hmmlearn is a set of algorithm for learning and inference of Hidden Markov
Models.
Historically, this code was present in scikit-learn, but unmaintained. It
has been orphaned and separated as a different package.
The learning algorithms in this package are unsupervised. For supervised learning of HMMs and similar models, see seqlearn.
To get the latest code using git, simply type:
$ git clone git://github.com/hmmlearn/hmmlearn.git
Make sure you have all the dependencies:
$ pip install scikit-learn Cython
and then install hmmlearn by running:
$ python setup.py install
in the source code directory.
To run the test suite, you need nosetests and the coverage modules.
Run the test suite using:
$ python setup.py build_ext --inplace && nosetests
from the root of the project.
To build the docs you need to have the following packages installed:
$ pip install Pillow matplotlib Sphinx numpydoc
Run the command:
$ cd doc $ make html
The docs are built in the _build/html directory.
To create a source tarball, eg for packaging or distributing, run the following command:
$ python setup.py sdist
The tarball will be created in the dist directory.
This command is only run by project manager, to make a release, and upload in to PyPI:
$ python setup.py sdist bdist_egg register upload