def drawTemplateFitter(tf, canvas = None, trueVal = None) :
if not canvas : canvas = r.TCanvas()
else: canvas.Clear()
canvas.cd(0)
canvas.Divide(2,2)
#------1
LL = r.TGraph(len(tf.pars), np.array(tf.pars), tf.templatesN2LL)
fit = r.TF1("fit","pol3",min(tf.pars),max(tf.pars))
for i,c in enumerate(tf.coefficients) : fit.SetParameter(i,c)
xMaxLL = [r.TGraph(2,np.array([val,val]),np.array([min(tf.templatesN2LL),max(tf.templatesN2LL)])) for val in [tf.value,tf.value+tf.error,tf.value-tf.error]]
for h in xMaxLL : h.SetLineColor(r.kBlue)
if trueVal != None :
xMaxLL.append(r.TGraph(2,np.array([trueVal,trueVal]),np.array([min(tf.templatesN2LL),max(tf.templatesN2LL)])))
xMaxLL[-1].SetLineColor(r.kRed)
xMaxLL[-1].SetLineWidth(2)
xMaxLL[1].SetLineStyle(r.kDashed)
xMaxLL[2].SetLineStyle(r.kDashed)
LL.SetTitle("best fit: %s | corrected: %s"%(utils.roundString(tf.value,tf.error, noSci=True),
utils.roundString(tf.value-tf.bias, tf.error*tf.pull,noSci=True)) +
(" | %0.3f"%trueVal if trueVal is not None else ""))
canvas.cd(1)
LL.Draw('A*')
for h in reversed(xMaxLL) : h.Draw('')
fit.Draw('same')
#------2
n2lls = utils.rHist("-2logLs", *np.histogram([toy.n2LL for toy in tf.ensemble], 100) )
n2ll = n2lls.Clone('-2logL') ; n2ll.Reset(); n2ll.SetBinContent(n2ll.FindFixBin(tf.n2LL), n2lls.GetMaximum());
n2ll.SetFillColor(r.kBlue); n2lls.SetTitle("p-value: %0.4f"%tf.p_value)
canvas.cd(2)
n2lls.Draw()
n2ll.Draw('same')
#------3
edges = range(len(tf.observed)+1)
observed = utils.rHist("observed", tf.observed, edges, True)
spars,stemplates = zip(*sorted(zip(tf.pars,tf.templates)))
templates = [utils.rHist("template%d"%i, templ, edges) for i,templ in enumerate(stemplates) if i in [0,len(spars)-1,len(spars)/2]]
observed.SetTitle("observed")
observed.SetMarkerStyle(20)
for i,templ in enumerate(templates) : templ.SetLineColor([r.kRed,r.kGreen,r.kBlue][i])
maxHeight = max(h.GetMaximum() for h in [observed]+templates)
for h in [observed]+templates : h.SetMaximum(1.1*maxHeight)
canvas.cd(3)
observed.Draw()
for t in templates : t.Draw("same")
#------4
relMean = np.mean(tf.relResiduals)
pull = utils.rHist("relative residuals", *np.histogram(tf.relResiduals,100,(relMean-5,relMean+5)))
canvas.cd(4)
pull.Draw()
canvas.Update()
return canvas,observed,templates,LL,fit,xMaxLL,n2lls,n2ll,pull
def printSteps(self, steps, printAll=False) :
if printAll and len(steps)>self.nLinesMax : self.printSteps(steps[:1-self.nLinesMax],printAll)
self.canvas.cd(0)
self.canvas.Clear()
text = r.TText()
text.SetNDC()
text.SetTextFont(102)
text.SetTextSize(0.45*text.GetTextSize())
pageWidth = 111
nSamples = len(self.someOrganizer.samples)
if self.printRatios : nSamples += 1
colWidth = min(25, pageWidth/nSamples)
space = 1
nametitle = "{0}: {1:<%d} {2}" % (3+max([len(s.name) for s in steps]))
for i,step in enumerate(steps[-self.nLinesMax:]) :
absI = i + (0 if len(steps) <= self.nLinesMax else len(steps)-self.nLinesMax)
text.SetTextColor(self.rowColors[absI%len(self.rowColors)])
