

def test_quantile_strategy_regressor():
    random_state = np.random.RandomState(seed=1)
    X = ([[0]] * 5)
    y = random_state.randn(5)
    reg = DummyRegressor(strategy='quantile', quantile=0.5)
    reg.fit(X, y)
    assert_array_equal(reg.predict(X), ([np.median(y)] * len(X)))
    reg = DummyRegressor(strategy='quantile', quantile=0)
    reg.fit(X, y)
    assert_array_equal(reg.predict(X), ([np.min(y)] * len(X)))
    reg = DummyRegressor(strategy='quantile', quantile=1)
    reg.fit(X, y)
    assert_array_equal(reg.predict(random_state), ([np.max(y)] * len(X)))
    reg = DummyRegressor(strategy='quantile', quantile=0.3)
    reg.fit(X, y)
    assert_array_equal(reg.predict(X), ([np.percentile(y, q=30)] * len(X)))

dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/tests/test_dummy.py test_quantile_strategy_regressor/VarMisuse@167/202 `X`->`random_state`