def generate_map_and_waterfall_plots(domain):
""" Generate map and waterfall plots to visualise pulse propagation. """
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(
Fibre("fibre",
length=0.5 * np.pi,
beta=[0.0, 0.0, -1.0, 0.0],
gamma=1.0,
method="rk4ip",
total_steps=1000,
traces=50))
system.run()
storage = system['fibre'].stepper.storage
(x, y, z) = storage.get_plot_data(reduced_range=(95.0, 105.0))
map_plot(x,
y,
z,
labels["t"],
labels["P_t"],
labels["z"],
filename="soliton_map")
waterfall_plot(x,
y,
z,
labels["t"],
labels["z"],
labels["P_t"],
filename="soliton_waterfall",
y_range=(0.0, 16.0))
def generate_overview_plots(domain):
""" Generate single, map, and waterfall plots of the soliton collision. """
system = System(domain)
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.625))
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.375, offset_nu=-0.8))
system.add(Fibre(length=400.0, beta=[0.0, 0.0, -0.1, 0.0],
gamma=2.2, total_steps=400, traces=100,
method='ARK4IP', local_error=1e-6))
system.run()
storage = system['fibre'].stepper.storage
(x, y, z) = storage.get_plot_data(reduced_range=(140.0, 360.0))
# Split step_sizes (list of tuples) into separate lists;
# distances and steps:
(distances, steps) = zip(*storage.step_sizes)
print np.sum(steps)
single_plot(distances, steps, labels["z"], "Step size, h (km)",
filename="soliton_collision_steps")
map_plot(x, y, z, labels["t"], labels["P_t"], labels["z"],
filename="soliton_collision_map")
waterfall_plot(x, y, z, labels["t"], labels["z"], labels["P_t"],
filename="soliton_collision_waterfall",
y_range=(0.0, 0.02))
def save_simulations(domain, data_directory, methods, target_errors):
""" Save simulation data for each method to file. """
for method in methods:
print("%s" % method)
for target_error in target_errors:
print("\t%.1e" % target_error)
method_error = "-".join([method, "%.0e" % (target_error)])
filename = os.path.join(data_directory, method_error)
system = System(domain)
system.add(
Sech(peak_power=8.8e-3, width=(1.0 / 0.44), position=0.625))
system.add(
Sech(peak_power=8.8e-3,
width=(1.0 / 0.44),
position=0.375,
offset_nu=-0.8))
system.add(
Fibre("fibre",
length=400.0,
beta=[0.0, 0.0, -0.1, 0.0],
gamma=2.2,
method=method,
local_error=target_error))
system.run()
A_calc = system.fields['fibre']
storage = system["fibre"].stepper.storage
np.savez(filename, field=A_calc, ffts=storage.fft_total)
def save_simulations(domain, data_directory, methods, target_errors):
""" Save simulation data for each method to file. """
for method in methods:
print "%s" % method
for target_error in target_errors:
print "\t%.1e" % target_error
method_error = "-".join([method, "%.0e" % (target_error)])
filename = os.path.join(data_directory, method_error)
system = System(domain)
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.625))
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.375, offset_nu=-0.8))
system.add(Fibre("fibre", length=400.0,
beta=[0.0, 0.0, -0.1, 0.0], gamma=2.2,
method=method, local_error=target_error))
system.run()
A_calc = system.fields['fibre']
storage = system["fibre"].stepper.storage
np.savez(filename, field=A_calc, ffts=storage.fft_total)
def generate_overview_plots(domain):
""" Generate single, map, and waterfall plots of the soliton collision. """
system = System(domain)
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.625))
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.375, offset_nu=-0.8))
system.add(Fibre(length=400.0, beta=[0.0, 0.0, -0.1, 0.0],
gamma=2.2, total_steps=400, traces=100,
method='ARK4IP', local_error=1e-6))
system.run()
storage = system['fibre'].stepper.storage
(x, y, z) = storage.get_plot_data(reduced_range=(140.0, 360.0))
# Split step_sizes (list of tuples) into separate lists;
# distances and steps:
(distances, steps) = list(zip(*storage.step_sizes))
print(np.sum(steps))
single_plot(distances, steps, labels["z"], "Step size, h (km)",
filename="soliton_collision_steps")
map_plot(x, y, z, labels["t"], labels["P_t"], labels["z"],
filename="soliton_collision_map")
waterfall_plot(x, y, z, labels["t"], labels["z"], labels["P_t"],
filename="soliton_collision_waterfall",
y_range=(0.0, 0.02))
def save_simulations(domain, data_directory, methods, target_errors):
""" Save data for each method and target error to file. """
for method in methods:
print("%s" % method)
for target_error in target_errors:
print("\t%.1e" % target_error)
method_error = "-".join([method, "%.0e" % (target_error)])
filename = os.path.join(data_directory, method_error)
