[Numpy-discussion] Compact way of performing array math with specified result type?

[Sebastian Haase]

On Sat, Apr 28, 2007 at 10:04 PM, Travis Oliphant
<oliphant.travis at ieee.org> wrote:
> Russell E. Owen wrote:
>> I often find myself doing simple math on sequences of numbers (which
>> might or might not be numpy arrays) where I want the result (and thus
>> the inputs) coerced to a particular data type.
>>
>> I'd like to be able to say:
>>
>>   numpy.divide(seq1, seq2, dtype=float)
>>
>> but ufuncs don't allow on to specify a result type. So I do this instead:
>>
>>   numpy.array(seq1, dtype=float) / numpy.array(seq2, dtype=float)
>>
>> Is there a more compact solution (without having to create the result
>> array first and supply it as an argument)?
>>
>
> Every ufunc has a little-documented keyword "sig" for (signature) which
> allows you to specify the signature of the inner loop.
>
> Thus,
>
> numpy.divide(seq1, seq1, sig=('d',)*3)
>
> will do what you want.
>
> -Travis
>
Hi,

going through my very old emails - I was wondering if this has gotten
better documented by now !?
(and where ?)

-Sebastian Haase