morphology.is_local_maximum --> feature.peak_local_max

[Guillaume Gay]

Ok so **1D** is not supported...

I guess if you just do:

a = np.atleast_2D(a) before calling is_local_maximum it will be correct...

Cheers

Guillaume
On 06/09/2013 10:39, Sigmund wrote:
> 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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