def main():
squid = loadCSVToList('../calc/bfields_leiterschleife_fit.txt')
theo = loadCSVToList('../calc/bfields_leiterschleife_theo.txt')
resistors = loadCSVToList('../data/resistors.txt')
x = [u / r for r, u in resistors]
sx = [0.01 / r for r, u in resistors]
ysquid, sysquid = zip(*squid)
ytheo, sytheo = zip(*theo)
c = TCanvas('c', '', 1280, 720)
theoData = DataErrors.fromLists(x, ytheo, sx, sytheo)
gTheo = theoData.makeGraph('gTheo', 'Strom I / A', 'Magnetfeld B_{z} / T')
gTheo.SetMarkerColor(2)
gTheo.SetLineColor(2)
gTheo.Draw('AP')
squidData = DataErrors.fromLists(x, ysquid, sx, sysquid)
gSquid = squidData.makeGraph('gSquid', 'Strom I / A', 'Magnetfeld B_{z} / T')
gSquid.Draw('P')
l = TLegend(0.15, 0.7, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(gSquid, 'gemessene Magnetfeldst#ddot{a}rke B_{z}', 'p')
l.AddEntry(gTheo, 'theoreitsche Magnetfeldst#ddot{a}rke B_{z}', 'p')
l.Draw()
c.Update()
c.Print('../img/compare.pdf', 'pdf')
c.SetLogy()
c.SetLogx()
c.Update()
c.Print('../img/compare_loglog.pdf', 'pdf')
def evalSigmaChannelDatas(datas):
x = list(zip(*datas))[0]
sx = list(zip(*datas))[1]
y = list(zip(*datas))[2]
sy = list(zip(*datas))[3]
data = DataErrors.fromLists(x, y, sx, sy)
c = TCanvas('c_sc', '', 1280, 720)
g = data.makeGraph('g_sc', 'channel c', '#sigma(channels)')
g.Draw('AP')
c.Update()
c.Print('../img/energieaufloesung_channels.pdf', 'pdf')
ecallist = loadCSVToList('../calc/ecal_sigmas.txt')
x, sx, y, sy = list(zip(*ecallist))
ecaldata = DataErrors.fromLists(x, y, sx, sy)
g.SetMaximum(50)
g.Draw('AP')
gecal = ecaldata.makeGraph('g_ecal', 'channel c', '#sigma(channels)')
gecal.SetMarkerColor(2)
gecal.SetLineColor(2)
gecal.Draw('P')
l = TLegend(0.15, 0.7, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'fitted #sigma of LED-Peaks', 'p')
l.AddEntry(gecal, 'fitted #sigma of energy calibration peaks', 'p')
l.Draw()
c.Update()
c.Print('../img/energieaufloesung_channels+ecal.pdf', 'pdf')
def main():
z, sz = 840, 40
d = [210, 106, 75]
sd = [10, 4, 4]
calc = list(map(lambda x:-20 * log10(x/z), d))
scalc = list(map(lambda x:20 * sqrt((x[1]/x[0]) ** 2 + (sz/z)**2) / log(10), zip(*[d, sd])))
data = DataErrors.fromLists(calc, [12, 18, 21], scalc, [0]*3)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'measured attenuation m / dB', 'nominal value n / dB')
g.Draw('AP')
fit = Fitter('fit', 'pol1(0)')
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 1)
fit.fit(g, 11, 22)
fit.saveData('../fit/attenuator.txt')
l = TLegend(0.15, 0.6, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'measured att. vs. nominal value', 'p')
l.AddEntry(fit.function, 'fit with n = a + b m', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f')), chisquareformat='%.4f', units=['dB', ''], lang='en')
l.Draw()
c.Update()
c.Print('../img/attenuator.pdf', 'pdf')
def loadCrossSection(ctype):
datalist = loadCSVToList('../calc/crosssections_%s.txt' % ctype)
xlist = list(zip(*datalist))[0]
sxlist = [0] * len(xlist)
ylist = list(zip(*datalist))[1]
sylist = list(zip(*datalist))[2]
return DataErrors.fromLists(xlist, ylist, sxlist, sylist)
def main():
x, y, sy = zip(*loadCSVToList('../calc/part3/Co-Si_mergedbins.txt'))
data = DataErrors.fromLists(x, y, [0]*len(x), sy)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'Kanal k', 'Counts N')
g.SetMarkerStyle(8)
g.SetMarkerSize(0.5)
g.SetLineColor(15)
g.SetLineWidth(0)
g.Draw('AP')
fit = Fitter('f', '1/(sqrt(2*pi*[2]^2))*gaus(0)')
fit.setParam(0, 'A', 50)
fit.setParam(1, 'x_{c}', 690)
fit.setParam(2, 's', 20)
fit.fit(g, 672, 712)
fit.saveData('../calc/part3/fit_Co-Si_01_mergedbins.txt', 'w')
with TxtFile('../calc/part3/fit_Co-Si_01_mergedbins_raw.txt', 'w') as f:
for key, param in fit.params.iteritems():
f.writeline('\t', *map(str, [param['value'], param['error']]))
l = TLegend(0.7, 0.5, 0.95, 0.85)
l.SetTextSize(0.0225)
l.AddEntry(g, 'Gemittelte Messwerte', 'p')
l.AddEntry(fit.function, 'Fit mit', 'l')
