@geomstats.tests.np_and_autograd_only
def test_fit_matrix_se(self):
    se_mat = SpecialEuclidean(n=3)
    X = se_mat.random_point(self.n_samples)
    estimator = ExponentialBarycenter(se_mat)
    estimator.fit(X)
    mean = estimator.estimate_
    tpca = TangentPCA(metric=se_mat)
    tangent_projected_data = tpca.fit_transform(X, base_point=mean)
    result = tpca.inverse_transform(tangent_projected_data)
    expected = X
    self.assertAllClose(result, expected)
@geomstats.tests.np_and_autograd_only
def test_fit_matrix_se(self):
    se_mat = SpecialEuclidean(n=3)
    X = se_mat.random_point(self.n_samples)
    estimator = ExponentialBarycenter(se_mat)
    estimator.fit(X)
    mean = estimator.estimate_
    tpca = TangentPCA(metric=se_mat)
    tangent_projected_data = tpca.fit_transform(X, base_point=mean)
    result = tpca.inverse_transform(tangent_projected_data)
    expected = X
    self.assertAllClose(result, expected)