On Thu, Oct 16, 2014 at 8:25 PM, Matthew Brett <matthew.br...@gmail.com> wrote:
> Hi, > > On Thu, Oct 16, 2014 at 6:38 PM, Benjamin Root <ben.r...@ou.edu> wrote: > > That isn't what I meant. Higher order doesn't "necessarily" mean more > > accurate. The results simply have different properties. The user needs to > > choose the differentiation order that they need. One interesting effect > in > > data assimilation/modeling is that even-order differentiation can often > have > > detrimental effects while higher odd order differentiation are better, > but > > it is highly dependent upon the model. > > > > This change in gradient broke a unit test in matplotlib (for a new > feature, > > so it isn't *that* critical). We didn't notice it at first because we > > weren't testing numpy 1.9 at the time. I want the feature (I have need > for > > it elsewhere), but I don't want the change in default behavior. > > I think it would be a bad idea to revert now. > > I suspect, if you revert, then a lot of other code will assume the < > 1.9.0, >= 1.9.1 behavior. In that case, the code will work as > expected most of the time, except when combined with 1.9.0, which > could be seriously surprising, and often missed. If you keep the new > behavior, then it will be clearer that other code will have to adapt > to this change >= 1.9.0 - surprise, but predictable surprise, if you > see what I mean... > 1.9.1 will be out in a week or so. To be honest, these days I regard the 1.x.0 releases as sort of an advanced release candidate. I think there are just a lot more changes going in between releases and the release gets a lot more testing than the official release candidates. Chuck
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