l.AddEntry(0, 'N(k) = #frac{A}{#sqrt{2#pi*#sigma^{2}}} exp(- #frac{1}{2} (#frac{x-x_{c}}{#sigma})^{2})', '')
l.AddEntry(0, '', '')
fit.addParamsToLegend(l, chisquareformat='%.2f')
l.Draw()
c.Update()
c.Print('../img/part3/Co-Si_01_mergedbins.pdf', 'pdf')
def loadCrossSection(ctype):
datalist = loadCSVToList('../calc/crosssections_%s.txt' % ctype)
xlist = list(zip(*datalist))[0]
sxlist = [0] * len(xlist)
ylist = list(zip(*datalist))[1]
sylist = list(zip(*datalist))[2]
return DataErrors.fromLists(xlist, ylist, sxlist, sylist)
def compareSpectrum(prefix, spectrum, litvals):
xlist = list(zip(*spectrum))[0]
sxlist = list(zip(*spectrum))[1]
compData = DataErrors.fromLists(xlist, litvals, sxlist, [0] * len(litvals))
c = TCanvas('c_%s_compspectrum' % prefix, '', 1280, 720)
g = compData.makeGraph('g_%s_compspectrum' % prefix,
'experimentell bestimmte HFS-Aufspaltung #Delta#nu^{exp}_{%s} / GHz' % prefix,
'theoretische HFS-Aufspaltung #Delta#nu^{theo} / GHz')
g.Draw('AP')
fit = Fitter('fit_%s_compspectum' % prefix, 'pol1(0)')
fit.setParam(0, 'a_{%s}' % prefix, 0)
fit.setParam(1, 'b_{%s}' % prefix, 1)
fit.fit(g, compData.getMinX() - 0.5, compData.getMaxX() + 0.5)
if prefix == "up":
l = TLegend(0.15, 0.6, 0.45, 0.85)
else:
l = TLegend(0.15, 0.6, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Spektrum', 'p')
l.AddEntry(fit.function, 'Fit mit #Delta#nu^{theo} = a_{%s} + b_{%s} #Delta#nu^{exp}_{%s}' % (prefix, prefix, prefix), 'l')
fit.addParamsToLegend(l, [('%.2f', '%.2f'), ('%.3f', '%.3f')], chisquareformat='%.2f', units=['GHz', ''])
l.Draw()
c.Update()
if not DEBUG:
c.Print('../img/part2/%s-spectrum.pdf' % prefix, 'pdf')
def main():
z, sz = 840, 40
d = [210, 106, 75]
sd = [10, 4, 4]
calc = list(map(lambda x: -20 * log10(x / z), d))
scalc = list(
map(lambda x: 20 * sqrt((x[1] / x[0])**2 + (sz / z)**2) / log(10),
zip(*[d, sd])))
data = DataErrors.fromLists(calc, [12, 18, 21], scalc, [0] * 3)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'measured attenuation m / dB',
'nominal value n / dB')
g.Draw('AP')
fit = Fitter('fit', 'pol1(0)')
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 1)
fit.fit(g, 11, 22)
fit.saveData('../fit/attenuator.txt')
l = TLegend(0.15, 0.6, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'measured att. vs. nominal value', 'p')
l.AddEntry(fit.function, 'fit with n = a + b m', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f')),
chisquareformat='%.4f',
units=['dB', ''],
lang='en')
l.Draw()
c.Update()
c.Print('../img/attenuator.pdf', 'pdf')
def fitSigma(sigs, times):
listx, listsx = zip(*times)
listy, listsy = zip(*sigs)
listy = map(abs, listy) # fits can yield negative sigma, because it only occurse to
data = DataErrors.fromLists(listx, listy, listsx, listsy)
c = TCanvas('cSigma', '', 1280, 720)
g = data.makeGraph('Sigma', 'Zeit t / s', 'Standardabweichung #sigma / cm')
g.Draw('AP')
fit = Fitter('fitS', 'sqrt(2*[0]*(x + [1]))')
fit.setParam(0, 'D_{n}', 100)
fit.setParam(1, 't_{0}', 0)
fit.fit(g, 1e-6, 21e-6)
fit.saveData('../calc/part2/dist_fit_sigma.txt')
l = TLegend(0.15, 0.625, 0.45, 0.85)
l.SetTextSize(0.03)
l.AddEntry('Sigma', 'Messung', 'p')
l.AddEntry(fit.function, 'Fit mit #sigma(t) = #sqrt{2*D_{n}*(t + t_{0})}', 'l')
fit.addParamsToLegend(l, [('%.1f', '%.1f'), ('%.2e', '%.2e')], chisquareformat='%.2f')
l.Draw()
if PRINTGRAPHS or True:
c.Update()
c.Print('../img/part2/dist_fitSigma.pdf', 'pdf')
def makeBFit(darkTimes, Bs):
dt, sdt = list(zip(*darkTimes))
b, sb = list(zip(*Bs))
data = DataErrors.fromLists(dt, b, sdt, sb)
c = TCanvas('c_B', '', 1280, 720)
g = data.makeGraph('g_B', 'Dunkelzeit t_{D} / ms', 'Fitparameter B / V')
g.Draw('APX')
fit = Fitter('fit_B', '[0] + [1] * (1 - exp(-x/[2]))')
fit.function.SetNpx(1000)
fit.setParam(0, 'a', 0.1)
fit.setParam(1, 'b', 0.1)
fit.setParam(2, 'T_{R_{F}}', 6)
fit.fit(g, 0, 25)
fit.saveData('../fit/B.txt')
l = TLegend(0.55, 0.15, 0.85, 0.6)
l.SetTextSize(0.03)
l.AddEntry(g, 'Fitparameter B', 'p')
