bump min python version to 3.11 due to Self type

.flake8

@@ -0,0 +1,29 @@
+[flake8]
+ignore =
+    # E501 line too long
+    E501,
+    # W391 newlines at EOF
+    W391,
+    # E241 multiple spaces after comma
+    E241,
+    # E302 expected 2 newlines
+    E302,
+    # W503 line break before binary operator (to be deprecated)
+    W503,
+    # E265 block comment should start with '# '
+    E265,
+    # E123 closing bracket does not match indentation of opening bracket's line
+    E123,
+    # E124 closing bracket does not match visual indentation
+    E124,
+    # E221 multiple spaces before operator
+    E221,
+    # E201 whitespace after '['
+    E201,
+    # E741 ambiguous variable name 'I'
+    E741,
+
+
+per-file-ignores =
+    # F401 import without use
+    */__init__.py: F401,

README.md

@@ -14,7 +14,7 @@ the coordinates of the boundary points along each axis).
 ## Installation
 
 Requirements:
-* python 3 (written and tested with 3.9)
+* python >3.11 (written and tested with 3.12)
 * numpy
 * [float_raster](https://mpxd.net/code/jan/float_raster)
 * matplotlib (optional, used for visualization functions)

gridlock/draw.py

@@ -1,7 +1,7 @@
 """
 Drawing-related methods for Grid class
 """
-from typing import List, Optional, Union, Sequence, Callable
+from typing import Union, Sequence, Callable
 
 import numpy
 from numpy.typing import NDArray, ArrayLike
@@ -27,7 +27,7 @@ def draw_polygons(
         center: ArrayLike,
         polygons: Sequence[NDArray],
         thickness: float,
-        foreground: Union[Sequence[foreground_t], foreground_t],
+        foreground: Sequence[foreground_t] | foreground_t,
         ) -> None:
     """
     Draw polygons on an axis-aligned plane.
@@ -59,7 +59,7 @@ def draw_polygons(
     for i, polygon in enumerate(polygons):
         malformed = f'Malformed polygon: ({i})'
         if polygon.shape[1] not in (2, 3):
-                raise GridError(malformed + 'must be a Nx2 or Nx3 ndarray')
+            raise GridError(malformed + 'must be a Nx2 or Nx3 ndarray')
         if polygon.shape[1] == 3:
             polygon = polygon[surface, :]
 
@@ -70,9 +70,9 @@ def draw_polygons(
                             + 'xyz'[surface_normal])
 
     # Broadcast foreground where necessary
-    foregrounds: Union[Sequence[foreground_callable_t], Sequence[float]]
+    foregrounds: Sequence[foreground_callable_t] | Sequence[float]
     if numpy.size(foreground) == 1:     # type: ignore
-        foregrounds = [foreground] * len(cell_data) # type: ignore
+        foregrounds = [foreground] * len(cell_data)  # type: ignore
     elif isinstance(foreground, numpy.ndarray):
         raise GridError('ndarray not supported for foreground')
     else:
@@ -113,7 +113,7 @@ def draw_polygons(
         foregrounds_i = foregrounds[i]
         if callable(foregrounds_i):
             # meshgrid over the (shifted) domain
-            domain = [self.shifted_xyz(i)[k][bdi_min[k]:bdi_max[k]+1] for k in range(3)]
+            domain = [self.shifted_xyz(i)[k][bdi_min[k]:bdi_max[k] + 1] for k in range(3)]
             (x0, y0, z0) = numpy.meshgrid(*domain, indexing='ij')
 
