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- # Copyright (c) 2019 Ultimaker B.V.
- # Cura is released under the terms of the LGPLv3 or higher.
- import numpy
- import copy
- from typing import Optional, Tuple, TYPE_CHECKING
- from UM.Math.Polygon import Polygon
- if TYPE_CHECKING:
- from UM.Scene.SceneNode import SceneNode
- ## Polygon representation as an array for use with Arrange
- class ShapeArray:
- def __init__(self, arr: numpy.array, offset_x: float, offset_y: float, scale: float = 1) -> None:
- self.arr = arr
- self.offset_x = offset_x
- self.offset_y = offset_y
- self.scale = scale
- ## Instantiate from a bunch of vertices
- # \param vertices
- # \param scale scale the coordinates
- @classmethod
- def fromPolygon(cls, vertices: numpy.array, scale: float = 1) -> "ShapeArray":
- # scale
- vertices = vertices * scale
- # flip y, x -> x, y
- flip_vertices = numpy.zeros((vertices.shape))
- flip_vertices[:, 0] = vertices[:, 1]
- flip_vertices[:, 1] = vertices[:, 0]
- flip_vertices = flip_vertices[::-1]
- # offset, we want that all coordinates have positive values
- offset_y = int(numpy.amin(flip_vertices[:, 0]))
- offset_x = int(numpy.amin(flip_vertices[:, 1]))
- flip_vertices[:, 0] = numpy.add(flip_vertices[:, 0], -offset_y)
- flip_vertices[:, 1] = numpy.add(flip_vertices[:, 1], -offset_x)
- shape = numpy.array([int(numpy.amax(flip_vertices[:, 0])), int(numpy.amax(flip_vertices[:, 1]))])
- shape[numpy.where(shape == 0)] = 1
- arr = cls.arrayFromPolygon(shape, flip_vertices)
- if not numpy.ndarray.any(arr):
- # set at least 1 pixel
- arr[0][0] = 1
- return cls(arr, offset_x, offset_y)
- ## Instantiate an offset and hull ShapeArray from a scene node.
- # \param node source node where the convex hull must be present
- # \param min_offset offset for the offset ShapeArray
- # \param scale scale the coordinates
- @classmethod
- def fromNode(cls, node: "SceneNode", min_offset: float, scale: float = 0.5, include_children: bool = False) -> Tuple[Optional["ShapeArray"], Optional["ShapeArray"]]:
- transform = node._transformation
- transform_x = transform._data[0][3]
- transform_y = transform._data[2][3]
- hull_verts = node.callDecoration("getConvexHull")
- # If a model is too small then it will not contain any points
- if hull_verts is None or not hull_verts.getPoints().any():
- return None, None
- # For one_at_a_time printing you need the convex hull head.
- hull_head_verts = node.callDecoration("getConvexHullHead") or hull_verts
- if hull_head_verts is None:
- hull_head_verts = Polygon()
- # If the child-nodes are included, adjust convex hulls as well:
- if include_children:
- children = node.getAllChildren()
- if not children is None:
- for child in children:
- # 'Inefficient' combination of convex hulls through known code rather than mess it up:
- child_hull = child.callDecoration("getConvexHull")
- if not child_hull is None:
- hull_verts = hull_verts.unionConvexHulls(child_hull)
- child_hull_head = child.callDecoration("getConvexHullHead") or child_hull
- if not child_hull_head is None:
- hull_head_verts = hull_head_verts.unionConvexHulls(child_hull_head)
- offset_verts = hull_head_verts.getMinkowskiHull(Polygon.approximatedCircle(min_offset))
- offset_points = copy.deepcopy(offset_verts._points) # x, y
- offset_points[:, 0] = numpy.add(offset_points[:, 0], -transform_x)
- offset_points[:, 1] = numpy.add(offset_points[:, 1], -transform_y)
- offset_shape_arr = ShapeArray.fromPolygon(offset_points, scale = scale)
- hull_points = copy.deepcopy(hull_verts._points)
- hull_points[:, 0] = numpy.add(hull_points[:, 0], -transform_x)
- hull_points[:, 1] = numpy.add(hull_points[:, 1], -transform_y)
- hull_shape_arr = ShapeArray.fromPolygon(hull_points, scale = scale) # x, y
- return offset_shape_arr, hull_shape_arr
- ## Create np.array with dimensions defined by shape
- # Fills polygon defined by vertices with ones, all other values zero
- # Only works correctly for convex hull vertices
- # Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
- # \param shape numpy format shape, [x-size, y-size]
- # \param vertices
- @classmethod
- def arrayFromPolygon(cls, shape: Tuple[int, int], vertices: numpy.array) -> numpy.array:
- base_array = numpy.zeros(shape, dtype = numpy.int32) # Initialize your array of zeros
- fill = numpy.ones(base_array.shape) * True # Initialize boolean array defining shape fill
- # Create check array for each edge segment, combine into fill array
- for k in range(vertices.shape[0]):
- check_array = cls._check(vertices[k - 1], vertices[k], base_array)
- if check_array is not None:
- fill = numpy.all([fill, check_array], axis=0)
- # Set all values inside polygon to one
- base_array[fill] = 1
- return base_array
- ## Return indices that mark one side of the line, used by arrayFromPolygon
- # Uses the line defined by p1 and p2 to check array of
- # input indices against interpolated value
- # Returns boolean array, with True inside and False outside of shape
- # Originally from: http://stackoverflow.com/questions/37117878/generating-a-filled-polygon-inside-a-numpy-array
- # \param p1 2-tuple with x, y for point 1
- # \param p2 2-tuple with x, y for point 2
- # \param base_array boolean array to project the line on
- @classmethod
- def _check(cls, p1: numpy.array, p2: numpy.array, base_array: numpy.array) -> Optional[numpy.array]:
- if p1[0] == p2[0] and p1[1] == p2[1]:
- return None
- idxs = numpy.indices(base_array.shape) # Create 3D array of indices
- p1 = p1.astype(float)
- p2 = p2.astype(float)
- if p2[0] == p1[0]:
- sign = numpy.sign(p2[1] - p1[1])
- return idxs[1] * sign
- if p2[1] == p1[1]:
- sign = numpy.sign(p2[0] - p1[0])
- return idxs[1] * sign
- # Calculate max column idx for each row idx based on interpolated line between two points
- max_col_idx = (idxs[0] - p1[0]) / (p2[0] - p1[0]) * (p2[1] - p1[1]) + p1[1]
- sign = numpy.sign(p2[0] - p1[0])
- return idxs[1] * sign <= max_col_idx * sign
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