def main():
periods = [30, 45, 60]
fitresults = []
for period in periods:
fitresults.append(fitX0(period))
# output xm
with TxtFile('../calc/fixed_T_xm.txt', 'w') as f:
for i, result in enumerate(fitresults):
f.writeline('\t', str(periods[i]), *map(str, result[0]))
f.writeline('\t', *map(str, avgerrors(*zip(*zip(*fitresults)[0])))) # weighted average
# calculate + output alphas
alphas = []
for i, result in enumerate(fitresults):
alphas.append(calcAlpha(periods[i], X0Data.ST, *result[1]))
with TxtFile('../calc/fixed_T_alpha.txt', 'w') as f:
for i, alpha in enumerate(alphas):
f.writeline('\t', str(periods[i]), *map(str, alpha))
f.writeline('\t', *map(str, avgerrors(*zip(*alphas))))
# make latex tables for fit results an alphas
with TxtFile('../src/fit_x0.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(*([(periods)] + zip(*zip(*fitresults)[0]) + zip(*zip(*fitresults)[1]))),
['$T$ / ms', '$x_m$ / mm', '$s_{x_m}$ / mm', '$m$ / (mm / kHz)', '$s_m$ / (mm / kHz)'],
['%d', '%.3f', '%.3f', '%.4f', '%.4f'],
'Fitergebnisse von $x_0\'(\Delta \\nu)$ bei festen Periodendauern $T$.', 'tab:fit:x0')
with TxtFile('../src/fit_x0_alpha.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(*([(periods)] + zip(*alphas))), ['$T$ / ms', '$\\alpha$', '$s_{\\alpha}$'],
['%d', '%.3f', '%.3f'], 'Mitf\\"uhrungskoeffizienten bei festen Periodendauern $T$. ',
'tab:x0:alpha')
def main():
x0s = [36, 40, 53, 57]
fitresults = []
for x0 in x0s:
fitresults.append(fitT(x0))
xm, sxm = getXm('../calc/fixed_T_xm.txt')
alphas = []
for i, result in enumerate(fitresults):
alphas.append(calcAlpha(x0s[i], TData.SX, xm, sxm, *result[1]))
with TxtFile('../calc/fixed_x0_alpha.txt', 'w') as f:
for i, alpha in enumerate(alphas):
f.writeline('\t', str(x0s[i]), *map(str, alpha))
f.writeline('\t', *map(str, avgerrors(*zip(*alphas))))
# make latex tables for fit results an alphas
with TxtFile('../src/fit_T.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(*([(x0s)] + zip(*zip(*fitresults)[0]) + zip(*zip(*fitresults)[1]))),
['$x_0\'$ / mm', '$a$ / kHz', '$s_{a}$ / kHz', '$b$ / (kHz $\cdot$ ms / rad)', '$s_b$ / (kHz $\cdot$ ms / rad)'],
['%d', '%.1f', '%.1f', '%.0f', '%.0f'],
'Fitergebnisse von $\Delta \\nu(\\omega)$ bei festen Auftrittpunkten $x_0\'$.', 'tab:fit:T')
with TxtFile('../src/fit_T_alpha.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(*([(x0s)] + zip(*alphas))), ['$x_0\'$ / mm', '$\\alpha$', '$s_{\\alpha}$'],
['%d', '%.3f', '%.3f'], 'Mitf\\"uhrungskoeffizienten bei festen Auftreffpunkten $x_0\'$. ',
'tab:T:alpha')
def main():
gROOT.Reset()
gROOT.SetStyle('Plain')
gStyle.SetPadTickY(1)
gStyle.SetPadTickX(1)
params = []
fitlist = [False, True, True, True]
for i in xrange(4):
param = eval('pock_saege_winkel%d' % i, fitlist[i])
if fitlist[i]:
params.append(param)
print(params)
with TxtFile('../calc/fitparams_parabolas.txt', 'w') as f:
for par in params:
f.writeline('\t', *map(lambda x: '%.6f\t%.6f' % x, par))
difflist = []
for i in xrange(3):
difflist.append((params[i][1][0]-params[i][0][0],np.sqrt(params[i][1][1]**2 + params[i][0][1]**2)))
av = avgerrors(*zip(*difflist))
with TxtFile('../calc/diff_minmax.txt', 'w') as f:
for dif in difflist:
f.writeline('\t', *map(str, dif))
f.writeline('\t', str(av[0]),str(av[1]),'weighted average')
def main():
setupROOT()
elems = ['Si', 'Ge']
filterxs = [(0, 1.8), (0, 1)]
ymaxs = [0.25, 0.25]
yundergrounds = [0.03, 0.1]
energies = []