             # evaluate on the meshgrid
@@ -202,7 +202,7 @@ def draw_polygon(
         center: ArrayLike,
         polygon: ArrayLike,
         thickness: float,
-        foreground: Union[Sequence[foreground_t], foreground_t],
+        foreground: Sequence[foreground_t] | foreground_t,
         ) -> None:
     """
     Draw a polygon on an axis-aligned plane.
@@ -226,7 +226,7 @@ def draw_slab(
         surface_normal: int,
         center: ArrayLike,
         thickness: float,
-        foreground: Union[Sequence[foreground_t], foreground_t],
+        foreground: Sequence[foreground_t] | foreground_t,
         ) -> None:
     """
     Draw an axis-aligned infinite slab.
@@ -276,7 +276,7 @@ def draw_cuboid(
         cell_data: NDArray,
         center: ArrayLike,
         dimensions: ArrayLike,
-        foreground: Union[Sequence[foreground_t], foreground_t],
+        foreground: Sequence[foreground_t] | foreground_t,
         ) -> None:
     """
     Draw an axis-aligned cuboid
@@ -305,7 +305,7 @@ def draw_cylinder(
         radius: float,
         thickness: float,
         num_points: int,
-        foreground: Union[Sequence[foreground_t], foreground_t],
+        foreground: Sequence[foreground_t] | foreground_t,
         ) -> None:
     """
     Draw an axis-aligned cylinder. Approximated by a num_points-gon
@@ -319,7 +319,7 @@ def draw_cylinder(
         num_points: The circle is approximated by a polygon with `num_points` vertices
         foreground: Value to draw with ('brush color'). See `draw_polygons()` for details.
     """
-    theta = numpy.linspace(0, 2*numpy.pi, num_points, endpoint=False)
+    theta = numpy.linspace(0, 2 * numpy.pi, num_points, endpoint=False)
     x = radius * numpy.sin(theta)
     y = radius * numpy.cos(theta)
     polygon = numpy.hstack((x[:, None], y[:, None]))
@@ -360,8 +360,8 @@ def draw_extrude_rectangle(
     surface = numpy.delete(range(3), direction)
 
     dim = numpy.fabs(numpy.diff(rectangle, axis=0).T)[surface]
-    p = numpy.vstack((numpy.array([-1, -1, 1, 1], dtype=float) * dim[0]/2.0,
-                      numpy.array([-1, 1, 1, -1], dtype=float) * dim[1]/2.0)).T
+    p = numpy.vstack((numpy.array([-1, -1, 1, 1], dtype=float) * dim[0] * 0.5,
+                      numpy.array([-1, 1, 1, -1], dtype=float) * dim[1] * 0.5)).T
     thickness = distance
 
     foreground_func = []
@@ -371,7 +371,7 @@ def draw_extrude_rectangle(
         ind = [int(numpy.floor(z)) if i == direction else slice(None) for i in range(3)]
 
         fpart = z - numpy.floor(z)
-        mult = [1-fpart, fpart][::s]  # reverses if s negative
+        mult = [1 - fpart, fpart][::s]  # reverses if s negative
 
         foreground = mult[0] * grid[tuple(ind)]
         ind[direction] += 1                         # type: ignore #(known safe)

gridlock/grid.py

@@ -1,8 +1,7 @@
-from typing import List, Tuple, Callable, Dict, Optional, Union, Sequence, ClassVar, TypeVar
+from typing import Callable, Sequence, ClassVar, Self
 
 import numpy
 from numpy.typing import NDArray, ArrayLike
-from numpy import diff, floor, ceil, zeros, hstack, newaxis
 
 import pickle
 import warnings
@@ -12,7 +11,6 @@ from . import GridError
 
 
 foreground_callable_type = Callable[[NDArray, NDArray, NDArray], NDArray]
-T = TypeVar('T', bound='Grid')
 
 
 class Grid:
@@ -49,10 +47,10 @@ class Grid:
      Because of this, we either assume this 'ghost' cell is the same size as the last
       real cell, or, if `self.periodic[a]` is set to `True`, the same size as the first cell.
     """
-    exyz: List[NDArray]
+    exyz: list[NDArray]
     """Cell edges. Monotonically increasing without duplicates."""
 
-    periodic: List[bool]
+    periodic: list[bool]
     """For each axis, determines how far the rightmost boundary gets shifted. """
 
     shifts: NDArray
@@ -80,7 +78,7 @@ class Grid:
     from .position import ind2pos, pos2ind
 
     @property
-    def dxyz(self) -> List[NDArray]:
+    def dxyz(self) -> list[NDArray]:
         """
         Cell sizes for each axis, no shifts applied
 
@@ -90,7 +88,7 @@ class Grid:
         return [numpy.diff(ee) for ee in self.exyz]
 
     @property
-    def xyz(self) -> List[NDArray]:
+    def xyz(self) -> list[NDArray]:
         """
         Cell centers for each axis, no shifts applied
 
@@ -124,7 +122,7 @@ class Grid:
         return numpy.hstack((self.num_grids, self.shape))
 
