mirror of
https://git.mirrors.martin98.com/https://github.com/Ultimaker/Cura
synced 2025-05-01 08:14:22 +08:00
c54605a134
As it cannot decorate a class. Also, the deprecated decorator has to be applied before the @classmethod. CURA-7440
259 lines
11 KiB
Python
259 lines
11 KiB
Python
# Copyright (c) 2020 Ultimaker B.V.
|
|
# Cura is released under the terms of the LGPLv3 or higher.
|
|
from typing import Optional
|
|
|
|
from UM.Decorators import deprecated
|
|
from UM.Scene.Iterator.DepthFirstIterator import DepthFirstIterator
|
|
from UM.Logger import Logger
|
|
from UM.Math.Polygon import Polygon
|
|
from UM.Math.Vector import Vector
|
|
from UM.Scene.SceneNode import SceneNode
|
|
from cura.Arranging.ShapeArray import ShapeArray
|
|
from cura.BuildVolume import BuildVolume
|
|
from cura.Scene import ZOffsetDecorator
|
|
|
|
from collections import namedtuple
|
|
|
|
import numpy
|
|
import copy
|
|
|
|
LocationSuggestion = namedtuple("LocationSuggestion", ["x", "y", "penalty_points", "priority"])
|
|
"""Return object for bestSpot"""
|
|
|
|
|
|
class Arrange:
|
|
"""
|
|
The Arrange classed is used together with :py:class:`cura.Arranging.ShapeArray.ShapeArray`. Use it to find good locations for objects that you try to put
|
|
on a build place. Different priority schemes can be defined so it alters the behavior while using the same logic.
|
|
|
|
.. note::
|
|
|
|
Make sure the scale is the same between :py:class:`cura.Arranging.ShapeArray.ShapeArray` objects and the :py:class:`cura.Arranging.Arrange.Arrange` instance.
|
|
"""
|
|
|
|
build_volume = None # type: Optional[BuildVolume]
|
|
|
|
@deprecated("Use the functions in Nest2dArrange instead", "4.8")
|
|
def __init__(self, x, y, offset_x, offset_y, scale = 0.5):
|
|
self._scale = scale # convert input coordinates to arrange coordinates
|
|
world_x, world_y = int(x * self._scale), int(y * self._scale)
|
|
self._shape = (world_y, world_x)
|
|
self._priority = numpy.zeros((world_y, world_x), dtype=numpy.int32) # beware: these are indexed (y, x)
|
|
self._priority_unique_values = []
|
|
self._occupied = numpy.zeros((world_y, world_x), dtype=numpy.int32) # beware: these are indexed (y, x)
|
|
self._offset_x = int(offset_x * self._scale)
|
|
self._offset_y = int(offset_y * self._scale)
|
|
self._last_priority = 0
|
|
self._is_empty = True
|
|
|
|
@classmethod
|
|
@deprecated("Use the functions in Nest2dArrange instead", "4.8")
|
|
def create(cls, scene_root = None, fixed_nodes = None, scale = 0.5, x = 350, y = 250, min_offset = 8) -> "Arrange":
|
|
"""Helper to create an :py:class:`cura.Arranging.Arrange.Arrange` instance
|
|
|
|
Either fill in scene_root and create will find all sliceable nodes by itself, or use fixed_nodes to provide the
|
|
nodes yourself.
