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
Release files for pyEMMA 2.5.12
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| pyEMMA-2.5.12.tar.gz | 1.3 MB | Without provenance | Details |
Release files / pyEMMA-2.5.12.tar.gz
| Download URL | pyEMMA-2.5.12.tar.gz |
|---|---|
| Size | 1.3 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
0916b33151c7a3e945b3810cf660eb13bb371718355cced808f510aef7da275d
|
|
BLAKE2b-256 checksum How to use checksums |
fbf27bb51bcfad7bd49ab6f86c597fff4ac9a7143dd906e5ed707d9922a7be51
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.0 CPython/3.10.6
|
Security for pyEMMA 2.5.12
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
