def test_clique_merge8():
"""
Test for clique merge where same_as appear as both node and edge properties.
"""
ppm = {"biolink:Gene": ["HGNC", "NCBIGene", "ENSEMBL", "OMIM"]}
g1 = NxGraph()
g1.add_node("HGNC:1", **{"category": ["biolink:Gene"]})
g1.add_node("OMIM:2", **{"category": ["biolink:Gene"], "same_as": ["HGNC:1"]})
g1.add_node("NCBIGene:3", **{"category": ["biolink:NamedThing"]})
g1.add_node("ENSEMBL:4", **{"category": ["biolink:Gene"], "same_as": ["HGNC:1"]})
g1.add_node(
"ENSEMBL:6", **{"category": ["biolink:Gene"], "same_as": ["NCBIGene:8"]}
)
g1.add_node("HGNC:7", **{"category": ["biolink:Gene"]})
g1.add_node("NCBIGene:8", **{"category": ["biolink:Gene"]})
g1.add_edge(
"NCBIGene:3",
"HGNC:1",
edge_key=generate_edge_key("NCBIGene:3", "biolink:same_as", "HGNC:1"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"ENSEMBL:6",
"NCBIGene:8",
edge_key=generate_edge_key("ENSEMBL:6", "biolink:same_as", "NCBIGene:8"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"HGNC:7",
"NCBIGene:8",
edge_key=generate_edge_key("HGNC:7", "biolink:same_as", "NCBIGene:8"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
updated_graph, clique_graph = clique_merge(
target_graph=g1, prefix_prioritization_map=ppm
)
assert updated_graph.number_of_nodes() == 2
assert updated_graph.number_of_edges() == 0
assert updated_graph.has_node("HGNC:1")
assert updated_graph.has_node("HGNC:7")
n1 = updated_graph.nodes()["HGNC:1"]
assert "OMIM:2" in n1["same_as"]
assert "NCBIGene:3" in n1["same_as"]
assert "ENSEMBL:4" in n1["same_as"]
n2 = updated_graph.nodes()["HGNC:7"]
assert "ENSEMBL:6" in n2["same_as"]
assert "NCBIGene:8" in n2["same_as"]
assert not updated_graph.has_node("OMIM:2")
assert not updated_graph.has_node("NCBIGene:3")
assert not updated_graph.has_node("ENSEMBL:4")
assert not updated_graph.has_node("ENSEMBL:6")
assert not updated_graph.has_node("NCBIGene:8")
def load_edge(self, edge: Dict) -> None:
"""
Load an edge into a networkx.MultiDiGraph
.. Note::
This methods transformers Reasoner Std API format fields to Biolink Model fields.
Parameters
----------
edge : dict
An edge
"""
if 'source_id' in edge:
edge['subject'] = edge['source_id']
if 'target_id' in edge:
edge['object'] = edge['target_id']
if 'relation_label' in edge:
edge['edge_label'] = edge['relation_label'][0]
edge = self.validate_edge(edge)
kwargs = PandasTransformer._build_kwargs(edge.copy())
if 'subject' in kwargs and 'object' in kwargs:
s = kwargs['subject']
o = kwargs['object']
key = generate_edge_key(s, kwargs['edge_label'], o)
self.graph.add_edge(s, o, key, **kwargs)
else:
logging.info(
"Ignoring edge with either a missing 'subject' or 'object': {}"
.format(kwargs))
def load_edge(self, edge_record: List) -> Tuple:
"""
Load an edge into an instance of BaseGraph
Parameters
----------
edge_record: List
A 4-tuple edge record
Returns
-------
Tuple
A tuple with subject ID, object ID, edge key, and edge data
"""
subject_node = edge_record[0]
edge = edge_record[1]
object_node = edge_record[2]
if 'provided_by' in self.graph_metadata and 'provided_by' not in edge.keys():
edge['provided_by'] = self.graph_metadata['provided_by']
if 'id' not in edge.keys():
edge['id'] = generate_uuid()
key = generate_edge_key(subject_node['id'], edge['predicate'], object_node['id'])
edge = validate_edge(edge)
edge = sanitize_import(edge.copy())
self.edge_properties.update(edge.keys())
return subject_node['id'], object_node['id'], key, edge
def read_edge(self, edge: Dict) -> Optional[Tuple]:
"""
Load an edge into an instance of BaseGraph.
Parameters
----------
edge: Dict
An edge
Returns
-------
Optional[Tuple]
A tuple that contains subject id, object id, edge key, and edge data
"""
edge = validate_edge(edge)
edge_data = sanitize_import(edge.copy())
if 'id' not in edge_data:
edge_data['id'] = generate_uuid()
s = edge_data['subject']
o = edge_data['object']
if 'provided_by' in self.graph_metadata and 'provided_by' not in edge_data.keys():
edge_data['provided_by'] = self.graph_metadata['provided_by']
key = generate_edge_key(s, edge_data['predicate'], o)
self.edge_properties.update(list(edge_data.keys()))
if self.check_edge_filter(edge_data):
self.node_properties.update(edge_data.keys())
return s, o, key, edge_data
def load_edge(self, edge_record: List) -> Tuple:
"""
Load an edge into an instance of BaseGraph
Parameters
----------
edge_record: List
A 4-tuple edge record
Returns
-------
Tuple
A tuple with subject ID, object ID, edge key, and edge data
"""
subject_node = edge_record[0]
edge_data = edge_record[1]
object_node = edge_record[2]
self.set_edge_provenance(edge_data)
if "id" not in edge_data.keys():
edge_data["id"] = generate_uuid()
key = generate_edge_key(subject_node["id"], edge_data["predicate"],
object_node["id"])
edge_data = self.validate_edge(edge_data)
if not edge_data:
return ()
edge_data = sanitize_import(edge_data.copy())
self.edge_properties.update(edge_data.keys())
return subject_node["id"], object_node["id"], key, edge_data
def load_ontologies(self):
"""
Load all required ontologies.