l.AddEntry(fit.function, 'Fit mit B(t_{D}) = a + b (1 - e^{-x/T_{R_{F}}})', 'l')
fit.addParamsToLegend(l, (('%.3f', '%.3f'), ('%.3f', '%.3f'), ('%.1f', '%.1f')), chisquareformat='%.2f', units=['V', 'V', 'ms'])
l.Draw()
g.Draw('P')
c.Print('../img/part6/BFit.pdf', 'pdf')
def makeSigmaFit(darkTimes, sigmas):
dt, sdt = list(zip(*darkTimes))
s, ss = list(zip(*sigmas))
data = DataErrors.fromLists(dt, s, sdt, ss)
c = TCanvas('c_sigma', '', 1280, 720)
g = data.makeGraph('g_sigma', 'Dunkelzeit t_{D} / ms', 'Verschmierung #sigma / #mus')
g.Draw('APX')
fit = Fitter('fit_sigma', 'pol1(0)')
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 1)
fit.fit(g, 0, 25)
fit.saveData('../fit/sigma.txt')
l = TLegend(0.6, 0.15, 0.85, 0.5)
l.SetTextSize(0.03)
l.AddEntry(g, 'Verschmierung #sigma', 'p')
l.AddEntry(None, 'der Fermi-Verteilung', '')
l.AddEntry(fit.function, 'Fit mit #sigma(t_{D}) = a + b t_{D}', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.2f', '%.2f')), chisquareformat='%.2f', units=['#mus', '10^{-3}'])
l.Draw()
g.Draw('P')
c.Print('../img/part6/sigmaFit.pdf', 'pdf')
def fitA(amps, times):
listx, listsx = zip(*times)
listy, listsy = zip(*amps)
slaser_rel = 0.05
listsy = list(listsy)
for i, y in enumerate(listy):
listsy[i] = y * np.sqrt(listsy[i] ** 2 + slaser_rel ** 2)
data = DataErrors.fromLists(listx, listy, listsx, listsy)
c = TCanvas('cA', '', 1280, 720)
g = data.makeGraph('A', 'Zeit t / s', 'Amplitude A / V')
g.GetYaxis().SetTitleOffset(1.2)
g.Draw('AP')
fit = Fitter('A', '[0]*exp(-(x)/[1])+[2]')
fit.function.SetNpx(1000)
fit.setParam(0, 'C', 5e-8)
fit.setParam(1, '#tau_{n}', 45e-6)
fit.setParam(2, 'a', 0)
fit.fit(g, 7.5e-6, 18e-6)
fit.saveData('../calc/part2/volt_fit_A.txt')
l = TLegend(0.625, 0.625, 0.85, 0.85)
l.SetTextSize(0.03)
l.AddEntry('A', 'Messung', 'p')
l.AddEntry(fit.function, 'Fit mit A(t) = C*e^{- #frac{t}{#tau_{n}}} + a', 'l')
fit.addParamsToLegend(l, [('%.2e', '%.1e'), ('%.2e', '%.1e'), ('%.2e', '%.1e')], chisquareformat='%.2f')
l.Draw()
if PRINTGRAPHS or True:
c.Update()
c.Print('../img/part2/volt_fitA.pdf', 'pdf')
c.SetLogy()
c.Update()
c.Print('../img/part2/volt_fitA_log.pdf', 'pdf')
def main():
snu = ERRORS["nu"] # TODO get error
sB = ERRORS["B"]
sgyrorel = 0
files = ["H", "Glycol", "Teflon"]
for file in files:
datalist = loadCSVToList("../data/03-%s.txt" % file)
if len(datalist) == 1:
B, nu = datalist[0]
gyro, sgyro = calcGyro(nu, snu, B, sB)
if not sgyrorel == 0:
sgyro = gyro * sgyrorel
with TxtFile("../calc/%s.txt" % file, "w") as f:
f.writeline("\t", "gyro", *map(str, (gyro, sgyro)))
f.writeline("\t", "mu", *map(str, calcMu(gyro, sgyro)))
f.writeline("\t", "gI", *map(str, calcNucGFactor(gyro, sgyro)))
else:
x, y = zip(*datalist)
sx = [0] * len(x)
sy = [snu] * len(y)
data = DataErrors.fromLists(x, y, sx, sy)
data.setXErrorAbs(sB)
c = TCanvas("c%s" % file, "", 1280, 720)
g = data.makeGraph("g%s" % file, "Magnetfeld B / mT", "Resonanzfrequenz #nu / MHz")
g.Draw("AP")
fit = Fitter("fit%s" % file, "[0]*x")
fit.setParam(0, "m", 0.002)
fit.fit(g, datalist[0][0] * 0.95, datalist[-1][0] * 1.05)
fit.saveData("../calc/fit-%s.txt" % file, "w")
l = TLegend(0.15, 0.60, 0.475, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, "Messdaten", "p")
l.AddEntry(fit.function, "Fit mit #nu(B) = m*B", "l")
l.AddEntry(0, "", "")
fit.addParamsToLegend(
l,
[("%.5f", "%.5f"), ("%.2f", "%.2f")],
chisquareformat="%.2f",
advancedchi=True,
units=["MHz / mT", "MHz"],
)
l.Draw()
gyro = 2 * np.pi * fit.params[0]["value"] * 1e9 # in Hz / T
sgyro = 2 * np.pi * fit.params[0]["error"] * 1e9 # in Hz / T
sgyrorel = sgyro / gyro
with TxtFile("../calc/%s.txt" % file, "w") as f:
f.writeline("\t", "gyro", *map(str, (gyro, sgyro)))
f.writeline("\t", "sgyrorel", str(sgyrorel))
f.writeline("\t", "mu", *map(str, calcMu(gyro, sgyro)))
f.writeline("\t", "gI", *map(str, calcNucGFactor(gyro, sgyro)))
c.Update()
c.Print("../img/03-%s.pdf" % file, "pdf")
