pyhmc: Hybrid Monte Carlo Sampling with python
This package is a straight-forward port of the functions hmc2.m and
hmc2_opt.m from the MCMCstuff matlab toolbox written by Aki Vehtari
The code is originally based on the functions hmc.m from the netlab toolbox
written by Ian T Nabney <http://www.ncrg.aston.ac.uk/netlab/index.php>.
The portion of algorithm involving "windows" is derived from the C code for
this function included in the Software for Flexible Bayesian Modeling
written by Radford Neal <http://www.cs.toronto.edu/~radford/fbm.software.html>.
This software is distributed under the BSD License (see LICENSE file).
- Kilian Koepsell <firstname.lastname@example.org>
The files in this directory are distributed under the BSD license.
The main module with Hybrid Monte Carlo sampler.
This is the only file needed, which can serve as a drop-in replacement
of hmc2.m. Run some tests: 'python hm2.py'
If cython is installed, this file will be used to speed up the main loop.
Some example energy functions with gradients.
Cython version of some example energy functions with gradients.
A couple of tests. (requires nose)
* hmc.m, hmc2.m, hmc2_opt.m:
Original matlab version as a reference.