"""
for ontology in self.ontologies.values():
rdfgraph = rdflib.Graph()
input_format = rdflib.util.guess_format(ontology)
rdfgraph.parse(ontology, format=input_format)
triples = rdfgraph.triples((None, rdflib.RDFS.subClassOf, None))
for s, p, o in triples:
subject_curie = contract(s)
object_curie = contract(o)
self.ontology_graph.add_node(subject_curie)
self.ontology_graph.add_node(object_curie)
key = generate_edge_key(subject_curie, 'subclass_of',
object_curie)
self.ontology_graph.add_edge(
subject_curie, object_curie, key, **{
'edge_label': 'subclass_of',
'relation': 'rdfs:subClassOf'
})
triples = rdfgraph.triples((None, rdflib.RDFS.label, None))
for s, p, o in triples:
key = contract(s)
value = o.value
value = value.replace(' ', '_')
self.curie_map[key] = value
self.ontology_graph.add_node(key, name=value)
def load_edge(self, edge: Dict) -> None:
"""
Load an edge into a networkx.MultiDiGraph
Parameters
----------
edge : dict
An edge
"""
if self.check_edge_filter(edge):
edge = Transformer.validate_edge(edge)
kwargs = PandasTransformer._build_kwargs(edge.copy())
if 'subject' in kwargs and 'object' in kwargs:
s = kwargs['subject']
o = kwargs['object']
if 'provided_by' in self.graph_metadata and 'provided_by' not in kwargs.keys(
):
kwargs['provided_by'] = self.graph_metadata['provided_by']
key = generate_edge_key(s, kwargs['edge_label'], o)
self.graph.add_edge(s, o, key, **kwargs)
self._edge_properties.update(list(kwargs.keys()))
else:
logging.info(
"Ignoring edge with either a missing 'subject' or 'object': {}"
.format(kwargs))
else:
logging.debug(f"Edge fails edge filters: {edge}")
def read_edge(self, edge: Dict) -> Optional[Tuple]:
"""
Load an edge into an instance of BaseGraph.
Parameters
----------
edge: Dict
An edge
Returns
-------
Optional[Tuple]
A tuple that contains subject id, object id, edge key, and edge data
"""
edge = self.validate_edge(edge)
if not edge:
return None
edge_data = sanitize_import(edge.copy(), self.list_delimiter)
if "id" not in edge_data:
edge_data["id"] = generate_uuid()
s = edge_data["subject"]
o = edge_data["object"]
self.set_edge_provenance(edge_data)
key = generate_edge_key(s, edge_data["predicate"], o)
self.edge_properties.update(list(edge_data.keys()))
if self.check_edge_filter(edge_data):
self.node_properties.update(edge_data.keys())
return s, o, key, edge_data
def add_edge(self, subject_iri: URIRef, object_iri: URIRef, predicate_iri: URIRef) -> Tuple[str, str, str]:
"""
This method should be used by all derived classes when adding an edge to the networkx.MultiDiGraph.
This ensures that the `subject` and `object` identifiers are CURIEs, and that `edge_label` is in the correct form.
Returns the CURIE identifiers used for the `subject` and `object` in the
networkx.MultiDiGraph, and the processed `edge_label`.
Parameters
----------
subject_iri: rdflib.URIRef
Subject IRI for the subject in a triple
object_iri: rdflib.URIRef
Object IRI for the object in a triple
predicate_iri: rdflib.URIRef
Predicate IRI for the predicate in a triple
Returns
-------
Tuple[str, str, str]
A 3-nary tuple (of the form subject, object, predicate) that represents the edge
"""
s = self.add_node(subject_iri)
o = self.add_node(object_iri)
relation = self.prefix_manager.contract(predicate_iri)
edge_label = process_iri(predicate_iri)
if ' ' in edge_label:
logging.debug("predicate IRI '{}' yields edge_label '{}' that not in snake_case form; replacing ' ' with '_'".format(predicate_iri, edge_label))
if edge_label.startswith(self.BIOLINK):
logging.debug("predicate IRI '{}' yields edge_label '{}' that starts with '{}'; removing IRI prefix".format(predicate_iri, edge_label, self.BIOLINK))
edge_label = edge_label.replace(self.BIOLINK, '')
if PrefixManager.is_curie(edge_label):
name = curie_lookup(edge_label)
if name:
logging.debug("predicate IRI '{}' yields edge_label '{}' that is actually a CURIE; Using its mapping instead: {}".format(predicate_iri, edge_label, name))
edge_label = name
else:
logging.debug("predicate IRI '{}' yields edge_label '{}' that is actually a CURIE; defaulting back to {}".format(predicate_iri, edge_label, self.DEFAULT_EDGE_LABEL))
edge_label = self.DEFAULT_EDGE_LABEL
kwargs = {
'subject': s,
'predicate': str(predicate_iri),
'object': o,
'relation': relation,
'edge_label': f"biolink:{edge_label}"
}
if 'provided_by' in self.graph_metadata:
kwargs['provided_by'] = self.graph_metadata['provided_by']
key = generate_edge_key(s, edge_label, o)
if not self.graph.has_edge(s, o, key=key):
self.graph.add_edge(s, o, key=key, **kwargs)
# TODO: support append
return s, o, edge_label
def write_edge(self, record: Dict) -> None:
"""
Write an edge record to graph.
Parameters
----------
record: Dict
An edge record
"""
key = (record['key'] if 'key' in record else generate_edge_key(
record['subject'], record['predicate'], record['object']))
self.graph.add_edge(record['subject'], record['object'], key, **record)
def add_edge_attribute(self, subject_iri: Union[URIRef, str],
object_iri: URIRef, predicate_iri: URIRef, key: str,
value: str) -> None:
"""
Adds an attribute to an edge, while taking into account whether the attribute
should be multi-valued.
Multi-valued properties will not contain duplicates.
The key may be a rdflib.URIRef or a URI string that maps onto a property name
as defined in `rdf_utils.property_mapping`.
If the nodes in the edge does not exist then they will be created
using subject_iri and object_iri.
If the edge itself does not exist then it will be created using
subject_iri, object_iri and predicate_iri.
Parameters
----------
subject_iri: [rdflib.URIRef, str]
The IRI of the subject node of an edge in rdflib.Graph
object_iri: rdflib.URIRef
The IRI of the object node of an edge in rdflib.Graph
predicate_iri: rdflib.URIRef
The IRI of the predicate representing an edge in rdflib.Graph
key: str
The name of the attribute. Can be a rdflib.URIRef or URI string
value: str
The value of the attribute
"""
if key.lower() in is_property_multivalued:
key = key.lower()
else:
if not isinstance(key, URIRef):
key = URIRef(key)
key = property_mapping.get(key)
if key is not None:
subject_curie = make_curie(subject_iri)
object_curie = make_curie(object_iri)
edge_label = process_iri(predicate_iri)
if is_curie(edge_label):
edge_label = curie_lookup(edge_label)
edge_key = generate_edge_key(subject_curie, edge_label,
object_curie)
attr_dict = self.graph.get_edge_data(subject_curie,
object_curie,
key=edge_key)
self._add_attribute(attr_dict, key, value)
def write_edge(self, record: Dict) -> None:
"""
Write an edge record to graph.
