def test_turtle_load_user(self):
turtleName = self.get_turtle()
if not monkapi.has_turtle_in_store(turtleName, self.user):
monkapi.follow_turtle(turtleName, self.user, self.leader)
result = monkapi.load_turtle(turtleName, self.user)
assert result != None
# load can be repeated, overwrite the memory from database
result = monkapi.load_turtle(turtleName, self.user)
assert result != None
def test_turtle_load_user(self):
turtleName = self.get_turtle()
if not monkapi.has_turtle_in_store(turtleName, self.user):
monkapi.follow_turtle(turtleName, self.user, self.leader)
result = monkapi.load_turtle(turtleName, self.user)
assert result != None
# load can be repeated, overwrite the memory from database
result = monkapi.load_turtle(turtleName, self.user)
assert result != None
stemT.save()
[ent.save() for ent in ents]
likeTS = ms.yaml2json('turtle_scripts/turtle_like.yml')
# print likeTS
likeT = ms.create_turtle(likeTS)
likeT.save()
ent = ents[0]
# print ents[0].generic()
ent._setattr('likeTravel', 'Y')
ms.crane.entityStore.save_one(ent)
ms.add_data('likeTravel', 'monk', str(ents[0]._id))
print likeT.tigress.p
print likeT.pandas[0].mantis.data
likeT.tigress.defaulting=True
likeT.save()
likeT = ms.load_turtle('likeTravel','monk')
likeT.train()
for i in ents:
ent = ms.load_entity(i._id)
print likeT.pandas[0].predict(ent)
print sign0(likeT.pandas[0].predict(ent))
# likeTS = ms.yaml2json('turtle_scripts/turtle_like.yml')
# # print likeTS
# likeT = ms.create_turtle(likeTS)
# likeT.save()
# ent = ents[0]
# # print ents[0].generic()
# ent._setattr('likeTravel', 'Y')
# ms.crane.entityStore.save_all(ents)
def train(turtleName,creator='monk'):
trainer = ms.load_turtle(turtleName,creator)
trainer.train()
return trainer