def __init__(self, graph, outfile):
self.outfile = outfile
self.graph = graph
self.network = nx.MultiDiGraph()
edge_labels = set()
# iterate through rdf triples and add to the network graph
# NOTE: could also iterate through the graph by contexts...
for cx in self.graph.contexts():
for triple in cx.triples((None, None, None)):
subj, pred, obj = triple
# NOTE: skipping rdf sequences here because treating
# as normal triples makes for weird results
if pred == rdflib.RDF.first or pred == rdflib.RDF.rest:
continue
# make sure subject and object are added to the graph as nodes,
# if appropriate
self._add_nodes(triple)
# get the short-hand name for property or edge label
name = self._edge_label(pred)
# if the object is a literal, add it to the node as a property of the subject
if subj in self.network and isinstance(obj, rdflib.Literal) \
or pred == rdflib.RDF.type:
if pred == rdflib.RDF.type:
ns, val = rdflib.namespace.split_uri(obj)
# special case (for now)
if val == 'Manuscript' and isinstance(cx.value(subj, rdfns.DC.title), rdflib.BNode):
val = 'BelfastGroupSheet'
else:
val = unicode(obj)
self.network.node[self._uri_to_node_id(subj)][name] = normalize_whitespace(val)
# otherwise, add an edge between the two resource nodes
else:
# NOTE: gephi doesn't support multiple edges, and
# the d3/json output probably elides them also.
# Consider instead: if an edge already exists,
# add to the strength of the exesting edge
edge_labels.add(name)
self.network.add_edge(self._uri_to_node_id(subj),
self._uri_to_node_id(obj),
label=name,
weight=connection_weights.get(name, 1))
print '%d nodes, %d edges in full network' % \
(self.network.number_of_nodes(), self.network.number_of_edges())
# TODO: useful for verbose output? (also report on relations with no weight?)
#print 'edge labels: %s' % ', '.join(edge_labels)
gexf.write_gexf(self.network, self.outfile)
def _node_label(self, res):
# NOTE: consider adding/calculating a preferredlabel
# for important nodes in our data
name = None
# *first* use preferred label if available
names = self.graph.preferredLabel(res)
# returns list of labelprop (preflabel or label), value
# if we got any matches, grab the first value
if names:
name = names[0][1]
# second check for schema.org name, if we have one
if not name:
name = self.graph.value(res, rdfns.SCHEMA_ORG.name)
if name:
return normalize_whitespace(name)
title = self.graph.value(res, rdfns.DC.title)
if title:
# if title is a bnode, convert from list/collection
if isinstance(title, rdflib.BNode):
title_list = RdfCollection(self.graph, title)
title = 'Group sheet: ' + '; '.join(title_list)
# truncate list if too long
if len(title) > 50:
title = title[:50] + ' ...'
# otherwise, title should be a literal (no conversion needed)
return normalize_whitespace(title)
# as a fall-back, use type for a label
type = self.graph.value(res, rdflib.RDF.type)
if type:
ns, short_type = rdflib.namespace.split_uri(type)
return short_type