Parameters
----------
record: Dict
An edge record
"""
if "key" in record:
key = (record["key"])
else:
key = generate_edge_key(
record["subject"], record["predicate"], record["object"]
)
self.graph.add_edge(record["subject"], record["object"], key, **record)
def load_edge(self, edge: Dict) -> None:
"""
Load an edge into a networkx.MultiDiGraph
Parameters
----------
edge : dict
An edge
"""
edge = Transformer.validate_edge(edge)
kwargs = PandasTransformer._build_kwargs(edge.copy())
if 'subject' in kwargs and 'object' in kwargs:
s = kwargs['subject']
o = kwargs['object']
key = generate_edge_key(s, kwargs['edge_label'], o)
self.graph.add_edge(s, o, key, **kwargs)
else:
logging.info(
"Ignoring edge with either a missing 'subject' or 'object': {}"
.format(kwargs))
def load_edge(self, edge: Relationship) -> None:
"""
Load an edge from neo4jrestclient.client.Relationship into networkx.MultiDiGraph
Parameters
----------
edge: neo4jrestclient.client.Relationship
An edge
"""
edge_subject = edge.start
edge_predicate = edge.properties
edge_object = edge.end
subject_id = edge_subject[
'id'] if 'id' in edge_subject else edge_subject.id
object_id = edge_object['id'] if 'id' in edge_object else edge_object.id
attributes = {}
for key, value in edge_predicate.items():
attributes[key] = value
if 'subject' not in attributes:
attributes['subject'] = subject_id
if 'object' not in attributes:
attributes['object'] = object_id
if 'edge_label' not in attributes:
attributes['edge_label'] = edge.type
if not self.graph.has_node(subject_id):
self.load_node(edge_subject)
if not self.graph.has_node(object_id):
self.load_node(edge_object)
key = generate_edge_key(subject_id, attributes['edge_label'],
object_id)
self.graph.add_edge(subject_id, object_id, key, **attributes)
def consolidate_edges(
target_graph: BaseGraph, clique_graph: nx.MultiDiGraph, leader_annotation: str
) -> BaseGraph:
"""
Move all edges from nodes in a clique to the clique leader.
Original subject and object of a node are preserved via ``ORIGINAL_SUBJECT_PROPERTY`` and ``ORIGINAL_OBJECT_PROPERTY``
Parameters
----------
target_graph: kgx.graph.base_graph.BaseGraph
The original graph
clique_graph: networkx.MultiDiGraph
The clique graph
leader_annotation: str
The field on a node that signifies that the node is the leader of a clique
Returns
-------
kgx.graph.base_graph.BaseGraph
The target graph where all edges from nodes in a clique are moved to clique leader
"""
cliques = list(nx.strongly_connected_components(clique_graph))
log.info(f"Consolidating edges in {len(cliques)} cliques")
for clique in cliques:
log.debug(f"Processing clique: {clique}")
leaders: List = [
x
for x in clique
if leader_annotation in clique_graph.nodes()[x]
and clique_graph.nodes()[x][leader_annotation]
]
if len(leaders) == 0:
log.debug("No leader elected for clique {}; skipping".format(clique))
continue
leader: str = leaders[0]
# update nodes in target graph
target_graph.set_node_attributes(
target_graph,
{
leader: {
leader_annotation: clique_graph.nodes()[leader].get(
leader_annotation
),
"election_strategy": clique_graph.nodes()[leader].get(
"election_strategy"
),
}
},
)
leader_equivalent_identifiers = set([x for x in clique_graph.neighbors(leader)])
for node in clique:
if node == leader:
continue
log.debug(f"Looking for in_edges for {node}")
in_edges = target_graph.in_edges(node, keys=False, data=True)
filtered_in_edges = [x for x in in_edges if x[2]["predicate"] != SAME_AS]
equiv_in_edges = [x for x in in_edges if x[2]["predicate"] == SAME_AS]
log.debug(f"Moving {len(in_edges)} in-edges from {node} to {leader}")
for u, v, edge_data in filtered_in_edges:
key = generate_edge_key(u, edge_data["predicate"], v)
target_graph.remove_edge(u, v, edge_key=key)
edge_data[ORIGINAL_SUBJECT_PROPERTY] = edge_data["subject"]
edge_data[ORIGINAL_OBJECT_PROPERTY] = edge_data["object"]
edge_data["object"] = leader
key = generate_edge_key(u, edge_data["predicate"], leader)
if (
edge_data["subject"] == edge_data["object"]
and edge_data["predicate"] == SUBCLASS_OF
):
continue
target_graph.add_edge(
edge_data["subject"], edge_data["object"], key, **edge_data
)
log.debug(f"Looking for out_edges for {node}")
out_edges = target_graph.out_edges(node, keys=False, data=True)
filtered_out_edges = [x for x in out_edges if x[2]["predicate"] != SAME_AS]
equiv_out_edges = [x for x in out_edges if x[2]["predicate"] == SAME_AS]
log.debug(f"Moving {len(out_edges)} out-edges from {node} to {leader}")
for u, v, edge_data in filtered_out_edges:
key = generate_edge_key(u, edge_data["predicate"], v)
target_graph.remove_edge(u, v, edge_key=key)
edge_data[ORIGINAL_SUBJECT_PROPERTY] = edge_data["subject"]
edge_data[ORIGINAL_OBJECT_PROPERTY] = edge_data["object"]
edge_data["subject"] = leader
key = generate_edge_key(leader, edge_data["predicate"], v)
if (
edge_data["subject"] == edge_data["object"]
and edge_data["predicate"] == SUBCLASS_OF
):
continue
target_graph.add_edge(
edge_data["subject"], edge_data["object"], key, **edge_data
)
log.debug(f"equiv out edges: {equiv_out_edges}")
equivalent_identifiers = set()
for u, v, edge_data in equiv_in_edges:
if u != leader:
equivalent_identifiers.add(u)
if v != leader:
equivalent_identifiers.add(v)
target_graph.remove_edge(
u, v, edge_key=generate_edge_key(u, SAME_AS, v)
)
log.debug(f"equiv out edges: {equiv_out_edges}")
for u, v, edge_data in equiv_out_edges:
if u != leader:
log.debug(f"{u} is an equivalent identifier of leader {leader}")
equivalent_identifiers.add(u)
if v != leader:
log.debug(f"{v} is an equivalent identifier of leader {leader}")
equivalent_identifiers.add(v)
target_graph.remove_edge(
u, v, edge_key=generate_edge_key(u, SAME_AS, v)
)
leader_equivalent_identifiers.update(equivalent_identifiers)
log.debug(
f"setting same_as property to leader node with {leader_equivalent_identifiers}"
)
target_graph.set_node_attributes(
target_graph, {leader: {"same_as": list(leader_equivalent_identifiers)}}
)
log.debug(
f"removing equivalent nodes of leader: {leader_equivalent_identifiers}"
)
for n in leader_equivalent_identifiers:
target_graph.remove_node(n)
return target_graph
def test_generate_edge_key():
key = generate_edge_key('S:CURIE', 'related_to', 'O:CURIE')
assert key == 'S:CURIE-related_to-O:CURIE'
def test_clique_merge7():
"""
Test for clique merge where each clique has a node that has
a disjoint category from other nodes in a clique and the node is
not a participant in same_as edges.
