1. Updated numpy as np

theano/tensor/tests/test_fourier.py

 from __future__ import absolute_import, print_function, division
-import numpy
+import numpy as np
 from numpy.testing import dec
 
 import theano
@@ -10,7 +10,7 @@ from theano.tensor.fourier import Fourier, fft
 
 class TestFourier(utt.InferShapeTester):
 
-    rng = numpy.random.RandomState(43)
+    rng = np.random.RandomState(43)
 
     def setUp(self):
         super(TestFourier, self).setUp()
@@ -20,24 +20,24 @@ class TestFourier(utt.InferShapeTester):
     def test_perform(self):
         a = tensor.dmatrix()
         f = theano.function([a], self.op(a, n=10, axis=0))
-        a = numpy.random.rand(8, 6)
-        assert numpy.allclose(f(a), numpy.fft.fft(a, 10, 0))
+        a = np.random.rand(8, 6)
+        assert np.allclose(f(a), np.fft.fft(a, 10, 0))
 
     def test_infer_shape(self):
         a = tensor.dvector()
         self._compile_and_check([a], [self.op(a, 16, 0)],
-                                [numpy.random.rand(12)],
+                                [np.random.rand(12)],
                                self.op_class)
         a = tensor.dmatrix()
         for var in [self.op(a, 16, 1), self.op(a, None, 1),
                      self.op(a, 16, None), self.op(a, None, None)]:
             self._compile_and_check([a], [var],
-                                    [numpy.random.rand(12, 4)],
+                                    [np.random.rand(12, 4)],
                                     self.op_class)
         b = tensor.iscalar()
         for var in [self.op(a, 16, b), self.op(a, None, b)]:
             self._compile_and_check([a, b], [var],
-                                    [numpy.random.rand(12, 4), 0],
+                                    [np.random.rand(12, 4), 0],
                                     self.op_class)
 
     @dec.skipif(True, "Complex grads not enabled, see #178")
@@ -54,10 +54,10 @@ class TestFourier(utt.InferShapeTester):
         def fft_test4(a):
             return self.op(a, 4, 0)
 
-        pts = [numpy.random.rand(5, 2, 4, 3),
-               numpy.random.rand(2, 3, 4),
-               numpy.random.rand(2, 5),
-               numpy.random.rand(5)]
+        pts = [np.random.rand(5, 2, 4, 3),
+               np.random.rand(2, 3, 4),
+               np.random.rand(2, 5),
+               np.random.rand(5)]
         for fft_test in [fft_test1, fft_test2, fft_test3, fft_test4]:
             for pt in pts:
                 theano.gradient.verify_grad(fft_test, [pt],