Matthew, you are correct. A lot of things happened with random integer generation recently (including deprecating random_integers), but I believe those warnings should be squashed in the up and coming version of SciPy from what I remember.
On Mon, Apr 4, 2016 at 6:47 PM, Matthew Brett <matthew.br...@gmail.com> wrote: > Hi, > > On Mon, Apr 4, 2016 at 9:02 AM, Peter Cock <p.j.a.c...@googlemail.com> > wrote: > > On Sun, Apr 3, 2016 at 2:11 AM, Matthew Brett <matthew.br...@gmail.com> > wrote: > >> On Fri, Mar 25, 2016 at 6:39 AM, Peter Cock <p.j.a.c...@googlemail.com> > wrote: > >>> On Fri, Mar 25, 2016 at 3:02 AM, Robert T. McGibbon < > rmcgi...@gmail.com> wrote: > >>>> I suspect that many of the maintainers of major scipy-ecosystem > projects are > >>>> aware of these (or other similar) travis wheel caches, but would > guess that > >>>> the pool of travis-ci python users who weren't aware of these wheel > caches > >>>> is much much larger. So there will still be a lot of travis-ci clock > cycles > >>>> saved by manylinux wheels. > >>>> > >>>> -Robert > >>> > >>> Yes exactly. Availability of NumPy Linux wheels on PyPI is definitely > something > >>> I would suggest adding to the release notes. Hopefully this will help > trigger > >>> a general availability of wheels in the numpy-ecosystem :) > >>> > >>> In the case of Travis CI, their VM images for Python already have a > version > >>> of NumPy installed, but having the latest version of NumPy and SciPy > etc > >>> available as Linux wheels would be very nice. > >> > >> We're very nearly there now. > >> > >> The latest versions of numpy, scipy, scikit-image, pandas, numexpr, > >> statsmodels wheels for testing at > >> > http://ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com/ > >> > >> Please do test with: > >> ... > >> > >> We would love to get any feedback as to whether these work on your > machines. > > > > Hi Matthew, > > > > Testing on a 64bit CentOS 6 machine with Python 3.5 compiled > > from source under my home directory: > > > > > > $ python3.5 -m pip install --upgrade pip > > Requirement already up-to-date: pip in ./lib/python3.5/site-packages > > > > $ python3.5 -m pip install > > --trusted-host= > ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com > > --find-links= > http://ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com > > numpy scipy > > Requirement already satisfied (use --upgrade to upgrade): numpy in > > ./lib/python3.5/site-packages > > Requirement already satisfied (use --upgrade to upgrade): scipy in > > ./lib/python3.5/site-packages > > > > $ python3.5 -m pip install > > --trusted-host= > ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com > > --find-links= > http://ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com > > numpy scipy --upgrade > > Collecting numpy > > Downloading > http://ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com/numpy-1.11.0-cp35-cp35m-manylinux1_x86_64.whl > > (15.5MB) > > 100% |████████████████████████████████| 15.5MB 42.1MB/s > > Collecting scipy > > Downloading > http://ccdd0ebb5a931e58c7c5-aae005c4999d7244ac63632f8b80e089.r77.cf2.rackcdn.com/scipy-0.17.0-cp35-cp35m-manylinux1_x86_64.whl > > (40.8MB) > > 100% |████████████████████████████████| 40.8MB 53.6MB/s > > Installing collected packages: numpy, scipy > > Found existing installation: numpy 1.10.4 > > Uninstalling numpy-1.10.4: > > Successfully uninstalled numpy-1.10.4 > > Found existing installation: scipy 0.16.0 > > Uninstalling scipy-0.16.0: > > Successfully uninstalled scipy-0.16.0 > > Successfully installed numpy-1.11.0 scipy-0.17.0 > > > > > > $ python3.5 -c 'import numpy; numpy.test("full")' > > Running unit tests for numpy > > NumPy version 1.11.0 > > NumPy relaxed strides checking option: False > > NumPy is installed in /home/xxx/lib/python3.5/site-packages/numpy > > Python version 3.5.0 (default, Sep 28 2015, 11:25:31) [GCC 4.4.7 > > 20120313 (Red Hat 4.4.7-16)] > > nose version 1.3.7 > > > 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> > ---------------------------------------------------------------------- > > Ran 6332 tests in 243.029s > > > > OK (KNOWNFAIL=7, SKIP=2) > > > > > > > > So far so good, but there are a lot of deprecation warnings etc from > SciPy, > > > > > > $ python3.5 -c 'import scipy; scipy.test("full")' > > Running unit tests for scipy > > NumPy version 1.11.0 > > NumPy relaxed strides checking option: False > > NumPy is installed in /home/xxx/lib/python3.5/site-packages/numpy > > SciPy version 0.17.0 > > SciPy is installed in /home/xxx/lib/python3.5/site-packages/scipy > > Python version 3.5.0 (default, Sep 28 2015, 11:25:31) [GCC 4.4.7 > > 20120313 (Red Hat 4.4.7-16)] > > nose version 1.3.7 > > [snip] > > /home/xxx/lib/python3.5/site-packages/numpy/lib/utils.py:99: > > DeprecationWarning: `rand` is deprecated! > > numpy.testing.rand is deprecated in numpy 1.11. Use numpy.random.rand > instead. > > warnings.warn(depdoc, DeprecationWarning) > > [snip] > > > /home/xxx/lib/python3.5/site-packages/scipy/io/arff/tests/test_arffread.py:254: > > DeprecationWarning: parsing timezone aware datetimes is deprecated; > > this will raise an error in the future > > ], dtype='datetime64[m]') > > /home/xxx/lib/python3.5/site-packages/scipy/io/arff/arffread.py:638: > > PendingDeprecationWarning: generator '_loadarff.<locals>.generator' > > raised StopIteration > > [snip] > > > /home/xxx/lib/python3.5/site-packages/scipy/sparse/tests/test_base.py:2425: > > DeprecationWarning: This function is deprecated. Please call > > randint(-5, 5 + 1) instead > > I = np.random.random_integers(-M + 1, M - 1, size=NUM_SAMPLES) > > [snip] > > 0-th dimension must be fixed to 3 but got 15 > > [snip] > > ---------------------------------------------------------------------- > > Ran 21407 tests in 741.602s > > > > OK (KNOWNFAIL=130, SKIP=1775) > > > > > > Hopefully I didn't miss anything important in hand editing the scipy > output. > > Thanks a lot for testing. > > I believe the deprecation warnings are expected, because numpy 1.11.0 > introduced a new deprecation warning when using `random_integers`. > Scipy 0.17.0 is using `random_integers` in a few places. > > Best, > > Matthew > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > https://mail.scipy.org/mailman/listinfo/numpy-discussion >
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