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Isolated Python 3 (from source) with Scientific Stack in a Virtual-Environment (double isolation) on Ubuntu Precise (As of Feb 2014)
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This document will walk you through compiling your own scientific python distribution from source,
without sudo, on a linux machine. The core numpy and scipy libraries will be linked against
Intel MKL for maximum performance.
This procedure has been tested with Rocks Cluster Linux 6.0 (Mamba) and CentOS 6.3.
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A lot of math grad school is reading books and papers and trying to understand what's going on. The difficulty is that reading math is not like reading a mystery thriller, and it's not even like reading a history book or a New York Times article.
The main issue is that, by the time you get to the frontiers of math, the words to describe the concepts don't really exist yet. Communicating these ideas is a bit like trying to explain a vacuum cleaner to someone who has never seen one, except you're only allowed to use words that are four letters long or shorter.
It's a résumé, as a readable and compilable C source file. Since Hacker News got here, this has been updated to be most of my actual résumé. This isn't a serious document, just a concept to annoy people who talk about recruiting and the formats they accept résumés in. It's also relatively representative of my coding style.
I apologize for the use of _t in my types. I spend a lot of time at a level where I can do that; "reserved for system libraries? I am the system libraries".
Since people kept complaining, I've fixed the assignments of string literals to non-const char *s.
If you're using an older compiler, you might have trouble with the anonymous unions and the designated initializers - I think gcc 4.4 requires some extra braces to get them working together. Anything reasonably recent should work fine. Clang and gcc (newer than 4.4, at le