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https://git.mirrors.martin98.com/https://github.com/Ultimaker/Cura
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348 lines
17 KiB
Python
348 lines
17 KiB
Python
import math
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from typing import List, TYPE_CHECKING, Tuple, Set, Union
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if TYPE_CHECKING:
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from UM.Scene.SceneNode import SceneNode
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from cura.BuildVolume import BuildVolume
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from UM.Application import Application
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from UM.Math.AxisAlignedBox import AxisAlignedBox
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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.Operations.AddSceneNodeOperation import AddSceneNodeOperation
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from UM.Operations.GroupedOperation import GroupedOperation
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from UM.Operations.TranslateOperation import TranslateOperation
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from cura.Arranging.Arranger import Arranger
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class GridArrange(Arranger):
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def __init__(self, nodes_to_arrange: List["SceneNode"], build_volume: "BuildVolume", fixed_nodes: List["SceneNode"] = None):
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if fixed_nodes is None:
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fixed_nodes = []
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self._nodes_to_arrange = nodes_to_arrange
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self._build_volume = build_volume
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self._build_volume_bounding_box = build_volume.getBoundingBox()
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self._fixed_nodes = fixed_nodes
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self._margin_x: float = 1
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self._margin_y: float = 1
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self._grid_width = 0
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self._grid_height = 0
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for node in self._nodes_to_arrange:
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bounding_box = node.getBoundingBox()
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self._grid_width = max(self._grid_width, bounding_box.width)
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self._grid_height = max(self._grid_height, bounding_box.depth)
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self._grid_width += self._margin_x
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self._grid_height += self._margin_y
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# Round up the grid size to the nearest cm, this assures that new objects will
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# be placed on integer offsets from each other
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grid_precision = 10 # 1cm
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rounded_grid_width = math.ceil(self._grid_width / grid_precision) * grid_precision
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rounded_grid_height = math.ceil(self._grid_height / grid_precision) * grid_precision
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# The space added by the "grid precision rounding up" of the grid size
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self._grid_round_margin_x = rounded_grid_width - self._grid_width
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self._grid_round_margin_y = rounded_grid_height - self._grid_height
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self._grid_width = rounded_grid_width
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self._grid_height = rounded_grid_height
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self._offset_x = 0
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self._offset_y = 0
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self._findOptimalGridOffset()
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coord_initial_leftover_x = self._build_volume_bounding_box.right + 2 * self._grid_width
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coord_initial_leftover_y = (self._build_volume_bounding_box.back + self._build_volume_bounding_box.front) * 0.5
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self._initial_leftover_grid_x, self._initial_leftover_grid_y = self._coordSpaceToGridSpace(
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coord_initial_leftover_x, coord_initial_leftover_y)
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self._initial_leftover_grid_x = math.floor(self._initial_leftover_grid_x)
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self._initial_leftover_grid_y = math.floor(self._initial_leftover_grid_y)
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# Find grid indexes that intersect with fixed objects
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self._fixed_nodes_grid_ids = set()
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for node in self._fixed_nodes:
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self._fixed_nodes_grid_ids = self._fixed_nodes_grid_ids.union(
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self._intersectingGridIdxInclusive(node.getBoundingBox()))
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# grid indexes that are in disallowed area
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for polygon in self._build_volume.getDisallowedAreas():
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self._fixed_nodes_grid_ids = self._fixed_nodes_grid_ids.union(self._intersectingGridIdxInclusive(polygon))
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self._build_plate_grid_ids = self._intersectingGridIdxExclusive(self._build_volume_bounding_box)
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# Filter out the corner grid squares if the build plate shape is elliptic
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if self._build_volume.getShape() == "elliptic":
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self._build_plate_grid_ids = set(
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filter(lambda grid_id: self._checkGridUnderDiscSpace(grid_id[0], grid_id[1]),
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self._build_plate_grid_ids))
