pyemma

🚂 Python API for Emma's Markov Model Algorithms 🚂

Science Score: 10.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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codemeta.json file
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.zenodo.json file
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DOI references
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Academic publication links
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Committers with academic emails
21 of 53 committers (39.6%) from academic institutions
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (16.1%) to scientific vocabulary

Keywords

analysis bayesian-methods hidden-markov-model hmm kinetic-modeling markov-model markov-state-model mbar molecular-dynamics molecular-modeling python tica time-series umbrella-sampling

Keywords from Contributors

closember hyperparameter-optimization biomolecular-simulation molecular-dynamics-simulation monte-carlo path-sampling

Last synced: 6 months ago · JSON representation

Repository

🚂 Python API for Emma's Markov Model Algorithms 🚂

Basic Info

Host: GitHub
Owner: markovmodel
License: lgpl-3.0
Language: Python
Default Branch: devel
Homepage: http://pyemma.org
Size: 10.3 MB

Statistics

Stars: 327
Watchers: 30
Forks: 124
Open Issues: 57
Releases: 26

Archived

Topics

analysis bayesian-methods hidden-markov-model hmm kinetic-modeling markov-model markov-state-model mbar molecular-dynamics molecular-modeling python tica time-series umbrella-sampling

Created over 11 years ago · Last pushed over 2 years ago

Metadata Files

Readme License

README.rst

=============================================
This project is no longer actively maintained
=============================================

An alternative package reflecting most of PyEMMA's functionality is `deeptime `__.

=====================================
EMMA (Emma's Markov Model Algorithms)
=====================================

.. image:: https://img.shields.io/azure-devops/build/clonker/e16cf5d1-7827-4597-8bb5-b0f7577c73d1/6
   :target: https://dev.azure.com/clonker/pyemma/_build
.. image:: https://img.shields.io/pypi/v/pyemma.svg
   :target: https://pypi.python.org/pypi/pyemma
.. image:: https://anaconda.org/conda-forge/pyemma/badges/downloads.svg
   :target: https://anaconda.org/conda-forge/pyemma
.. image:: https://anaconda.org/conda-forge/pyemma/badges/installer/conda.svg
   :target: https://conda.anaconda.org/conda-forge
.. image:: https://img.shields.io/codecov/c/github/markovmodel/PyEMMA/devel.svg
   :target: https://codecov.io/gh/markovmodel/PyEMMA/branch/devel


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
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 Jupyter (former IPython, recommended), or by
writing Python scripts. The docs, can be found at
`http://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
------------
If you want to use Miniconda on Linux or OSX, you can run this script to download and install everything::

   curl -s https://raw.githubusercontent.com/markovmodel/PyEMMA/devel/install_miniconda%2Bpyemma.sh | bash

If you have Anaconda/Miniconda installed, use the following::

   conda install -c conda-forge pyemma

With pip::

   pip install 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 `__ 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/suggestions/complaints please file an issue on
`GitHub `__.

Or start a discussion on our mailing list: pyemma-users@lists.fu-berlin.de


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

Owner

Name: Markov model
Login: markovmodel
Kind: organization

Repositories: 34
Profile: https://github.com/markovmodel

GitHub Events

Total

Watch event: 19
Fork event: 6

Last Year

Watch event: 19
Fork event: 6

Committers

Last synced: over 2 years ago

All Time

Total Commits: 5,960
Total Committers: 53
Avg Commits per committer: 112.453
Development Distribution Score (DDS): 0.376

Past Year

Commits: 6
Committers: 5
Avg Commits per committer: 1.2
Development Distribution Score (DDS): 0.667

