def test_transfer_mech_inputs_mismatched_with_default_shorter(self):
with pytest.raises(MechanismError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0, 0, 0],
integrator_mode=True)
T.execute([1, 2, 3, 4, 5])
assert "does not match required length" in str(error_text.value)
def test_runtime_params_reset_isolated(self):
T = TransferMechanism()
# Intercept attr updated
T.function_object.intercept = 2.0
assert T.function_object.intercept == 2.0
# Runtime param used for slope
T.execute(runtime_params={"slope": 10.0}, input=2.0)
assert T.function_object.slope == 10.0
assert T.parameter_states['slope'].value == 10.0
# Intercept attr NOT affected by runtime params
assert T.function_object.intercept == 2.0
assert T.value == 22.0
# Runtime param NOT used for slope
T.execute(input=2.0)
assert T.function_object.slope == 1.0
assert T.parameter_states['slope'].value == 1.0
# Intercept attr NOT affected by runtime params reset
assert T.function_object.intercept == 2.0
assert T.value == 4.0
def test_transfer_mech_inputs_list_of_strings(self):
with pytest.raises(UtilitiesError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
integrator_mode=True)
T.execute(["one", "two", "three", "four"])
assert "has non-numeric entries" in str(error_text.value)
def test_projection_tuple_with_matrix_spec(self):
R2 = TransferMechanism(size=3)
T = TransferMechanism(size=2, input_states=[(R2, None, None, np.zeros((3, 2)))])
np.testing.assert_array_equal(T.instance_defaults.variable, np.array([[0, 0]]))
assert len(T.input_states) == 1
assert len(T.input_state.path_afferents[0].sender.instance_defaults.variable) == 3
assert len(T.input_state.instance_defaults.variable) == 2
T.execute()
def test_2_item_tuple_value_for_first_item(self):
R2 = TransferMechanism(size=3)
T = TransferMechanism(input_states=[([0,0], R2)])
np.testing.assert_array_equal(T.instance_defaults.variable, np.array([[0, 0]]))
assert len(T.input_states) == 1
assert len(T.input_state.path_afferents[0].sender.instance_defaults.variable) == 3
assert len(T.input_state.instance_defaults.variable) == 2
T.execute()
def test_mech_spec_list(self):
R1 = TransferMechanism(output_states=['FIRST', 'SECOND'])
T = TransferMechanism(default_variable=[[0]], input_states=[R1])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0]]))
assert len(T.input_states) == 1
assert T.input_state.path_afferents[0].sender == R1.output_state
T.execute()
def test_2_item_tuple_spec(self):
R2 = TransferMechanism(size=3)
T = TransferMechanism(size=2, input_states=[(R2, np.zeros((3, 2)))])
np.testing.assert_array_equal(T.instance_defaults.variable, np.array([[0, 0]]))
assert len(T.input_states) == 1
assert len(T.input_state.path_afferents[0].sender.instance_defaults.variable) == 3
assert T.input_state.socket_width == 2
T.execute()
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_transfer_mech_reduce_fun(self):
with pytest.raises(TransferError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Reduce(),
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_output_state_spec_standalone(self):
R1 = TransferMechanism(output_states=['FIRST', 'SECOND'])
T = TransferMechanism(default_variable=[0],
input_states=R1.output_states['FIRST'])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0]]))
assert len(T.input_states) == 1
assert T.input_states.names[0] == 'InputState-0'
T.input_state.path_afferents[0].sender == R1.output_state
T.execute()
def test_transfer_mech_time_constant_0_8(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
integrator_mode=True)
val = T.execute([1, 1, 1, 1])
assert np.allclose(val, [[0.8, 0.8, 0.8, 0.8]])
val = T.execute([1, 1, 1, 1])
assert np.allclose(val, [[0.96, 0.96, 0.96, 0.96]])
def test_transfer_mech_time_constant_0(self):
with pytest.raises(TransferError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0,
integrator_mode=True)
T.execute([1, 1, 1, 1])
assert ("time_constant parameter" in str(error_text.value)
and "must be a float between 0 and 1" in str(error_text.value))
def test_projection_in_tuple(self):
R2 = TransferMechanism(size=3)
P = MappingProjection(sender=R2)
T = TransferMechanism(size=2, input_states=[(R2, None, None, P)])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0, 0]]))
assert len(T.input_states) == 1
assert len(T.input_state.path_afferents[0].sender.instance_defaults.
