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Running on Zero
Running on Zero
| """The parcellation's pure-numpy pieces: the node table (84 nodes, 14 lobar groups), the majority vote and the | |
| derived labels / stop mask. No SynthSeg, no TensorFlow, no download -- everything here is synthetic and fast.""" | |
| import numpy as np | |
| import pytest | |
| from tools import build_parcellation as BP | |
| def test_node_table_has_84_nodes_and_14_lobar_groups(): | |
| nodes = BP.node_table() | |
| assert len(nodes) == 84 | |
| assert len(set(n["id"] for n in nodes)) == 84 | |
| assert set(n["id"] for n in nodes) == set(range(1, 85)) | |
| left = [n for n in nodes if n["hemisphere"] == "left"] | |
| right = [n for n in nodes if n["hemisphere"] == "right"] | |
| assert len(left) == 42 and len(right) == 42 | |
| cortical = [n for n in nodes if n["lobe"] != "subcortical"] | |
| subcortical = [n for n in nodes if n["lobe"] == "subcortical"] | |
| assert len(cortical) == 68 and len(subcortical) == 16 | |
| regions = BP.regions_payload() | |
| groups = regions["lobes"] | |
| assert len(groups) == 14 and len(set(groups)) == 14 | |
| for lobe in BP.LOBES: | |
| assert f"{lobe}-left" in groups and f"{lobe}-right" in groups | |
| def test_node_table_ids_are_unique_per_fs_label_and_hemisphere(): | |
| nodes = BP.node_table() | |
| keys = [(n["fs_label"], n["hemisphere"]) for n in nodes] | |
| assert len(set(keys)) == len(keys) | |
| def test_supersampled_affine_centres_subvoxels_within_the_parent_voxel(): | |
| ref_affine = np.array([[2.5, 0, 0, 10.0], [0, 2.5, 0, -5.0], [0, 0, 2.5, 3.0], [0, 0, 0, 1]]) | |
| for factor in (1, 2, 4, 5): | |
| sup = BP._supersampled_affine(ref_affine, factor) | |
| # the mean of the factor**3 sub-voxel centres of parent voxel (2, 1, 0) must equal that parent's own centre | |
| idx = np.arange(factor) | |
| grid = np.stack(np.meshgrid(idx, idx, idx, indexing="ij"), axis=-1).reshape(-1, 3) | |
| sub_index = np.array([2, 1, 0]) * factor + grid | |
| world = sub_index @ sup[:3, :3].T + sup[:3, 3] | |
| parent_world = ref_affine[:3, :3] @ [2, 1, 0] + ref_affine[:3, 3] | |
| np.testing.assert_allclose(world.mean(axis=0), parent_world, atol=1e-9) | |
| def test_majority_vote_picks_the_plurality_label_under_identity_registration(): | |
| # a tiny "T1" label volume at 1 mm, two blocks of 3x3x3 mostly-9 voxels with a 2-voxel minority, at the origin; | |
| # the "diffusion" grid is 3x coarser (3 mm) and exactly covers one combined super-voxel. | |
| seg = np.full((3, 3, 3), 9, dtype=np.int32) | |
| seg[0, 0, 0] = 5 | |
| seg[0, 0, 1] = 5 | |
| seg_affine = np.eye(4) | |
| ref_affine = np.diag([3.0, 3.0, 3.0, 1.0]) | |
| ref_affine[:3, 3] = 1.0 # the single ref voxel's centre sits at the seg block's centre | |
| majority = BP.majority_vote(seg, seg_affine, (1, 1, 1), ref_affine, np.eye(4), factor=3) | |
| assert majority.shape == (1, 1, 1) | |
| assert majority[0, 0, 0] == 9 # 25 votes for 9 against 2 for 5 | |
| def test_labels_and_stop_mask_from_majority_labels(): | |
| majority = np.array([[[0, 2, 1001]]]) # background, left cerebral WM, left bankssts | |
| labels, stop = BP.labels_and_stop_mask(majority) | |
| assert labels[0, 0, 0] == 0 | |
| assert labels[0, 0, 2] == 1 # bankssts is fs id 1001, the first (lowest) left-hemisphere node | |
| assert stop.tolist() == [[[False, True, False]]] | |
| def test_label_volumes_mm3(): | |
| labels = np.array([0, 0, 1, 1, 1, 2], dtype=np.int16) | |
| vols = BP.label_volumes_mm3(labels, voxel_volume_mm3=8.0) | |
| assert vols == {1: 24.0, 2: 8.0} | |
| def test_every_cortical_name_has_a_lobe(): | |
| assert set(BP.LOBE_OF_CORTICAL) == set(BP.CORTICAL_NAMES.values()) | |
| assert set(BP.LOBE_OF_CORTICAL.values()) <= set(BP.LOBES) | |