"""
ppm = {'biolink:Gene': ['HGNC', 'NCBIGene', 'ENSEMBL', 'OMIM']}
g1 = NxGraph()
g1.add_node('HGNC:1', **{'category': ['biolink:Gene']})
g1.add_node('OMIM:2', **{'category': ['biolink:Disease']})
g1.add_node('NCBIGene:3', **{'category': ['biolink:NamedThing']})
g1.add_node('ENSEMBL:4', **{'category': ['biolink:Gene']})
g1.add_node('ENSEMBL:6', **{'category': ['biolink:Gene']})
g1.add_node('HGNC:7', **{'category': ['biolink:Disease']})
g1.add_node('NCBIGene:8', **{'category': ['biolink:Gene']})
g1.add_edge('ENSEMBL:4',
'HGNC:1',
edge_key=generate_edge_key('ENSEMBL:4', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('NCBIGene:3',
'HGNC:1',
edge_key=generate_edge_key('NCBIGene:3', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('OMIM:2',
'HGNC:1',
edge_key=generate_edge_key('OMIM:2', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('ENSEMBL:6',
'NCBIGene:8',
edge_key=generate_edge_key('ENSEMBL:6', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('HGNC:7',
'NCBIGene:8',
edge_key=generate_edge_key('HGNC:7', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
updated_graph, clique_graph = clique_merge(target_graph=g1,
prefix_prioritization_map=ppm)
assert updated_graph.number_of_nodes() == 4
assert updated_graph.number_of_edges() == 2
assert updated_graph.has_node('HGNC:1')
assert updated_graph.has_node('NCBIGene:8')
n1 = updated_graph.nodes()['HGNC:1']
assert 'NCBIGene:3' in n1['same_as']
assert 'ENSEMBL:4' in n1['same_as']
assert 'OMIM:2' not in n1['same_as']
n2 = updated_graph.nodes()['NCBIGene:8']
assert 'ENSEMBL:6' in n2['same_as']
assert updated_graph.has_node('OMIM:2')
assert not updated_graph.has_node('NCBIGene:3')
assert not updated_graph.has_node('ENSEMBL:4')
assert updated_graph.has_node('HGNC:7')
def test_clique_merge9():
"""
Test for clique merge where same_as appear as both node and edge properties,
but an invalid node also has a same_as property and participates in same_as edge.
"""
ppm = {'biolink:Gene': ['HGNC', 'NCBIGene', 'ENSEMBL', 'OMIM']}
g1 = NxGraph()
g1.add_node('HGNC:1', **{'category': ['biolink:Gene']})
g1.add_node('OMIM:2', **{
'category': ['biolink:Disease'],
'same_as': ['HGNC:1']
})
g1.add_node('NCBIGene:3', **{'category': ['biolink:NamedThing']})
g1.add_node('ENSEMBL:4', **{
'category': ['biolink:Gene'],
'same_as': ['HGNC:1']
})
g1.add_node('ENSEMBL:6', **{
'category': ['biolink:Gene'],
'same_as': ['NCBIGene:8']
})
g1.add_node('HGNC:7', **{'category': ['biolink:Gene']})
g1.add_node('NCBIGene:8', **{'category': ['biolink:Gene']})
g1.add_edge('X:00001',
'OMIM:2',
edge_key=generate_edge_key('X:00001', 'biolink:same_as',
'OMIM:2'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('NCBIGene:3',
'HGNC:1',
edge_key=generate_edge_key('NCBIGene:3', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('ENSEMBL:6',
'NCBIGene:8',
edge_key=generate_edge_key('ENSEMBL:6', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('HGNC:7',
'NCBIGene:8',
edge_key=generate_edge_key('HGNC:7', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
updated_graph, clique_graph = clique_merge(target_graph=g1,
prefix_prioritization_map=ppm)
assert updated_graph.number_of_nodes() == 4
assert updated_graph.number_of_edges() == 1
assert updated_graph.has_node('HGNC:1')
assert updated_graph.has_node('HGNC:7')
n1 = updated_graph.nodes()['HGNC:1']
assert 'OMIM:2' not in n1['same_as']
assert 'NCBIGene:3' in n1['same_as']
assert 'ENSEMBL:4' in n1['same_as']
n2 = updated_graph.nodes()['HGNC:7']
assert 'ENSEMBL:6' in n2['same_as']
assert 'NCBIGene:8' in n2['same_as']
assert updated_graph.has_node('OMIM:2')
def test_generate_edge_key():
"""
Test generation of edge key via generate_edge_key method.
"""
key = generate_edge_key("S:CURIE", "related_to", "O:CURIE")
assert key == "S:CURIE-related_to-O:CURIE"
def triple(self, s: URIRef, p: URIRef, o: URIRef) -> None:
"""
Parse a triple.