|
|
|
|
:param scene_root: Root for finding all scene nodes default = None
|
|
:param fixed_nodes: Scene nodes to be placed default = None
|
|
:param scale: default = 0.5
|
|
:param x: default = 350
|
|
:param y: default = 250
|
|
:param min_offset: default = 8
|
|
"""
|
|
|
|
arranger = Arrange(x, y, x // 2, y // 2, scale = scale)
|
|
arranger.centerFirst()
|
|
|
|
if fixed_nodes is None:
|
|
fixed_nodes = []
|
|
for node_ in DepthFirstIterator(scene_root):
|
|
# Only count sliceable objects
|
|
if node_.callDecoration("isSliceable"):
|
|
fixed_nodes.append(node_)
|
|
|
|
# Place all objects fixed nodes
|
|
for fixed_node in fixed_nodes:
|
|
vertices = fixed_node.callDecoration("getConvexHullHead") or fixed_node.callDecoration("getConvexHull")
|
|
if not vertices:
|
|
continue
|
|
vertices = vertices.getMinkowskiHull(Polygon.approximatedCircle(min_offset))
|
|
points = copy.deepcopy(vertices._points)
|
|
|
|
# After scaling (like up to 0.1 mm) the node might not have points
|
|
if not points.size:
|
|
continue
|
|
try:
|
|
shape_arr = ShapeArray.fromPolygon(points, scale = scale)
|
|
except ValueError:
|
|
Logger.logException("w", "Unable to create polygon")
|
|
continue
|
|
arranger.place(0, 0, shape_arr)
|
|
|
|
# If a build volume was set, add the disallowed areas
|
|
if Arrange.build_volume:
|
|
disallowed_areas = Arrange.build_volume.getDisallowedAreasNoBrim()
|
|
for area in disallowed_areas:
|
|
points = copy.deepcopy(area._points)
|
|
shape_arr = ShapeArray.fromPolygon(points, scale = scale)
|
|
arranger.place(0, 0, shape_arr, update_empty = False)
|
|
return arranger
|
|
|
|
def resetLastPriority(self):
|
|
"""This resets the optimization for finding location based on size"""
|
|
|
|
self._last_priority = 0
|
|
|
|
@deprecated("Use the functions in Nest2dArrange instead", "4.8")
|
|
def findNodePlacement(self, node: SceneNode, offset_shape_arr: ShapeArray, hull_shape_arr: ShapeArray, step = 1) -> bool:
|
|
"""Find placement for a node (using offset shape) and place it (using hull shape)
|
|
|
|
:param node: The node to be placed
|
|
:param offset_shape_arr: shape array with offset, for placing the shape
|
|
:param hull_shape_arr: shape array without offset, used to find location
|
|
:param step: default = 1
|
|
:return: the nodes that should be placed
|
|
"""
|
|
|
|
best_spot = self.bestSpot(
|
|
hull_shape_arr, start_prio = self._last_priority, step = step)
|
|
x, y = best_spot.x, best_spot.y
|
|
|
|
# Save the last priority.
|
|
self._last_priority = best_spot.priority
|
|
|
|
# Ensure that the object is above the build platform
|
|
node.removeDecorator(ZOffsetDecorator.ZOffsetDecorator)
|
|
bbox = node.getBoundingBox()
|
|
if bbox:
|
|
center_y = node.getWorldPosition().y - bbox.bottom
|
|
else:
|
|
center_y = 0
|
|
|
|
if x is not None: # We could find a place
|
|
node.setPosition(Vector(x, center_y, y))
|
|
found_spot = True
|
|
self.place(x, y, offset_shape_arr) # place the object in arranger
|
|
else:
|
|
Logger.log("d", "Could not find spot!")
|
|
found_spot = False
|
|
node.setPosition(Vector(200, center_y, 100))
|
|
return found_spot
|
|
|
|
def centerFirst(self):
|
|
"""Fill priority, center is best. Lower value is better. """
|
|
|
|
# Square distance: creates a more round shape
|
|
self._priority = numpy.fromfunction(
|
|
lambda j, i: (self._offset_x - i) ** 2 + (self._offset_y - j) ** 2, self._shape, dtype=numpy.int32)
|
|
self._priority_unique_values = numpy.unique(self._priority)
|
|
self._priority_unique_values.sort()
|
|
|
|
def backFirst(self):
|
|
"""Fill priority, back is best. Lower value is better """
|
|
|
|
self._priority = numpy.fromfunction(
|
|
lambda j, i: 10 * j + abs(self._offset_x - i), self._shape, dtype=numpy.int32)
|
|
self._priority_unique_values = numpy.unique(self._priority)
|
|
self._priority_unique_values.sort()
|
|
|
|
def checkShape(self, x, y, shape_arr) -> Optional[numpy.ndarray]:
|
|
