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

[Robert Kern]

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)?

def fasarray(seq):
    return numpy.asarray(seq, dtype=float)

fasarray(seq1) / fasarray(seq2)

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
 that is made terrible by our own mad attempt to interpret it as though it had
 an underlying truth."
  -- Umberto Eco