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248 lines
8.5 KiB
Python
248 lines
8.5 KiB
Python
"""
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SubPattern provides basic support for nesting Pattern objects within each other, by adding
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offset, rotation, scaling, and other such properties to the reference.
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"""
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#TODO more top-level documentation
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from typing import Dict, Tuple, Optional, Sequence, TYPE_CHECKING, Any, TypeVar
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import copy
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import numpy
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from numpy import pi
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from numpy.typing import NDArray, ArrayLike
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from .error import PatternError
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from .utils import is_scalar, AutoSlots, annotations_t
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from .repetition import Repetition
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from .traits import (PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl,
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Mirrorable, PivotableImpl, Copyable, LockableImpl, RepeatableImpl,
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AnnotatableImpl)
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if TYPE_CHECKING:
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from . import Pattern
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S = TypeVar('S', bound='SubPattern')
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class SubPattern(PositionableImpl, DoseableImpl, RotatableImpl, ScalableImpl, Mirrorable,
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PivotableImpl, Copyable, RepeatableImpl, LockableImpl, AnnotatableImpl,
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metaclass=AutoSlots):
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"""
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SubPattern provides basic support for nesting Pattern objects within each other, by adding
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offset, rotation, scaling, and associated methods.
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"""
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__slots__ = ('_pattern',
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'_mirrored',
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'identifier',
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)
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_pattern: Optional['Pattern']
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""" The `Pattern` being instanced """
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_mirrored: NDArray[numpy.bool_]
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""" Whether to mirror the instance across the x and/or y axes. """
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identifier: Tuple[Any, ...]
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""" Arbitrary identifier, used internally by some `masque` functions. """
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def __init__(
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self,
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pattern: Optional['Pattern'],
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*,
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offset: ArrayLike = (0.0, 0.0),
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rotation: float = 0.0,
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mirrored: Optional[Sequence[bool]] = None,
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dose: float = 1.0,
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scale: float = 1.0,
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repetition: Optional[Repetition] = None,
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annotations: Optional[annotations_t] = None,
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locked: bool = False,
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identifier: Tuple[Any, ...] = (),
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) -> None:
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"""
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Args:
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pattern: Pattern to reference.
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offset: (x, y) offset applied to the referenced pattern. Not affected by rotation etc.
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rotation: Rotation (radians, counterclockwise) relative to the referenced pattern's (0, 0).
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mirrored: Whether to mirror the referenced pattern across its x and y axes.
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dose: Scaling factor applied to the dose.
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scale: Scaling factor applied to the pattern's geometry.
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repetition: TODO
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locked: Whether the `SubPattern` is locked after initialization.
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identifier: Arbitrary tuple, used internally by some `masque` functions.
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"""
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LockableImpl.unlock(self)
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self.identifier = identifier
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self.pattern = pattern
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self.offset = offset
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self.rotation = rotation
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self.dose = dose
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self.scale = scale
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if mirrored is None:
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mirrored = (False, False)
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self.mirrored = mirrored
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self.repetition = repetition
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self.annotations = annotations if annotations is not None else {}
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self.set_locked(locked)
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def __copy__(self) -> 'SubPattern':
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new = SubPattern(pattern=self.pattern,
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offset=self.offset.copy(),
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rotation=self.rotation,
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dose=self.dose,
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scale=self.scale,
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mirrored=self.mirrored.copy(),
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repetition=copy.deepcopy(self.repetition),
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annotations=copy.deepcopy(self.annotations),
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locked=self.locked)
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return new
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def __deepcopy__(self, memo: Dict = None) -> 'SubPattern':
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memo = {} if memo is None else memo
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new = copy.copy(self).unlock()
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new.pattern = copy.deepcopy(self.pattern, memo)
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new.repetition = copy.deepcopy(self.repetition, memo)
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new.annotations = copy.deepcopy(self.annotations, memo)
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new.set_locked(self.locked)
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return new
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# pattern property
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@property
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def pattern(self) -> Optional['Pattern']:
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return self._pattern
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@pattern.setter
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def pattern(self, val: Optional['Pattern']) -> None:
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from .pattern import Pattern
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if val is not None and not isinstance(val, Pattern):
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raise PatternError(f'Provided pattern {val} is not a Pattern object or None!')
