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
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