def test_dynamic(self):
dynamic_simulation = DynamicSimulation(self.time_steps, self.fiber)
dynamic_simulation.add_forward_signal(wl=self.signal_wl,
input_power=self.signal_power,
loss=decibel_to_exp(1))
dynamic_simulation.add_backward_pump(wl=self.pump_wl,
input_power=self.pump_power,
loss=decibel_to_exp(2))
dynamic_simulation.add_forward_pump(wl=self.pump_wl,
input_power=self.pump_power)
dynamic_result = dynamic_simulation.run(self.z_nodes,
stop_at_steady_state=True,
dt=1e-7)
dyn_losses = dynamic_result.powers_at_fiber_end() / np.array(
[self.signal_power, self.pump_power, self.pump_power])
self.assertTrue(
np.allclose(to_db(dyn_losses),
self.expected_losses,
atol=1e-2,
rtol=1e-5))
def test_steady_state_python_and_cpp_two_rings(self):
fiber_with_rings = deepcopy(self.fiber)
dynamic_simulation = DynamicSimulation(self.time_steps, fiber_with_rings)
fiber_with_rings.doping_profile = DopingProfile(ion_number_densities=[self.nt, self.nt],
radii=[self.fiber.core_radius / 2, self.fiber.core_radius],
num_of_angular_sections=1,
core_radius=fiber_with_rings.core_radius)
dynamic_simulation.add_forward_signal(wl=self.signal_wl, input_power=self.signal_power)
dynamic_simulation.add_backward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
dynamic_simulation.add_forward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
dynamic_simulation.add_ase(wl_start=1020e-9, wl_end=1040e-9, n_bins=3)
dynamic_simulation.use_cpp_backend()
cpp_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
dynamic_simulation.use_python_backend()
python_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
dynamic_simulation.use_pythran_backend()
pythran_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_numba_backend()
numba_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
cpp_output_powers = cpp_result.powers_at_fiber_end()
python_output_powers = python_result.powers_at_fiber_end()
pythran_output_powers = pythran_result.powers_at_fiber_end()
numba_output_powers = numba_result.powers_at_fiber_end()
expected_output_regression = np.array([1.24777744e-01, 3.00422189e-01, 2.20328594e-07,
2.32154962e-07, 1.80296310e-07, 3.01232103e-01,
2.42163293e-07, 2.52449606e-07, 1.91762700e-07])
self.assertTrue(np.allclose(cpp_output_powers, python_output_powers, rtol=1e-6))
self.assertTrue(np.allclose(cpp_output_powers, expected_output_regression, rtol=1e-6))
self.assertTrue(np.allclose(pythran_output_powers, expected_output_regression, rtol=1e-6))
self.assertTrue(np.allclose(numba_output_powers, expected_output_regression, rtol=1e-6))
def test_steady_state_python_and_cpp_single_ring(self):
steady_state_simulation = SteadyStateSimulation(self.fiber)
steady_state_simulation.add_forward_signal(wl=self.signal_wl, input_power=self.signal_power)
steady_state_simulation.add_backward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
steady_state_simulation.add_forward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
steady_state_simulation.add_ase(wl_start=1020e-9, wl_end=1040e-9, n_bins=3)
steady_state_result = steady_state_simulation.run(tol=1e-5)
dynamic_simulation = DynamicSimulation(self.time_steps, self.fiber)
dynamic_simulation.add_forward_signal(wl=self.signal_wl, input_power=self.signal_power)
dynamic_simulation.add_backward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
dynamic_simulation.add_forward_pump(wl=self.pump_wl, input_power=self.pump_power / 2)
dynamic_simulation.add_ase(wl_start=1020e-9, wl_end=1040e-9, n_bins=3)
dynamic_simulation.use_cpp_backend()
cpp_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
