========================== Announcing Numexpr 1.3.1 ==========================

Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python.

This is a maintenance release. On it, support for the `unit32` type has been added (it is internally upcasted to `int64`), as well as a new `abs()` function (thanks to Pauli Virtanen for the patch).

Also, a little tweaking in the treatment of unaligned arrays on Intel architectures allowed for up to 2x speedups in computations involving unaligned arrays. For example, for multiplying 2 arrays (see the included ``unaligned-simple.py`` benchmark), figures before the tweaking were:

NumPy aligned: 0.63 s NumPy unaligned: 1.66 s Numexpr aligned: 0.65 s Numexpr unaligned: 1.09 s

while now they are:

NumPy aligned: 0.63 s NumPy unaligned: 1.65 s Numexpr aligned: 0.65 s Numexpr unaligned: 0.57 s <-- almost 2x faster than above

You can also see how the unaligned case can be even faster than the aligned one. The explanation is that the 'aligned' array was actually a strided one (actually a column of an structured array), and the total working data size was a bit larger for this case.

In case you want to know more in detail what has changed in this version, see:

http://code.google.com/p/numexpr/wiki/ReleaseNotes

or have a look at RELEASE_NOTES.txt in the tarball.

Where I can find Numexpr? =========================

The project is hosted at Google code in:

http://code.google.com/p/numexpr/

And you can get the packages from PyPI as well:

http://pypi.python.org/pypi

How it works? =============

See:

http://code.google.com/p/numexpr/wiki/Overview

for a detailed description by the original author (David M. Cooke).

Share your experience =====================

Let us know of any bugs, suggestions, gripes, kudos, etc. you may have.

Enjoy!