def test_recurrent_mech_inputs_list_of_strings(self):
with pytest.raises(UtilitiesError) as error_text:
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
integrator_mode=True)
R.execute(["one", "two", "three", "four"])
assert "has non-numeric entries" in str(error_text.value)
def test_recurrent_mech_inputs_list_of_ints(self):
R = RecurrentTransferMechanism(name='R', default_variable=[0, 0, 0, 0])
val = R.execute([10, 12, 0, -1])
np.testing.assert_allclose(val, [[10.0, 12.0, 0, -1]])
val = R.execute([1, 2, 3, 0])
np.testing.assert_allclose(
val, [[1, 2, 3, 0]]
) # because recurrent projection is not used when executing: mech is reset each time
def test_recurrent_mech_reduce_fun(self):
with pytest.raises(TransferError) as error_text:
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Reduce(),
time_constant=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_recurrent_mech_reinforcement_fun(self):
with pytest.raises(TransferError) as error_text:
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Reinforcement(),
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_recurrent_mech_time_constant_0_8(self):
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
integrator_mode=True)
val = R.execute([1, 1, 1, 1])
np.testing.assert_allclose(val, [[0.8, 0.8, 0.8, 0.8]])
val = R.execute([1, 1, 1, 1])
np.testing.assert_allclose(val, [[.96, .96, .96, .96]])
def test_recurrent_mech_time_constant_0_8_initial_0_5(self):
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
initial_value=np.array(
[[0.5, 0.5, 0.5, 0.5]]),
integrator_mode=True)
val = R.execute([1, 1, 1, 1])
np.testing.assert_allclose(val, [[0.9, 0.9, 0.9, 0.9]])
val = R.execute([1, 2, 3, 4])
np.testing.assert_allclose(
val, [[.98, 1.78, 2.5800000000000005, 3.3800000000000003]
]) # due to inevitable floating point errors
def test_recurrent_mech_function_psyneulink(self):
a = Logistic(gain=2, offset=1)
R = RecurrentTransferMechanism(name='R', size=7, function=a)
val = R.execute(np.zeros(7))
np.testing.assert_allclose(val, [np.full(7, 0.2689414213699951)])
def test_recurrent_mech_function_logistic(self):
R = RecurrentTransferMechanism(name='R',
size=10,
function=Logistic(gain=2, offset=1))
val = R.execute(np.ones(10))
np.testing.assert_allclose(val, [np.full(10, 0.7310585786300049)])
def test_recurrent_mech_matrix_auto_hetero_spec_size_4(self):
R = RecurrentTransferMechanism(name='R', size=4, auto=2.2, hetero=-3)
val = R.execute([10, 10, 10, 10])
np.testing.assert_allclose(val, [[10., 10., 10., 10.]])
np.testing.assert_allclose(R.matrix,
[[2.2, -3, -3, -3], [-3, 2.2, -3, -3],
[-3, -3, 2.2, -3], [-3, -3, -3, 2.2]])
assert isinstance(R.matrix, np.ndarray)
def test_recurrent_mech_time_constant_0_8_initial_1_8(self):
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
initial_value=np.array(
[[1.8, 1.8, 1.8, 1.8]]),
integrator_mode=True)
val = R.execute([1, 1, 1, 1])
np.testing.assert_allclose(val, [[1.16, 1.16, 1.16, 1.16]])
val = R.execute([2, 2, 2, 2])
np.testing.assert_allclose(val, [[1.832, 1.832, 1.832, 1.832]])
val = R.execute([-4, -3, 0, 1])
np.testing.assert_allclose(val, [[
-2.8336, -2.0336000000000003, .36639999999999995,
1.1663999999999999
]])
def test_clip_2d_array(self):
R = RecurrentTransferMechanism(default_variable=[[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0],
[0.0, 0.0, 0.0]],
clip=[-2.0, 2.0])
assert np.allclose(
R.execute([[-5.0, -1.0, 5.0], [5.0, -5.0, 1.0], [1.0, 5.0, 5.0]]),
[[-2.0, -1.0, 2.0], [2.0, -2.0, 1.0], [1.0, 2.0, 2.0]])
def test_recurrent_mech_hetero_matrix_matrix_spec(self):
R = RecurrentTransferMechanism(name='R',
size=4,
hetero=np.array([[-4, -3, -2, -1]] * 4),
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([1, 2, 3, 4])
np.testing.assert_allclose(val, [[1., 2., 3., 4.]])
