def test_Model_predict_percept():
# A None Model has nothing to build, nothing to perceive:
model = Model()
npt.assert_equal(model.predict_percept(ArgusI()), None)
npt.assert_equal(model.predict_percept(ArgusI(stim={'A1': 1})), None)
npt.assert_equal(
model.predict_percept(ArgusI(stim={'A1': 1}), t_percept=[0, 1]), None)
# Just the spatial model:
model = Model(spatial=ValidSpatialModel()).build()
npt.assert_equal(model.predict_percept(ArgusI()), None)
# Just the temporal model:
model = Model(temporal=ValidTemporalModel()).build()
npt.assert_equal(model.predict_percept(ArgusI()), None)
# Invalid calls:
model = Model(spatial=ValidSpatialModel(), temporal=ValidTemporalModel())
with pytest.raises(NotBuiltError):
# Must call build first:
model.predict_percept(ArgusI())
model.build()
with pytest.raises(ValueError):
# Cannot request t_percepts that are not multiples of dt:
model.predict_percept(ArgusI(stim=np.ones(16)), t_percept=[0.1, 0.11])
with pytest.raises(ValueError):
# stim.time==None but requesting t_percept != None
model.predict_percept(ArgusI(stim=np.ones(16)), t_percept=[0, 1, 2])
with pytest.raises(TypeError):
# Must pass an implant:
model.predict_percept(Stimulus(3))
def test_Model_build():
# A None model:
model = Model()
# Nothing to build, so `is_built` is always True (we want to be able to
# call `predict_percept`):
npt.assert_equal(model.is_built, True)
model.build()
npt.assert_equal(model.is_built, True)
# SpatialModel, but no TemporalModel:
model = Model(spatial=ValidSpatialModel())
npt.assert_equal(model.is_built, False)
model.build()
npt.assert_equal(model.is_built, True)
# TemporalModel, but no SpatialModel:
model = Model(temporal=ValidTemporalModel())
npt.assert_equal(model.is_built, False)
model.build()
npt.assert_equal(model.is_built, True)
# SpatialModel and TemporalModel:
model = Model(spatial=ValidSpatialModel(), temporal=ValidTemporalModel())
npt.assert_equal(model.is_built, False)
model.build()
npt.assert_equal(model.is_built, True)
