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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