Function assert_constraint

tests/python-gpu/test_monotonic_constraints.py:19–36

(constraint: int, tree_method: str)

def assert_constraint(constraint: int, tree_method: str) -> None:
    from sklearn.datasets import make_regression

    n = 1000
    X, y = make_regression(n, random_state=rng, n_features=1, n_informative=1)
    dtrain = xgb.DMatrix(X, y)
    param = {}
    param["tree_method"] = tree_method
    param["device"] = "cuda"
    param["monotone_constraints"] = "(" + str(constraint) + ")"
    bst = xgb.train(param, dtrain)
    dpredict = xgb.DMatrix(X[X[:, 0].argsort()])
    pred = bst.predict(dpredict)

    if constraint > 0:
        assert non_decreasing(pred)
    elif constraint < 0:
        assert non_increasing(pred)


@pytest.mark.skipif(**tm.no_sklearn())