| import numpy as np | |
| import pytest | |
| import torch | |
| from hi3d_mac.fast_unique import unique_keys | |
| from hi3d_mac.lean_extract import construct_voxel_grid | |
| def test_unique_empty_keys_matches_numpy(counts): | |
| keys = np.empty(0, dtype=np.int64) | |
| values, inverse, observed_counts = unique_keys(keys, return_counts=counts) | |
| reference = np.unique(keys, return_inverse=True, return_counts=counts) | |
| np.testing.assert_array_equal(values, reference[0]) | |
| np.testing.assert_array_equal(inverse, reference[1]) | |
| if counts: | |
| np.testing.assert_array_equal(observed_counts, reference[2]) | |
| else: | |
| assert observed_counts is None | |
| def test_empty_voxel_grid_preserves_shapes_and_dtypes(): | |
| vertices, cubes = construct_voxel_grid(torch.empty((0, 3), dtype=torch.int32)) | |
| assert vertices.shape == (0, 3) and vertices.dtype == torch.int32 | |
| assert cubes.shape == (0, 8) and cubes.dtype == torch.int64 | |