def fit(x, y):
from ROOT import TF1, TGraphAsymmErrors
g = TGraphAsymmErrors(len(x))
for i in xrange(len(x)):
g.SetPoint(i, x[i], y[i].nominal_value)
g.SetPointError(i, 0, 0, y[i].std_dev, y[i].std_dev)
fit = TF1("fit", "-[1]*x*x+[0]", -40, 120)
fit.SetParNames("z0", "a")
g.Fit(fit)
return fit
gDplusOverD0.Fit('fDplusOverD0', 'rq')
hFrameDstar = cRatios.cd(2).DrawFrame(
0., 0., 50., 1.5, ';#it{p}_{T} (GeV/#it{c}); D*^{+} / D^{0}')
hFrameDstar.GetYaxis().SetDecimals()
gDstarOverD0.Draw('p')
gDstarOverD0.Fit('fDstarOverD0', 'rq')
hFrameDs = cRatios.cd(3).DrawFrame(
0., 0., 50., 1.5, ';#it{p}_{T} (GeV/#it{c}); D_{s}^{+} / D^{0}')
hFrameDs.GetYaxis().SetDecimals()
gDsOverD0.Draw('p')
gDsOverD0.Fit('fDsOverD0', 'rq')
hFrameLc = cRatios.cd(4).DrawFrame(
0., 0., 50., 1.5, ';#it{p}_{T} (GeV/#it{c}); #Lambda_{c}^{+} / D^{0}')
hFrameLc.GetYaxis().SetDecimals()
gLcOverD0.Draw('p')
gLcOverD0.Fit('fLcOverD0', 'r')
dfDplus = dfD0FONLL.copy()
for col in dfDplus.columns:
if col not in ['ptmin', 'ptmax']:
dfDplus[col] = dfDplus.apply(lambda x: x[col] * gDplusOverD0.Eval(
(x['ptmax'] + x['ptmin']) / 2),
axis=1)
dfDs = dfD0FONLL.copy()
for col in dfDs.columns:
if col not in ['ptmin', 'ptmax']:
dfDs[col] = dfDs.apply(lambda x: x[col] * gDsOverD0.Eval(
(x['ptmax'] + x['ptmin']) / 2),
axis=1)
def draw_geff(target_dir,
c_title,
ext,
t,
title,
h_name,
h_bins,
to_draw,
denom_cut,
extra_num_cut,
opt,
color,
marker_st=1,
marker_sz=1):
c = TCanvas("c", "c", 600, 600)
c.Clear()
gPad.SetGrid(1)
gStyle.SetStatStyle(0)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
t.Draw(to_draw + ">>num_" + h_name + h_bins, extra_num_cut + denom_cut,
"goff")
num = TH1F(gDirectory.Get("num_" + h_name))
if not num:
sys.exit('num does not exist')
num = TH1F(num.Clone("eff_" + h_name))
t.Draw(to_draw + ">>denom_" + h_name + h_bins, denom_cut, "goff")
den = TH1F(gDirectory.Get("denom_" + h_name).Clone("denom_" + h_name))
eff = TGraphAsymmErrors(num, den)
if not "same" in opt:
num.Reset()
num.GetYaxis().SetRangeUser(0., 1.05)
num.SetStats(0)
num.SetTitle(title)
num.Draw()
eff.SetLineWidth(2)
eff.SetLineColor(color)
eff.SetMarkerStyle(marker_st)
eff.SetMarkerColor(color)
eff.SetMarkerSize(marker_sz)
eff.Draw(opt + " same")
## Do fit in the flat region
if "eta" in c_title:
xmin = eta_min
xmax = eta_max
else:
xmin = -999.
xmax = 999.
