def test_Model_predict_percept_correctly_parallelizes():
# setup and time spatial model with 1 thread
one_thread_spatial = Model(spatial=ValidSpatialModel(n_threads=1)).build()
start_time_one_thread_spatial = time.perf_counter()
one_thread_spatial.predict_percept(ArgusI())
one_thread_spatial_predict_time = time.perf_counter(
) - start_time_one_thread_spatial
# setup and time spatial model with 2 threads
two_thread_spatial = Model(spatial=ValidSpatialModel(n_threads=2)).build()
start_time_two_thread_spatial = time.perf_counter()
two_thread_spatial.predict_percept(ArgusI())
two_threaded_spatial_predict_time = time.perf_counter(
) - start_time_two_thread_spatial
# we expect roughly a linear decrease in time as thread count increases
npt.assert_almost_equal(actual=two_threaded_spatial_predict_time,
desired=one_thread_spatial_predict_time / 2,
decimal=1e-5)
# setup and time temporal model with 1 thread
one_thread_temporal = Model(temporal=ValidTemporalModel(
n_threads=1)).build()
start_time_one_thread_temporal = time.perf_counter()
one_thread_temporal.predict_percept(ArgusI())
one_thread_temporal_predict_time = time.perf_counter(
) - start_time_one_thread_temporal
# setup and time temporal model with 2 threads
two_thread_temporal = Model(temporal=ValidTemporalModel(
n_threads=2)).build()
start_time_two_thread_temporal = time.perf_counter()
two_thread_temporal.predict_percept(ArgusI())
two_thread_temporal_predict_time = time.perf_counter(
) - start_time_two_thread_temporal
# we expect roughly a linear decrease in time as thread count increases
npt.assert_almost_equal(actual=two_thread_temporal_predict_time,
desired=one_thread_temporal_predict_time / 2,
decimal=1e-5)
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))