if spectrogram:
# plot spec
figFT = plt.figure('scan_{0:03}_{1}_d{2}_SG_{3}'.format(
run, dev, d, i))
print(T_d[0], T_d[-1])
slide_step = Td #in fs
FWHM_slide = 20.0 #in fs
t_lim = data_window
slide_positions = np.arange(T_d[0], T_d[-1], slide_step)
S = np.zeros((np.size(T_d), np.size(wn)))
i = 0
for slide_pos in slide_positions:
Z_slide = fk.slide_window(
T_d, Z, slide_pos, FWHM_slide
) # multiply gaussian onto data set which is centered at current sliding position
wn, DFT_slide = fk.DFT(
T_d, Z_slide, Td, l_ref, harmonic, zeroPaddingFactor=2
) # FFT of interferogram which has been truncated by mulitplying wiht gaussian
# add DFT to spectrum-matrix while weighting with temporal gaussian envelope
# for i in range(np.size(T_d)):
# S[i,:] += abs(DFT_slide)/max(abs(DFT_slide))*fk.weighting_coeff(T_d[i], slide_pos, FWHM_slide)
S[i, :] += abs(DFT_slide) / max(abs(DFT_slide))
i += 1
S[:, :] /= np.size(slide_positions)
fk.plot_spectrogram(figFT, wn, T_d, S, l_fel, wn_lim, t_lim)
# plt.show()
if not interactive_plots:
plt.close('all')
else:
plt.show()
for slide_pos in slide_positions:
Z_slide = fk.slide_window(
delay, Z, slide_pos, FWHM_slide
) # multiply gaussian onto data set which is centered at current sliding position
wn, DFT_slide = fk.DFT(
T_d,
Z_slide,
Td,
l_ref,
harmonic,
zeroPaddingFactor=zeroPaddingFactor
) # FFT of interferogram which has been truncated by mulitplying wiht gaussian
S[i, :] += abs(DFT_slide) / max(abs(DFT_slide))
i += 1
S[:, :] /= np.size(slide_positions)
fk.plot_spectrogram(figFT, wn, delay, S, l_fel / 5., l_trans,
wn_lim_s, data_window)
plt.tight_layout()
if not interactive_plots:
plt.close('all')
else:
plt.show()
#i0_list = [i0_0H,i0_1H,i0_2H,i0_3H,i0_4H,i0_5H,i0_0H+i0_1H+i0_2H+i0_3H+i0_4H+i0_5H]
#for ii in i0_list:
# plt.plot(delay,ii)
# plt.xlabel('delay [fs]')
# plt.ylabel('i0 [a.u.]')
#plt.legend(['0H','1H','2H','3H','4H','5H','sum'])
#
slide_step = Td #in fs
FWHM_slide = 20.0 #in fs
t_lim = data_window
slide_positions = np.arange(delay[0],delay[-1], slide_step)
S = np.zeros((np.size(delay), np.size(wn)))
i = 0
for slide_pos in slide_positions:
Z_slide = fk.slide_window(delay, Z, slide_pos, FWHM_slide) # multiply gaussian onto data set which is centered at current sliding position
wn, DFT_slide = fk.DFT(delay, Z_slide, Td, l_ref, harmonic, zeroPaddingFactor = zeroPaddingFactor) # FFT of interferogram which has been truncated by mulitplying wiht gaussian
# add DFT to spectrum-matrix while weighting with temporal gaussian envelope
# for i in range(np.size(T_d)):
# S[i,:] += abs(DFT_slide)/max(abs(DFT_slide))*fk.weighting_coeff(T_d[i], slide_pos, FWHM_slide)
S[i,:] += abs(DFT_slide)/max(abs(DFT_slide))
i += 1
S[:,:] /= np.size(slide_positions)
fk.plot_spectrogram(figFT, wn, delay, S, l_fel/6., 1E7/l_trans, wn_lim_s, t_lim)
# plt.show()
#print delay
#figTD = plt.figure("zoom",figsize=(7,6))
#
#ax = figTD.add_subplot(111)
##ax.errorbar(delay, X, yerr=X_s, color='b', linestyle='')
#ax.plot(delay, Z.real, 'o-', color='b')
#ax.plot(delay, Z.imag, 'o-', color='g')
#ax.plot(Ttheo, Xt*0.34, 'b', alpha=0.3)
#ax.legend(['real','imag','real_theo'])
#ax.set_xlim(-20,20)
S = np.zeros((np.size(T_d), np.size(wn)))
i = 0
for slide_pos in slide_positions:
Z_slide = fk.slide_window(
T_d, Z, slide_pos, FWHM_slide
) # multiply gaussian onto data set which is centered at current sliding position
wn, DFT_slide = fk.DFT(
T_d, Z_slide, Td, l_ref, harmonic, zeroPaddingFactor=2
) # FFT of interferogram which has been truncated by mulitplying wiht gaussian
# add DFT to spectrum-matrix while weighting with temporal gaussian envelope
# for i in range(np.size(T_d)):
# S[i,:] += abs(DFT_slide)/max(abs(DFT_slide))*fk.weighting_coeff(T_d[i], slide_pos, FWHM_slide)
S[i, :] += abs(DFT_slide) / max(abs(DFT_slide))
i += 1
S[:, :] /= np.size(slide_positions)
fk.plot_spectrogram(figFT, wn, T_d, S, l_fel / 5, l_trans, wn_lim,
t_lim)
# plt.show()
if not interactive_plots:
plt.close('all')
else:
plt.show()
#''' Plots for Paper '''
#ticksize= 2.
#ticklength = 5.
#fontsize=16.
#plt.rcParams['xtick.labelsize'] = fontsize
#plt.rcParams['ytick.labelsize'] = fontsize
#plt.rcParams['axes.labelsize'] = fontsize
#plt.rcParams['xtick.major.width'] = ticksize
