pyEMMA 2.1rc2

EMMA: Emma's Markov Model Algorithms

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EMMA (Emma's Markov Model Algorithms)
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What is it?
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PyEMMA (EMMA = Emma's Markov Model Algorithms) is an open source
Python/C package for analysis of extensive molecular dynamics simulations.
In particular, it includes algorithms for estimation, validation and analysis
of:

* Clustering and Featurization
* Markov state models (MSMs)
* Hidden Markov models (HMMs)
* multi-ensemble Markov models (MEMMs)
* Time-lagged independent component analysis (TICA)
* Transition Path Theory (TPT)

PyEMMA can be used from Jupyther (former IPython, recommended), or by
writing Python scripts. The docs, can be found at
`http://pyemma.org <http://www.pyemma.org/>`__.

Citation
--------
If you use PyEMMA in scientific work, please cite:

M. K. Scherer, B. Trendelkamp-Schroer, F. Paul, G. Pérez-Hernández,
M. Hoffmann, N. Plattner, C. Wehmeyer, J.-H. Prinz and F. Noé:
PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models,
J. Chem. Theory Comput. 11, 5525-5542 (2015)


Installation
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With pip::

pip install pyemma

with conda::

conda install -c omnia pyemma


or install latest devel branch with pip::

pip install git+https://github.com/markovmodel/PyEMMA.git@devel

For a complete guide to installation, please have a look at the version
`online <http://www.emma-project.org/latest/INSTALL.html>`__ or offline in file
doc/source/INSTALL.rst

To build the documentation offline you should install the requirements with::

pip install -r requirements-build-doc.txt

Then build with make::

cd doc; make html

Support and development
-----------------------
For bug reports/sugguestions/complains please file an issue on
`GitHub <http://github.com/markovmodel/PyEMMA>`__.

Or start a discussion on our mailing list: [e-mail]


External Libraries
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* mdtraj (LGPLv3): https://mdtraj.org
* bhmm (LGPLv3): http://github.com/bhmm/bhmm
* msmtools (LGLPv3): http://github.com/markovmodel/msmtools