def test_input_port_and_assigned_projection_names(self):
T1 = pnl.TransferMechanism(name='T1')
T2 = pnl.TransferMechanism(name='T2', input_ports=[T1])
I1 = pnl.InputPort(owner=T2)
I2 = pnl.InputPort(projections=[T1])
assert I2.name == 'Deferred Init InputPort'
T2.add_ports([I2])
assert I1.name == 'InputPort-1'
assert I2.name == 'InputPort-2'
assert T2.input_ports[0].path_afferents[0].name == \
'MappingProjection from T1[RESULT] to T2[InputPort-0]'
assert T2.input_ports[2].path_afferents[0].name == \
'MappingProjection from T1[RESULT] to T2[InputPort-2]'
# ------------------------------------------------------------------------------------------------
# TEST 10
# Test that OutputPorts are properly named
T1 = pnl.TransferMechanism(output_ports=['MY OUTPUT_PORT', [0]])
assert T1.output_ports[0].name == 'MY OUTPUT_PORT'
assert T1.output_ports[1].name == 'OutputPort-0'
O = pnl.OutputPort(owner=T1)
assert T1.output_ports[2].name == 'OutputPort-1'
O2 = pnl.OutputPort()
T1.add_ports([O2])
assert T1.output_ports[3].name == 'OutputPort-2'
def test_internal_only(self):
m = pnl.TransferMechanism(input_ports=[
'EXTERNAL',
pnl.InputPort(name='INTERNAL_ONLY', internal_only=True)
])
assert m.input_values == [[0.], [0.]]
assert m.external_input_values == [[0.]]
def test_combine_param_conflicting_fct_class_spec(self):
with pytest.raises(pnl.InputPortError) as error_text:
t = pnl.TransferMechanism(input_ports=pnl.InputPort(
function=psyneulink.core.components.functions.nonstateful.
transferfunctions.Linear,
combine=pnl.PRODUCT))
assert "Specification of 'combine' argument (PRODUCT) conflicts with Function specified " \
"in 'function' argument (Linear) for InputPort" in str(error_text.value)
def test_combine_param_conflicting_fct_operation_spec(self):
with pytest.raises(pnl.InputPortError) as error_text:
t = pnl.TransferMechanism(input_ports=pnl.InputPort(
function=psyneulink.core.components.functions.nonstateful.
combinationfunctions.LinearCombination(operation=pnl.SUM),
combine=pnl.PRODUCT))
assert "Specification of 'combine' argument (PRODUCT) conflicts with specification of 'operation' (SUM) " \
"for LinearCombination in 'function' argument for InputPort" in str(error_text.value)
def test_combine_param_alone(self):
t1 = pnl.TransferMechanism(size=2)
t2 = pnl.TransferMechanism(size=2)
t3 = pnl.TransferMechanism(
size=2, input_ports=pnl.InputPort(combine=pnl.PRODUCT))
c = pnl.Composition(pathways=[[t1, t3], [t2, t3]])
input_dict = {t1: [1, 2], t2: [3, 4]}
val = c.run(inputs=input_dict)
assert np.allclose(val, [[3, 8]])
def test_combine_param_redundant_fct_constructor_spec(self):
t1 = pnl.TransferMechanism(size=2)
t2 = pnl.TransferMechanism(size=2)
t3 = pnl.TransferMechanism(
size=2,
input_ports=pnl.InputPort(function=psyneulink.core.components.functions.combinationfunctions.LinearCombination(operation=pnl.PRODUCT),
combine=pnl.PRODUCT))
p1 = pnl.Process(pathway=[t1, t3])
p2 = pnl.Process(pathway=[t2, t3])
s = pnl.System(processes=[p1,p2])
input_dict = {t1:[1,2],t2:[3,4]}
val = s.run(inputs=input_dict)
assert np.allclose(val, [[3, 8]])
def test_combine_param_alone(self):
t1 = pnl.TransferMechanism(size=2)
t2 = pnl.TransferMechanism(size=2)
t3 = pnl.TransferMechanism(
size=2,
input_ports=pnl.InputPort(
combine=pnl.PRODUCT))
p1 = pnl.Process(pathway=[t1, t3])
p2 = pnl.Process(pathway=[t2, t3])
s = pnl.System(processes=[p1,p2])
input_dict = {t1:[1,2],t2:[3,4]}
val = s.run(inputs=input_dict)
assert np.allclose(val, [[3, 8]])
def test_combine_param_redundant_fct_constructor_spec(self):
t1 = pnl.TransferMechanism(size=2)
t2 = pnl.TransferMechanism(size=2)
t3 = pnl.TransferMechanism(
size=2,
input_ports=pnl.InputPort(
function=psyneulink.core.components.functions.nonstateful.
combinationfunctions.LinearCombination(operation=pnl.PRODUCT),
combine=pnl.PRODUCT))
c = pnl.Composition(pathways=[[t1, t3], [t2, t3]])
input_dict = {t1: [1, 2], t2: [3, 4]}
val = c.run(inputs=input_dict)
assert np.allclose(val, [[3, 8]])
activation.set_log_conditions([pnl.RESULT, "mod_gain"])
stimulusInfo = pnl.TransferMechanism(default_variable=[[0.0, 0.0]],
size=2,
function=pnl.Linear(slope=1, intercept=0),
output_ports=[pnl.RESULT],
name="Stimulus Info")
stimulusInfo.set_log_conditions([pnl.RESULT])
controlledElement = pnl.TransferMechanism(
default_variable=[[0.0, 0.0]],
size=2,
function=pnl.Linear(slope=1, intercept=0),
input_ports=pnl.InputPort(combine=pnl.PRODUCT),
output_ports=[pnl.RESULT],
name='Stimulus Info * Activity')
controlledElement.set_log_conditions([pnl.RESULT])
ddmCombination = pnl.TransferMechanism(size=1,
function=pnl.Linear(slope=1,
intercept=0),
output_ports=[pnl.RESULT],
name="DDM Integrator")
ddmCombination.set_log_conditions([pnl.RESULT])
decisionMaker = pnl.DDM(
function=pnl.DriftDiffusionAnalytical(drift_rate=DRIFT,
starting_point=STARTING_POINT,