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https://git.mirrors.martin98.com/https://github.com/Ultimaker/Cura
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199 lines
8.7 KiB
Python
199 lines
8.7 KiB
Python
from UM.Scene.Iterator.DepthFirstIterator import DepthFirstIterator
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from UM.Logger import Logger
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from UM.Math.Vector import Vector
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from cura.Arranging.ShapeArray import ShapeArray
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from cura.Scene import ZOffsetDecorator
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from collections import namedtuple
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import numpy
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import copy
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## Return object for bestSpot
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LocationSuggestion = namedtuple("LocationSuggestion", ["x", "y", "penalty_points", "priority"])
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## The Arrange classed is used together with ShapeArray. Use it to find
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# good locations for objects that you try to put on a build place.
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# Different priority schemes can be defined so it alters the behavior while using
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# the same logic.
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class Arrange:
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build_volume = None
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def __init__(self, x, y, offset_x, offset_y, scale= 1.0):
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self.shape = (y, x)
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self._priority = numpy.zeros((x, y), dtype=numpy.int32)
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self._priority_unique_values = []
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self._occupied = numpy.zeros((x, y), dtype=numpy.int32)
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self._scale = scale # convert input coordinates to arrange coordinates
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self._offset_x = offset_x
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self._offset_y = offset_y
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self._last_priority = 0
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self._is_empty = True
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## Helper to create an Arranger instance
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#
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# Either fill in scene_root and create will find all sliceable nodes by itself,
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# or use fixed_nodes to provide the nodes yourself.
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# \param scene_root Root for finding all scene nodes
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# \param fixed_nodes Scene nodes to be placed
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@classmethod
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def create(cls, scene_root = None, fixed_nodes = None, scale = 0.5, x = 220, y = 220):
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arranger = Arrange(x, y, x // 2, y // 2, scale = scale)
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arranger.centerFirst()
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if fixed_nodes is None:
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fixed_nodes = []
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for node_ in DepthFirstIterator(scene_root):
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# Only count sliceable objects
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if node_.callDecoration("isSliceable"):
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fixed_nodes.append(node_)
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# Place all objects fixed nodes
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for fixed_node in fixed_nodes:
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vertices = fixed_node.callDecoration("getConvexHull")
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if not vertices:
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continue
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points = copy.deepcopy(vertices._points)
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shape_arr = ShapeArray.fromPolygon(points, scale = scale)
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arranger.place(0, 0, shape_arr)
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# If a build volume was set, add the disallowed areas
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if Arrange.build_volume:
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disallowed_areas = Arrange.build_volume.getDisallowedAreas()
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for area in disallowed_areas:
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points = copy.deepcopy(area._points)
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shape_arr = ShapeArray.fromPolygon(points, scale = scale)
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arranger.place(0, 0, shape_arr, update_empty = False)
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return arranger
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## Find placement for a node (using offset shape) and place it (using hull shape)
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# return the nodes that should be placed
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# \param node
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# \param offset_shape_arr ShapeArray with offset, used to find location
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# \param hull_shape_arr ShapeArray without offset, for placing the shape
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def findNodePlacement(self, node, offset_shape_arr, hull_shape_arr, step = 1):
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new_node = copy.deepcopy(node)
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best_spot = self.bestSpot(
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offset_shape_arr, start_prio = self._last_priority, step = step)
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x, y = best_spot.x, best_spot.y
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# Save the last priority.
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self._last_priority = best_spot.priority
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# Ensure that the object is above the build platform
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new_node.removeDecorator(ZOffsetDecorator.ZOffsetDecorator)
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if new_node.getBoundingBox():
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center_y = new_node.getWorldPosition().y - new_node.getBoundingBox().bottom
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else:
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center_y = 0
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if x is not None: # We could find a place
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new_node.setPosition(Vector(x, center_y, y))
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found_spot = True
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self.place(x, y, hull_shape_arr) # place the object in arranger
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else:
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Logger.log("d", "Could not find spot!"),
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found_spot = False
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new_node.setPosition(Vector(200, center_y, 100))
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return new_node, found_spot
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## Fill priority, center is best. Lower value is better
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# This is a strategy for the arranger.
