def test_infer_category(query):
"""
Test inferring of biolink category for a given IRI.
"""
graph = Graph()
graph.parse(os.path.join(RESOURCE_DIR, "goslim_generic.owl"))
[c] = infer_category(query[0], graph)
assert c == query[1]
def load_node_attributes(self, rdfgraph: rdflib.Graph) -> None:
"""
This method loads the properties of nodes into networkx.MultiDiGraph
As there can be many values for a single key, all properties are lists by default.
This method assumes that ``RdfTransformer.load_edges()`` has been called, and that all nodes
have had their IRI as an attribute.
Parameters
----------
rdfgraph: rdflib.Graph
Graph containing nodes and edges
"""
logging.info(
"Loading node attributes from rdflib.Graph into networkx.MultiDiGraph"
)
with click.progressbar(self.graph.nodes(data=True),
label='Progress') as bar:
for n, data in bar:
print(n, data)
if 'id' not in data:
data['id'] = n
if 'iri' in data:
uriref = URIRef(data['iri'])
else:
provided_by = self.graph_metadata.get('provided_by')
logging.warning(
"No 'iri' property for {} provided by {}".format(
n, provided_by))
continue
for s, p, o in rdfgraph.triples((uriref, None, None)):
if p in property_mapping:
# predicate corresponds to a property on subject
if not (isinstance(s, rdflib.term.BNode)
and isinstance(o, rdflib.term.BNode)):
# neither subject nor object is a BNode
if isinstance(o, rdflib.term.Literal):
o = o.value
self.add_node_attribute(uriref, key=p, value=o)
elif isinstance(o, rdflib.term.Literal):
# object is a Literal
# i.e. predicate corresponds to a property on subject
self.add_node_attribute(uriref, key=p, value=o.value)
categories = infer_category(uriref, rdfgraph)
logging.debug("Inferred '{}' as category for node '{}'".format(
categories, uriref))
for category in categories:
self.add_node_attribute(uriref,
key='category',
value=category)
def test_infer_category(query):
graph = Graph()
graph.parse(os.path.join(resource_dir, 'goslim_generic.owl'))
[c] = infer_category(query[0], graph)
assert c == query[1]