def calcFermiKuriePlot(data):
new = MyonData()
for (x, y, sx, sy) in data.getPoints():
ny = sqrt(y / x**2) # sqrt(N/E^2)
if not y == 0:
nsy = sqrt(sy**2 / (4 * x**2 * y) + (sx**2 * y) / x**4) # sy / y^2
else:
nsy = 0
new.addPoint(x, ny, sx, nsy)
return new
def evalPedestal():
name = 'pedestal'
data = MyonData.fromPath('../data/%s.TKA' % name)
data.convertToCountrate()
c = TCanvas('c_ped', '', 1280, 720)
g = data.makeGraph('g_ped', 'channel c', 'countrate n / (1/s)')
g.SetLineColor(1)
g.SetLineWidth(1)
g.GetXaxis().SetRangeUser(0, 20)
g.Draw('APX')
fit = Fitter('fit_%s' % name, 'gaus(0)')
fit.setParam(0, 'A', 30)
fit.setParam(1, 'x', 6)
fit.setParam(2, '#sigma', 3)
fit.setParamLimits(2, 0, 100)
fit.fit(g, 3.5, 10.5)
fit.saveData('../fit/%s.txt' % name)
l = TLegend(0.55, 0.6, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'pedestal', 'p')
l.AddEntry(fit.function, 'fit with n(c) = A gaus(c; x, #sigma)', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.3f', '%.3f'),
('%.3f', '%.3f')),
chisquareformat='%.2f',
units=('1/s', '', ''),
lang='en')
l.Draw()
g.Draw('P')
c.Update()
c.Print('../img/%s.pdf' % name, 'pdf')
return (fit.params[1]['value'], fit.params[1]['error'])
def evalPedestal():
name = 'pedestal'
data = MyonData.fromPath('../data/%s.TKA' % name)
data.convertToCountrate()
c = TCanvas('c_ped', '', 1280, 720)
g = data.makeGraph('g_ped', 'channel c', 'countrate n / (1/s)')
g.SetLineColor(1)
g.SetLineWidth(1)
g.GetXaxis().SetRangeUser(0, 20)
g.Draw('APX')
fit = Fitter('fit_%s' % name, 'gaus(0)')
fit.setParam(0, 'A', 30)
fit.setParam(1, 'x', 6)
fit.setParam(2, '#sigma', 3)
fit.setParamLimits(2, 0, 100)
fit.fit(g, 3.5, 10.5)
fit.saveData('../fit/%s.txt' % name)
l = TLegend(0.55, 0.6, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'pedestal', 'p')
l.AddEntry(fit.function, 'fit with n(c) = A gaus(c; x, #sigma)', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.3f', '%.3f'), ('%.3f', '%.3f')), chisquareformat='%.2f', units=('1/s', '', ''), lang='en')
l.Draw()
g.Draw('P')
c.Update()
c.Print('../img/%s.pdf' % name, 'pdf')
return (fit.params[1]['value'], fit.params[1]['error'])
def evalUnderground():
data1 = MyonData.fromPath('../data/untergrund.TKA')
data2 = MyonData.fromPath('../data/untergrund_2.TKA')
data = MyonData.fromDataErrors(data1 + data2, data1.time + data2.time,
data1.timed + data2.timed)
data.convertToCountrate()
datarebin = data.rebin(20)
for d, suffix in [(data, ""), (datarebin, "_rebin")]:
c = TCanvas('cu%s' % suffix, '', 1280, 720)
g = d.makeGraph('gu%s' % suffix, 'channel c', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 700)
g.Draw('APX')
g.Draw('P')
c.Update()
c.Print('../img/underground%s.pdf' % suffix, 'pdf')
def makeEnergyPlot():
data = MyonData.fromPath('../data/betaspektrum.TKA')
data.convertToCountrate()
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'channel c', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 250)
g.GetYaxis().SetTitleOffset(1.2)
g.Draw('APX')
g.Draw('AP')
c.Update()
c.Print('../img/betaspectrum.pdf', 'pdf')
def makeGraph(channel):
data = MyonData.fromPath('../data/energieaufloesung_%s.TKA' % channel)
data.convertToCountrate()
c = TCanvas('c_%s' % channel, '', 1280, 720)
g = data.makeGraph('g%s' % channel, 'channel c', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 700)
g.Draw('APX')
ch = int(channel)
if ch < 100:
