--- check out the py3 branch for a Python 3 version ---
binf is a collection of classes I use for Bayesian inference problems: probability distributions (likelihood, posterior, priors) and forward- and error models and a Gibbs- and HMC sampler. I use this code in my research on Bayesian chromatin structure determination (Carstens et al., PLOS Comput. Biol. 2016). The code has limited functionality (namely, it does what I need it to do), but maybe you'll find it useful.
binf has two dependencies (if I remember correctly): numpy (download) and the Computational Structural Biology Toolbox (CSB, download). Install these and you should be able to install binf by typing:
$ python setup.py install
possibly with the --user option, if you don't have administrator privileges.
For most classes, there are unit tests to make sure things work as they're supposed to. You can run the tests by typing:
$ cd binf $ python run_test.py
The API is fully documented. I tried to pay attention to some coding practices, so hopefully it is not too bad to read / use / adapt. There also is a fully worked-out example, which infers the coefficients of a polynomial model to some data points and plots the results. You can run it by typing:
$ cd binf $ python example_script.py
(requires matplotlib). This example and the imports from the example/ subfolder should give you an idea of how the code works.
If you have questions, don't hesitate to drop me a message.
binf is open source and distributed under the OSI-approved MIT license:
Copyright (c) 2018 Simeon Carstens Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.