Add tests and implement boundary smoothing and cutout functionality

- Introduced tests for boundary smoothing in `test_boundary_smoothing.py`, verifying that smoothing reduces stair-step artifacts while preserving boundary integrity.
- Added tests for cutout boundary behavior in `test_cutout_boundary.py`, ensuring proper handling of boundary triangles and normal blending.
- Created `test_temporary_attributes.py` to check the cleanup of temporary attributes across depth modifier branches, ensuring no warnings are raised.
- Implemented point culling functionality in `test_validity.py`, confirming that invalid points are removed without affecting adjacent geometry.
- Developed boundary smoothing logic in `boundary_smoothing.py`, allowing for depth smoothing while maintaining edge integrity.
- Added cutout boundary management in `cutout_boundary.py`, including functions for removing boundary triangles and tapering thickness profiles.
- Implemented validity checks in `validity.py` to ensure proper deletion of invalid vertices and associated wire edges.
This commit is contained in:
2026-09-11 20:37:20 +08:00
parent e8129fe495
commit 31074bd511
85 changed files with 2501 additions and 1451 deletions

View File

@@ -26,6 +26,17 @@ def test_new_cutout_does_not_reuse_a_saved_wrapper():
assert any(item.name == "Shape" for item in saved.interface.items_tree)
def test_depth_cutout_loads_boundary_blur_revision_and_preserves_existing_group():
bpy.ops.wm.read_factory_settings(use_empty=True)
saved = bpy.data.node_groups.new("O Image Depth Cutout", "GeometryNodeTree")
saved["anyimage_asset_revision"] = 11
current = load_cutout_node_group("DEPTH_SOLID")
assert current != saved and current["anyimage_asset_revision"] == 18
assert saved in bpy.data.node_groups.values()
assert saved["anyimage_asset_revision"] == 11
assert load_cutout_node_group("DEPTH_SOLID") == current
def test_refined_boundary_ears_have_interior_balloon_samples():
points = np.array([(0, 0), (1, 0), (1, 1), (0, 1)], dtype=float)
points, faces, boundary = refine_balloon_triangles(points, [(0, 1, 2), (0, 2, 3)], np.ones(4, bool))