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digitalmars.D.announce - Numpy Random Number Generators
I've ported a large portion of the Numpy random number generation library to D. (I excluded the uniform random number generators because Phobos and Tango already have good implementations of these, and a few distributions because they were obscure and hard to test properly. I may add the obscure probability distributions later.) The results appear pretty good (I added unit tests that make sure the results are sane while I was at it). The module is licensed under the BSD license. The code is available at: http://dsource.org/projects/dstats/browser/trunk/random.d Docs are at http://svn.dsource.org/projects/dstats/docs/random.html although there's not much there. If you understand the probability distribution you're trying to sample from, it's pretty self-explanatory. If not, a little bit of ddoc isn't going to help, and Wikipedia is probably a better choice. Apr 30 2009
dsimcha wrote:I've ported a large portion of the Numpy random number generation library to D. (I excluded the uniform random number generators because Phobos and Tango already have good implementations of these, and a few distributions because they were obscure and hard to test properly. I may add the obscure probability distributions later.) The results appear pretty good (I added unit tests that make sure the results are sane while I was at it). The module is licensed under the BSD license. The code is available at: http://dsource.org/projects/dstats/browser/trunk/random.d Docs are at http://svn.dsource.org/projects/dstats/docs/random.html although there's not much there. If you understand the probability distribution you're trying to sample from, it's pretty self-explanatory. If not, a little bit of ddoc isn't going to help, and Wikipedia is probably a better choice. Apr 30 2009
== Quote from Andrei Alexandrescu (SeeWebsiteForEmail erdani.org)'s articledsimcha wrote:I've ported a large portion of the Numpy random number generation library to D. (I excluded the uniform random number generators because Phobos and Tango already have good implementations of these, and a few distributions because they were obscure and hard to test properly. I may add the obscure probability distributions later.) The results appear pretty good (I added unit tests that make sure the results are sane while I was at it). The module is licensed under the BSD license. The code is available at: http://dsource.org/projects/dstats/browser/trunk/random.d Docs are at http://svn.dsource.org/projects/dstats/docs/random.html although there's not much there. If you understand the probability distribution you're trying to sample from, it's pretty self-explanatory. If not, a little bit of ddoc isn't going to help, and Wikipedia is probably a better choice. May 01 2009
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