dynamic_simulation.use_python_backend()
python_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
dynamic_simulation.use_pythran_backend()
pythran_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_numba_backend()
numba_result = dynamic_simulation.run(z_nodes=self.z_nodes, dt=self.steady_state_dt, stop_at_steady_state=True)
steady_state_output_powers = steady_state_result.powers_at_fiber_end()
cpp_output_powers = cpp_result.powers_at_fiber_end()
python_output_powers = python_result.powers_at_fiber_end()
pythran_output_powers = pythran_result.powers_at_fiber_end()
numba_output_powers = numba_result.powers_at_fiber_end()
self.assertTrue(np.allclose(steady_state_output_powers, cpp_output_powers, rtol=1e-3))
self.assertTrue(np.allclose(cpp_output_powers, python_output_powers, rtol=1e-6))
self.assertTrue(np.allclose(pythran_output_powers, python_output_powers, rtol=1e-6))
self.assertTrue(np.allclose(numba_output_powers, python_output_powers, rtol=1e-6))
def test_available_backends(self):
dynamic_simulation = DynamicSimulation(self.time_steps, self.fiber)
print('Tested dynamic backends: {}'.format(dynamic_simulation.backends))
def test_steady_state_reflection(self):
dynamic_simulation = DynamicSimulation(self.time_steps, self.fiber)
dynamic_simulation.add_forward_signal(wl=self.signal_wl,
input_power=self.signal_power,
channel_id='forward_signal',
reflection_target_id='reflected_signal',
reflectance=0.04)
dynamic_simulation.add_backward_signal(wl=self.signal_wl,
input_power=1e-15,
channel_id='reflected_signal')
dynamic_simulation.add_backward_pump(wl=self.pump_wl,
input_power=self.pump_power)
dynamic_simulation.use_cpp_backend()
cpp_res = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_python_backend()
python_res = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_pythran_backend()
pythran_res = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_numba_backend()
numba_res = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
cpp_output = cpp_res.powers_at_fiber_end()
python_output = python_res.powers_at_fiber_end()
pythran_output = pythran_res.powers_at_fiber_end()
numba_output = numba_res.powers_at_fiber_end()
expected_output = np.array([0.11878692, 0.00564412, 0.47651562])
self.assertTrue(np.allclose(cpp_output, python_output, rtol=1e-6))
self.assertTrue(np.allclose(cpp_output, expected_output, rtol=1e-6))
self.assertTrue(np.allclose(pythran_output, expected_output, rtol=1e-6))
self.assertTrue(np.allclose(numba_output, expected_output, rtol=1e-6))
def test_steady_state_python_and_cpp_two_rings(self):
dynamic_simulation = DynamicSimulation(self.time_steps)
fiber_with_rings = deepcopy(self.fiber)
fiber_with_rings.set_doping_profile(
ion_number_densities=[self.nt, self.nt],
radii=[self.fiber.core_radius / 2, self.fiber.core_radius])
dynamic_simulation.fiber = fiber_with_rings
dynamic_simulation.add_forward_signal(wl=self.signal_wl,
input_power=self.signal_power)
dynamic_simulation.add_backward_pump(wl=self.pump_wl,
input_power=self.pump_power / 2)
dynamic_simulation.add_forward_pump(wl=self.pump_wl,
input_power=self.pump_power / 2)
dynamic_simulation.add_ase(wl_start=1020e-9, wl_end=1040e-9, n_bins=3)
dynamic_simulation.use_cpp_backend()
cpp_result = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
dynamic_simulation.use_python_backend()
python_result = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt,
stop_at_steady_state=True)
cpp_output_powers = cpp_result.powers_at_fiber_end()
python_output_powers = python_result.powers_at_fiber_end()
