def test_transfer_mech_array_var_normal_array_noise(self):
T = TransferMechanism(
name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
noise=[NormalDist(), NormalDist(), NormalDist(), NormalDist()],
integration_rate=1.0,
integrator_mode=True
)
T.reinitialize_when = Never()
val = T.execute([0, 0, 0, 0])
expected = [0.7610377251469934, 0.12167501649282841, 0.44386323274542566, 0.33367432737426683]
for i in range(len(val[0])):
assert val[0][i] == expected[i]
def test_transfer_mech_2d_variable_noise(self):
T = TransferMechanism(
name='T',
function=Linear(slope=2.0, intercept=1.0),
noise=NormalDist(),
default_variable=[[0.0, 0.0], [0.0, 0.0]]
)
val = T.execute([[1.0, 2.0], [3.0, 4.0]])
def test_integrator_adaptive_noise_fn(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=AdaptiveIntegrator(noise=NormalDist().function),
time_scale=TimeScale.TIME_STEP)
val = float(I.execute(10))
np.testing.assert_allclose(val, 11.86755799)
def test_integrator_adaptive_noise_fn(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=AdaptiveIntegrator(noise=NormalDist()),
)
val = float(I.execute(10))
np.testing.assert_allclose(val, 12.240893199201459)
def test_transfer_mech_normal_fun(self):
with pytest.raises(TransferError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=NormalDist(),
time_constant=1.0,
integrator_mode=True)
T.execute([0, 0, 0, 0])
assert "must be a TRANSFER FUNCTION TYPE" in str(error_text.value)
def test_recurrent_mech_normal_fun(self):
with pytest.raises(TransferError) as error_text:
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=NormalDist(),
smoothing_factor=1.0,
integrator_mode=True)
R.execute([0, 0, 0, 0])
assert "must be a TRANSFER FUNCTION TYPE" in str(error_text.value)
def test_integrator_constant_noise_fn(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=ConstantIntegrator(noise=NormalDist()),
)
val = float(I.execute(10))
np.testing.assert_allclose(val, 1.8675579901499675)
def test_integrator_accumulator_noise_fn_var_list(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=AccumulatorIntegrator(noise=NormalDist(), ),
)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(
val, [0.95008842, -0.15135721, -0.10321885, 0.4105985])
def test_DDM_input_fn():
with pytest.raises(TypeError) as error_text:
stim = NormalDist().function
T = DDM(name='DDM',
function=DriftDiffusionIntegrator(noise=0.0,
rate=1.0,
time_step_size=1.0),
time_scale=TimeScale.TIME_STEP)
float(T.execute(stim))
assert "not supported for the input types" in str(error_text.value)
def test_integrator_constant_noise_fn_var_list(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=ConstantIntegrator(noise=NormalDist(), ),
)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(
val, [-0.15135721, -0.10321885, 0.4105985, 0.14404357])
def test_integrator_accumulator_noise_fn_var_list(self):
I = IntegratorMechanism(name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=AccumulatorIntegrator(
noise=NormalDist().function,
default_variable=[0, 0, 0, 0]),
time_scale=TimeScale.TIME_STEP)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(
val, [0.12167502, 0.44386323, 0.33367433, 1.49407907])
def test_DDM_rate_fn():
with pytest.raises(typecheck.framework.InputParameterError) as error_text:
stim = [10]
T = DDM(name='DDM',
default_variable=[0],
function=DriftDiffusionIntegrator(noise=0.0,
rate=NormalDist().function,
time_step_size=1.0),
time_scale=TimeScale.TIME_STEP)
float(T.execute(stim)[0])
assert "incompatible value" in str(error_text.value)
def test_DDM_noise_fn():
with pytest.raises(FunctionError) as error_text:
stim = 10
T = DDM(name='DDM',
function=DriftDiffusionIntegrator(noise=NormalDist().function,
rate=1.0,
time_step_size=1.0),
time_scale=TimeScale.TIME_STEP)
float(T.execute(stim)[0])
assert "DriftDiffusionIntegrator requires noise parameter to be a float" in str(
error_text.value)
def test_integrator_adaptive_noise_fn_var_list(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=AdaptiveIntegrator(noise=NormalDist(), ),
)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(
val, [10.95008842, 9.84864279, 9.89678115, 10.4105985])
def test_integrator_accumulator_noise_fn_var_list(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=AccumulatorIntegrator(
noise=NormalDist(),
),
)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(val, [0.14404357, 1.45427351, 0.76103773, 0.12167502])
def test_integrator_constant_noise_fn_var_list(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
default_variable=[0, 0, 0, 0],
function=ConstantIntegrator(
noise=NormalDist(),
),
)
val = I.execute([10, 10, 10, 10])[0]
np.testing.assert_allclose(val, [1.45427351, 0.76103773, 0.12167502, 0.44386323])
def test_transfer_mech_array_var_normal_len_1_noise(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
noise=NormalDist().function,
time_constant=1.0,
integrator_mode=True)
val = T.execute([0, 0, 0, 0])
assert np.allclose(val, [[
0.41059850193837233, 0.144043571160878, 1.454273506962975,
0.7610377251469934
]])
def test_transfer_mech_normal_noise_standard_dev_error(self):
with pytest.raises(FunctionError) as error_text:
standard_deviation = -2.0
T = TransferMechanism(
name="T",
default_variable=[0, 0, 0, 0],
function=Linear(),
noise=NormalDist(standard_dev=standard_deviation).function,
time_constant=1.0,
integrator_mode=True)
assert "The standard_dev parameter" in str(
error_text) and "must be greater than zero" in str(error_text)
def test_integrator_simple_noise_fn(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=SimpleIntegrator(noise=NormalDist().function),
time_scale=TimeScale.TIME_STEP)
val = float(I.execute(10))
I.function_object.reset_initializer = 5.0
val2 = float(I.execute(0))
np.testing.assert_allclose(val, 11.86755799)
np.testing.assert_allclose(val2, 4.022722120123589)
def test_integrator_simple_noise_fn(self):
I = IntegratorMechanism(
name='IntegratorMechanism',
function=SimpleIntegrator(noise=NormalDist()),
)
val = float(I.execute(10))
I.function_object.reinitialize(5.0)
val2 = float(I.execute(0))
np.testing.assert_allclose(val, 12.240893199201459)
np.testing.assert_allclose(val2, 6.867557990149967)
def target_function():
val_1 = NormalDist(mean=3.0).function()
return val_1
def target_function():
val_1 = NormalDist(mean=3.0).function()
val_2 = NormalDist(mean=3.0).function()
return [val_1, val_2]
def target_function():
val_1 = NormalDist(mean=3.0).function()
val_2 = NormalDist(mean=3.0).function()
target_value = np.array([val_1, val_2])
return target_value
