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318 lines
8.6 KiB
Python
318 lines
8.6 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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from typing import Union, List, Dict, Tuple
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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 .error import PatternError, PatternLockedError
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from .utils import is_scalar, rotation_matrix_2d, vector2
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__author__ = 'Jan Petykiewicz'
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class SubPattern:
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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', '_offset', '_rotation', '_dose', '_scale', '_mirrored',
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'identifier', 'locked')
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pattern: 'Pattern' or None
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""" The `Pattern` being instanced """
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_offset: numpy.ndarray
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""" (x, y) offset for the instance """
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_rotation: float
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""" rotation for the instance, radians counterclockwise """
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_dose: float
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""" dose factor for the instance """
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_scale: float
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""" scale factor for the instance """
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_mirrored: List[bool]
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""" Whether to mirror the instanc across the x and/or y axes. """
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identifier: Tuple
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""" An arbitrary identifier """
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locked: bool
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""" If `True`, disallows changes to the GridRepetition """
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#TODO more documentation?
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def __init__(self,
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pattern: 'Pattern' or None,
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offset: vector2 = (0.0, 0.0),
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rotation: float = 0.0,
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mirrored: List[bool] = None,
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dose: float = 1.0,
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scale: float = 1.0,
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locked: bool = False):
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if pattern is not None and not hasattr(pattern, 'lock'):
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raise PatternError('Provided pattern has no "lock()" method.\n'
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'Maybe it''s not a Pattern instance?')
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self.unlock()
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self.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.locked = locked
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def __setattr__(self, name, value):
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if self.locked and name != 'locked':
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raise PatternLockedError()
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object.__setattr__(self, name, value)
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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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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.locked = self.locked
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return new
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# offset property
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@property
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def offset(self) -> numpy.ndarray:
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return self._offset
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@offset.setter
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def offset(self, val: vector2):
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if not isinstance(val, numpy.ndarray):
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val = numpy.array(val, dtype=float)
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if val.size != 2:
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raise PatternError('Offset must be convertible to size-2 ndarray')
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self._offset = val.flatten().astype(float)
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# dose property
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@property
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def dose(self) -> float:
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return self._dose
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@dose.setter
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def dose(self, val: float):
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if not is_scalar(val):
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raise PatternError('Dose must be a scalar')
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if not val >= 0:
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raise PatternError('Dose must be non-negative')
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self._dose = val
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# scale property
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@property
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def scale(self) -> float:
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return self._scale
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@scale.setter
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def scale(self, val: float):
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if not is_scalar(val):
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raise PatternError('Scale must be a scalar')
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if not val > 0:
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raise PatternError('Scale must be positive')
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self._scale = val
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# Rotation property [ccw]
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@property
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def rotation(self) -> float:
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return self._rotation
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@rotation.setter
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def rotation(self, val: float):
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if not is_scalar(val):
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raise PatternError('Rotation must be a scalar')
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self._rotation = val % (2 * pi)
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# Mirrored property
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@property
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def mirrored(self) -> List[bool]:
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return self._mirrored
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@mirrored.setter
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def mirrored(self, val: List[bool]):
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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)
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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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pattern = self.pattern.deepcopy().deepunlock()
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pattern.scale_by(self.scale)
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[pattern.mirror(ax) for ax, do in enumerate(self.mirrored) if do]
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pattern.rotate_around((0.0, 0.0), self.rotation)
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pattern.translate_elements(self.offset)
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pattern.scale_element_doses(self.dose)
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return pattern
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def translate(self, offset: vector2) -> 'SubPattern':
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"""
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Translate by the given offset
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Args:
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offset: Offset `[x, y]` to translate by
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Returns:
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self
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"""
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self.offset += offset
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return self
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def rotate_around(self, pivot: vector2, rotation: float) -> 'SubPattern':
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"""
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Rotate around a point
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Args:
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pivot: Point `[x, y]` to rotate around
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rotation: Angle to rotate by (counterclockwise, radians)
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Returns:
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self
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"""
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pivot = numpy.array(pivot, dtype=float)
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self.translate(-pivot)
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self.offset = numpy.dot(rotation_matrix_2d(rotation), self.offset)
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self.rotate(rotation)
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self.translate(+pivot)
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return self
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def rotate(self, rotation: float) -> 'SubPattern':
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"""
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Rotate the instance around it's origin
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Args:
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rotation: Angle to rotate by (counterclockwise, radians)
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Returns:
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self
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"""
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self.rotation += rotation
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return self
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def mirror(self, axis: int) -> 'SubPattern':
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"""
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Mirror the subpattern across an axis.
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Args:
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axis: Axis to mirror across.
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Returns:
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self
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"""
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self.mirrored[axis] = not self.mirrored[axis]
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self.rotation *= -1
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return self
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def get_bounds(self) -> numpy.ndarray or None:
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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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return self.as_pattern().get_bounds()
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def scale_by(self, c: float) -> 'SubPattern':
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"""
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Scale the subpattern by a factor
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Args:
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c: scaling factor
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Returns:
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self
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"""
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self.scale *= c
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return self
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def copy(self) -> 'SubPattern':
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"""
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Return a shallow copy of the subpattern.
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Returns:
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`copy.copy(self)`
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"""
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return copy.copy(self)
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def deepcopy(self) -> 'SubPattern':
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"""
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Return a deep copy of the subpattern.
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Returns:
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`copy.deepcopy(self)`
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"""
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return copy.deepcopy(self)
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def lock(self) -> 'SubPattern':
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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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object.__setattr__(self, 'locked', True)
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return self
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def unlock(self) -> 'SubPattern':
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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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object.__setattr__(self, 'locked', False)
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return self
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def deeplock(self) -> 'SubPattern':
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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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self.lock()
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self.pattern.deeplock()
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return self
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def deepunlock(self) -> 'SubPattern':
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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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self.unlock()
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self.pattern.deepunlock()
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return self
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