def test_get_files_by_path():
single_neurom = utils.get_files_by_path(NO_SOMA_FILE)
nt.eq_(len(single_neurom), 1)
neuron_dir = utils.get_files_by_path(VALID_DATA_PATH)
nt.eq_(len(neuron_dir), 6)
nt.assert_raises(IOError, utils.get_files_by_path, 'this/is/a/fake/path')
def test_get_files_by_path():
single_neurom = utils.get_files_by_path(NO_SOMA_FILE)
assert len(single_neurom) == 1
neuron_dir = utils.get_files_by_path(VALID_DATA_PATH)
assert len(neuron_dir) == 4
with pytest.raises(IOError):
utils.get_files_by_path(Path('this/is/a/fake/path'))
def main(datapath, config, output_file, is_full_config, as_population,
ignored_exceptions):
"""Main function that get statistics for morphologies.
Args:
datapath (str|Path): path to a morphology file or folder
config (str|Path): path to a statistics config file
output_file (str|Path): path to output the resulted statistics file
is_full_config (bool): should be statistics made over all possible features, modes, neurites
as_population (bool): treat ``datapath`` as directory of morphologies population
ignored_exceptions (list|tuple|None): exceptions to ignore when loading a morphology
"""
if is_full_config:
config = full_config()
else:
try:
config = get_config(config, EXAMPLE_CONFIG)
config = sanitize_config(config)
except ConfigError as e:
L.error(e)
raise
if ignored_exceptions is None:
ignored_exceptions = ()
ignored_exceptions = tuple(IGNORABLE_EXCEPTIONS[k]
for k in ignored_exceptions)
neurons = nm.load_neurons(get_files_by_path(datapath),
ignored_exceptions=ignored_exceptions)
results = {}
if as_population:
results[datapath] = extract_stats(neurons, config)
else:
for neuron in tqdm(neurons):
results[neuron.name] = extract_stats(neuron, config)
if not output_file:
print(
json.dumps(results,
indent=2,
separators=(',', ':'),
cls=NeuromJSON))
elif output_file.endswith('.json'):
with open(output_file, 'w') as f:
json.dump(results, f, cls=NeuromJSON)
else:
with open(output_file, 'w') as f:
csvwriter = csv.writer(f)
header = get_header(results)
csvwriter.writerow(header)
for line in generate_flattened_dict(header, dict(results)):
csvwriter.writerow(line)
def run(self, path):
"""Test a bunch of files and return a summary JSON report."""
SEPARATOR = '=' * 40
summary = {}
res = True
for _f in utils.get_files_by_path(path):
L.info(SEPARATOR)
status, summ = self._check_file(_f)
res &= status
if summ is not None:
summary.update(summ)
L.info(SEPARATOR)
status = 'PASS' if res else 'FAIL'
return {'files': summary, 'STATUS': status}
def run(self, path):
'''Test a bunch of files and return a summary JSON report'''
SEPARATOR = '=' * 40
summary = {}
res = True
for _f in utils.get_files_by_path(path):
L.info(SEPARATOR)
status, summ = self._check_file(_f)
res &= status
if summ is not None:
summary.update(summ)
L.info(SEPARATOR)
status = 'PASS' if res else 'FAIL'
return {'files': summary, 'STATUS': status}
