def fitSpectrum(detector, element, params, logy=True):
data = P3SemiCon.fromPath('../data/part3/%s-%s.mca' % (element, detector))
printTotalSpectrum(data, element, detector, logy)
fitresults = []
for i, peak in enumerate(params):
c = TCanvas('cpeakl_%s-%s_%d' % (element, detector, i), '', 1280, 720)
g = data.makeGraph('g%s-%s_%d' % (element, detector, i), 'Kanal k', 'Counts N')
prepareGraph(g)
g.GetXaxis().SetRangeUser(peak[2][0], peak[2][1])
g.SetMinimum(peak[3][0])
g.SetMaximum(peak[3][1])
g.Draw('AP')
fit = None
paramnames = []
if len(peak[0]) == 5:
fit = Fitter('fit%d' % i, 'pol1(0) + 1/(sqrt(2*pi*[4]^2))*gaus(2)')
paramnames = ['a', 'b', 'A', 'k_{c}', 's']
elif len(peak[0]) == 4:
fit = Fitter('fit%d' % i, '[0] + 1/(sqrt(2*pi*[3]^2))*gaus(1)')
paramnames = ['a', 'A', 'k_{c}', 's']
elif len(peak[0]) == 3:
fit = Fitter('fit%d' % i, '1/(sqrt(2*pi*[2]^2))*gaus(0)')
paramnames = ['A', 'k_{c}', 's']
l = None
if len(peak[0]) > 0:
for j, param in enumerate(peak[0]):
fit.setParam(j, paramnames[j], param)
fit.fit(g, *peak[1])
fitname = ''
if len(peak[0]) == 5:
fitname = 'N(k) = a + b*k + #frac{A}{#sqrt{2#pi*#sigma^{2}}} exp(- #frac{1}{2} (#frac{k-k_{c}}{#sigma})^{2})'
elif len(peak[0]) == 4:
fitname = 'N(k) = a + #frac{A}{#sqrt{2#pi*#sigma^{2}}} exp(- #frac{1}{2} (#frac{k-k_{c}}{#sigma})^{2})'
elif len(peak[0]) == 3:
fitname = 'N(k) = #frac{A}{#sqrt{2#pi*#sigma^{2}}} exp(- #frac{1}{2} (#frac{k-k_{c}}{#sigma})^{2})'
fit.saveData('../calc/part3/fit_%s-%s_%02d.txt' % (element, detector, i), 'w')
results = []
for j, param in fit.params.iteritems():
results.append((param['value'], param['error']))
fitresults.append(results)
# legend
l = TLegend(0.675, 0.5, 0.995, 0.85)
l.SetTextSize(0.025)
l.AddEntry(g, 'Messwerte', 'p')
l.AddEntry(fit.function, 'Fit mit', 'l')
l.AddEntry(0, fitname, '')
l.AddEntry(0, '', '')
fit.addParamsToLegend(l, chisquareformat='%.2f')
l.Draw()
c.Update()
if PRINTGRAPHS:
c.Print('../img/part3/%s-%s_%02d.pdf' % (element, detector, i), 'pdf')
return fitresults
def printTotalSpectrum(data, element, detector, logy=True):
c = TCanvas('total_%s-%s' % (element, detector), '', 1280, 720)
c.SetLogy(logy)
g = data.makeGraph('g%s-%s' % (element, detector), 'Kanal k', 'Counts N')
prepareGraph(g)
g.GetXaxis().SetRangeUser(0, 2500)
g.SetMinimum(0.9)
g.Draw('APX')
c.Update()
if PRINTGRAPHS:
c.Print('../img/part3/%s-%s_spectrum.pdf' % (element, detector), 'pdf')