     @property
-    def dxyz_with_ghost(self) -> List[NDArray]:
+    def dxyz_with_ghost(self) -> list[NDArray]:
         """
         Gives dxyz with an additional 'ghost' cell at the end, whose value depends
          on whether or not the axis has periodic boundary conditions. See main description
@@ -153,7 +151,7 @@ class Grid:
         return numpy.array(centers, dtype=float)
 
     @property
-    def dxyz_limits(self) -> Tuple[NDArray, NDArray]:
+    def dxyz_limits(self) -> tuple[NDArray, NDArray]:
         """
         Returns the minimum and maximum cell size for each axis, as a tuple of two 3-element
          ndarrays. No shifts are applied, so these are extreme bounds on these values (as a
@@ -166,7 +164,7 @@ class Grid:
         d_max = numpy.array([max(self.dxyz[a]) for a in range(3)], dtype=float)
         return d_min, d_max
 
-    def shifted_exyz(self, which_shifts: Optional[int]) -> List[NDArray]:
+    def shifted_exyz(self, which_shifts: int | None) -> list[NDArray]:
         """
         Returns edges for which_shifts.
 
@@ -188,7 +186,7 @@ class Grid:
 
         return [self.exyz[a] + dxyz[a] * shifts[a] for a in range(3)]
 
-    def shifted_dxyz(self, which_shifts: Optional[int]) -> List[NDArray]:
+    def shifted_dxyz(self, which_shifts: int | None) -> list[NDArray]:
         """
         Returns cell sizes for `which_shifts`.
 
@@ -215,7 +213,7 @@ class Grid:
 
         return sdxyz
 
-    def shifted_xyz(self, which_shifts: Optional[int]) -> List[NDArray[numpy.float64]]:
+    def shifted_xyz(self, which_shifts: int | None) -> list[NDArray[numpy.float64]]:
         """
         Returns cell centers for `which_shifts`.
 
@@ -231,7 +229,7 @@ class Grid:
         dxyz = self.shifted_dxyz(which_shifts)
         return [exyz[a][:-1] + dxyz[a] / 2.0 for a in range(3)]
 
-    def autoshifted_dxyz(self) -> List[NDArray[numpy.float64]]:
+    def autoshifted_dxyz(self) -> list[NDArray[numpy.float64]]:
         """
         Return cell widths, with each dimension shifted by the corresponding shifts.
 
@@ -242,7 +240,7 @@ class Grid:
             raise GridError('Autoshifting requires exactly 3 grids')
         return [self.shifted_dxyz(which_shifts=a)[a] for a in range(3)]
 
-    def allocate(self, fill_value: Optional[float] = 1.0, dtype=numpy.float32) -> NDArray:
+    def allocate(self, fill_value: float | None = 1.0, dtype=numpy.float32) -> NDArray:
         """
         Allocate an ndarray for storing grid data.
 
@@ -263,7 +261,7 @@ class Grid:
             self,
             pixel_edge_coordinates: Sequence[ArrayLike],
             shifts: ArrayLike = Yee_Shifts_E,
-            periodic: Union[bool, Sequence[bool]] = False,
+            periodic: bool | Sequence[bool] = False,
             ) -> None:
         """
         Args:
@@ -320,7 +318,7 @@ class Grid:
         g.__dict__.update(tmp_dict)
         return g
 
-    def save(self: T, filename: str) -> T:
+    def save(self, filename: str) -> Self:
         """
         Save to file.
 
@@ -334,7 +332,7 @@ class Grid:
             pickle.dump(self.__dict__, f, protocol=2)
         return self
 
-    def copy(self: T) -> T:
+    def copy(self) -> Self:
         """
         Returns:
             Deep copy of the grid.

gridlock/position.py

@@ -1,8 +1,6 @@
 """
 Position-related methods for Grid class
 """
-from typing import List, Optional, Sequence
-
 import numpy
 from numpy.typing import NDArray, ArrayLike
 
@@ -12,7 +10,7 @@ from . import GridError
 def ind2pos(
         self,
         ind: NDArray,
-        which_shifts: Optional[int] = None,
+        which_shifts: int | None = None,
         round_ind: bool = True,
         check_bounds: bool = True
         ) -> NDArray[numpy.float64]:
@@ -64,7 +62,7 @@ def ind2pos(
 def pos2ind(
         self,
         r: ArrayLike,
-        which_shifts: Optional[int],
+        which_shifts: int | None,
         round_ind: bool = True,
         check_bounds: bool = True
         ) -> NDArray[numpy.float64]:
@@ -101,7 +99,7 @@ def pos2ind(
 
     grid_pos = numpy.zeros((3,))
     for a in range(3):
-        xi = numpy.digitize(r[a], sexyz[a]) - 1 # Figure out which cell we're in
+        xi = numpy.digitize(r[a], sexyz[a]) - 1  # Figure out which cell we're in
         xi_clipped = numpy.clip(xi, 0, sexyz[a].size - 2)  # Clip back into grid bounds
 
