diff --git a/masque/shapes/poly_collection.py b/masque/shapes/poly_collection.py new file mode 100644 index 0000000..d7d1c95 --- /dev/null +++ b/masque/shapes/poly_collection.py @@ -0,0 +1,210 @@ +from typing import Any, cast, Iterable +from collections.abc import Sequence +import copy +import functools + +import numpy +from numpy import pi +from numpy.typing import NDArray, ArrayLike + +from . import Shape, normalized_shape_tuple +from ..error import PatternError +from ..repetition import Repetition +from ..utils import is_scalar, rotation_matrix_2d, annotations_lt, annotations_eq, rep2key +from ..utils import remove_colinear_vertices, remove_duplicate_vertices, annotations_t + + +@functools.total_ordering +class PolyCollection(Shape): + """ + A collection of polygons, consisting of list of vertex arrays (N_m x 2 ndarrays) which specify + implicitly-closed boundaries, and an offset. + + Note that the setter for `PolyCollection.vertex_list` creates a copy of the + passed vertex coordinates. + + A `normalized_form(...)` is available, but can be quite slow with lots of vertices. + """ + __slots__ = ( + '_vertex_lists', + # Inherited + '_offset', '_repetition', '_annotations', + ) + + _vertex_lists: list[NDArray[numpy.float64]] + """ List of ndarrays (N_m x 2) of vertices `[ [[x0, y0], [x1, y1], ...] ]` """ + + # vertex_lists property + @property + def vertex_lists(self) -> Any: # mypy#3004 NDArray[numpy.float64]: + """ + Vertices of the polygons (ist of ndarrays (N_m x 2) `[ [[x0, y0], [x1, y1], ...] ]` + + When setting, note that a copy will be made, + """ + return self._vertex_lists + + @vertex_lists.setter + def vertex_lists(self, val: ArrayLike) -> None: + val = [numpy.array(vv, dtype=float) for vv in val] + for ii, vv in enumerate(val): + if len(vv.shape) < 2 or vv.shape[1] != 2: + raise PatternError(f'vertex_lists contents must be an Nx2 arrays (polygon #{ii} fails)') + if vv.shape[0] < 3: + raise PatternError(f'vertex_lists contents must have at least 3 vertices (Nx2 where N>2) (polygon ${ii} has shape {vv.shape})') + self._vertices = val + + # xs property + @property + def xs(self) -> NDArray[numpy.float64]: + """ + All vertex x coords as a 1D ndarray + """ + return self.vertices[:, 0] + + def __init__( + self, + vertex_lists: Iterable[ArrayLike], + *, + offset: ArrayLike = (0.0, 0.0), + rotation: float = 0.0, + repetition: Repetition | None = None, + annotations: annotations_t | None = None, + raw: bool = False, + ) -> None: + if raw: + assert isinstance(vertex_lists, list) + assert all(isinstance(vv, numpy.ndarray) for vv in vertex_lists) + assert isinstance(offset, numpy.ndarray) + self._vertex_lists = vertex_lists + self._offset = offset + self._repetition = repetition + self._annotations = annotations if annotations is not None else {} + else: + self.vertices = vertices + self.offset = offset + self.repetition = repetition + self.annotations = annotations if annotations is not None else {} + self.rotate(rotation) + + def __deepcopy__(self, memo: dict | None = None) -> 'PolyCollection': + memo = {} if memo is None else memo + new = copy.copy(self) + new._offset = self._offset.copy() + new._vertex_lists = [vv.copy() for vv in self._vertex_lists] + new._annotations = copy.deepcopy(self._annotations) + return new + + def __eq__(self, other: Any) -> bool: + return ( + type(self) is type(other) + and numpy.array_equal(self.offset, other.offset) + and all(numpy.array_equal(ss, oo) for ss, oo in zip(self.vertices, other.vertices)) + and self.repetition == other.repetition + and annotations_eq(self.annotations, other.annotations) + ) + + def __lt__(self, other: Shape) -> bool: + if