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Major typing updates

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Split field types to differentiate between complex and purely-real

Fix lots of numpy-related stuff
This commit is contained in:
Jan Petykiewicz 2022-10-04 17:17:44 -07:00
commit 52df24ad98
18 changed files with 191 additions and 151 deletions
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26
meanas/fdfd/waveguide_2d.py
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@ -185,7 +185,7 @@ from numpy.linalg import norm
import scipy.sparse as sparse # type: ignore
from ..fdmath.operators import deriv_forward, deriv_back, cross
from ..fdmath import unvec, dx_lists_t, vfdfield_t
from ..fdmath import unvec, dx_lists_t, vfdfield_t, vcfdfield_t
from ..eigensolvers import signed_eigensolve, rayleigh_quotient_iteration
@ -335,7 +335,7 @@ def normalized_fields_e(
epsilon: vfdfield_t,
mu: Optional[vfdfield_t] = None,
prop_phase: float = 0,
) -> Tuple[vfdfield_t, vfdfield_t]:
) -> Tuple[vcfdfield_t, vcfdfield_t]:
"""
Given a vector `e_xy` containing the vectorized E_x and E_y fields,
returns normalized, vectorized E and H fields for the system.
@ -370,7 +370,7 @@ def normalized_fields_h(
epsilon: vfdfield_t,
mu: Optional[vfdfield_t] = None,
prop_phase: float = 0,
) -> Tuple[vfdfield_t, vfdfield_t]:
) -> Tuple[vcfdfield_t, vcfdfield_t]:
"""
Given a vector `h_xy` containing the vectorized H_x and H_y fields,
returns normalized, vectorized E and H fields for the system.
@ -398,14 +398,14 @@ def normalized_fields_h(
def _normalized_fields(
e: ArrayLike,
h: ArrayLike,
e: vcfdfield_t,
h: vcfdfield_t,
omega: complex,
dxes: dx_lists_t,
epsilon: vfdfield_t,
mu: Optional[vfdfield_t] = None,
prop_phase: float = 0,
) -> Tuple[vfdfield_t, vfdfield_t]:
) -> Tuple[vcfdfield_t, vcfdfield_t]:
# TODO documentation
shape = [s.size for s in dxes[0]]
dxes_real = [[numpy.real(d) for d in numpy.meshgrid(*dxes[v], indexing='ij')] for v in (0, 1)]
@ -581,7 +581,7 @@ def e2h(
"""
op = curl_e(wavenumber, dxes) / (-1j * omega)
if not numpy.any(numpy.equal(mu, None)):
op = sparse.diags(1 / mu) @ op # type: ignore # checked that mu is not None
op = sparse.diags(1 / mu) @ op
return op
@ -649,7 +649,7 @@ def curl_h(wavenumber: complex, dxes: dx_lists_t) -> sparse.spmatrix:
def h_err(
h: vfdfield_t,
h: vcfdfield_t,
wavenumber: complex,
omega: complex,
dxes: dx_lists_t,
@ -684,12 +684,12 @@ def h_err(
def e_err(
e: vfdfield_t,
e: vcfdfield_t,
wavenumber: complex,
omega: complex,
dxes: dx_lists_t,
epsilon: vfdfield_t,
mu: vfdfield_t = Optional[None]
mu: Optional[vfdfield_t] = None,
) -> float:
"""
Calculates the relative error in the E field
@ -711,7 +711,7 @@ def e_err(
if numpy.any(numpy.equal(mu, None)):
op = ch @ ce @ e - omega ** 2 * (epsilon * e)
else:
mu_inv = sparse.diags(1 / mu) # type: ignore # checked that mu is not None
mu_inv = sparse.diags(1 / mu)
op = ch @ mu_inv @ ce @ e - omega ** 2 * (epsilon * e)
return norm(op) / norm(e)
@ -724,7 +724,7 @@ def solve_modes(
epsilon: vfdfield_t,
mu: vfdfield_t = None,
mode_margin: int = 2,
) -> Tuple[NDArray[numpy.float64], List[complex]]:
) -> Tuple[NDArray[numpy.float64], NDArray[numpy.complex128]]:
"""
Given a 2D region, attempts to solve for the eigenmode with the specified mode numbers.
@ -771,7 +771,7 @@ def solve_mode(
mode_number: int,
*args: Any,
**kwargs: Any,
) -> Tuple[vfdfield_t, complex]:
) -> Tuple[vcfdfield_t, complex]:
"""
Wrapper around `solve_modes()` that solves for a single mode.