") if (FULL): leg.AddEntry(GraphErr1Sig, "Expected 95% CL limit, 1 s.d.", "f") leg.AddEntry(GraphErr2Sig, "Expected 95% CL limit, 2 s.d.", "f") leg1 = TLegend(0.665517, 0.483051, 0.834885, 0.623051, "", "brNDC") leg1.SetTextSize(0.032) if not SPIN2: leg1.AddEntry(GraphZPrimePsiSmooth, "Z'_{#Psi} (LOx1.3)", "l") leg1.AddEntry(GraphZPrimeSmooth, "Z'_{SSM} (LOx1.3)", "l") leg.SetLineWidth(0) leg.SetLineStyle(0) leg.SetLineColor(0) leg.Draw("hist") leg1.SetLineWidth(0) leg1.SetLineStyle(0) leg1.SetLineColor(0) leg1.Draw("hist") if "Moriond" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") else: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") plLumi.SetTextSize(0.5) plLumi.SetTextFont(42) plLumi.SetFillColor(0) plLumi.SetBorderSize(0) plLumi.Draw() plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC") #plCMS.SetTextSize(0.8) plCMS.SetTextAlign(12) plCMS.SetTextFont(62) plCMS.SetFillColor(0) plCMS.SetBorderSize(0) plCMS.Draw() plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC") plPrelim.SetTextSize(0.6) plPrelim.SetTextAlign(12) plPrelim.SetTextFont(52) plPrelim.SetFillColor(0) plPrelim.SetBorderSize(0) plPrelim.Draw() if not obs2 == "": ratioPad.cd() line = ROOT.TLine(400, 1, 4500, 1) line.SetLineStyle(ROOT.kDashed) ROOT.gStyle.SetTitleSize(0.12, "Y") ROOT.gStyle.SetTitleYOffset(0.35) ROOT.gStyle.SetNdivisions(000, "Y") ROOT.gStyle.SetNdivisions(408, "Y") ratioPad.DrawFrame(400, 0.9, 4500, 1.1, "; ; %s" % ratioLabel) line.Draw("same") ratioGraph.Draw("sameP") cCL.Update() printPlots(cCL, output)
theory.SetLineWidth(3) observed_p = TGraphAsymmErrors(massv, obsv, masserrv, masserrv, obserrv, obserrv) observed_p.SetLineColor(ROOT.kBlack) observed_p.SetLineWidth(2) observed_p.SetMarkerStyle(20) expected_p = TGraphAsymmErrors(massv, expv, masserrv, masserrv, experrv, experrv) expected_p.SetLineColor(ROOT.kBlack) expected_p.SetLineWidth(2) expected_p.SetLineStyle(2) expected68 = TGraphAsymmErrors(massv, expv, masserrv, masserrv, exp68Lv, exp68Hv) expected68.SetFillColor(ROOT.kGreen) expected95 = TGraphAsymmErrors(massv, expv, masserrv, masserrv, exp95Lv, exp95Hv) expected95.SetFillColor(ROOT.kYellow) c4 = TCanvas("c4", "Diphoton c = 01 Limits", 1000, 800) c4.SetBottomMargin(0.15) c4.SetRightMargin(0.06) #c4.SetLogy(1) #expected95.SetMinimum(0.0001); expected95.SetMaximum(0.0057) expected95.Draw("a3") expected95.GetXaxis().SetTitle("Diphoton Mass [GeV/c^{2}]")
def makeLimitPlot(output, obs, exp, chan, printStats=False, obs2="", ratioLabel=""): #fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE") fileObs = open(obs, 'r') fileExp = open(exp, 'r') observedx = [] observedy = [] obsLimits = {} for entry in fileObs: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in obsLimits: obsLimits[massPoint] = [] obsLimits[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits) for massPoint in sorted(obsLimits): observedx.append(massPoint) observedy.append(numpy.mean(obsLimits[massPoint])) if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits[massPoint]), " std dev: ", numpy.std( obsLimits[massPoint]), " from: ", obsLimits[massPoint] if not obs2 == "": fileObs2 = open(obs2, 'r') observedx2 = [] observedy2 = [] obsLimits2 = {} for entry in fileObs2: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in obsLimits2: obsLimits2[massPoint] = [] obsLimits2[massPoint].append(limitEntry) if printStats: print "len