def compare_from_cli(args):
"""
Compare fingerprints.
Parameters
----------
args : argsparse.Namespace
CLI arguments.
"""
configure_logger(Path(args.output) / "distances.log")
fingerprint_generator = FingerprintGenerator.from_json(args.input)
compare(fingerprint_generator, args.output, args.weights, args.ncores)
def outliers(fingerprints_path,
distance_cutoff,
fingerprints_wo_outliers_path=None):
"""
Remove outlier fingerprints (defined by spatial distances maximum).
Parameters
----------
fingerprints_path : str or pathlib.Path
Path to fingerprints JSON file.
distance_cutoff : float
Tolerated distance maximum; fingerprints with distances greater than this cutoff will be
removed.
fingerprints_wo_outliers_path : None or str or pathlib.Path
Path to fingerprints JSON file with outliers removed.
Returns
-------
kissim.encoding.FingerprintGenerator
Fingerprints without outliers.
"""
# Load fingerprints
logger.info("Read fingerprints...")
fingerprints_path = Path(fingerprints_path)
fingerprint_generator = FingerprintGenerator.from_json(fingerprints_path)
logger.info(f"Number of fingerprints: {len(fingerprint_generator.data)}")
# Find structures/fingerprints IDs to be removed
logger.info(f"Use the following distance minimum/maximum cutoffs"
f" to identify outlier structures: {distance_cutoff}")
remove_structure_ids = []
for structure_id, fp in fingerprint_generator.data.items():
if (fp.distances > distance_cutoff).any().any():
remove_structure_ids.append(structure_id)
logger.info(f"Structure IDs to be removed: {remove_structure_ids}")
# Remove fingerprints
logger.info("Remove fingerprints with distance outliers...")
for structure_id in remove_structure_ids:
del fingerprint_generator.data[structure_id]
logger.info(f"Number of fingerprints: {len(fingerprint_generator.data)}")
# Optionally: Save to file
if fingerprints_wo_outliers_path is not None:
logger.info(
f"Save cleaned fingerprints to {fingerprints_wo_outliers_path}...")
fingerprints_wo_outliers_path = Path(fingerprints_wo_outliers_path)
fingerprint_generator.to_json(fingerprints_wo_outliers_path)
return fingerprint_generator
def test_main_encode(args):
"""
Test CLI for encoding using subprocesses.
"""
output = Path("fingerprints.json")
args = args.split()
with enter_temp_directory():
subprocess.run(args, check=True)
# Json file there?
assert output.exists()
# Log file there?
assert Path(f"{output.stem}.log").exists()
# Json file can be loaded as FingerprintGenerator object?
fingerprint_generator = FingerprintGenerator.from_json(output)
assert isinstance(fingerprint_generator, FingerprintGenerator)
assert isinstance(list(fingerprint_generator.data.values())[0], Fingerprint)
def test_to_from_json(self, structure_klifs_ids, normalize,
values_array_sum):
"""
Test if saving/loading a fingerprint to/from a json file.
"""
fingerprints = FingerprintGenerator.from_structure_klifs_ids(
structure_klifs_ids, LOCAL, 1)
json_filepath = Path("fingerprints.json")
with enter_temp_directory():
# Save json file
fingerprints.to_json(json_filepath)
assert json_filepath.exists()
# Load json file
fingerprints_reloaded = FingerprintGenerator.from_json(
json_filepath, normalize)
assert isinstance(fingerprints_reloaded, FingerprintGenerator)
# Attribute data
assert list(fingerprints.data.keys()) == list(
fingerprints_reloaded.data.keys())
if normalize:
assert list(fingerprints.data_normalized.keys()) == list(
fingerprints_reloaded.data_normalized.keys())
else:
assert fingerprints_reloaded.data_normalized is None
values_array_sum_calculated = sum([
np.nansum(fingerprint.values_array(True, True, True))
for structure_klifs_id, fingerprint in
fingerprints_reloaded.data.items()
])
assert pytest.approx(values_array_sum_calculated,
abs=1e-4) == values_array_sum