def build_onehop_query(
q_object_category,
q_subject_category,
q_subject=None,
q_object=None,
genes=None,
drugs=None,
outcome=None,
outcome_name=None,
outcome_op=None,
outcome_value=None,
disease=None,
trapi_version='1.1',
biolink_version=None,
):
# Initialize query
message = Message(trapi_version, biolink_version)
q = message.query_graph
# Add nodes
subject_node = q.add_node(q_subject, q_subject_category)
object_node = q.add_node(q_object, q_object_category)
# Add edge
try:
edge_predicate = SUBJECT_TO_OBJECT_PREDICATE_MAP[q_subject_category[0]][q_object_category[0]]
except KeyError:
raise QueryBuildError('Edge from {} to {} is not supported.'.format(q_subject_category, q_object_category))
edge_id = q.add_edge(subject_node, object_node, edge_predicate)
# Add constraints
if outcome is not None:
q.add_constraint('predicate_proxy', 'CHP:PredicateProxy', '==', [outcome], edge_id=edge_id)
q.add_constraint(outcome, outcome, outcome_op, outcome_value, edge_id=edge_id)
# Get context
context = []
if genes is not None:
context.append(BIOLINK_GENE)
if drugs is not None:
context.append(BIOLINK_DRUG)
if disease is not None:
context.append(BIOLINK_DISEASE)
# Process context
if len(context) > 0:
q.add_constraint('predicate_context', 'CHP:PredicateContext', '==', context, edge_id=edge_id)
if genes is not None:
q.add_constraint(BIOLINK_GENE, BIOLINK_GENE, 'matches', genes, edge_id=edge_id)
if drugs is not None:
q.add_constraint(BIOLINK_DRUG, BIOLINK_DRUG, 'matches', drugs, edge_id=edge_id)
if disease is not None:
q.add_constraint(BIOLINK_DISEASE, BIOLINK_DISEASE, 'matches', disease, edge_id=edge_id)
query = Query(trapi_version=trapi_version, biolink_version=biolink_version)
query.message = message
return query
def test_ars_predicates_queries(self):
ars_predicates_dir = os.path.join(self.ncats_test_dir,
'ars-requests/predicates')
# Added supported Query filenames to list below:
supported_query_filenames = [
'conditionGene.json',
'geneCondition.json',
]
# Run tests
for filename in supported_query_filenames:
filepath = os.path.join(ars_predicates_dir, filename)
query = Query('1.0').load(query_filepath=filepath)
print(json.dumps(query.to_dict(), indent=2))
def test_batch_drug_wildcard_query(self):
for trapi_version, queries in self.drug_batch_queries.items():
query = Query.load(trapi_version, None, query=queries[0])
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_simple_batch_query(self):
# These are simple queries
logger.info('Running batch simple query test.')
for trapi_version, queries in self.batch_queries.items():
query = Query.load(trapi_version, None, query=queries[0])
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_simple_single_query(self):
# This is a simple query
logger.info('Running single simple query test.')
for trapi_version, queries in self.queries.items():
query = Query.load(trapi_version, None, query=queries[1])
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_wildcard_batch_onehop_query(self):
for trapi_version, queries in self.wildcard_batch_queries.items():
for name, query_dict in queries.items():
#if name != 'gene_to_disease_proxy_context':
# continue
query = Query.load(trapi_version, None, query=query_dict)
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_inverse_wildcard_query(self):
for trapi_version, queries in self.gene_queries.items():
query = Query.load(trapi_version, None, query=queries[0])
for edge_id, edge in query.message.query_graph.edges.items():
predicate = edge.predicates[0]
inverse = edge.predicates[0].get_inverse()
edge.set_predicates(inverse)
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_inverse_query(self):
# This is a simple query
logger.info('Running default inverse query test.')
for trapi_version, queries in self.queries.items():
query = Query.load(trapi_version, None, query=queries[1])
for edge_id, edge in query.message.query_graph.edges.items():
predicate = edge.predicates[0]
inverse = edge.predicates[0].get_inverse()
edge.set_predicates(inverse)
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def process_request(self, request, trapi_version):
""" Helper function that extracts the query from the message.
"""
logger.info('Starting query.')
