Added Testcase for LDA-Covariance

Author: mbillingr

sklearn/tests/test_lda.py

@@ -149,3 +149,17 @@ def test_lda_scaling():
         # should be able to separate the data perfectly
         assert_equal(clf.fit(x, y).score(x, y), 1.0,
                      'using covariance: %s' % solver)
+
+
+def test_covariance():
+    x, y = make_blobs(n_samples=100, n_features=5,
+                      centers=1, random_state=42)
+
+    # make features correlated
+    x = np.dot(x, np.arange(x.shape[1] ** 2).reshape(x.shape[1], x.shape[1]))
+
+    c_e = lda._cov(x, 'empirical')
+    assert_almost_equal(c_e, c_e.T)
+
+    c_s = lda._cov(x, 'auto')
+    assert_almost_equal(c_s, c_s.T)