Replaced double-underscores to fit with PEP8, and testing the types r…

…eturned by the serialisation. If it's numpy arrays' then it's guaranteed cross platform.

sknn/mlp.py

@@ -313,7 +313,7 @@ def _create_mlp(self):
             input_space=self.input_space)
 
         if self.weights is not None:
-            self.__array_to_mlp(self.weights, self.mlp)
+            self._array_to_mlp(self.weights, self.mlp)
             self.weights = None
 
         inputs = self.mlp.get_input_space().make_theano_batch()
@@ -388,14 +388,14 @@ def __getstate__(self):
             "The neural network has not been initialized."
 
         d = self.__dict__.copy()
-        d['weights'] = self.__mlp_to_array()
+        d['weights'] = self._mlp_to_array()
 
         for k in ['ds', 'vs', 'f', 'trainer', 'mlp']:
             if k in d:
                 del d[k]
         return d
 
-    def __mlp_to_array(self):
+    def _mlp_to_array(self):
         return [(l.get_weights(), l.get_biases()) for l in self.mlp.layers]
 
     def __setstate__(self, d):
@@ -404,7 +404,7 @@ def __setstate__(self, d):
             setattr(self, k, None)
         self._create_mlp()
 
-    def __array_to_mlp(self, array, nn):
+    def _array_to_mlp(self, array, nn):
         for layer, (weights, biases) in zip(nn.layers, array):
             assert layer.get_weights().shape == weights.shape
             layer.set_weights(weights)

sknn/tests/test_linear.py

@@ -76,6 +76,11 @@ def setUp(self):
         buf.seek(0)
         self.nn = pickle.load(buf)
 
+    def test_TypeOfWeightsArray(self):
+        for w, b in self.nn._mlp_to_array():
+            assert_equal(type(w), numpy.ndarray)
+            assert_equal(type(b), numpy.ndarray)
+
     def test_FitAutoInitialize(self):
         # Override base class test, you currently can't re-train a network that
         # was serialized and deserialized.