[Numpy-discussion] Extracting values from one array corresponding to argmax elements in another array
Ken Basye
kbasye1@jhu....
Tue Apr 6 08:22:10 CDT 2010
From: Vincent Schut <schut@sarvision.nl>
> On 04/05/2010 06:06 PM, Keith Goodman wrote:
>
>> On Mon, Apr 5, 2010 at 8:44 AM, Ken Basye<kbasye1@jhu.edu> wrote:
>>
>>> Hi Folks,
>>> I have two arrays, A and B, with the same shape. I want to find the
>>> highest values in A along some axis, then extract the corresponding
>>> values from B. I can get the highest values in A with A.max(axis=0) and
>>> the indices of these highest values with A.argmax(axis=0). I'm trying
>>> to figure out a loop-free way to extract the corresponding elements from
>>> B using these indices. Here's code with a loop that will do what I want
>>> for two-dimensional arrays:
>>>
>>> >>> a
>>> array([[ 100., 0., 0.],
>>> [ 0., 100., 100.],
>>> [ 0., 0., 0.]])
>>>
>>> >>> a.max(axis=0)
>>> array([ 100., 100., 100.])
>>>
>>> >>> sel = a.argmax(axis=0)
>>> >>>sel
>>> array([0, 1, 1])
>>>
>>> >>> b = np.arange(9).reshape((3,3))
>>> >>> b
>>> array([[0, 1, 2],
>>> [3, 4, 5],
>>> [6, 7, 8]])
>>>
>>> >>> b_best = np.empty(3)
>>> >>> for i in xrange(3):
>>> ... b_best[i] = b[sel[i], i]
>>> ...
>>> >>> b_best
>>> array([ 0., 4., 5.])
>>>
>> Here's one way:
>>
>>
>>>> b[a.argmax(axis=0), range(3)]
>>>>
>> array([0, 4, 5])
>>
>
> Which does not work anymore when your arrays become more-dimensional
> (like in my case: 4 or more) and the axis you want to select on is not
> the first/last one. If I recall correctly, I needed to construct the
> full index arrays for the other dimensions too (like with ogrid I
> think). So: create the ogrid, replace the one for the dimensions you
> want the argmax selection to take place on with the argmax parameter,
> and use those index arrays to index your b array.
> I'd need to look up my source code to be more sure/precise. If anyone
> would like me to, please let me know. If anyone knows a less elaborate
> way, also please let us know! :-)
>
Hi Vincent,
I'd like to see more about your solution. For my present purposes,
Keith's solution was sufficient, but I'm still very interested in a
solution that's independent of dimension and axis.
Thanks (and thanks, Keith),
Ken
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