vec_E_mean = np.zeros([vec_len])
vec_E_med = np.zeros([vec_len])
vec_E_std = np.zeros([vec_len])
vec_E_mad = np.zeros([vec_len])
vec_spectrum = np.zeros([vec_len,nbins])
vec_q = np.zeros([vec_len])
vec_size_x = np.zeros([vec_len])
vec_emittance_y = np.zeros([vec_len])
vec_emittance_z = np.zeros([vec_len])
vec_divergence_rms = np.zeros([vec_len])
for t in range(len(tsi)):
print('file:\t',f,' \t timestep:\t',t)
# energy distribution characteristics
energy_axis[f], vec_spectrum[t], vec_E_peak[t], vec_dQdE_max[t], vec_E_fwhm[t] = l.getSpectrum(tmp,tsi[t], E_min=Emin, E_max = Emax, print_flag=False)
# beam parameter filter around energy peak
if (vec_E_peak[t] == 0) or (vec_E_fwhm[t] == 0) :
try:
param_dict = l.getBeamParam(tmp,tsi[t], E_min=Emin, E_max = Emax,print_flag=False)
vec_E_mean[t] = param_dict['energy_wmean']
vec_E_med[t] = param_dict['energy_wmedian']
vec_E_std[t] = param_dict['energy_rms']
vec_E_mad[t] = param_dict['energy_wmad']
vec_E_peak[t] = np.nan
vec_E_fwhm[t] = np.nan
vec_dQdE_max[t] = vec_spectrum.max()
vec_emittance_y[t] = param_dict['emittance_y']
vec_emittance_z[t] = param_dict['emittance_z']
vec_emittance_y = np.zeros([vec_len])
vec_emittance_z = np.zeros([vec_len])
vec_divergence_rms = np.zeros([vec_len])
for t in range(len(tsi)):
print('file:\t', f)
print('timestep:\t', t)
# value and position of the max of a0
x, a = l.getMaxinMovingWindow(tmp)
vec_a0_max[t] = a.max()
vec_x_a0_max[t] = x[a.argmax()]
# energy distribution characteristics
energy_axis[f], vec_spectrum[t], vec_E_peak[
t], vec_dQdE_max[t], vec_E_fwhm[t] = l.getSpectrum(
tmp,
tsi[t],
E_min=Emin,
E_max=Emax,
print_flag=True)
# beam parameter filter around energy peak
if (vec_E_peak[t] == 0) or (vec_E_fwhm[t] == 0):
param_list = l.getBeamParam(tmp,
ts[t],
E_min=Emin,
E_max=Emax,
print_flag=True)
vec_E_std[t] = param_list[3]
vec_E_peak[t] = np.nan
vec_E_fwhm[t] = np.nan
vec_E_std[t] = param_list[3]
vec_dQdE_max[t] = spectrum.max()
vec_emittance_y[t] = param_list[5]
else :
injection_flag[f] = True
print(" ###################################################\n",
'#\t injection occured at:\t',ti[f],' \n',
"###################################################")
# only the given the timestep value
# laser self-focusing
x,a = l.getMaxinMovingWindow(tmp)
a0_max[f] = a.max()
x_a0_max[f] = x[a.argmax()]
# energy distribution
energy_axis[f], spectrum[f], E_peak[f], dQdE_max[f], E_fwhm[f] = l.getSpectrum(tmp,ts[timeStep], E_min=Emin, E_max = Emax, print_flag=False)
# beam parameter filter around
if (E_peak[f] == 0) or (E_fwhm[f] == 0) :
param_list = l.getBeamParam(tmp,ts[-1], E_min=Emin, E_max = Emax,print_flag=False)
E_mean[f] = param_list['energy_wmean']
E_med[f] = param_list['energy_wmedian']
E_wstd[f] = param_list['energy_wrms']
E_std[f] = param_list["energy_rms"]
E_mad[f] = param_list['energy_wmad']
E_peak[f] = np.nan
E_fwhm[f] = np.nan
dQdE_max[f] = spectrum.max()
emittance_y[f] = param_list['emittancey']
emittance_z[f] = param_list['emittancez']
divergence_rms[f] = param_list['divergence_rms']
vec_E_mad = np.zeros([vec_len])
vec_spectrum = np.zeros([vec_len, nbins])
vec_q = np.zeros([vec_len])
vec_size_x = np.zeros([vec_len])
vec_emittance_y = np.zeros([vec_len])
vec_emittance_z = np.zeros([vec_len])
vec_divergence_rms = np.zeros([vec_len])
for t in tqdm(range(len(tsi)), leave=False):
print('file:\t', f, ' \t timestep:\t', t)
# energy distribution characteristics
energy_axis[f], vec_spectrum[t, :], vec_E_peak[t], vec_dQdE_max[
t], vec_E_fwhm[t] = l.getSpectrum(tmp,
tsi[t],
E_min=Emin,
E_max=Emax,
print_flag=False)
# beam parameter filter around energy peak
if (vec_E_peak[t] == 0) or (vec_E_fwhm[t] == 0):
try:
param_list = l.getBeamParam(tmp,
tsi[t],
E_min=Emin,
E_max=Emax,
print_flag=False)
#print('DEBUG :\n',param_list)
vec_E_mean[t] = param_list['energy_wmean']
vec_E_med[t] = param_list['energy_wmedian']
vec_E_std[t] = param_list['energy_rms']