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.
> > > > >
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