Formally allow instances to point to None (i.e. an 'empty' pattern)
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@ -100,7 +100,9 @@ def write(patterns: Pattern or List[Pattern],
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# Get a dict of id(pattern) -> pattern
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patterns_by_id = {id(pattern): pattern for pattern in patterns}
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for pattern in patterns:
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patterns_by_id.update(pattern.referenced_patterns_by_id())
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for i, p in pattern.referenced_patterns_by_id().items():
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if p is not None:
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patterns_by_id[i] = p
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disambiguate_func(patterns_by_id.values())
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@ -170,7 +172,9 @@ def dose2dtype(patterns: List[Pattern],
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# Get a dict of id(pattern) -> pattern
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patterns_by_id = {id(pattern): pattern for pattern in patterns}
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for pattern in patterns:
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patterns_by_id.update(pattern.referenced_patterns_by_id())
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for i, p in pattern.referenced_patterns_by_id().items():
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if p is not None:
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patterns_by_id[i] = p
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# Get a table of (id(pat), written_dose) for each pattern and subpattern
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sd_table = make_dose_table(patterns)
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@ -466,6 +470,8 @@ def _subpatterns_to_refs(subpatterns: List[SubPattern or GridRepetition]
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) -> List[gdsii.elements.ARef or gdsii.elements.SRef]:
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refs = []
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for subpat in subpatterns:
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if subpat.pattern is None:
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continue
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encoded_name = subpat.pattern.name
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# Note: GDS mirrors first and rotates second
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@ -61,6 +61,8 @@ def writefile(pattern: Pattern,
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# Now create a group for each row in sd_table (ie, each pattern + dose combination)
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# and add in any Boundary and Use elements
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for pat in patterns_by_id.values():
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if pat is None:
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continue
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svg_group = svg.g(id=mangle_name(pat), fill='blue', stroke='red')
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for shape in pat.shapes:
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@ -75,6 +77,8 @@ def writefile(pattern: Pattern,
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svg_group.add(path)
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for subpat in pat.subpatterns:
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if subpat.pattern is None:
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continue
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transform = 'scale({:g}) rotate({:g}) translate({:g},{:g})'.format(
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subpat.scale, subpat.rotation, subpat.offset[0], subpat.offset[1])
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use = svg.use(href='#' + mangle_name(subpat.pattern), transform=transform)
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@ -38,6 +38,8 @@ def make_dose_table(patterns: List[Pattern], dose_multiplier: float=1.0) -> Set[
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dose_table = {(id(pattern), dose_multiplier) for pattern in patterns}
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for pattern in patterns:
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for subpat in pattern.subpatterns:
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if subpat.pattern is None:
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continue
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subpat_dose_entry = (id(subpat.pattern), subpat.dose * dose_multiplier)
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if subpat_dose_entry not in dose_table:
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subpat_dose_table = make_dose_table([subpat.pattern], subpat.dose * dose_multiplier)
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@ -151,7 +151,9 @@ class Pattern:
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A Pattern containing all the shapes and subpatterns for which the parameter
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functions return True
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"""
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def do_subset(src):
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def do_subset(src: Optional['Pattern']) -> Optional['Pattern']:
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if src is None:
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return None
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pat = Pattern(name=src.name)
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if shapes_func is not None:
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pat.shapes = [s for s in src.shapes if shapes_func(s)]
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@ -165,6 +167,8 @@ class Pattern:
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pat = self.apply(do_subset)
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else:
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pat = do_subset(self)
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assert(pat is not None)
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return pat
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def apply(self,
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@ -197,7 +201,11 @@ class Pattern:
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if pat_id not in memo:
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memo[pat_id] = None
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pat = func(self)
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if pat is not None:
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for subpat in pat.subpatterns:
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if subpat.pattern is None:
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subpat.pattern = func(None)
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else:
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subpat.pattern = subpat.pattern.apply(func, memo)
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memo[pat_id] = pat
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elif memo[pat_id] is None:
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@ -277,6 +285,7 @@ class Pattern:
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else:
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sp_transform = False
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if subpattern.pattern is not None:
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subpattern.pattern = subpattern.pattern.dfs(visit_before=visit_before,
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visit_after=visit_after,
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transform=sp_transform,
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@ -311,6 +320,7 @@ class Pattern:
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(shape.to_polygons(poly_num_points, poly_max_arclen)
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for shape in old_shapes)))
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for subpat in self.subpatterns:
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if subpat.pattern is not None:
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subpat.pattern.polygonize(poly_num_points, poly_max_arclen)
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return self
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@ -368,6 +378,8 @@ class Pattern:
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if recursive:
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for subpat in self.subpatterns:
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if subpat.pattern is None:
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continue
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subpat.pattern.subpatternize(recursive=True,
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norm_value=norm_value,
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exclude_types=exclude_types)
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@ -431,6 +443,7 @@ class Pattern:
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for subpat in self.subpatterns:
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if id(subpat.pattern) not in ids:
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ids[id(subpat.pattern)] = subpat.pattern
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if subpat.pattern is not None:
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ids.update(subpat.pattern.referenced_patterns_by_id())
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return ids
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@ -446,7 +459,7 @@ class Pattern:
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List of `(pat.name, pat)` tuples for all referenced Pattern objects
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"""
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pats_by_id = self.referenced_patterns_by_id()
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pat_list = [(p.name, p) for p in pats_by_id.values()]
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pat_list = [(p.name if p is not None else None, p) for p in pats_by_id.values()]
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return pat_list
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def get_bounds(self) -> Union[numpy.ndarray, None]:
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@ -496,6 +509,8 @@ class Pattern:
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self.subpatterns = []
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shape_counts = {}
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for subpat in subpatterns:
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if subpat.pattern is None:
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continue
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subpat.pattern.flatten()
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p = subpat.as_pattern()
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@ -839,7 +854,7 @@ class Pattern:
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if pat in memo:
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return memo
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children = set(sp.pattern for sp in pat.subpatterns)
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children = set(sp.pattern for sp in pat.subpatterns if sp.pattern is not None)
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new_children = children - memo
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memo |= children
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@ -298,6 +298,7 @@ class GridRepetition:
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A copy of self.pattern which has been scaled, rotated, repeated, etc.
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etc. according to this `GridRepetition`'s properties.
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"""
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assert(self.pattern is not None)
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patterns = []
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for a in range(self.a_count):
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@ -411,7 +412,7 @@ class GridRepetition:
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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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def get_bounds(self) -> Optional[numpy.ndarray]:
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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 `GridRepetition` in each dimension.
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@ -420,6 +421,8 @@ class GridRepetition:
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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 scale_by(self, c: float) -> 'GridRepetition':
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@ -496,6 +499,7 @@ class GridRepetition:
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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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@ -510,6 +514,7 @@ class GridRepetition:
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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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@ -55,7 +55,7 @@ class SubPattern:
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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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pattern: Optional['Pattern'],
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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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@ -176,6 +176,7 @@ class SubPattern:
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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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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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@ -242,7 +243,7 @@ class SubPattern:
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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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def get_bounds(self) -> Optional[numpy.ndarray]:
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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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@ -251,6 +252,8 @@ class SubPattern:
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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 scale_by(self, c: float) -> 'SubPattern':
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@ -311,6 +314,7 @@ class SubPattern:
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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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@ -325,6 +329,7 @@ class SubPattern:
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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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