letter = string.ascii_letters[absI]
x = 0.01
y = 0.98 - 0.33*(i+0.5+(absI/5) - ((absI-i)/5) )/self.nLinesMax
text.DrawTextNDC(x, y, nametitle.format(letter, step.name, step.title ))
self.cutDict[letter] = (step.name, step.title)
nums = []
ratios = [None]*len(self.samplesForRatios)
for k,sample in zip(step.yields,self.someOrganizer.samples) :
special = "lumi" in sample and not self.showErrorsOnDataYields
s = utils.roundString(*k, width=(colWidth-space), noSci = self.noSci or special, noErr = special) if k else "- "
if sample["name"] in self.samplesForRatios : ratios[self.samplesForRatios.index(sample["name"])] = k
nums.append(s.rjust(colWidth))
if self.printRatios and len(ratios)==2 :
s = "- "
if ratios[0] and ratios[1] and ratios[0][0] and ratios[1][0] :
value = ratios[0][0]/float(ratios[1][0])
error = value*math.sqrt((ratios[0][1]/float(ratios[0][0]))**2 + (ratios[1][1]/float(ratios[1][0]))**2)
ratio = (value, error)
s = utils.roundString(*ratio, width=(colWidth-space))
nums.append(s.rjust(colWidth))
text.DrawTextNDC(x, y-0.51, "%s: %s"%(letter, "".join(nums)))
self.yieldDict[letter] = nums
self.sampleList = [s["name"][:(colWidth-space)].rjust(colWidth) for s in self.someOrganizer.samples]
if self.printRatios and len(self.samplesForRatios)==2 :
self.sampleList += ("%s/%s"%self.sampleLabelsForRatios)[:(colWidth-space)].rjust(colWidth)
text.SetTextColor(r.kBlack)
text.DrawTextNDC(x, 0.5, " "+"".join(self.sampleList))
text.SetTextAlign(13)
text.DrawTextNDC(0.05, 0.03, "events / %.3f pb^{-1}"% self.someOrganizer.lumi )
self.flushPage()
def drawComponentSolver(cs, canvas = None) :
if not canvas : canvas = r.TCanvas()
canvas.cd(0)
canvas.Divide(2,2)
rTemplates = [utils.rHist("template%d"%i,d,range(len(d)+1)) for i,d in enumerate(cs.components)]
rObs = utils.rHist("observed",cs.observed,range(len(d)+1),True)
rObs.SetTitle("ML fractions: "+", ".join(utils.roundString(f,e,noSci=True) for f,e in zip(cs.fractions,cs.errors) ))
nlls = utils.rHist("-logLs", *np.histogram([-toy.logL for toy in cs.ensemble], 100) )
nll = nlls.Clone('-logL') ; nll.Reset(); nll.SetBinContent(nll.FindFixBin(-cs.logL), nlls.GetMaximum());
nll.SetFillColor(r.kBlue); nll.SetTitle("p-value: %0.4f"%cs.p_value)
pulls = [ utils.rHist("relative residuals %d"%i, *np.histogram(pull,100,(-5,5))) for i,pull in enumerate(cs.relResiduals.transpose())]
corr = cs.correlation
corrH = r.TH2D("correlations","correlations", len(corr), -0.5, len(corr)-0.5, len(corr), -0.5, len(corr)-0.5)
for i,j in itertools.product(range(len(corr)), repeat = 2) : corrH.SetBinContent(i+1,j+1,round(corr[i][j],3))
corrH.SetMaximum(1)
corrH.SetMinimum(-1)
canvas.cd(3)
corrH.Draw("colztext")
stats = []
for i,a,t in zip(range(len(cs.fractions)),pulls,rTemplates) :
t.SetFillColor(i+2)
t.SetLineColor(i+2)
a.SetLineColor(i+2)
a.SetMaximum(1.1*max(h.GetMaximum() for h in pulls))
canvas.cd(4); a.Draw("sames" if i else "")
canvas.Update()
st = a.GetListOfFunctions().FindObject("stats")
