diff --git a/GPy/testing/mapping_tests.py b/GPy/testing/mapping_tests.py
index d07561ab..0c10e53b 100644
--- a/GPy/testing/mapping_tests.py
+++ b/GPy/testing/mapping_tests.py
@@ -5,6 +5,7 @@ import unittest
 import numpy as np
 import GPy
 
+
 class MappingGradChecker(GPy.core.Model):
     """
     This class has everything we need to check the gradient of a mapping. It
@@ -12,63 +13,65 @@ class MappingGradChecker(GPy.core.Model):
     mapping. the gradients are checked against the parameters of the mapping
     and the input.
     """
-    def __init__(self, mapping, X, name='map_grad_check'):
+
+    def __init__(self, mapping, X, name="map_grad_check"):
         super(MappingGradChecker, self).__init__(name)
         self.mapping = mapping
         self.link_parameter(self.mapping)
-        self.X = GPy.core.Param('X',X)
+        self.X = GPy.core.Param("X", X)
         self.link_parameter(self.X)
         self.dL_dY = np.random.randn(self.X.shape[0], self.mapping.output_dim)
+
     def log_likelihood(self):
         return np.sum(self.mapping.f(self.X) * self.dL_dY)
+
     def parameters_changed(self):
         self.X.gradient = self.mapping.gradients_X(self.dL_dY, self.X)
         self.mapping.update_gradients(self.dL_dY, self.X)
 
 
 class MappingTests(unittest.TestCase):
-
     def test_kernelmapping(self):
-        X = np.random.randn(100,3)
-        Z = np.random.randn(10,3)
+        X = np.random.randn(100, 3)
+        Z = np.random.randn(10, 3)
         mapping = GPy.mappings.Kernel(3, 2, Z, GPy.kern.RBF(3))
         self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
     def test_linearmapping(self):
         mapping = GPy.mappings.Linear(3, 2)
-        X = np.random.randn(100,3)
+        X = np.random.randn(100, 3)
         self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
     def test_mlpmapping(self):
         mapping = GPy.mappings.MLP(input_dim=3, hidden_dim=5, output_dim=2)
-        X = np.random.randn(100,3)
+        X = np.random.randn(100, 3)
         self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
     def test_mlpextmapping(self):
         np.random.seed(42)
-        X = np.random.randn(100,3)
-        for activation in ['tanh', 'relu', 'sigmoid']:
-            mapping = GPy.mappings.MLPext(input_dim=3, hidden_dims=[5,5], output_dim=2, activation=activation)
+        X = np.random.randn(100, 3)
+        for activation in ["tanh", "relu", "sigmoid"]:
+            mapping = GPy.mappings.MLPext(
+                input_dim=3, hidden_dims=[5, 5], output_dim=2, activation=activation
+            )
             self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
     def test_addmapping(self):
         m1 = GPy.mappings.MLP(input_dim=3, hidden_dim=5, output_dim=2)
         m2 = GPy.mappings.Linear(input_dim=3, output_dim=2)
         mapping = GPy.mappings.Additive(m1, m2)
-        X = np.random.randn(100,3)
+        X = np.random.randn(100, 3)
         self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
     def test_compoundmapping(self):
         m1 = GPy.mappings.MLP(input_dim=3, hidden_dim=5, output_dim=2)
-        Z = np.random.randn(10,2)
+        Z = np.random.randn(10, 2)
         m2 = GPy.mappings.Kernel(2, 4, Z, GPy.kern.RBF(2))
         mapping = GPy.mappings.Compound(m1, m2)
-        X = np.random.randn(100,3)
+        X = np.random.randn(100, 3)
         self.assertTrue(MappingGradChecker(mapping, X).checkgrad())
 
 
-
-
 if __name__ == "__main__":
     print("Running unit tests, please be (very) patient...")
     unittest.main()