Steven D'Aprano added the comment: On Thu, Jun 09, 2016 at 09:24:04AM +0000, Mark Dickinson wrote:
> On the other hand, apparently `exp(mean(log(...)))` is good enough for SciPy: Hmm, well, I don't have SciPy installed, but I've found that despite their (well-deserved) reputation, numpy (and presumably scipy) often have rather naive algorithms that can lose accuracy rather spectacularly. py> statistics.mean([1e50, 2e-50, -1e50, 2e-50]) 1e-50 py> np.mean(np.array([1e50, 2e-50, -1e50, 2e-50])) 5e-51 py> statistics.mean([1e50, 2e-50, -1e50, 2e-50]*1000) 1e-50 py> np.mean(np.array([1e50, 2e-50, -1e50, 2e-50]*1000)) 5.0000000000000002e-54 On the other hand, np is probably a hundred times (or more) faster, so I suppose accuracy/speed makes a good trade off. ---------- _______________________________________ Python tracker <rep...@bugs.python.org> <http://bugs.python.org/issue27181> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
