def test_AGTUtility_valid(self):
I = IntegratorMechanism(name="I",
function=AGTUtilityIntegrator())
I.reinitialize_when = Never()
assert np.allclose([[0.0]], I.function_object.previous_short_term_utility)
assert np.allclose([[0.0]], I.function_object.previous_long_term_utility)
I.function_object.reinitialize(0.2, 0.8)
assert np.allclose([[0.2]], I.function_object.previous_short_term_utility)
assert np.allclose([[0.8]], I.function_object.previous_long_term_utility)
I.function_object.reinitialize()
assert np.allclose([[0.0]], I.function_object.previous_short_term_utility)
assert np.allclose([[0.0]], I.function_object.previous_long_term_utility)
I.reinitialize(0.3, 0.7)
assert np.allclose([[0.3]], I.function_object.previous_short_term_utility)
assert np.allclose([[0.7]], I.function_object.previous_long_term_utility)
print(I.value)
print(I.function_object.combine_utilities(0.3, 0.7))
assert np.allclose(I.function_object.combine_utilities(0.3, 0.7), I.value)
I.reinitialize()
assert np.allclose([[0.0]], I.function_object.previous_short_term_utility)
assert np.allclose([[0.0]], I.function_object.previous_long_term_utility)
assert np.allclose(I.function_object.combine_utilities(0.0, 0.0), I.value)
def test_reset_state_integrator_mechanism(self):
A = IntegratorMechanism(name='A', function=DriftDiffusionIntegrator())
# Execute A twice
# [0] saves decision variable only (not time)
original_output = [A.execute(1.0)[0], A.execute(1.0)[0]]
# SAVING STATE - - - - - - - - - - - - - - - - - - - - - - - - -
reinitialize_values = []
for attr in A.function_object.stateful_attributes:
reinitialize_values.append(getattr(A.function_object, 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)[0], A.execute(1.0)[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)[0], A.execute(1.0)[0]]
assert np.allclose(output_after_saving_state,
output_after_reinitialization)
assert np.allclose(
original_output,
[np.array([[1.0]]), np.array([[2.0]])])
assert np.allclose(
output_after_reinitialization,
[np.array([[3.0]]), np.array([[4.0]])])
def test_reinitialize_not_integrator(self):
with pytest.raises(MechanismError) as err_txt:
I_not_integrator = IntegratorMechanism(function=Linear)
I_not_integrator.execute(1.0)
I_not_integrator.reinitialize(0.0)
assert "not allowed because this Mechanism is not stateful." in str(err_txt) \
and "(It does not have an accumulator to reinitialize)" in str(err_txt)
def test_Constant_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=ConstantIntegrator(
rate=1.0
),
)
# returns previous_value + rate + noise
# so in this case, returns 0.0 + 1.0
I.execute(1000)
assert np.allclose(I.value, 1.0)
assert np.allclose(I.output_state.value, 1.0)
# reinitialize function
I.function_object.reinitialize(2.0)
assert np.allclose(I.function_object.value, 2.0)
assert np.allclose(I.value, 1.0)
assert np.allclose(I.output_states[0].value, 1.0)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 1.0)
assert np.allclose(I.output_states[0].value, 1.0)
# reinitialize mechanism
I.reinitialize(2.0)
assert np.allclose(I.function_object.value, 2.0)
assert np.allclose(I.value, 2.0)
assert np.allclose(I.output_states[0].value, 2.0)
I.execute(1.0)
# 2.0 + 1.0 = 3.0
assert np.allclose(I.value, 3.0)
assert np.allclose(I.output_states[0].value, 3.0)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_Adaptive_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=AdaptiveIntegrator(
rate=0.5
),
)
# returns (1-rate)*previous_value + rate*variable + noise
# so in this case, returns 0.5*0 + 0.5*10 + 0 = 5.0
I.execute(10)
assert np.allclose(I.value, 5.0)
assert np.allclose(I.output_state.value, 5.0)
# reinitialize function
I.function_object.reinitialize(1.0)
assert np.allclose(I.function_object.value, 1.0)
assert np.allclose(I.value, 5.0)
assert np.allclose(I.output_states[0].value, 5.0)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 5.0)
assert np.allclose(I.output_states[0].value, 5.0)
# reinitialize mechanism
I.reinitialize(2.0)
assert np.allclose(I.function_object.value, 2.0)
assert np.allclose(I.value, 2.0)
assert np.allclose(I.output_states[0].value, 2.0)
I.execute(1.0)
# (1-0.5)*2.0 + 0.5*1.0 + 0 = 1.5
assert np.allclose(I.value, 1.5)
assert np.allclose(I.output_states[0].value, 1.5)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_LCA_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=LCAIntegrator(),
)
# previous_value + (rate*previous_value + new_value)*time_step_size + noise
# initializer=0.0, rate=1.0, time_step_size=0.1, noise=0.0
# returns 0.0 + (1.0*0.0 + 2.0)*0.1 = 2.0
I.execute(2.0)
assert np.allclose(I.value, 0.2)
assert np.allclose(I.output_state.value, 0.2)
# reinitialize function
I.function_object.reinitialize(5.0)
assert np.allclose(I.function_object.value, 5.0)
assert np.allclose(I.value, 0.2)
assert np.allclose(I.output_states[0].value, 0.2)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.2)
