diff --git a/GPy/mappings/additive.py b/GPy/mappings/additive.py
index 1c86b680..0fb72ca4 100644
--- a/GPy/mappings/additive.py
+++ b/GPy/mappings/additive.py
@@ -23,9 +23,10 @@ class Additive(Mapping):
         assert(mapping1.input_dim==mapping2.input_dim)
         assert(mapping1.output_dim==mapping2.output_dim)
         input_dim, output_dim = mapping1.input_dim, mapping1.output_dim
-        Mapping.__init__(self, input_dim=input_dim, output_dim=output_dim)
+        super(Additive, self).__init__(input_dim=input_dim, output_dim=output_dim)
         self.mapping1 = mapping1
         self.mapping2 = mapping2
+        self.link_parameters(self.mapping1, self.mapping2)
 
     def f(self, X):
         return self.mapping1.f(X) + self.mapping2.f(X)
diff --git a/GPy/mappings/linear.py b/GPy/mappings/linear.py
index c105dd81..26504830 100644
--- a/GPy/mappings/linear.py
+++ b/GPy/mappings/linear.py
@@ -33,7 +33,7 @@ class Linear(Mapping):
         return np.dot(X, self.A)
 
     def update_gradients(self, dL_dF, X):
-        self.A.gradient = np.dot( X.T, dL_dF)
+        self.A.gradient = np.dot(X.T, dL_dF)
 
     def gradients_X(self, dL_dF, X):
         return np.dot(dL_dF, self.A.T)
diff --git a/GPy/testing/baseline/bayesian_gplvm_magnification.npz b/GPy/testing/baseline/bayesian_gplvm_magnification.npz
index 86f03dba..a9158607 100644
Binary files a/GPy/testing/baseline/bayesian_gplvm_magnification.npz and b/GPy/testing/baseline/bayesian_gplvm_magnification.npz differ
diff --git a/GPy/testing/baseline/gplvm_magnification.npz b/GPy/testing/baseline/gplvm_magnification.npz
index f1844df9..79ebe836 100644
Binary files a/GPy/testing/baseline/gplvm_magnification.npz and b/GPy/testing/baseline/gplvm_magnification.npz differ
diff --git a/GPy/testing/meanfunc_tests.py b/GPy/testing/meanfunc_tests.py
index 815c024f..53482a7a 100644
--- a/GPy/testing/meanfunc_tests.py
+++ b/GPy/testing/meanfunc_tests.py
@@ -28,10 +28,49 @@ class MFtests(unittest.TestCase):
         A linear mean function with parameters that we'll learn alongside the kernel
         """
 
+        X = np.linspace(-1,10,50).reshape(-1,1)
+        
+        Y = 3-np.abs((X-6))
+        Y += .5*np.cos(3*X) + 0.3*np.random.randn(*X.shape) 
+
+        mf = GPy.mappings.PiecewiseLinear(1, 1, [-1,1], [9,2])
+
+        k =GPy.kern.RBF(1)
+        lik = GPy.likelihoods.Gaussian()
+        m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf)
+        self.assertTrue(m.checkgrad())
+
+    def test_parametric_mean_function_composition(self):
+        """
+        A linear mean function with parameters that we'll learn alongside the kernel
+        """
+
         X = np.linspace(0,10,50).reshape(-1,1)
         Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + 3*X
 
-        mf = GPy.mappings.Linear(1,1)
+        mf = GPy.mappings.Compound(GPy.mappings.Linear(1,1), 
+                                   GPy.mappings.Kernel(1, 1, np.random.normal(0,1,(1,1)), 
+                                                       GPy.kern.RBF(1))
+                                   )
+
+        k =GPy.kern.RBF(1)
+        lik = GPy.likelihoods.Gaussian()
+        m = GPy.core.GP(X, Y, kernel=k, likelihood=lik, mean_function=mf)
+        self.assertTrue(m.checkgrad())
+
+    def test_parametric_mean_function_additive(self):
+        """
+        A linear mean function with parameters that we'll learn alongside the kernel
+        """
+
+        X = np.linspace(0,10,50).reshape(-1,1)
+        Y = np.sin(X) + 0.5*np.cos(3*X) + 0.1*np.random.randn(*X.shape) + 3*X
+
+        mf = GPy.mappings.Additive(GPy.mappings.Constant(1,1,3),
+               GPy.mappings.Additive(GPy.mappings.MLP(1,1),
+                     GPy.mappings.Identity(1,1)
+                           )
+                        )
 
         k =GPy.kern.RBF(1)
         lik = GPy.likelihoods.Gaussian()
diff --git a/travis_tests.py b/travis_tests.py
index 3c1c5c95..d44a1638 100644
--- a/travis_tests.py
+++ b/travis_tests.py
@@ -36,5 +36,5 @@ matplotlib.use('agg')
 import nose, warnings
 with warnings.catch_warnings():
     warnings.simplefilter("ignore")
-    nose.main('GPy', defaultTest='GPy/testing/', argv=['', '--show-skipped'])
+    nose.main('GPy', defaultTest='GPy/testing/plotting_tests.py', argv=['', '--show-skipped'])