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https://git.mirrors.martin98.com/https://github.com/Ultimaker/Cura
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2b8a2d0c20
It should really just not print anything except what pytest prints, so you can easily see what tests have failed and what have not.
223 lines
9.9 KiB
Python
223 lines
9.9 KiB
Python
# Copyright (c) 2018 Ultimaker B.V.
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# Cura is released under the terms of the LGPLv3 or higher.
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from typing import List
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from UM.Scene.Iterator.DepthFirstIterator import DepthFirstIterator
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from UM.Logger import Logger
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from UM.Math.Polygon import Polygon
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from UM.Math.Vector import Vector
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from UM.Scene.SceneNode import SceneNode
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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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#
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# Note: Make sure the scale is the same between ShapeArray objects and the Arrange instance.
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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= 0.5):
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self._scale = scale # convert input coordinates to arrange coordinates
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world_x, world_y = int(x * self._scale), int(y * self._scale)
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self._shape = (world_y, world_x)
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self._priority = numpy.zeros((world_y, world_x), dtype=numpy.int32) # beware: these are indexed (y, x)
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self._priority_unique_values = []
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self._occupied = numpy.zeros((world_y, world_x), dtype=numpy.int32) # beware: these are indexed (y, x)
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self._offset_x = int(offset_x * self._scale)
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self._offset_y = int(offset_y * self._scale)
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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 = 350, y = 250, min_offset = 8):
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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("getConvexHullHead") or fixed_node.callDecoration("getConvexHull")
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if not vertices:
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continue
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vertices = vertices.getMinkowskiHull(Polygon.approximatedCircle(min_offset))
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points = copy.deepcopy(vertices._points)
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# After scaling (like up to 0.1 mm) the node might not have points
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if len(points) == 0:
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continue
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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.getDisallowedAreasNoBrim()
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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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## This resets the optimization for finding location based on size
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def resetLastPriority(self):
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self._last_priority = 0
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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, for placing the shape
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# \param hull_shape_arr ShapeArray without offset, used to find location
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def findNodePlacement(self, node: SceneNode, offset_shape_arr: ShapeArray, hull_shape_arr: ShapeArray, step = 1):
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best_spot = self.bestSpot(
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hull_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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node.removeDecorator(ZOffsetDecorator.ZOffsetDecorator)
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bbox = node.getBoundingBox()
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if bbox:
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center_y = node.getWorldPosition().y - bbox.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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node.setPosition(Vector(x, center_y, y))
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found_spot = True
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self.place(x, y, offset_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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node.setPosition(Vector(200, center_y, 100))
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return 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 j, i: (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 j, i: 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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if offset_x < 0 or offset_y < 0:
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return None # out of bounds in self._occupied
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occupied_x_max = offset_x + shape_arr.arr.shape[1]
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occupied_y_max = offset_y + shape_arr.arr.shape[0]
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if occupied_x_max > self._occupied.shape[1] + 1 or occupied_y_max > self._occupied.shape[0] + 1:
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return None # out of bounds in self._occupied
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occupied_slice = self._occupied[
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offset_y:occupied_y_max,
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offset_x:occupied_x_max]
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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[1][idx]
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y = tryout_idx[0][idx]
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projected_x = int((x - self._offset_x) / self._scale)
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projected_y = int((y - self._offset_y) / self._scale)
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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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# \param update_empty updates the _is_empty, used when adding disallowed areas
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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[new_occupied] = 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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