xmin, xmax = ch - 25, ch + 25
elif ch < 120:
xmin, xmax = ch - 50, ch + 40
elif ch < 200:
xmin, xmax = ch - 50, ch + 50
elif ch < 600:
xmin, xmax = 0, 700
else:
xmin, xmax = 0, ch + 45
fit = Fitter('fit_%s' % channel, '[0] + gaus(1)')
fit.function.SetNpx(1000)
fit.setParam(0, 'b', 0) # offset
fit.setParam(1, 'A', data.getMaxY()) # amplitude
fit.setParam(2, 'x', ch) # channel
fit.setParam(3, '#sigma', 50) # sigma
#fit.setParamLimits(0, 0, 1000)
fit.fit(g, xmin, xmax)
fit.saveData('../fit/energieaufloesung_%s.txt' % channel)
if ch > 350:
l = TLegend(0.15, 0.5, 0.45, 0.85)
else:
l = TLegend(0.55, 0.5, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, "measurement", 'p')
l.AddEntry(fit.function, "fit with n(c) =", 'l')
l.AddEntry(None, "b + A gaus(c; x, #sigma)", '')
fit.addParamsToLegend(l, (('%.4f', '%.4f'), ('%.2f', '%.2f'), ('%.2f', '%.2f'), ('%.2f', '%.2f'),),
chisquareformat='%.2f', units=['1/s', '1/s', '', ''], lang='en')
l.Draw()
g.Draw('P')
c.Update()
c.Print('../img/energieaufloesung_%s.pdf' % channel, 'pdf')
return (fit.params[2]['value'], fit.params[2]['error'], abs(fit.params[3]['value']), fit.params[3]['error']) # abs(sigma)
def evalFlythroughSpectrum(name, xmin, xmax):
data = MyonData.fromPath('../data/%s.TKA' % name)
data.convertToCountrate()
c = TCanvas('c_%s' % name, '', 1280, 720)
g = data.makeGraph('g_%s' % name, 'channel c', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 700)
g.GetYaxis().SetTitleOffset(1.2)
g.Draw('APX') # don't draw error bars => fit function in front
maxY = data.getByY(data.getMaxY())[0]
area = g.Integral(xmin, xmax)
print('start fitting %s' % name)
t1 = datetime.datetime.now()
fit = Fitter('fit_%s' % name, langaufun, (xmin, xmax, 4))
fit.setParam(0, 's', 1)
fit.setParam(1, 'm', maxY)
fit.setParam(2, 'A', area)
fit.setParam(3, '#sigma', 30)
fit.fit(g, xmin, xmax, 'RBO')
t2 = datetime.datetime.now()
delta = t2 - t1
print('fitted in %d s' % int(delta.total_seconds()))
fit.saveData('../fit/%s.txt' % name)
if not name == "energiekalibration_100":
l = TLegend(0.5, 0.55, 0.85, 0.85)
else:
l = TLegend(0.15, 0.55, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'flight through with %s%% energy' % name.split('_')[1], 'p')
l.AddEntry(fit.function, 'fit with n(c) =', 'l')
l.AddEntry(None, '(landau(m, s) * gaus(0, #sigma))(c)', '')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f'),
('%.3f', '%.3f'), ('%.2f', '%.2f')),
chisquareformat='%.2f',
lang='en')
l.Draw()
g.Draw('P') # redraw points with error bars
c.Update()
c.Print('../img/%s.pdf' % name, 'pdf')
return ((fit.params[1]['value'], fit.params[1]['error']),
(fit.params[3]['value'], fit.params[3]['error']))
def evalFlythroughSpectrum(name, xmin, xmax):
data = MyonData.fromPath('../data/%s.TKA' % name)
data.convertToCountrate()
c = TCanvas('c_%s' % name, '', 1280, 720)
g = data.makeGraph('g_%s' % name, 'channel c', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 700)
g.GetYaxis().SetTitleOffset(1.2)
g.Draw('APX') # don't draw error bars => fit function in front
maxY = data.getByY(data.getMaxY())[0]
area = g.Integral(xmin, xmax)
print('start fitting %s' % name)
t1 = datetime.datetime.now()
fit = Fitter('fit_%s' % name, langaufun, (xmin, xmax, 4))
fit.setParam(0, 's', 1)
fit.setParam(1, 'm', maxY)
fit.setParam(2, 'A', area)
fit.setParam(3, '#sigma', 30)
fit.fit(g, xmin, xmax, 'RBO')
t2 = datetime.datetime.now()