obsLimits:", len(obsLimits2) for massPoint in sorted(obsLimits2): observedx2.append(massPoint) observedy2.append(numpy.mean(obsLimits2[massPoint])) if (numpy.std(obsLimits2[massPoint]) / numpy.mean(obsLimits2[massPoint]) > 0.05): print massPoint, " mean: ", numpy.mean( obsLimits2[massPoint]), " std dev: ", numpy.std( obsLimits2[massPoint] ), " from: ", obsLimits2[massPoint] limits = {} expectedx = [] expectedy = [] expected1SigLow = [] expected1SigHigh = [] expected2SigLow = [] expected2SigHigh = [] for entry in fileExp: massPoint = float(entry.split()[0]) limitEntry = float(entry.split()[1]) if massPoint not in limits: limits[massPoint] = [] limits[massPoint].append(limitEntry) if printStats: print "len limits:", len(limits) for massPoint in sorted(limits): limits[massPoint].sort() numLimits = len(limits[massPoint]) nrExpts = len(limits[massPoint]) medianNr = int(nrExpts * 0.5) #get indexes: upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5)) lower1Sig = int(nrExpts * (1 - 0.68) * 0.5) upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5)) lower2Sig = int(nrExpts * (1 - 0.95) * 0.5) if printStats: print massPoint, ":", limits[massPoint][lower2Sig], limits[ massPoint][lower1Sig], limits[massPoint][medianNr], limits[ massPoint][upper1Sig], limits[massPoint][upper2Sig] #fill lists: expectedx.append(massPoint) print massPoint, limits[massPoint][medianNr] expectedy.append(limits[massPoint][medianNr]) expected1SigLow.append(limits[massPoint][lower1Sig]) expected1SigHigh.append(limits[massPoint][upper1Sig]) expected2SigLow.append(limits[massPoint][lower2Sig]) expected2SigHigh.append(limits[massPoint][upper2Sig]) expX = numpy.array(expectedx) expY = numpy.array(expectedy) values2 = [] xPointsForValues2 = [] values = [] xPointsForValues = [] xPointsForErrors = [] if printStats: print "length of expectedx: ", len(expectedx) if printStats: print "length of expected1SigLow: ", len(expected1SigLow) if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh) #Here is some Voodoo via Sam: for x in range(0, len(expectedx)): values2.append(expected2SigLow[x]) xPointsForValues2.append(expectedx[x]) xPointsForErrors.append(0) for x in range(len(expectedx) - 1, 0 - 1, -1): values2.append(expected2SigHigh[x]) xPointsForValues2.append(expectedx[x]) if printStats: print "length of values2: ", len(values2) for x in range(0, len(expectedx)): values.append(expected1SigLow[x]) xPointsForValues.append(expectedx[x]) for x in range(len(expectedx) - 1, 0 - 1, -1): values.append(expected1SigHigh[x]) xPointsForValues.append(expectedx[x]) if printStats: print "length of values: ", len(values) exp2Sig = numpy.array(values2) xPoints2 = numpy.array(xPointsForValues2) exp1Sig = numpy.array(values) xPoints = numpy.array(xPointsForValues) xPointsErrors = numpy.array(xPointsForErrors) if printStats: print "xPoints2: ", xPoints2 if printStats: print "exp2Sig: ", exp2Sig if printStats: print "xPoints: ", xPoints if printStats: print "exp1Sig: ", exp1Sig GraphErr2SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY, numpy.array(xPointsErrors), numpy.array(xPointsErrors), numpy.array(expected2SigLow), numpy.array(expected2SigHigh)) GraphErr1SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY, numpy.array(xPointsErrors), numpy.array(xPointsErrors), numpy.array(expected1SigLow), numpy.array(expected1SigHigh)) GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig) GraphErr2Sig.SetFillColor(ROOT.kOrange) GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig) GraphErr1Sig.SetFillColor(ROOT.kGreen + 1) #cCL=TCanvas("cCL", "cCL",0,0,567,384) cCL = TCanvas("cCL", "cCL", 0, 0, 600, 450) gStyle.SetOptStat(0) gStyle.SetPadRightMargin(0.063) gStyle.SetPadLeftMargin(0.14) gStyle.SetPadBottomMargin(0.12) if not obs2 == "": plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1) ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3) plotPad.Draw() ratioPad.Draw() plotPad.cd() else: plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1) plotPad.Draw() plotPad.cd() expX = numpy.array(expectedx) expY = numpy.array(expectedy) GraphExp = TGraph(len(expX), expX, expY) GraphExp.SetLineWidth(3) GraphExp.SetLineStyle(2) GraphExp.SetLineColor(ROOT.kBlue) obsX = numpy.array(observedx) obsY = numpy.array(observedy) if printStats: print "obsX: ", obsX if printStats: print "obsY: ", obsY if SMOOTH: smooth_obs = TGraphSmooth("normal") GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY) GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0, 0.005) else: GraphObs = TGraph(len(obsX), obsX, obsY) GraphObs.SetLineWidth(3) if not obs2 == "": ratio = [] ratiox = [] for index, val in enumerate(observedy): mass = observedx[index] foundIndex = -1 for index2, mass2 in enumerate(observedx2): if mass == mass2: foundIndex = index2 if foundIndex > 0: ratio.append(observedy2[foundIndex] / val) ratiox.append(mass) ratioA = numpy.array(ratio) ratioX = numpy.array(ratiox) obsX2 = numpy.array(observedx2) obsY2 = numpy.array(observedy2) ratioGraph = TGraph(len(ratioX), ratioX, ratioA) if printStats: print "obsX2: ", obsX2 if printStats: print "obsY2: ", obsY2 if SMOOTH: smooth_obs2 = TGraphSmooth("normal") GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2) GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear", 0, 0.005) else: GraphObs2 = TGraph(len(obsX2), obsX2, obsY2) GraphObs2.SetLineWidth(3) if SPIN2: signals = ["RS_kMpl01", "RS_kMpl005", "RS_kMpl001"] elif GUT: signals = ["ssm", "psi", "kai", "eta", "I", "S", "N"] else: signals = ["ssm", "psi"] xSecCurves = [] for signal in signals: xSecCurves.append(getXSecCurve(signal, kFacs[signal])) #xSecCurves.append(getXSecCurve(signal,kFacs[signal],massDependent=True)) #Draw the graphs: plotPad.SetLogy() DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500) DummyGraph.GetXaxis().SetTitle("M [GeV]") if SPIN2: DummyGraph.GetYaxis().SetTitle( "[#sigma#upoint#font[12]{B}] G_{KK} / [#sigma#upoint#font[12]{B}] Z" ) else: DummyGraph.GetYaxis().SetTitle( "[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z") # if SPIN2: # if chan=="mumu": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)") # elif chan=="elel": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)") # elif chan=="elmu": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)") # else: # if chan=="mumu": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)") # elif chan=="elel": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)") # elif chan=="elmu": # DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)") gStyle.SetOptStat(0) DummyGraph.GetXaxis().SetRangeUser(200, 5500) DummyGraph.SetMinimum(1e-8) DummyGraph.SetMaximum(1e-4) DummyGraph.GetXaxis().SetLabelSize(0.055) DummyGraph.GetXaxis().SetTitleSize(0.055) DummyGraph.GetXaxis().SetTitleOffset(1.05) DummyGraph.GetYaxis().SetLabelSize(0.055) DummyGraph.GetYaxis().SetTitleSize(0.055) DummyGraph.GetYaxis().SetTitleOffset(1.3) DummyGraph.Draw() if (FULL): GraphErr2Sig.Draw("F") GraphErr1Sig.Draw("F") GraphExp.Draw("lpsame") else: if obs2 == "": GraphExp.Draw("lp") if not EXPONLY: GraphObs.Draw("plsame") if not obs2 == "": GraphObs2.SetLineColor(ROOT.kRed) GraphObs2.SetLineStyle(ROOT.kDashed) GraphObs2.Draw("plsame") for curve in xSecCurves: curve.Draw("lsame") plCMS = TPaveLabel(.16, .81, .27, .88, "CMS", "NBNDC") #plCMS.SetTextSize(0.8) plCMS.SetTextAlign(12) plCMS.SetTextFont(62) plCMS.SetFillColor(0) plCMS.SetFillStyle(0) plCMS.SetBorderSize(0) plCMS.Draw() plPrelim = TPaveLabel(.16, .76, .27, .82, "Preliminary", "NBNDC") plPrelim.SetTextSize(0.6) plPrelim.SetTextAlign(12) plPrelim.SetTextFont(52) plPrelim.SetFillColor(0) plPrelim.SetFillStyle(0) plPrelim.SetBorderSize(0) if "2017" in output or "Combination" in output: plPrelim.Draw() cCL.SetTickx(1) cCL.SetTicky(1) cCL.RedrawAxis() cCL.Update() #leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC") #leg=TLegend(0.540517,0.623051,0.834885,0.878644,"","brNDC") Default leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC") if SPIN2: leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC") # leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC") leg.SetTextSize(0.0425) if not obs2 == "": if ratioLabel == "": ratioLabel = "Variant/Default" ratioLabels = ratioLabel.split("/") print ratioLabels leg.AddEntry(GraphObs, "%s Obs. 95%% CL limit" % ratioLabels[1], "l") leg.AddEntry(GraphObs2, "%s Obs. 95%% CL limit" % ratioLabels[0], "l") else: if not EXPONLY: leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l") leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l") if (FULL): leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f") leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f") leg1 = TLegend(0.7, 0.4, 0.9, 0.55, "", "brNDC") leg1.SetTextSize(0.05) if GUT: leg1 = TLegend(0.6, 0.35, 0.75, 0.623051, "", "brNDC") if SPIN2: leg1 = TLegend(0.7, 0.35, 0.9, 0.58, "G_{KK} (LO x 1.6)", "brNDC") leg1.SetTextSize(0.045) for index, signal in enumerate(signals): xSecCurves[index].SetName(labels[signal]) xSecCurves[index].Write(labels[signal]) leg1.AddEntry(xSecCurves[index], labels[signal], "l") leg1.SetBorderSize(0) leg.SetLineWidth(0) leg.SetLineStyle(0) leg.SetFillStyle(0) leg.SetLineColor(0) leg.Draw("hist") leg1.SetLineWidth(0) leg1.SetLineStyle(0) leg1.SetFillStyle(0) leg1.SetLineColor(0) leg1.Draw("hist") if "Moriond" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .885, .9, .99, "36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .885, .9, .99, "35.9 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .27, .885, .9, .99, "35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})", "NBNDC") elif "2017" in output or "Combination" in output: if (chan == "mumu"): plLumi = TPaveLabel(.65, .885, .9, .99, "42.4 fb^{-1} (13 TeV, #mu^{+}#mu^{-})", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .885, .9, .99, "41.4 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .27, .885, .9, .99, "77.3 fb^{-1} (13 TeV, ee) + 78.