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

[Travis Oliphant]

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


> -- Russell
>
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