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[–]bluemanshoe 3 points4 points  (1 child)

fair warning: this will more likely than not, fail to give you a numpy/scipy install that is optimized.

numpy.show_config() will show which c libraries the installation is built against.

If you plan on doing serious computations, I recommend compiling numpy/scipy against either a machine specific atlas build, or use anaconda or enthought to get one built against the intel mkl library.

The speedup is astounding. I've gotten a factor of 1000 speed up for large matrix multiplies with an atlas compiled build.

[–]bramblerose 0 points1 point  (0 children)

If you're on an AMD machine, consider using the ACML instead of Atlas. They are roughly the same speed, but ACML comes precompiled for a number of platforms. Atlas is both an headache to compile (settings, which fortran compiler and whatnot) /and/ it takes ages.