def plot_landau(source_scan_filename, tdc_hists, target_threshold, fit_range=(13000, 30000)):
with tb.open_file(tdc_hists, 'r') as in_file_h5:
x, count, count_error = in_file_h5.root.HistTdcCalibratedCondition_2[:]['charge'], in_file_h5.root.HistTdcCalibratedCondition_2[:]['count'], in_file_h5.root.HistTdcCalibratedCondition_2[:]['count_error']
charge = plsr_dac_to_charge(source_scan_filename, x)
target_threshold_charge = plsr_dac_to_charge(source_scan_filename, target_threshold)
plt.clf()
plt.grid()
x_fit_range = np.logical_and(charge > fit_range[0], charge < fit_range[1])
coeff, err = fit_landau_bootstrap(charge[x_fit_range], count[x_fit_range], p0 = (7000, np.std(charge[x_fit_range]), 150, np.amax(count[x_fit_range])), yerr=count_error[x_fit_range], n_iterations=100)
plt.bar(charge, count, width=charge[1] - charge[0], color='blue', label='data')
plt.plot(charge[x_fit_range], landau.langau(charge[x_fit_range], *coeff), 'r-')
plt.plot([target_threshold_charge, target_threshold_charge], [plt.ylim()[0], plt.ylim()[1]], 'b--', linewidth=2, label='Threshold $%d$ e' % target_threshold_charge)
plt.plot([coeff[0], coeff[0]], [plt.ylim()[0], plt.ylim()[1]], 'r--', linewidth=2, label='MPV $%d\pm%d$ e' % (coeff[0], err[0]))
plt.title('Landau, -30 C')
plt.legend(loc=0)
plt.show()
def plot_landau(source_scan_filename,
tdc_hists,
target_threshold,
fit_range=(13000, 30000)):
with tb.open_file(tdc_hists, 'r') as in_file_h5:
x, count, count_error = in_file_h5.root.HistTdcCalibratedCondition_2[:][
'charge'], in_file_h5.root.HistTdcCalibratedCondition_2[:][
'count'], in_file_h5.root.HistTdcCalibratedCondition_2[:][
'count_error']
charge = plsr_dac_to_charge(source_scan_filename, x)
target_threshold_charge = plsr_dac_to_charge(source_scan_filename,
target_threshold)
plt.clf()
plt.grid()
x_fit_range = np.logical_and(charge > fit_range[0],
charge < fit_range[1])
coeff, err = fit_landau_bootstrap(charge[x_fit_range],
count[x_fit_range],
p0=(7000,
np.std(charge[x_fit_range]), 150,
np.amax(count[x_fit_range])),
yerr=count_error[x_fit_range],
n_iterations=100)
plt.bar(charge,
count,
width=charge[1] - charge[0],
color='blue',
label='data')
plt.plot(charge[x_fit_range], landau.langau(charge[x_fit_range],
*coeff), 'r-')
plt.plot([target_threshold_charge, target_threshold_charge],
[plt.ylim()[0], plt.ylim()[1]],
'b--',
linewidth=2,
label='Threshold $%d$ e' % target_threshold_charge)
plt.plot([coeff[0], coeff[0]],
[plt.ylim()[0], plt.ylim()[1]],
'r--',
linewidth=2,
label='MPV $%d\pm%d$ e' % (coeff[0], err[0]))
plt.title('Landau, -30 C')
plt.legend(loc=0)
plt.show()
def errfunc(p, x, y): # langau errorfunktion to minimize in fit
return landau.langau(x, *p) - y
def errfunc(p, x, y): # langau errorfunktion to minimize in fit
return landau.langau(x, *p) - y