_____________________________ test_sag_regressor ______________________________
    @pytest.mark.filterwarnings('ignore:The max_iter was reached')
    def test_sag_regressor():
        """tests if the sag regressor performs well"""
        xmin, xmax = -5, 5
        n_samples = 20
        tol = .001
        max_iter = 20
        alpha = 0.1
        rng = np.random.RandomState(0)
        X = np.linspace(xmin, xmax, n_samples).reshape(n_samples, 1)
    
        # simple linear function without noise
        y = 0.5 * X.ravel()
    
        clf1 = Ridge(tol=tol, solver='sag', max_iter=max_iter,
                     alpha=alpha * n_samples)
        clf2 = clone(clf1)
        clf1.fit(X, y)
        clf2.fit(sp.csr_matrix(X), y)
        score1 = clf1.score(X, y)
        score2 = clf2.score(X, y)
        assert_greater(score1, 0.99)
>       assert_greater(score2, 0.99)
c:\python37\lib\site-packages\sklearn\linear_model\tests\test_sag.py:477: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
c:\python37\lib\unittest\case.py:1238: in assertGreater
    self.fail(self._formatMessage(msg, standardMsg))
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
self = <sklearn.utils._unittest_backport.TestCase testMethod=__init__>
msg = '0.9774630692168063 not greater than 0.99'
    def fail(self, msg=None):
        """Fail immediately, with the given message."""
>       raise self.failureException(msg)
E       AssertionError: 0.9774630692168063 not greater than 0.99