On Di, 2016-01-19 at 16:28 +0000, G Young wrote: > In rand range, it raises an exception if low >= high. > > I should also add that AFAIK enforcing low >= high with floats is a > lot trickier than it is for integers. I have been knee-deep in > corner cases for some time with randint where numbers that are > visually different are cast as the same number by numpy due to > rounding and representation issues. That situation only gets worse > with floats. >
Well, actually random.uniform docstring says: Get a random number in the range [a, b) or [a, b] depending on rounding. and is true to the word, it does not care about the relative value of a vs. b. So my guess it is identical to your version (though one could check a bit more careful with corner cases) Quick check would suggests it is the same (though I guess if there was a slight rounding issue somewhere, it could be different): >>> np.random.set_state(('MT19937', random.getstate()[1][:-1], >>> random.getstate()[1][-1])) Will enable you to draw the same numbers with random.uniform and np.random.uniform. - Sebastian > Greg > > On Tue, Jan 19, 2016 at 4:23 PM, Chris Barker - NOAA Federal < > chris.bar...@noaa.gov> wrote: > > What does the standard lib do for rand range? I see that randint Is > > closed on both ends, so order doesn't matter, though if it raises > > for b<a, then that's a precedent we could follow. > > > > (Sorry, on a phone, can't check) > > > > CHB > > > > > > > > On Jan 19, 2016, at 6:21 AM, G Young <gfyoun...@gmail.com> wrote: > > > > > Of the methods defined in numpy/mtrand.pyx (excluding helper > > > functions and random_integers, as they are all related to > > > randint), randint is the only other function with low and high > > > parameters. However, it enforces high > low. > > > > > > Greg > > > > > > On Tue, Jan 19, 2016 at 1:36 PM, Benjamin Root < > > > ben.v.r...@gmail.com> wrote: > > > > Are there other functions where this behavior may or may not be > > > > happening? If it isn't consistent across all np.random > > > > functions, it probably should be, one way or the other. > > > > > > > > Ben Root > > > > > > > > On Tue, Jan 19, 2016 at 5:10 AM, Jaime Fernández del Río < > > > > jaime.f...@gmail.com> wrote: > > > > > Hi all, > > > > > > > > > > There is a PR (#7026) that documents the current behavior of > > > > > np.random.uniform when the low and high parameters it takes > > > > > do not conform to the expected low < high. Basically: > > > > > if low < high, random numbers are drawn from [low, high), > > > > > if low = high, all random numbers will be equal to low, and > > > > > if low > high, random numbers are drawn from (high, low] > > > > > (notice the change in the open side of the interval.) > > > > > My only worry is that, once we document this, we can no > > > > > longer claim that it is a bug. So I would like to hear from > > > > > others what do they think. The other more or less obvious > > > > > options would be to: > > > > > Raise an error, but this would require a deprecation cycle, > > > > > as people may be relying on the current undocumented > > > > > behavior. > > > > > Check the inputs and draw numbers from [min(low, high), > > > > > max(low, high)), which is minimally different from current > > > > > behavior. > > > > > I will be merging the current documentation changes in the > > > > > next few days, so it would be good if any concerns were > > > > > voiced before that. > > > > > > > > > > Thanks, > > > > > > > > > > Jaime > > > > > > > > > > -- > > > > > (\__/) > > > > > ( O.o) > > > > > ( > <) Este es Conejo. Copia a Conejo en tu firma y ayúdale > > > > > en sus planes de dominación mundial. > > > > > > > > > > _______________________________________________ > > > > > NumPy-Discussion mailing list > > > > > NumPy-Discussion@scipy.org > > > > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > > > > > > > > > _______________________________________________ > > > > NumPy-Discussion mailing list > > > > NumPy-Discussion@scipy.org > > > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > > > > > _______________________________________________ > > > NumPy-Discussion mailing list > > > NumPy-Discussion@scipy.org > > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > _______________________________________________ > > NumPy-Discussion mailing list > > NumPy-Discussion@scipy.org > > https://mail.scipy.org/mailman/listinfo/numpy-discussion > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion
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