variable) == 3
assert len(T.input_state.instance_defaults.variable) == 2
T.execute()
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(),
integration_rate=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_transfer_mech_mismatched_shape_noise(self):
with pytest.raises(MechanismError) as error_text:
T = TransferMechanism(name='T',
default_variable=[0, 0],
function=Linear(),
noise=[5.0, 5.0, 5.0],
time_constant=0.1,
integrator_mode=True)
T.execute()
assert 'Noise parameter' in str(
error_text.value) and "does not match default variable" in str(
error_text.value)
def test_transfer_mech_integration_rate_0_8(self):
T = TransferMechanism(
name='T',
default_variable=[0 for i in range(VECTOR_SIZE)],
function=Linear(),
integration_rate=0.8,
integrator_mode=True
)
val = T.execute([1 for i in range(VECTOR_SIZE)])
assert np.allclose(val, [[0.8 for i in range(VECTOR_SIZE)]])
val = T.execute([1 for i in range(VECTOR_SIZE)])
assert np.allclose(val, [[0.96 for i in range(VECTOR_SIZE)]])
def test_transfer_mech_time_constant_0_8_initial_0_5(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
initial_value=np.array([[.5, .5, .5, .5]]),
integrator_mode=True)
val = T.execute([1, 1, 1, 1])
assert np.allclose(val, [[0.9, 0.9, 0.9, 0.9]])
T.noise = 10
val = T.execute([1, 2, -3, 0])
assert np.allclose(val, [[10.98, 11.78, 7.779999999999999, 10.18]
]) # testing noise changes to an integrator
def test_default_variable_override_mech_list(self):
R2 = TransferMechanism(size=3)
# default_variable override of OutputState.value
T = TransferMechanism(default_variable=[[0, 0]], input_states=[R2])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0, 0]]))
assert len(T.input_states) == 1
assert len(T.input_state.path_afferents[0].sender.instance_defaults.
variable) == 3
assert len(T.input_state.instance_defaults.variable) == 2
T.execute()
def test_transfer_mech_integration_rate_0_8_list(self):
with pytest.raises(TransferError) as error_text:
T = TransferMechanism(
name='T',
default_variable=[0, 0, 0, 0],
function=Linear(),
integration_rate=[0.8, 0.8, 0.8, 0.8],
integrator_mode=True
)
T.execute([1, 1, 1, 1])
assert (
"integration_rate parameter" in str(error_text.value)
and "must be a float" in str(error_text.value)
)
def test_transfer_mech_size_int_inputs_floats(self):
T = TransferMechanism(
name='T',
size=VECTOR_SIZE
)
val = T.execute([10.0 for i in range(VECTOR_SIZE)])
assert np.allclose(val, [[10.0 for i in range(VECTOR_SIZE)]])
def test_multiple_output_states_for_multiple_input_states(self):
T = TransferMechanism(input_states=['a', 'b', 'c'])
val = T.execute([[1], [2], [3]])
assert len(T.variable) == 3
assert all(a == b for a, b in zip(val, [[1.], [2.], [3.]]))
assert len(T.output_states) == 3
assert all(a == b for a, b in zip(T.output_values, val))
def test_transfer_mech_2d_variable(self):
from psyneulink.globals.keywords import MEAN
T = TransferMechanism(name='T',
function=Linear(slope=2.0, intercept=1.0),
default_variable=[[0.0, 0.0], [0.0, 0.0]],
output_states=[MEAN])
val = T.execute([[1.0, 2.0], [3.0, 4.0]])
def test_output_state_spec_list_two_items(self):
R1 = TransferMechanism(output_states=['FIRST', 'SECOND'])
T = TransferMechanism(default_variable=[[0], [0]],
input_states=[
R1.output_states['FIRST'],
R1.output_states['SECOND']
])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0], [0]]))
assert len(T.input_states) == 2
assert T.input_states.names[0] == 'InputState-0'
assert T.input_states.names[1] == 'InputState-1'
for input_state in T.input_states:
for projection in input_state.path_afferents:
assert projection.sender.owner is R1
T.execute()
def test_transfer_mech_inputs_list_of_floats(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
integrator_mode=True)
val = T.execute([10.0, 10.0, 10.0, 10.0])
assert np.allclose(val, [[10.0, 10.0, 10.0, 10.0]])
def test_transfer_mech_size_float_inputs_floats(self):
T = TransferMechanism(
name='T',
size=4.0
)
val = T.execute([10.0, 10.0, 10.0, 10.0])
assert np.allclose(val, [[10.0, 10.0, 10.0, 10.0]])
def test_projection_in_specification_dict(self):
R1 = TransferMechanism(output_states=['FIRST', 'SECOND'])
T = TransferMechanism(input_states=[{
NAME:
'My InputState with Two Projections',
PROJECTIONS:
[R1.output_states['FIRST'], R1.output_states['SECOND']]
}])
np.testing.assert_array_equal(T.instance_defaults.variable,
np.array([[0]]))
assert len(T.input_states) == 1
assert T.input_state.name == 'My InputState with Two Projections'
for input_state in T.input_states:
for projection in input_state.path_afferents:
assert projection.sender.owner is R1
T.execute()
def test_transfer_mech_var_1D_size_wrong_2(self):
T = TransferMechanism(name='T',
default_variable=[1, 2, 3, 4],
size=[2, 3, 4])
assert len(T.instance_defaults.variable) == 1 and (
T.instance_defaults.variable[0] == [1, 2, 3, 4]).all()
val = T.execute([10.0, 10.0, 10.0, 10.0])
assert np.allclose(val, [[10.0, 10.0, 10.0, 10.0]])
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_transfer_mech_softmax_fun(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=SoftMax(),
time_constant=1.0,
integrator_mode=True)
val = T.execute([0, 0, 0, 0])
assert np.allclose(val, [[0.25, 0.25, 0.25, 0.25]])
def test_transfer_mech_exponential_fun(self):
T = TransferMechanism(name='T',
default_variable=[0, 0, 0, 0],
function=Exponential(),
time_constant=1.0,
integrator_mode=True)
val = T.execute([0, 0, 0, 0])
assert np.allclose(val, [[1.0, 1.0, 1.0, 1.0]])