for elem, filterx, ymax, yunderground in zip(elems, filterxs, ymaxs, yundergrounds):
energies.append(fitAbsTrans(elem, filterx, ymax))
plotMultiChannelSpectrum(elem, 'Messung',
[(P1SemiCon.CANGLE, P1SemiCon.CPYRO), (P1SemiCon.CANGLE, P1SemiCon.CSAMPLE)],
['Signal des Pyrodetektors', 'Signal der Probe'], (-5, 80), connect=True)
plotMultiChannelSpectrum(elem, 'Untergrund',
[(P1SemiCon.CANGLE, P1SemiCon.CPYRO), (P1SemiCon.CANGLE, P1SemiCon.CSAMPLE)],
['Untergrund des Pyrodetektors', 'Untergrund der Probe'], (-5, 80), (0, yunderground))
plotMultiChannelSpectrum(elem, 'Lampe', [(P1SemiCon.CANGLE, P1SemiCon.CPYRO)], ['Signal des Pyrodetektors'], (-5, 80), connect=True)
plotMultiChannelSpectrum(elem, 'Messung',
[(P1SemiCon.CANGLE, P1SemiCon.CENERGY)],
['Energie E(#alpha)'], (0, 80), connect=True, addlabel='_ea')
for i, energie in enumerate(energies):
listenergy = []
listnewerrors = []
with TxtFile('../calc/part1/%s_bandgap_syserror.txt' % elems[i], 'w') as f:
for e, se in energie:
listenergy.append(e)
sesys = calcsE(convertEnergyToAngle(e, elems[i]), elems[i])
newerror = np.sqrt(se ** 2 + sesys ** 2)
listnewerrors.append(newerror)
f.writeline('\t', str(e), str(se), str(sesys), str(newerror))
with TxtFile('../calc/part1/%s_bandgap_avg.txt' % elems[i], 'w') as f:
f.writeline('\t', *map(str, avgerrors(listenergy, listnewerrors)))
def eval(freq):
# load data
data = loadCSVToList('../data/pock_gleich_%dhz.txt' % freq)
sv = 1 # error on single meassurement
# calculate r41
diffs = map(lambda x: (x[0] + x[1], np.sqrt(2) * sv), data)
avg = avgerrors(*zip(*diffs))
return calcr41(*avg)
def main():
freqs = [1e3, 1e4]
with TxtFile('../calc/pock_dc.txt', 'w') as f:
r41s = []
for freq in freqs:
r41 = eval(freq)
r41s.append(r41)
f.writeline('\t', str(freq), *map(str, r41))
f.writeline('average:')
f.writeline('\t', *map(str, avgerrors(*zip(*r41s))))
def evalTotalGamma(gammas):
gammas.append(avgerrors(list(zip(*gammas))[0], list(zip(*gammas))[1]))
with TxtFile('../calc/gamma_total.txt', 'w') as f:
f.write2DArrayToFile(gammas, ['%f'] * 2)
table = []
desc = [LATEXE, LATEXM, LATEXT, LATEXQ, "gew. Mittel"]
for i, (gamma, sgamma) in enumerate(gammas):
table.append([desc[i], gamma, sgamma])
with TxtFile('../src/tab_gamma_total.tex', 'w') as f:
f.write2DArrayToLatexTable(table, ["Zerfallskanal", r"$\Gamma_\text{Z}$ / GeV", r"$s_{\Gamma_\text{Z}}$ / GeV"],
['%s', '%.3f', '%.3f'],
r"Durch Fits bestimmte totale Zerfallsbreite des \Z-Bosons und gewichtetes Mittel.", "tab:gamma:total")
def evalMasses(masses):
masses.append(avgerrors(list(zip(*masses))[0], list(zip(*masses))[1]))
with TxtFile('../calc/mass.txt', 'w') as f:
f.write2DArrayToFile(masses, ['%f'] * 2)
table = []
desc = [LATEXE, LATEXM, LATEXT, LATEXQ, "gew. Mittel"]
for i, (mass, smass) in enumerate(masses):
table.append([desc[i], mass, smass])
with TxtFile('../src/tab_mass.tex', 'w') as f:
f.write2DArrayToLatexTable(table, ["Zerfallskanal", r"$M_\text{Z}$ / GeV", r"$s_{M_\text{Z}}$ / GeV"],
['%s', '%.3f', '%.3f'],
r"Durch Fits bestimmte Masse des \Z-Bosons und gewichtetes Mittel.", "tab:mass")
def evalTotalGamma(gammas):
gammas.append(avgerrors(list(zip(*gammas))[0], list(zip(*gammas))[1]))
with TxtFile('../calc/gamma_total.txt', 'w') as f:
f.write2DArrayToFile(gammas, ['%f'] * 2)
table = []
desc = [LATEXE, LATEXM, LATEXT, LATEXQ, "gew. Mittel"]
for i, (gamma, sgamma) in enumerate(gammas):
table.append([desc[i], gamma, sgamma])
