def _Calculate_spectrum_fired(self):
# delete values from previous measurement
self.delete_all_values()
# load data
rabi_x, rabi_y, unused1, unused2 = self.load_file(self.rabi_file)
xy8_x, xy8_y, xy8_xx, xy8_yy = self.load_file(self.xy8_file)
# performing rabi-fit
rabi_fit_parameters = self.rabi_fit(rabi_x, rabi_y)
rabi_contrast = 200 * rabi_fit_parameters[0] / rabi_fit_parameters[3]
rabi_period = rabi_fit_parameters[1] / 1e3 # /1e3 gives us nanoseconds
rabi_amplitude = rabi_fit_parameters[0]
rabi_level = rabi_fit_parameters[3]
print 'rabi_level: ', rabi_level
# plotting rabi + rabi-fit
rabi_y = np.array(rabi_y) / 1e3
self.y_rabi_lo = min(rabi_y) - 0.02
self.y_rabi_hi = max(rabi_y) + 0.02
rabi_fit_y = Fit.Cosinus_dec(*rabi_fit_parameters)(rabi_x) / 1e3
self._plot_rabi_changed(rabi_x, rabi_y, rabi_fit_y)
# plotting yx8-data
self._plot_xy8_changed(xy8_x, xy8_y, xy8_yy)
# decide if rabi-level or xy8-level (if alternating)
level = rabi_level
if xy8_yy != []:
xy8_level = ((np.array(xy8_y) + np.array(xy8_yy)) / 2).mean()
level = xy8_level
print 'xy8_level: ', xy8_level
# performing xy8 to rabi normalization
xy8norm_x = xy8_x
xy8norm_y = Calculate.do_normalization(xy8_y, rabi_amplitude, level)
xy8norm_yy = []
if xy8_yy != []:
xy8norm_yy = Calculate.do_normalization(xy8_yy, rabi_amplitude,
level)
# plotting xy8norm
self._plot_xy8norm_changed(xy8norm_x, xy8norm_y, xy8norm_yy)
# calculating the spectral density
nu = Calculate.nu_from_tau(
xy8norm_x) #this nu is in MHz, since xy8norm_x is in µs
gamma_e = 1 #setting gamma_e to 1
tau_x = np.array(xy8norm_x) / 1e6 #tau_x is in seconds
if xy8_yy == []:
temp = float(sum(xy8norm_y) / len(xy8norm_y))
if temp < 0.5:
xy8norm_y = 1 - xy8norm_y
spectrum_y = Calculate.S_from_data(tau_x, xy8norm_y, gamma_e,
self.Number_pulses)
spectrum_y = np.array(spectrum_y) / 1e6 #to change to MHz
spectrum_yy = []
if xy8_yy != []:
xy8norm_yy = 1 - xy8norm_yy
spectrum_yy = Calculate.S_from_data(tau_x, xy8norm_yy, gamma_e,
self.Number_pulses)
spectrum_yy = np.array(spectrum_yy) / 1e6 #to change to MHz
# plotting the spectral density
self.spec_min = min(nu)
self.spec_max = max(nu)
self._plot_density_changed(nu, spectrum_y, spectrum_yy)
# saving nu and spectra, to use them in Calculate_depth
self.nu = nu
self.spectrum_y = spectrum_y
self.spectrum_yy = spectrum_yy