f1 = TF1("fit1", "pol0", xmin, xmax)
r = eff.Fit("fit1", "RQS")
ptstats = TPaveStats(0.25, 0.35, 0.75, 0.55, "brNDC")
ptstats.SetName("stats")
ptstats.SetBorderSize(0)
ptstats.SetLineWidth(0)
ptstats.SetFillColor(0)
ptstats.SetTextAlign(11)
ptstats.SetTextFont(42)
ptstats.SetTextSize(.05)
ptstats.SetTextColor(kRed)
ptstats.SetOptStat(0)
ptstats.SetOptFit(1111)
chi2 = int(r.Chi2())
ndf = int(r.Ndf())
## prob = r.Prob()
round(2.675, 2)
p0 = f1.GetParameter(0)
p0e = f1.GetParError(0)
ptstats.AddText("#chi^{2} / ndf: %d/%d" % (chi2, ndf))
## ptstats.AddText("Fit probability: %f %" %(prob))
ptstats.AddText("Efficiency: %f #pm %f %%" % (p0, p0e))
ptstats.Draw("same")
pt = TPaveText(0.09899329, 0.9178322, 0.8993289, 0.9737762, "blNDC")
pt.SetName("title")
pt.SetBorderSize(1)
pt.SetFillColor(0)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.AddText(eff.GetTitle())
pt.Draw("same")
c.Modified()
c.SaveAs(target_dir + c_title + ext)
graph.GetXaxis().SetLimits(x[0]-2*x_low[0], x[-1]+2*x_low[-1])
if args.logy:
c.SetLogy(1)
graph.GetHistogram().SetMinimum(y.min()/2)
graph.GetHistogram().SetMaximum(y.max()*3)
graph.SetTitle("")
Frame(gPad)
yrlabel = TextAuto(gPad, args.year, align = 31)
last = histo.GetNbinsX() - 1
func = TF1("func","sqrt(([0]/(x))^2 + 2*([1]^2))", x[0]-x_low[0], x[last]+x_high[last])
func.SetParameter(0, N)
func.SetParameter(1, C)
graph.Fit("func","R")
Nlabel = Text(gPad, 0.6, 0.7, "N = {:.3f} #pm {:.3f} ns".format(func.GetParameter(0), func.GetParError(0)))
Clabel = Text(gPad, 0.6, 0.65,"C = {:.3f} #pm {:.3f} ns".format(func.GetParameter(1), func.GetParError(1)))
c.Update()
c.Modified()
if args.show: input()
if (args.effs):
ename = "effs_deltaT_e1_seeds_vs_effA_e1_seeds"
if args.glob:
ename = "effs_deltaT_ee_vs_effA_ee"
eff_s_graph = inFile.Get(ename+"_"+args.sel)
eff_s_graph.SetMarkerStyle(8)
def plotQIcalibration(results, outDir = "results", currentMode = ""):
gROOT.SetBatch(True)
calibGraphs = []
gStyle.SetMarkerColor(kBlue)
gStyle.SetLineColor(kBlack)
#for ch in xrange(1, len(results)+1): # Number of channels
for ch in sorted(results.keys()):
gr = TGraphAsymmErrors()
gr.SetMarkerStyle(22)
gr.SetMarkerSize(1.2)
gr.SetName("Channel_%d_Charge_vs_DAC" % ch)
gr.SetTitle("Channel %d Charge vs DAC value%s" % (ch, " %s current mode" % currentMode if currentMode in ["low", "high"] else ""))
res = results[ch]
for i, dacVal in enumerate(sorted(res.keys())):
mean = res[dacVal]["mean"] * 25.e6 # Convert to fC
err = res[dacVal]["std"] * 25.e6
# Index of new point
np = gr.GetN()
# Set value and error
gr.SetPoint(np, dacVal, mean)
gr.SetPointError(np, 0., 0., err, err)
calibGraphs.append((gr,ch))
if outDir[-1] == "/": outDir = outDir[:-1]
