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)))