On Tue, May 31, 2011 at 9:53 PM, Warren Weckesser <warren.weckes...@enthought.com> wrote: > > > On Tue, May 31, 2011 at 8:36 PM, Skipper Seabold <jsseab...@gmail.com> > wrote: >> I don't know if it's one pass off the top of my head, but I've used >> percentile for interpercentile ranges. >> >> [docs] >> [1]: X = np.random.random(1000) >> >> [docs] >> [2]: np.percentile(X,[0,100]) >> [2]: [0.00016535235312509222, 0.99961513543316571] >> >> [docs] >> [3]: X.min(),X.max() >> [3]: (0.00016535235312509222, 0.99961513543316571) >> > > > percentile() isn't one pass; using percentile like that is much slower: > > In [25]: %timeit np.percentile(X,[0,100]) > 10000 loops, best of 3: 103 us per loop > > In [26]: %timeit X.min(),X.max() > 100000 loops, best of 3: 11.8 us per loop >
Probably should've checked that before opening my mouth. Never actually used it for a minmax, but it is faster than two calls to scipy.stats.scoreatpercentile. Guess I'm +1 to fast order statistics. Skipper _______________________________________________ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