st.SetOptStat(1101)
st.SetLineColor(i+2)
st.SetY1NDC(0.85-0.16*i)
st.SetY2NDC(1.0-0.16*i)
stats.append( st.Clone("stats%d"%i) )
for s in stats : s.Draw()
canvas.cd(2) ; nll.Draw(); nlls.Draw("histsame")
rObs.SetMarkerStyle(20)
def draw(i,logY = False) :
canvas.cd(i).SetLogy(logY)
rObs.Draw("e")
for t in rTemplates : t.Draw("histsame")
rObs.Draw("esame")
base = utils.rHist("base",cs.base,range(len(cs.base)+1)) ; base.SetFillColor(r.kGray)
rTemplates = sorted(rTemplates,key=lambda t: -t.Integral()) + [base]
for t,h in reversed(zip(rTemplates[:-1],rTemplates[1:])) : t.Add(h)
draw(1, logY = False)
#draw(3, logY = True)
canvas.Update()
return [canvas,rObs,rTemplates,stats,pulls,nlls,nll,corrH]
def printSteps(self, steps, printAll=False) :
if printAll and len(steps)>self.nLinesMax : self.printSteps(steps[:1-self.nLinesMax],printAll)
self.canvas.cd(0)
self.canvas.Clear()
text = r.TText()
text.SetNDC()
text.SetTextFont(102)
text.SetTextSize(0.45*text.GetTextSize())
pageWidth = 111
colWidth = min(25, pageWidth/len(self.someOrganizer.samples))
space = 1
nametitle = "{0}: {1:<%d} {2}" % (3+max([len(s.name) for s in steps]))
for i,step in enumerate(steps[-self.nLinesMax:]) :
absI = i + (0 if len(steps) <= self.nLinesMax else len(steps)-self.nLinesMax)
letter = string.ascii_letters[absI]
x = 0.01
y = 0.98 - 0.33*(i+0.5+absI/5)/self.nLinesMax
text.DrawTextNDC(x, y, nametitle.format(letter, step.name, step.title ))
self.cutDict[letter] = (step.name, step.title)
nums = []
for k,sample in zip(step.yields,self.someOrganizer.samples) :
special = "lumi" in sample and not self.showErrorsOnDataYields
s = utils.roundString(*k, width=(colWidth-space), noSci = self.noSci or special, noErr = special) if k else "- "
nums.append(s.rjust(colWidth))
text.DrawTextNDC(x, y-0.49, "%s: %s"%(letter, "".join(nums)))
self.yieldDict[letter] = nums
self.sampleList = [s["name"][:(colWidth-space)].rjust(colWidth) for s in self.someOrganizer.samples]
text.DrawTextNDC(x, 0.5, " "+"".join(self.sampleList))
text.SetTextAlign(13)
text.DrawTextNDC(0.05, 0.03, "events / %.3f pb^{-1}"% self.someOrganizer.lumi )
self.flushPage()
def printSteps(self, steps, printAll=False) :
if printAll and len(steps)>self.nLinesMax : self.printSteps(steps[:1-self.nLinesMax],printAll)
self.canvas.cd(0)
self.canvas.Clear()
text = r.TText()
text.SetNDC()
text.SetTextFont(102)
text.SetTextSize(0.40*text.GetTextSize())
pageWidth = 120
nSamples = len(self.someOrganizer.samples) + len(self.foms)
colWidth = min(25, pageWidth/nSamples)
space = 1
nametitle = "{0}: {1:<%d} {2}" % (3+max([len(s.name) for s in steps]))
for i,step in enumerate(steps[-self.nLinesMax:]) :
absI = i + (0 if len(steps) <= self.nLinesMax else len(steps)-self.nLinesMax)
text.SetTextColor(self.rowColors[absI%len(self.rowColors)])
letter = string.ascii_letters[absI]
x = 0.02
y = 0.98 - 0.34*(i+0.5+(absI/self.rowCycle) - ((absI-i)/self.rowCycle) )/self.nLinesMax
nums = []
ratios = [None]*len(self.samplesForRatios)
