def test_penalty_custom_fail(penalty_origin, value):
def custom_no_mult(ocp, nlp, t, x, u, p):
my_values = DM.zeros((12, 1)) + x[0]
return my_values
def custom_with_mult(ocp, nlp, t, x, u, p, mult):
my_values = DM.zeros((12, 1)) + x[0] * mult
return my_values
ocp = prepare_test_ocp()
x = [DM.ones((12, 1)) * value]
penalty_type = penalty_origin.CUSTOM
if isinstance(penalty_type, (ObjectiveFcn.Lagrange, ObjectiveFcn.Mayer)):
penalty = Objective(penalty_type)
else:
penalty = Constraint(penalty_type)
with pytest.raises(TypeError):
penalty.custom_function = custom_no_mult
penalty_type.value[0](penalty, ocp, ocp.nlp[0], [], x, [], [], mult=2)
with pytest.raises(TypeError):
penalty.custom_function = custom_with_mult
penalty_type.value[0](penalty, ocp, ocp.nlp[0], [], x, [], [])
with pytest.raises(TypeError):
keywords = [
"phase",
"list_index",
"name",
"type",
"params",
"node",
"quadratic",
"index",
"target",
"sliced_target",
"min_bound",
"max_bound",
"custom_function",
"weight",
]
for keyword in keywords:
exec(f"""def custom_with_keyword(ocp, nlp, t, x, u, p, {keyword}):
my_values = DM.zeros((12, 1)) + x[index]
return my_values""")
exec("""penalty.custom_function = custom_with_keyword""")
exec(
f"""penalty_type.value[0](penalty, ocp, ocp.nlp[0], [], x, [], [], {keyword}=0)"""
)
def test_penalty_custom(penalty_origin, value):
def custom(pn, mult):
my_values = DM.zeros((12, 1)) + pn.x[0] * mult
return my_values
ocp = prepare_test_ocp()
t = [0]
x = [DM.ones((12, 1)) * value]
penalty_type = penalty_origin.CUSTOM
if isinstance(penalty_type, (ObjectiveFcn.Lagrange, ObjectiveFcn.Mayer)):
penalty = Objective(penalty_type, index=0)
else:
penalty = Constraint(penalty_type, index=0)
penalty.custom_function = custom
mult = 2
penalty_type.value[0](penalty,
PenaltyNodes(ocp, ocp.nlp[0], t, x, [], []),
mult=mult)
if isinstance(penalty_type, (ObjectiveFcn.Lagrange, ObjectiveFcn.Mayer)):
res = ocp.nlp[0].J[0][0]["val"]
else:
res = ocp.nlp[0].g[0][0]["val"]
np.testing.assert_almost_equal(res, np.array([[value * mult]] * 12))
if isinstance(penalty_type, ConstraintFcn):
np.testing.assert_almost_equal(ocp.nlp[0].g[0][0]["bounds"].min,
np.array([[0]] * 12))
np.testing.assert_almost_equal(ocp.nlp[0].g[0][0]["bounds"].max,
np.array([[0]] * 12))
