def merge(inputs, output):
"""
Loads a series of knowledge graphs and merges cliques using `same_as` edges
as well as `same_as` node properties. The resulting graph will not have any
`same_as` edges, and the remaining clique leader nodes will have all
equivalent identifiers in their `same_as` property.
"""
transformers = []
output_transformer = get_transformer(get_type(output))()
graph = None
for path in inputs:
construct = get_transformer(get_type(path))
if construct is None:
raise Exception('No transformer for {}'.format(path))
transformers.append(construct())
for transformer, path in zip(transformers, inputs):
if graph is None:
graph = transformer.graph
else:
transformer.graph = graph
transformer.parse(path)
output_transformer.graph = graph
output_transformer.graph = clique_merge(output_transformer.graph)
output_transformer.save(output)
from kgx import JsonTransformer, clique_merge
t = JsonTransformer()
t.parse('results/hp.owl')
t.parse('results/mondo.json')
t.parse('results/hgnc.json')
t.parse('results/clinvar.json')
t.parse('results/omim.json')
t.parse('results/hpoa.json')
t.parse('results/orphanet.json')
#t = PandasTransformer(t.graph)
#t.parse('data/semmeddb_edges.csv')
#t.parse('data/semmeddb_nodes.csv')
t.graph = clique_merge(t.graph)
t.save('results/clique_merged.json')