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def centerFirst(self):
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# Square distance: creates a more round shape
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self._priority = numpy.fromfunction(
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lambda i, j: (self._offset_x - i) ** 2 + (self._offset_y - j) ** 2, self.shape, dtype=numpy.int32)
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self._priority_unique_values = numpy.unique(self._priority)
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self._priority_unique_values.sort()
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## Fill priority, back is best. Lower value is better
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# This is a strategy for the arranger.
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def backFirst(self):
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self._priority = numpy.fromfunction(
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lambda i, j: 10 * j + abs(self._offset_x - i), self.shape, dtype=numpy.int32)
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self._priority_unique_values = numpy.unique(self._priority)
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self._priority_unique_values.sort()
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## Return the amount of "penalty points" for polygon, which is the sum of priority
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# None if occupied
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# \param x x-coordinate to check shape
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# \param y y-coordinate
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# \param shape_arr the ShapeArray object to place
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def checkShape(self, x, y, shape_arr):
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x = int(self._scale * x)
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y = int(self._scale * y)
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offset_x = x + self._offset_x + shape_arr.offset_x
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offset_y = y + self._offset_y + shape_arr.offset_y
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occupied_slice = self._occupied[
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offset_y:offset_y + shape_arr.arr.shape[0],
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offset_x:offset_x + shape_arr.arr.shape[1]]
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try:
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if numpy.any(occupied_slice[numpy.where(shape_arr.arr == 1)]):
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return None
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except IndexError: # out of bounds if you try to place an object outside
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return None
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prio_slice = self._priority[
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offset_y:offset_y + shape_arr.arr.shape[0],
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offset_x:offset_x + shape_arr.arr.shape[1]]
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return numpy.sum(prio_slice[numpy.where(shape_arr.arr == 1)])
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## Find "best" spot for ShapeArray
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# Return namedtuple with properties x, y, penalty_points, priority
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# \param shape_arr ShapeArray
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# \param start_prio Start with this priority value (and skip the ones before)
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# \param step Slicing value, higher = more skips = faster but less accurate
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def bestSpot(self, shape_arr, start_prio = 0, step = 1):
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start_idx_list = numpy.where(self._priority_unique_values == start_prio)
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if start_idx_list:
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start_idx = start_idx_list[0][0]
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else:
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start_idx = 0
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for priority in self._priority_unique_values[start_idx::step]:
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tryout_idx = numpy.where(self._priority == priority)
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for idx in range(len(tryout_idx[0])):
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x = tryout_idx[0][idx]
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y = tryout_idx[1][idx]
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projected_x = x - self._offset_x
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projected_y = y - self._offset_y
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# array to "world" coordinates
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penalty_points = self.checkShape(projected_x, projected_y, shape_arr)
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if penalty_points is not None:
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return LocationSuggestion(x = projected_x, y = projected_y, penalty_points = penalty_points, priority = priority)
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return LocationSuggestion(x = None, y = None, penalty_points = None, priority = priority) # No suitable location found :-(
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## Place the object.
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# Marks the locations in self._occupied and self._priority
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# \param x x-coordinate
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# \param y y-coordinate
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# \param shape_arr ShapeArray object
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def place(self, x, y, shape_arr, update_empty = True):
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x = int(self._scale * x)
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y = int(self._scale * y)
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offset_x = x + self._offset_x + shape_arr.offset_x
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offset_y = y + self._offset_y + shape_arr.offset_y
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shape_y, shape_x = self._occupied.shape
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min_x = min(max(offset_x, 0), shape_x - 1)
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min_y = min(max(offset_y, 0), shape_y - 1)
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max_x = min(max(offset_x + shape_arr.arr.shape[1], 0), shape_x - 1)
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max_y = min(max(offset_y + shape_arr.arr.shape[0], 0), shape_y - 1)
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occupied_slice = self._occupied[min_y:max_y, min_x:max_x]
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# we use a slice of shape because it can be out of bounds
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new_occupied = numpy.where(shape_arr.arr[
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min_y - offset_y:max_y - offset_y, min_x - offset_x:max_x - offset_x] == 1)
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if update_empty and new_occupied:
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self._is_empty = False
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occupied_slice[new_occupied] = 1
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# Set priority to low (= high number), so it won't get picked at trying out.
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prio_slice = self._priority[min_y:max_y, min_x:max_x]
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prio_slice[numpy.where(shape_arr.arr[
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min_y - offset_y:max_y - offset_y, min_x - offset_x:max_x - offset_x] == 1)] = 999
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@property
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def isEmpty(self):
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return self._is_empty
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