diff options
author | Jack Ha <j.ha@ultimaker.com> | 2017-03-29 10:32:29 +0300 |
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committer | Jack Ha <j.ha@ultimaker.com> | 2017-03-29 10:32:29 +0300 |
commit | f357dea086682e8b249d03105e386ab93c63e31c (patch) | |
tree | c13cdaf197503981bbd96ceee0e60ad9cd737773 /cura/Arrange.py | |
parent | bf08d30e7dc9a9fdd8f83db80d35cb1461bbb6f5 (diff) |
Tuned arranger a bit, good enough for proof of concept. CURA-3239
Diffstat (limited to 'cura/Arrange.py')
-rwxr-xr-x | cura/Arrange.py | 38 |
1 files changed, 15 insertions, 23 deletions
diff --git a/cura/Arrange.py b/cura/Arrange.py index d1f166ef87..db6a7c781e 100755 --- a/cura/Arrange.py +++ b/cura/Arrange.py @@ -12,20 +12,17 @@ class ShapeArray: def from_polygon(cls, vertices, scale = 1): # scale vertices = vertices * scale - # flip x, y + # flip y, x -> x, y flip_vertices = np.zeros((vertices.shape)) flip_vertices[:, 0] = vertices[:, 1] flip_vertices[:, 1] = vertices[:, 0] flip_vertices = flip_vertices[::-1] - # offset + # offset, we want that all coordinates have positive values offset_y = int(np.amin(flip_vertices[:, 0])) offset_x = int(np.amin(flip_vertices[:, 1])) - # offset to 0 flip_vertices[:, 0] = np.add(flip_vertices[:, 0], -offset_y) flip_vertices[:, 1] = np.add(flip_vertices[:, 1], -offset_x) shape = [int(np.amax(flip_vertices[:, 0])), int(np.amax(flip_vertices[:, 1]))] - #from UM.Logger import Logger - #Logger.log("d", " Vertices: %s" % str(flip_vertices)) arr = cls.array_from_polygon(shape, flip_vertices) return cls(arr, offset_x, offset_y) @@ -85,6 +82,7 @@ class Arrange: def __init__(self, x, y, offset_x, offset_y, scale=1): self.shape = (y, x) self._priority = np.zeros((x, y), dtype=np.int32) + self._priority_unique_values = [] self._occupied = np.zeros((x, y), dtype=np.int32) self._scale = scale # convert input coordinates to arrange coordinates self._offset_x = offset_x @@ -92,8 +90,12 @@ class Arrange: ## Fill priority, take offset as center. lower is better def centerFirst(self): + #self._priority = np.fromfunction( + # lambda i, j: abs(self._offset_x-i)+abs(self._offset_y-j), self.shape) self._priority = np.fromfunction( - lambda i, j: abs(self._offset_x-i)+abs(self._offset_y-j), self.shape) + lambda i, j: abs(self._offset_x-i)**2+abs(self._offset_y-j)**2, self.shape, dtype=np.int32) + self._priority_unique_values = np.unique(self._priority) + self._priority_unique_values.sort() ## Return the amount of "penalty points" for polygon, which is the sum of priority # 999999 if occupied @@ -115,24 +117,14 @@ class Arrange: offset_x:offset_x + shape_arr.arr.shape[1]] return np.sum(prio_slice[np.where(shape_arr.arr == 1)]) - ## Slower but better (it tries all possible locations) - def bestSpot2(self, shape_arr): - best_x, best_y, best_points = None, None, None - min_y = max(-shape_arr.offset_y, 0) - self._offset_y - max_y = self.shape[0] - shape_arr.arr.shape[0] - self._offset_y - min_x = max(-shape_arr.offset_x, 0) - self._offset_x - max_x = self.shape[1] - shape_arr.arr.shape[1] - self._offset_x - for y in range(min_y, max_y): - for x in range(min_x, max_x): - penalty_points = self.check_shape(x, y, shape_arr) - if best_points is None or penalty_points < best_points: - best_points = penalty_points - best_x, best_y = x, y - return best_x, best_y, best_points - - ## Faster + ## Find "best" spot def bestSpot(self, shape_arr, start_prio = 0): - for prio in range(start_prio, 300): + start_idx_list = np.where(self._priority_unique_values == start_prio) + if start_idx_list: + start_idx = start_idx_list[0] + else: + start_idx = 0 + for prio in self._priority_unique_values[start_idx:]: tryout_idx = np.where(self._priority == prio) for idx in range(len(tryout_idx[0])): x = tryout_idx[0][idx] |