def save_snapshot_nml_read_and_write():
for i in range(0, len(INPUT_FILES)):
input_file = INPUT_FILES[i]
output_file = OUTPUT_FILES[i]
parsed = wknml.parse_nml(input_file)
with open(output_file + '.snapshot', 'wb') as f:
wknml.write_nml(f, parsed)
def test_read_and_write_and_read():
for i in range(0, len(INPUT_FILES)):
input_file = INPUT_FILES[i]
output_file = OUTPUT_FILES[i]
first = wknml.parse_nml(input_file)
with open(output_file, 'wb') as f:
wknml.write_nml(f, first)
second = wknml.parse_nml(output_file)
assert first == second
def test_snapshot_read_and_compare_nml():
for i in range(0, len(INPUT_FILES)):
input_file = INPUT_FILES[i]
snapshot_file = SNAPSHOT_FILES[i]
output_file = OUTPUT_FILES[i]
parsed = wknml.parse_nml(input_file)
with open(output_file, 'wb') as f:
wknml.write_nml(f, parsed)
assert filecmp.cmp(snapshot_file + '.snapshot', output_file)
def test_calc_supervoxel_eftpl(tmp_path):
dummy_data = np.random.randint(100, size=(10, 10, 10))
with h5py.File(tmp_path / 'test.h5', 'w') as h5file:
h5file.create_dataset('with_background/test_data/labels',
data=dummy_data)
nml = util_get_nml()
with open(tmp_path / "test.nml", "wb") as f:
wknml.write_nml(f, nml)
calc_supervoxel_eftpl(tmp_path / 'test.nml', tmp_path / 'test.h5')
return
def write_nml(self, nml_write_path):
""" Writes the present state of the skeleton object to a .nml file.
Args:
nml_write_path: Path to which .nml file should be written
"""
# If the object does not have any trees, construct an empty tree before writing to enable webKnossos import
if self.num_trees() == 0:
self.add_tree()
nml = self._skeleton_to_nml()
with open(nml_write_path, "wb") as f:
wknml.write_nml(f, nml)
def load_and_save_merged_nml_trees(source: str, destination: str, scale):
assert os.path.isfile(source), "No file was provided as source."
assert os.path.exists(os.path.dirname(os.path.realpath(destination))), "The destination directory does not exists."
logger.info("Reading data")
with open(source, "rb") as f:
nml = parse_nml(f)
logger.info("Starting to merge tree groups")
merged_nml = create_merged_nml(nml, scale)
logger.info("Writing data")
with open(destination, "wb") as f:
write_nml(f, merged_nml)
logger.info("Done")
def test_generate_nml():
with open("testdata/nml_with_invalid_ids.nml", "r") as file:
test_nml = parse_nml(file)
(graph, parameter_dict) = generate_graph(test_nml)
test_result_nml = generate_nml(tree_dict=graph, parameters=parameter_dict)
with open("testdata/expected_result.nml", "r") as file:
expected_nml = parse_nml(file)
# need to save and load the test_result_nml since reading applies default values
# thus this is needed to be able to compare the nmls
with open("testoutput/temp.nml", "wb") as file:
write_nml(file=file, nml=test_result_nml)
with open("testoutput/temp.nml", "r") as file:
test_result_nml = parse_nml(file)
assert test_result_nml == expected_nml
def test_no_default_values_written():
input_file_name = "testdata/nml_without_default_values.nml"
output_file_name = "testoutput/nml_without_default_values.nml"
# read and write the test file
with open(input_file_name, "r") as file:
test_nml = parse_nml(file)
with open(output_file_name, "wb") as output_file:
write_nml(file=output_file, nml=test_nml)
# read the written testfile and compare the content
with open(input_file_name, "r") as file:
test_nml = parse_nml(file)
with open(output_file_name, "r") as output_file:
test_result_nml = parse_nml(output_file)
assert test_nml == test_result_nml, "The testdata file and the testoutput file do not have the same content."
# test if both files have the same content
assert filecmp.cmp(
input_file_name, output_file_name
), "The testdata and the testoutput file do not have the same content."
nml.trees)
new_tree = wknml.Tree(
id=i,
color=old_tree.color,
name=old_tree.name,
groupId=old_tree.groupId,
nodes=[n for n in all_nodes if n.id in node_ids],
edges=[
e for e in all_edges
if e.source in node_ids or e.target in node_ids
],
)
old_new_mapping[old_tree.id].append(i)
new_trees.append(new_tree)
new_trees_with_groups = []
new_groups = []
for i, (old_id, new_ids) in enumerate(old_new_mapping.items()):
group_id = i + 1
old_tree = find(lambda t: t.id == old_id, nml.trees)
new_groups.append(wknml.Group(id=group_id, name=old_tree.name,
children=[]))
for new_id in new_ids:
new_tree = find(lambda t: t.id == new_id, new_trees)
new_trees_with_groups.append(new_tree._replace(groupId=group_id))
nml = nml._replace(trees=new_trees_with_groups, groups=new_groups)
with open(args.target, "wb") as f:
wknml.write_nml(f, nml)