def update_graph_context(updates,update_count=False):
if update_count :
with collection.pipeline() as pipe:
for x in updates:
context_vector = x['updated_context']
unit_context_vector = context_vector / np.linalg.norm(context_vector)
pipe.hset(x['connection_key'],'context',unit_context_vector.tobytes())
pipe.hincrby(x['connection_key'],'update_count',1)
pipe.execute()
else :
with collection.pipeline() as pipe:
for x in updates:
context_vector = x['updated_context']
unit_context_vector = context_vector / np.linalg.norm(context_vector)
pipe.hset(x['connection_key'],'context',unit_context_vector.tobytes())
pipe.execute()
def update_graph_nodes(updates):
with collection.pipeline() as pipe:
for x in updates:
#context_vector = x['updated_context']
update_vector = x['update_vector']
weight_vector = x['weight_vector']
unit_update_vector = update_vector /np.linalg.norm(update_vector)
unit_weight_vector = weight_vector / np.linalg.norm(weight_vector)
#unit_context_vector = context_vector / np.linalg.norm(context_vector)
#pipe.hset(x['connection_key'],'context',unit_context_vector.tobytes())
pipe.hset(x['connection_key'], 'update_vector', unit_update_vector.tobytes())
pipe.hset(x['connection_key'], 'weight_vector', unit_weight_vector.tobytes())
pipe.execute()
def release_db_lock(unlock=False):
if unlock:
with collection.pipeline() as pipe:
for key in collection.keys():
pipe.hset(key,b'lock',0)
pipe.execute()