ENH: Rename ssid to structural_similarity to avoid confusion with self-similarity features.

skimage/measure/_ssim.py

@@ -1,6 +1,6 @@
 from __future__ import division
 
-__all__ = ['ssim']
+__all__ = ['structural_similarity']
 
 import numpy as np
 from numpy.lib import stride_tricks
@@ -39,8 +39,8 @@ def _as_windows(X, win_size=7, flatten_first_axis=True):
     return windows
 
 
-def ssim(X, Y, win_size=7, gradient=False, dynamic_range=255):
-    """Compute the structural similarity index between two images.
+def structural_similarity(X, Y, win_size=7, gradient=False, dynamic_range=255):
+    """Compute the mean structural similarity index between two images.
 
     Parameters
     ----------

skimage/measure/tests/test_ssim.py

@@ -1,7 +1,7 @@
 import numpy as np
 from numpy.testing import assert_equal
 
-from skimage.measure._ssim import ssim, _as_windows
+from skimage.measure._ssim import structural_similarity as ssim, _as_windows
 import scipy.optimize as opt
 
 def test_ssim_patch_range():
@@ -29,7 +29,7 @@ def test_ssim_image():
 
     S0 = ssim(X, X, win_size=3)
     assert_equal(S0, 1)
-    
+
     S1 = ssim(X, Y, win_size=3)
     assert(S1 < 0.3)
 
@@ -46,12 +46,6 @@ def test_ssim_grad():
 
     assert(np.all(opt.check_grad(func, grad, Y) < 0.05))
 
-#    N = 200
-#    X = np.random.random((N, N))
-#    Y = np.random.random((N, N))
-
-#    assert(np.all(np.abs(ssim(X, Y, gradient=True))[1] < 1e-2))
-
 
 if __name__ == "__main__":
     np.testing.run_module_suite()