old_contents: import os.path
  
  import numpy as np
  from numpy.testing import *
  
  from scikits.image import data_dir
  from scikits.image.io import *
  from scikits.image.filter import *
  
  class TestLPIFilter2D():
      img = imread(os.path.join(data_dir, 'camera.png'),
                   flatten=True)[:-101,:-100]
  
      def filt_func(self,r,c):
          return np.exp(-np.hypot(r,c)/1)
  
      def setUp(self):
          self.f = LPIFilter2D(self.filt_func)
  
      def tst_shape(self, x):
          X = self.f(x)
          assert_equal(X.shape,x.shape)
  
      def test_ip_shape(self):
          rows,columns = self.img.shape[:2]
  
          for c_slice in [slice(0, columns), slice(0, columns - 5),
                          slice(0, columns - 100)]:
              yield (self.tst_shape, self.img[:,c_slice])
  
      def test_inverse(self):
          F = self.f(self.img)
          g = inverse(F, predefined_filter=self.f)
          assert_equal(g.shape, self.img.shape)
  
          g1 = inverse(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
          # test cache
          g1 = inverse(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
          g1 = inverse(F[::-1, ::-1], self.filt_func)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
      def test_wiener(self):
          F = self.f(self.img)
          g = wiener(F, predefined_filter=self.f)
          assert_equal(g.shape, self.img.shape)
  
          g1 = wiener(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 1)
  
          g1 = wiener(F[::-1,::-1], self.filt_func)
          assert ((g - g1[::-1,::-1]).sum() < 1)
  
  if __name__ == "__main__":
      run_module_suite()
  
  
new_contents: import os.path
  
  import numpy as np
  from numpy.testing import *
  
  from scikits.image import data_dir
  from scikits.image.io import *
  from scikits.image.filter import *
  
  class TestLPIFilter2D():
      img = imread(os.path.join(data_dir, 'camera.png'),
                   flatten=True)[:50,:50]
  
      def filt_func(self,r,c):
          return np.exp(-np.hypot(r,c)/1)
  
      def setUp(self):
          self.f = LPIFilter2D(self.filt_func)
  
      def tst_shape(self, x):
          X = self.f(x)
          assert_equal(X.shape, x.shape)
  
      def test_ip_shape(self):
          rows, columns = self.img.shape[:2]
  
          for c_slice in [slice(0, columns), slice(0, columns - 5),
                          slice(0, columns - 20)]:
              yield (self.tst_shape, self.img[:, c_slice])
  
      def test_inverse(self):
          F = self.f(self.img)
          g = inverse(F, predefined_filter=self.f)
          assert_equal(g.shape, self.img.shape)
  
          g1 = inverse(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
          # test cache
          g1 = inverse(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
          g1 = inverse(F[::-1, ::-1], self.filt_func)
          assert ((g - g1[::-1,::-1]).sum() < 55)
  
      def test_wiener(self):
          F = self.f(self.img)
          g = wiener(F, predefined_filter=self.f)
          assert_equal(g.shape, self.img.shape)
  
          g1 = wiener(F[::-1,::-1], predefined_filter=self.f)
          assert ((g - g1[::-1,::-1]).sum() < 1)
  
          g1 = wiener(F[::-1,::-1], self.filt_func)
          assert ((g - g1[::-1,::-1]).sum() < 1)
  
  if __name__ == "__main__":
      run_module_suite()
  
  
subject: Make LPIFilter tests operate on a smaller image, since they take long to execute, and cameraman.png is now bigger than before.