#Z = Z_uhlia
if i0_correction:
Z = Z*(np.nanmean(data['LDM']['I0'])/data['LDM']['I0'])
if i0_6H_correction:
Z = Z*i0_6H
Z *= np.exp(1j*np.pi/180.*phas_corr) #phasing of dataset according to phase difference between reference and WPI signal
R = np.abs(Z)
Phi = np.angle(Z, deg=False)
# plt.plot(np.unwrap(Phi))
# Create theoretical curve
Ttheo = np.linspace(delay[0],delay[-1], 30000)
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)
mfli_harmonic = data[dev]['harmonic'][int(d)]
i = str(mfli_harmonic) + 'H'
Z = (data[dev]['x' + d] + 1j * data[dev]['y' + d]
) # / data['LDM']['I0']
if i0_correction:
Z = Z * (np.nanmean(data['LDM']['I0']) / data['LDM']['I0'])
Z_s = data[dev]['s_x' + d] + 1j * data[dev]['s_y' + d]
R = np.sqrt(Z.real**2 + Z.imag**2)
R_s = np.sqrt(Z_s.real**2 + Z_s.imag**2)
Phi = np.angle(Z, deg=False)
# Create theoretical curve
# if draw_theory:
#Ttheo = np.linspace(T[0],T[-1], 1000)
Xtd, Ytd, Xt, Yt = fk.Curve(l_trans, l_ref, harmonic, phi,
a * max(abs(Z)), offset, T[0], T[-1], 1000)
delay = T
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:
"""Plotting parameters"""
demod = 0 # in [0,1,2,3]. Choose which demodulator channel to analyse and plot
downshifted = False # plot downshifted spectrum
absolute = True # plot absorption spectrum
absorptive = False # plot absorptive and dispersive spectrum
"""TD Analysis & Plotting"""
# delay parameters
start = min(data['delay'])
stop = max(data['delay'])
length = len(data['delay'])
T = np.linspace(start, stop, length, endpoint=True)
print(np.unique(np.diff(data['delay'])))
#calculation of theoretical curve
Xtd, Ytd, X, Y = fk.Curve(l_He, l_ref, h, phi, A,
offset, start, stop, length) # Xtd/Ytd is time domain data, where 10fs are added/substracted to start/stop of dataset,X and Y start/stop at edges of data set and are used for DFT
#plot in phase and in quadrature components of theoretical curve and of data
plt.figure()
fk.PlotCurve(Xtd, Ytd, start, stop)
fk.PlotTdData(data, demod)
#
#"""FD Analysis & Plotting"""
#""""""""""""""""""
#
## discrete complex fourier transform of theoretical curve:
#Z = X + 1j * Y
#
#
## from phancy
i = str(mfli_harmonic) + 'H'
Z = (data[dev]['x' + d] + 1j * data[dev]['y' + d]
) # / data['LDM']['I0']
# Z *= np.exp(1j*40./360.*2.*np.pi)
if i0_correction:
Z = Z * (np.nanmean(data['LDM']['I0']) / data['LDM']['I0'])
Z_s = data[dev]['s_x' + d] + 1j * data[dev]['s_y' + d]
R = np.sqrt(Z.real**2 + Z.imag**2)
R_s = np.sqrt(Z_s.real**2 + Z_s.imag**2)
Phi = np.angle(Z, deg=False)
# Create theoretical curve
# if draw_theory:
#Ttheo = np.linspace(T[0],T[-1], 1000)
Xtd, Ytd, Xt, Yt = fk.Curve(l_trans, l_ref, harmonic, phi,
a * max(abs(Z)), offset, T[0], T[-1], 1000)
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
Z *= np.exp(1j * np.pi / 180 * phas_corr)
scaling = 1E-4 #max(Z.real)/max(Ttheo)
T_d, X_d, Y_d = fk.CutDataSet(T, Z.real, Z.imag, data_window)
Z_cut = X_d + 1j * Y_d
while 1:
try:
imp_data.append(pickle.load(fp))
except EOFError:
break
fp.close()
T = imp_data[0]
Z = imp_data[1] + 1j*imp_data [3]
Z_s = imp_data[2] + 1j*imp_data [4]
R = np.sqrt(Z.real**2 + Z.imag**2)
R_s = np.sqrt(Z_s.real**2 + Z_s.imag**2)
Phi = np.angle(Z, deg=True)
Ttheo = np.linspace(T[0],T[-1], 1000)
Xtd,Ytd,Xt,Yt = fk.Curve(l_He, l_ref, harmonic, -90.0, max(abs(Z)), offset, T[0], T[-1], 1000)
# Optimal phase
Phi_theo = T * 1e-6 * (spc.c/l_ref * harmonic - spc.c/l_He) * 360.0
Phi_theo -= (Phi_theo[0]- Phi[0])
Phi -= Phi_theo
delay = T
X = Z.real
X_s = Z_s.real
Y = Z.imag
Y_s = Z_s.imag
# Fourier traffo
Zg = fk.GaussWindow(T, Z, False)
Td = T[1]-T[0]
AC = np.exp(-4.0 * np.log(2) * ((Ttheo) / AC_FWHM)**2)
Fano = np.exp((Ttheo) / Fano_FWHM)
# loop over the mfli devices
for dev in device:
# loop over the demodulators
for d in demod:
mfli_harmonic = data[dev]['harmonic'][int(d)]
i = str(mfli_harmonic) + 'H'
Z = data[dev]['x' + d] + 1j * data[dev]['y' + d]
Z_s = data[dev]['s_x' + d] + 1j * data[dev]['s_y' + d]
# Create theoretical curve
# if draw_theory:
Xtd, Ytd, Xt, Yt = fk.Curve(l_trans, l_ref, harmonic, phi,
a * max(abs(Z)), offset, T[0], T[-1],
np.size(T))
Xtd_gaus, Ytd_gaus, Xt_gaus, Yt_gaus = fk.Curve(
l_fel / harmonic, l_ref, harmonic, phi, a * max(abs(Z)), offset,
T[0] - t_corr, T[-1] - t_corr, np.size(T))
Xt *= Fano
Yt *= Fano
# Xt -= 1*Xt_gaus*abs(data[dev]['x0'] + 1j * data[dev]['y0'])/max(abs(data[dev]['x0'] + 1j * data[dev]['y0']))
# Yt -= 1*Yt_gaus*abs(data[dev]['x0'] + 1j * data[dev]['y0'])/max(abs(data[dev]['x0'] + 1j * data[dev]['y0']))
# correct time and phase for susceptibility
T += t_corr
Z *= np.exp(1j * np.pi * phi_sus / 180.0) # correction of phase
if plotTheo:
T = Ttheo + t_corr
mfli_harmonic = data[device]['harmonic'][int(demod)]
i = str(mfli_harmonic) + 'H'
Z = (data[device]['x' + demod] + 1j * data[device]['y' + demod]
) # / data['LDM']['I0']
if i0_correction:
Z = Z * (np.nanmean(data['LDM']['I0']) / data['LDM']['I0'])
R = np.abs(Z)
Phi = np.angle(Z, deg=False)
# plt.plot(np.unwrap(Phi))
# Create theoretical curve
Ttheo = np.linspace(delay[0], delay[-1], 30000)
Xtd, Ytd, Xt, Yt = fk.Curve(spc.h * spc.c / (spc.e * l_trans) * 1e9, l_ref,
harmonic, phi, A, 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
# Fourier traffo
Td = np.mean(np.unique(np.diff(delay)))
if gauss:
Zg = fk.GaussWindow(T_d, Z_cut, suscept)