improve type annotations

meanas/fdfd/waveguide_3d.py

@@ -7,6 +7,7 @@ its parameters into 2D equivalents and expands the results back into 3D.
 from typing import Sequence, Any
 import numpy
 from numpy.typing import NDArray
+from numpy import complexfloating
 
 from ..fdmath import vec, unvec, dx_lists_t, fdfield_t, cfdfield_t
 from . import operators, waveguide_2d
@@ -21,7 +22,7 @@ def solve_mode(
         slices: Sequence[slice],
         epsilon: fdfield_t,
         mu: fdfield_t | None = None,
-        ) -> dict[str, complex | NDArray[numpy.float_]]:
+        ) -> dict[str, complex | NDArray[complexfloating]]:
     """
     Given a 3D grid, selects a slice from the grid and attempts to
      solve for an eigenmode propagating through that slice.
@@ -40,8 +41,8 @@ def solve_mode(
     Returns:
         ```
         {
-            'E': list[NDArray[numpy.float_]],
+            'E': NDArray[complexfloating],
-            'H': list[NDArray[numpy.float_]],
+            'H': NDArray[complexfloating],
             'wavenumber': complex,
         }
         ```

meanas/fdfd/waveguide_cyl.py

@@ -11,7 +11,7 @@ As the z-dependence is known, all the functions in this file assume a 2D grid
 import numpy
 import scipy.sparse as sparse       # type: ignore
 
-from ..fdmath import vec, unvec, dx_lists_t, fdfield_t, vfdfield_t, cfdfield_t
+from ..fdmath import vec, unvec, dx_lists_t, vfdfield_t, cfdfield_t
 from ..fdmath.operators import deriv_forward, deriv_back
 from ..eigensolvers import signed_eigensolve, rayleigh_quotient_iteration
 

meanas/fdmath/functional.py

@@ -7,12 +7,13 @@ from typing import Sequence, Callable
 
 import numpy
 from numpy.typing import NDArray
+from numpy import floating
 
 from .types import fdfield_t, fdfield_updater_t
 
 
 def deriv_forward(
-        dx_e: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_e: Sequence[NDArray[floating]] | None = None,
         ) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
     """
     Utility operators for taking discretized derivatives (backward variant).
@@ -36,7 +37,7 @@ def deriv_forward(
 
 
 def deriv_back(
-        dx_h: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_h: Sequence[NDArray[floating]] | None = None,
         ) -> tuple[fdfield_updater_t, fdfield_updater_t, fdfield_updater_t]:
     """
     Utility operators for taking discretized derivatives (forward variant).
@@ -60,7 +61,7 @@ def deriv_back(
 
 
 def curl_forward(
-        dx_e: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_e: Sequence[NDArray[floating]] | None = None,
         ) -> fdfield_updater_t:
     r"""
     Curl operator for use with the E field.
@@ -89,7 +90,7 @@ def curl_forward(
 
 
 def curl_back(
-        dx_h: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_h: Sequence[NDArray[floating]] | None = None,
         ) -> fdfield_updater_t:
     r"""
     Create a function which takes the backward curl of a field.
@@ -118,7 +119,7 @@ def curl_back(
 
 
 def curl_forward_parts(
-        dx_e: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_e: Sequence[NDArray[floating]] | None = None,
         ) -> Callable:
     Dx, Dy, Dz = deriv_forward(dx_e)
 
@@ -131,7 +132,7 @@ def curl_forward_parts(
 
 
 def curl_back_parts(
-        dx_h: Sequence[NDArray[numpy.float_]] | None = None,
+        dx_h: Sequence[NDArray[floating]] | None = None,
         ) -> Callable:
     Dx, Dy, Dz = deriv_back(dx_h)
 

meanas/fdmath/operators.py

@@ -6,6 +6,7 @@ Basic discrete calculus etc.
 from typing import Sequence
 import numpy
 from numpy.typing import NDArray
+from numpy import floating
 import scipy.sparse as sparse   # type: ignore
 
 from .types import vfdfield_t
@@ -96,7 +97,7 @@ def shift_with_mirror(
 
 
 def deriv_forward(
-        dx_e: Sequence[NDArray[numpy.float_]],
+        dx_e: Sequence[NDArray[floating]],
         ) -> list[sparse.spmatrix]:
     """
     Utility operators for taking discretized derivatives (forward variant).
@@ -123,7 +124,7 @@ def deriv_forward(
 
 
 def deriv_back(
-        dx_h: Sequence[NDArray[numpy.float_]],
+        dx_h: Sequence[NDArray[floating]],
         ) -> list[sparse.spmatrix]:
     """
     Utility operators for taking discretized derivatives (backward variant).
@@ -218,7 +219,7 @@ def avg_back(axis: int, shape: Sequence[int]) -> sparse.spmatrix:
 
 
 def curl_forward(
-        dx_e: Sequence[NDArray[numpy.float_]],
+        dx_e: Sequence[NDArray[floating]],
         ) -> sparse.spmatrix:
     """
     Curl operator for use with the E field.
@@ -234,7 +235,7 @@ def curl_forward(
 
 
 def curl_back(
-        dx_h: Sequence[NDArray[numpy.float_]],
+        dx_h: Sequence[NDArray[floating]],
         ) -> sparse.spmatrix:
     """
     Curl operator for use with the H field.

meanas/fdmath/types.py

@@ -2,25 +2,25 @@
 Types shared across multiple submodules
 """
 from typing import Sequence, Callable, MutableSequence
-import numpy
 from numpy.typing import NDArray
+from numpy import floating, complexfloating
 
 
 # Field types
-fdfield_t = NDArray[numpy.float_]
+fdfield_t = NDArray[floating]
 """Vector field with shape (3, X, Y, Z) (e.g. `[E_x, E_y, E_z]`)"""
 
-vfdfield_t = NDArray[numpy.float_]
+vfdfield_t = NDArray[floating]
 """Linearized vector field (single vector of length 3*X*Y*Z)"""
 
-cfdfield_t = NDArray[numpy.complex_]
+cfdfield_t = NDArray[complexfloating]
 """Complex vector field with shape (3, X, Y, Z) (e.g. `[E_x, E_y, E_z]`)"""
 
-vcfdfield_t = NDArray[numpy.complex_]
+vcfdfield_t = NDArray[complexfloating]
 """Linearized complex vector field (single vector of length 3*X*Y*Z)"""
 
 
-dx_lists_t = Sequence[Sequence[NDArray[numpy.float_]]]
+dx_lists_t = Sequence[Sequence[NDArray[floating]]]
 """
  'dxes' datastructure which contains grid cell width information in the following format:
 
@@ -31,7 +31,7 @@ dx_lists_t = Sequence[Sequence[NDArray[numpy.float_]]]
    and `dy_h[0]` is the y-width of the `y=0` cells, as used when calculating dH/dy, etc.
 """
 
-dx_lists_mut = MutableSequence[MutableSequence[NDArray[numpy.float_]]]
+dx_lists_mut = MutableSequence[MutableSequence[NDArray[floating]]]
 """Mutable version of `dx_lists_t`"""