os.system("mkdir -p %s/calibGraphs" % outDir )
c1 = TCanvas('c1','c1', 1200, 800)
c1.SetLeftMargin(0.15);
c1.SetRightMargin(0.25)
c1.SetBottomMargin(0.25);
pad1=TPad('p1','p1',0.,0.,1.0,1.0)
pad1.Draw()
outF = TFile.Open(outDir + "/calibration.root", "RECREATE")
fitParams = {} # Converted to charge by * 25ns
for i,(gr,ch) in enumerate(calibGraphs):
gr.Fit('pol1', "Q") # Q: Quiet mode
f = gr.GetFunction("pol1")
p0 = f.GetParameter(0)
p0_err = f.GetParError(0)
p1 = f.GetParameter(1)
p1_err = f.GetParError(1)
fitline = "offset %g #pm %g slope %g #pm %g" % (p0, p0_err, p1, p1_err)
# Convert to fC
fitParams[ch] = {"slope":(p1), "offset":(p0)}
#fitParams[(i+1)] = {"slope":(p1), "offset":(p0)}
gr.GetXaxis().SetTitle("DAC value")
gr.GetYaxis().SetTitle("Charge [fC]")
if currentMode == "low":
gr.GetYaxis().SetTitleOffset(1.37)
pad1.cd()
gr.Draw("AP")
gr.Write()
txt=TLatex()
txt.SetNDC(True)
txt.SetTextFont(43)
txt.SetTextSize(20)
txt.SetTextAlign(12)
txt.DrawLatex(0.40,0.87, fitline)
Quiet(c1.SaveAs)(outDir + "/calibGraphs/channel_%d.png" % (i+1))
# for g in adcGraphs:
#
# g.Write()
# for g in chargeGraphs:
# g.Write()
#outF.Write()
outF.Close()
return fitParams
def plotHistos(dac, histVals, qiCalib = None, outDir = "results", currentMode = ""):
adcGraphs = []
chargeGraphs = []
gStyle.SetMarkerColor(kBlue)
gStyle.SetLineColor(kBlack)
convFactor = 1.
if qiCalib is None:
# Use nominal qiCalib
print "Using nominal QI calibrations"
if currentMode == "low":
convFactor = 1.375
elif currentMode == "high":
convFactor = 7.7
offset = 0.
else:
print "Using custom QI calibrations"
#for i in range(len(histVals[dac[0]])):
for i in range(12):
adcGr = TGraphAsymmErrors()
adcGr.SetMarkerStyle(22)
#adcGr.SetMarkerSize(1.0)
adcGr.SetName("h%d_ADC" % i)
adcGr.SetTitle("h%d ADC vs %s" % (i, "Charge %s current mode" % currentMode if currentMode in ["low", "high"] else "DAC value"))
chGr = TGraphAsymmErrors()
chGr.SetMarkerStyle(22)
#chGr.SetMarkerSize(1.3)
chGr.SetName("h%d_LinADC" % i)
chGr.SetTitle("h%d Lin ADC vs %s" % (i, "Charge %s current mode" % currentMode if currentMode in ["low", "high"] else "DAC value"))
adcGraphs.append(adcGr)
chargeGraphs.append(chGr)
for i, dv in enumerate(dac):
for n in range(len(adcGraphs)):
mean = histVals[dv][n]["mean"]
err = histVals[dv][n]["rms"]
if qiCalib is not None:
QIchan = int(n/6)*8 + n%6 + 1
convFactor = qiCalib[QIchan]["slope"]
offset = qiCalib[QIchan]["offset"]
# Index of new point
np = adcGraphs[n].GetN()
# Set value and error
adcGraphs[n].SetPoint(np, dv*convFactor + offset, mean)
adcGraphs[n].SetPointError(np, 0., 0., err, err)
chMean, chErr = linADC(mean, err)
chargeGraphs[n].SetPoint(np, dv*convFactor + offset, chMean)
