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