Parameters
----------
s: URIRef
Subject
p: URIRef
Predicate
o: URIRef
Object
"""
self.count += 1
(element_uri, canonical_uri, predicate, property_name) = self.process_predicate(p)
if element_uri:
prop_uri = element_uri
elif predicate:
prop_uri = predicate
else:
prop_uri = property_name
s_curie = self.prefix_manager.contract(s)
if s_curie.startswith('biolink') or s_curie.startswith('OBAN'):
log.warning(f"Skipping {s} {p} {o}")
elif s_curie in self.reified_nodes:
# subject is a reified node
self.add_node_attribute(s, key=prop_uri, value=o)
elif p in self.reification_predicates:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif property_name in {'subject', 'predicate', 'object', 'predicate', 'relation'}:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif o in self.reification_types:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif element_uri and element_uri in self.node_property_predicates:
# treating predicate as a node property
self.add_node_attribute(s, key=prop_uri, value=o)
elif (
p in self.node_property_predicates
or predicate in self.node_property_predicates
or property_name in self.node_property_predicates
):
# treating predicate as a node property
self.add_node_attribute(s, key=prop_uri, value=o)
elif isinstance(o, rdflib.term.Literal):
self.add_node_attribute(s, key=prop_uri, value=o)
else:
# treating predicate as an edge
self.add_edge(s, o, p)
if len(self.edge_cache) >= self.CACHE_SIZE:
while self.reified_nodes:
n = self.reified_nodes.pop()
data = self.node_cache.pop(n)
try:
self.dereify(n, data)
except ValueError as e:
log.info(e)
self._incomplete_nodes[n] = data
for n in self._incomplete_nodes.keys():
self.node_cache[n] = self._incomplete_nodes[n]
self.reified_nodes.add(n)
self._incomplete_nodes.clear()
for k in self.edge_cache.keys():
if 'id' not in self.edge_cache[k] and 'association_id' not in self.edge_cache[k]:
edge_key = generate_edge_key(
self.edge_cache[k]['subject'],
self.edge_cache[k]['predicate'],
self.edge_cache[k]['object'],
)
self.edge_cache[k]['id'] = edge_key
data = self.edge_cache[k]
data = validate_edge(data)
data = sanitize_import(data)
if 'provided_by' in self.graph_metadata and 'provided_by' not in data.keys():
data['provided_by'] = self.graph_metadata['provided_by']
if self.check_edge_filter(data):
self.edge_properties.update(data.keys())
yield k[0], k[1], k[2], data
self.edge_cache.clear()
yield None
def test_clique_merge1():
"""
Test to perform a clique merge where all nodes in a clique are valid.
"""
ppm = {'biolink:Gene': ['HGNC', 'NCBIGene', 'ENSEMBL', 'OMIM']}
g1 = NxGraph()
g1.add_node('HGNC:1', **{'category': ['biolink:Gene']})
g1.add_node('OMIM:2', **{'category': ['biolink:Gene']})
g1.add_node('NCBIGene:3', **{'category': ['biolink:Gene']})
g1.add_node('ENSEMBL:4', **{'category': ['biolink:Gene']})
g1.add_node('ENSEMBL:6', **{'category': ['biolink:Gene']})
g1.add_node('HGNC:7', **{'category': ['biolink:Gene']})
g1.add_node('NCBIGene:8', **{'category': ['biolink:Gene']})
g1.add_edge('ENSEMBL:4',
'HGNC:1',
edge_key=generate_edge_key('ENSEMBL:4', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('NCBIGene:3',
'HGNC:1',
edge_key=generate_edge_key('NCBIGene:3', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('OMIM:2',
'HGNC:1',
edge_key=generate_edge_key('OMIM:2', 'biolink:same_as',
'HGNC:1'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('ENSEMBL:6',
'NCBIGene:8',
edge_key=generate_edge_key('ENSEMBL:6', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
g1.add_edge('HGNC:7',
'NCBIGene:8',
edge_key=generate_edge_key('HGNC:7', 'biolink:same_as',
'NCBIGene:8'),
**{
'predicate': 'biolink:same_as',
'relation': 'owl:equivalentClass'
})
updated_graph, clique_graph = clique_merge(target_graph=g1,
prefix_prioritization_map=ppm)
print_graph(updated_graph)
assert updated_graph.number_of_nodes() == 2
assert updated_graph.number_of_edges() == 0
assert updated_graph.has_node('HGNC:1')
assert updated_graph.has_node('HGNC:7')
n1 = updated_graph.nodes()['HGNC:1']
assert 'OMIM:2' in n1['same_as']
assert 'NCBIGene:3' in n1['same_as']
assert 'ENSEMBL:4' in n1['same_as']
n2 = updated_graph.nodes()['HGNC:7']
assert 'ENSEMBL:6' in n2['same_as']
assert 'NCBIGene:8' in n2['same_as']
assert not updated_graph.has_node('OMIM:2')
assert not updated_graph.has_node('NCBIGene:3')
assert not updated_graph.has_node('ENSEMBL:4')
assert not updated_graph.has_node('ENSEMBL:6')
assert not updated_graph.has_node('NCBIGene:8')
def remap_node_identifier(graph: nx.MultiDiGraph, category: str, alternative_property: str, prefix=None) -> nx.MultiDiGraph:
"""
Remap a node's 'id' attribute with value from a node's ``alternative_property`` attribute.
Parameters
----------
graph: networkx.MultiDiGraph
The graph
category: string
category referring to nodes whose 'id' needs to be remapped
alternative_property: string
property name from which the new value is pulled from
prefix: string
signifies that the value for ``alternative_property`` is a list
and the ``prefix`` indicates which value to pick from the list
Returns
-------
networkx.MultiDiGraph
The modified graph
"""
mapping = {}
for nid, data in graph.nodes(data=True):
node_data = data.copy()
if 'category' in node_data and category not in node_data['category']:
continue
if alternative_property in node_data:
alternative_values = node_data[alternative_property]
if isinstance(alternative_values, (list, set, tuple)):
if prefix:
for v in alternative_values:
if prefix in v:
# take the first occurring value that contains the given prefix
mapping[nid] = v
break
else:
# no prefix defined; pick the 1st one from list
mapping[nid] = alternative_values[0]
elif isinstance(alternative_values, str):
if prefix:
