def test_sim_parameters():
sim_params = {'nli_params': {}, 'raman_params': {}}
SimParams.set_params(sim_params)
s1 = SimParams.get()
assert s1.nli_params.method == 'gn_model_analytic'
s2 = SimParams.get()
assert not s1.raman_params.flag
sim_params['raman_params']['flag'] = True
SimParams.set_params(sim_params)
assert s2.raman_params.flag
assert s1.raman_params.flag
empty, vstack, trapz, arcsinh, clip, abs, sum
from operator import attrgetter
from logging import getLogger
import scipy.constants as ph
from scipy.integrate import solve_bvp
from scipy.integrate import cumtrapz
from scipy.interpolate import interp1d
from scipy.optimize import OptimizeResult
from math import isclose
from gnpy.core.utils import db2lin, lin2db
from gnpy.core.exceptions import EquipmentConfigError
from gnpy.core.parameters import SimParams
logger = getLogger(__name__)
sim_params = SimParams.get()
def propagate_raman_fiber(fiber, *carriers):
raman_params = sim_params.raman_params
nli_params = sim_params.nli_params
# apply input attenuation to carriers
attenuation_in = db2lin(fiber.params.con_in + fiber.params.att_in)
chan = []
for carrier in carriers:
pwr = carrier.power
pwr = pwr._replace(signal=pwr.signal / attenuation_in,
nli=pwr.nli / attenuation_in,
ase=pwr.ase / attenuation_in)
carrier = carrier._replace(power=pwr)
chan.append(carrier)
carriers = tuple(f for f in chan)