def evalEnergyCalibration(peaks, percents):
maxenergy = 1.95 * 0.87 * 84
smaxenergy = maxenergy * sqrt((0.05 / 1.95)**2 + (0.01 / 0.87)**2 +
(5 / 84)**2)
channels = list(list(zip(*peaks))[0])
schannels = list(list(zip(*peaks))[1])
energies = list(map(lambda x: x / 100 * maxenergy, percents))
senergies = list(map(lambda x: x / 100 * smaxenergy, percents))
print(energies)
print(senergies)
with TxtFile('../src/tab_energycalibration.tex', 'w') as f:
f.write2DArrayToLatexTable(
list(zip(*[percents, channels, schannels, energies, senergies])),
['\% energy', '$c$', '$s_c$', '$E$ / MeV', '$s_E$ / MeV'],
['%d', '%.3f', '%.3f', '%.1f', '%.1f'],
"Channels of fitted peaks and their theoretical energy for the energy calibration.",
"tab:ecal")
data = DataErrors.fromLists(channels, energies, schannels, senergies)
c = TCanvas('c_energycalibration', '', 1280, 720)
g = data.makeGraph('g_energycalibration', 'channel c', 'energy E / MeV')
g.Draw('AP')
fit = Fitter('fit_energycalibration', 'pol1(0)')
fit.function.SetNpx(1000)
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 1 / 3)
fit.fit(g, 0, max(channels) + 5)
fit.saveData('../fit/energyCalibration.txt')
l = TLegend(0.15, 0.6, 0.575, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Peaks of flight through spectra / pedestal', 'p')
l.AddEntry(fit.function, 'fit with E(c) = a + b * c', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.3f', '%.3f')),
chisquareformat='%.2f',
units=('MeV', 'MeV / channel'),
lang='en')
l.Draw()
c.Update()
c.Print('../img/energyCalibration.pdf', 'pdf')
with TxtFile('../calc/energyCalibration.txt', 'w') as f:
f.writeline('\t', str(fit.params[0]['value']),
str(fit.params[0]['error']))
f.writeline('\t', str(fit.params[1]['value']),
str(fit.params[1]['error']))
f.writeline('\t', str(fit.getCovMatrixElem(0, 1)))
def printGraph(datas, phi, name='', fit=False):
"""make graph with measured taus for one specific angle phi
Arguments:
datas -- datalists (sorted by series in dictonary)
phi -- angle
name -- additional name for file name
fit -- if true fit data with linear model (default=False)
"""
# setup canvas and legend
c = TCanvas('c_%d' % phi, '', 1280, 720)
if fit:
l = TLegend(0.6, 0.15, 0.85, 0.5)
else:
l = TLegend(0.65, 0.15, 0.85, 0.35)
l.SetTextSize(0.03)
# make and draw graphs, graphs are organized by TMultiGraph
graphs = TMultiGraph()
for s, datalist in datas.iteritems():
data = DataErrors.fromLists(*zip(*datalist))
g = data.makeGraph('g_%d_%d' % (phi, s))
g.SetMarkerColor(seriescolors[s])
g.SetLineColor(seriescolors[s])
l.AddEntry(g, serieslabels[s], 'p')
graphs.Add(g)
graphs.Draw('AP')
gPad.Update()
setMultiGraphTitle(graphs, 'Druck p / mPa', '#tau / ns')
# fit data with linear fit
if fit:
fit = Fitter('fit_%d' % phi, 'pol1(0)')
fit.function.SetNpx(1000)
fit.setParam(0, '#tau_{0}', 119)
fit.setParam(1, 'm', 0.5)
fit.fit(graphs, 0, 225, 'M')
fit.saveData('../calc/fit_tau_%02d%s.txt' % (phi, name), 'w')
l.AddEntry(fit.function, 'Fit mit #tau(p) = #tau_{0} + m * p', 'l')
fit.addParamsToLegend(l, [('%.1f', '%.1f'), ('%.2f', '%.2f')], chisquareformat='%.2f',
advancedchi=True, units=['ns', 'ns / mPa'])
# draw legend and print canvas to file
l.Draw()
c.Update()
c.Print('../img/taus_%02d%s.pdf' % (phi, name), 'pdf')
# return required fit parameter
if fit:
return fit.params[0]['value'], fit.params[0]['error']
def makePeakFreqGraph(peaks, name):
xlist = list(list(zip(*peaks))[0])
sxlist = list(list(zip(*peaks))[1])
ylist = list(map(lambda i: i * 9.924, range(len(peaks))))
sylist = list(map(lambda i: i * 0.03, range(len(peaks))))
direction = name.split('-')[0]
tabledata = list(zip(*[list(range(1, len(xlist) + 1)), list(map(lambda x:x * 1000, xlist)), list(map(lambda x:x * 1000, sxlist)),
ylist, sylist]))
with TxtFile('../src/tab_part2_etalonfreqs_%s.tex' % direction, 'w') as f:
f.write2DArrayToLatexTable(tabledata,
["i", r"$x_i$ / ms", r"$0.2 \cdot s_i$ / ms", r"$\nu_i$ / GHz", r"$s_{\nu_i}$ / GHz"],