with TxtFile('../src/tab_gamma_total.tex', 'w') as f:
f.write2DArrayToLatexTable(
table, [
"Zerfallskanal", r"$\Gamma_\text{Z}$ / GeV",
r"$s_{\Gamma_\text{Z}}$ / GeV"
], ['%s', '%.3f', '%.3f'],
r"Durch Fits bestimmte totale Zerfallsbreite des \Z-Bosons und gewichtetes Mittel.",
"tab:gamma:total")
def evalMasses(masses):
masses.append(avgerrors(list(zip(*masses))[0], list(zip(*masses))[1]))
with TxtFile('../calc/mass.txt', 'w') as f:
f.write2DArrayToFile(masses, ['%f'] * 2)
table = []
desc = [LATEXE, LATEXM, LATEXT, LATEXQ, "gew. Mittel"]
for i, (mass, smass) in enumerate(masses):
table.append([desc[i], mass, smass])
with TxtFile('../src/tab_mass.tex', 'w') as f:
f.write2DArrayToLatexTable(
table, [
"Zerfallskanal", r"$M_\text{Z}$ / GeV",
r"$s_{M_\text{Z}}$ / GeV"
], ['%s', '%.3f', '%.3f'],
r"Durch Fits bestimmte Masse des \Z-Bosons und gewichtetes Mittel.",
"tab:mass")
def main():
phis = [0, 45, 90]
tempDict = loadTempDict()
avgphis = dict()
taus = []
for phi in phis:
# read data
datalist = loadCSVToList('../calc/taus_%02d.txt' % phi)
datas = {0: [], 1: [], 2: []}
for T, tau, stau, fitphi, sfitphi in datalist:
p, sp = tempDict[T]
datas[TempToSeries(T)].append((p, tau, sp, stau)) # sort in right series list
# make graphs with different series
printGraph(datas, phi)
printGraph(datas, phi, '_total', True)
del datas[0]
taus.append(printGraph(datas, phi, '_day2', True))
del datas[2]
printGraph(datas, phi, '_partial', True)
# calculate average fitted phi
philist = zip(*datalist)[3]
avgphis[phi] = np.average(philist), np.std(zip(*datalist)[3], ddof=1) / np.sqrt(len(philist))
# print out average fittet phis
with TxtFile('../calc/avgphis.txt', 'w') as f:
for phi, avgphi in avgphis.iteritems():
f.writeline('\t', str(phi), *map(str, avgphi))
# print out extraplated taus as LaTeX table
with TxtFile('../src/taus_final.tex', 'w') as f:
f.write2DArrayToLatexTable(zip(phis, *zip(*taus)),
['$\\Phi$ / ${}^{\\circ}$', '$\\tau$ / ns', '$s_{\\tau}$ / ns'],
['%d', '%.1f', '%.1f'],
'Extrapolierte mittlere Lebensdauern bei verschiedenen Winkeleinstellungen.',
'tab:tau:final')
# print out extrapolated taus as csv and calculate weighted average
with TxtFile('../calc/taus_final.txt', 'w') as f:
for tau, error in taus:
f.writeline('\t', str(tau), str(error))
f.writeline('weighted average')
f.writeline('\t', *map(str, avgerrors(*zip(*taus))))
def main():
evalGraph('141022', 'Spule_R1', 1, 'both')
# make fits
fitfiles = [('141022', 'Spule_R1', 100), ('141022', 'Spule_R2', 100), ('141022', 'Spule_R3', 100),
('141022', 'Spule_R4', 100), ('141022', 'Spule_R5_1', 100), ('141021', 'Magnet', 1),
('141022', 'Magnetspan_0grad', 100), ('141022', 'Magnetspan_45grad', 20),
('141022', 'Magnetspan_90grad', 50)]
results = dict()
rfbs = dict()
for dir, file, rfb in fitfiles:
results[file] = evalGraph(dir, file, rfb, 'fit')
rfbs[file] = rfb
# print fit results to file
reslabels = {0: 'Amplitude', 1: 'omega', 2: 'phi'}
for i, label in reslabels.iteritems():
with TxtFile('../calc/%s.txt' % label, 'w') as f:
for key in results:
f.writeline('\t', key, *map(str, results[key][i]))
# calculate b-field from fitted amplitudes
bfields = [(key, results[key][0], ampToB(rfbs[key], *results[key][0])) for key in results]
bfields.sort(key=lambda x: x[0])
with TxtFile('../calc/bfields_fit.txt', 'w') as f:
for key, res, bfield in bfields:
f.writeline('\t', key, *map(str, res + bfield))
with TxtFile('../calc/bfields_leiterschleife_fit.txt', 'w') as f:
