[Numpy-discussion] Bug in logaddexp2.reduce

[T J]

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.