["%d", "%.3f", "%.3f", "%.2f", "%.2f"],
"Zentren $x_i$ der gefitteten Cauchy-Funktionen mit Fehler aus den " +
"Breiteparametern $s_i$ und Frequenzdifferenzen zum ersten Peak. ",
"tab:etalon:calib:%s" % direction)
etalonData = DataErrors.fromLists(xlist, ylist, sxlist, sylist)
etalonData.multiplyX(1000)
c = TCanvas('c_pf_' + name, '', 1280, 720)
g = etalonData.makeGraph('g_pf_' + name, 'Zeit t / ms', 'Frequenzabstand #Delta#nu / GHz')
g.SetMinimum(etalonData.getMinY() - 5)
g.SetMaximum(etalonData.getMaxY() + 5)
g.Draw('AP')
fit = Fitter('fit_pf_' + name, 'pol1(0)')
fit.setParam(0, 'a')
fit.setParam(1, 'r')
xmin, xmax = etalonData.getMinX(), etalonData.getMaxX()
deltax = (xmax - xmin) / 10
fit.fit(g, xmin - deltax, xmax + deltax)
fit.saveData('../fit/part2/%s-etalon_calibration.txt' % name)
if fit.params[1]['value'] < 0:
l = TLegend(0.575, 0.6, 0.85, 0.85)
else:
l = TLegend(0.15, 0.6, 0.425, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Etalonpeaks', 'p')
l.AddEntry(fit.function, 'Fit mit #Delta#nu = a + r * t', 'l')
fit.addParamsToLegend(l, [('%.1f', '%.1f'), ('%.2f', '%.2f')], chisquareformat='%.2f', units=('GHz', 'GHz/ms'))
l.Draw()
c.Update()
if not DEBUG:
c.Print('../img/part2/%s-etalon_calibration.pdf' % name, 'pdf')
return (fit.params[1]['value'], fit.params[1]['error'])
def fitXc(volts, times, d, sd):
listx, listsx = zip(*times)
listy = []
listsy = []
for u, su in volts: # convert u to 1/u
y = 1. / u
sy = su / (u ** 2)
listy.append(y)
listsy.append(sy)
data = DataErrors.fromLists(listx, listy, listsx, listsy)
c = TCanvas('cXc', '', 1280, 720)
g = data.makeGraph('xc', 'Zeit t / s', 'reziproke Treibspannung 1/U_{T} / (1/V)')
g.GetYaxis().SetTitleOffset(1.25)
g.Draw('AP')
fit = Fitter('fitXc', '1/[0] + [1]*x')
fit.setParam(0, 'U_{0}', -150)
fit.setParam(1, 'm', 3e-3)
fit.fit(g, 8e-6, 18e-6)
fit.saveData('../calc/part2/volt_fit_xc.txt')
l = TLegend(0.15, 0.55, 0.4, 0.85)
l.SetTextSize(0.03)
l.AddEntry('xc', 'Messung', 'p')
l.AddEntry(fit.function, 'Fit mit #frac{1}{U_{T}} = m*t + #frac{1}{U_{0}}', 'l')
l.AddEntry(0, '', '')
fit.addParamsToLegend(l, [('%.0f', '%.0f'), ('%.0f', '%.0f')], chisquareformat='%.2f')
l.Draw()
if PRINTGRAPHS or True:
c.Update()
c.Print('../img/part2/volt_fitXc.pdf', 'pdf')
# calculate mu
m, sm = fit.params[1]['value'], fit.params[1]['error']
l = 30
mu = m * l * d / 100 # /100 -> from mm in cm
smu = mu * np.sqrt((sm / m) ** 2 + (sd / d) ** 2)
with TxtFile('../calc/part2/volt_mu.txt', 'w') as f:
f.writeline('\t', str(mu), str(smu))
return mu, smu
def evalEnergyCalibration(peaks, percents):
maxenergy = 1.95 * 0.87 * 84
smaxenergy = maxenergy * sqrt((0.05/1.95) ** 2 + (0.01/0.87) ** 2 + (5/84) ** 2 )
channels = list(list(zip(*peaks))[0])
schannels = list(list(zip(*peaks))[1])
energies = list(map(lambda x:x/100*maxenergy, percents))
senergies = list(map(lambda x:x/100*smaxenergy, percents))
print(energies)
print(senergies)
with TxtFile('../src/tab_energycalibration.tex', 'w') as f:
f.write2DArrayToLatexTable(list(zip(*[percents, channels, schannels, energies, senergies])),
['\% energy', '$c$', '$s_c$', '$E$ / MeV', '$s_E$ / MeV'],
['%d', '%.3f', '%.3f', '%.1f', '%.1f'],
"Channels of fitted peaks and their theoretical energy for the energy calibration.", "tab:ecal")
data = DataErrors.fromLists(channels, energies, schannels, senergies)
c = TCanvas('c_energycalibration', '', 1280, 720)
g = data.makeGraph('g_energycalibration', 'channel c', 'energy E / MeV')
g.Draw('AP')
fit = Fitter('fit_energycalibration', 'pol1(0)')
fit.function.SetNpx(1000)
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 1/3)
fit.fit(g, 0, max(channels) + 5)
fit.saveData('../fit/energyCalibration.txt')
l = TLegend(0.15, 0.6, 0.575, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'Peaks of flight through spectra / pedestal', 'p')
l.AddEntry(fit.function, 'fit with E(c) = a + b * c', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.3f', '%.3f')), chisquareformat='%.2f', units=('MeV', 'MeV / channel'), lang='en')
