Test for training function.

TF_Implementation/test/test_RBF_tf.py

@@ -43,6 +43,15 @@ class TestRBFAdaptiveModel(unittest.TestCase):
         
         self.assertEqual(output.shape, (3, 1))
 
-        
+    def test_train(self):
+        """ Test the train method."""
+        initial_weights = self.model.rbf_layer.centers.numpy().copy()
+        errors = np.random.normal(size=(100, self.input_dim))   # create 100 samples of input errors
+        control_signals = np.random.normal(size=(100, 1)) # create 100 matching control signals
+        train_rbf_adaptive(self.model, errors, control_signals, 10)
+
+        new_weights = self.model.rbf_layer.centers.numpy()
+        self.assertFalse(np.array_equal(initial_weights, new_weights))
+
 if __name__ == '__main__':
     unittest.main()