def test_tubes_from_paths():
"""Tests that, given valid paths, valid tubes are created."""
sess = NeuroglancerSession(url, 0, url_seg)
img, bbox, verts = sess.pull_voxel(2, 300,
radius=5) # A valid bbox with data.
G_paths = sess.get_segments(2, bbox)
bbox = bbox.to_list()
paths = G_paths[1] # valid paths
size = np.subtract(bbox[3:], bbox[:3])
tubes = tube_seg.tubes_from_paths(size, paths)
assert (tubes != 0).any()
def test_tubes_from_paths_bad_inputs():
"""Tests that the tubes_from_paths method raises errors when given bad inputs."""
sess = NeuroglancerSession(url, 0, url_seg)
img, bbox, verts = sess.pull_voxel(2, 300,
radius=5) # A valid bbox with data.
G_paths = sess.get_segments(2, bbox)
G = G_paths[0]
paths = G_paths[1] # valid paths
bbox = bbox.to_list()
size = np.subtract(bbox[3:], bbox[:3])
with pytest.raises(TypeError):
tube_seg.tubes_from_paths("asdf", paths)
with pytest.raises(ValueError):
tube_seg.tubes_from_paths((-1, -1, -1), paths)
with pytest.raises(TypeError):
tube_seg.tubes_from_paths(size, "asdf")
with pytest.raises(TypeError):
tube_seg.tubes_from_paths(size, [[0, 0, "asdf"]])
with pytest.raises(TypeError):
tube_seg.tubes_from_paths(size, paths, radius="asdf")
with pytest.raises(ValueError):
tube_seg.tubes_from_paths(size, paths, radius=-1)
def test_pull():
url = "s3://mouse-light-viz/precomputed_volumes/brain1"
ngl = NeuroglancerSession(url, mip=4, url_segments=url + "_segments")
img, bounds, voxel = ngl.pull_voxel(2, 300)
img2 = ngl.pull_bounds_img(bounds)
assert np.all(np.squeeze(np.array(img)) == np.squeeze(np.array(img2)))