On Mon, Feb 15, 2016 at 11:31 PM, Charles R Harris < charlesr.har...@gmail.com> wrote:
> > > On Mon, Feb 15, 2016 at 9:15 PM, <josef.p...@gmail.com> wrote: > >> >> >> On Mon, Feb 15, 2016 at 11:05 PM, Charles R Harris < >> charlesr.har...@gmail.com> wrote: >> >>> >>> >>> On Mon, Feb 15, 2016 at 8:50 PM, <josef.p...@gmail.com> wrote: >>> >>>> >>>> >>>> On Mon, Feb 15, 2016 at 10:46 PM, <josef.p...@gmail.com> wrote: >>>> >>>> >>>>> >>>>> On Fri, Feb 12, 2016 at 4:19 PM, Nathan Goldbaum < >>>>> nathan12...@gmail.com> wrote: >>>>> >>>>>> >>>>>> https://github.com/numpy/numpy/blob/master/doc/release/1.11.0-notes.rst >>>>>> >>>>>> On Fri, Feb 12, 2016 at 3:17 PM, Andreas Mueller <t3k...@gmail.com> >>>>>> wrote: >>>>>> >>>>>>> Hi. >>>>>>> Where can I find the changelog? >>>>>>> It would be good for us to know which changes are done one purpos >>>>>>> without hunting through the issue tracker. >>>>>>> >>>>>>> Thanks, >>>>>>> Andy >>>>>>> >>>>>>> >>>>>>> On 02/09/2016 09:09 PM, Charles R Harris wrote: >>>>>>> >>>>>>> Hi All, >>>>>>> >>>>>>> I'm pleased to announce the release of NumPy 1.11.0b3. This beta >>>>>>> contains additional bug fixes as well as limiting the number of >>>>>>> FutureWarnings raised by assignment to masked array slices. One issue >>>>>>> that >>>>>>> remains to be decided is whether or not to postpone raising an error for >>>>>>> floats used as indexes. Sources may be found on Sourceforge >>>>>>> <https://sourceforge.net/projects/numpy/files/NumPy/1.11.0b3/> and >>>>>>> both sources and OS X wheels are availble on pypi. Please test, >>>>>>> hopefully >>>>>>> this will be that last beta needed. >>>>>>> >>>>>>> As a note on problems encountered, twine uploads continue to fail >>>>>>> for me, but there are still variations to try. The wheeluploader >>>>>>> downloaded >>>>>>> wheels as it should, but could not upload them, giving the error message >>>>>>> "HTTPError: 413 Client Error: Request Entity Too Large for url: >>>>>>> <https://www.python.org/pypi>https://www.python.org/pypi";. Firefox >>>>>>> also complains that http://wheels.scipy.org is incorrectly >>>>>>> configured with an invalid certificate. >>>>>>> >>>>>>> Enjoy, >>>>>>> >>>>>>> Chuck >>>>>>> >>>>>>> >>>>>>> _______________________________________________ >>>>>>> NumPy-Discussion mailing >>>>>>> listNumPy-Discussion@scipy.orghttps://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 >>>>>> >>>>>> >>>>> >>>> (try to send again) >>>> >>>> >>>>> >>>>> another indexing question: (not covered by unit test but showed up in >>>>> examples in statsmodels) >>>>> >>>>> >>>>> This works in numpy at least 1.9.2 and 1.6.1 (python 2.7, and python >>>>> 3.4) >>>>> >>>>> >>> list(range(5))[np.array([0])] >>>>> 0 >>>>> >>>>> >>>>> >>>>> on numpy 0.11.0b2 (I'm not yet at b3) (python 3.4) >>>>> >>>>> I get the same exception as here but even if there is just one element >>>>> >>>>> >>>>> >>> list(range(5))[np.array([0, 1])] >>>>> Traceback (most recent call last): >>>>> File "<pyshell#7>", line 1, in <module> >>>>> list(range(5))[np.array([0, 1])] >>>>> TypeError: only integer arrays with one element can be converted to an >>>>> index >>>>> >>>> >>> Looks like a misleading error message. Apparently it requires scalar >>> arrays (ndim == 0) >>> >>> In [3]: list(range(5))[np.array(0)] >>> Out[3]: 0 >>> >> >> >> We have a newer version of essentially same function a second time that >> uses squeeze and that seems to work fine. >> >> Just to understand >> >> Why does this depend on the numpy version? I would have understood that >> this always failed, but this code worked for several years. >> https://github.com/statsmodels/statsmodels/issues/2817 >> > > It's part of the indexing cleanup. > > In [2]: list(range(5))[np.array([0])] > /home/charris/.local/bin/ipython:1: VisibleDeprecationWarning: converting > an array with ndim > 0 to an index will result in an error in the future > #!/usr/bin/python > Out[2]: 0 > > The use of multidimensional arrays as indexes is likely a coding error. Or > so we hope... > Thanks for the explanation Or, it forces everyone to watch out for the color of the ducks :) It's just a number, whether it's python scalar, numpy scalar, 1D or 2D. And once we squeeze, we cannot iterate over it anymore. This looks like the last problem with have in statsmodels master. Part of the reason that 0.10 hurt quite a bit is that we are using in statsmodels some of the grey zones so we don't have to commit to a specific usage. Even if a user or developer tries a "weird" case, it works for most of the results, but breaks in some unknown places. (In the current case a cryptic exception would be raised if the user has two constant columns in the regression. Which is fine for some usecases but not for every result.) Josef > > Chuck > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion > >
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