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124 lines
3.0 KiB
Python
124 lines
3.0 KiB
Python
from typing import Self, Any
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from abc import ABCMeta, abstractmethod
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import numpy
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from numpy.typing import NDArray, ArrayLike
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from ..error import MasqueError
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_empty_slots = () # Workaround to get mypy to ignore intentionally empty slots for superclass
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class Positionable(metaclass=ABCMeta):
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"""
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Trait class for all positionable entities
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"""
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__slots__ = ()
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#
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# Properties
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#
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@property
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@abstractmethod
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def offset(self) -> NDArray[numpy.float64]:
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"""
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[x, y] offset
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"""
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pass
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@offset.setter
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@abstractmethod
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def offset(self, val: ArrayLike) -> None:
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pass
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@abstractmethod
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def set_offset(self, offset: ArrayLike) -> Self:
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"""
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Set the offset
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Args:
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offset: [x_offset, y,offset]
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Returns:
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self
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"""
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pass
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@abstractmethod
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def translate(self, offset: ArrayLike) -> Self:
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"""
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Translate the entity by the given offset
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Args:
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offset: [x_offset, y,offset]
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Returns:
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self
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"""
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pass
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class PositionableImpl(Positionable, metaclass=ABCMeta):
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"""
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Simple implementation of Positionable
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"""
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__slots__ = _empty_slots
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_offset: NDArray[numpy.float64]
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""" `[x_offset, y_offset]` """
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#
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# Properties
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#
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# offset property
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@property
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def offset(self) -> Any: # mypy#3004 NDArray[numpy.float64]:
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"""
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[x, y] offset
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"""
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return self._offset
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@offset.setter
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def offset(self, val: ArrayLike) -> None:
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if not isinstance(val, numpy.ndarray) or val.dtype != numpy.float64:
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val = numpy.array(val, dtype=float)
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if val.size != 2:
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raise MasqueError('Offset must be convertible to size-2 ndarray')
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self._offset = val.flatten() # type: ignore
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#
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# Methods
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#
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def set_offset(self, offset: ArrayLike) -> Self:
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self.offset = offset
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return self
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def translate(self, offset: ArrayLike) -> Self:
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self._offset += offset # type: ignore # NDArray += ArrayLike should be fine??
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return self
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class Bounded(metaclass=ABCMeta):
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@abstractmethod
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def get_bounds(self, *args, **kwargs) -> NDArray[numpy.float64] | None:
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"""
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Returns `[[x_min, y_min], [x_max, y_max]]` which specify a minimal bounding box for the entity.
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Returns `None` for an empty entity.
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"""
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pass
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def get_bounds_nonempty(self, *args, **kwargs) -> NDArray[numpy.float64]:
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"""
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Returns `[[x_min, y_min], [x_max, y_max]]` which specify a minimal bounding box for the entity.
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Asserts that the entity is non-empty (i.e., `get_bounds()` does not return None).
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This is handy for destructuring like `xy_min, xy_max = entity.get_bounds_nonempty()`
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"""
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bounds = self.get_bounds(*args, **kwargs)
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assert bounds is not None
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return bounds
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