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})", "NBNDC") else: if (chan == "mumu"): plLumi = TPaveLabel(.65, .905, .9, .99, "13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") elif (chan == "elel"): plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)", "NBNDC") elif (chan == "elmu"): plLumi = TPaveLabel( .4, .905, .9, .99, "12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC") plLumi.SetTextSize(0.5) plLumi.SetTextFont(42) plLumi.SetFillColor(0) plLumi.SetBorderSize(0) plLumi.Draw() plotPad.SetTicks(1, 1) plotPad.RedrawAxis() if not obs2 == "": ratioPad.cd() line = ROOT.TLine(200, 1, 5500, 1) line.SetLineStyle(ROOT.kDashed) ROOT.gStyle.SetTitleSize(0.12, "Y") ROOT.gStyle.SetTitleYOffset(0.35) ROOT.gStyle.SetNdivisions(000, "Y") ROOT.gStyle.SetNdivisions(408, "Y") ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel) line.Draw("same") ratioGraph.Draw("sameP") #GraphErr2SigForHEPData.SetName("graph2Sig") #GraphErr2SigForHEPData.Write("graph2Sig") #GraphErr1SigForHEPData.SetName("graph1Sig") #GraphErr1SigForHEPData.Write("graph1Sig") #GraphExp.SetName("graphExp") #GraphExp.Write("graphExp") #GraphObs.SetName("graphObs") #GraphObs.Write("graphObs") #fileForHEPData.Write() #fileForHEPData.Close() cCL.Update() printPlots(cCL, output)
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)
def makePlot1D(filepath, foutname, plottitle='', masstitle=''): br = 1 if 'Resonant' in plottitle else 0.68 limits = parseLimitFiles2D(filepath, br) xaxis = [] xseclist = [] xsecerr = [] cent = [] obs = [] up1 = [] up2 = [] down1 = [] down2 = [] maxval = 0 minval = 999 for m in sorted(limits): l = limits[m] xaxis.append(m) xseclist.append(l.xsec) xsecerr.append(l.xsec * .2) cent.append(l.cent) up1.append(l.up1 - l.cent) up2.append(l.up2 - l.cent) down1.append(l.cent - l.down1) down2.append(l.cent - l.down2) obs.append(l.obs) maxval = max(maxval, l.up2) minval = min(minval, l.down2) N = len(xaxis) up1Sigma = array('f', up1) up2Sigma = array('f', up2) down1Sigma = array('f', down1) down2Sigma = array('f', down2) cent = array('f', cent) obs = array('f', obs) xarray = array('f', xaxis) xsecarray = array('f', xseclist) xsecerrarray = array('f', xsecerr) zeros = array('f', [0 for i in xrange(N)]) graphXsec = TGraphErrors(N, xarray, xsecarray, zeros, xsecerrarray) graphCent = TGraph(N, xarray, cent) graphObs = TGraph(N, xarray, obs) graph1Sigma = TGraphAsymmErrors(N, xarray, cent, zeros, zeros, down1Sigma, up1Sigma) graph2Sigma = TGraphAsymmErrors(N, xarray, cent, zeros, zeros, down2Sigma, up2Sigma) c = TCanvas('c', 'c', 700, 600) c.SetLogy() c.SetLeftMargin(.15) graph2Sigma.GetXaxis().SetTitle(masstitle + ' [GeV]') graph2Sigma.GetYaxis().SetTitle( '95% C.L. upper limit [#sigma/#sigma_{theory}]') c2 = root.kOrange c1 = root.kGreen + 1 graph2Sigma.SetLineColor(c2) graph1Sigma.SetLineColor(c1) graph2Sigma.SetFillColor(c2) graph1Sigma.SetFillColor(c1) graph2Sigma.SetMinimum(0.5 * minval) graph2Sigma.SetMaximum(10 * maxval) graphCent.SetLineWidth(2) graphCent.SetLineStyle(2) graphObs.SetLineColor(1) graphObs.SetLineWidth(3) graphObs.SetMarkerStyle(20) graphObs.SetMarkerSize(1) graphObs.SetMarkerColor(1) graph1Sigma.SetLineStyle(0) graph2Sigma.SetLineStyle(0) leg = TLegend(0.55, 0.7, 0.9, 0.9) leg.AddEntry(graphCent, 'Expected', 'L') if not BLIND: leg.AddEntry(graphObs, 'Observed', 'Lp') leg.AddEntry(graph1Sigma, '1 std. dev.', 'F') leg.AddEntry(graph2Sigma, '2 std. dev.', 'F') leg.SetFillStyle(0) leg.SetBorderSize(0) graph2Sigma.Draw('A3') graph1Sigma.Draw('3 same') graphCent.Draw('same L') if not BLIND: graphObs.Draw('same Lp') subscript = 'SR' if 'Resonant' in plottitle else 'FC' coupling = '0.1' if 'Resonant' in