typing and formatting updates
This commit is contained in:
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7d3b2272bc
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ec5c77e018
@ -3,7 +3,8 @@ Drawing-related methods for Grid class
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"""
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from typing import List, Optional, Union, Sequence, Callable
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import numpy # type: ignore
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import numpy
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from numpy.typing import NDArray, ArrayLike
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from float_raster import raster
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from . import GridError
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@ -15,16 +16,18 @@ from . import GridError
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# without having to pass `cell_data` again each time?
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foreground_callable_t = Callable[[numpy.ndarray, numpy.ndarray, numpy.ndarray], numpy.ndarray]
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foreground_callable_t = Callable[[NDArray, NDArray, NDArray], NDArray]
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foreground_t = Union[float, foreground_callable_t]
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def draw_polygons(self,
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cell_data: numpy.ndarray,
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def draw_polygons(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: numpy.ndarray,
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polygons: Sequence[numpy.ndarray],
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center: ArrayLike,
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polygons: Sequence[NDArray],
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thickness: float,
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foreground: Union[Sequence[Union[float, foreground_callable_t]], float, foreground_callable_t],
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foreground: Union[Sequence[foreground_t], foreground_t],
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) -> None:
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"""
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Draw polygons on an axis-aligned plane.
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@ -74,8 +77,8 @@ def draw_polygons(self,
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# ## Compute sub-domain of the grid occupied by polygons
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# 1) Compute outer bounds (bd) of polygons
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bd_2d_min = [0, 0]
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bd_2d_max = [0, 0]
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bd_2d_min = numpy.array([0, 0])
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bd_2d_max = numpy.array([0, 0])
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for polygon in polygons:
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bd_2d_min = numpy.minimum(bd_2d_min, polygon.min(axis=0))
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bd_2d_max = numpy.maximum(bd_2d_max, polygon.max(axis=0))
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@ -97,7 +100,7 @@ def draw_polygons(self,
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polygons = [poly + center[surface] for poly in polygons]
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# ## Generate weighing function
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def to_3d(vector: numpy.ndarray, val: float = 0.0) -> numpy.ndarray:
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def to_3d(vector: NDArray, val: float = 0.0) -> NDArray[numpy.float64]:
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v_2d = numpy.array(vector, dtype=float)
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return numpy.insert(v_2d, surface_normal, (val,))
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@ -188,13 +191,14 @@ def draw_polygons(self,
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cell_data[g_slice] = (1 - w) * cell_data[g_slice] + w * foreground_i
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def draw_polygon(self,
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cell_data: numpy.ndarray,
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def draw_polygon(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: numpy.ndarray,
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polygon: numpy.ndarray,
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center: ArrayLike,
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polygon: ArrayLike,
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thickness: float,
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foreground: Union[Sequence[Union[float, foreground_callable_t]], float, foreground_callable_t],
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foreground: Union[Sequence[foreground_t], foreground_t],
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) -> None:
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"""
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Draw a polygon on an axis-aligned plane.
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@ -212,12 +216,13 @@ def draw_polygon(self,
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self.draw_polygons(cell_data, surface_normal, center, [polygon], thickness, foreground)
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def draw_slab(self,
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cell_data: numpy.ndarray,
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def draw_slab(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: numpy.ndarray,
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center: ArrayLike,
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thickness: float,
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foreground: Union[List[Union[float, foreground_callable_t]], float, foreground_callable_t],
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foreground: Union[Sequence[foreground_t], foreground_t],
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) -> None:
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"""
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Draw an axis-aligned infinite slab.
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@ -262,11 +267,12 @@ def draw_slab(self,
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self.draw_polygon(cell_data, surface_normal, center_shift, p, thickness, foreground)
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def draw_cuboid(self,
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cell_data: numpy.ndarray,
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center: numpy.ndarray,
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dimensions: numpy.ndarray,
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foreground: Union[List[Union[float, foreground_callable_t]], float, foreground_callable_t],
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def draw_cuboid(
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self,
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cell_data: NDArray,
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center: ArrayLike,
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dimensions: ArrayLike,
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foreground: Union[Sequence[foreground_t], foreground_t],
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) -> None:
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"""
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Draw an axis-aligned cuboid
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@ -278,6 +284,7 @@ def draw_cuboid(self,
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sizes of the cuboid
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foreground: Value to draw with ('brush color'). See `draw_polygons()` for details.
