hmmlearn is a set of algorithm for learning and inference of Hidden Markov
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.
Getting the latest code
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.
Running the test suite
To run the test suite, you need
nosetests and the
Run the test suite using:
$ python setup.py build_ext --inplace && nosetests
from the root of the project.
Building the docs
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
Making a source tarball
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
Making a release and uploading it to PyPI
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