def extract_subgraph(self, ids=[], relationshipType='subClassOf'):
"""
Returns subgraph module extracted using list of node IDs as seed
"""
g=BBOPGraph()
visited=[]
while len(ids)>0:
id = ids.pop()
nextg = self.neighbors(id, blankNodes=False, relationshipType=relationshipType, direction='OUTGOING',depth=1)
for edge in nextg.edges:
next_id = edge.obj
if next_id not in visited:
ids.append(next_id)
visited.append(next_id)
g.merge(nextg)
return g
def cbd(self, id=None):
"""
Returns the Concise Bounded Description of a node
See https://www.w3.org/Submission/CBD/
"""
nodes = [id]
g=BBOPGraph()
while len(nodes)>0:
n = nodes.pop()
nextg = self.neighbors(n, params={'blankNodes':True, 'direction':'OUTGOING','depth':1})
for nn in nextg.nodes:
if nn.id.startswith("_:"):
n.append(nn.id)
g.merge(nextg)
return g
def neighbors(self, id=None, **params):
"""
Get neighbors of a node
parameters are directly passed through to SciGraph: e.g. depth, relationshipType
Returns a BBOPGraph
"""
response = self.get_response("graph/neighbors", id, "json", **params)
return BBOPGraph(response.json())
def bioobject(self, id, node_type=None, class_name='BioObject', **params):
"""
Get a node in a graph and translates it to biomodels datamodel
Arguments
---------
id
identifier or CURIE
class_name
name of the class in the biomodel data model to instantiate
Returns: biomodel.BioObject or subclass
"""
bio_object = self.get_clique_leader(id)
# get nodes connected with edge 'in_taxon'
response = self.get_response(
"graph/neighbors",
q=bio_object.id,
format="json",
depth=1,
relationshipType=IN_TAXON,
direction="OUTGOING"
)
graph = BBOPGraph(response.json())
bio_object.taxon = None
for tax_edge in graph.edges:
bio_object.taxon = self.make_NamedObject(
**graph.get_node(tax_edge.obj).as_dict()
)
# Type specific
if node_type == 'disease':
# get nodes connected with edge 'has_disposition'
response = self.get_response(
"graph/neighbors",
q=bio_object.id,
format="json",
depth=1,
relationshipType=HAS_DISPOSITION,
direction="OUTGOING"
)
graph = BBOPGraph(response.json())
bio_object.inheritance = []
bio_object.clinical_modifiers = []
for disposition_edge in graph.edges:
disposition = graph.get_node(disposition_edge.obj)
if 'inheritance' in disposition.meta.category_list:
bio_object.inheritance.append(
self.make_NamedObject(**disposition.as_dict())
)
else:
bio_object.clinical_modifiers.append(
self.make_NamedObject(**disposition.as_dict())
)
return bio_object
def neighbors(self, id=None, **params):
"""
Get neighbors of a node
parameters are directly passed through to SciGraph: e.g. depth, relationshipType
Returns a BBOPGraph
"""
response = self.get_response("graph/neighbors", id, "json", **params)
if response.status_code == 404:
raise NoResultFoundException('SciGraph graph/neighbors yields no result for {}'.format(id))
return BBOPGraph(response.json())