On Wed, Mar 31, 2010 at 10:30 AM, T J <
tjhnson@gmail.com> wrote:
> Hi,
>
> I'm getting some strange behavior with logaddexp2.reduce:
>
> from itertools import permutations
> import numpy as np
> x = np.array([-53.584962500721154, -1.5849625007211563, -0.5849625007211563])
> for p in permutations([0,1,2]):
> print p, np.logaddexp2.reduce(x[list(p)])
>
> Essentially, the result depends on the order of the array...and we get
> nans in the "bad" orders. Likely, this also affects logaddexp.
>