assert np.allclose(I.output_states[0].value, 0.2)
# reinitialize mechanism
I.reinitialize(4.0)
assert np.allclose(I.function_object.value, 4.0)
assert np.allclose(I.value, 4.0)
assert np.allclose(I.output_states[0].value, 4.0)
I.execute(1.0)
# 4.0 + (1.0*4.0 + 1.0)*0.1 + 0.0
assert np.allclose(I.value, 4.5)
assert np.allclose(I.output_states[0].value, 4.5)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_Accumulator_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=AccumulatorIntegrator(increment=0.1),
)
# returns previous_value * rate + noise + increment
# initializer = 0.0, rate = 1.0, noise = 0.0, increment = 0.1
# returns 0.0*1.0 + 0.0 + 0.1 = 0.1
I.execute(10000)
assert np.allclose(I.value, 0.1)
assert np.allclose(I.output_state.value, 0.1)
# reinitialize function
I.function_object.reinitialize(2.0)
assert np.allclose(I.function_object.value, 2.0)
assert np.allclose(I.value, 0.1)
assert np.allclose(I.output_states[0].value, 0.1)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.1)
assert np.allclose(I.output_states[0].value, 0.1)
# reinitialize mechanism
I.reinitialize(5.0)
assert np.allclose(I.function_object.value, 5.0)
assert np.allclose(I.value, 5.0)
assert np.allclose(I.output_states[0].value, 5.0)
I.execute(10000)
# 5.0 * 1.0 + 0.0 + 0.1
assert np.allclose(I.value, 5.1)
assert np.allclose(I.output_states[0].value, 5.1)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_OU_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=OrnsteinUhlenbeckIntegrator(),
)
# previous_value + (decay * previous_value - rate * variable) * time_step_size + noise
# decay=1.0, initializer=0.0, rate=1.0, time_step_size=1.0, noise=0.0
# returns 0.0 + (1.0*0.0 - 1.0*10.0*1.0) + 0.0 = -10.0
I.execute(2.0)
assert np.allclose(I.value, -2.0)
assert np.allclose(I.output_state.value, -2.0)
# reinitialize function
I.function_object.reinitialize(5.0)
assert np.allclose(I.function_object.value, 5.0)
assert np.allclose(I.value, -2.0)
assert np.allclose(I.output_states[0].value, -2.0)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, -2.0)
assert np.allclose(I.output_states[0].value, -2.0)
# reinitialize mechanism
I.reinitialize(4.0)
assert np.allclose(I.function_object.value, 4.0)
assert np.allclose(I.value, 4.0)
assert np.allclose(I.output_states[0].value, 4.0)
I.execute(1.0)
# 4.0 + (1.0 * 4.0 - 1.0 * 1.0) * 1.0 = 4 + 3 = 7
assert np.allclose(I.value, 7.0)
assert np.allclose(I.output_states[0].value, 7.0)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_Simple_valid(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=SimpleIntegrator(
),
)
I.reinitialize_when = Never()
# returns previous_value + rate*variable + noise
# so in this case, returns 10.0
I.execute(10)
assert np.allclose(I.value, 10.0)
assert np.allclose(I.output_state.value, 10.0)
# reinitialize function
I.function_object.reinitialize(5.0)
assert np.allclose(I.function_object.value, 5.0)
assert np.allclose(I.value, 10.0)
assert np.allclose(I.output_states[0].value, 10.0)
# reinitialize function without value spec
I.function_object.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 10.0)
assert np.allclose(I.output_states[0].value, 10.0)
# reinitialize mechanism
I.reinitialize(4.0)
assert np.allclose(I.function_object.value, 4.0)
assert np.allclose(I.value, 4.0)
assert np.allclose(I.output_states[0].value, 4.0)
I.execute(1)
assert np.allclose(I.value, 5.0)
assert np.allclose(I.output_states[0].value, 5.0)
# reinitialize mechanism without value spec
I.reinitialize()
assert np.allclose(I.function_object.value, 0.0)
assert np.allclose(I.value, 0.0)
assert np.allclose(I.output_states[0].value, 0.0)
def test_FHN_valid(self):
I = IntegratorMechanism(name="I",
function=FHNIntegrator())
I.reinitialize_when = Never()
I.execute(1.0)
assert np.allclose([[0.05127053]], I.value[0])
assert np.allclose([[0.00279552]], I.value[1])
assert np.allclose([[0.05]], I.value[2])
I.function_object.reinitialize(0.01, 0.02, 0.03)
assert np.allclose(0.01, I.function_object.value[0])
assert np.allclose(0.02, I.function_object.value[1])
assert np.allclose(0.03, I.function_object.value[2])
assert np.allclose([[0.05127053]], I.value[0])
assert np.allclose([[0.00279552]], I.value[1])
assert np.allclose([[0.05]], I.value[2])
assert np.allclose([[0.05127053]], I.output_states[0].value)
I.execute(1.0)
assert np.allclose([[0.06075727]], I.value[0])
assert np.allclose([[0.02277156]], I.value[1])
assert np.allclose([[0.08]], I.value[2])
assert np.allclose([[0.06075727]], I.output_states[0].value)
# I.reinitialize(new_previous_v=0.01, new_previous_w=0.02, new_previous_time=0.03)
I.reinitialize(0.01, 0.02, 0.03)
assert np.allclose(0.01, I.value[0])
assert np.allclose(0.02, I.value[1])
assert np.allclose(0.03, I.value[2])
assert np.allclose(0.01, I.output_states[0].value)
