old_contents: import numpy as np
  from numpy.testing import assert_equal, assert_array_equal
  from nose.tools import assert_true
  from skimage._shared.testing import assert_greater
  from skimage.segmentation import quickshift
  
  
  def test_grey():
      rnd = np.random.RandomState(0)
      img = np.zeros((20, 21))
      img[:10, 10:] = 0.2
      img[10:, :10] = 0.4
      img[10:, 10:] = 0.6
      img += 0.1 * rnd.normal(size=img.shape)
      seg = quickshift(img, kernel_size=2, max_dist=3, random_seed=0,
                       convert2lab=False, sigma=0)
      # we expect 4 segments:
      assert_equal(len(np.unique(seg)), 4)
      # that mostly respect the 4 regions:
      for i in range(4):
          hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0]
          assert_greater(hist[i], 20)
  
  
  def test_color():
      rnd = np.random.RandomState(0)
      img = np.zeros((20, 21, 3))
      img[:10, :10, 0] = 1
      img[10:, :10, 1] = 1
      img[10:, 10:, 2] = 1
      img += 0.01 * rnd.normal(size=img.shape)
      img[img > 1] = 1
      img[img < 0] = 0
      seg = quickshift(img, random_seed=0, max_dist=30, kernel_size=10, sigma=0)
      # we expect 4 segments:
      assert_equal(len(np.unique(seg)), 4)
      assert_array_equal(seg[:10, :10], 0)
      assert_array_equal(seg[10:, :10], 3)
      assert_array_equal(seg[:10, 10:], 1)
      assert_array_equal(seg[10:, 10:], 2)
  
      seg2 = quickshift(img, kernel_size=1, max_dist=2, random_seed=0,
              convert2lab=False, sigma=0)
      # very oversegmented:
      assert_equal(len(np.unique(seg2)), 7)
      # still don't cross lines
      assert_true((seg2[9, :] != seg2[10, :]).all())
      assert_true((seg2[:, 9] != seg2[:, 10]).all())
  
  
  if __name__ == '__main__':
      from numpy import testing
      testing.run_module_suite()
  
new_contents: import numpy as np
  from numpy.testing import assert_equal, assert_array_equal
  from nose.tools import assert_true
  from skimage._shared.testing import assert_greater
  from skimage.segmentation import quickshift
  
  
  def test_grey():
      rnd = np.random.RandomState(0)
      img = np.zeros((20, 21))
      img[:10, 10:] = 0.2
      img[10:, :10] = 0.4
      img[10:, 10:] = 0.6
      img += 0.1 * rnd.normal(size=img.shape)
      seg = quickshift(img, kernel_size=2, max_dist=3, random_seed=0,
                       convert2lab=False, sigma=0)
      # we expect 4 segments:
      assert_equal(len(np.unique(seg)), 4)
      # that mostly respect the 4 regions:
      for i in range(4):
          hist = np.histogram(img[seg == i], bins=[0, 0.1, 0.3, 0.5, 1])[0]
          assert_greater(hist[i], 20)
  
  
  def test_color():
      rnd = np.random.RandomState(0)
      img = np.zeros((20, 21, 3))
      img[:10, :10, 0] = 1
      img[10:, :10, 1] = 1
      img[10:, 10:, 2] = 1
      img += 0.01 * rnd.normal(size=img.shape)
      img[img > 1] = 1
      img[img < 0] = 0
      seg = quickshift(img, random_seed=0, max_dist=30, kernel_size=10, sigma=0)
      # we expect 4 segments:
      assert_equal(len(np.unique(seg)), 4)
      assert_array_equal(seg[:10, :10], 1)
      assert_array_equal(seg[10:, :10], 2)
      assert_array_equal(seg[:10, 10:], 0)
      assert_array_equal(seg[10:, 10:], 3)
  
      seg2 = quickshift(img, kernel_size=1, max_dist=2, random_seed=0,
              convert2lab=False, sigma=0)
      # very oversegmented:
      assert_equal(len(np.unique(seg2)), 7)
      # still don't cross lines
      assert_true((seg2[9, :] != seg2[10, :]).all())
      assert_true((seg2[:, 9] != seg2[:, 10]).all())
  
  
  if __name__ == '__main__':
      from numpy import testing
      testing.run_module_suite()
  
subject: FIX quickshift nosetest with different xyz color conversion