plottitle else '0.25' graphXsec.SetLineColor(2) graphXsec.SetLineWidth(2) graphXsec.SetLineStyle(2) graphXsec.SetFillColor(2) graphXsec.SetFillStyle(3005) graphXsec.Draw('same L3') ''' if not scale: if 'Resonant' in plottitle: leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=%s}{m_{#chi}=100 GeV}'%(subscript,subscript,coupling),'l') else: leg.AddEntry(graphXsec,'Theory #splitline{a_{%s}=b_{%s}=%s}{m_{#chi}=10 GeV}'%(subscript,subscript,coupling),'l') ''' if not BLIND: findIntersect1D(graphObs, graphXsec, xaxis[0], xaxis[-1]) findIntersect1D(graphCent, graphXsec, xaxis[0], xaxis[-1]) leg.Draw() label = TLatex() label.SetNDC() label.SetTextSize(0.8 * c.GetTopMargin()) label.SetTextFont(62) label.SetTextAlign(11) label.DrawLatex(0.15, 0.94, "CMS") label.SetTextFont(52) label.SetTextSize(0.6 * c.GetTopMargin()) # label.DrawLatex(0.25,0.94,"Preliminary") label.SetTextFont(42) label.SetTextSize(0.7 * c.GetTopMargin()) label.DrawLatex(0.19, 0.83, plottitle) if 'Resonant' in plottitle: label.DrawLatex(0.19, 0.75, "a_{SR} = b_{SR} = %s" % coupling) label.DrawLatex(0.19, 0.68, "m_{#chi}=100 GeV") else: label.DrawLatex(0.19, 0.75, "g_{DM}^{V}=1,g_{q}^{V}=0.25") label.DrawLatex(0.19, 0.68, "m_{#chi}=1 GeV") label.SetTextSize(0.6 * c.GetTopMargin()) label.SetTextFont(42) label.SetTextAlign(31) # align right label.DrawLatex(0.95, 0.94, "%.1f fb^{-1} (13 TeV)" % (plotConfig.lumi)) c.SaveAs(foutname + '.pdf') c.SaveAs(foutname + '.png')
exp1sigma = TGraphAsymmErrors(3, x, y_exp, zeros, zeros, y_err1down, y_err1up) exp2sigma = TGraphAsymmErrors(3, x, y_exp, zeros, zeros, y_err2down, y_err2up) explim = TGraph(3, x, y_exp) obslim = TGraph(3, x, y_obs) obslim.SetLineWidth(3) explim.SetLineWidth(3) explim.SetLineStyle(2) explim.SetTitle('') obslim.SetTitle('') exp2sigma.SetTitle('') exp1sigma.SetTitle('') #obslim.SetMinimum(0.001); #duesigma=TGraphAsymmErrors(3,) exp1sigma.SetFillColor(kGreen + 1) exp2sigma.SetFillColor(kOrange) exp2sigma.SetMaximum(150) exp2sigma.SetMinimum(0.07) exp2sigma.Draw('a3lp') exp2sigma.GetXaxis().SetTitle("Z' mass [TeV]") exp2sigma.GetXaxis().SetRangeUser(1.4, 2.6) exp2sigma.GetYaxis().SetTitle("Upper cross section limit [pb]") sizefactor = 1.6 exp2sigma.GetXaxis().SetTitleSize( sizefactor * exp2sigma.GetXaxis().GetTitleSize()) exp2sigma.GetYaxis().SetTitleSize( sizefactor * exp2sigma.GetYaxis().GetTitleSize()) exp2sigma.GetXaxis().SetLabelSize( sizefactor * exp2sigma.GetXaxis().GetLabelSize())
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...")
vexh = array('d',exh) vey1l = array('d',ey1l) vey1h = array('d',ey1h) vey2l = array('d',ey2l) vey2h = array('d',ey2h) g1 = TGraphAsymmErrors(len(vx),vx,vy1,vexl,vexh,vey1l,vey1h) g2 = TGraphAsymmErrors(len(vx),vx,vy2,vexl,vexh,vey2l,vey2h) gObs = TGraph(len(vx),vx,vyObs) gExp = TGraph(len(vx),vx,vyExp) gxs = TGraph(len(vx),vx,vxs) gExpDinko = TGraph(len(massesTeV_v),massesTeV_v,xs_exp_limits) for i in range(0,len(massesTeV_v)): print "exp limit Dinko: "+str(xs_exp_limits[i]) g2.SetFillColor(ROOT.kYellow) g2.SetLineColor(ROOT.kYellow) g1.SetFillColor(ROOT.kGreen) g1.SetLineColor(ROOT.kGreen) gExp.SetLineWidth(2) gExp.SetLineStyle(9) gExpDinko.SetLineWidth(2) gExpDinko.SetLineStyle(2) gObs.SetLineWidth(2) gObs.SetLineStyle(1) gObs.SetLineColor(ROOT.kBlue+1) gObs.SetMarkerColor(ROOT.kBlue+1) gObs.SetMarkerStyle(21) gObs.SetMarkerSize(1.5) gxs.SetLineStyle(5) gxs.SetLineWidth(3)