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meanas/meanas/fdtd/pml.py

128 lines
4.0 KiB
Python

"""
PML implementations
#TODO discussion of PMLs
#TODO cpml documentation
"""
# TODO retest pmls!
from typing import List, Callable, Tuple, Dict, Any
import numpy # type: ignore
from ..fdmath import fdfield_t
__author__ = 'Jan Petykiewicz'
5 years ago
def cpml(direction: int,
polarity: int,
dt: float,
epsilon: fdfield_t,
thickness: int = 8,
ln_R_per_layer: float = -1.6,
epsilon_eff: float = 1,
mu_eff: float = 1,
m: float = 3.5,
ma: float = 1,
cfs_alpha: float = 0,
dtype: numpy.dtype = numpy.float32,
) -> Tuple[Callable, Callable, Dict[str, fdfield_t]]:
if direction not in range(3):
raise Exception('Invalid direction: {}'.format(direction))
if polarity not in (-1, 1):
raise Exception('Invalid polarity: {}'.format(polarity))
if thickness <= 2:
raise Exception('It would be wise to have a pml with 4+ cells of thickness')
if epsilon_eff <= 0:
raise Exception('epsilon_eff must be positive')
sigma_max = -ln_R_per_layer / 2 * (m + 1)
kappa_max = numpy.sqrt(epsilon_eff * mu_eff)
alpha_max = cfs_alpha
transverse = numpy.delete(range(3), direction)
u, v = transverse
xe = numpy.arange(1, thickness + 1, dtype=float)
xh = numpy.arange(1, thickness + 1, dtype=float)
if polarity > 0:
xe -= 0.5
elif polarity < 0:
xh -= 0.5
xe = xe[::-1]
xh = xh[::-1]
else:
raise Exception('Bad polarity!')
expand_slice_l: List[Any] = [None] * 3
expand_slice_l[direction] = slice(None)
expand_slice = tuple(expand_slice_l)
def par(x):
scaling = (x / thickness) ** m
sigma = scaling * sigma_max
kappa = 1 + scaling * (kappa_max - 1)
alpha = ((1 - x / thickness) ** ma) * alpha_max
p0 = numpy.exp(-(sigma / kappa + alpha) * dt)
p1 = sigma / (sigma + kappa * alpha) * (p0 - 1)
p2 = 1 / kappa
return p0[expand_slice], p1[expand_slice], p2[expand_slice]
p0e, p1e, p2e = par(xe)
p0h, p1h, p2h = par(xh)
region_list = [slice(None)] * 3
if polarity < 0:
region_list[direction] = slice(None, thickness)
elif polarity > 0:
region_list[direction] = slice(-thickness, None)
else:
raise Exception('Bad polarity!')
region = tuple(region_list)
se = 1 if direction == 1 else -1
# TODO check if epsilon is uniform in pml region?
shape = list(epsilon[0].shape)
shape[direction] = thickness
psi_e = [numpy.zeros(shape, dtype=dtype), numpy.zeros(shape, dtype=dtype)]
psi_h = [numpy.zeros(shape, dtype=dtype), numpy.zeros(shape, dtype=dtype)]
fields = {
'psi_e_u': psi_e[0],
'psi_e_v': psi_e[1],
'psi_h_u': psi_h[0],
'psi_h_v': psi_h[1],
}
# Note that this is kinda slow -- would be faster to reuse dHv*p2h for the original
# H update, but then you have multiple arrays and a monolithic (field + pml) update operation
def pml_e(e: fdfield_t, h: fdfield_t, epsilon: fdfield_t) -> Tuple[fdfield_t, fdfield_t]:
dHv = h[v][region] - numpy.roll(h[v], 1, axis=direction)[region]
dHu = h[u][region] - numpy.roll(h[u], 1, axis=direction)[region]
psi_e[0] *= p0e
psi_e[0] += p1e * dHv * p2e
psi_e[1] *= p0e
psi_e[1] += p1e * dHu * p2e
e[u][region] += se * dt / epsilon[u][region] * (psi_e[0] + (p2e - 1) * dHv)
e[v][region] -= se * dt / epsilon[v][region] * (psi_e[1] + (p2e - 1) * dHu)
return e, h
def pml_h(e: fdfield_t, h: fdfield_t) -> Tuple[fdfield_t, fdfield_t]:
dEv = (numpy.roll(e[v], -1, axis=direction)[region] - e[v][region])
dEu = (numpy.roll(e[u], -1, axis=direction)[region] - e[u][region])
psi_h[0] *= p0h
psi_h[0] += p1h * dEv * p2h
psi_h[1] *= p0h
psi_h[1] += p1h * dEu * p2h
h[u][region] -= se * dt * (psi_h[0] + (p2h - 1) * dEv)
h[v][region] += se * dt * (psi_h[1] + (p2h - 1) * dEu)
return e, h
return pml_e, pml_h, fields