type(self) is not type(other): + if repr(type(self)) != repr(type(other)): + return repr(type(self)) < repr(type(other)) + return id(type(self)) < id(type(other)) + + other = cast(PolyCollection, other) + for vv, oo in zip(self.vertices, other.vertices): + if not numpy.array_equal(vv, oo): + min_len = min(vv.shape[0], oo.shape[0]) + eq_mask = vv[:min_len] != oo[:min_len] + eq_lt = vv[:min_len] < oo[:min_len] + eq_lt_masked = eq_lt[eq_mask] + if eq_lt_masked.size > 0: + return eq_lt_masked.flat[0] + return vv.shape[0] < oo.shape[0] + if len(self.vertex_lists) != len(other.vertex_lists): + return len(self.vertex_lists) < len(other.vertex_lists): + if not numpy.array_equal(self.offset, other.offset): + return tuple(self.offset) < tuple(other.offset) + if self.repetition != other.repetition: + return rep2key(self.repetition) < rep2key(other.repetition) + return annotations_lt(self.annotations, other.annotations) + + def pop_as_polygon(self, index: int) -> 'Polygon': + """ + Remove one polygon from the list, and return it as a `Polygon` object. + + Args: + index: which polygon to pop + """ + verts = self.vertex_lists.pop(index) + return Polygon( + vertices=verts, + offset=self.offset, + repetition=self.repetition.copy(), + annotations=copy.deepcopy(self.annotations), + ) + + def to_polygons( + self, + num_vertices: int | None = None, # unused # noqa: ARG002 + max_arclen: float | None = None, # unused # noqa: ARG002 + ) -> list['Polygon']: + return [Polygon( + vertices=vv, + offset=self.offset, + repetition=self.repetition.copy(), + annotations=copy.deepcopy(self.annotations), + ) for vv in self.vertex_lists] + + def get_bounds_single(self) -> NDArray[numpy.float64]: # TODO note shape get_bounds doesn't include repetition + mins = [numpy.min(vv, axis=0) for vv self.vertex_lists] + maxs = [numpy.max(vv, axis=0) for vv self.vertex_lists] + return numpy.vstack((self.offset + numpy.min(self.vertex_lists, axis=0), + self.offset + numpy.max(self.vertex_lists, axis=0))) + + def rotate(self, theta: float) -> 'Polygon': + if theta != 0: + for vv in self.vertex_lists: + vv[:] = numpy.dot(rotation_matrix_2d(theta), vv.T).T + return self + + def mirror(self, axis: int = 0) -> 'Polygon': + for vv in self.vertex_lists: + vv[:, axis - 1] *= -1 + return self + + def scale_by(self, c: float) -> 'Polygon': + for vv in self.vertex_lists: + vv *= c + return self + + def normalized_form(self, norm_value: float) -> normalized_shape_tuple: + # Note: this function is going to be pretty slow for many-vertexed polygons, relative to + # other shapes + meanv = numpy.concatenate(self.vertex_lists).mean(axis=0) + zeroed_vertices = [vv - meanv for vv in self.vertex_lists] + offset = meanv + self.offset + + scale = zeroed_vertices.std() + normed_vertices = zeroed_vertices / scale + + _, _, vertex_axis = numpy.linalg.svd(zeroed_vertices) + rotation = numpy.arctan2(vertex_axis[0][1], vertex_axis[0][0]) % (2 * pi) + rotated_vertices = numpy.vstack([numpy.dot(rotation_matrix_2d(-rotation), v) + for v in normed_vertices]) + + # Reorder the vertices so that the one with lowest x, then y, comes first. + x_min = rotated_vertices[:, 0].argmin() + if not is_scalar(x_min): + y_min = rotated_vertices[x_min, 1].argmin() + x_min = cast(Sequence, x_min)[y_min] + reordered_vertices = numpy.roll(rotated_vertices, -x_min, axis=0) + + # TODO: normalize mirroring? + + return ((type(self), reordered_vertices.data.tobytes()), + (offset, scale / norm_value, rotation, False), + lambda: Polygon(reordered_vertices * norm_value)) + + def __repr__(self) -> str: + centroid = self.offset + numpy.concatenate(self.vertex_lists).mean(axis=0) + return f''