def test_get_closest_vertex_to_vertex_0_coordinate():
try:
from scipy.spatial.distance import cdist
except ImportError:
pytest.skip("Optional dependency scipy not installed, skipping tests which require scipy.")
vert_coords, faces, _ = bl.subject_mesh('subject1', TEST_DATA_DIR, surf='white', hemi='both')
locator = loc.BrainLocate(vert_coords, faces)
known_vertex_0_coord = (-1.85223234, -107.98274994, 22.76972961) # coordinate for vertex 0 in the test data.
assert_allclose(vert_coords[0], np.array(known_vertex_0_coord))
query_coords = np.array([known_vertex_0_coord])
res = locator.get_closest_vertex_and_distance(query_coords)
assert res.shape == (1, 2)
assert res[0, 0] == 0 # vertex index of closest vertex. The query coordinate is the known coordinate of vertex 0, so this must be 0.
assert abs(res[0, 1]) <= 0.001 # distance to closest vertex. The query coordinate is the known coordinate of vertex 0, so this must be very close to 0.0
def test_vertices_to_label():
vert_coords, faces, meta_data = bl.subject_mesh('subject1',
TEST_DATA_DIR,
surf='white',
hemi='both')
selected_vert_indices = [0, 1, 2, 4]
label_str = an.vertices_to_label(selected_vert_indices, vert_coords)
expected = """#!ascii label
4
0 -1.852232 -107.982750 22.769730 0.0000000000
1 -2.139076 -108.102333 22.826056 0.0000000000
2 -3.120585 -108.130928 22.830750 0.0000000000
4 -4.798367 -108.059784 22.777563 0.0000000000"""
assert label_str == expected
def test_closest_vertex_to_very_close_point():
try:
from scipy.spatial.distance import cdist
except ImportError:
pytest.skip("Optional dependency scipy not installed, skipping tests which require scipy.")
vert_coords, faces, _ = bl.subject_mesh('subject1', TEST_DATA_DIR, surf='white', hemi='both')
locator = loc.BrainLocate(vert_coords, faces)
query_coords = np.array([[58.0 , -45.0, 75.0]])
res = locator.get_closest_vertex(query_coords)
assert res.shape == (1, )
assert res[0] == 210683 # the vertex index in the mesh
expected_vert_210683_coords = (58.005173, -44.736935, 74.418076)
assert_allclose(vert_coords[210683], np.array(expected_vert_210683_coords))
dist = cdist(np.array([expected_vert_210683_coords]), query_coords)
assert dist[0][0] == pytest.approx(0.6386434810831467, 0.001)
def test_get_closest_vertex_and_distance_to_far_away_point():
try:
from scipy.spatial.distance import cdist
except ImportError:
pytest.skip("Optional dependency scipy not installed, skipping tests which require scipy.")
vert_coords, faces, _ = bl.subject_mesh('subject1', TEST_DATA_DIR, surf='white', hemi='both')
locator = loc.BrainLocate(vert_coords, faces)
query_coords = np.array([[134.37332 , -57.259495, 149.267631], [134.37332 , -57.259495, 149.267631], [134.37332 , -57.259495, 149.267631]]) # just query 3 times for the same coord to see whether results and consistent
res = locator.get_closest_vertex_and_distance(query_coords)
assert res.shape == (3, 2)
assert res[0,0] == 209519 # the vertex index in the mesh
assert res[1,0] == 209519
assert res[2,0] == 209519
assert res[0,1] == 107.47776120258028 # the distance
assert res[1,1] == 107.47776120258028
assert res[2,1] == 107.47776120258028
def test_closest_vertex_to_far_away_point():
try:
from scipy.spatial.distance import cdist
except ImportError:
pytest.skip("Optional dependency scipy not installed, skipping tests which require scipy.")
vert_coords, faces, _ = bl.subject_mesh('subject1', TEST_DATA_DIR, surf='white', hemi='both')
locator = loc.BrainLocate(vert_coords, faces)
query_coords = np.array([[134.37332 , -57.259495, 149.267631], [134.37332 , -57.259495, 149.267631], [58.0 , -45.0, 75.0]])
res = locator.get_closest_vertex(query_coords)
assert res.shape == (3, )
assert res[0] == 209519 # the vertex index in the mesh
assert res[1] == 209519
assert res[2] == 210683
assert_allclose(vert_coords[209519], np.array((58.258751, -45.213722, 74.348068)))
dist = cdist(np.array([[58.258751, -45.213722, 74.348068]]), np.array([[134.37332 , -57.259495, 149.267631]]))
assert dist[0][0] == pytest.approx(107.47776133, 0.001)
def test_surface_graph():
try:
import networkx as nx
import brainload.surfacegraph as sg
except ImportError:
pytest.skip(
"Optional dependency networkx not installed, skipping tests which require it."
)
vert_coords, faces, meta_data = bl.subject_mesh('subject1',
TEST_DATA_DIR,
surf='white',
hemi='lh')
surface_graph = sg.SurfaceGraph(vert_coords, faces)
g = surface_graph.graph
assert len(g) == SUBJECT1_SURF_LH_WHITE_NUM_VERTICES
assert g.number_of_nodes() == SUBJECT1_SURF_LH_WHITE_NUM_VERTICES
# now for some neighborhood queries
source_vertex = 100
neighbors_dist_1 = surface_graph.get_neighbors_up_to_dist(source_vertex, 1)
assert len(neighbors_dist_1) == 9
neighbors_dist_2 = surface_graph.get_neighbors_up_to_dist(source_vertex, 2)
assert len(neighbors_dist_2) == 25
neighbors_dist_3 = surface_graph.get_neighbors_up_to_dist(source_vertex, 3)
assert len(neighbors_dist_3) == 48