On Sun, May 24, 2015 at 7:46 PM, Sturla Molden <sturla.mol...@gmail.com> wrote: > > On 24/05/15 17:13, Anne Archibald wrote: > > Do we want a deprecation-like approach, so that eventually people who > > want replicability will specify versions, and everyone else gets bug > > fixes and improvements? This would presumably take several major > > versions, but it might avoid people getting unintentionally trapped on > > this version. > > > > Incidentally, bug fixes are complicated: if a bug fix uses more or fewer > > raw random numbers, it breaks repeatability not just for the call that > > got fixed but for all successive random number generations. > > If a function has a bug, changing it will change the output of the > function. This is not special for random numbers. If not retaining the > old erroneous output means we break-backwards compatibility, then no > bugs can ever be fixed, anywhere in NumPy. I think we need to clarify > what we mean by backwards compatibility for random numbers. What > guarantees should we make from one version to another?
The policy thus far has been that we will fix bugs in the distributions and make changes that allow a strictly wider domain of distribution parameters (e.g. allowing b==0 where before we only allowed b>0), but we will not make other enhancements that would change existing good output. -- Robert Kern
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