fafe8422549c1809ad66f124e842431009bbddba,skbio/stats/ordination/tests/test_ordination.py,TestCAResults,test_scaling2,#TestCAResults#,271

Before Change

        V_hat = np.array([[-0.84896, -0.88276],
                          [-0.22046,  1.34482],
                          [1.66697, -0.47032]])
        npt.assert_almost_equal(*normalize_signs(V_hat, scores.site),
                                decimal=5)

    def test_scaling1(self):
        scores = self.ordination.scores(scaling=1)
        // p. 458

After Change

    def test_scaling2(self):

        eigvals = pd.Series(np.array([0.09613302, 0.04094181]), ["CA1", "CA2"])
        // p. 460 L&L 1998
        features = pd.DataFrame(np.array([[0.40887, -0.06955], // F_hat
                                          [-0.11539, 0.29977],
                                          [-0.30997, -0.18739]]),
                                ["Species1", "Species2", "Species3"],
                                ["CA1", "CA2"])
        samples = pd.DataFrame(np.array([[-0.84896, -0.88276], // V_hat
                                         [-0.22046, 1.34482],
                                         [1.66697, -0.47032]]),
                               ["Site1", "Site2", "Site3"],
                               ["CA1", "CA2"])
        exp = OrdinationResults("CA", "Correspondance Analysis",
                                eigvals=eigvals, features=features,
                                samples=samples)

        scores = ca(self.contingency, 2)

        assert_ordination_results_equal(exp, scores,

Instances