l.Draw()
c.Update()
c.Print('../img/energyCalibration.pdf', 'pdf')
with TxtFile('../calc/energyCalibration.txt', 'w') as f:
f.writeline('\t', str(fit.params[0]['value']), str(fit.params[0]['error']))
f.writeline('\t', str(fit.params[1]['value']), str(fit.params[1]['error']))
f.writeline('\t', str(fit.getCovMatrixElem(0, 1)))
def makeEnergyGauge(detector, peaks, litvals):
x, sx = zip(*peaks)
data = DataErrors.fromLists(x, litvals, sx, [0] * len(x))
c = TCanvas('c_eg_%s' % detector, '', 1280, 720)
g = data.makeGraph('g_eg_%s' % detector, 'Kanal k', 'Energie E / eV')
g.Draw('AP')
fit = Fitter('f_eg_%s' % detector, 'pol1(0)')
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b')
fit.fit(g, x[0] - 20, x[-1] + 20)
fit.saveData('../calc/part3/energygauge_%s.txt' % detector, 'w')
l = TLegend(0.15, 0.6, 0.4, 0.85)
l.AddEntry(g, 'Messwerte', 'p')
l.AddEntry(fit.function, 'Fit mit E(k) = a + b*k', 'l')
fit.addParamsToLegend(l, [('%.2f', '%.2f'), ('%.4f', '%.4f')], chisquareformat='%.2f')
l.Draw()
c.Update()
if PRINTGRAPHS:
c.Print('../img/part3/energygauge_%s.pdf' % detector, 'pdf')
def main():
times = [2.4, 4.5, 6.25, 8.6]
times_error = [0.02] * len(times)
channels = [113, 223, 315.5, 441]
channels_error = [0.5] * len(times)
with TxtFile('../src/tab_timecalibration.tex', 'w') as f:
f.write2DArrayToLatexTable(list(zip(*[times, times_error, channels, channels_error])),
["$t$ / \\textmu s", "$s_t$ / \\textmu s", "$c$", "$s_c$"],
["%.2f", "%.2f", "%.1f", "%.1f"],
"Measured times and channels with errors for the time calibration.", "tab:tcal")
data = DataErrors.fromLists(channels, times, channels_error, times_error)
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'channel c', 'time t / #mus')
g.Draw('APX')
fit = Fitter('fit', 'pol1(0)')
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 50)
fit.fit(g, 100, 450)
fit.saveData('../fit/timeCalibration.txt')
l = TLegend(0.15, 0.6, 0.5, 0.85)
l.SetTextSize(0.03)
l.AddEntry(g, 'measurement', 'p')
l.AddEntry(fit.function, 'fit with t(c) = a + b * c', 'l')
fit.addParamsToLegend(l, (('%.2f', '%.2f'), ('%.5f', '%.5f')), chisquareformat='%.2f', units=('#mus', '#mus/channel'), lang='en')
l.Draw()
g.Draw('P')
c.Update()
c.Print('../img/timeCalibration.pdf', 'pdf')
with TxtFile('../calc/timeCalibration.txt', 'w') as f:
f.writeline('\t', str(fit.params[0]['value']), str(fit.params[0]['error']))
f.writeline('\t', str(fit.params[1]['value']), str(fit.params[1]['error']))
f.writeline('\t', str(fit.getCovMatrixElem(0, 1)))
def fitXc(dists, times):
listx, listsx = zip(*times)
listy, listsy = zip(*dists)
data = DataErrors.fromLists(listx, listy, listsx, listsy)
c = TCanvas('cXc', '', 1280, 720)
g = data.makeGraph('xc', 'Zeit t / s', 'x_{c} / mm')
g.SetLineWidth(0)
g.Draw('AP')
fit = Fitter('fitXc', 'pol1(0)')
fit.setParam(0, 'x_{0}', 1)
fit.setParam(1, 'm', 0.5e-6)
fit.fit(g, 1e-6, 23e-6)
fit.saveData('../calc/part2/dist_fit_xc.txt')
l = TLegend(0.15, 0.625, 0.4, 0.85)
l.SetTextSize(0.03)
l.AddEntry('xc', 'Messung', 'p')
l.AddEntry(fit.function, 'Fit mit x_{c}(t) = x_{0}+m*t', 'l')
l.AddEntry(0, '', '')
fit.addParamsToLegend(l, [('%.3f', '%.3f'), ('%.2e', '%.2e')], chisquareformat='%.2f')
l.Draw()
if PRINTGRAPHS or True:
c.Update()
c.Print('../img/part2/dist_fitXc.pdf', 'pdf')
# calculate mu
m, sm = fit.params[1]['value'], fit.params[1]['error']
U, sU = 48.8, P2SemiCon.UERROR
l = 30
mu = m * l / U / 100 # /100 -> from mm in cm
smu = mu * np.sqrt((sm / m) ** 2 + (sU / U) ** 2)
with TxtFile('../calc/part2/dist_mu.txt', 'w') as f:
f.writeline('\t', str(mu), str(smu))
return mu, smu
def eval():
data1 = PockData.fromPath('../data/%s.tab' % 'pock_licht_01', 1)
data2 = PockData.fromPath('../data/%s.tab' % 'pock_licht_02', 1)
data3 = PockData.fromPath('../data/%s.tab' % 'pock_licht_03', 1)
data4 = PockData.fromPath('../data/%s.tab' % 'pock_licht_04', 1)
L0 = [0]*data1.getLength()
