def test_owlsim_singleton(self):
"""
test that two calls to get_owlsim_api()
get the same object
"""
foo = get_owlsim_api()
bar = get_owlsim_api()
assert foo is bar
class AnnotationScore(Resource):
annotation_scorer = AnnotationScorer(get_owlsim_api())
@api.expect(sufficiency_input)
@api.marshal_with(sufficiency_output)
def post(self):
"""
Get annotation score
"""
data = request.json
phenotypes = [
feature['id'] for feature in data['features']
if feature['isPresent'] is True
]
absent_phenotypes = [
feature['id'] for feature in data['features']
if feature['isPresent'] is False
]
return AnnotationScore.annotation_scorer.get_annotation_sufficiency(
profile=phenotypes, negated_classes=absent_phenotypes)
@api.expect(score_get)
@api.marshal_with(sufficiency_output)
def get(self):
"""
Get annotation score
"""
input_args = score_get.parse_args()
return AnnotationScore.annotation_scorer.get_annotation_sufficiency(
profile=input_args['id'], negated_classes=input_args['absent_id'])
class SimSearch(Resource):
sim_engine = PhenoSimEngine(get_owlsim_api())
@api.expect(sim_search_parser)
@api.marshal_with(sim_result)
def get(self):
"""
Search for phenotypically similar diseases or model genes
"""
input_args = sim_search_parser.parse_args()
return SimCompare.sim_engine.search(
id_list=input_args['id'],
limit=input_args['limit'],
taxon_filter=input_args['taxon'],
method=SimAlgorithm(input_args['metric']),
is_feature_set=input_args['is_feature_set']
)
class SimCompare(Resource):
sim_engine = PhenoSimEngine(get_owlsim_api())
@api.expect(compare_input)
@api.marshal_with(sim_result)
def post(self):
"""
Compare a reference profile vs one or more profiles
"""
data = request.json
if 'metric' not in data:
data['metric'] = 'phenodigm'
if 'is_feature_set' not in data:
data['is_feature_set'] = True
return SimCompare.sim_engine.compare(
reference_ids=data['reference_ids'],
query_profiles=data['query_ids'],
method=SimAlgorithm(data['metric']),
is_feature_set=data['is_feature_set']
)
@api.expect(sim_compare_parser)
@api.marshal_with(sim_result)
def get(self):
"""
Compare a reference profile vs one profiles
"""
input_args = sim_compare_parser.parse_args()
return SimCompare.sim_engine.compare(
reference_ids=input_args['ref_id'],
query_profiles=[input_args['query_id']],
method=SimAlgorithm(input_args['metric']),
is_feature_set = input_args['is_feature_set']
)
from dataclasses import asdict
from flask_restplus import Resource
from flask import request, make_response
from marshmallow import ValidationError
from biolink.api.restplus import api
from biolink.api.sim.endpoints.owlsim import get_owlsim_api
from biolink.datamodel.mme_serializers import mme_request_marshmallow
from biolink.datamodel.serializers import mme
from ontobio.sim.mme import query_owlsim
from ontobio.sim.phenosim_engine import PhenoSimEngine
sim_engine = PhenoSimEngine(get_owlsim_api())
def get_mme_response(data, taxon: str = None):
try:
mme_request = mme_request_marshmallow.load(data)
except ValidationError as err:
return {
'error': {
'message': f'missing/invalid data {err}',
'code': 400
}
}, 400
match_data = query_owlsim(mme_request, sim_engine, taxon=taxon)