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Objective: Refactoring

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This commit is contained in:
Alinson S. Xavier
2021-04-03 18:52:17 -05:00
parent 185b95118a
commit ea5c35fe18
5 changed files with 90 additions and 112 deletions
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97
tests/components/test_objective.py
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@@ -114,18 +114,30 @@ def test_fit_xy() -> None:
reg = Mock(spec=Regressor)
reg.clone = Mock(side_effect=lambda: Mock(spec=Regressor))
comp = ObjectiveValueComponent(regressor=reg)
assert comp.ub_regressor is None
assert comp.lb_regressor is None
assert "Upper bound" not in comp.regressors
assert "Lower bound" not in comp.regressors
comp.fit_xy(x, y)
assert reg.clone.call_count == 2
assert comp.ub_regressor is not None
assert comp.lb_regressor is not None
assert comp.ub_regressor.fit.call_count == 1
assert comp.lb_regressor.fit.call_count == 1
assert_array_equal(comp.ub_regressor.fit.call_args[0][0], x["Upper bound"])
assert_array_equal(comp.lb_regressor.fit.call_args[0][0], x["Lower bound"])
assert_array_equal(comp.ub_regressor.fit.call_args[0][1], y["Upper bound"])
assert_array_equal(comp.lb_regressor.fit.call_args[0][1], y["Lower bound"])
assert "Upper bound" in comp.regressors
assert "Lower bound" in comp.regressors
assert comp.regressors["Upper bound"].fit.call_count == 1 # type: ignore
assert comp.regressors["Lower bound"].fit.call_count == 1 # type: ignore
assert_array_equal(
comp.regressors["Upper bound"].fit.call_args[0][0], # type: ignore
x["Upper bound"],
)
assert_array_equal(
comp.regressors["Lower bound"].fit.call_args[0][0], # type: ignore
x["Lower bound"],
)
assert_array_equal(
comp.regressors["Upper bound"].fit.call_args[0][1], # type: ignore
y["Upper bound"],
)
assert_array_equal(
comp.regressors["Lower bound"].fit.call_args[0][1], # type: ignore
y["Lower bound"],
)
def test_fit_xy_without_ub() -> None:
@@ -139,15 +151,21 @@ def test_fit_xy_without_ub() -> None:
reg = Mock(spec=Regressor)
reg.clone = Mock(side_effect=lambda: Mock(spec=Regressor))
comp = ObjectiveValueComponent(regressor=reg)
assert comp.ub_regressor is None
assert comp.lb_regressor is None
assert "Upper bound" not in comp.regressors
assert "Lower bound" not in comp.regressors
comp.fit_xy(x, y)
assert reg.clone.call_count == 1
assert comp.ub_regressor is None
assert comp.lb_regressor is not None
assert comp.lb_regressor.fit.call_count == 1
assert_array_equal(comp.lb_regressor.fit.call_args[0][0], x["Lower bound"])
assert_array_equal(comp.lb_regressor.fit.call_args[0][1], y["Lower bound"])
assert "Upper bound" not in comp.regressors
assert "Lower bound" in comp.regressors
assert comp.regressors["Lower bound"].fit.call_count == 1 # type: ignore
assert_array_equal(
comp.regressors["Lower bound"].fit.call_args[0][0], # type: ignore
x["Lower bound"],
)
assert_array_equal(
comp.regressors["Lower bound"].fit.call_args[0][1], # type: ignore
y["Lower bound"],
)
def test_sample_predict(
@@ -156,17 +174,27 @@ def test_sample_predict(
) -> None:
x, y = ObjectiveValueComponent.sample_xy(features, sample)
comp = ObjectiveValueComponent()
comp.lb_regressor = Mock(spec=Regressor)
comp.ub_regressor = Mock(spec=Regressor)
comp.lb_regressor.predict = Mock(side_effect=lambda _: np.array([[50.0]]))
comp.ub_regressor.predict = Mock(side_effect=lambda _: np.array([[60.0]]))
comp.regressors["Lower bound"] = Mock(spec=Regressor)
comp.regressors["Upper bound"] = Mock(spec=Regressor)
comp.regressors["Lower bound"].predict = Mock( # type: ignore
side_effect=lambda _: np.array([[50.0]])
)
comp.regressors["Upper bound"].predict = Mock( # type: ignore
side_effect=lambda _: np.array([[60.0]])
)
pred = comp.sample_predict(features, sample)
assert pred == {
"Lower bound": 50.0,
"Upper bound": 60.0,
}
assert_array_equal(comp.ub_regressor.predict.call_args[0][0], x["Upper bound"])
assert_array_equal(comp.lb_regressor.predict.call_args[0][0], x["Lower bound"])
assert_array_equal(
comp.regressors["Upper bound"].predict.call_args[0][0], # type: ignore
x["Upper bound"],
)
assert_array_equal(
comp.regressors["Lower bound"].predict.call_args[0][0], # type: ignore
x["Lower bound"],
)
def test_sample_predict_without_ub(
@@ -175,21 +203,26 @@ def test_sample_predict_without_ub(
) -> None:
x, y = ObjectiveValueComponent.sample_xy(features, sample_without_ub)
comp = ObjectiveValueComponent()
comp.lb_regressor = Mock(spec=Regressor)
comp.lb_regressor.predict = Mock(side_effect=lambda _: np.array([[50.0]]))
comp.regressors["Lower bound"] = Mock(spec=Regressor)
comp.regressors["Lower bound"].predict = Mock( # type: ignore
side_effect=lambda _: np.array([[50.0]])
)
pred = comp.sample_predict(features, sample_without_ub)
assert pred == {
"Lower bound": 50.0,
}
assert_array_equal(comp.lb_regressor.predict.call_args[0][0], x["Lower bound"])
assert_array_equal(
comp.regressors["Lower bound"].predict.call_args[0][0], # type: ignore
x["Lower bound"],
)
def test_sample_evaluate(features: Features, sample: TrainingSample) -> None:
comp = ObjectiveValueComponent()
comp.lb_regressor = Mock(spec=Regressor)
comp.lb_regressor.predict = lambda _: np.array([[1.05]])
comp.ub_regressor = Mock(spec=Regressor)
comp.ub_regressor.predict = lambda _: np.array([[2.50]])
comp.regressors["Lower bound"] = Mock(spec=Regressor)
comp.regressors["Lower bound"].predict = lambda _: np.array([[1.05]]) # type: ignore
comp.regressors["Upper bound"] = Mock(spec=Regressor)
comp.regressors["Upper bound"].predict = lambda _: np.array([[2.50]]) # type: ignore
ev = comp.sample_evaluate(features, sample)
assert ev == {
"Lower bound": {
@@ -213,5 +246,5 @@ def test_usage() -> None:
solver.solve(instance)
solver.fit([instance])
stats = solver.solve(instance)
assert stats["Lower bound"] == stats["Objective: Predicted LB"]
assert stats["Upper bound"] == stats["Objective: Predicted UB"]
assert stats["Lower bound"] == stats["Objective: Predicted lower bound"]
assert stats["Upper bound"] == stats["Objective: Predicted upper bound"]

2
tests/solvers/test_learning_solver.py
View File

@@ -133,7 +133,7 @@ def test_simulate_perfect():
simulate_perfect=True,
)
stats = solver.solve(tmp.name)
assert stats["Lower bound"] == stats["Objective: Predicted LB"]
assert stats["Lower bound"] == stats["Objective: Predicted lower bound"]
def test_gap():