Hyperparamopt - #58
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Can one of the admins verify this patch? |
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Can one of the admins verify this patch? |
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OK to test. |
| # limitations under the License. | ||
| """Metropolis-Hasting Random number generator | ||
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| This implementation provides random samples from a user-given |
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How is this MCMC different or better than other MCMC implementations for Python? May want to explain here.
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I looked for other python packages that do what I want i.e generate samples from a user-specified pdf. I couldn't find any, so had to write my own. If you know of any other implementation, please let me know as I am not aware of any at this point.
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Or maybe http://dan.iel.fm/emcee/current/ . It's OK if neither of these does what you need, you can just say that (and why) in the comments so people know there's a reason for having an MCMC module in brainiak rather than using an existing library.
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Still and MCMC module should be outside this package, maybe in utils or some other package.
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After some searching, I see that I only need samples from a 1D Gaussian mixture model. I have changed the code to do this using other simpler methods in numpy+scipy. I will remove this file (mcmc.py) and the corresponding tests.
…d cython; all scipy.stats continuous distributions supported; more comments added
| logger = logging.getLogger(__name__) | ||
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| def get_sigma(x, minlimit=-np.inf, maxlimit=np.inf): |
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