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EMMA: Emma's Markov Model Algorithms

Project description

EMMA (Emma's Markov Model Algorithms)

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What is it?
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

* 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
` <>`__.

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)

With pip::

pip install pyemma

with conda::

conda install -c omnia pyemma

or install latest devel branch with pip::

pip install git+

For a complete guide to installation, please have a look at the version
`online <>`__ or offline in file

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 <>`__.

Or start a discussion on our mailing list:

External Libraries
* mdtraj (LGPLv3):
* bhmm (LGPLv3):
* msmtools (LGLPv3):

Project details

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