fix issues with manifold tests throwing pep8 errors (scikit-learn#7209)

kykosic · Aug 20, 2016 · 5c6409c · 5c6409c
1 parent fa8fe85
commit 5c6409c
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Showing 2 changed files with 9 additions and 6 deletions.
diff --git a/sklearn/manifold/tests/test_locally_linear.py b/sklearn/manifold/tests/test_locally_linear.py
@@ -14,7 +14,7 @@
 eigen_solvers = ['dense', 'arpack']
 
 
-#----------------------------------------------------------------------
+# ----------------------------------------------------------------------
 # Test utility routines
 def test_barycenter_kneighbors_graph():
     X = np.array([[0, 1], [1.01, 1.], [2, 0]])
@@ -33,7 +33,7 @@ def test_barycenter_kneighbors_graph():
     assert_less(linalg.norm(pred - X) / X.shape[0], 1)
 
 
-#----------------------------------------------------------------------
+# ----------------------------------------------------------------------
 # Test LLE by computing the reconstruction error on some manifolds.
 
 def test_lle_simple_grid():

diff --git a/sklearn/manifold/tests/test_t_sne.py b/sklearn/manifold/tests/test_t_sne.py
@@ -196,10 +196,13 @@ def test_gradient():
 
     P = _joint_probabilities(distances, desired_perplexity=25.0,
                              verbose=0)
-    fun = lambda params: _kl_divergence(params, P, alpha, n_samples,
-                                        n_components)[0]
-    grad = lambda params: _kl_divergence(params, P, alpha, n_samples,
-                                         n_components)[1]
+
+    def fun(params):
+        return _kl_divergence(params, P, alpha, n_samples, n_components)[0]
+
+    def grad(params):
+        return _kl_divergence(params, P, alpha, n_samples, n_components)[1]
+
     assert_almost_equal(check_grad(fun, grad, X_embedded.ravel()), 0.0,
                         decimal=5)