We’ve been struggling with some pretty nasty bugs relating to predictable runtime. The logs the testcases produced are enormous, and we were struggling to visualize what was actually going on. I spent some time whipping up a visualization tool using python, numpy, scipy, and pylab. I haven’t used scipy since my Signals and Systems course at the university, it felt great to dust it off and make use of it again. With only a meager understanding of signal theory and statistical analysis you can easily create scatter and line plots, histograms, and even fast fourier transforms. One of the most useful things about the pylab plotting interface is that it is interactive. You can zoom in and out and pan the original plot, increasing the amount of discernable information. Kudos to the python guys for creating such an excellent language for rapid tool development.
Update (May 27, 2011): Source available here: http://git.kernel.org/?p=linux/kernel/git/dvhart/plotter.git