def rooFit106():
print ">>> setup model..."
x = RooRealVar("x", "x", -3, 3)
mean = RooRealVar("mean", "mean of gaussian", 1, -10, 10)
sigma = RooRealVar("sigma", "width of gaussian", 1, 0.1, 10)
gauss = RooGaussian("gauss", "gauss", x, mean, sigma)
data = gauss.generate(RooArgSet(x), 10000) # RooDataSet
gauss.fitTo(data)
print ">>> plot pdf and data..."
frame = x.frame(Name("frame"), Title("RooPlot with decorations"),
Bins(40)) # RooPlot
data.plotOn(frame)
gauss.plotOn(frame)
print ">>> RooGaussian::paramOn - add box with pdf parameters..."
# https://root.cern.ch/doc/master/classRooAbsPdf.html#aa43b2556a1b419bad2b020ba9b808c1b
# Layout(Double_t xmin, Double_t xmax, Double_t ymax)
# left edge of box starts at 20% of x-axis
gauss.paramOn(frame, Layout(0.55))
print ">>> RooDataSet::statOn - add box with data statistics..."
# https://root.cern.ch/doc/master/classRooAbsData.html#a538d58020b296a1623323a84d2bb8acb
# x size of box is from 55% to 99% of x-axis range, top of box is at 80% of y-axis range)
data.statOn(frame, Layout(0.20, 0.55, 0.8))
print ">>> add text and arrow..."
text = TText(2, 100, "Signal")
text.SetTextSize(0.04)
text.SetTextColor(kRed)
frame.addObject(text)
arrow = TArrow(2, 100, -1, 50, 0.01, "|>")
arrow.SetLineColor(kRed)
arrow.SetFillColor(kRed)
arrow.SetLineWidth(3)
frame.addObject(arrow)
print ">>> persist frame with all decorations in ROOT file..."
file = TFile("rooFit106.root", "RECREATE")
frame.Write()
file.Close()
# To read back and plot frame with all decorations in clean root session do
# [0] TFile f("rooFit106.root")
# [1] xframe->Draw()
print ">>> draw functions and toy data on canvas..."
canvas = TCanvas("canvas", "canvas", 100, 100, 800, 600)
gPad.SetLeftMargin(0.15)
gPad.SetRightMargin(0.05)
frame.GetYaxis().SetTitleOffset(1.6)
frame.GetYaxis().SetLabelOffset(0.010)
frame.GetYaxis().SetTitleSize(0.045)
frame.GetYaxis().SetLabelSize(0.042)
frame.GetXaxis().SetTitleSize(0.045)
frame.GetXaxis().SetLabelSize(0.042)
frame.Draw()
canvas.SaveAs("rooFit106.png")
class CBfunction:
doubleSidedCB = False
gaussian = False
nbins = 600
xmin = 0
xmax = 12000
xaxis_scale = 0.2
a_initial = 0.5
n_initial = 7
a2_initial = 0.5
n2_initial = 7
s_initial = 60
def __init__(self,data):
self.data = data ## data should be TChain already
def set_crystal(self,crystal):
self.crystal = crystal
def set_energy(self,energy):
self.energy = energy
def set_position(self,x=0,y=0,window=20):
self.xcenter = x
self.ycenter = y
self.window = window
def set_selection(self):
self.selection = "n_tracks==1 && fabs(X-(%.2f))<%.2f && fabs(Y-(%.2f))<%.2f"%(self.xcenter,self.window,self.ycenter,self.window)
def prepare_sumhistogram(self,dict_crystals_calibration,matrix):
self.set_selection()
self.hist = ROOT.TH1F("ampl_%s_%s"%(self.crystal,self.energy),"ampl_%s_%s"%(self.crystal,self.energy),self.nbins,self.xmin,self.xmax)
draw_function = '('
for enum,cryst in enumerate(matrix):
#draw_function +='fit_ampl[%s]*%.4f'%(cryst,dict_crystals_calibration[cryst])
draw_function +='((fit_ampl[%s] > 0) ? fit_ampl[%s] : amp_max[%s])*%.4f'%(cryst,cryst,cryst,dict_crystals_calibration[cryst])
if enum!=len(matrix)-1 : draw_function+='+'