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(
Fibre("fibre",
length=0.5 * np.pi,
beta=[0.0, 0.0, -1.0, 0.0],
gamma=1.0,
method=method,
local_error=target_error))
system.run()
A_calc = system.fields['fibre']
storage = system["fibre"].stepper.storage
np.savez(filename, field=A_calc, ffts=storage.fft_total)
def generate_reference(domain, data_directory):
""" Generate a reference field (to machine precision), used as A_true. """
system = System(domain)
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.125))
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=-0.125, offset_nu=-0.8))
system.add(Fibre("fibre", length=400.0, beta=[0.0, 0.0, -0.1, 0.0],
gamma=2.2, method="ark4ip", local_error=1e-14))
system.run()
A_true = system.field
filename = os.path.join(data_directory, "reference_field")
np.save(filename, A_true)
def generate_reference(domain, data_directory):
""" Generate a reference field (to machine precision), used as A_true. """
system = System(domain)
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.625))
system.add(Sech(peak_power=8.8e-3, width=(1.0 / 0.44),
position=0.375, offset_nu=-0.8))
system.add(Fibre("fibre", length=400.0, beta=[0.0, 0.0, -0.1, 0.0],
gamma=2.2, method="ark4ip", local_error=1e-14))
system.run()
A_true = system.field
filename = os.path.join(data_directory, "reference_field")
np.save(filename, A_true)
def save_simulations(domain, data_directory, methods, steps):
""" Save data for each method and step to file. """
for method in methods:
print "%s" % method
for step in steps:
print "\t%d" % step
method_step = "-".join([method, str(step)])
filename = os.path.join(data_directory, method_step)
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(
Fibre(
"fibre", length=0.5 * np.pi, beta=[0.0, 0.0, -1.0, 0.0], gamma=1.0, method=method, total_steps=step
)
)
system.run()
A_calc = system.fields["fibre"]
np.save(filename, A_calc)
def save_simulations(domain, data_directory, methods, target_errors):
""" Save data for each method and target error to file. """
for method in methods:
print "%s" % method
for target_error in target_errors:
print "\t%.1e" % target_error
method_error = "-".join([method, "%.0e" % (target_error)])
filename = os.path.join(data_directory, method_error)
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(Fibre("fibre", length=0.5 * np.pi,
beta=[0.0, 0.0, -1.0, 0.0], gamma=1.0,
method=method, local_error=target_error))
system.run()
A_calc = system.fields['fibre']
storage = system["fibre"].stepper.storage
np.savez(filename, field=A_calc, ffts=storage.fft_total)
def generate_map_and_waterfall_plots(domain):
""" Generate map and waterfall plots to visualise pulse propagation. """
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(
Fibre(
"fibre",
length=0.5 * np.pi,
beta=[0.0, 0.0, -1.0, 0.0],
gamma=1.0,
method="rk4ip",
total_steps=1000,
traces=50,
)
)
system.run()
storage = system["fibre"].stepper.storage
(x, y, z) = storage.get_plot_data(reduced_range=(95.0, 105.0))
map_plot(x, y, z, labels["t"], labels["P_t"], labels["z"], filename="soliton_map")
waterfall_plot(x, y, z, labels["t"], labels["z"], labels["P_t"], filename="soliton_waterfall", y_range=(0.0, 16.0))
def save_simulations(domain, data_directory, methods, steps):
""" Save data for each method and step to file. """
for method in methods:
print "%s" % method
for step in steps:
print "\t%d" % step
method_step = "-".join([method, str(step)])
filename = os.path.join(data_directory, method_step)
system = System(domain)
system.add(Sech(peak_power=4.0, width=1.0))
system.add(
Fibre("fibre",
length=0.5 * np.pi,
beta=[0.0, 0.0, -1.0, 0.0],
gamma=1.0,
method=method,
total_steps=step))
system.run()
A_calc = system.fields['fibre']
np.save(filename, A_calc)
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
from pyofss import Domain, System, Gaussian, Fibre
from pyofss import temporal_power, multi_plot, labels
system = System(Domain(bit_width=200.0, samples_per_bit=2048))
system.add(Gaussian("gaussian", peak_power=1.0, width=1.0))
system.run()
P_ts = [temporal_power(system.fields['gaussian'])]
fibres = [
Fibre(length=5.0, beta=[0.0, 0.0, 0.0, 1.0], total_steps=100),
Fibre(length=5.0, beta=[0.0, 0.0, 1.0, 1.0], total_steps=100)
]
for fibre in fibres:
system = System(Domain(bit_width=200.0, samples_per_bit=2048))
system.add(Gaussian(peak_power=1.0, width=1.0))
system.add(fibre)
system.run()
P_ts.append(temporal_power(system.fields['fibre']))
z_labels = [
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see <http://www.gnu.org/licenses/>.