expected_output_regression = np.array([
1.24777656e-01, 3.00423131e-01, 2.20330515e-07, 2.32158298e-07,
1.80295869e-07, 3.01233048e-01, 2.42165526e-07, 2.52453304e-07,
1.91762386e-07
])
self.assertTrue(
np.allclose(cpp_output_powers, python_output_powers, rtol=1e-6))
self.assertTrue(
np.allclose(cpp_output_powers,
expected_output_regression,
rtol=1e-6))
def test_steady_state_python_and_cpp_preset_areas_and_overlaps(self):
dynamic_simulation = DynamicSimulation(self.time_steps)
fiber_with_rings = deepcopy(self.fiber)
r = self.fiber.core_radius
areas = np.pi * (np.array([r / 2, r])**2 - np.array([0, r / 2])**2)
overlaps = [0.5, 0.2]
fiber_with_rings.set_doping_profile(
ion_number_densities=[self.nt, self.nt], areas=areas)
dynamic_simulation.fiber = fiber_with_rings
dynamic_simulation.add_forward_signal(
wl=self.signal_wl,
input_power=self.signal_power,
mode_shape_parameters={'overlaps': overlaps})
dynamic_simulation.add_backward_pump(
wl=self.pump_wl,
input_power=self.pump_power / 2,
mode_shape_parameters={'overlaps': overlaps})
dynamic_simulation.add_forward_pump(
wl=self.pump_wl,
input_power=self.pump_power / 2,
mode_shape_parameters={'overlaps': overlaps})
dynamic_simulation.use_cpp_backend()
cpp_result = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt / 10,
stop_at_steady_state=True)
dynamic_simulation.use_python_backend()
python_result = dynamic_simulation.run(z_nodes=self.z_nodes,
dt=self.steady_state_dt / 10,
stop_at_steady_state=True)
expected_output_regression = np.array(
[0.1166232, 0.23989275, 0.23988858])
cpp_output_powers = cpp_result.powers_at_fiber_end()
python_output_powers = python_result.powers_at_fiber_end()
self.assertTrue(
np.allclose(cpp_output_powers, python_output_powers, rtol=1e-6))
self.assertTrue(
np.allclose(cpp_output_powers,
expected_output_regression,
rtol=1e-6))
def setUpClass(cls):
yb_number_density = 5e25
radii = np.array([2, 4, 6, 8, 10]) * 1e-6
core_radius = 10e-6
doping_radius = 6e-6
confined_doping_profile = DopingProfile(
radii=radii[:-2],
num_of_angular_sections=6,
ion_number_densities=[yb_number_density] * 18,
core_radius=core_radius)
confined_fiber_length = 30
core_na = 0.065
core_clad_ratio = 20 / 400
signal_wl = 1064e-9
pump_wl = 976e-9
confined_fiber_20_400 = YbDopedDoubleCladFiber(
length=confined_fiber_length,
core_radius=core_radius,
ion_number_density=0,
background_loss=0,
core_na=core_na,
ratio_of_core_and_cladding_diameters=core_clad_ratio)
confined_fiber_20_400.doping_profile = confined_doping_profile
fundamental_mode_content = 0.98
lp11_content = (1 - fundamental_mode_content)
signal_power = 5 # W
LP01_power = fundamental_mode_content * signal_power
LP11_cos_power = 0.5 * lp11_content * signal_power
LP11_sin_power = 0.5 * lp11_content * signal_power
pump_power = 1000
max_time_steps = 1_000_000
z_nodes = 200
fiber_modes = mode_solver.find_all_modes(core_radius, core_na,
signal_wl)
confined_fiber_simulation = DynamicSimulation(max_time_steps,
confined_fiber_20_400)
confined_fiber_simulation.add_forward_signal(wl=signal_wl,
input_power=LP01_power,
mode=fiber_modes[0],
channel_id='LP01')
confined_fiber_simulation.add_forward_signal(
wl=signal_wl,
input_power=LP11_cos_power,
mode=fiber_modes[1],
channel_id='LP11_cos')
confined_fiber_simulation.add_forward_signal(
wl=signal_wl,
input_power=LP11_sin_power,
mode=fiber_modes[2],
channel_id='LP11_sin')
confined_fiber_simulation.add_backward_pump(wl=pump_wl,
input_power=pump_power,
channel_id='Pump')
cls.confined_res = confined_fiber_simulation.run(
z_nodes, dt=1e-7, stop_at_steady_state=True)