def setUpClass(cls):
"""Set up this class with several pre-loaded BEL graphs."""
super().setUpClass()
with mock_bel_resources:
cls.thorough_graph = from_bel_script(test_bel_thorough, manager=cls.manager, disallow_nested=False)
cls.slushy_graph = from_bel_script(
test_bel_slushy,
manager=cls.manager,
disallow_unqualified_translocations=True,
disallow_nested=True,
)
cls.simple_graph = from_bel_script_url(Path(test_bel_simple).as_uri(), manager=cls.manager)
cls.isolated_graph = from_bel_script(test_bel_isolated, manager=cls.manager)
cls.misordered_graph = from_bel_script(test_bel_misordered, manager=cls.manager, citation_clearing=False)
def ci(directory: str, connection: str, required_annotations: List[str]):
"""Run in continuous integration setting."""
repo = Repo(directory)
file_names = get_changed(repo)
if not file_names:
click.secho(f'{EMOJI} no BEL files changed')
sys.exit(0)
manager = Manager(connection=connection)
failures = []
for file_name in file_names:
click.echo(f'{EMOJI} file changed: {file_name}')
t = time.time()
graph = from_bel_script(file_name,
manager=manager,
required_annotations=required_annotations)
fg_color = 'green'
if graph.warnings:
failures.append((file_name, graph))
fg_color = 'red'
click.secho(
f'{EMOJI} done checking: {file_name} ({time.time() - t:.2f} seconds)',
fg=fg_color)
click.echo(graph.summary_str())
if not failures:
sys.exit(0)
click.echo('')
for file_name, graph in failures:
click.secho(f'failed: {file_name} - {graph}', fg='red')
sys.exit(1)
def process_belscript(file_name, **kwargs):
"""Return a PybelProcessor by processing a BEL script file.
Key word arguments are passed directly to pybel.from_path,
for further information, see
pybel.readthedocs.io/en/latest/io.html#pybel.from_path
Some keyword arguments we use here differ from the defaults
of PyBEL, namely we set `citation_clearing` to False
and `no_identifier_validation` to True.
Parameters
----------
file_name : str
The path to a BEL script file.
Returns
-------
bp : PybelProcessor
A PybelProcessor object which contains INDRA Statements in
bp.statements.
"""
if 'citation_clearing' not in kwargs:
kwargs['citation_clearing'] = False
if 'no_identifier_validation' not in kwargs:
kwargs['no_identifier_validation'] = True
pybel_graph = pybel.from_bel_script(file_name, **kwargs)
return process_pybel_graph(pybel_graph)
def setUpClass(cls):
"""Set up the class with a BEL graph and its corresponding SQLAlchemy model."""
super().setUpClass()
with mock_bel_resources:
cls.graph = from_bel_script(test_bel_simple,
manager=cls.manager,
disallow_nested=False)
cls.network = cls.manager.insert_graph(cls.graph)
def get_graph(graph_name: str, force: bool = False) -> pybel.BELGraph:
"""Get the Selventa large corpus as a BEL Graph."""
url = f'https://github.com/cthoyt/selventa-knowledge/raw/master/selventa_knowledge/{graph_name}.bel'
cache_path = module.join(name=f'{graph_name}.bel.pickle')
if cache_path.exists() and not force:
return pybel.load(cache_path)
path = module.ensure(url=url, force=force)
graph = pybel.from_bel_script(path, citation_clearing=False)
pybel.dump(graph, path.as_posix())
return graph
def test_bep_0008(self):
"""Test parsing works right"""
graph = from_bel_script(test_bel_with_obo)
self.assertIn('hgnc', graph.namespace_pattern)
self.assertEqual(r'\d+', graph.namespace_pattern['hgnc'])
self.assertEqual(0, graph.number_of_warnings(), msg=',\n'.join(map(str, graph.warnings)))
self.assertEqual(2, graph.number_of_nodes())
self.assertIn(Protein(namespace='hgnc', identifier='391', name='AKT1'), graph)
self.assertIn(Protein(namespace='hgnc', identifier='3236', name='EGFR'), graph)
def upload_neurommsig_graphs(manager: Manager):
"""Only upload NeuroMMSig Sample Networks."""
if not (os.path.exists(alzheimer_directory)
and os.path.isdir(alzheimer_directory)):
logger.warning('directory does not exist: %s', alzheimer_directory)
return
if not os.path.exists(neurommsig_directory):
logger.info('created neurommsig directory: %s', neurommsig_directory)
os.makedirs(neurommsig_directory)
path = os.path.join(alzheimer_directory, 'alzheimers.bel')
gpickle_path = os.path.join(alzheimer_directory, 'alzheimers.gpickle')
if os.path.exists(gpickle_path):
graph = from_pickle(gpickle_path)
elif os.path.exists(path):
graph = from_bel_script(path, manager=manager)
to_pickle(graph, gpickle_path)
else:
raise RuntimeError('missing NeuroMMSig source file: {}'.format(path))
subgraphs = {
name: subgraph
for name, subgraph in get_subgraphs_by_annotation(
graph, annotation='Subgraph').items()
if name in neurommsig_sample_networks
}
networks = []
for subgraph_name, subgraph in subgraphs.items():
subgraph.name = 'NeuroMMSig AD {}'.format(subgraph_name)
subgraph.authors = 'Daniel Domingo-Fernandez et. al'
subgraph.version = graph.version
subgraph.license = graph.license
# output to directory as gpickle
to_pickle(
subgraph,
os.path.join(neurommsig_directory,
'{}.gpickle'.format(subgraph_name)))
network = insert_graph(manager, subgraph, public=True, use_tqdm=True)
networks.append(network)
write_manifest(neurommsig_directory, networks)
def parse(manager: WebManager, path: str, public: bool):
"""Parses a BEL script and uploads."""
t = time.time()
graph = from_bel_script(path, manager=manager)
logger.info('parsing done in %.2f seconds', time.time() - t)
insert_graph(manager, graph, public=public, use_tqdm=True)