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use ArrayLike when accepting pseudo-ndarrays

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This commit is contained in:
Jan Petykiewicz 2021-06-22 18:59:13 -07:00
commit 4796676a4e
7 changed files with 31 additions and 24 deletions
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11
masque/shapes/path.py
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@ -4,6 +4,7 @@ from enum import Enum
import numpy # type: ignore
from numpy import pi, inf
from numpy.typing import ArrayLike
from . import Shape, normalized_shape_tuple, Polygon, Circle
from .. import PatternError
@ -102,7 +103,7 @@ class Path(Shape, metaclass=AutoSlots):
return self._vertices
@vertices.setter
def vertices(self, val: numpy.ndarray):
def vertices(self, val: ArrayLike):
val = numpy.array(val, dtype=float) # TODO document that these might not be copied
if len(val.shape) < 2 or val.shape[1] != 2:
raise PatternError('Vertices must be an Nx2 array')
@ -119,7 +120,7 @@ class Path(Shape, metaclass=AutoSlots):
return self.vertices[:, 0]
@xs.setter
def xs(self, val: numpy.ndarray):
def xs(self, val: ArrayLike):
val = numpy.array(val, dtype=float).flatten()
if val.size != self.vertices.shape[0]:
raise PatternError('Wrong number of vertices')
@ -134,18 +135,18 @@ class Path(Shape, metaclass=AutoSlots):
return self.vertices[:, 1]
@ys.setter
def ys(self, val: numpy.ndarray):
def ys(self, val: ArrayLike):
val = numpy.array(val, dtype=float).flatten()
if val.size != self.vertices.shape[0]:
raise PatternError('Wrong number of vertices')
self.vertices[:, 1] = val
def __init__(self,
vertices: numpy.ndarray,
vertices: ArrayLike,
width: float = 0.0,
*,
cap: PathCap = PathCap.Flush,
cap_extensions: numpy.ndarray = None,
cap_extensions: Optional[ArrayLike] = None,
offset: vector2 = (0.0, 0.0),
rotation: float = 0,
mirrored: Sequence[bool] = (False, False),

9
masque/shapes/polygon.py
View file

@ -3,6 +3,7 @@ import copy
import numpy # type: ignore
from numpy import pi
from numpy.typing import ArrayLike
from . import Shape, normalized_shape_tuple
from .. import PatternError
@ -33,7 +34,7 @@ class Polygon(Shape, metaclass=AutoSlots):
return self._vertices
@vertices.setter
def vertices(self, val: numpy.ndarray):
def vertices(self, val: ArrayLike):
val = numpy.array(val, dtype=float) # TODO document that these might not be copied
if len(val.shape) < 2 or val.shape[1] != 2:
raise PatternError('Vertices must be an Nx2 array')
@ -50,7 +51,7 @@ class Polygon(Shape, metaclass=AutoSlots):
return self.vertices[:, 0]
@xs.setter
def xs(self, val: numpy.ndarray):
def xs(self, val: ArrayLike):
val = numpy.array(val, dtype=float).flatten()
if val.size != self.vertices.shape[0]:
raise PatternError('Wrong number of vertices')
@ -65,14 +66,14 @@ class Polygon(Shape, metaclass=AutoSlots):
return self.vertices[:, 1]
@ys.setter
def ys(self, val: numpy.ndarray):
def ys(self, val: ArrayLike):
val = numpy.array(val, dtype=float).flatten()
if val.size != self.vertices.shape[0]:
raise PatternError('Wrong number of vertices')
self.vertices[:, 1] = val
def __init__(self,
vertices: numpy.ndarray,
vertices: ArrayLike,
*,
offset: vector2 = (0.0, 0.0),
rotation: float = 0.0,

9
masque/shapes/shape.py
View file

@ -2,6 +2,7 @@ from typing import List, Tuple, Callable, TypeVar, Optional, TYPE_CHECKING
from abc import ABCMeta, abstractmethod
import numpy # type: ignore
from numpy.typing import ArrayLike
from ..traits import (PositionableImpl, LayerableImpl, DoseableImpl,
Rotatable, Mirrorable, Copyable, Scalable,
@ -93,8 +94,8 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
---- Non-abstract methods
'''
def manhattanize_fast(self,
grid_x: numpy.ndarray,
grid_y: numpy.ndarray,
grid_x: ArrayLike,
grid_y: ArrayLike,
) -> List['Polygon']:
"""
Returns a list of polygons with grid-aligned ("Manhattan") edges approximating the shape.
@ -200,8 +201,8 @@ class Shape(PositionableImpl, LayerableImpl, DoseableImpl, Rotatable, Mirrorable
return manhattan_polygons
def manhattanize(self,
grid_x: numpy.ndarray,
grid_y: numpy.ndarray
grid_x: ArrayLike,
grid_y: ArrayLike,
) -> List['Polygon']:
"""
Returns a list of polygons with grid-aligned ("Manhattan") edges approximating the shape.