Skip to main content

Python Multiscale Thermochemistry Toolbox (pMuTT)

The Python Multiscale Thermochemistry Toolbox (pMuTT) is a Python library for Thermochemistry developed by the Vlachos Research Group at the University of Delaware. This code was originally developed to convert ab-initio data from DFT to observable thermodynamic properties such as heat capacity, enthalpy, entropy, and Gibbs energy. These properties can be fit to empirical equations and written to different formats.

https://raw.githubusercontent.com/VlachosGroup/pMuTT/master/docs/source/logos/pmutt_web.png

Documentation

See our documentation page for examples, equations used, and docstrings.

Developers

Dependencies

  • Python3

  • Atomic Simulation Environment: Used for I/O operations and to calculate some thermodynamic properties

  • Numpy: Used for vector and matrix operations

  • Pandas: Used to import data from Excel files

  • xlrd: Used by Pandas to import Excel files

  • SciPy: Used for fitting heat capacities and generating smooth curves for reaction coordinate diagram

  • Matplotlib: Used for plotting thermodynamic data

  • pyGal: Similar to Matplotlib. Used for plotting interactive graphs

  • PyMongo: Used to read/write to databases

  • dnspython: Used to connect to databases

  • NetworkX: Used to plot reaction networks

  • More Itertools: Used for writing ranges for OpenMKM output.

  • PyYAML: Used to write YAML input files for OpenMKM.

Getting Started

  1. Install using pip (see documentation for more thorough instructions):

    pip install pmutt
  2. Look at examples using the code

  3. Run the unit tests.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Publications

  • J. Lym, G.R. Wittreich and D.G. Vlachos, A Python Multiscale Thermochemistry Toolbox (pMuTT) for thermochemical and kinetic parameter estimation, Computer Physics Communications (2019) 106864, https://doi.org/10.1016/j.cpc.2019.106864.

Contributing

If you have a suggestion or find a bug, please post to our Issues page with the enhancement_label or bug_label tag respectively.

Finally, if you would like to add to the body of code, please:

  • fork the development branch

  • make the desired changes

  • write the appropriate unit tests

  • submit a pull request.

Questions

If you are having issues, please post to our Issues page with the help_wanted_label or question_label tag. We will do our best to assist.

Funding

This material is based upon work supported by the Department of Energy’s Office of Energy Efficient and Renewable Energy’s Advanced Manufacturing Office under Award Number DE-EE0007888-9.5.

Special Thanks

  • Dr. Jeffrey Frey (pip and conda compatibility)

  • Jaynell Keely (Logo design)

Metadata

Release files for pmutt 1.4.17

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for pmutt 1.4.17
File Size Uploaded Provenance Actions
pmutt-1.4.17.tar.gz 682.7 kB Without provenance Details for pmutt-1.4.17.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for pmutt 1.4.17
File Interpreter ABI Platform Actions
pmutt-1.4.17-py3-none-any.whl Python 3 none any Details for pmutt-1.4.17-py3-none-any.whl

Total release size: 1.4 MB

Release files / pmutt-1.4.17.tar.gz

Download URL pmutt-1.4.17.tar.gz
Size 682.7 kB
Tags Source
SHA-256 checksum
How to use checksums
591572b61bfc23611c2acabe23083486f9fe3d02b9b9e1becaa158f2519b8096
BLAKE2b-256 checksum
How to use checksums
e151d2179a29f74fb986ce095889bf9e7f2c8741578457bf9a08eb89ac088c72
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.10.9

Release files / pmutt-1.4.17-py3-none-any.whl

Download URL pmutt-1.4.17-py3-none-any.whl
Size 735.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4630c1e55d40c1491e0e13a147948e93fc057859ff681fad86ac4bb2ab559de6
BLAKE2b-256 checksum
How to use checksums
8e142773857e185c6fd39a3e0823689e8bfcc5fac548bc5c14b4991657bd7b9d
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.1.0 CPython/3.10.9

Security for pmutt 1.4.17

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.

Release history Release notifications | RSS feed

This release

1.4.17 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page