diff --git a/GPy/testing/quadrature_tests.py b/GPy/testing/quadrature_tests.py
index e519d87e..f6b361e9 100644
--- a/GPy/testing/quadrature_tests.py
+++ b/GPy/testing/quadrature_tests.py
@@ -1,9 +1,6 @@
 from __future__ import print_function, division
 import numpy as np
-import GPy
-import warnings
-from  ..util.quad_integrate import quadgk_int, quadvgk
-
+from ..util.quad_integrate import quadgk_int, quadvgk
 
 
 class QuadTests(np.testing.TestCase):
@@ -12,12 +9,14 @@ class QuadTests(np.testing.TestCase):
     we will take a function which can be integrated analytically and check if quadgk result is similar or not!
     through this file we can test how numerically accurate quadrature implementation in native numpy or manual code is.
     """
+
     def setUp(self):
         pass
 
     def test_infinite_quad(self):
         def f(x):
-            return np.exp(-0.5*x**2)*np.power(x,np.arange(3)[:,None])
+            return np.exp(-0.5 * x**2) * np.power(x, np.arange(3)[:, None])
+
         quad_int_val = quadgk_int(f)
         real_val = np.sqrt(np.pi * 2)
         np.testing.assert_almost_equal(real_val, quad_int_val[0], decimal=7)
@@ -25,15 +24,18 @@ class QuadTests(np.testing.TestCase):
     def test_finite_quad(self):
         def f2(x):
             return x**2
-        quad_int_val = quadvgk(f2, 1.,2.)
-        real_val = 7/3.
+
+        quad_int_val = quadvgk(f2, 1.0, 2.0)
+        real_val = 7 / 3.0
         np.testing.assert_almost_equal(real_val, quad_int_val, decimal=5)
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
+
     def f(x):
-        return np.exp(-0.5 * x ** 2) * np.power(x, np.arange(3)[:, None])
+        return np.exp(-0.5 * x**2) * np.power(x, np.arange(3)[:, None])
 
     quad_int_val = quadgk_int(f)
-    real_val = np.sqrt(np.pi*2)
+    real_val = np.sqrt(np.pi * 2)
     np.testing.assert_almost_equal(real_val, quad_int_val[0], decimal=7)
     print(quadgk_int(f))