if alternative_values.startswith(prefix):
mapping[nid] = alternative_values
else:
# no prefix defined
mapping[nid] = alternative_values
else:
logging.error(f"Cannot use {alternative_values} from alternative_property {alternative_property}")
nx.set_node_attributes(graph, values=mapping, name='id')
nx.relabel_nodes(graph, mapping, copy=False)
# update 'subject' of all outgoing edges
update_edge_keys = {}
updated_subject_values = {}
updated_object_values = {}
for u, v, k, edge_data in graph.edges(keys=True, data=True):
if u is not edge_data['subject']:
updated_subject_values[(u, v, k)] = u
update_edge_keys[(u, v, k)] = generate_edge_key(u, edge_data['edge_label'], v)
if v is not edge_data['object']:
updated_object_values[(u, v, k)] = v
update_edge_keys[(u, v, k)] = generate_edge_key(u, edge_data['edge_label'], v)
nx.set_edge_attributes(graph, values=updated_subject_values, name='subject')
nx.set_edge_attributes(graph, values=updated_object_values, name='object')
nx.set_edge_attributes(graph, values=update_edge_keys, name='edge_key')
return graph
def load_edge(self, edge: Dict) -> Generator:
"""
Load an edge into an instance of BaseGraph
Parameters
----------
edge : Dict
An edge
Returns
-------
Generator
A generator for node and edge records
"""
(element_uri, canonical_uri, predicate,
property_name) = process_predicate(self.prefix_manager,
edge['predicate_id'],
self.predicate_mapping)
if element_uri:
edge_predicate = element_uri
elif predicate:
edge_predicate = predicate
else:
edge_predicate = property_name
if canonical_uri:
edge_predicate = element_uri
data = {
'subject': edge['subject_id'],
'predicate': edge_predicate,
'object': edge['object_id'],
}
del edge['predicate_id']
data = validate_edge(data)
subject_node = {}
object_node = {}
for k, v in edge.items():
if k in SSSOM_NODE_PROPERTY_MAPPING:
if k.startswith('subject'):
mapped_k = SSSOM_NODE_PROPERTY_MAPPING[k]
if mapped_k == 'category' and not PrefixManager.is_curie(
v):
v = f"biolink:OntologyClass"
subject_node[mapped_k] = v
elif k.startswith('object'):
mapped_k = SSSOM_NODE_PROPERTY_MAPPING[k]
if mapped_k == 'category' and not PrefixManager.is_curie(
v):
v = f"biolink:OntologyClass"
object_node[mapped_k] = v
else:
log.info(f"Ignoring {k} {v}")
else:
data[k] = v
objs = [self.load_node(subject_node), self.load_node(object_node)]
for k, v in self.graph_metadata.items():
if k not in {'curie_map'}:
data[k] = v
edge_data = sanitize_import(data.copy())
if 'subject' in edge_data and 'object' in edge_data:
if 'id' not in edge_data:
edge_data['id'] = generate_uuid()
s = edge_data['subject']
o = edge_data['object']
if 'provided_by' in self.graph_metadata and 'provided_by' not in edge_data.keys(
):
edge_data['provided_by'] = self.graph_metadata['provided_by']
key = generate_edge_key(s, edge_data['predicate'], o)
self.edge_properties.update(list(edge_data.keys()))
objs.append((s, o, key, edge_data))
else:
log.info(
"Ignoring edge with either a missing 'subject' or 'object': {}"
.format(edge_data))
for o in objs:
yield o
def test_generate_edge_key():
"""
Test generation of edge key via generate_edge_key method.
"""
key = generate_edge_key('S:CURIE', 'related_to', 'O:CURIE')
assert key == 'S:CURIE-related_to-O:CURIE'
def remap_node_identifier(
graph: BaseGraph, category: str, alternative_property: str, prefix=None
) -> BaseGraph:
"""
Remap a node's 'id' attribute with value from a node's ``alternative_property`` attribute.
Parameters
----------
graph: kgx.graph.base_graph.BaseGraph
The graph
category: string
category referring to nodes whose 'id' needs to be remapped
alternative_property: string
property name from which the new value is pulled from
prefix: string
signifies that the value for ``alternative_property`` is a list
and the ``prefix`` indicates which value to pick from the list
Returns
-------
kgx.graph.base_graph.BaseGraph
The modified graph
"""
mapping: Dict = {}
for nid, data in graph.nodes(data=True):
node_data = data.copy()
if "category" in node_data and category not in node_data["category"]:
continue
if alternative_property in node_data:
alternative_values = node_data[alternative_property]
if isinstance(alternative_values, (list, set, tuple)):
if prefix:
for v in alternative_values:
if prefix in v:
# take the first occurring value that contains the given prefix
mapping[nid] = {"id": v}
break
else:
# no prefix defined; pick the 1st one from list
mapping[nid] = {"id": next(iter(alternative_values))}
elif isinstance(alternative_values, str):
if prefix:
if alternative_values.startswith(prefix):
mapping[nid] = {"id": alternative_values}
else:
# no prefix defined
mapping[nid] = {"id": alternative_values}
else:
log.error(
f"Cannot use {alternative_values} from alternative_property {alternative_property}"
)
graph.set_node_attributes(graph, attributes=mapping)
graph.relabel_nodes(graph, {k: list(v.values())[0] for k, v in mapping.items()})
# update 'subject' of all outgoing edges
update_edge_keys = {}
updated_subject_values = {}
updated_object_values = {}
for u, v, k, edge_data in graph.edges(data=True, keys=True):
if u is not edge_data["subject"]:
updated_subject_values[(u, v, k)] = {"subject": u}
update_edge_keys[(u, v, k)] = {
"edge_key": generate_edge_key(u, edge_data["predicate"], v)
}
if v is not edge_data["object"]:
updated_object_values[(u, v, k)] = {"object": v}
update_edge_keys[(u, v, k)] = {
"edge_key": generate_edge_key(u, edge_data["predicate"], v)
}
graph.set_edge_attributes(graph, attributes=updated_subject_values)
graph.set_edge_attributes(graph, attributes=updated_object_values)
graph.set_edge_attributes(graph, attributes=update_edge_keys)
return graph
def triple(self, s: URIRef, p: URIRef, o: URIRef) -> None:
"""
Parse a triple.
