========================== 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! -- Francesc Alted