for key, res, bfield in bfields[-5:]:
f.writeline('\t', *map(str, bfield))
# calculate average omega
omegas = [results[key][1] for key in results]
avgomega = avgerrors(*zip(*omegas))
with TxtFile('../calc/omega_avg.txt', 'w') as f:
f.writeline('\t', *map(str, avgomega))
# print graphs without fitting, averaged omega from fits is used for polar plot
drawfiles = [('141022', 'Au-Plaettchen', 100), ('141022', 'emptyHolder', 100), ('141022', 'emptyHolder_afterShaking', 100),
('141022', 'emptyHolder_perpendicular', 100), ('141022', 'Fe-Span', 100), ('141022', 'Stabmagnet_parallel', 1),
('141022', 'Untergrund', 100)]
for dir, file, rfb in drawfiles:
evalGraph(dir, file, rfb, omega=avgomega[0])
def main():
print('make graphs')
print('===========')
makeGraphs()
print('eval etalon data')
print('================')
freqCalibrations = evalEtalonData()
print('eval hfs peak data')
print('==================')
hfspeaks = evalHFSPeakData()
litvals = (-3.07, -2.25, mean([-1.48, -1.12]), mean([1.56, 1.92]), 3.76, 4.58)
reflit = litvals[3]
litvals = list(map(lambda x: x - reflit, litvals))
spectra = dict()
for key in freqCalibrations.keys():
gps, sgps = freqCalibrations[key]
isUp = key[:2] == "up"
spectrum = []
if isUp:
refpeak, srefpeak = hfspeaks[key][2]
m = 1
else:
refpeak, srefpeak = hfspeaks[key][3]
m = -1
for peak, speak in hfspeaks[key]:
freq = m * (refpeak - peak) * 1000 * gps
if not compare2Floats(refpeak, peak):
sfreq = abs(freq) * sqrt((sgps / gps) ** 2 + (sqrt(srefpeak ** 2 + speak ** 2) / (refpeak - peak)) ** 2)
else:
sfreq = 1000 * gps * speak
if compare2Floats(freq, 0):
freq = abs(freq)
spectrum.append((freq, sfreq))
if isUp:
spectrum.reverse()
spectra['up' if isUp else 'down'] = spectrum
compareSpectrum('up' if isUp else 'down', spectrum, litvals)
tabledata = []
names = [r"\rb{87}, F:2$\to$1", r"\rb{87}, F:2$\to$2", r"\rb{85}, F:3$\to$2, 3$\to$3", r"\rb{85}, F:2$\to$2, 2$\to$3",
r"\rb{87}, F:1$\to$1", r"\rb{87}, F:1$\to$2"] # Übergänge
for i, litval in enumerate(litvals):
tabledata.append([names[i]] + [litval] + list(spectra['up'][i]) + list(spectra['down'][i]))
with TxtFile('../src/tab_part2_spectrum.tex', 'w') as f:
f.write2DArrayToLatexTable(tabledata,
["Übergang",
r'$\Delta \nu^\text{theo}$ / GHz',
r'$\Delta \nu^\text{exp}_\text{up}$ / GHz', r'$s_{\Delta \nu^\text{exp}_\text{up}}$ / GHz',
r'$\Delta \nu^\text{exp}_\text{down}$ / GHz', r'$s_{\Delta \nu^\text{exp}_\text{down}}$ / GHz'],
['%s', '%.2f', '%.2f', '%.2f', '%.2f', '%.2f'],
"Theoretisches und (steigende und fallende Flanke) experimentell bestimmtes Hyperfeinstrukturspektrum von Rubidium.",
"tab:hfs:spectrum")
avgdata = []
avgspectrum = []
for name, lit, f1, sf1, f2, sf2 in tabledata:
f, sf = avgerrors([f1, f2], [sf1, sf2])
avgdata.append([name, lit, f, sf])
avgspectrum.append((f, sf))
compareSpectrum('avg', avgspectrum, litvals)
with TxtFile('../src/tab_part2_spectrum_avg.tex', 'w') as f:
f.write2DArrayToLatexTable(avgdata,
["Übergang",
r'$\Delta \nu^\text{theo}$ / GHz',
r'$\Delta \nu^\text{exp}_\text{avg}$ / GHz', r'$s_{\Delta \nu^\text{exp}_\text{avg}}$ / GHz'],
['%s', '%.2f', '%.2f', '%.2f', ],
r"Theoretisches und aus den experimentellen Daten (\autoref{tab:hfs:spectrum}) gemitteltes Hyperfeinstrukturspektrum von Rubidium.",
"tab:hfs:spectrum:avg")
evalIntervalConst(avgspectrum)
def avg2vals(val1, val2):
return avgerrors([val1[0], val2[0]], [val1[1], val2[1]])
