Update tests

Docstring and TODO

Update docstring

Style fixes

Update equalize_adapthist to use new view_as_windows

Update equalize_adapthist to use new view_as_windows

Try rbase again

Update equalize_adapthist to use new view_as_windows

Fix relative imports

Style fixes

Add a deprecation warning and add to api_changes.txt

Update TODO and switch to 0.13 deprecation

Preserve the current API as much as possible and defer to 0.14

Move the new kwarg to the very end

Clarify deprecation warning

Update to use row/col in clahe

Update docstring

Use optimal_step to set up view_as_windows

Update equalize_adapthist to use new view_as_windows

Try rbase again

Update equalize_adapthist to use new view_as_windows

Fix relative imports

Style fixes

Add a deprecation warning and add to api_changes.txt

Update TODO and switch to 0.13 deprecation

Preserve the current API as much as possible and defer to 0.14

TODO.txt

@@ -16,7 +16,7 @@ Version 0.13
 * Remove deprecated edge filters `hsobel`, `vsobel`, `hscharr`, `vscharr`,
   `hprewitt`, `vprewitt`, `roberts_positive_diagonal`,
   `roberts_negative_diagonal` in `skimage/filters/edges.py`
-* Remove deprecated ``ntiles_*` kwargs in ``equalize_adapthist``.
+
 
 
 Version 0.12

skimage/exposure/_adapthist.py

@@ -22,12 +22,16 @@ from ..exposure import rescale_intensity
 from ..util import view_as_windows
 <<<<<<< HEAD
 <<<<<<< HEAD
+<<<<<<< HEAD
 from .._shared.utils import skimage_deprecation, warnings
 =======
 >>>>>>> 3bcbbc0... Update equalize_adapthist to use new view_as_windows
 =======
 from .._shared.utils import skimage_deprecation
 >>>>>>> 446f383... Add a deprecation warning and add to api_changes.txt
+=======
+from .._shared.utils import skimage_deprecation, warnings
+>>>>>>> 204208a... Preserve the current API as much as possible and defer to 0.14
 
 
 NR_OF_GREY = 2 ** 14  # number of grayscale levels to use in CLAHE algorithm
@@ -35,6 +39,7 @@ NR_OF_GREY = 2 ** 14  # number of grayscale levels to use in CLAHE algorithm
 
 @adapt_rgb(hsv_value)
 <<<<<<< HEAD
+<<<<<<< HEAD
 def equalize_adapthist(image, ntiles_x=8, ntiles_y=8, clip_limit=0.01,
                        nbins=256, kernel_size=None):
 =======
@@ -43,6 +48,9 @@ def equalize_adapthist(image, kernel_size=64, ntiles_x=None, ntiles_y=None,
         clip_limit=0.01, nbins=256):
 >>>>>>> 3bcbbc0... Update equalize_adapthist to use new view_as_windows
 =======
+=======
+def equalize_adapthist(image, ntiles_x=8, ntiles_y=8, kernel_size=None,
+>>>>>>> 204208a... Preserve the current API as much as possible and defer to 0.14
                        clip_limit=0.01, nbins=256):
 >>>>>>> 172fb0d... Style fixes
     """Contrast Limited Adaptive Histogram Equalization (CLAHE).
@@ -58,23 +66,11 @@ def equalize_adapthist(image, kernel_size=64, ntiles_x=None, ntiles_y=None,
     kernel_size: integer or 2-tuple
         Defines the shape of contextual regions used in the algorithm.
         If an integer is given, the shape will be a square of
-<<<<<<< HEAD
-<<<<<<< HEAD
         sidelength given by this value.
     ntiles_x : int, optional (deprecated in favor of ``kernel_size``)
         Number of tile regions in the X direction (horizontal).
     ntiles_y : int, optional (deprecated if favor of ``kernel_size``)
         Number of tile regions in the Y direction (vertical).
-=======
-        sidelength given by its value.
-=======
-        sidelength given by this value.
->>>>>>> 172fb0d... Style fixes
-    ntiles_x : int, optional
-        Number of tile regions in the X direction.
-    ntiles_y : int, optional
-        Number of tile regions in the Y direction.
->>>>>>> 3bcbbc0... Update equalize_adapthist to use new view_as_windows
     clip_limit : float: optional
         Clipping limit, normalized between 0 and 1 (higher values give more
         contrast).
@@ -113,7 +109,7 @@ def equalize_adapthist(image, kernel_size=64, ntiles_x=None, ntiles_y=None,
         ntiles_x = ntiles_x or 8
         ntiles_y = ntiles_y or 8
         kernel_size = (np.round(image.shape[0] / ntiles_y),
-                       np.round(image.shape[1] / ntiles_x))
+                       np.round(image.shape[1] / ntiles_x))0.14
 
     if isinstance(kernel_size, numbers.Number):
         kernel_size = (kernel_size, kernel_size)

skimage/exposure/tests/test_exposure.py

@@ -214,8 +214,7 @@ def test_adapthist_grayscale():
     with expected_warnings(['precision loss|non-contiguous input', 
                             'deprecated']):
         adapted_old = exposure.equalize_adapthist(img, 10, 9, clip_limit=0.01,
-        adapted = exposure.equalize_adapthist(img, kernel_size=(57, 51), clip_limit=0.01, nbins=128)
-    assert_almost_equal = np.testing.assert_almost_equal
+        adapted = exposure.equalize_adapthist(img, kernel_size=(57, 51), clip_limit=0.01, nbins=128)most_equal
     assert img.shape == adapted.shape
     assert_almost_equal(peak_snr(img, adapted), 90.669, 3)
     assert_almost_equal(norm_brightness_err(img, adapted), 0.084, 3)