import sys
import numpy as np
from scipy import interpolate
import optcom.utils.plot as plot
import optcom.layout as layout
import optcom.components.gaussian as gaussian
import optcom.domain as domain
from optcom.utils.utilities_user import temporal_power, spectral_power,\
CSVFit
lt = layout.Layout(domain.Domain(samples_per_bit=512,bit_width=20.0))
pulse = gaussian.Gaussian(channels=2, peak_power=[10.0, 10e-1],
width=[1.0, 5.0], center_lambda=[1050.0, 1048.0])
gamma_data = CSVFit('./data/gamma_test.txt')
fiber = Fiber(length=.10, method="ssfm_symmetric", alpha=[0.046],
alpha_order=4, beta_order=4, gamma=1.5,
nl_approx=False, ATT=True, DISP=True,
SPM=True, XPM=False, SS=False, RS=False, approx_type=1,
steps=1000, medium='sio2')
lt.link((pulse[0], fiber[0]))
lt.run(pulse)
x_datas = [pulse.fields[0].nu, fiber.fields[1].nu,
pulse.fields[0].time, fiber.fields[1].time]
y_datas = [spectral_power(pulse.fields[0].channels),
spectral_power(fiber.fields[1].channels),
temporal_power(pulse.fields[0].channels),
temporal_power(fiber.fields[1].channels)]
nbr_samples)
omegas = Domain.omega_to_lambda(lambdas)
absorp = Absorption(dopant=dopant)
sigmas = absorp.get_cross_section(omegas)
x_data.append(lambdas)
y_data.append(sigmas)
dopant_name = dopant[0].upper() + dopant[1:]
plot_titles.append(
'Cross sections {} from formula'.format(dopant_name))
for i, file in enumerate(files):
nbr_samples = 1000
lambdas = np.linspace(file_range[i][0], file_range[i][1], nbr_samples)
omegas = Domain.omega_to_lambda(lambdas)
file_name = folder + file + '.txt'
predict = CSVFit(file_name=file_name, conv_factor=[1e9, 1e18]) # in nm
absorp = Absorption(predict=predict)
sigmas = absorp.get_cross_section(omegas)
x_data.append(lambdas)
y_data.append(sigmas)
dopant_name = file[0].upper() + file[1:]
plot_titles.append(
'Absorption cross sections {} from data file'.format(dopant_name))
plot.plot(x_data,
y_data,
x_labels=['Lambda'],
y_labels=['sigma_a'],
split=True,
plot_colors='red',
plot_titles=plot_titles,
peak_power=[1.6 * or_p, 1.3 * or_p, 1.2 * or_p],
width=signal_width,
center_lambda=[1030.0, 1025.0, 1019.0])
nbr_ch_p = 2
#pump = gaussian.Gaussian(channels=nbr_ch_p, peak_power=[45.0, 35.0],
# center_lambda=[940.0, 977.0], width=[7.0, 6.0])
pump = cw.CW(channels=nbr_ch_p,
peak_power=[4 * or_p, 3 * or_p],
center_lambda=[976.0, 940.0])
steps = 500
length = 0.0005 # km
file_sigma_a = ('./data/fiber_amp/cross_section/absorption/yb.txt')
file_sigma_e = ('./data/fiber_amp/cross_section/emission/yb.txt')
sigma_a = CSVFit(file_sigma_a, conv_factor=[1e9, 1e18])
sigma_e = CSVFit(file_sigma_e, conv_factor=[1e9, 1e18])
#sigma_a = [3e-8, 2e-6]
#sigma_e = [2e-7, 1e-6]
#sigma_e = None
n_core = None
n_clad = None
NA = 0.2
r_core = 5.0 # um
r_clad = 62.5 # um
temperature = 293.15 # K
tau_meta = 840.0 # us
N_T = 6.3e-2 # nm^{-3}
eta_s = 1.26 # km^-1
eta_p = 1.41 # km^-1
R_0 = 8e-4