The numexpr package evaluates multiple-operator array expressions many times
faster than NumPy can. It accepts the expression as a string, analyzes it,
rewrites it more efficiently, and compiles it to faster Python code on the fly.
It's the next best thing to writing the expression in C and compiling it with
a specialized just-in-time (JIT) compiler, i.e. it does not require a compiler
at runtime.
Also, numexpr has support for the Intel VML (Vector Math Library) -- integrated
in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing
transcendental functions (like trigonometrical, exponentials...) on top of
Intel-compatible platforms. This support also allows to use multiple cores in
your computations.
WWW: http://code.google.com/p/numexpr/
PR: ports/148372
Submitted by: Ju Pengfei <jupengfei@gmail.com>
Feature safe: yes
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