delta = t2 - t1
print('fitted in %d s' % int(delta.total_seconds()))
fit.saveData('../fit/%s.txt' % name)
if not name == "energiekalibration_100":
l = TLegend(0.5, 0.55, 0.85, 0.85)
else:
l = TLegend(0.15, 0.55, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'flight through with %s%% energy' % name.split('_')[1], 'p')
l.AddEntry(fit.function, 'fit with n(c) =', 'l')
l.AddEntry(None, '(landau(m, s) * gaus(0, #sigma))(c)', '')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f'), ('%.3f', '%.3f'), ('%.2f', '%.2f')), chisquareformat='%.2f', lang='en')
l.Draw()
g.Draw('P') # redraw points with error bars
c.Update()
c.Print('../img/%s.pdf' % name, 'pdf')
return ((fit.params[1]['value'], fit.params[1]['error']), (fit.params[3]['value'], fit.params[3]['error']))
def makeFermiKuriePlot():
data = MyonData.fromPath('../data/betaspektrum.TKA')
data.convertToCountrate()
data.convertChannelToEnergy()
data = calcFermiKuriePlot(data)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'energy E / MeV', '#sqrt{n/E^{2}}')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 150)
g.SetMaximum(0.004)
g.GetYaxis().SetTitleOffset(1.3)
g.Draw('APX')
g.Draw('P')
c.Update()
c.Print('../img/betaspectrum_FermiKurie.pdf', 'pdf')
g.GetXaxis().SetRangeUser(0, 80)
g.SetMaximum(3e-3)
fit = Fitter('fit', '[0]*(x-[1])*1e-6')
fit.setParam(0, 'a', -0.3)
fit.setParam(1, 'b', 55)
fit.fit(g, 23, 45)
fit.saveData('../fit/FermiKurie.txt')
l = TLegend(0.65, 0.6, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Fermi-Kurie plot', 'p')
l.AddEntry(fit.function, 'fit with a(E-b)', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f')),
chisquareformat='%.2f',
units=["10^{-6}", ""],
lang='en')
l.Draw()
c.Update()
c.Print('../img/betaspectrum_FermiKurie_fit.pdf', 'pdf')
return fit.params[1]["value"], fit.params[1]["error"]
def makeMultiGraph(files):
c = TCanvas('c_m', '', 1280, 720)
graphs = []
for file in files:
if file.startswith('energieaufloesung'):
data = MyonData.fromPath('../data/%s' % file)
data.convertToCountrate()
graphs.append(data.makeGraph('g_%s' % file, 'channel c', 'countrate n / (1/s)'))
first = True
for i, g in enumerate(graphs):
g.SetMarkerStyle(1)
g.SetMarkerColor(int(round(51 + (100. - 51) / 11 * i)))
g.GetXaxis().SetRangeUser(0, 700)
g.SetMaximum(100)
if first:
g.Draw('APX')
first = False
else:
g.Draw('PX')
c.Update()
c.Print('../img/energieaufloesung_multi.pdf', 'pdf')
def main():
xmin, xmax = 0.55, 8
data = MyonData.fromPath('../data/zerfallszeit.TKA')
data.convertToCountrate()
data.convertChannelToTime()
data.filterY(None, 0.2e-3)
data.filterX(xmin, xmax)
data = data.rebin(3)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 't / #mus', 'countrate n / (1/s)')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 8.2)
g.Draw('APX')
fit = Fitter('fit', '[0]*1e-3*exp(-x/[1])')
fit.setParam(0, 'A', 0.2)
fit.setParam(1, '#tau', 2.2)
fit.fit(g, xmin, xmax)
fit.saveData('../fit/decayTime.txt')
l = TLegend(0.6, 0.6, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'measurement', 'p')
l.AddEntry(fit.function, 'fit with n(t) = 10^{-3} A e^{- #frac{t}{#tau}}', 'l')
fit.addParamsToLegend(l, (('%.3f', '%.3f'), ('%.2f', '%.2f')), chisquareformat='%.2f', units=['1/ms', '#mus'], lang='de')
l.Draw()
g.Draw('P')
c.Update()
c.Print('../img/decayTime.pdf', 'pdf')
c.SetLogy()
c.Update()
c.Print('../img/decayTime_log.pdf', 'pdf')