# else : draw_function+=")*%.4f>>ampl_%s_%s"%(dict_crystals_calibration['conversion_factor'],self.crystal,self.energy)
else : draw_function+=")>>ampl_%s_%s"%(self.crystal,self.energy)
self.data.Draw(draw_function,self.selection,"goff")
self.peak_position = self.hist.GetXaxis().GetBinCenter(self.hist.GetMaximumBin())
self.ymax_value = self.hist.GetMaximum()
def prepare_histogram(self):
self.set_selection()
self.hist = ROOT.TH1F("ampl_%s_%s"%(self.crystal,self.energy),"ampl_%s_%s"%(self.crystal,self.energy),self.nbins,self.xmin,self.xmax)
self.data.Draw("fit_ampl[%s]>>ampl_%s_%s"%(self.crystal,self.crystal,self.energy),self.selection,"goff")
self.peak_position = self.hist.GetXaxis().GetBinCenter(self.hist.GetMaximumBin())
self.ymax_value = self.hist.GetMaximum()
def prepare_histogram_time(self):
self.set_selection()
self.hist = ROOT.TH1F("ampl_%s_%s"%(self.crystal,self.energy),"ampl_%s_%s"%(self.crystal,self.energy),self.nbins,self.xmin,self.xmax)
self.data.Draw("((fit_time[%s]-fit_time[MCP2]+fit_time[VFE_CLK])-int((fit_time[%s]-fit_time[MCP2]+fit_time[VFE_CLK])/6.238)*6.238)>>ampl_%s_%s"%(self.crystal,self.crystal,self.crystal,self.energy),self.selection,"goff")
self.peak_position = self.hist.GetXaxis().GetBinCenter(self.hist.GetMaximumBin())
self.ymax_value = self.hist.GetMaximum()
def plot_histogram_time(self):
self.hist.Draw("HISTsame")
def CBintialization(self):
round_energy = round(float(self.energy),-1)
if round_energy ==240 : round_energy = 250
self.x = RooRealVar("signal_%s_%dGeV"%(self.crystal,round_energy),"signal_%s_%dGeV"%(self.crystal,round_energy),max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.roohist = RooDataHist("roohist_fit_%s_%s"%(self.crystal,self.energy),"roohist_fit_%s_%s"%(self.crystal,self.energy),RooArgList(self.x),self.hist)
self.m = RooRealVar("mean_%s_%s"%(self.crystal,self.energy),"mean_%s_%s"%(self.crystal,self.energy),self.peak_position,max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.s = RooRealVar("sigma_%s_%s"%(self.crystal,self.energy),"sigma_%s_%s"%(self.crystal,self.energy),self.s_initial,0.001,1.) #500.
self.a = RooRealVar("alpha_%s_%s"%(self.crystal,self.energy),"alpha_%s_%s"%(self.crystal,self.energy),self.a_initial,-10.,10)
self.n = RooRealVar("exp_%s_%s"%(self.crystal,self.energy),"exp_%s_%s"%(self.crystal,self.energy),self.n_initial,0.,30)
self.sig = RooCBShape("signal_%s_%s"%(self.crystal,self.energy),"signal_%s_%s"%(self.crystal,self.energy),self.x,self.m,self.s,self.a,self.n)
def Gausintialization(self):
round_energy = round(float(self.energy),-1)
if round_energy ==240 : round_energy = 250
self.x = RooRealVar("signal_%s_%dGeV"%(self.crystal,round_energy),"signal_%s_%dGeV"%(self.crystal,round_energy),max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.roohist = RooDataHist("roohist_fit_%s_%s"%(self.crystal,self.energy),"roohist_fit_%s_%s"%(self.crystal,self.energy),RooArgList(self.x),self.hist)
self.m = RooRealVar("mean_%s_%s"%(self.crystal,self.energy),"mean_%s_%s"%(self.crystal,self.energy),self.peak_position,max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.s = RooRealVar("sigma_%s_%s"%(self.crystal,self.energy),"sigma_%s_%s"%(self.crystal,self.energy),self.s_initial,0.001,1.)