"""
from pyofss import Domain, System, Gaussian, Fibre
from pyofss import temporal_power, spectral_power, double_plot, labels
system = System(Domain(bit_width=200.0, samples_per_bit=2048))
system.add(Gaussian(peak_power=1.0, width=1.0))
system.add(Fibre(length=5.0, beta=[0.0, 0.0, 0.0, 1.0],
gamma=1.0, total_steps=100))
system.run()
P_t = temporal_power(system.fields['fibre'])
P_nu_normalised = spectral_power(system.fields['fibre'], True)
double_plot(system.domain.t, P_t, system.domain.nu, P_nu_normalised,
labels['t'], labels['P_t'], labels['nu'], labels['P_nu'],
x_range=(95.0, 120.0), X_range=(192.6, 193.7), filename="4-15")
a high zoom level.
"""
from pyofss import Domain, System, Gaussian, Fibre
from pyofss import temporal_power, multi_plot, labels
domain = Domain(bit_width=200.0, samples_per_bit=2048)
gaussian = Gaussian(peak_power=1.0, width=1.0)
P_ts = []
methods = ['ss_simple', 'ss_symmetric', 'ss_sym_rk4', 'rk4ip']
for m in methods:
sys = System(domain)
sys.add(gaussian)
sys.add(
Fibre(length=5.0,
method=m,
total_steps=50,
beta=[0.0, 0.0, 0.0, 1.0],
gamma=1.0))
sys.run()
P_ts.append(temporal_power(sys.field))
multi_plot(sys.domain.t,
P_ts,
methods,
labels["t"],
labels["P_t"],
methods,
x_range=(80.0, 140.0))
import time
TS = 4096
GAMMA = 100.0
STEPS = 800
LENGTH = 0.1
DOMAIN = Domain(bit_width=30.0, samples_per_bit=TS)
SYS = System(DOMAIN)
SYS.add(Gaussian("gaussian", peak_power=1.0, width=1.0))
SYS.add(Fibre("fibre", beta=[0.0, 0.0, 0.0, 1.0], gamma=GAMMA,
length=LENGTH, total_steps=STEPS, method="RK4IP"))
start = time.clock()
SYS.run()
stop = time.clock()
NO_OCL_DURATION = (stop - start) / 1000.0
NO_OCL_OUT = SYS.fields["fibre"]
sys = System(DOMAIN)
sys.add(Gaussian("gaussian", peak_power=1.0, width=1.0))
sys.add(OpenclFibre(TS, dorf="float", length=LENGTH, total_steps=STEPS))
start = time.clock()
sys.run()
stop = time.clock()
OCL_DURATION = (stop - start) / 1000.0
OCL_OUT = sys.fields["ocl_fibre"]
NO_OCL_POWER = temporal_power(NO_OCL_OUT)
return self.nonlinearity.exp_non(A, h, B)
if __name__ == "__main__":
"""
Plot the result of a Gaussian pulse propagating through optical fibre.
Simulates both (third-order) dispersion and nonlinearity.
Use five different methods: ss_simple, ss_symmetric, ss_sym_rk4,
ss_sym_rkf, and rk4ip. Expect all five methods to produce similar results;
plot traces should all overlap. Separate traces should only be seen at
a high zoom level.
"""
from pyofss import Domain, System, Gaussian, Fibre
from pyofss import temporal_power, multi_plot, labels
domain = Domain(bit_width=200.0, samples_per_bit=2048)
gaussian = Gaussian(peak_power=1.0, width=1.0)
P_ts = []
methods = ['ss_simple', 'ss_symmetric', 'ss_sym_rk4', 'rk4ip']
for m in methods:
sys = System(domain)
sys.add(gaussian)
sys.add(Fibre(length=5.0, method=m, total_steps=50,
beta=[0.0, 0.0, 0.0, 1.0], gamma=1.0))
sys.run()
P_ts.append(temporal_power(sys.field))
multi_plot(sys.domain.t, P_ts, methods, labels["t"], labels["P_t"],
methods, x_range=(80.0, 140.0))
