From e49a2168f0b23cbb41a3393bc806d838d5a6d634 Mon Sep 17 00:00:00 2001
From: Marianne Corvellec <marianne.corvellec@ens-lyon.org>
Date: Sat, 12 Oct 2013 20:25:56 -0400
Subject: [PATCH] Added deprecation decorator according to discussion.

---
 skimage/filter/ctmf.py | 17 ++++++++++-------
 1 file changed, 10 insertions(+), 7 deletions(-)

diff --git a/skimage/filter/ctmf.py b/skimage/filter/ctmf.py
index 1763e536..e39aa8bc 100644
--- a/skimage/filter/ctmf.py
+++ b/skimage/filter/ctmf.py
@@ -1,5 +1,4 @@
-"""
-ctmf.py - constant time per pixel median filtering with an octagonal shape
+"""ctmf.py - constant time per pixel median filtering with an octagonal shape
 
 Reference: S. Perreault and P. Hebert, "Median Filtering in Constant Time",
 IEEE Transactions on Image Processing, September 2007.
@@ -16,8 +15,10 @@ import warnings
 import numpy as np
 from . import _ctmf
 from ._rank_order import rank_order
+from .._shared.utils import deprecated
 
 
+@deprecated('filter.rank.median')
 def median_filter(image, radius=2, mask=None, percent=50):
     """Masked median filter with octagon shape.
 
@@ -28,7 +29,7 @@ def median_filter(image, radius=2, mask=None, percent=50):
     radius : int
         Radius (in pixels) of a circle inscribed into the filtering
         octagon. Must be at least 2. Default radius is 2.
-    mask : (M,N) ndarray
+    mask : (M, N) ndarray
         Mask with 1's for significant pixels, 0's for masked pixels.
         By default, all pixels are considered significant.
     percent : int
@@ -43,6 +44,11 @@ def median_filter(image, radius=2, mask=None, percent=50):
         not overlap the mask, the filtered result is undefined, but
         in practice, it will be the lowest value in the valid area.
 
+    Notes
+    -----
+    Because of the histogram implementation, the number of unique values
+    for the output is limited to 256.
+
     Examples
     --------
     >>> a = np.ones((5, 5))
@@ -65,10 +71,7 @@ def median_filter(image, radius=2, mask=None, percent=50):
     if np.all(~ mask):
         warnings.warn('Mask is all over image! Returning copy of input image.')
         return image.copy()
-    #
-    # Some manipulation to handle float images and integer values outside
-    # range(256).
-    #
+    
     if (not np.issubdtype(image.dtype, np.int) or
         np.min(image) < 0 or np.max(image) > 255):
         ranked_values, translation = rank_order(image[mask])