"""Return the amount of "penalty points" for polygon, which is the sum of priority
|
|
|
|
:param x: x-coordinate to check shape
|
|
:param y: y-coordinate to check shape
|
|
:param shape_arr: the shape array object to place
|
|
:return: None if occupied
|
|
"""
|
|
|
|
x = int(self._scale * x)
|
|
y = int(self._scale * y)
|
|
offset_x = x + self._offset_x + shape_arr.offset_x
|
|
offset_y = y + self._offset_y + shape_arr.offset_y
|
|
if offset_x < 0 or offset_y < 0:
|
|
return None # out of bounds in self._occupied
|
|
occupied_x_max = offset_x + shape_arr.arr.shape[1]
|
|
occupied_y_max = offset_y + shape_arr.arr.shape[0]
|
|
if occupied_x_max > self._occupied.shape[1] + 1 or occupied_y_max > self._occupied.shape[0] + 1:
|
|
return None # out of bounds in self._occupied
|
|
occupied_slice = self._occupied[
|
|
offset_y:occupied_y_max,
|
|
offset_x:occupied_x_max]
|
|
try:
|
|
if numpy.any(occupied_slice[numpy.where(shape_arr.arr == 1)]):
|
|
return None
|
|
except IndexError: # out of bounds if you try to place an object outside
|
|
return None
|
|
prio_slice = self._priority[
|
|
offset_y:offset_y + shape_arr.arr.shape[0],
|
|
offset_x:offset_x + shape_arr.arr.shape[1]]
|
|
return numpy.sum(prio_slice[numpy.where(shape_arr.arr == 1)])
|
|
|
|
def bestSpot(self, shape_arr, start_prio = 0, step = 1) -> LocationSuggestion:
|
|
"""Find "best" spot for ShapeArray
|
|
|
|
:param shape_arr: shape array
|
|
:param start_prio: Start with this priority value (and skip the ones before)
|
|
:param step: Slicing value, higher = more skips = faster but less accurate
|
|
:return: namedtuple with properties x, y, penalty_points, priority.
|
|
"""
|
|
|
|
start_idx_list = numpy.where(self._priority_unique_values == start_prio)
|
|
if start_idx_list:
|
|
try:
|
|
start_idx = start_idx_list[0][0]
|
|
except IndexError:
|
|
start_idx = 0
|
|
else:
|
|
start_idx = 0
|
|
priority = 0
|
|
for priority in self._priority_unique_values[start_idx::step]:
|
|
tryout_idx = numpy.where(self._priority == priority)
|
|
for idx in range(len(tryout_idx[0])):
|
|
x = tryout_idx[1][idx]
|
|
y = tryout_idx[0][idx]
|
|
projected_x = int((x - self._offset_x) / self._scale)
|
|
projected_y = int((y - self._offset_y) / self._scale)
|
|
|
|
penalty_points = self.checkShape(projected_x, projected_y, shape_arr)
|
|
if penalty_points is not None:
|
|
return LocationSuggestion(x = projected_x, y = projected_y, penalty_points = penalty_points, priority = priority)
|
|
return LocationSuggestion(x = None, y = None, penalty_points = None, priority = priority) # No suitable location found :-(
|
|
|
|
def place(self, x, y, shape_arr, update_empty = True):
|
|
"""Place the object.
|
|
|
|
Marks the locations in self._occupied and self._priority
|
|
|
|
:param x:
|
|
:param y:
|
|
:param shape_arr:
|
|
:param update_empty: updates the _is_empty, used when adding disallowed areas
|
|
"""
|
|
|
|
x = int(self._scale * x)
|
|
y = int(self._scale * y)
|
|
offset_x = x + self._offset_x + shape_arr.offset_x
|
|
offset_y = y + self._offset_y + shape_arr.offset_y
|
|
shape_y, shape_x = self._occupied.shape
|
|
|
|
min_x = min(max(offset_x, 0), shape_x - 1)
|
|
min_y = min(max(offset_y, 0), shape_y - 1)
|
|
max_x = min(max(offset_x + shape_arr.arr.shape[1], 0), shape_x - 1)
|
|
max_y = min(max(offset_y + shape_arr.arr.shape[0], 0), shape_y - 1)
|
|
occupied_slice = self._occupied[min_y:max_y, min_x:max_x]
|
|
# we use a slice of shape because it can be out of bounds
|
|
new_occupied = numpy.where(shape_arr.arr[
|
|
min_y - offset_y:max_y - offset_y, min_x - offset_x:max_x - offset_x] == 1)
|
|
if update_empty and new_occupied:
|
|
self._is_empty = False
|
|
occupied_slice[new_occupied] = 1
|
|
|
|
# Set priority to low (= high number), so it won't get picked at trying out.
|
|
prio_slice = self._priority[min_y:max_y, min_x:max_x]
|
|
prio_slice[new_occupied] = 999
|
|
|
|
@property
|
|
def isEmpty(self):
|
|
return self._is_empty
|