[Numpy-discussion] loop through values in a array and find maximum as looping

[Olivier Delalleau]

Weird, it worked for me (with a and b two 1d numpy arrays). Anyway, Josef's
solution is probably much more efficient (especially if you can put all
your arrays into a single tensor).

-=- Olivier

2011/12/6 questions anon <questions.anon at gmail.com>

> Hi Olivier,
> No that does not seem to do anything
> am I missing another step whereever b is greater than a replace b with a?
> thanks
>
>
> On Wed, Dec 7, 2011 at 11:55 AM, Olivier Delalleau <shish at keba.be> wrote:
>
>> It may not be the most efficient way to do this, but you can do:
>> mask = b > a
>> a[mask] = b[mask]
>>
>> -=- Olivier
>>
>> 2011/12/6 questions anon <questions.anon at gmail.com>
>>
>>> I would like to produce an array with the maximum values out of many
>>> (10000s) of arrays.
>>> I need to loop through many multidimentional arrays and if a value is
>>> larger (in the same place as the previous array) then I would like that
>>> value to replace it.
>>>
>>> e.g.
>>> a=[1,1,2,2
>>> 11,2,2
>>> 1,1,2,2]
>>> b=[1,1,3,2
>>> 2,1,0,0
>>> 1,1,2,0]
>>>
>>> where b>a replace with value in b, so the new a should be :
>>>
>>> a=[1,1,3,2]
>>> 2,1,2,2
>>> 1,1,2,2]
>>>
>>> and then keep looping through many arrays and replace whenever value is
>>> larger.
>>>
>>> I have tried numpy.putmask but that results in
>>> TypeError: putmask() argument 1 must be numpy.ndarray, not list
>>> Any other ideas? Thanks
>>>
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>>> NumPy-Discussion at scipy.org
>>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>>
>>>
>>
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>
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