[Numpy-discussion] ndarray with double comparison

Chao YUE chaoyuejoy@gmail....
Thu Oct 13 11:32:15 CDT 2011


Thanks. I starts to use python do some real data processing and has bunch of
questions.

Chao

2011/10/13 Benjamin Root <ben.root@ou.edu>

> On Thu, Oct 13, 2011 at 11:13 AM, Chao YUE <chaoyuejoy@gmail.com> wrote:
>
>> Dear all,
>>
>> sorry for this stupid question but I cannot find it in numpy tutorial or
>> google.
>> suppose I have a=np.arange(11).
>>
>> In [32]: a < 8
>> Out[32]:
>> array([ True,  True,  True,  True,  True,  True,  True,  True, False,
>>        False, False], dtype=bool)
>>
>> In [34]: a > 4
>> Out[34]:
>> array([False, False, False, False, False,  True,  True,  True,  True,
>>         True,  True], dtype=bool)
>>
>> how can I have boolean index like 4 < a < 8
>> np.where(a>4 and a<8);or plainly input "a>4 and a<8" doesn't work.
>>
>> thanks,
>>
>> Chao
>>
>>
> Unfortunately, you can't use "and", "or", "not" keywords with boolean
> arrays because numpy can't overload them.  Instead, use the bitwise
> operators: '&', '|', and '~'.  Be careful, though, because of operator
> precedence is different for bitwise operators than the boolean keywords.  I
> am in the habit of always wrapping my boolean expressions in parentheses,
> just in case.
>
> (a > 4) & (a < 8)
>
> is what you want.  Note that "a > 4 & a < 8" would be evaluated in a
> different order -- "4 & a" would be first.
>
> I hope that helps!
>
> Ben Root
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>


-- 
***********************************************************************************
Chao YUE
Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL)
UMR 1572 CEA-CNRS-UVSQ
Batiment 712 - Pe 119
91191 GIF Sur YVETTE Cedex
Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16
************************************************************************************
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.scipy.org/pipermail/numpy-discussion/attachments/20111013/57a6a5d6/attachment.html 


More information about the NumPy-Discussion mailing list