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"""
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dimensions = numpy.array(dimensions, copy=False)
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p = numpy.array([[-dimensions[0], +dimensions[1]],
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[+dimensions[0], +dimensions[1]],
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[+dimensions[0], -dimensions[1]],
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@ -286,14 +293,15 @@ def draw_cuboid(self,
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self.draw_polygon(cell_data, 2, center, p, thickness, foreground)
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def draw_cylinder(self,
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cell_data: numpy.ndarray,
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def draw_cylinder(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: numpy.ndarray,
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center: ArrayLike,
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radius: float,
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thickness: float,
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num_points: int,
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foreground: Union[List[Union[float, foreground_callable_t]], float, foreground_callable_t],
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foreground: Union[Sequence[foreground_t], foreground_t],
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) -> None:
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"""
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Draw an axis-aligned cylinder. Approximated by a num_points-gon
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@ -314,9 +322,10 @@ def draw_cylinder(self,
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self.draw_polygon(cell_data, surface_normal, center, polygon, thickness, foreground)
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def draw_extrude_rectangle(self,
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cell_data: numpy.ndarray,
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rectangle: numpy.ndarray,
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def draw_extrude_rectangle(
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self,
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cell_data: NDArray,
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rectangle: ArrayLike,
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direction: int,
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polarity: int,
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distance: float,
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@ -361,10 +370,10 @@ def draw_extrude_rectangle(self,
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mult = [1-fpart, fpart][::s] # reverses if s negative
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foreground = mult[0] * grid[tuple(ind)]
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ind[direction] += 1
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ind[direction] += 1 # type: ignore #(known safe)
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foreground += mult[1] * grid[tuple(ind)]
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def f_foreground(xs, ys, zs, i=i, foreground=foreground) -> numpy.ndarray:
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def f_foreground(xs, ys, zs, i=i, foreground=foreground) -> NDArray[numpy.int_]:
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# transform from natural position to index
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xyzi = numpy.array([self.pos2ind(qrs, which_shifts=i)
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for qrs in zip(xs.flat, ys.flat, zs.flat)], dtype=int)
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@ -1,4 +1,4 @@
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import numpy # type: ignore
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import numpy
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from gridlock import Grid
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@ -1,6 +1,7 @@
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from typing import List, Tuple, Callable, Dict, Optional, Union, Sequence, ClassVar, TypeVar
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import numpy # type: ignore
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import numpy
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from numpy.typing import NDArray, ArrayLike
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from numpy import diff, floor, ceil, zeros, hstack, newaxis
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import pickle
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@ -10,7 +11,7 @@ import copy
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from . import GridError
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foreground_callable_type = Callable[[numpy.ndarray, numpy.ndarray, numpy.ndarray], numpy.ndarray]
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foreground_callable_type = Callable[[NDArray, NDArray, NDArray], NDArray]
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T = TypeVar('T', bound='Grid')
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@ -48,23 +49,27 @@ class Grid:
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Because of this, we either assume this 'ghost' cell is the same size as the last
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real cell, or, if `self.periodic[a]` is set to `True`, the same size as the first cell.
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"""
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exyz: List[numpy.ndarray]
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exyz: List[NDArray]
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"""Cell edges. Monotonically increasing without duplicates."""
