test_ransac.py 文件源码

def test_ransac_min_n_samples():
    base_estimator = LinearRegression()
    ransac_estimator1 = RANSACRegressor(base_estimator, min_samples=2,
                                        residual_threshold=5, random_state=0)
    ransac_estimator2 = RANSACRegressor(base_estimator,
                                        min_samples=2. / X.shape[0],
                                        residual_threshold=5, random_state=0)
    ransac_estimator3 = RANSACRegressor(base_estimator, min_samples=-1,
                                        residual_threshold=5, random_state=0)
    ransac_estimator4 = RANSACRegressor(base_estimator, min_samples=5.2,
                                        residual_threshold=5, random_state=0)
    ransac_estimator5 = RANSACRegressor(base_estimator, min_samples=2.0,
                                        residual_threshold=5, random_state=0)
    ransac_estimator6 = RANSACRegressor(base_estimator,
                                        residual_threshold=5, random_state=0)
    ransac_estimator7 = RANSACRegressor(base_estimator,
                                        min_samples=X.shape[0] + 1,
                                        residual_threshold=5, random_state=0)

    ransac_estimator1.fit(X, y)
    ransac_estimator2.fit(X, y)
    ransac_estimator5.fit(X, y)
    ransac_estimator6.fit(X, y)

    assert_array_almost_equal(ransac_estimator1.predict(X),
                              ransac_estimator2.predict(X))
    assert_array_almost_equal(ransac_estimator1.predict(X),
                              ransac_estimator5.predict(X))
    assert_array_almost_equal(ransac_estimator1.predict(X),
                              ransac_estimator6.predict(X))

    assert_raises(ValueError, ransac_estimator3.fit, X, y)
    assert_raises(ValueError, ransac_estimator4.fit, X, y)
    assert_raises(ValueError, ransac_estimator7.fit, X, y)