Ly1 = [0]*data1.getLength()
Ly2 = [0.03]*data1.getLength()
Ly3 = [0.08]*data1.getLength()
Ly4 = [0.17]*data1.getLength()
Offset1 = DataErrors.fromLists(L0, Ly1, L0, L0)
Offset2 = DataErrors.fromLists(L0, Ly2, L0, L0)
Offset3 = DataErrors.fromLists(L0, Ly3, L0, L0)
Offset4 = DataErrors.fromLists(L0, Ly4, L0, L0)
data1 += Offset1
data2 += Offset2
data3 += Offset3
data4 += Offset4
c = TCanvas('c', '', 1280, 720)
g1 = data1.makeGraph('g1', 'Zeit t / s', 'Spannung U / V')
g1.SetMarkerStyle(8)
g1.SetMarkerSize(0.5)
g1.SetMarkerColor(1)
g1.GetXaxis().SetRangeUser(0, 0.1)
g1.SetMinimum(-0.02)
g1.SetMaximum(0.25)
g1.Draw('AP')
g2 = data2.makeGraph('g2', 'Zeit t / s', 'Spannung U / V')
g2.SetMarkerStyle(8)
g2.SetMarkerSize(0.5)
g2.SetMarkerColor(100)
g2.Draw('P')
g3 = data3.makeGraph('g3', 'Zeit t / s', 'Spannung U / V')
g3.SetMarkerStyle(8)
g3.SetMarkerSize(0.5)
g3.SetMarkerColor(95)
g3.Draw('P')
g4 = data4.makeGraph('g4', 'Zeit t / s', 'Spannung U / V')
g4.SetMarkerStyle(8)
g4.SetMarkerSize(0.5)
g4.SetMarkerColor(89)
g4.Draw('P')
l = TLegend(0.63, 0.51, 0.87, 0.87)
l.SetTextSize(0.027)
l.AddEntry('g4', 'Licht an,', 'p')
l.AddEntry('', 'ohne Abschirmung', '')
l.AddEntry('g3', 'Licht an,', 'p')
l.AddEntry('', 'mit Papier als Abschirmung', '')
l.AddEntry('g2', 'Licht an,', 'p')
l.AddEntry('', 'mit Tuch als Abschirmung', '')
l.AddEntry('g1', 'Licht aus,', 'p')
l.AddEntry('', 'mit Tuch als Abschirmung', '')
l.SetFillColor(0)
l.Draw()
c.Update()
c.Print('../img/%s.pdf' % 'licht', 'pdf')
def eval():
data1 = PockData.fromPath('../data/%s.tab' % 'pock_gleich_01', 2)
data2 = PockData.fromPath('../data/%s.tab' % 'pock_gleich_02', 2)
data3 = PockData.fromPath('../data/%s.tab' % 'pock_gleich_03', 2)
data4 = PockData.fromPath('../data/%s.tab' % 'pock_gleich_01', 1)
L0 = [0]*data1.getLength()
Ly1 = [0.41]*data1.getLength()
Ly2 = [0.31]*data1.getLength()
Ly3 = [0.14]*data1.getLength()
Ly4 = [0]*data1.getLength()
Offset1 = DataErrors.fromLists(L0, Ly1, L0, L0)
Offset2 = DataErrors.fromLists(L0, Ly2, L0, L0)
Offset3 = DataErrors.fromLists(L0, Ly3, L0, L0)
Offset4 = DataErrors.fromLists(L0, Ly4, L0, L0)
data1 += Offset1
data2 += Offset2
data3 += Offset3
data4 += Offset4
c = TCanvas('c', '', 1280, 720)
g1 = data1.makeGraph('g1', 'Zeit t / s', 'Spannung U / V')
g1.SetMarkerStyle(8)
g1.SetMarkerSize(0.5)
g1.SetMarkerColor(65)
g1.GetXaxis().SetRangeUser(0, 0.005)
g1.SetMinimum(-0.08)
g1.SetMaximum(0.45)
g1.Draw('AP')
g2 = data2.makeGraph('g2', 'Zeit t / s', 'Spannung U / V')
g2.SetMarkerStyle(8)
g2.SetMarkerSize(0.5)
g2.SetMarkerColor(60)
g2.Draw('P')
g3 = data3.makeGraph('g3', 'Zeit t / s', 'Spannung U / V')
g3.SetMarkerStyle(8)
g3.SetMarkerSize(0.5)
g3.SetMarkerColor(53)
g3.Draw('P')
g4 = data4.makeGraph('g4', 'Zeit t / s', 'Spannung U / V')
g4.SetMarkerStyle(8)
g4.SetMarkerSize(0.5)
g4.SetMarkerColor(2)
g4.Draw('P')
l = TLegend(0.63, 0.51, 0.87, 0.87)
l.SetTextSize(0.027)
l.AddEntry('g1', 'Photodiodensignal,', 'p')
l.AddEntry('', 'U_{G} = 120 V', '')
l.AddEntry('g2', 'Photodiodensignal,', 'p')
l.AddEntry('', 'U_{G} = 122 V', '')
l.AddEntry('g3', 'Photodiodensignal,', 'p')
l.AddEntry('', 'U_{G} = 128 V', '')
l.AddEntry('g4', 'Wechselsignal vom', 'p')
l.AddEntry('', 'Sinusgenerator mit', '')
l.AddEntry('', 'Frequenz #omega', '')
l.SetFillColor(0)
l.Draw()
c.Update()
c.Print('../img/%s.pdf' % 'pockdurchf', 'pdf')
def makeGraph(xlist, ylist, slist, xerror, yerror, xlabel, ylabel, name, fit=False, fitlabel=""):
""" make graph with optional linear fit
Arguments:
xlist -- list with x-values
ylist -- list with y-values
slist -- list with measurement series
xerror -- absolute error on x-values
yerror -- absolute error on y-values
xlabel -- title of x-axis
ylabel -- title of y-axis
name -- appendix to file name
fit -- if True fits data with linear model (default=False)
fitlabel -- fit function as string for legend
"""
xmin = min(xlist)
xmax = max(xlist)
datas = dict()