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periodic: List[bool]
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"""For each axis, determines how far the rightmost boundary gets shifted. """
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shifts: numpy.ndarray
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shifts: NDArray
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"""Offsets `[[x0, y0, z0], [x1, y1, z1], ...]` for grid `0,1,...`"""
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Yee_Shifts_E: ClassVar[numpy.ndarray] = 0.5 * numpy.array([[1, 0, 0],
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Yee_Shifts_E: ClassVar[NDArray] = 0.5 * numpy.array([
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[1, 0, 0],
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[0, 1, 0],
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[0, 0, 1]], dtype=float)
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[0, 0, 1],
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], dtype=float)
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"""Default shifts for Yee grid E-field"""
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Yee_Shifts_H: ClassVar[numpy.ndarray] = 0.5 * numpy.array([[0, 1, 1],
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Yee_Shifts_H: ClassVar[NDArray] = 0.5 * numpy.array([
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[0, 1, 1],
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[1, 0, 1],
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[1, 1, 0]], dtype=float)
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[1, 1, 0],
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], dtype=float)
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"""Default shifts for Yee grid H-field"""
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from .draw import (
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@ -75,7 +80,7 @@ class Grid:
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from .position import ind2pos, pos2ind
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@property
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def dxyz(self) -> List[numpy.ndarray]:
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def dxyz(self) -> List[NDArray]:
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"""
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Cell sizes for each axis, no shifts applied
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@ -85,7 +90,7 @@ class Grid:
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return [numpy.diff(ee) for ee in self.exyz]
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@property
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def xyz(self) -> List[numpy.ndarray]:
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def xyz(self) -> List[NDArray]:
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"""
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Cell centers for each axis, no shifts applied
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@ -95,7 +100,7 @@ class Grid:
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return [self.exyz[a][:-1] + self.dxyz[a] / 2.0 for a in range(3)]
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@property
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def shape(self) -> numpy.ndarray:
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def shape(self) -> NDArray[numpy.int_]:
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"""
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The number of cells in x, y, and z
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@ -119,7 +124,7 @@ class Grid:
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return numpy.hstack((self.num_grids, self.shape))
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@property
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def dxyz_with_ghost(self) -> List[numpy.ndarray]:
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def dxyz_with_ghost(self) -> List[NDArray]:
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"""
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Gives dxyz with an additional 'ghost' cell at the end, whose value depends
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on whether or not the axis has periodic boundary conditions. See main description
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@ -135,7 +140,7 @@ class Grid:
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return [numpy.hstack((self.dxyz[a], self.dxyz[a][e])) for a, e in zip(range(3), el)]
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@property
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def center(self) -> numpy.ndarray:
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def center(self) -> NDArray[numpy.float64]:
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"""
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Center position of the entire grid, no shifts applied
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@ -148,7 +153,7 @@ class Grid:
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return numpy.array(centers, dtype=float)
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@property
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def dxyz_limits(self) -> Tuple[numpy.ndarray, numpy.ndarray]:
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def dxyz_limits(self) -> Tuple[NDArray, NDArray]:
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"""
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Returns the minimum and maximum cell size for each axis, as a tuple of two 3-element
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ndarrays. No shifts are applied, so these are extreme bounds on these values (as a
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@ -161,7 +166,7 @@ class Grid:
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d_max = numpy.array([max(self.dxyz[a]) for a in range(3)], dtype=float)
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return d_min, d_max
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def shifted_exyz(self, which_shifts: Optional[int]) -> List[numpy.ndarray]:
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def shifted_exyz(self, which_shifts: Optional[int]) -> List[NDArray]:
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"""
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Returns edges for which_shifts.
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@ -183,7 +188,7 @@ class Grid:
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return [self.exyz[a] + dxyz[a] * shifts[a] for a in range(3)]
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def shifted_dxyz(self, which_shifts: Optional[int]) -> List[numpy.ndarray]:
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def shifted_dxyz(self, which_shifts: Optional[int]) -> List[NDArray]:
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"""
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Returns cell sizes for `which_shifts`.
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@ -210,7 +215,7 @@ class Grid:
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return sdxyz
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def shifted_xyz(self, which_shifts: Optional[int]) -> List[numpy.ndarray]:
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def shifted_xyz(self, which_shifts: Optional[int]) -> List[NDArray[numpy.float64]]:
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"""
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Returns cell centers for `which_shifts`.
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@ -226,7 +231,7 @@ class Grid:
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dxyz = self.shifted_dxyz(which_shifts)
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return [exyz[a][:-1] + dxyz[a] / 2.0 for a in range(3)]
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def autoshifted_dxyz(self) -> List[numpy.ndarray]:
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def autoshifted_dxyz(self) -> List[NDArray[numpy.float64]]:
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"""
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Return cell widths, with each dimension shifted by the corresponding shifts.
