Remove workaround for since-fixed scipy regression, to remove recent scipy DeprecationWarning

Tests/test_scipy.py

@@ -1,53 +0,0 @@
-from helper import unittest, PillowTestCase
-from distutils.version import LooseVersion
-try:
-    import numpy as np
-    from numpy.testing import assert_equal
-
-    from scipy import misc
-    import scipy
-    HAS_SCIPY = True
-except ImportError:
-    HAS_SCIPY = False
-
-
-class Test_scipy_resize(PillowTestCase):
-    """ Tests for scipy regression in Pillow 2.6.0
-
-    Tests from https://github.com/scipy/scipy/blob/master/scipy/misc/pilutil.py
-    """
-
-    def setUp(self):
-        if not HAS_SCIPY:
-            self.skipTest("Scipy Required")
-
-    def test_imresize(self):
-        im = np.random.random((10, 20))
-        for T in np.sctypes['float'] + [float]:
-            # 1.1 rounds to below 1.1 for float16, 1.101 works
-            im1 = misc.imresize(im, T(1.101))
-            self.assertEqual(im1.shape, (11, 22))
-
-    # this test fails prior to scipy 0.14.0b1
-    # https://github.com/scipy/scipy/commit/855ff1fff805fb91840cf36b7082d18565fc8352
-    @unittest.skipIf(HAS_SCIPY and
-					 (LooseVersion(scipy.__version__) < LooseVersion('0.14.0')),
-                     "Test fails on scipy < 0.14.0")
-    def test_imresize4(self):
-        im = np.array([[1, 2],
-                       [3, 4]])
-        res = np.array([[1.,   1.25,  1.75,  2.],
-                        [1.5,  1.75,  2.25,  2.5],
-                        [2.5,  2.75,  3.25,  3.5],
-                        [3.,   3.25,  3.75,  4.]], dtype=np.float32)
-        # Check that resizing by target size, float and int are the same
-        im2 = misc.imresize(im, (4, 4), mode='F')  # output size
-        im3 = misc.imresize(im, 2., mode='F')  # fraction
-        im4 = misc.imresize(im, 200, mode='F')  # percentage
-        assert_equal(im2, res)
-        assert_equal(im3, res)
-        assert_equal(im4, res)
-
-
-if __name__ == '__main__':
-    unittest.main()

src/PIL/Image.py

@@ -1725,8 +1725,6 @@ class Image(object):
         ):
             raise ValueError("unknown resampling filter")
 
-        size = tuple(size)
-
         if box is None:
             box = (0, 0) + self.size
         else: