rescale calls _multichannel_default too. update multichannel docstrings

skimage/transform/_warps.py

@@ -6,6 +6,14 @@
                          _convert_warp_input, _clip_warp_output)
 
 
+def _multichannel_default(multichannel, ndim):
+    # utility for maintaining previous color image default behavior
+    if ndim == 3:
+        return True
+    else:
+        return False
+
+
 def resize(image, output_shape, order=1, mode='constant', cval=0, clip=True,
            preserve_range=False):
     """Resize image to match a certain size.
@@ -156,7 +164,8 @@ def rescale(image, scale, order=1, mode='constant', cval=0, clip=True,
         Whether to keep the original range of values. Otherwise, the input
         image is converted according to the conventions of `img_as_float`.
     multichannel : bool, optional
-        If True, last axis will not be rescaled.
+        If True, last axis will not be rescaled.  The default is True for 3D
+        (2D+color) inputs, False otherwise.
 
     Examples
     --------
@@ -170,7 +179,7 @@ def rescale(image, scale, order=1, mode='constant', cval=0, clip=True,
 
     """
     if multichannel is None:
-        multichannel = False  # maintain previous default behavior
+        multichannel = _multichannel_default(multichannel, image.ndim)
     scale = np.atleast_1d(scale)
     if len(scale) > 1 and len(scale) != image.ndim:
         raise ValueError("must supply a single scale or one value per axis.")

skimage/transform/pyramids.py

@@ -3,22 +3,13 @@
 from scipy import ndimage
 from ..transform import resize
 from ..util import img_as_float
-
-
-def _previous_multichannel_default(multichannel, ndim):
-    if multichannel is None:
-        # needed to maintain previous default behavior
-        if ndim == 3:
-            return True
-        else:
-            return False
-    else:
-        return multichannel
+from ._warps import _multichannel_default
 
 
 def _smooth(image, sigma, mode, cval, multichannel=None):
     """Return image with each channel smoothed by the Gaussian filter."""
-    multichannel = _previous_multichannel_default(multichannel, image.ndim)
+    if multichannel is None:
+        multichannel = _multichannel_default(multichannel, image.ndim)
     smoothed = np.empty(image.shape, dtype=np.double)
 
     # apply Gaussian filter to all channels independently
@@ -61,8 +52,8 @@ def pyramid_reduce(image, downscale=2, sigma=None, order=1,
         cval is the value when mode is equal to 'constant'.
     cval : float, optional
         Value to fill past edges of input if mode is 'constant'.
-    multichannel : bool, optional
-        If True and ``image.ndim > 2``, treat last axis as channels.
+        If True, last axis will not be rescaled.  The default is True for 3D
+        (2D+color) inputs, False otherwise.
 
     Returns
     -------
@@ -74,7 +65,8 @@ def pyramid_reduce(image, downscale=2, sigma=None, order=1,
     .. [1] http://web.mit.edu/persci/people/adelson/pub_pdfs/pyramid83.pdf
 
     """
-    multichannel = _previous_multichannel_default(multichannel, image.ndim)
+    if multichannel is None:
+        multichannel = _multichannel_default(multichannel, image.ndim)
     _check_factor(downscale)
 
     image = img_as_float(image)
@@ -116,7 +108,8 @@ def pyramid_expand(image, upscale=2, sigma=None, order=1,
     cval : float, optional
         Value to fill past edges of input if mode is 'constant'.
     multichannel : bool, optional
-        If True and ``image.ndim > 2``, treat last axis as channels.
+        If True, last axis will not be rescaled.  The default is True for 3D
+        (2D+color) inputs, False otherwise.
 
     Returns
     -------
@@ -128,7 +121,8 @@ def pyramid_expand(image, upscale=2, sigma=None, order=1,
     .. [1] http://web.mit.edu/persci/people/adelson/pub_pdfs/pyramid83.pdf
 
     """
-    multichannel = _previous_multichannel_default(multichannel, image.ndim)
+    if multichannel is None:
+        multichannel = _multichannel_default(multichannel, image.ndim)
     _check_factor(upscale)
 
     image = img_as_float(image)
@@ -182,7 +176,8 @@ def pyramid_gaussian(image, max_layer=-1, downscale=2, sigma=None, order=1,
     cval : float, optional
         Value to fill past edges of input if mode is 'constant'.
     multichannel : bool, optional
-        If True and ``image.ndim > 2``, treat last axis as channels.
+        If True, last axis will not be rescaled.  The default is True for 3D
+        (2D+color) inputs, False otherwise.
 
     Returns
     -------
@@ -261,7 +256,8 @@ def pyramid_laplacian(image, max_layer=-1, downscale=2, sigma=None, order=1,
     cval : float, optional
         Value to fill past edges of input if mode is 'constant'.
     multichannel : bool, optional
-        If True and ``image.ndim > 2``, treat last axis as channels.
+        If True, last axis will not be rescaled.  The default is True for 3D
+        (2D+color) inputs, False otherwise.
 
     Returns
     -------
@@ -274,7 +270,8 @@ def pyramid_laplacian(image, max_layer=-1, downscale=2, sigma=None, order=1,
     .. [2] http://sepwww.stanford.edu/~morgan/texturematch/paper_html/node3.html
 
     """
-    multichannel = _previous_multichannel_default(multichannel, image.ndim)
+    if multichannel is None:
+        multichannel = _multichannel_default(multichannel, image.ndim)
     _check_factor(downscale)
 
     # cast to float for consistent data type in pyramid