improve type annotations
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@ -931,7 +931,7 @@ def inner_product( # TODO documentation
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prop_phase: float = 0,
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prop_phase: float = 0,
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conj_h: bool = False,
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conj_h: bool = False,
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trapezoid: bool = False,
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trapezoid: bool = False,
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) -> tuple[vcfdfield_t, vcfdfield_t]:
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) -> complex:
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shape = [s.size for s in dxes[0]]
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shape = [s.size for s in dxes[0]]
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@ -8,7 +8,7 @@ As the z-dependence is known, all the functions in this file assume a 2D grid
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"""
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"""
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# TODO update module docs
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# TODO update module docs
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from typing import Any
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from typing import Any, cast
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from collections.abc import Sequence
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from collections.abc import Sequence
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import logging
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import logging
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@ -142,7 +142,7 @@ def solve_modes(
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# Wavenumbers assume the mode is at rmin, which is unlikely
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# Wavenumbers assume the mode is at rmin, which is unlikely
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# Instead, return the wavenumber in inverse radians
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# Instead, return the wavenumber in inverse radians
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angular_wavenumbers = wavenumbers * rmin
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angular_wavenumbers = wavenumbers * cast(complex, rmin)
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order = angular_wavenumbers.argsort()[::-1]
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order = angular_wavenumbers.argsort()[::-1]
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e_xys = e_xys[order]
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e_xys = e_xys[order]
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@ -14,7 +14,7 @@ from .types import fdfield_t, fdfield_updater_t
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def deriv_forward(
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def deriv_forward(
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dx_e: Sequence[NDArray[floating]] | None = None,
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dx_e: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
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) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
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"""
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"""
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Utility operators for taking discretized derivatives (backward variant).
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Utility operators for taking discretized derivatives (backward variant).
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@ -38,7 +38,7 @@ def deriv_forward(
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def deriv_back(
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def deriv_back(
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dx_h: Sequence[NDArray[floating]] | None = None,
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dx_h: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
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) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
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"""
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"""
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Utility operators for taking discretized derivatives (forward variant).
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Utility operators for taking discretized derivatives (forward variant).
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@ -65,7 +65,7 @@ TT = TypeVar('TT', bound='NDArray[floating | complexfloating]')
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def curl_forward(
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def curl_forward(
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dx_e: Sequence[NDArray[floating]] | None = None,
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dx_e: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> Callable[[TT], TT]:
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) -> Callable[[TT], TT]:
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r"""
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r"""
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Curl operator for use with the E field.
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Curl operator for use with the E field.
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@ -94,7 +94,7 @@ def curl_forward(
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def curl_back(
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def curl_back(
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dx_h: Sequence[NDArray[floating]] | None = None,
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dx_h: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> Callable[[TT], TT]:
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) -> Callable[[TT], TT]:
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r"""
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r"""
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Create a function which takes the backward curl of a field.
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Create a function which takes the backward curl of a field.
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@ -123,7 +123,7 @@ def curl_back(
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def curl_forward_parts(
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def curl_forward_parts(
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dx_e: Sequence[NDArray[floating]] | None = None,
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dx_e: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> Callable:
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) -> Callable:
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Dx, Dy, Dz = deriv_forward(dx_e)
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Dx, Dy, Dz = deriv_forward(dx_e)
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@ -136,7 +136,7 @@ def curl_forward_parts(
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def curl_back_parts(
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def curl_back_parts(
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dx_h: Sequence[NDArray[floating]] | None = None,
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dx_h: Sequence[NDArray[floating | complexfloating]] | None = None,
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) -> Callable:
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) -> Callable:
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Dx, Dy, Dz = deriv_back(dx_h)
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Dx, Dy, Dz = deriv_back(dx_h)
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@ -6,7 +6,7 @@ Basic discrete calculus etc.
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from collections.abc import Sequence
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from collections.abc import Sequence
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import numpy
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import numpy
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from numpy.typing import NDArray
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from numpy.typing import NDArray
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from numpy import floating
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from numpy import floating, complexfloating
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from scipy import sparse
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from scipy import sparse
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from .types import vfdfield_t
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from .types import vfdfield_t
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@ -97,7 +97,7 @@ def shift_with_mirror(
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def deriv_forward(
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def deriv_forward(
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dx_e: Sequence[NDArray[floating]],
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dx_e: Sequence[NDArray[floating | complexfloating]],
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) -> list[sparse.spmatrix]:
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) -> list[sparse.spmatrix]:
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"""
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"""
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Utility operators for taking discretized derivatives (forward variant).
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Utility operators for taking discretized derivatives (forward variant).
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@ -124,7 +124,7 @@ def deriv_forward(
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def deriv_back(
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def deriv_back(
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dx_h: Sequence[NDArray[floating]],
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dx_h: Sequence[NDArray[floating | complexfloating]],
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) -> list[sparse.spmatrix]:
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) -> list[sparse.spmatrix]:
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"""
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"""
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Utility operators for taking discretized derivatives (backward variant).
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Utility operators for taking discretized derivatives (backward variant).
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@ -219,7 +219,7 @@ def avg_back(axis: int, shape: Sequence[int]) -> sparse.spmatrix:
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def curl_forward(
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def curl_forward(
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dx_e: Sequence[NDArray[floating]],
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dx_e: Sequence[NDArray[floating | complexfloating]],
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) -> sparse.spmatrix:
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) -> sparse.spmatrix:
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"""
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"""
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Curl operator for use with the E field.
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Curl operator for use with the E field.
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@ -235,7 +235,7 @@ def curl_forward(
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def curl_back(
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def curl_back(
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dx_h: Sequence[NDArray[floating]],
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dx_h: Sequence[NDArray[floating | complexfloating]],
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) -> sparse.spmatrix:
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) -> sparse.spmatrix:
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"""
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"""
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Curl operator for use with the H field.
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Curl operator for use with the H field.
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@ -49,15 +49,15 @@ def vec(
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@overload
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@overload
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def unvec(v: None, shape: Sequence[int], nvdim: int) -> None:
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def unvec(v: None, shape: Sequence[int], nvdim: int = 3) -> None:
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pass
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pass
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@overload
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@overload
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def unvec(v: vfdfield_t, shape: Sequence[int], nvdim: int) -> fdfield_t:
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def unvec(v: vfdfield_t, shape: Sequence[int], nvdim: int = 3) -> fdfield_t:
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pass
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pass
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@overload
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@overload
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def unvec(v: vcfdfield_t, shape: Sequence[int], nvdim: int) -> cfdfield_t:
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def unvec(v: vcfdfield_t, shape: Sequence[int], nvdim: int = 3) -> cfdfield_t:
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pass
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pass
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def unvec(
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def unvec(
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