chargeGraphs[n].SetPointError(np, 0., 0., chErr, chErr)
if outDir[-1] == "/": outDir = outDir[:-1]
os.system("mkdir -p %s/adcH; mkdir -p %s/chargeH" % (outDir, outDir) )
c1 = TCanvas('c1','c1', 1200, 800)
c1.SetLeftMargin(0.15);
c1.SetRightMargin(0.25)
c1.SetBottomMargin(0.25);
pad1=TPad('p1','p1',0.,0.,1.0,1.0)
pad1.Draw()
outF = TFile.Open(outDir + "/histos.root", "RECREATE")
xAxisTitle = "Charge [fC]" if currentMode in ["low", "high"] else "DAC value"
for i,adcGr in enumerate(adcGraphs):
"""
adcGr.Fit('pol1', "Q") # Q: Quiet mode
f = adcGr.GetFunction("pol1")
p0 = f.GetParameter(0)
p0_err = f.GetParError(0)
p1 = f.GetParameter(1)
p1_err = f.GetParError(1)
fitline = "offset %.3f #pm %.2f slope %.3f #pm %.6f" % (p0, p0_err, p1, p1_err)
"""
adcGr.GetXaxis().SetTitle(xAxisTitle)
adcGr.GetYaxis().SetTitle("ADC")
adcGr.GetYaxis().SetTitleOffset(1.2)
pad1.cd()
pad1.SetLogx(True)
adcGr.Draw("AP")
adcGr.Write()
Quiet(c1.SaveAs)(outDir + "/adcH/adc_hist_%d.png" % i)
c1.SetLogy(True)
for i,chGr in enumerate(chargeGraphs):
chGr.Fit('pol1', "Q") # Q: Quiet mode
f = chGr.GetFunction("pol1")
p0 = f.GetParameter(0)
p0_err = f.GetParError(0)
p1 = f.GetParameter(1)
p1_err = f.GetParError(1)
fitline = "offset %.3f #pm %.2f slope %.3f #pm %.6f" % (p0, p0_err, p1, p1_err)
chGr.GetXaxis().SetTitle(xAxisTitle)
chGr.GetYaxis().SetTitle("Linearized ADC")
chGr.GetYaxis().SetTitleOffset(1.2)
pad1.cd()
pad1.SetLogx(True)
pad1.SetLogy(True)
chGr.Draw("AP")
chGr.Write()
txt=TLatex()
txt.SetNDC(True)
txt.SetTextFont(43)
txt.SetTextSize(20)
txt.SetTextAlign(12)
txt.DrawLatex(0.45,0.87, fitline)
Quiet(c1.SaveAs)(outDir + "/chargeH/charge_hist_%d.png" % i)
# for g in adcGraphs:
#
# g.Write()
# for g in chargeGraphs:
# g.Write()
#outF.Write()
outF.Close()
#calculate the efficiency
hEff = TGraphAsymmErrors(hSel, hAll)
#hEff = TH1D("hEffBemc", "", nbins, bins.data());
#hEff.Divide(hSel, hAll, 1, 1, "B");
fitFunc = TF1("fitFunc", fitFuncErf, 0., 10. , 4)
fitFunc.SetParNames("n", "pthr", "sigma", "e0")
fitFunc.SetParameters(0.45, 1., 0.3, 0.01)
fitFunc.FixParameter(3, 0.)
fitFunc.SetLineColor(clin)
fitFunc.SetLineWidth(2)
fitFunc.SetNpx(1000)
#make the fit
r1 = ( hEff.Fit(fitFunc, "RS") ).Get()
out.write(ut.log_tfit_result(r1))
#test for cast in fit result
#gROOT.LoadMacro("../plot_utils.h")
#rt.FitResultShow(r1)
ut.show_tfit_result(r1)
#log fit parameters in 3-digit precision
ut.log_results(out, "Fit parameters in 3-digit precision:")
chistr = "chi2/ndf: {0:.3f}".format(r1.Chi2()/r1.Ndf())
ut.log_results(out, chistr)
for ipar in xrange(3):
nam = fitFunc.GetParName(ipar)
val = fitFunc.GetParameter(ipar)
err = fitFunc.GetParError(ipar)
