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Ground work for plasma done

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This commit is contained in:
Benoît Sierro
2021-10-21 15:53:04 +02:00
parent aebc0cef85
commit 7b490d110e
1 changed files with 227 additions and 217 deletions
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444
src/scgenerator/operators.py
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@@ -153,223 +153,6 @@ class ConstantDirectDispersion(AbstractDispersion):
return self.disp_arr_const
##################################################
##################### LINEAR #####################
##################################################
class LinearOperator(Operator):
def __init__(self, dispersion_op: AbstractDispersion, loss_op: AbstractLoss):
self.dispersion_op = dispersion_op
self.loss_op = loss_op
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the linear operator to be multiplied by the spectrum in the frequency domain
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
linear component
"""
return self.dispersion_op(state) - self.loss_op(state) / 2
##################################################
################### NON LINEAR ###################
##################################################
# Raman
class AbstractRaman(Operator):
f_r: float = 0.0
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the raman component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
raman component
"""
class NoRaman(NoOp, AbstractRaman):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class Raman(AbstractRaman):
def __init__(self, raman_type: str, t: np.ndarray):
self.hr_w = fiber.delayed_raman_w(t, raman_type)
self.f_r = 0.245 if raman_type == "agrawal" else 0.18
def __call__(self, state: CurrentState) -> np.ndarray:
return self.f_r * np.fft.ifft(self.hr_w * np.fft.fft(state.field2))
# SPM
class AbstractSPM(Operator):
fraction: float = 1.0
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the SPM component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
SPM component
"""
class NoSPM(NoOp, AbstractSPM):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class SPM(AbstractSPM):
def __init__(self, raman_op: AbstractRaman):
self.fraction = 1 - raman_op.f_r
def __call__(self, state: CurrentState) -> np.ndarray:
return self.fraction * state.field2
# Self-Steepening
class AbstractSelfSteepening(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the self-steepening component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
self-steepening component
"""
class NoSelfSteepening(NoOp, AbstractSelfSteepening):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class SelfSteepening(AbstractSelfSteepening):
def __init__(self, w_c: np.ndarray, w0: float):
self.arr = w_c / w0
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr
# Gamma operator
class AbstractGamma(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the gamma component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
gamma component
"""
class ConstantScalarGamma(AbstractGamma):
def __init__(self, gamma: np.ndarray, t_num: int):
self.arr_const = gamma * np.ones(t_num)
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class NoGamma(ConstantScalarGamma):
def __init__(self, w: np.ndarray) -> None:
super().__init__(0, w)
class ConstantGamma(AbstractGamma):
def __init__(self, gamma_arr: np.ndarray):
self.arr = gamma_arr
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr
# Nonlinear combination
class NonLinearOperator(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the nonlinear operator applied on the spectrum in the frequency domain
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
nonlinear component
"""
class EnvelopeNonLinearOperator(NonLinearOperator):
def __init__(
self,
gamma_op: AbstractGamma,
ss_op: AbstractSelfSteepening,
spm_op: AbstractSPM,
raman_op: AbstractRaman,
):
self.gamma_op = gamma_op
self.ss_op = ss_op
self.spm_op = spm_op
self.raman_op = raman_op
def __call__(self, state: CurrentState) -> np.ndarray:
return (
-1j
* self.gamma_op(state)
* (1 + self.ss_op(state))
* np.fft.fft(state.field * (self.spm_op(state) + self.raman_op(state)))
)
##################################################
###################### LOSS ######################
##################################################
@@ -435,6 +218,233 @@ class CustomConstantLoss(ConstantLoss):
return self.arr
##################################################
##################### LINEAR #####################
##################################################
class LinearOperator(Operator):
def __init__(self, dispersion_op: AbstractDispersion, loss_op: AbstractLoss):
self.dispersion_op = dispersion_op
self.loss_op = loss_op
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the linear operator to be multiplied by the spectrum in the frequency domain
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
linear component
"""
return self.dispersion_op(state) - self.loss_op(state) / 2
##################################################
###################### RAMAN #####################
##################################################
class AbstractRaman(Operator):
f_r: float = 0.0
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the raman component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
raman component
"""
class NoRaman(NoOp, AbstractRaman):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class Raman(AbstractRaman):
def __init__(self, raman_type: str, t: np.ndarray):
self.hr_w = fiber.delayed_raman_w(t, raman_type)
self.f_r = 0.245 if raman_type == "agrawal" else 0.18
def __call__(self, state: CurrentState) -> np.ndarray:
return self.f_r * np.fft.ifft(self.hr_w * np.fft.fft(state.field2))
##################################################
####################### SPM ######################
##################################################
class AbstractSPM(Operator):
fraction: float = 1.0
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the SPM component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
SPM component
"""
class NoSPM(NoOp, AbstractSPM):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class SPM(AbstractSPM):
def __init__(self, raman_op: AbstractRaman):
self.fraction = 1 - raman_op.f_r
def __call__(self, state: CurrentState) -> np.ndarray:
return self.fraction * state.field2
##################################################
################# SELF-STEEPENING ################
##################################################
class AbstractSelfSteepening(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the self-steepening component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
self-steepening component
"""
class NoSelfSteepening(NoOp, AbstractSelfSteepening):
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class SelfSteepening(AbstractSelfSteepening):
def __init__(self, w_c: np.ndarray, w0: float):
self.arr = w_c / w0
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr
##################################################
###################### GAMMA #####################
##################################################
class AbstractGamma(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the gamma component
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
gamma component
"""
class ConstantScalarGamma(AbstractGamma):
def __init__(self, gamma: np.ndarray, t_num: int):
self.arr_const = gamma * np.ones(t_num)
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr_const
class NoGamma(ConstantScalarGamma):
def __init__(self, w: np.ndarray) -> None:
super().__init__(0, w)
class ConstantGamma(AbstractGamma):
def __init__(self, gamma_arr: np.ndarray):
self.arr = gamma_arr
def __call__(self, state: CurrentState) -> np.ndarray:
return self.arr
##################################################
##################### PLASMA #####################
##################################################
##################################################
#################### NONLINEAR ###################
##################################################
class NonLinearOperator(Operator):
@abstractmethod
def __call__(self, state: CurrentState) -> np.ndarray:
"""returns the nonlinear operator applied on the spectrum in the frequency domain
Parameters
----------
state : CurrentState
current state of the simulation
Returns
-------
np.ndarray
nonlinear component
"""
class EnvelopeNonLinearOperator(NonLinearOperator):
def __init__(
self,
gamma_op: AbstractGamma,
ss_op: AbstractSelfSteepening,
spm_op: AbstractSPM,
raman_op: AbstractRaman,
):
self.gamma_op = gamma_op
self.ss_op = ss_op
self.spm_op = spm_op
self.raman_op = raman_op
def __call__(self, state: CurrentState) -> np.ndarray:
return (
-1j
* self.gamma_op(state)
* (1 + self.ss_op(state))
* np.fft.fft(state.field * (self.spm_op(state) + self.raman_op(state)))
)
##################################################
############### CONSERVED QUANTITY ###############
##################################################