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

questions anon questions.anon at gmail.com
Tue Dec 6 21:06:15 EST 2011

```I have 2d numpy arrays

On Wed, Dec 7, 2011 at 1:05 PM, Olivier Delalleau <shish at keba.be> wrote:

> 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
>>>
>>> -=- 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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>>>>
>>>>
>>>
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>>
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>
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