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modernize type annotations

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Jan Petykiewicz 2023-02-23 13:15:32 -08:00 • committed by jan
commit 1463535676
34 changed files with 409 additions and 444 deletions
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18
masque/repetition.py
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@ -3,7 +3,7 @@
instances of an object .
"""
from typing import Union, Dict, Optional, Any, Type
from typing import Any, Type
import copy
from abc import ABCMeta, abstractmethod
@ -52,7 +52,7 @@ class Grid(Repetition):
_a_count: int
""" Number of instances along the direction specified by the `a_vector` """
_b_vector: Optional[NDArray[numpy.float64]]
_b_vector: NDArray[numpy.float64] | None
""" Vector `[x, y]` specifying a second lattice vector for the grid.
Specifies center-to-center spacing between adjacent elements.
Can be `None` for a 1D array.
@ -65,8 +65,8 @@ class Grid(Repetition):
self,
a_vector: ArrayLike,
a_count: int,
b_vector: Optional[ArrayLike] = None,
b_count: Optional[int] = 1,
b_vector: ArrayLike | None = None,
b_count: int | None = 1,
) -> None:
"""
Args:
@ -133,7 +133,7 @@ class Grid(Repetition):
)
return new
def __deepcopy__(self, memo: Optional[Dict] = None) -> 'Grid':
def __deepcopy__(self, memo: dict | None = None) -> 'Grid':
memo = {} if memo is None else memo
new = copy.copy(self)
return new
@ -154,7 +154,7 @@ class Grid(Repetition):
# b_vector property
@property
def b_vector(self) -> Optional[NDArray[numpy.float64]]:
def b_vector(self) -> NDArray[numpy.float64] | None:
return self._b_vector
@b_vector.setter
@ -228,7 +228,7 @@ class Grid(Repetition):
self.b_vector[1 - axis] *= -1
return self
def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
def get_bounds(self) -> NDArray[numpy.float64] | None:
"""
Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
extent of the `Grid` in each dimension.
@ -237,7 +237,7 @@ class Grid(Repetition):
`[[x_min, y_min], [x_max, y_max]]` or `None`
"""
a_extent = self.a_vector * self.a_count
b_extent = self.b_vector * self.b_count if (self.b_vector is not None) else 0 # type: Union[NDArray[numpy.float64], float]
b_extent = self.b_vector * self.b_count if (self.b_vector is not None) else 0 # type: NDArray[numpy.float64] | float
corners = numpy.stack(((0, 0), a_extent, b_extent, a_extent + b_extent))
xy_min = numpy.min(corners, axis=0)
@ -350,7 +350,7 @@ class Arbitrary(Repetition):
self.displacements[1 - axis] *= -1
return self
def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
def get_bounds(self) -> NDArray[numpy.float64] | None:
"""
Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
extent of the `displacements` in each dimension.