def test_file_to_dict_list():
"""
GIVEN compound files of different types (.tsv, .csv, and .json)
WHEN the file contents are converted to a list of compound dicts
THEN check that the list of compound dicts is produced as expected
"""
res_7 = OrderedDict([('id', 'cpd01211'), ('abbreviation', 'tcynt'),
('name', 'Thiocyanate'), ('formula', 'CNS'),
('mass', '58'), ('source', 'ModelSEED'),
('structure', 'InChI=1S/CHNS/c2-1-3/h3H'),
('charge', '-1'), ('is_core', '1'),
('is_obsolete', '0'), ('linked_compound', 'null'),
('is_cofactor', '0'), ('deltag', '22.2'),
('deltagerr', '5.68687'), ('pka', '3:0.5'),
('pkb', ''), ('abstract_compound', 'null'),
('comprised_of', 'null'), ('aliases', 'null')])
filenames = [
'test_compounds.tsv', 'test_compounds.csv', 'test_compounds.json'
]
for file in filenames:
res = utils.file_to_dict_list(DATA_DIR + file)
assert len(res) == 15
assert res[7] == res_7
def load_compound_set(self,
compound_file=None,
structure_field=None,
id_field='id'):
"""If a compound file is provided, this function loads the compounds
into it's internal dictionary. If not, it attempts to find the
compounds in it's associated MINE database.
:param compound_file: Path to a file containing compounds as tsv
:type compound_file: basestring
:param structure_field: the name of the column containing the
structure incarnation as Inchi or SMILES (Default:'structure')
:type structure_field: str
:param id_field: the name of the column containing the desired
compound ID (Default: 'id)
:type id_field: str
:return: compound SMILES
:rtype: list
"""
compound_smiles = []
if compound_file:
for line in utils.file_to_dict_list(compound_file):
mol = self._mol_from_dict(line, structure_field)
if not mol:
continue
# Add compound to internal dictionary as a starting
# compound and store SMILES string to be returned
smi = AllChem.MolToSmiles(mol, True)
_id = line[id_field]
# Do not operate on inorganic compounds
if "C" in smi or "c" in smi:
AllChem.SanitizeMol(mol)
self._add_compound(_id,
smi,
mol=mol,
type='Starting Compound')
compound_smiles.append(smi)
# If a MINE database is being used instead, search for compounds
# annotated as starting compounds and return those as a list of
# SMILES strings
elif self.mine:
db = MINE(self.mine)
for compound in db.compounds.find():
_id = compound['_id']
smi = compound['SMILES']
# Assume unannotated compounds are starting compounds
if 'type' not in compound:
compound['Type'] = 'Starting Compound'
self._add_compound(_id, smi, type=compound['Type'])
compound_smiles.append(smi)
else:
raise ValueError('No input file or database specified for '
'starting compounds')
print("%s compounds loaded" % len(compound_smiles))
return compound_smiles
def test_file_to_dict_list():
res_7 = OrderedDict([('id', 'cpd01211'), ('abbreviation', 'tcynt'),
('name', 'Thiocyanate'), ('formula', 'CNS'),
('mass', '58'), ('source', 'ModelSEED'),
('structure', 'InChI=1S/CHNS/c2-1-3/h3H'),
('charge', '-1'), ('is_core', '1'),
('is_obsolete', '0'), ('linked_compound', 'null'),
('is_cofactor', '0'), ('deltag', '22.2'),
('deltagerr', '5.68687'), ('pka', '3:0.5'),
('pkb', ''), ('abstract_compound', 'null'),
('comprised_of', 'null'), ('aliases', 'null')])
for file in [
'test_compounds.tsv', 'test_compounds.csv', 'test_compounds.json'
]:
res = utils.file_to_dict_list(data_dir + file)
assert len(res) == 15
assert res[7] == res_7
print(file)
def test_file_to_dict_list():
"""
GIVEN compound files of different types (.tsv, .csv, and .json)
WHEN the file contents are converted to a list of compound dicts
THEN check that the list of compound dicts is produced as expected
"""
res_7 = OrderedDict(
[
("id", "cpd01211"),
("abbreviation", "tcynt"),
("name", "Thiocyanate"),
("formula", "CNS"),
("mass", "58"),
("source", "ModelSEED"),
("structure", "InChI=1S/CHNS/c2-1-3/h3H"),
("charge", "-1"),
("is_core", "1"),
("is_obsolete", "0"),
("linked_compound", "null"),
("is_cofactor", "0"),
("deltag", "22.2"),
("deltagerr", "5.68687"),
("pka", "3:0.5"),
("pkb", ""),
("abstract_compound", "null"),
("comprised_of", "null"),
("aliases", "null"),
]
)
filenames = ["test_compounds.tsv", "test_compounds.csv", "test_compounds.json"]
for file in filenames:
res = utils.file_to_dict_list(DATA_DIR / file)
assert len(res) == 15
assert res[7] == res_7
neutralise=options.bnice,
image_dir=options.image_dir,
database=options.database)
# Create a directory for image output file if it doesn't already exist
if options.image_dir and not os.path.exists(options.image_dir):
os.mkdir(options.image_dir)
# If starting compound specified as SMILES string, then add it
if options.smiles:
pk._add_compound("Start", options.smiles, type='Starting Compound')
else:
pk.load_compound_set(compound_file=options.compound_file)
# Generate reaction network
pk.transform_all(max_generations=options.generations,
num_workers=options.max_workers)
if options.pruning_whitelist:
mols = [
pk._mol_from_dict(line)
for line in utils.file_to_dict_list(options.pruning_whitelist)
]
pk.prune_network([utils.compound_hash(x) for x in mols if x])
# Save to database (e.g. Mongo) if present, otherwise create output file
if options.database:
print("Saving results to %s" % options.database)
pk.save_to_MINE(options.database)
else:
pk.assign_ids()
pk.write_compound_output_file(options.output_dir + '/compounds.tsv')
pk.write_reaction_output_file(options.output_dir + '/reactions.tsv')
print("Execution took %s seconds." % (time.time() - t1))