         # No need to interpolate if round_ind is true or we were outside the grid

gridlock/read.py

@@ -1,13 +1,18 @@
 """
 Readback and visualization methods for Grid class
 """
-from typing import Dict, Optional, Union, Any
+from typing import Any, TYPE_CHECKING
 
 import numpy
-from numpy.typing import NDArray, ArrayLike
+from numpy.typing import NDArray
 
 from . import GridError
 
+if TYPE_CHECKING:
+    import matplotlib.axes
+    import matplotlib.figure
+
+
 # .visualize_* uses matplotlib
 # .visualize_isosurface uses skimage
 # .visualize_isosurface uses mpl_toolkits.mplot3d
@@ -85,8 +90,8 @@ def visualize_slice(
         which_shifts: int = 0,
         sample_period: int = 1,
         finalize: bool = True,
-        pcolormesh_args: Optional[Dict[str, Any]] = None,
-        ) -> None:
+        pcolormesh_args: dict[str, Any] | None = None,
+        ) -> tuple['matplotlib.axes.Axes', 'matplotlib.figure.Figure']:
     """
     Visualize a slice of a grid.
     Interpolates if given a position between two planes.
@@ -97,6 +102,9 @@ def visualize_slice(
         which_shifts: Which grid to display. Default is the first grid (0).
         sample_period: Period for down-sampling the image. Default 1 (disabled)
         finalize: Whether to call `pyplot.show()` after constructing the plot. Default `True`
+
+    Returns:
+        (Figure, Axes)
     """
     from matplotlib import pyplot
 
@@ -115,25 +123,27 @@ def visualize_slice(
     xmesh, ymesh = numpy.meshgrid(x, y, indexing='ij')
     x_label, y_label = ('xyz'[a] for a in surface)
 
-    pyplot.figure()
-    pyplot.pcolormesh(xmesh, ymesh, grid_slice, **pcolormesh_args)
-    pyplot.colorbar()
-    pyplot.gca().set_aspect('equal', adjustable='box')
-    pyplot.xlabel(x_label)
-    pyplot.ylabel(y_label)
+    fig, ax = pyplot.subplots()
+    mappable = ax.pcolormesh(xmesh, ymesh, grid_slice, **pcolormesh_args)
+    fig.colorbar(mappable)
+    ax.set_aspect('equal', adjustable='box')
+    ax.set_xlabel(x_label)
+    ax.set_ylabel(y_label)
     if finalize:
         pyplot.show()
 
+    return fig, ax
+
 
 def visualize_isosurface(
         self,
         cell_data: NDArray,
-        level: Optional[float] = None,
+        level: float | None = None,
         which_shifts: int = 0,
         sample_period: int = 1,
         show_edges: bool = True,
         finalize: bool = True,
-        ) -> None:
+        ) -> tuple['matplotlib.axes.Axes', 'matplotlib.figure.Figure']:
     """
     Draw an isosurface plot of the device.
 
@@ -144,6 +154,9 @@ def visualize_isosurface(
         sample_period: Period for down-sampling the image. Default 1 (disabled)
         show_edges: Whether to draw triangle edges. Default `True`
         finalize: Whether to call `pyplot.show()` after constructing the plot. Default `True`
+
+    Returns:
+        (Figure, Axes)
     """
     from matplotlib import pyplot
     import skimage.measure
@@ -185,3 +198,5 @@ def visualize_isosurface(
 
     if finalize:
         pyplot.show()
+
+    return fig, ax

pyproject.toml

@@ -32,13 +32,13 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Physics",
     "Topic :: Scientific/Engineering :: Visualization",
     ]
-requires-python = ">=3.8"
+requires-python = ">=3.11"
 include = [
     "LICENSE.md"
     ]
 dynamic = ["version"]
 dependencies = [
-    "numpy~=1.21",
+    "numpy~=1.26",
     "float_raster",
     ]