X = Z.real
X_s = Z_s.real
Y = Z.imag
Y_s = Z_s.imag
T_d, X_d, Y_d = fk.CutDataSet(T, X, Y, data_window)
Z = X_d + 1j * Y_d
scaling = 1E-4 #max(Z.real)/max(Ttheo)
# Fourier traffo
Zg = fk.GaussWindow(T_d, Z, suscept)
Td = T[1] - T[0]
if gauss:
wn, dft = fk.DFT(T_d,
Zg,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor)
else:
wn, dft = fk.DFT(T_d,
Z,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor)
FWHM, peakFullWidth = fk.PeakWidth(T, 0.1, False, zeroPaddingFactor)
FWHM = FWHM
# theoretical spectrum
center = 1E7 * (1 / l_fel -
1 / l_ref) * mfli_harmonic + harmonic * 1E7 / l_ref
Y_s = Z_s.imag
#print T
T_d = T[:]
X_d = X[:]
Y_d = Y[:]
T_d, X_d, Y_d = fk.CutDataSet(T, X, Y, data_window)
Z = X_d + 1j * Y_d
# Fourier traffo
Zg = fk.GaussWindow(T_d, Z, False)
Td = T[1] - T[0]
wn, dft = fk.DFT(T_d,
Zg,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor)
FWHM, peakFullWidth = fk.PeakWidth(T, 0.1, False,
zeroPaddingFactor)
FWHM = FWHM
#print(FWHM)
# Plot time domain
figTD = plt.figure('scan_{0}_{1}_d{2}_TD_{3}'.format(
run, dev, d, i),
figsize=(9, 12))
ax = figTD.add_subplot(511)
ax.set_title('scan_{0}_{1}_d{2}_TD_{3}'.format(run, dev, d, i))
ax.errorbar(delay, X, yerr=X_s, color='b', linestyle='')
Xtd,Ytd,Xt,Yt = fk.Curve(spc.h*spc.c/(spc.e*l_trans)*1e9, l_ref, harmonic, phi, a*max(abs(Z)), offset, delay[0], delay[-1], 30000) # theo curve for transition
Xtd,Ytd,Xt,Yt = fk.Curve(l_fel/harmonic, l_ref, harmonic, phi, a*max(abs(Z)), offset, delay[0], delay[-1], 30000) # theo curve for laser CWL
T_d,X_d,Y_d = fk.CutDataSet(delay, Z.real, Z.imag, data_window)
Z_cut = X_d + 1j*Y_d
Z_plot = Z_cut
Z_cut = fk.Phasing_TD(Z_cut,T_d,E_r) #time domain phasing of data set to take into account position of data window
scaling = 1 #max(Z.real)/max(Ttheo)
# Fourier traffo
Td = np.mean(np.unique(np.diff(delay)))
if gauss:
Zg = fk.GaussWindow(T_d, Z_cut, suscept)
wn, dft = fk.DFT(T_d, Zg, Td, l_ref , harmonic, zeroPaddingFactor = zeroPaddingFactor)
else:
wn, dft = fk.DFT(T_d, Z_cut, Td, l_ref , harmonic, zeroPaddingFactor = zeroPaddingFactor)
# dft = dft[::-1]
FWHM , peakFullWidth = fk.PeakWidth(T_d, 0.05, False, zeroPaddingFactor)
#Fouriert Trafo of the theoretical dataset
wn_theo, dft_theo = fk.DFT(t_fano_theo, I_fano_theo, t_fano_theo[1]-t_fano_theo[0], l_ref , harmonic, zeroPaddingFactor = zeroPaddingFactor)
''' Fitting the dephasing for 6th harmonic R'''
def decay(t,amp,tau):
return amp*np.exp(-t/tau) + 0.001828
def decay_theo(t,amp,tau):
return amp*np.exp(-t/tau)
T_d, X_d, Y_d = fk.CutDataSet(delay, Z.real, Z.imag, data_window)
Z_cut = X_d + 1j * Y_d
Z_cut = fk.Phasing_TD(
Z_cut, data_window, E_r
) #time domain phasing of data set to take into account position of data window
scaling = 1 #max(Z.real)/max(Ttheo)
# Fourier traffo
Td = np.mean(np.unique(np.diff(delay)))
# print Td
if gauss:
Zg = fk.GaussWindow(T_d, Z_cut, suscept)
wn, dft = fk.DFT(T_d,
Zg,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor)
else:
wn, dft = fk.DFT(T_d,
Z_cut,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor)
# dft = dft[::-1]
FWHM, peakFullWidth = fk.PeakWidth(T_d, 0.1, False, zeroPaddingFactor)
#Fouriert Trafo of the theoretical dataset
wn_theo, dft_theo = fk.DFT(t_fano_theo,
I_fano_theo,