scikit-image
diff --git a/‎skimage/_shared/utils.py
Lines changed: 47 additions & 6 deletions b/‎skimage/_shared/utils.py
Lines changed: 47 additions & 6 deletions
diff --git a/‎skimage/color/adapt_rgb.py
Lines changed: 2 additions & 2 deletions b/‎skimage/color/adapt_rgb.py
Lines changed: 2 additions & 2 deletions
@@ -1,19 +1,19 @@
 import inspect
 import functools
-import numbers
 import sys
 import warnings
 from collections.abc import Iterable
 
 import numpy as np
-from numpy.lib import NumpyVersion
 import scipy
+from numpy.lib import NumpyVersion
 
 from ..util import img_as_float
 from ._warnings import all_warnings, warn
 
 __all__ = ['deprecated', 'get_bound_method_class', 'all_warnings',
-           'safe_as_int', 'check_nD', 'check_shape_equality', 'warn']
+           'safe_as_int', 'check_shape_equality', 'check_nD', 'warn',
+           'reshape_nd', 'identity']
 
 
 class skimage_deprecation(Warning):
@@ -211,7 +211,6 @@ def fixed_func(*args, **kwargs):
                 convert = {True: -1, False: None}
                 kwargs['channel_axis'] = convert[kwargs.pop('multichannel')]
 
-
             # Call the function with the fixed arguments
             return func(*args, **kwargs)
         return fixed_func
@@ -457,6 +456,41 @@ def slice_at_axis(sl, axis):
     return (slice(None),) * axis + (sl,) + (...,)
 
 
+def reshape_nd(arr, ndim, dim):
+    """Reshape a 1D array to have n dimensions, all singletons but one.
+
+    Parameters
+    ----------
+    arr : array, shape (N,)
+        Input array
+    ndim : int
+        Number of desired dimensions of reshaped array.
+    dim : int
+        Which dimension/axis will not be singleton-sized.
+
+    Returns
+    -------
+    arr_reshaped : array, shape ([1, ...], N, [1,...])
+        View of `arr` reshaped to the desired shape.
+
+    Examples
+    --------
+    >>> rng = np.random.default_rng()
+    >>> arr = rng.random(7)
+    >>> _reshape_nd(arr, 2, 0).shape
+    (7, 1)
+    >>> _reshape_nd(arr, 3, 1).shape
+    (1, 7, 1)
+    >>> _reshape_nd(arr, 4, -1).shape
+    (1, 1, 1, 7)
+    """
+    if arr.ndim != 1:
+        raise ValueError("arr must be a 1D array")
+    new_shape = [1] * ndim
+    new_shape[dim] = -1
+    return np.reshape(arr, new_shape)
+
+
 def check_nD(array, ndim, arg_name='image'):
     """
     Verify an array meets the desired ndims and array isn't empty.
@@ -478,8 +512,10 @@ def check_nD(array, ndim, arg_name='image'):
         ndim = [ndim]
     if array.size == 0:
         raise ValueError(msg_empty_array % (arg_name))
-    if not array.ndim in ndim:
-        raise ValueError(msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim])))
+    if array.ndim not in ndim:
+        raise ValueError(
+            msg_incorrect_dim % (arg_name, '-or-'.join([str(n) for n in ndim]))
+        )
 
 
 def convert_to_float(image, preserve_range):
@@ -627,3 +663,8 @@ def _supported_float_type(input_dtype, allow_complex=False):
     if not allow_complex and input_dtype.kind == 'c':
         raise ValueError("complex valued input is not supported")
     return new_float_type.get(input_dtype.char, np.float64)
+
+
+def identity(image, *args, **kwargs):
+    """Returns the first argument unmodified."""
+    return image
@@ -9,14 +9,14 @@
 __all__ = ['adapt_rgb', 'hsv_value', 'each_channel']
 
 
-def is_rgb_like(image):
+def is_rgb_like(image, channel_axis=-1):
     """Return True if the image *looks* like it's RGB.
 
     This function should not be public because it is only intended to be used
     for functions that don't accept volumes as input, since checking an image's
     shape is fragile.
     """
-    return (image.ndim == 3) and (image.shape[2] in (3, 4))
+    return (image.ndim == 3) and (image.shape[channel_axis] in (3, 4))
 
 
 def adapt_rgb(apply_to_rgb):