* Remove Python 2.6 support
Some details about some slightly orthogonal changes:
* Note about cheking safely for nan is likely not valid any more (commit
introducing it is c80ca91b)
* scipy.linalg.qr econ parameter removed since scipy 0.9 in favour of
mode='economic'
* Remove unnecessary libgfortran in conda create command
* Putative fix by setting the random seed
* Revert unintended change
* Reinstate previous logic for checking for NaNs
* Reinstate change in error message
Error messages from Python 2.7 assertRegexp does not contain the
function name, in contrast with Python 3 assertRegex
* Rewriting of cythonization in setup.py
By using Cython.Build.cythonize and switching between .c and .pyx files
as appropriate cython dependencies are correctly taken into account.
* Use cythonize once on the root config rather than in each subpackage
* Fix for Windows
* Remove caching from Travis
Cython dependencies are taken care of by Cython.Build.cythonize and
based on file timestamps, so .C and .so files will always be rebuild
from scratch on each build in Travis.
* Specify .pyx in setup.files for cython generated extensions
More natural this way. Tweak the extensions to generate from .c and .cpp
files for a release.
* COSMIT Remove commented out code
* Check cython version is greater than 0.23
* COSMIT better names for functions
* flake8 fix (imported module not at top of file)
* Install cython 0.23 for Python 2.6
now that cython >= 0.23 requirement is enforced in setup.py
* Use module constant for minimum required cython version
* Fix Travis install.sh
No easy way to put comments inside multi-line command
This allows advanced users who are using standard Python package
management tools to install scikit-learn[alldeps], which includes the
appropriate numpy and scipy dependencies.
pip installs would fail when compiling against ATLAS.
This is due to a distutils-setuptools issue with monkeypatching that
is triggered if Cython is imported.
See https://github.com/numpy/numpy/issues/7235 for details.
wheelhouse-uploader makes it possible to leverage our CI infrastructure
(travis and appveyor) to automate the generation of binary packages
for OSX and windows (both .exe and .whl packages).
The cloud containers that are used to store the build artifacts of the
CI workers are configured in the setup.cfg file.
More details at: https://github.com/ogrisel/wheelhouse-uploader
during pre-install. This should allow
'pip install numpy cython scipy scikit-learn'
to install scikit.
This fix is based of issue and fixes in Scipy:
https://github.com/scipy/scipy/pull/453ad0dd3e883
Adrin Jalali