More python2.5 fixes

Fabian Pedregosa · Fabian Pedregosa · commit 9c3f807a9246 · 2011-09-21T11:07:41.000+02:00
diff --git a/sklearn/manifold/locally_linear.py b/sklearn/manifold/locally_linear.py
@@ -263,7 +263,8 @@ def locally_linear_embedding(
         # we'll compute M = (I-W)'(I-W)
         # depending on the solver, we'll do this differently
         if M_sparse:
-            M = eye(*W.shape, format=W.format) - W
+            # the **kwargs syntax is for python2.5 compatibility
+            M = eye(*W.shape, **{'format' : W.format}) - W
             M = np.dot(M.T, M).tocsr()
         else:
             M = (np.dot(W.T, W) - (W.T + W)).todense()
diff --git a/sklearn/neighbors/regression.py b/sklearn/neighbors/regression.py
@@ -234,8 +234,6 @@ def predict(self, X):
                              for (i, ind) in enumerate(neigh_ind)])
 
 
-@deprecated("deprecated in v0.9; will be removed in v0.11; "
-            "use KNeighborsRegressor or RadiusNeighborsRegressor instead")
 class NeighborsRegressor(NeighborsBase, KNeighborsMixin, RadiusNeighborsMixin,
                          SupervisedFloatMixin,
                          RegressorMixin):
@@ -349,3 +347,8 @@ def predict(self, X):
             # compute interpolation on y
             return np.array([np.mean(self._y[ind])
                              for ind in neigh_ind])
+
+NeighborsRegressor = deprecated(
+    "deprecated in v0.9; will be removed in v0.11; "
+    "use KNeighborsRegressor or RadiusNeighborsRegressor instead")(
+    NeighborsRegressor)
diff --git a/sklearn/utils/extmath.py b/sklearn/utils/extmath.py
@@ -58,7 +58,7 @@ def _fast_logdet_numpy(A):
 except AttributeError:
      # math.factorial is only available in Python >= 2.6
      import operator
-     def factorial(x):
+     def factorial(n):
          # don't use reduce operator or 2to3 will fail.
          # ripped from http://www.joelbdalley.com/page.pl?38
          # Ensure that n is a Natural number
