morphology.is_local_maximum --> feature.peak_local_max

[Sigmund]

I'm using the Enthough Canopy 2.7.3 distribution. 

>>> import skimage
>>> skimage.version.version
'0.8.2'
>>>


*the is_local_maximum function*
>>> import numpy as np
>>> from skimage.morphology import is_local_maximum
>>> a = np.zeros(5)
>>> a[2] = 2
>>> is_local_maximum(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File 
"c:\users\neher\appdata\local\enthought\canopy\user\lib\site-packages\skimage\_shared\utils.py", 
line 41, in wrapped
    return func(*args, **kwargs)
  File 
"c:\users\neher\appdata\local\enthought\canopy\user\lib\site-packages\skimage\morphology\watershed.py", 
line 297, in is_local_maximum
    indices=False, exclude_border=False)
  File 
"c:\users\neher\appdata\local\enthought\canopy\user\lib\site-packages\skimage\feature\peak.py", 
line 153, in peak_local_max
    out[coordinates[:, 0], coordinates[:, 1]] = True
IndexError: index 1 is out of bounds for axis 1 with size 1
>>>

*the peak_local_max function*

>>> import numpy as np
>>> from skimage.feature import peak_local_max
>>> a = np.zeros(5)
>>> a[2]= 2
>>>
>>> a
array([ 0.,  0.,  2.,  0.,  0.])
>>> peak_local_max(a)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File 
"c:\users\neher\appdata\local\enthought\canopy\user\lib\site-packages\skimage\feature\peak.py", 
line 136, in peak_local_max
    image[:, :min_distance] = 0
IndexError: too many indices
>>>

Thank you for your help!
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