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self._allowed_grid_idx = self._build_plate_grid_ids.difference(self._fixed_nodes_grid_ids)
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def createGroupOperationForArrange(self, add_new_nodes_in_scene: bool = False) -> Tuple[GroupedOperation, int]:
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# Find the sequence in which items are placed
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coord_build_plate_center_x = self._build_volume_bounding_box.width * 0.5 + self._build_volume_bounding_box.left
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coord_build_plate_center_y = self._build_volume_bounding_box.depth * 0.5 + self._build_volume_bounding_box.back
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grid_build_plate_center_x, grid_build_plate_center_y = self._coordSpaceToGridSpace(coord_build_plate_center_x,
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coord_build_plate_center_y)
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sequence: List[Tuple[int, int]] = list(self._allowed_grid_idx)
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sequence.sort(key=lambda grid_id: (grid_build_plate_center_x - grid_id[0]) ** 2 + (
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grid_build_plate_center_y - grid_id[1]) ** 2)
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scene_root = Application.getInstance().getController().getScene().getRoot()
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grouped_operation = GroupedOperation()
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for grid_id, node in zip(sequence, self._nodes_to_arrange):
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if add_new_nodes_in_scene:
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grouped_operation.addOperation(AddSceneNodeOperation(node, scene_root))
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grid_x, grid_y = grid_id
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operation = self._moveNodeOnGrid(node, grid_x, grid_y)
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grouped_operation.addOperation(operation)
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leftover_nodes = self._nodes_to_arrange[len(sequence):]
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left_over_grid_y = self._initial_leftover_grid_y
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for node in leftover_nodes:
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if add_new_nodes_in_scene:
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grouped_operation.addOperation(AddSceneNodeOperation(node, scene_root))
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# find the first next grid position that isn't occupied by a fixed node
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while (self._initial_leftover_grid_x, left_over_grid_y) in self._fixed_nodes_grid_ids:
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left_over_grid_y = left_over_grid_y - 1
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operation = self._moveNodeOnGrid(node, self._initial_leftover_grid_x, left_over_grid_y)
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grouped_operation.addOperation(operation)
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left_over_grid_y = left_over_grid_y - 1
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return grouped_operation, len(leftover_nodes)
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def _findOptimalGridOffset(self):
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if len(self._fixed_nodes) == 0:
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self._offset_x = 0
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self._offset_y = 0
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return
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if len(self._fixed_nodes) == 1:
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center_grid_x = 0.5 * self._grid_width + self._build_volume_bounding_box.left
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center_grid_y = 0.5 * self._grid_height + self._build_volume_bounding_box.back
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bounding_box = self._fixed_nodes[0].getBoundingBox()
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center_node_x = (bounding_box.left + bounding_box.right) * 0.5
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center_node_y = (bounding_box.back + bounding_box.front) * 0.5
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self._offset_x = center_node_x - center_grid_x
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self._offset_y = center_node_y - center_grid_y
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return
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# If there are multiple fixed nodes, an optimal solution is not always possible
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# We will try to find an offset that minimizes the number of grid intersections
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# with fixed nodes. The algorithm below achieves this by utilizing a scanline
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# algorithm. In this algorithm each axis is solved separately as offsetting
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# is completely independent in each axis. The comments explaining the algorithm
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# below are for the x-axis, but the same applies for the y-axis.
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#
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# Each node either occupies ceil((node.right - node.right) / grid_width) or
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# ceil((node.right - node.right) / grid_width) + 1 grid squares. We will call
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# these the node's "footprint".
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#
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# ┌────────────────┐
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# minimum foot-print │ NODE │
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# └────────────────┘
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# │ grid 1 │ grid 2 │ grid 3 │ grid 4 | grid 5 |
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# ┌────────────────┐
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# maximum foot-print │ NODE │
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# └────────────────┘
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#
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# The algorithm will find the grid offset such that the number of nodes with
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# a _minimal_ footprint is _maximized_.