np.testing.assert_allclose(R.matrix,
[[1, -3, -2, -1], [-4, 2, -2, -1],
[-4, -3, 3, -1], [-4, -3, -2, 4]])
def test_recurrent_mech_auto_array_matrix_spec(self):
R = RecurrentTransferMechanism(name='R',
size=4,
auto=[1.1, 2.2, 3.3, 4.4],
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([10, 11, 12, 13])
np.testing.assert_allclose(val, [[10., 11., 12., 13.]])
np.testing.assert_allclose(
R.matrix,
[[1.1, 2, 3, 4], [1, 2.2, 3, 4], [1, 2, 3.3, 4], [1, 2, 3, 4.4]])
def test_recurrent_mech_auto_hetero_matrix_spec_v3(self):
R = RecurrentTransferMechanism(name='R',
size=4,
auto=[3],
hetero=2,
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([1, 2, 3, 4])
np.testing.assert_allclose(val, [[1., 2., 3., 4.]])
np.testing.assert_allclose(
R.matrix, [[3, 2, 2, 2], [2, 3, 2, 2], [2, 2, 3, 2], [2, 2, 2, 3]])
def test_recurrent_mech_matrix_keyword_spec(self):
for m in MATRIX_KEYWORD_VALUES:
if m == RANDOM_CONNECTIVITY_MATRIX:
continue
R = RecurrentTransferMechanism(name='R', size=4, matrix=m)
val = R.execute([10, 10, 10, 10])
np.testing.assert_allclose(val, [[10., 10., 10., 10.]])
np.testing.assert_allclose(R.recurrent_projection.matrix,
get_matrix(m, R.size[0], R.size[0]))
def test_recurrent_mech_hetero_float_matrix_spec(self):
# hetero should override off-diagonal only
R = RecurrentTransferMechanism(name='R',
size=4,
hetero=-2.2,
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([1, 2, 3, 4])
np.testing.assert_allclose(val, [[1., 2., 3., 4.]])
np.testing.assert_allclose(
R.matrix, [[1, -2.2, -2.2, -2.2], [-2.2, 2, -2.2, -2.2],
[-2.2, -2.2, 3, -2.2], [-2.2, -2.2, -2.2, 4]])
def test_recurrent_mech_auto_matrix_spec(self):
# auto should override the diagonal only
R = RecurrentTransferMechanism(name='R',
size=4,
auto=2.2,
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([10, 11, 12, 13])
np.testing.assert_allclose(val, [[10., 11., 12., 13.]])
np.testing.assert_allclose(
R.matrix,
[[2.2, 2, 3, 4], [1, 2.2, 3, 4], [1, 2, 2.2, 4], [1, 2, 3, 2.2]])
def test_recurrent_mech_time_constant_0_8_initial_1_2(self):
R = RecurrentTransferMechanism(name='R',
default_variable=[0, 0, 0, 0],
function=Linear(),
time_constant=0.8,
initial_value=np.array([[-1, 1, -2,
2]]),
integrator_mode=True)
val = R.execute([3, 2, 1, 0])
np.testing.assert_allclose(
val, [[2.2, 1.8, .40000000000000013, .3999999999999999]])
def test_recurrent_mech_matrix_hetero_spec(self):
R = RecurrentTransferMechanism(name='R', size=3, hetero=-1)
# (7/28/17 CW) these numbers assume that execute() leaves its value in the outputState of the mechanism: if
# the behavior of execute() changes, feel free to change these numbers
val = R.execute([-1, -2, -3])
np.testing.assert_allclose(val, [[-1, -2, -3]])
assert isinstance(R.matrix, np.ndarray)
np.testing.assert_allclose(R.matrix,
[[1, -1, -1], [-1, 1, -1], [-1, -1, 1]])
np.testing.assert_allclose(
run_twice_in_system(R, [1, 2, 3], [10, 11, 12]), [8, 7, 6])
def test_recurrent_mech_auto_hetero_matrix_spec_v1(self):
# auto and hetero should override matrix
R = RecurrentTransferMechanism(name='R',
size=4,
auto=[1, 3, 5, 7],
hetero=np.array([[-4, -3, -2, -1]] * 4),
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([1, 2, 3, 4])
np.testing.assert_allclose(val, [[1., 2., 3., 4.]])
