These are instructions for installing Numexpr on Unix systems.  For
Windows, it is best to install it from binaries.  However, you should
note that, for the time being, we cannot provide Windows binaries with
VML support.


Building
========

This version of `Numexpr` requires Python 2.6 or greater,
and NumPy 1.6 or greater.

It's built in the standard Python way:

$ python setup.py build
$ python setup.py install

You can test `numexpr` with:

$ python -c "import numexpr; numexpr.test()"


Enabling Intel's VML support
~~~~~~~~~~~~~~~~~~~~~~~~~~~~

numexpr includes support for Intel's VML library.  This allows for
better performance on Intel architectures, mainly when evaluating
transcendental functions (trigonometrical, exponential...).  It also
enables numexpr using several CPU cores.

If you have Intel's MKL (the library that embeds VML), just copy the
`site.cfg.example` that comes in the distribution to `site.cfg` and
edit the latter giving proper directions on how to find your MKL
libraries in your system.  After doing this, you can proceed with the
usual building instructions listed above.  Pay attention to the
messages during the building process in order to know whether MKL has
been detected or not.  Finally, you can check the speed-ups on your
machine by running the `bench/vml_timing.py` script (you can play with
different parameters to the `set_vml_accuracy_mode()` and
`set_vml_num_threads()` functions in the script so as to see how it would
affect performance).



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