diff --git a/GPy/testing/gp_tests.py b/GPy/testing/gp_tests.py
index 60dbe673..32a6c89f 100644
--- a/GPy/testing/gp_tests.py
+++ b/GPy/testing/gp_tests.py
@@ -3,13 +3,13 @@ Created on 4 Sep 2015
 
 @author: maxz
 """
-import unittest
-import numpy as np, GPy
+import numpy as np
+import GPy
 from GPy.core.parameterization.variational import NormalPosterior
 
 
-class Test(unittest.TestCase):
-    def setUp(self):
+class TestGP:
+    def setup(self):
         np.random.seed(12345)
         self.N = 20
         self.N_new = 50
@@ -19,6 +19,8 @@ class Test(unittest.TestCase):
         self.X_new = np.random.uniform(-3.0, 3.0, (self.N_new, 1))
 
     def test_setxy_bgplvm(self):
+        self.setup()
+
         k = GPy.kern.RBF(1)
         m = GPy.models.BayesianGPLVM(self.Y, 1, kernel=k)
         mu, var = m.predict(m.X)
@@ -36,6 +38,8 @@ class Test(unittest.TestCase):
         np.testing.assert_allclose(var, var2)
 
     def test_setxy_gplvm(self):
+        self.setup()
+
         k = GPy.kern.RBF(1)
         m = GPy.models.GPLVM(self.Y, 1, kernel=k)
         mu, var = m.predict(m.X)
@@ -53,6 +57,8 @@ class Test(unittest.TestCase):
         np.testing.assert_allclose(var, var2)
 
     def test_setxy_gp(self):
+        self.setup()
+
         k = GPy.kern.RBF(1)
         m = GPy.models.GPRegression(self.X, self.Y, kernel=k)
         mu, var = m.predict(m.X)
@@ -72,6 +78,8 @@ class Test(unittest.TestCase):
         from GPy.core.parameterization.param import Param
         from GPy.core.mapping import Mapping
 
+        self.setup()
+
         class Parabola(Mapping):
             def __init__(self, variance, degree=2, name="parabola"):
                 super(Parabola, self).__init__(1, 1, name)
@@ -111,8 +119,3 @@ class Test(unittest.TestCase):
         m.randomize()
         assert m.checkgrad()
         _ = m.predict(m.X)
-
-
-if __name__ == "__main__":
-    # import sys;sys.argv = ['', 'Test.testName']
-    unittest.main()