np.testing.assert_allclose(R.matrix,
[[1, -3, -2, -1], [-4, 3, -2, -1],
[-4, -3, 5, -1], [-4, -3, -2, 7]])
def test_recurrent_mech_matrix_auto_hetero_matrix_spec(self):
# when auto, hetero, and matrix are all specified, auto and hetero should take precedence
R = RecurrentTransferMechanism(name='R',
size=4,
auto=2.2,
hetero=-3,
matrix=[[1, 2, 3, 4]] * 4)
val = R.execute([10, 10, 10, 10])
np.testing.assert_allclose(val, [[10., 10., 10., 10.]])
np.testing.assert_allclose(R.matrix,
[[2.2, -3, -3, -3], [-3, 2.2, -3, -3],
[-3, -3, 2.2, -3], [-3, -3, -3, 2.2]])
assert isinstance(R.matrix, np.ndarray)
def test_recurrent_mech_matrix_other_spec(self):
specs = [
np.matrix('1 2; 3 4'),
np.array([[1, 2], [3, 4]]), [[1, 2], [3, 4]], '1 2; 3 4'
]
for m in specs:
R = RecurrentTransferMechanism(name='R', size=2, matrix=m)
val = R.execute([10, 10])
np.testing.assert_allclose(val, [[10., 10.]])
assert isinstance(R.matrix, np.ndarray)
np.testing.assert_allclose(R.matrix, [[1, 2], [3, 4]])
np.testing.assert_allclose(R.recurrent_projection.matrix,
[[1, 2], [3, 4]])
assert isinstance(R.recurrent_projection.matrix, np.ndarray)
def test_recurrent_mech_matrix_hetero_spec(self):
R = RecurrentTransferMechanism(name='R', size=3, hetero=-1)
# (7/28/17 CW) these numbers assume that execute() leaves its value in the outputState of the mechanism: if
# the behavior of execute() changes, feel free to change these numbers
val = R.execute([-1, -2, -3])
np.testing.assert_allclose(val, [[-1, -2, -3]])
assert isinstance(R.matrix, np.ndarray)
np.testing.assert_allclose(R.matrix,
[[0, -1, -1], [-1, 0, -1], [-1, -1, 0]])
# Execution 1:
# Recurrent input = [5, 4, 3] | New input = [1, 2, 3] | Total input = [6, 6, 6]
# Output 1 = [6, 6, 6]
# Execution 2:
# Recurrent input =[-12, -12, -12] | New input = [10, 11, 12] | Total input = [-2, -1, 0]
# Output 2 = [-2, -1, 0]
np.testing.assert_allclose(
run_twice_in_system(R, [1, 2, 3], [10, 11, 12]), [-2., -1., 0.])
def test_clip_float(self):
R = RecurrentTransferMechanism(clip=[-2.0, 2.0])
assert np.allclose(R.execute(3.0), 2.0)
assert np.allclose(R.execute(-3.0), -2.0)
def test_clip_array(self):
R = RecurrentTransferMechanism(default_variable=[[0.0, 0.0, 0.0]],
clip=[-2.0, 2.0])
assert np.allclose(R.execute([3.0, 0.0, -3.0]), [2.0, 0.0, -2.0])
def test_recurrent_mech_inputs_list_of_floats(self):
R = RecurrentTransferMechanism(name='R', size=4)
val = R.execute([10.0, 10.0, 10.0, 10.0])
np.testing.assert_allclose(val, [[10.0, 10.0, 10.0, 10.0]])
def test_recurrent_mech_no_inputs(self):
R = RecurrentTransferMechanism(name='R')
np.testing.assert_allclose(R.instance_defaults.variable, [[0]])
val = R.execute([10])
np.testing.assert_allclose(val, [[10.]])
def test_recurrent_mech_inputs_mismatched_with_default_shorter(self):
with pytest.raises(MechanismError) as error_text:
R = RecurrentTransferMechanism(name='R', size=6)
R.execute([1, 2, 3, 4, 5])
assert "does not match required length" in str(error_text.value)
def test_recurrent_mech_matrix_auto_hetero_spec_size_1(self):
R = RecurrentTransferMechanism(name='R', size=1, auto=-2, hetero=4.4)
val = R.execute([10])
np.testing.assert_allclose(val, [[10.]])
assert isinstance(R.matrix, np.ndarray)
np.testing.assert_allclose(R.matrix, [[-2]])