Top Committers

Name	Email	Commits
marscher	m**r@f**e	3,722
Christoph Wehmeyer	c**r@f**e	442
Benjamin Trendelkamp-Schroer	b**r@f**e	421
noe	f**e@f**e	358
jouno	f**b@p**e	192
Moritz Hoffmann	c**r@g**m	186
Paul, Fabian (fapa)	f**l@m**e	121
gph82	g**z@f**e	104
thempel	t**l@z**e	75
Martin K. Scherer	m****r	59
Jan-Hendrik Prinz	j**z@g**e	46
fnueske	f**e@f**e	39
Simon Olsson	s**s@h**m	33
Benjamin Trendelkamp-Schroer	t**p@m**e	21
ppxasjsm	a**y@f**e	20
florianlitzinger	f****r	15
Guillermo Perez Hernandez	g**2@z**e	11
Fabian Paul	f**b@F**l	9
unknown	p**l@T**l	7
Guillermo Pérez-Hernández	g****2	7
Josh Fass	m****e	6
Josh Fass	j**4@c**u	5
John Chodera (MSKCC)	c**j@m**g	5
Nuria	n**r@f**e	4
Ismael Rodriguez Espigares	i**p@t**t	4
RobertArbon	r**n@b**k	4
Alexandra La Fleur	a**r@f**e	4
Stefan Doerr	s**r@u**u	3
leonardo	l**o@m**)	3
Sander Roet	s**t@h**m	3
and 23 more...

Committer Domains (Top 20 + Academic)

fu-berlin.de: 10 zedat.fu-berlin.de: 3 mi.fu-berlin.de: 2 stanford.edu: 1 loro.imim.es: 1 fabians-air.localdomain: 1 mantis.(none): 1 upf.edu: 1 bristol.ac.uk: 1 telefonica.net: 1 mskcc.org: 1 cornell.edu: 1 gmx.de: 1 mpikg.mpg.de: 1 physik.tu-berlin.de: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 102
Total pull requests: 20
Average time to close issues: 3 months
Average time to close pull requests: 18 days
Total issue authors: 63
Total pull request authors: 8
Average comments per issue: 3.73
Average comments per pull request: 1.55
Merged pull requests: 20
Bot issues: 0
Bot pull requests: 0

Past Year

Issues: 0
Pull requests: 0
Average time to close issues: N/A
Average time to close pull requests: N/A
Issue authors: 0
Pull request authors: 0
Average comments per issue: 0
Average comments per pull request: 0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

View more stats

Top Authors

Issue Authors

Bazzinga18 (9)
clonker (7)
hima111997 (5)
cgseitz (5)
orthonalmatrix (4)
rubinanoor9 (4)
germanbarcenas (3)
satyajitkhatua09 (3)
qasimpars (3)
Chakrabort123 (2)
Harshitasahni (2)
hl2500 (2)
debanjansen48 (2)
pojeda (1)
marscher (1)

Pull Request Authors

clonker (13)
evilsetg (1)
wehs7661 (1)
sroet (1)
comecattin (1)
sents (1)
sefalkner (1)
songyongshun (1)

Top Labels

Issue Labels

wontfix (19) tech-support (3) enhancement (2) design-discussion (2) documentation (2) question (2) coordinates (1) low-prio (1) msm (1) invalid (1)

Pull Request Labels

Packages

Total packages: 2
Total downloads:
- pypi 752 last-month

Total dependent packages: 9
(may contain duplicates)
Total dependent repositories: 14
(may contain duplicates)
Total versions: 63
Total maintainers: 2

pypi.org: pyemma

PyEMMA: Emma's Markov Model Algorithms

Homepage: http://github.com/markovmodel/PyEMMA
Documentation: https://pyemma.readthedocs.io/
License: LGPLv3+
Latest release: 2.5.12
published over 3 years ago

Versions: 45
Dependent Packages: 7
Dependent Repositories: 9
Downloads: 752 Last month

Rankings

Dependent packages count: 2.3%

Stargazers count: 3.7%

Forks count: 4.3%

Average: 4.7%

Dependent repos count: 4.9%

Downloads: 8.5%

Maintainers (2)

marscher clonker

Last synced: 6 months ago

conda-forge.org: pyemma

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)

Homepage: http://github.com/markovmodel/pyemma
License: LGPL-3.0-or-later
Latest release: 2.5.12
published over 3 years ago

Versions: 18
Dependent Packages: 2
Dependent Repositories: 5

Rankings

Dependent repos count: 14.8%

Forks count: 17.0%

Average: 18.6%

Dependent packages count: 19.6%

Stargazers count: 23.0%

Last synced: 6 months ago

Dependencies

doc/requirements-build-doc.txt pypi

msmb_theme >=1.2
sphinx-issues *

setup.py pypi

decorator >=4.0.0
deeptime >=0.4.2
h5py >=2.7.1
matplotlib *
mdtraj >=1.9.2
numpy >=1.8.0
pathos *
psutil >=3.1.1
pyyaml *
scipy >=0.11
tqdm >=4.23