Metadata-Version: 1.1
Name: hmmlearn
Version: 0.1.1
Summary: Hidden Markov Models in Python with scikit-learn like API
Home-page: https://github.com/hmmlearn/hmmlearn
Author: Sergei Lebedev
Author-email: superbobry@gmail.com
License: new BSD
Description: hmmlearn |Travis|_
        ========
        
        .. |Travis| image:: https://api.travis-ci.org/hmmlearn/hmmlearn.png?branch=master
        .. _Travis: https://travis-ci.org/hmmlearn/hmmlearn
        
        ``hmmlearn`` is a set of algorithm for learning and inference of Hiden 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
        <https://github.com/larsmans/seqlearn>`_.
        
        Getting the latest code
        =======================
        
        To get the latest code using git, simply type::
        
            $ git clone git://github.com/hmmlearn/hmmlearn.git
        
        Installing
        ==========
        
        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 ``coverage`` modules.
        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 ``_build/html`` directory.
        
        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 ``dist`` directory.
        
        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
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Software Development
Classifier: Topic :: Scientific/Engineering
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Requires: sklearn
