Raymond Hettinger <[EMAIL PROTECTED]> added the comment: Since we're not in a hurry for Py2.7 and 3.1, I would like to this kicked around a bit on the newsgroup and in numpy forums (personally, I would also post a pure python equivalent to the ASPN cookbook for further commentary).
There are several different approximations to choose from. Each of them has their own implications for speed and accuracy. IIRC, the one I used in test.test_random.gamma() was accompanied by a proof that its maximum error never exceeded a certain amount. I think there were some formulas that made guarantees only over a certain interval and others that had nice properties in the first and second derivatives (one that don't have those properties can throw newtonian solvers wildly off the mark). Let's let the community use its collective wisdom to select the best approach and not immediately commit ourselves to the one in this patch. At one point, Tim was reluctant to add any of these functions because it is non-trivial to do well and because it would open a can of worms about why python gets a different answer (possibly not as close to true) and some other favorite tool (matlab, excel, numpy, and engineering calculator, etc). FWIW, I changed the 2.6 version of test_random.gamma() to take advantage of msum() to increase its accuracy when some of the summands have nearly cancelling values. ---------- nosy: +rhettinger _______________________________________ Python tracker <[EMAIL PROTECTED]> <http://bugs.python.org/issue3366> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: http://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
