def test_file_write():
"""Tests that files are written correctly."""
files = sorted(glob.glob("*.feather"))
for f in sorted(files):
os.remove(f)
nbr = nbrhood.NeighborhoodFeatures(url=url,
radius=1,
offset=[15, 15, 15],
segment_url=url_seg)
nbr.fit([2], 5, file_path="test", batch_size=10)
files = sorted(glob.glob("*.feather"))
for f in sorted(files):
print(f)
os.remove(f)
assert files == ["test0_10_2_4.feather"]
df_nbr = nbr.fit([2],
5,
file_path="test",
batch_size=10,
start_seg=2,
start_vert=0)
files = sorted(glob.glob("*.feather"))
for f in sorted(files):
os.remove(f)
assert files == ["test0_10_2_4.feather"]
def test_init_bad_inputs():
"""Tests that proper errors are raised when bad inputs are given to __init__ method."""
with pytest.raises(TypeError):
nbrhood.NeighborhoodFeatures(url=0, radius=SIZE, offset=OFF)
with pytest.raises(NotImplementedError):
nbrhood.NeighborhoodFeatures(url="asdf", radius=SIZE, offset=OFF)
with pytest.raises(TypeError):
nbrhood.NeighborhoodFeatures(url=url, radius=0.5, offset=OFF)
with pytest.raises(ValueError):
nbrhood.NeighborhoodFeatures(url=url,
radius=-1,
offset=OFF,
segment_url=url_seg)
with pytest.raises(TypeError):
nbrhood.NeighborhoodFeatures(url=url,
radius=SIZE,
offset=12,
segment_url=url_seg)
with pytest.raises(TypeError):
nbrhood.NeighborhoodFeatures(url=url,
radius=SIZE,
offset=OFF,
segment_url=0)
with pytest.raises(NotImplementedError):
nbrhood.NeighborhoodFeatures(url=url,
radius=SIZE,
offset=OFF,
segment_url="asdf")
def gen_array():
nbr = nbrhood.NeighborhoodFeatures(url=url,
radius=SIZE,
offset=[15, 15, 15],
segment_url=url_seg)
df_nbr = nbr.fit([2], 5)
ind = SIZE * 2 + 1
arr = df_nbr.iloc[2, 3:].values.reshape((ind, ind, ind))
return arr
def test_neighborhood():
"""Tests that neighborhood data is generated correctly."""
nbr = nbrhood.NeighborhoodFeatures(url=url,
radius=1,
offset=[15, 15, 15],
segment_url=url_seg)
df_nbr = nbr.fit([2], 5)
assert df_nbr.shape == (10, 30) # 5on, 5off for each swc
assert not df_nbr.empty
def test_fit_bad_inputs():
"""Tests that proper errors are raised when bad inputs are given to fit method."""
nbr = nbrhood.NeighborhoodFeatures(url=url,
radius=SIZE,
offset=[15, 15, 15],
segment_url=url_seg)
with pytest.raises(TypeError):
nbr.fit(seg_ids=1, num_verts=5, file_path="demo", batch_size=1000)
with pytest.raises(cloudvolume.exceptions.SkeletonDecodeError):
nbr.fit(seg_ids=[1], num_verts=5, file_path="demo", batch_size=1000)