query = Query.load(self.trapi_version,
biolink_version=None,
query=request.data)
# Setup query in Base Processor
self.setup_query(query)
logger.info('Query loaded')
return query
def test_inverse_onehop_query(self):
for trapi_version, queries in self.standard_single_queries.items():
for name, query_dict in queries.items():
#if name != 'gene_to_disease_proxy_context':
# continue
query = Query.load(trapi_version, None, query=query_dict)
for edge_id, edge in query.message.query_graph.edges.items():
predicate = edge.predicates[0]
inverse = edge.predicates[0].get_inverse()
if inverse is not None:
edge.set_predicates(inverse)
interface = TrapiInterface(query=query)
interface.build_chp_queries()
interface.run_chp_queries()
response = interface.construct_trapi_response()
def test_ars_notnone_queries(self):
from trapi_model.query import Query
from trapi_model.exceptions import UnknownBiolinkEntity
ars_predicates_dir = os.path.join(self.ncats_test_dir,
'ars-requests/not-none')
# Run tests
for filename in os.listdir(ars_predicates_dir):
try:
if os.path.splitext(filename)[-1] == '.json':
filepath = os.path.join(ars_predicates_dir, filename)
query = Query.load('1.0', None, query_filepath=filepath)
query_dict = query.to_dict()
if query.is_batch_query():
batch = query.expand_batch_query()
except UnknownBiolinkEntity as ex:
logger.critical('Failed on file {} with {}'.format(
filename, ex.message))
def get_responses(self, queries=None, trapi_queries=None):
# Initialize interface
interface = TrapiInterface(
bkb_handler=self.bkb_handler,
dynamic_reasoner=self.dynamic_reasoner,
joint_reasoner=self.joint_reasoner,
)
# Load queries
if trapi_queries is None:
trapi_queries = [
Query.load(query["trapi_version"], None, query=query)
for query in queries
]
# Process trapi query
interface.setup_trapi_queries(trapi_queries)
# Build CHP queries
interface.build_chp_queries()
# Run CHP queries
interface.run_chp_queries()
# Get Responses
responses = interface.construct_trapi_responses()
return responses
def test_inverse_query(self):
standard_queries = copy.deepcopy(self.standard_queries)
descriptions = [
query.pop("test_description", None)
for query in self.standard_queries
]
# Make inverse queries
trapi_queries = [
Query.load(query["trapi_version"], None, query=query)
for query in standard_queries
]
for query in trapi_queries:
for edge_id, edge in query.message.query_graph.edges.items():
predicate = edge.predicates[0]
inverse = edge.predicates[0].get_inverse()
if inverse is not None:
edge.set_predicates(inverse)
# Switch subject and object
edge_subject = copy.deepcopy(edge.subject)
edge_object = copy.deepcopy(edge.object)
edge.subject = edge_object
edge.object = edge_subject
responses = self.get_responses(trapi_queries=trapi_queries)
def build_standard_query(
genes=None,
drugs=None,
outcome=None,
outcome_name=None,
outcome_op=None,
outcome_value=None,
disease=None,
trapi_version='1.1',
biolink_version=None,
batch_genes=None,
batch_drugs=None,
batch_diseases=None,
):
if outcome is None:
raise QueryBuildError('You must specify an outcome CURIE.')
if outcome_op is None:
raise QueryBuildError("You must specify an outcome operation consistent with \
with your desired TRAPI version's Constraint Object.")
if outcome_value is None:
raise QueryBuildError('You must specify an outcome value to test.')
if disease is None and batch_diseases is None:
raise QueryBuildError('You must specify a disease.')
if disease is not None and batch_diseases is not None:
raise QueryBuildError('Only specify either diseases or batch diseases not both.')
# Initialize Message
message = Message(trapi_version, biolink_version)
q = message.query_graph
# Add disease or batch disease node
if disease is not None:
disease_node = q.add_node(disease, BIOLINK_DISEASE)
else:
disease_node = q.add_node(batch_diseases, BIOLINK_DISEASE)
if genes is not None:
# Add gene nodes
gene_nodes = []
for gene in genes:
gene_nodes.append(q.add_node(gene, BIOLINK_GENE))
# Connect all gene nodes to disease.
for gene_node in gene_nodes:
q.add_edge(gene_node, disease_node, BIOLINK_GENE_ASSOCIATED_WITH_CONDITION)
# Setup batch genes
if batch_genes is not None:
if type(batch_genes) is not list:
raise QueryBuildError('Batch genes must be a list.')
batch_gene_node = q.add_node(batch_genes, BIOLINK_GENE)
q.add_edge(batch_gene_node, disease_node, BIOLINK_GENE_ASSOCIATED_WITH_CONDITION)
if drugs is not None:
# Add drug nodes
if drugs is not None:
drug_nodes = []
for drug in drugs:
drug_nodes.append(q.add_node(drug, BIOLINK_DRUG))
# Connect all drug nodes to disease.
for drug_node in drug_nodes:
q.add_edge(drug_node, disease_node, BIOLINK_TREATS)
# Setup batch drugs
if batch_drugs is not None:
if type(batch_drugs) is not list:
raise QueryBuildError('Batch drugs must be a list.')
batch_drug_node = q.add_node(batch_drugs, BIOLINK_DRUG)
q.add_edge(batch_drug_node, disease_node, BIOLINK_TREATS)
# Connect drug node to outcome node
outcome_node = q.add_node(outcome, BIOLINK_PHENOTYPIC_FEATURE)
phenotype_edge = q.add_edge(disease_node, outcome_node, BIOLINK_HAS_PHENOTYPE)
q.add_constraint(outcome_name, outcome, outcome_op, outcome_value, edge_id=phenotype_edge)
query = Query(trapi_version=trapi_version, biolink_version=biolink_version)
query.message = message
return query