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# The scanline algorithm works as follows, we create events for both end points
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# of each node's footprint. The event have two properties,
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# - the coordinate: the amount the endpoint can move to the
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# left before it crosses a grid line
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# - the change: either +1 or -1, indicating whether crossing the grid line
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# would result in a minimal footprint node becoming a maximal footprint
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class Event:
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def __init__(self, coord: float, change: float):
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self.coord = coord
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self.change = change
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# create events for both the horizontal and vertical axis
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events_horizontal: List[Event] = []
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events_vertical: List[Event] = []
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for node in self._fixed_nodes:
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bounding_box = node.getBoundingBox()
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left = bounding_box.left - self._build_volume_bounding_box.left
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right = bounding_box.right - self._build_volume_bounding_box.left
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back = bounding_box.back - self._build_volume_bounding_box.back
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front = bounding_box.front - self._build_volume_bounding_box.back
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value_left = math.ceil(left / self._grid_width) * self._grid_width - left
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value_right = math.ceil(right / self._grid_width) * self._grid_width - right
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value_back = math.ceil(back / self._grid_height) * self._grid_height - back
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value_front = math.ceil(front / self._grid_height) * self._grid_height - front
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# give nodes a weight according to their size. This
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# weight is heuristically chosen to be proportional to
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# the number of grid squares the node-boundary occupies
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weight = bounding_box.width + bounding_box.depth
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events_horizontal.append(Event(value_left, weight))
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events_horizontal.append(Event(value_right, -weight))
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events_vertical.append(Event(value_back, weight))
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events_vertical.append(Event(value_front, -weight))
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events_horizontal.sort(key=lambda event: event.coord)
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events_vertical.sort(key=lambda event: event.coord)
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def findOptimalShiftAxis(events: List[Event], interval: float) -> float:
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# executing the actual scanline algorithm
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# iteratively go through events (left to right) and keep track of the
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# current footprint. The optimal location is the one with the minimal
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# footprint. If there are multiple locations with the same minimal
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# footprint, the optimal location is the one with the largest range
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# between the left and right endpoint of the footprint.
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prev_offset = events[-1].coord - interval
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current_minimal_footprint_count = 0
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best_minimal_footprint_count = float('inf')
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best_offset_span = float('-inf')
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best_offset = 0.0
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for event in events:
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offset_span = event.coord - prev_offset
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if current_minimal_footprint_count < best_minimal_footprint_count or (
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current_minimal_footprint_count == best_minimal_footprint_count and offset_span > best_offset_span):
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best_minimal_footprint_count = current_minimal_footprint_count
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best_offset_span = offset_span
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best_offset = event.coord
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current_minimal_footprint_count += event.change
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prev_offset = event.coord
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return best_offset - best_offset_span * 0.5
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center_grid_x = 0.5 * self._grid_width
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center_grid_y = 0.5 * self._grid_height
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optimal_center_x = self._grid_width - findOptimalShiftAxis(events_horizontal, self._grid_width)
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optimal_center_y = self._grid_height - findOptimalShiftAxis(events_vertical, self._grid_height)
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self._offset_x = optimal_center_x - center_grid_x
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self._offset_y = optimal_center_y - center_grid_y
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def _moveNodeOnGrid(self, node: "SceneNode", grid_x: int, grid_y: int) -> "Operation.Operation":
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coord_grid_x, coord_grid_y = self._gridSpaceToCoordSpace(grid_x, grid_y)
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center_grid_x = coord_grid_x + (0.5 * self._grid_width)
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center_grid_y = coord_grid_y + (0.5 * self._grid_height)
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bounding_box = node.getBoundingBox()
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center_node_x = (bounding_box.left + bounding_box.right) * 0.5
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center_node_y = (bounding_box.back + bounding_box.front) * 0.5
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delta_x = center_grid_x - center_node_x
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delta_y = center_grid_y - center_node_y
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return TranslateOperation(node, Vector(delta_x, 0, delta_y))
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def _getGridCornerPoints(
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self,
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bounds: Union[AxisAlignedBox, Polygon],
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*,
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margin_x: float = 0.0,