Parameters
----------
s: URIRef
Subject
p: URIRef
Predicate
o: URIRef
Object
"""
self.count += 1
(element_uri, canonical_uri, predicate,
property_name) = self.process_predicate(p)
if element_uri:
prop_uri = element_uri
elif predicate:
prop_uri = predicate
else:
prop_uri = property_name
s_curie = self.prefix_manager.contract(s)
if s_curie.startswith("biolink") or s_curie.startswith("OBAN"):
log.warning(f"Skipping {s} {p} {o}")
elif s_curie in self.reified_nodes:
# subject is a reified node
self.add_node_attribute(s, key=prop_uri, value=o)
elif p in self.reification_predicates:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif property_name in {
"subject",
"predicate",
"object",
"predicate",
"relation",
}:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif o in self.reification_types:
# subject is a reified node
self.reified_nodes.add(s_curie)
self.add_node_attribute(s, key=prop_uri, value=o)
elif element_uri and element_uri in self.node_property_predicates:
# treating predicate as a node property
self.add_node_attribute(s, key=prop_uri, value=o)
elif (p in self.node_property_predicates
or predicate in self.node_property_predicates
or property_name in self.node_property_predicates):
# treating predicate as a node property
self.add_node_attribute(s, key=prop_uri, value=o)
elif isinstance(o, rdflib.term.Literal):
self.add_node_attribute(s, key=prop_uri, value=o)
else:
# treating predicate as an edge
self.add_edge(s, o, p)
if len(self.edge_cache) >= self.CACHE_SIZE:
while self.reified_nodes:
n = self.reified_nodes.pop()
data = self.node_cache.pop(n)
try:
self.dereify(n, data)
except ValueError as e:
self.owner.log_error(
entity=str(data),
error_type=ErrorType.INVALID_EDGE_PROPERTY,
message=str(e),
message_level=MessageLevel.WARNING)
self._incomplete_nodes[n] = data
for n in self._incomplete_nodes.keys():
self.node_cache[n] = self._incomplete_nodes[n]
self.reified_nodes.add(n)
self._incomplete_nodes.clear()
for k in self.edge_cache.keys():
if ("id" not in self.edge_cache[k]
and "association_id" not in self.edge_cache[k]):
edge_key = generate_edge_key(
self.edge_cache[k]["subject"],
self.edge_cache[k]["predicate"],
self.edge_cache[k]["object"],
)
self.edge_cache[k]["id"] = edge_key
data = self.edge_cache[k]
data = self.validate_edge(data)
data = sanitize_import(data)
self.set_edge_provenance(data)
if self.check_edge_filter(data):
self.edge_properties.update(data.keys())
yield k[0], k[1], k[2], data
self.edge_cache.clear()
yield None
def add_edge(
self,
subject_iri: URIRef,
object_iri: URIRef,
predicate_iri: URIRef,
data: Optional[Dict[Any, Any]] = None,
) -> Dict:
"""
Add an edge to cache.
Parameters
----------
subject_iri: rdflib.URIRef
Subject IRI for the subject in a triple
object_iri: rdflib.URIRef
Object IRI for the object in a triple
predicate_iri: rdflib.URIRef
Predicate IRI for the predicate in a triple
data: Optional[Dict[Any, Any]]
Additional edge properties
Returns
-------
Dict
The edge data
"""
(element_uri, canonical_uri, predicate, property_name) = self.process_predicate(
predicate_iri
)
subject_curie = self.prefix_manager.contract(subject_iri)
object_curie = self.prefix_manager.contract(object_iri)
if subject_curie in self.node_cache:
subject_node = self.node_cache[subject_curie]
else:
subject_node = self.add_node(subject_iri)
if object_curie in self.node_cache:
object_node = self.node_cache[object_curie]
else:
object_node = self.add_node(object_iri)
edge_predicate = element_uri if element_uri else predicate
if not edge_predicate:
edge_predicate = property_name
if ' ' in edge_predicate:
log.debug(
f"predicate IRI '{predicate_iri}' yields edge_predicate '{edge_predicate}' that not in snake_case form; replacing ' ' with '_'"
)
edge_predicate_prefix = self.prefix_manager.get_prefix(edge_predicate)
if edge_predicate_prefix not in {'biolink', 'rdf', 'rdfs', 'skos', 'owl'}:
if PrefixManager.is_curie(edge_predicate):
# name = curie_lookup(edge_predicate)
# if name:
# log.debug(f"predicate IRI '{predicate_iri}' yields edge_predicate '{edge_predicate}' that is actually a CURIE; Using its mapping instead: {name}")
# edge_predicate = f"{edge_predicate_prefix}:{name}"
# else:
# log.debug(f"predicate IRI '{predicate_iri}' yields edge_predicate '{edge_predicate}' that is actually a CURIE; defaulting back to {self.DEFAULT_EDGE_PREDICATE}")
edge_predicate = DEFAULT_EDGE_PREDICATE
edge_key = generate_edge_key(subject_node['id'], edge_predicate, object_node['id'])
if (subject_node['id'], object_node['id'], edge_key) in self.edge_cache:
# edge already exists; process kwargs and update the edge
edge_data = self.update_edge(subject_node['id'], object_node['id'], edge_key, data)
else:
# add a new edge
edge_data = data if data else {}
edge_data.update(
{
'subject': subject_node['id'],
'predicate': f"{edge_predicate}",
'object': object_node['id'],
}
)
if 'relation' not in edge_data:
edge_data['relation'] = predicate
if 'provided_by' in self.graph_metadata and 'provided_by' not in edge_data:
edge_data['provided_by'] = self.graph_metadata['provided_by']
self.edge_cache[(subject_node['id'], object_node['id'], edge_key)] = edge_data
return edge_data
def load_edge(self, edge: Dict) -> Generator:
"""
Load an edge into an instance of BaseGraph
Parameters
----------
edge : Dict
An edge
Returns
-------
Generator
A generator for node and edge records
"""
(element_uri, canonical_uri, predicate, property_name) = process_predicate(
self.prefix_manager, edge["predicate_id"], self.predicate_mapping
)
if element_uri:
edge_predicate = element_uri
elif predicate:
edge_predicate = predicate
else:
edge_predicate = property_name
if canonical_uri:
edge_predicate = element_uri
data = {
"subject": edge["subject_id"],
"predicate": edge_predicate,
"object": edge["object_id"],
}
del edge["predicate_id"]
data = self.validate_edge(data)
if not data:
return # ?
subject_node = {}
object_node = {}
for k, v in edge.items():
if k in SSSOM_NODE_PROPERTY_MAPPING:
if k.startswith("subject"):
mapped_k = SSSOM_NODE_PROPERTY_MAPPING[k]
if mapped_k == "category" and not PrefixManager.is_curie(v):
v = f"biolink:OntologyClass"
subject_node[mapped_k] = v
elif k.startswith("object"):
mapped_k = SSSOM_NODE_PROPERTY_MAPPING[k]
if mapped_k == "category" and not PrefixManager.is_curie(v):
v = f"biolink:OntologyClass"
object_node[mapped_k] = v
else:
log.info(f"Ignoring {k} {v}")
else:
data[k] = v
subject_node = self.load_node(subject_node)
object_node = self.load_node(object_node)
if not (subject_node and object_node):
return # ?
objs = [subject_node, object_node]
for k, v in self.graph_metadata.items():
if k not in {"curie_map"}:
data[k] = v
edge_data = sanitize_import(data.copy())
if "subject" in edge_data and "object" in edge_data:
if "id" not in edge_data:
edge_data["id"] = generate_uuid()
s = edge_data["subject"]
o = edge_data["object"]
self.set_edge_provenance(edge_data)
key = generate_edge_key(s, edge_data["predicate"], o)
self.edge_properties.update(list(edge_data.keys()))
objs.append((s, o, key, edge_data))
else:
self.owner.log_error(
entity=str(edge_data),
error_type=ErrorType.MISSING_NODE,
message="Ignoring edge with either a missing 'subject' or 'object'",
message_level=MessageLevel.WARNING
)
for o in objs:
yield o
def consolidate_edges(self) -> nx.MultiDiGraph:
"""
Move all edges from nodes in a clique to the clique leader.