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self._pattern = val
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# Mirrored property
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@property
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def mirrored(self) -> Any: #TODO mypy#3004 NDArray[numpy.bool_]:
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return self._mirrored
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@mirrored.setter
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def mirrored(self, val: ArrayLike) -> None:
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if is_scalar(val):
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raise PatternError('Mirrored must be a 2-element list of booleans')
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self._mirrored = numpy.array(val, dtype=bool, copy=True)
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def as_pattern(self) -> 'Pattern':
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"""
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Returns:
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A copy of self.pattern which has been scaled, rotated, etc. according to this
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`SubPattern`'s properties.
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"""
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assert(self.pattern is not None)
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pattern = self.pattern.deepcopy().deepunlock()
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if self.scale != 1:
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pattern.scale_by(self.scale)
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if numpy.any(self.mirrored):
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pattern.mirror2d(self.mirrored)
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if self.rotation % (2 * pi) != 0:
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pattern.rotate_around((0.0, 0.0), self.rotation)
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if numpy.any(self.offset):
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pattern.translate_elements(self.offset)
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if self.dose != 0:
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pattern.scale_element_doses(self.dose)
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if self.repetition is not None:
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combined = type(pattern)(name='__repetition__')
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for dd in self.repetition.displacements:
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temp_pat = pattern.deepcopy()
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temp_pat.translate_elements(dd)
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combined.append(temp_pat)
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pattern = combined
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return pattern
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def rotate(self: S, rotation: float) -> S:
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self.rotation += rotation
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if self.repetition is not None:
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self.repetition.rotate(rotation)
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return self
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def mirror(self: S, axis: int) -> S:
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self.mirrored[axis] = not self.mirrored[axis]
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self.rotation *= -1
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if self.repetition is not None:
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self.repetition.mirror(axis)
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return self
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def get_bounds(self) -> Optional[NDArray[numpy.float64]]:
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"""
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Return a `numpy.ndarray` containing `[[x_min, y_min], [x_max, y_max]]`, corresponding to the
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extent of the `SubPattern` in each dimension.
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Returns `None` if the contained `Pattern` is empty.
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Returns:
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`[[x_min, y_min], [x_max, y_max]]` or `None`
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"""
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if self.pattern is None:
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return None
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return self.as_pattern().get_bounds()
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def lock(self: S) -> S:
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"""
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Lock the SubPattern, disallowing changes
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Returns:
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self
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"""
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self.mirrored.flags.writeable = False
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PositionableImpl._lock(self)
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LockableImpl.lock(self)
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return self
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def unlock(self: S) -> S:
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"""
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Unlock the SubPattern
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Returns:
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self
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"""
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LockableImpl.unlock(self)
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PositionableImpl._unlock(self)
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self.mirrored.flags.writeable = True
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return self
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def deeplock(self: S) -> S:
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"""
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Recursively lock the SubPattern and its contained pattern
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Returns:
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self
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"""
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assert(self.pattern is not None)
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self.lock()
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self.pattern.deeplock()
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return self
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def deepunlock(self: S) -> S:
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"""
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Recursively unlock the SubPattern and its contained pattern
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This is dangerous unless you have just performed a deepcopy, since
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the subpattern and its components may be used in more than one once!
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Returns:
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self
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"""
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assert(self.pattern is not None)
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self.unlock()
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self.pattern.deepunlock()
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return self
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def __repr__(self) -> str:
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name = self.pattern.name if self.pattern is not None else None
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rotation = f' r{self.rotation*180/pi:g}' if self.rotation != 0 else ''
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scale = f' d{self.scale:g}' if self.scale != 1 else ''
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mirrored = ' m{:d}{:d}'.format(*self.mirrored) if self.mirrored.any() else ''
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dose = f' d{self.dose:g}' if self.dose != 1 else ''
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locked = ' L' if self.locked else ''
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return f'<SubPattern "{name}" at {self.offset}{rotation}{scale}{mirrored}{dose}{locked}>'
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