self.sig = RooGaussian("signal_%s_%s"%(self.crystal,self.energy),"signal_%s_%s"%(self.crystal,self.energy),self.x,self.m,self.s)
def CB2intialization(self):
round_energy = round(float(self.energy),-1)
self.x = RooRealVar("signal_%s_%dGeV"%(self.crystal,round_energy),"signal_%s_%dGeV"%(self.crystal,round_energy),max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.roohist = RooDataHist("roohist_fit_%s_%s"%(self.crystal,self.energy),"roohist_fit_%s_%s"%(self.crystal,self.energy),RooArgList(self.x),self.hist)
self.m = RooRealVar("mean_%s_%s"%(self.crystal,self.energy),"mean_%s_%s"%(self.crystal,self.energy),self.peak_position,max(0.,self.peak_position*(1-self.xaxis_scale)),self.peak_position*(1+self.xaxis_scale))
self.s = RooRealVar("sigma_%s_%s"%(self.crystal,self.energy),"sigma_%s_%s"%(self.crystal,self.energy),self.s_initial,10,500)
self.a = RooRealVar("alpha_%s_%s"%(self.crystal,self.energy),"alpha_%s_%s"%(self.crystal,self.energy),self.a_initial,-10.,10)
self.a2 = RooRealVar("alpha2_%s_%s"%(self.crystal,self.energy),"alpha2_%s_%s"%(self.crystal,self.energy),self.a2_initial,-10.,10)
self.n = RooRealVar("exp_%s_%s"%(self.crystal,self.energy),"exp_%s_%s"%(self.crystal,self.energy),self.n_initial,0.,30)
self.n2 = RooRealVar("exp2_%s_%s"%(self.crystal,self.energy),"exp2_%s_%s"%(self.crystal,self.energy),self.n2_initial,0.,30)
self.sig = ROOT.My_double_CB("signal_%s_%s"%(self.crystal,self.energy),"signal_%s_%s"%(self.crystal,self.energy),self.x,self.m,self.s,self.a,self.n,self.a2,self.n2)
def fitToData(self):
self.res = self.sig.fitTo(self.roohist)
def fitResults(self):
self.dict_fit_results = {}
self.dict_fit_results['CBmean'] = [self.m.getVal(),self.m.getError()]
self.dict_fit_results['CBsigma'] = [self.s.getVal(),self.s.getError()]
if (self.gaussian==False) :
self.dict_fit_results['CBalpha'] = [self.a.getVal(),self.a.getError()]
self.dict_fit_results['CBexp'] = [self.n.getVal(),self.n.getError()]
if (self.doubleSidedCB==True) :
self.dict_fit_results['CBalpha2'] = [self.a2.getVal(),self.a2.getError()]
self.dict_fit_results['CBexp2'] = [self.n2.getVal(),self.n2.getError()]
self.dict_fit_results['chi2'] = self.chi2
return self.dict_fit_results
def plot(self):
self.frame = self.x.frame()
self.roohist.plotOn(self.frame,RooFit.Name("roohist_chi2_%s_%s"%(self.crystal,self.energy)))
self.sig.plotOn(self.frame,RooFit.Name("signal_chi2_%s_%s"%(self.crystal,self.energy)))
ndf = 4
self.chi2 = self.frame.chiSquare("signal_chi2_%s_%s"%(self.crystal,self.energy),"roohist_chi2_%s_%s"%(self.crystal,self.energy),ndf) # 4 = nFitParameters from CB
self.sig.paramOn(self.frame,RooFit.Layout(0.65,0.99,0.8))
self.frame.getAttText().SetTextSize(0.02)
txt_chi2 = ROOT.TText(self.peak_position*(1.01-self.xaxis_scale),self.ymax_value*0.95,"Chi2 = %.1f"%self.chi2)
txt_chi2.SetTextSize(0.04)
txt_chi2.SetTextColor(ROOT.kRed)
self.frame.addObject(txt_chi2)
self.frame.Draw()
def plot_time(self):
self.frame = self.x.frame()
self.roohist.plotOn(self.frame,RooFit.Name("roohist_chi2_%s_%s"%(self.crystal,self.energy)))
self.frame.Draw()