for k,sample in zip(step.yields,self.someOrganizer.samples) :
special = "lumi" in sample and not self.showErrorsOnDataYields
s = utils.roundString(*k, width=(colWidth-space), noSci = self.noSci or special, noErr = special) if k else "- "
if sample["name"] in self.samplesForRatios : ratios[self.samplesForRatios.index(sample["name"])] = k
nums.append(s.rjust(colWidth))
if len(ratios)==2 and ratios[0] and ratios[1]:
num = float(ratios[0][0])
den = float(ratios[1][0])
numUnc = float(ratios[0][1])
denUnc = float(ratios[1][1])
for fom in self.foms:
s = "- "
if num and den:
value = fom["value"](num, den)
error = value*fom["uncRel"](num, den, numUnc, denUnc)
s = utils.roundString(value, error, width=(colWidth-space))
nums.append(s.rjust(colWidth))
if step.name in ['master','label']: self.pdfOptions = step.title
if step.name=='label' :
text.SetTextColor(r.kBlack)
font = text.GetTextFont()
text.SetTextFont(62)
label = "[ %s ]"%step.title
text.DrawTextNDC(0.01, y, label)
text.DrawTextNDC(0.01, y-0.51, label )
text.SetTextFont(font)
else:
text.DrawTextNDC(x, y-0.00, nametitle.format(letter, step.name, step.title ))
text.DrawTextNDC(x, y-0.51, "%s: %s"%(letter, "".join(nums)))
self.cutDict[letter] = (step.name, step.title)
self.yieldDict[letter] = nums
if absI > self.formerMaxAbsI :
text.SetTextColor(r.kBlack)
text.DrawTextNDC(0.008,y-0.00,'|')
text.DrawTextNDC(0.008,y-0.51,'|')
self.formerMaxAbsI = absI
self.sampleList = [s["name"][:(colWidth-space)].rjust(colWidth) for s in self.someOrganizer.samples]
if len(self.samplesForRatios)==2:
for fom in self.foms:
self.sampleList += (fom["label"](*self.sampleLabelsForRatios))[:(colWidth-space)].rjust(colWidth)
text.SetTextColor(r.kBlack)
text.DrawTextNDC(x, 0.5, " "+"".join(self.sampleList))
text.SetTextAlign(13)
text.DrawTextNDC(0.05, 0.03, "events / %.0f fb^{-1}" % (self.someOrganizer.lumi/1.0e3) )
self.flushPage()
'''Test the template fitter.'''
r.gStyle.SetPalette(1)
r.gROOT.SetStyle("Plain")
if len(sys.argv)<2 : print "Usage: templateFit [trueParValue=0] [ScaleFactor=100]"
truePar = float(sys.argv[1]) if len(sys.argv)>1 else 0
norm = int(sys.argv[2]) if len(sys.argv)>2 else 100
def template(p) : return np.array([100+norm*math.exp(-0.5*(x-p)**2) for x in range(-5,5)])
templates = [(p,template(p)) for p in np.arange(-1.0,1.1,0.1)]
observed = np.array([np.random.poisson(mu) for mu in template(truePar)])
TF = templateFitter(observed, *templates)
print "true value: ", truePar
print "measured : ", utils.roundString(TF.value,TF.error)
canvas = drawTemplateFitter(TF)
print "p-value :", TF.p_value
print "bias : ", TF.bias
print "pull : ", TF.pull
raw_input()
def format(d) : return "[ %s ]"%', '.join("%.3f"%f for f in d)
ensembles = templateEnsembles(500, *templates )
print "pars : ".rjust(20), format(ensembles.pars)
print "biases : ".rjust(20), format(ensembles.biases)
print "pulls : ".rjust(20), format(ensembles.pulls)
print "meanErrors : ".rjust(20), format(ensembles.meanError)