diff --git a/Wrappers/Python/cil/optimisation/functions/Function.py b/Wrappers/Python/cil/optimisation/functions/Function.py
index 21d55e20b0..f1a6479cdb 100644
--- a/Wrappers/Python/cil/optimisation/functions/Function.py
+++ b/Wrappers/Python/cil/optimisation/functions/Function.py
@@ -394,7 +394,7 @@ def __call__(self, x):
                 		
         return super(SubsetSumFunction, self).__call__(x)      
         
-    def _full_gradient(self, x, out=None):
+    def full_gradient(self, x, out=None):
 
         r""" Computes the full gradient at :code:`x`. It is the sum of all the gradients for each function. """
         return super(SubsetSumFunction, self).gradient(x, out=out)
diff --git a/Wrappers/Python/test/test_SubsetSumFunction.py b/Wrappers/Python/test/test_SubsetSumFunction.py
index 58289f0f7d..bfe659b568 100644
--- a/Wrappers/Python/test/test_SubsetSumFunction.py
+++ b/Wrappers/Python/test/test_SubsetSumFunction.py
@@ -51,7 +51,7 @@ def test_call_method(self):
     def test_full_gradient(self):
         
         res1 = self.f.gradient(self.x_cil)
-        res2 = self.f_subset_sum_function._full_gradient(self.x_cil)
+        res2 = self.f_subset_sum_function.full_gradient(self.x_cil)
         np.testing.assert_allclose(res1.array, res2.array, atol=1e-3)        
 
     def test_sampling_sequential(self):