Returns
-------
nx.MultiDiGraph
The target graph where all edges from nodes in a clique are moved to clique leader
"""
cliques = list(nx.connected_components(self.clique_graph))
for clique in cliques:
logging.info("processing clique: {}".format(clique))
leader = [x for x in clique if LEADER_ANNOTATION in self.clique_graph.nodes[x] and self.clique_graph.nodes[x][LEADER_ANNOTATION]]
if len(leader) == 0:
logging.debug("No leader for clique {}; skipping".format(clique))
continue
else:
leader = leader[0]
nx.set_node_attributes(self.target_graph, {leader: {LEADER_ANNOTATION: self.clique_graph.nodes[leader].get(LEADER_ANNOTATION), 'election_strategy': self.clique_graph.nodes[leader].get('election_strategy')}})
for node in clique:
if node == leader:
continue
in_edges = self.target_graph.in_edges(node, True)
filtered_in_edges = [x for x in in_edges if x[2]['edge_label'] != SAME_AS]
equiv_in_edges = [x for x in in_edges if x[2]['edge_label'] == SAME_AS]
logging.debug("Moving {} in-edges from {} to {}".format(len(in_edges), node, leader))
for u, v, edge_data in filtered_in_edges:
key = generate_edge_key(u, edge_data['edge_label'], v)
self.target_graph.remove_edge(u, v, key=key)
edge_data['_original_subject'] = edge_data['subject']
edge_data['_original_object'] = edge_data['object']
edge_data['object'] = leader
key = generate_edge_key(u, edge_data['edge_label'], leader)
self.target_graph.add_edge(edge_data['subject'], edge_data['object'], key, **edge_data)
out_edges = self.target_graph.out_edges(node, True)
filtered_out_edges = [x for x in out_edges if x[2]['edge_label'] != SAME_AS]
equiv_out_edges = [x for x in out_edges if x[2]['edge_label'] == SAME_AS]
logging.debug("Moving {} out-edges from {} to {}".format(len(out_edges), node, leader))
for u, v, edge_data in filtered_out_edges:
key = generate_edge_key(u, edge_data['edge_label'], v)
self.target_graph.remove_edge(u, v, key=key)
edge_data['_original_subject'] = edge_data['subject']
edge_data['_original_object'] = edge_data['object']
edge_data['subject'] = leader
key = generate_edge_key(leader, edge_data['edge_label'], v)
self.target_graph.add_edge(edge_data['subject'], edge_data['object'], key, **edge_data)
aliases = self.target_graph.nodes[leader].get('aliases') if 'aliases' in self.target_graph.nodes[leader] else []
for u, v, edge_data in equiv_in_edges:
if u != leader:
aliases.append(u)
if v != leader:
aliases.append(v)
self.target_graph.remove_edge(u, v, key=generate_edge_key(u, SAME_AS, v))
logging.debug("equiv out edges: {}".format(equiv_out_edges))
for u, v, edge_data in equiv_out_edges:
if u != leader:
logging.debug("{} is an alias of leader {}".format(u, leader))
aliases.append(u)
if v != leader:
logging.debug("{} is an alias of leader {}".format(v, leader))
aliases.append(v)
self.target_graph.remove_edge(u, v, key=generate_edge_key(u, SAME_AS, v))
# set aliases for leader
nx.set_node_attributes(self.target_graph, {leader: {'aliases': aliases}})
# remove all node instances of aliases
self.target_graph.remove_nodes_from(aliases)
return self.target_graph
def test_clique_merge7():
"""
Test for clique merge where each clique has a node that has
a disjoint category from other nodes in a clique and the node is
not a participant in same_as edges.
"""
ppm = {"biolink:Gene": ["HGNC", "NCBIGene", "ENSEMBL", "OMIM"]}
g1 = NxGraph()
g1.add_node("HGNC:1", **{"category": ["biolink:Gene"]})
g1.add_node("OMIM:2", **{"category": ["biolink:Disease"]})
g1.add_node("NCBIGene:3", **{"category": ["biolink:NamedThing"]})
g1.add_node("ENSEMBL:4", **{"category": ["biolink:Gene"]})
g1.add_node("ENSEMBL:6", **{"category": ["biolink:Gene"]})
g1.add_node("HGNC:7", **{"category": ["biolink:Disease"]})
g1.add_node("NCBIGene:8", **{"category": ["biolink:Gene"]})
g1.add_edge(
"ENSEMBL:4",
"HGNC:1",
edge_key=generate_edge_key("ENSEMBL:4", "biolink:same_as", "HGNC:1"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"NCBIGene:3",
"HGNC:1",
edge_key=generate_edge_key("NCBIGene:3", "biolink:same_as", "HGNC:1"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"OMIM:2",
"HGNC:1",
edge_key=generate_edge_key("OMIM:2", "biolink:same_as", "HGNC:1"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"ENSEMBL:6",
"NCBIGene:8",
edge_key=generate_edge_key("ENSEMBL:6", "biolink:same_as", "NCBIGene:8"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
g1.add_edge(
"HGNC:7",
"NCBIGene:8",
edge_key=generate_edge_key("HGNC:7", "biolink:same_as", "NCBIGene:8"),
**{"predicate": "biolink:same_as", "relation": "owl:equivalentClass"}
)
updated_graph, clique_graph = clique_merge(
target_graph=g1, prefix_prioritization_map=ppm
)
assert updated_graph.number_of_nodes() == 4
assert updated_graph.number_of_edges() == 2
assert updated_graph.has_node("HGNC:1")
assert updated_graph.has_node("NCBIGene:8")
n1 = updated_graph.nodes()["HGNC:1"]
assert "NCBIGene:3" in n1["same_as"]
assert "ENSEMBL:4" in n1["same_as"]
assert "OMIM:2" not in n1["same_as"]
n2 = updated_graph.nodes()["NCBIGene:8"]
assert "ENSEMBL:6" in n2["same_as"]
assert updated_graph.has_node("OMIM:2")
assert not updated_graph.has_node("NCBIGene:3")
assert not updated_graph.has_node("ENSEMBL:4")
assert updated_graph.has_node("HGNC:7")
