Take a softer approach and raise a warning when a non-contiguous input is provided

doc/source/api_changes.txt

@@ -1,9 +1,6 @@
 Version 0.10
 ------------
 - Removed ``skimage.io.video`` functionality due to broken gstreamer bindings
-- The functions `skimage.util.view_as_blocks` and
-  `skimage.util.view_as_windows` now raise exceptions if the input data is not
-  contiguous.
 
 Version 0.9
 -----------

skimage/util/shape.py

@@ -2,6 +2,7 @@ __all__ = ['view_as_blocks', 'view_as_windows']
 
 import numpy as np
 from numpy.lib.stride_tricks import as_strided
+from warnings import warn
 
 
 def view_as_blocks(arr_in, block_shape):
@@ -12,8 +13,7 @@ def view_as_blocks(arr_in, block_shape):
     Parameters
     ----------
     arr_in : ndarray
-        Contiguous N-d input array.
-
+        N-d input array.
     block_shape : tuple
         The shape of the block. Each dimension must divide evenly into the
         corresponding dimensions of `arr_in`.
@@ -21,7 +21,8 @@ def view_as_blocks(arr_in, block_shape):
     Returns
     -------
     arr_out : ndarray
-        Block view of the input array.
+        Block view of the input array.  If `arr_in` is non-contiguous, a copy
+        is made.
 
     Examples
     --------
@@ -86,8 +87,10 @@ def view_as_blocks(arr_in, block_shape):
         raise ValueError("'block_shape' is not compatible with 'arr_in'")
 
     # -- restride the array to build the block view
+
     if not arr_in.flags.contiguous:
-        raise ValueError("Cannot provide views on a non-contiguous input array")
+        warn(RuntimeWarning("Cannot provide views on a non-contiguous input "
+                            "array without copying."))
 
     arr_in = np.ascontiguousarray(arr_in)
 
@@ -107,9 +110,9 @@ def view_as_windows(arr_in, window_shape, step=1):
 
     Parameters
     ----------
-    arr_in: ndarray
+    arr_in : ndarray
         Contiguous N-d input array.
-    window_shape: tuple
+    window_shape : tuple
         Defines the shape of the elementary n-dimensional orthotope
         (better know as hyperrectangle [1]_) of the rolling window view.
     step : int, optional
@@ -119,7 +122,7 @@ def view_as_windows(arr_in, window_shape, step=1):
 
     Returns
     -------
-    arr_out: ndarray
+    arr_out : ndarray
         (rolling) window view of the input array.
 
     Notes
@@ -230,7 +233,8 @@ def view_as_windows(arr_in, window_shape, step=1):
 
     # -- build rolling window view
     if not arr_in.flags.contiguous:
-        raise ValueError("Cannot provide views on a non-contiguous input array")
+        warn(RuntimeWarning("Cannot provide views on a non-contiguous input "
+                            "array without copying."))
 
     arr_in = np.ascontiguousarray(arr_in)
 

skimage/util/tests/test_shape.py

@@ -1,6 +1,7 @@
 import numpy as np
 from nose.tools import raises
-from numpy.testing import assert_equal, assert_raises
+from numpy.testing import assert_equal, assert_warns
+
 from skimage.util.shape import view_as_blocks, view_as_windows
 
 
@@ -151,8 +152,8 @@ def test_views_non_contiguous():
     A = np.arange(16).reshape((4, 4))
     A = A[::2, :]
 
-    assert_raises(ValueError, view_as_blocks, A, (2, 2))
-    assert_raises(ValueError, view_as_windows, A, (2, 2))
+    assert_warns(RuntimeWarning, view_as_blocks, A, (2, 2))
+    assert_warns(RuntimeWarning, view_as_windows, A, (2, 2))
 
 
 if __name__ == '__main__':