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@ -237,7 +242,7 @@ class Grid:
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raise GridError('Autoshifting requires exactly 3 grids')
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return [self.shifted_dxyz(which_shifts=a)[a] for a in range(3)]
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def allocate(self, fill_value: Optional[float] = 1.0, dtype=numpy.float32) -> numpy.ndarray:
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def allocate(self, fill_value: Optional[float] = 1.0, dtype=numpy.float32) -> NDArray:
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"""
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Allocate an ndarray for storing grid data.
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@ -254,9 +259,10 @@ class Grid:
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else:
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return numpy.full(self.cell_data_shape, fill_value, dtype=dtype)
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def __init__(self,
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pixel_edge_coordinates: Sequence[numpy.ndarray],
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shifts: numpy.ndarray = Yee_Shifts_E,
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def __init__(
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self,
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pixel_edge_coordinates: Sequence[ArrayLike],
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shifts: ArrayLike = Yee_Shifts_E,
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periodic: Union[bool, Sequence[bool]] = False,
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) -> None:
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"""
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@ -1,19 +1,21 @@
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"""
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Position-related methods for Grid class
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"""
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from typing import List, Optional
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from typing import List, Optional, Sequence
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import numpy # type: ignore
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import numpy
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from numpy.typing import NDArray, ArrayLike
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from . import GridError
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def ind2pos(self,
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ind: numpy.ndarray,
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def ind2pos(
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self,
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ind: NDArray,
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which_shifts: Optional[int] = None,
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round_ind: bool = True,
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check_bounds: bool = True
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) -> numpy.ndarray:
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) -> NDArray[numpy.float64]:
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"""
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Returns the natural position corresponding to the specified cell center indices.
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The resulting position is clipped to the bounds of the grid
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@ -59,12 +61,13 @@ def ind2pos(self,
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return numpy.array(position, dtype=float)
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def pos2ind(self,
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r: numpy.ndarray,
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def pos2ind(
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self,
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r: ArrayLike,
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which_shifts: Optional[int],
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round_ind: bool = True,
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check_bounds: bool = True
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) -> numpy.ndarray:
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) -> NDArray[numpy.float64]:
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"""
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Returns the cell-center indices corresponding to the specified natural position.
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The resulting position is clipped to within the outer centers of the grid.
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@ -3,7 +3,8 @@ Readback and visualization methods for Grid class
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"""
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from typing import Dict, Optional, Union, Any
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import numpy # type: ignore
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import numpy
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from numpy.typing import NDArray, ArrayLike
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from . import GridError
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@ -12,13 +13,14 @@ from . import GridError
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# .visualize_isosurface uses mpl_toolkits.mplot3d
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def get_slice(self,
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cell_data: numpy.ndarray,
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def get_slice(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: float,
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which_shifts: int = 0,
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sample_period: int = 1
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) -> numpy.ndarray:
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) -> NDArray:
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"""
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Retrieve a slice of a grid.
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Interpolates if given a position between two planes.
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@ -75,8 +77,9 @@ def get_slice(self,
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return sliced_grid
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def visualize_slice(self,
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cell_data: numpy.ndarray,
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def visualize_slice(
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self,
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cell_data: NDArray,
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surface_normal: int,
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center: float,
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which_shifts: int = 0,
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@ -122,8 +125,9 @@ def visualize_slice(self,
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pyplot.show()
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def visualize_isosurface(self,
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cell_data: numpy.ndarray,
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def visualize_isosurface(
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self,
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cell_data: NDArray,
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level: Optional[float] = None,
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which_shifts: int = 0,
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sample_period: int = 1,
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@ -1,6 +1,6 @@
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import pytest # type: ignore
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import numpy # type: ignore
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from numpy.testing import assert_allclose, assert_array_equal # type: ignore
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import numpy
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from numpy.testing import assert_allclose, assert_array_equal
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from .. import Grid
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