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Visualizations for statistical modelsof biomolecular dynamics.

Project description

MSMExplorer: data visualizations for biomolecular dynamics

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MSMExplorer is a Python visualization library for statistical models of
biomolecular dynamics. It provides a high-level interface for drawing
attractive statistical graphics with
`MSMBuilder <>`__.


Online documentation is available
`here <>`__. It includes IPython
notebooks, detailed API documentation, and other useful info.

There are docs for the development version
`here <>`__. These should
more or less correspond with the github master branch, but they\'re not
built automatically and thus may fall out of sync at times.


.. code:: python

from msmbuilder.example_datasets import FsPeptide
from msmbuilder.featurizer import RMSDFeaturizer

import msmexplorer as msme

# Load Fs Peptide Data
traj = FsPeptide().get().trajectories[0]

# Calculate RMSD
featurizer = RMSDFeaturizer(reference_traj=traj[0])
rmsd = featurizer.partial_transform(traj).flatten()

# Plot Trace
msme.plot_trace(rmsd, label=\'traj0\', xlabel=\'Timestep\', ylabel=\'RMSD (nm)\')

.. figure::

The documentation has an `example
gallery <>`__
with short scripts showing how to use different parts of the package.


- Python 3.4+


- `numpy <>`__

- `scipy <>`__

- `matplotlib <>`__

- `networkx <>`__

- `pandas <>`__

- `seaborn <>`__

- `statsmodels <>`__

- `corner <>`__

- `mdtraj <>`__

- `msmbuilder <>`__


The preferred installation mechanism for ``msmexplorer`` is with

.. code:: bash

$ conda install -c omnia msmexplorer

If you don\'t have conda, or are new to scientific python, we recommend
that you download the `Anaconda scientific python
distribution <>`__.

To install from PyPI, just do:


pip install msmexplorer

You may instead want to use the development version from Github, by


pip install git+git://


`submit <>`__ any
bugs you encounter to the Github issue tracker.


Released under a MIT license


.. code:: bibtex

author = {Carlos X. Hern\xc3\xa1ndez and
Vijay S. Pande},
title = {MSMExplorer},
month = aug,
year = 2016,
doi = {10.5281/zenodo.61277},
url = {}

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