def test_reset_state_transfer_mechanism(self):
A = TransferMechanism(name='A', integrator_mode=True)
# Execute A twice
original_output = [A.execute(1.0), A.execute(1.0)]
# SAVING STATE - - - - - - - - - - - - - - - - - - - - - - - - -
reinitialize_values = []
for attr in A.integrator_function.stateful_attributes:
reinitialize_values.append(getattr(A.integrator_function, attr))
# Execute A twice AFTER saving the state so that it continues accumulating.
# We expect the next two outputs to repeat once we reset the state b/c we will return it to the current state
output_after_saving_state = [A.execute(1.0), A.execute(1.0)]
# RESETTING STATE - - - - - - - - - - - - - - - - - - - - - - - -
A.reinitialize(*reinitialize_values)
# We expect these results to match the results from immediately after saving the state
output_after_reinitialization = [A.execute(1.0), A.execute(1.0)]
assert np.allclose(output_after_saving_state,
output_after_reinitialization)
assert np.allclose(
original_output,
[np.array([[0.5]]), np.array([[0.75]])])
assert np.allclose(
output_after_reinitialization,
[np.array([[0.875]]), np.array([[0.9375]])])
def test_reinitialize_not_integrator(self):
with pytest.raises(MechanismError) as err_txt:
T_not_integrator = TransferMechanism()
T_not_integrator.execute(1.0)
T_not_integrator.reinitialize(0.0)
assert "not allowed because this Mechanism is not stateful." in str(err_txt) \
and "try setting the integrator_mode argument to True." in str(err_txt)
def test_reinitialize_run_2darray(self):
initial_val = [[0.5, 0.5, 0.5]]
T = TransferMechanism(name="T",
default_variable=[[0.0, 0.0, 0.0]],
initial_value=initial_val,
integrator_mode=True,
integration_rate=0.1,
noise=0.0)
P = Process(name="P",
pathway=[T])
S = System(name="S",
processes=[P])
T.reinitialize_when = Never()
assert np.allclose(T.integrator_function.previous_value, initial_val)
S.run(inputs={T: [1.0, 1.0, 1.0]}, num_trials=2)
# Trial 1
# integration: 0.9*0.5 + 0.1*1.0 + 0.0 = 0.55 ---> previous value = 0.55
# linear fn: 0.55*1.0 = 0.55
# Trial 2
# integration: 0.9*0.55 + 0.1*1.0 + 0.0 = 0.595 ---> previous value = 0.595
# linear fn: 0.595*1.0 = 0.595
assert np.allclose(T.integrator_function.previous_value, [0.595, 0.595, 0.595])
T.integrator_function.reinitialize([0.9, 0.9, 0.9])
assert np.allclose(T.integrator_function.previous_value, [0.9, 0.9, 0.9])
assert np.allclose(T.value, [0.595, 0.595, 0.595])
T.reinitialize(initial_val)
assert np.allclose(T.integrator_function.previous_value, initial_val)
assert np.allclose(T.value, initial_val)
S.run(inputs={T: [1.0, 1.0, 1.0]}, num_trials=2)
# Trial 3
# integration: 0.9*0.5 + 0.1*1.0 + 0.0 = 0.55 ---> previous value = 0.55
# linear fn: 0.55*1.0 = 0.55
# Trial 4
# integration: 0.9*0.55 + 0.1*1.0 + 0.0 = 0.595 ---> previous value = 0.595
# linear fn: 0.595*1.0 = 0.595
assert np.allclose(T.integrator_function.previous_value, [0.595, 0.595, 0.595])
def test_reinitialize_run(self):
T = TransferMechanism(name="T",
initial_value=0.5,
integrator_mode=True,
integration_rate=0.1,
noise=0.0)
P = Process(name="P",
pathway=[T])
S = System(name="S",
processes=[P])
T.reinitialize_when = Never()
assert np.allclose(T.integrator_function.previous_value, 0.5)
S.run(inputs={T: 1.0}, num_trials=2)
# Trial 1
# integration: 0.9*0.5 + 0.1*1.0 + 0.0 = 0.55 ---> previous value = 0.55
# linear fn: 0.55*1.0 = 0.55
# Trial 2
# integration: 0.9*0.55 + 0.1*1.0 + 0.0 = 0.595 ---> previous value = 0.595
# linear fn: 0.595*1.0 = 0.595
assert np.allclose(T.integrator_function.previous_value, 0.595)
T.integrator_function.reinitialize(0.9)
assert np.allclose(T.integrator_function.previous_value, 0.9)
assert np.allclose(T.value, 0.595)
T.reinitialize(0.5)
assert np.allclose(T.integrator_function.previous_value, 0.5)
assert np.allclose(T.value, 0.5)
S.run(inputs={T: 1.0}, num_trials=2)
# Trial 3
# integration: 0.9*0.5 + 0.1*1.0 + 0.0 = 0.55 ---> previous value = 0.55
# linear fn: 0.55*1.0 = 0.55
# Trial 4
# integration: 0.9*0.55 + 0.1*1.0 + 0.0 = 0.595 ---> previous value = 0.595
# linear fn: 0.595*1.0 = 0.595
assert np.allclose(T.integrator_function.previous_value, 0.595)
def test_previous_value_reinitialize_execute(self):
T = TransferMechanism(name="T",
initial_value=0.5,
integrator_mode=True,
integration_rate=0.1,
noise=0.0)
T.reinitialize_when = Never()
assert np.allclose(T.integrator_function.previous_value, 0.5)
T.execute(1.0)
# integration: 0.9*0.5 + 0.1*1.0 + 0.0 = 0.55 ---> previous value = 0.55
# linear fn: 0.55*1.0 = 0.55
assert np.allclose(T.integrator_function.previous_value, 0.55)
assert np.allclose(T.value, 0.55)
# Reset integrator_function ONLY
T.integrator_function.reinitialize(0.6)
assert np.allclose(T.integrator_function.previous_value, 0.6) # previous_value is a property that looks at integrator_function
assert np.allclose(T.value, 0.55) # on mechanism only, so does not update until execution
T.execute(1.0)
# integration: 0.9*0.6 + 0.1*1.0 + 0.0 = 0.64 ---> previous value = 0.55
# linear fn: 0.64*1.0 = 0.64
assert np.allclose(T.integrator_function.previous_value, 0.64) # property that looks at integrator_function
assert np.allclose(T.value, 0.64) # on mechanism, but updates with execution
T.reinitialize(0.4)
# linear fn: 0.4*1.0 = 0.4
assert np.allclose(T.integrator_function.previous_value, 0.4) # property that looks at integrator, which updated with mech reset
assert np.allclose(T.value, 0.4) # on mechanism, but updates with mech reset
T.execute(1.0)
# integration: 0.9*0.4 + 0.1*1.0 + 0.0 = 0.46 ---> previous value = 0.46
# linear fn: 0.46*1.0 = 0.46
assert np.allclose(T.integrator_function.previous_value, 0.46) # property that looks at integrator, which updated with mech exec
assert np.allclose(T.value, 0.46) # on mechanism, but updates with exec
