def load_slim(self, module: Module, slim_url: str, slim_cache_path: str):
if slim_url and slim_cache_path:
relations = None
if module == Module.GO:
relations = self.go_relations
elif module == Module.DO_EXPERIMENTAL:
relations = self.do_relations
elif module == Module.EXPRESSION:
relations = None
slim_onto = OntologyFactory().create(
self._get_cached_file(file_source_url=slim_url,
cache_path=slim_cache_path)).subontology(
relations=relations)
slim_set = set([
node for node in slim_onto.nodes()
if "type" in slim_onto.node(node)
and slim_onto.node(node)["type"] == "CLASS"
])
if module == Module.GO:
logger.info("Setting GO Slim")
self.go_slim = slim_set
elif module == Module.DO_EXPERIMENTAL:
logger.info("Setting DO Slim")
self.do_slim = slim_set
elif module == Module.EXPRESSION:
logger.info("Setting Expression Slim")
self.exp_slim = slim_set
def test_semsearch():
afa = AssociationSetFactory()
f = POMBASE
ont = OntologyFactory().create(ONT)
parser = GafParser()
assocs = parser.parse(POMBASE, skipheader=True)
assocs = [a for a in assocs if a['subject']['label'] in GENES]
aset = afa.create_from_assocs(assocs, ontology=ont)
ont = aset.subontology()
aset.ontology = ont
logging.info('Genes={} Terms={}'.format(len(aset.subjects),
len(ont.nodes())))
print('STATS={}'.format(aset.as_dataframe().describe()))
#genes = aset.subjects[0:5]
sse = SemSearchEngine(assocmodel=aset)
logging.info('Calculating all MICAs')
sse.calculate_all_micas()
#h5path = 'tests/resources/mica_ic.h5'
#logging.info('Saving to {}'.format(h5path))
#sse.mica_ic_df.to_hdf(h5path, key='mica_ic', mode='w')
#logging.info('Saved to {}'.format(h5path))
logging.info('Doing pairwise')
for i in aset.subjects:
for j in aset.subjects:
sim = sse.pw_score_cosine(i, j)
#print('{} x {} = {}'.format(i,j,sim))
if i == j:
assert (sim > 0.9999)
tups = sse.pw_score_resnik_bestmatches(i, j)
print('{} x {} = {} // {}'.format(i, j, sim, tups))