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margin_y: float = 0.0
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) -> Tuple[float, float, float, float]:
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if isinstance(bounds, AxisAlignedBox):
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coord_x1 = bounds.left - margin_x
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coord_x2 = bounds.right + margin_x
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coord_y1 = bounds.back - margin_y
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coord_y2 = bounds.front + margin_y
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elif isinstance(bounds, Polygon):
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coord_x1 = float('inf')
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coord_y1 = float('inf')
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coord_x2 = float('-inf')
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coord_y2 = float('-inf')
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for x, y in bounds.getPoints():
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coord_x1 = min(coord_x1, x)
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coord_y1 = min(coord_y1, y)
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coord_x2 = max(coord_x2, x)
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coord_y2 = max(coord_y2, y)
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else:
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raise TypeError("bounds must be either an AxisAlignedBox or a Polygon")
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coord_x1 -= margin_x
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coord_x2 += margin_x
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coord_y1 -= margin_y
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coord_y2 += margin_y
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grid_x1, grid_y1 = self._coordSpaceToGridSpace(coord_x1, coord_y1)
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grid_x2, grid_y2 = self._coordSpaceToGridSpace(coord_x2, coord_y2)
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return grid_x1, grid_y1, grid_x2, grid_y2
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def _intersectingGridIdxInclusive(self, bounds: Union[AxisAlignedBox, Polygon]) -> Set[Tuple[int, int]]:
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grid_x1, grid_y1, grid_x2, grid_y2 = self._getGridCornerPoints(
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bounds,
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margin_x=-(self._margin_x + self._grid_round_margin_x) * 0.5,
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margin_y=-(self._margin_y + self._grid_round_margin_y) * 0.5,
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)
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grid_idx = set()
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for grid_x in range(math.floor(grid_x1), math.ceil(grid_x2)):
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for grid_y in range(math.floor(grid_y1), math.ceil(grid_y2)):
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grid_idx.add((grid_x, grid_y))
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return grid_idx
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def _intersectingGridIdxExclusive(self, bounds: Union[AxisAlignedBox, Polygon]) -> Set[Tuple[int, int]]:
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grid_x1, grid_y1, grid_x2, grid_y2 = self._getGridCornerPoints(
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bounds,
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margin_x=(self._margin_x + self._grid_round_margin_x) * 0.5,
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margin_y=(self._margin_y + self._grid_round_margin_y) * 0.5,
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)
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grid_idx = set()
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for grid_x in range(math.ceil(grid_x1), math.floor(grid_x2)):
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for grid_y in range(math.ceil(grid_y1), math.floor(grid_y2)):
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grid_idx.add((grid_x, grid_y))
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return grid_idx
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def _gridSpaceToCoordSpace(self, x: float, y: float) -> Tuple[float, float]:
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grid_x = x * self._grid_width + self._build_volume_bounding_box.left + self._offset_x
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grid_y = y * self._grid_height + self._build_volume_bounding_box.back + self._offset_y
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return grid_x, grid_y
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def _coordSpaceToGridSpace(self, grid_x: float, grid_y: float) -> Tuple[float, float]:
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coord_x = (grid_x - self._build_volume_bounding_box.left - self._offset_x) / self._grid_width
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coord_y = (grid_y - self._build_volume_bounding_box.back - self._offset_y) / self._grid_height
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return coord_x, coord_y
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def _checkGridUnderDiscSpace(self, grid_x: int, grid_y: int) -> bool:
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left, back = self._gridSpaceToCoordSpace(grid_x, grid_y)
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right, front = self._gridSpaceToCoordSpace(grid_x + 1, grid_y + 1)
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corners = [(left, back), (right, back), (right, front), (left, front)]
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return all([self._checkPointUnderDiscSpace(x, y) for x, y in corners])
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def _checkPointUnderDiscSpace(self, x: float, y: float) -> bool:
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disc_x, disc_y = self._coordSpaceToDiscSpace(x, y)
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distance_to_center_squared = disc_x ** 2 + disc_y ** 2
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return distance_to_center_squared <= 1.0
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def _coordSpaceToDiscSpace(self, x: float, y: float) -> Tuple[float, float]:
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# Transform coordinate system to
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#
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# coord_build_plate_left = -1
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# | coord_build_plate_right = 1
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# v (0,1) v
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# ┌───────┬───────┐ < coord_build_plate_back = -1
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# │ │ │
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# │ │(0,0) │
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# (-1,0)├───────o───────┤(1,0)
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# │ │ │
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# │ │ │
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# └───────┴───────┘ < coord_build_plate_front = +1
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# (0,-1)
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disc_x = ((x - self._build_volume_bounding_box.left) / self._build_volume_bounding_box.width) * 2.0 - 1.0
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disc_y = ((y - self._build_volume_bounding_box.back) / self._build_volume_bounding_box.depth) * 2.0 - 1.0
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return disc_x, disc_y
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