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... Chuck
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