for x, y, s in zip(xlist, ylist, slist):
if s in datas:
datas[s].append((x, y, xerror, yerror))
else:
datas[s] = [(x, y, xerror, yerror)]
c = TCanvas("c_%s" % name, "", 1280, 720)
graphs = TMultiGraph()
for s, datalist in datas.iteritems():
data = DataErrors.fromLists(*zip(*datalist))
g = data.makeGraph("g_%s_%d" % (name, s))
g.SetMarkerColor(seriescolors[s])
g.SetLineColor(seriescolors[s])
graphs.Add(g)
graphs.Draw("AP")
gPad.Update()
setMultiGraphTitle(graphs, xlabel, ylabel)
if fit:
fit = Fitter("fit_%s" % name, "pol1(0)")
fit.setParam(0, "a")
fit.setParam(1, "b")
fit.fit(graphs, xmin - 1, xmax + 1)
fit.saveData("../calc/fit_%s.txt" % name, "w")
if fit:
yheight = 0.3
else:
yheight = 0.15
if ylist[0] < ylist[-1]: # /
l = TLegend(0.15, 0.85 - yheight, 0.4, 0.85)
else: # \
l = TLegend(0.6, 0.85 - yheight, 0.85, 0.85)
l.SetTextSize(0.03)
for i, graph in enumerate(graphs.GetListOfGraphs()):
l.AddEntry(graph, serieslabels[i], "p")
if fit:
l.AddEntry(fit.function, "Fit mit %s" % fitlabel, "l")
fit.addParamsToLegend(
l, [("%.2f", "%.2f"), ("%.3f", "%.3f")], chisquareformat="%.2f", advancedchi=True, units=["U", "#Omega"]
)
l.Draw()
c.Update()
c.Print("../img/graph_%s.pdf" % name, "pdf")
def evalEnergyGauge():
# get data
datalist = funcs.loadCSVToList('../calc/energy_na.txt')
datalist += funcs.loadCSVToList('../calc/energy_co.txt')
datalist += funcs.loadCSVToList('../calc/energy_eu.txt')
#make latex table
elems = ['Na', 'Na', 'Co', 'Co', 'Eu', 'Eu']
with TxtFile('../src/energygauge.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(*([elems] + zip(*datalist))), ['Element', 'Literaturwert / keV', 'Kanal', 'Fehler auf Kanal'],
['%s', '%.0f', '%.2f', '%.2f'], 'Referenzpeaks mit Literaturwerten', 'tab:energygauge')
#convert do DataErrors
datalist = zip(*datalist)
data = DataErrors.fromLists(datalist[1], datalist[0], datalist[2], [0] * len(datalist[0]))
c = TCanvas('c', '', 1280, 720)
g = data.makeGraph('g', 'Kanalnummer', 'Energie / keV')
g.GetXaxis().SetRangeUser(0, 3500)
g.Draw('AP')
fit = Fitter('f', 'pol1(0)')
fit.function.SetNpx(1000)
fit.setParam(0, 'a', 0)
fit.setParam(1, 'b', 0.4)
fit.fit(g, 0, 3500)
fit.saveData('../calc/energy_gauge_lin.txt', 'w')
l = TLegend(0.15, 0.6, 0.5, 0.85)
l.AddEntry('g', 'Referenzpeaks', 'p')
l.AddEntry(fit.function, 'Fit mit y = a + b*x', 'l')
l.AddEntry(0, '#chi^{2} / DoF : %.0f' % fit.getChisquareOverDoF(), '')
l.AddEntry(0, 'Parameter:', '')
l.AddEntry(0, 'a = %.2f #pm %.2f' % (fit.params[0]['value'], fit.params[0]['error']), '')
l.AddEntry(0, 'b = %.5f #pm %.5f' % (fit.params[1]['value'], fit.params[1]['error']), '')
l.Draw()
c.Update()
c.Print('../img/energy_gauge_lin.pdf', 'pdf')
fit2 = Fitter('f', 'pol2(0)')
fit2.function.SetNpx(1000)
fit2.setParam(0, 'a', 0)
fit2.setParam(1, 'b', fit.params[1]['value'])
fit2.setParam(2, 'c', 0)
fit2.fit(g, 0, 3500)
fit2.saveData('../calc/energy_gauge_lin.txt')
l = TLegend(0.15, 0.575, 0.5, 0.85)
l.AddEntry('g', 'Referenzpeaks', 'p')
l.AddEntry(fit2.function, 'Fit mit y = a + b*x + c*x^2', 'l')
l.AddEntry(0, '#chi^{2} / DoF : %.0f' % fit2.getChisquareOverDoF(), '')
l.AddEntry(0, 'Parameter:', '')
l.AddEntry(0, 'a = %.2f #pm %.2f' % (fit2.params[0]['value'], fit2.params[0]['error']), '')
l.AddEntry(0, 'b = %.5f #pm %.5f' % (fit2.params[1]['value'], fit2.params[1]['error']), '')
l.AddEntry(0, 'c = %.8f #pm %.8f' % (fit2.params[2]['value'], fit2.params[2]['error']), '')
l.Draw()
c.Update()
c.Print('../img/energy_gauge_quad.pdf', 'pdf')
#write raw data for reuse
with TxtFile('../calc/energy_gauge_raw.txt', 'w') as f:
f.writeline('\t', str(fit2.params[0]['value']), str(fit2.params[0]['error']))
f.writeline('\t', str(fit2.params[1]['value']), str(fit2.params[1]['error']))
f.writeline('\t', str(fit2.params[2]['value']), str(fit2.params[2]['error']))
f.writeline(str(fit2.getCorrMatrixElem(0, 1))) #a, b
f.writeline(str(fit2.getCorrMatrixElem(0, 2))) #a, c
f.writeline(str(fit2.getCorrMatrixElem(1, 2))) #b, c
