def test_isotonic_regression(): y = np.array([3, 7, 5, 9, 8, 7, 10]) y_ = np.array([3, 6, 6, 8, 8, 8, 10]) assert_array_equal(y_, isotonic_regression(y)) x = np.arange(len(y)) ir = IsotonicRegression(y_min=0., y_max=1.) ir.fit(x, y) assert_array_equal(ir.fit(x, y).transform(x), ir.fit_transform(x, y)) assert_array_equal(ir.transform(x), ir.predict(x))
def test_isotonic_regression(): y = np.array([3, 7, 5, 9, 8, 7, 10]) y_ = np.array([3, 6, 6, 8, 8, 8, 10]) assert_array_equal(y_, isotonic_regression(y)) x = np.arange(len(y)) ir = IsotonicRegression(y_min=0., y_max=1.) ir.fit(x, y) assert_array_equal(ir.fit(x, y).transform(x), ir.fit_transform(x, y)) assert_array_equal(ir.transform(x), ir.predict(x)) # check that it is immune to permutation perm = np.random.permutation(len(y)) ir = IsotonicRegression(y_min=0., y_max=1.) assert_array_equal(ir.fit_transform(x[perm], y[perm]), ir.fit_transform(x, y)[perm]) assert_array_equal(ir.transform(x[perm]), ir.transform(x)[perm])