Skip to main content

Python Materials Genomics is a robust materials analysis code that defines core object representations for structures and molecules with support for many electronic structure codes. It is currently the core analysis code powering the Materials Project (https://www.materialsproject.org).

Project description

https://coveralls.io/repos/github/materialsproject/pymatgen/badge.svg?branch=master

Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis. These are some of the main features:

  1. Highly flexible classes for the representation of Element, Site, Molecule, Structure objects.

  2. Extensive input/output support, including support for VASP (http://cms.mpi.univie.ac.at/vasp/), ABINIT (http://www.abinit.org/), CIF, Gaussian, XYZ, and many other file formats.

  3. Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.

  4. Electronic structure analyses, such as density of states and band structure.

  5. Integration with the Materials Project REST API.

Pymatgen is free to use. However, we also welcome your help to improve this library by making your own contributions. These contributions can be in the form of additional tools or modules you develop, or feature requests and bug reports. Please report any bugs and issues at pymatgen’s Github page. If you wish to be notified of pymatgen releases, you may become a member of pymatgen’s Google Groups page.

Why use pymatgen?

There are many materials analysis codes out there, both commerical and free, but pymatgen offer several advantages:

  1. It is (fairly) robust. Pymatgen is used by thousands of researchers, and is the analysis code powering the Materials Project. The analysis it produces survives rigorous scrutiny every single day. Bugs tend to be found and corrected quickly. Pymatgen also uses CircleCI for continuous integration, which ensures that every commit passes a comprehensive suite of unittests.

  2. It is well documented. A fairly comprehensive documentation has been written to help you get to grips with it quickly.

  3. It is open. You are free to use and contribute to pymatgen. It also means that pymatgen is continuously being improved. We have a policy of attributing any code you contribute to any publication you choose. Contributing to pymatgen means your research becomes more visible, which translates to greater impact.

  4. It is fast. Many of the core numerical methods in pymatgen have been optimized by vectorizing in numpy. This means that coordinate manipulations are extremely fast and are in fact comparable to codes written in other languages. Pymatgen also comes with a complete system for handling periodic boundary conditions.

  5. It will be around. Pymatgen is not a pet research project. It is used in the well-established Materials Project. It is also actively being developed and maintained by the Materials Virtual Lab, the ABINIT group and many other research groups. The plan is to make sure pymatgen will stand the test of time and be the de facto analysis code for most materials and structural analysis.

With effect from version 3.0, pymatgen now supports both Python 2.7 as well as Python 3.x. All developers must ensure that their code passes the unittests on both Py2.7 and 3.x.

Getting pymatgen

Before installing pymatgen, you may need to first install a few critical dependencies manually. Please refer to the official pymatgen page for installation details and requirements, including instructions for the bleeding edge developmental version. For people who are absolutely new to Python packages, it is highly recommended you do the installation using conda, which will make things a lot easier, especially on Windows.

The version at the Python Package Index (PyPI) is always the latest stable release that is relatively bug-free. The easiest way to install pymatgen on any system is to use pip:

pip install pymatgen

Wheels for Mac (Python 2.7 and 3.5) and Windows (Python 3.5) have been built for convenience.

Some extra functionality (e.g., generation of POTCARs) do require additional setup (please see the pymatgen page).

Change Log

The latest change log is available here.

Using pymatgen

Please refer to the official pymatgen page for tutorials and examples.

How to cite pymatgen

If you use pymatgen in your research, please consider citing the following work:

Shyue Ping Ong, William Davidson Richards, Anubhav Jain, Geoffroy Hautier, Michael Kocher, Shreyas Cholia, Dan Gunter, Vincent Chevrier, Kristin A. Persson, Gerbrand Ceder. Python Materials Genomics (pymatgen) : A Robust, Open-Source Python Library for Materials Analysis. Computational Materials Science, 2013, 68, 314-319. doi:10.1016/j.commatsci.2012.10.028

In addition, some of pymatgen’s functionality is based on scientific advances / principles developed by the computational materials scientists in our team. Please refer to pymatgen’s documentation on how to cite them.

License

Pymatgen is released under the MIT License. The terms of the license are as follows:

The MIT License (MIT)
Copyright (c) 2011-2012 MIT & LBNL

Permission is hereby granted, free of charge, to any person obtaining a copy of
this software and associated documentation files (the "Software"), to deal in
the Software without restriction, including without limitation the rights to
use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of
the Software, and to permit persons to whom the Software is furnished to do so,
subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN
CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

About the Pymatgen Development Team

Shyue Ping Ong of the Materials Virtual Lab started Pymatgen in 2011, and is still the project lead.

The Pymatgen Development Team is the set of all contributors to the pymatgen project, including all subprojects.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pymatgen-4.4.12.tar.gz (1.4 MB view details)

Uploaded Source

Built Distributions

pymatgen-4.4.12-cp35-cp35m-win_amd64.whl (1.7 MB view details)

Uploaded CPython 3.5m Windows x86-64

pymatgen-4.4.12-cp35-cp35m-macosx_10_6_x86_64.whl (1.8 MB view details)

Uploaded CPython 3.5m macOS 10.6+ x86-64

pymatgen-4.4.12-cp27-cp27m-macosx_10_6_x86_64.whl (1.8 MB view details)

Uploaded CPython 2.7m macOS 10.6+ x86-64

File details

Details for the file pymatgen-4.4.12.tar.gz.

File metadata

  • Download URL: pymatgen-4.4.12.tar.gz
  • Upload date:
  • Size: 1.4 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No

File hashes

Hashes for pymatgen-4.4.12.tar.gz
Algorithm Hash digest
SHA256 c69696aa8a368f8ab83c4653a2561459424dfe1ceb5eaf50d86e2fbc4168eb5d
MD5 798a51040fa2b96321af4af3aa834cd0
BLAKE2b-256 45fd8afa6827141c1c8c16f47c2bdd769a91739d564461479f03ce4eee514d52

See more details on using hashes here.

File details

Details for the file pymatgen-4.4.12-cp35-cp35m-win_amd64.whl.

File metadata

File hashes

Hashes for pymatgen-4.4.12-cp35-cp35m-win_amd64.whl
Algorithm Hash digest
SHA256 7d7939e981ce343335bef25d577f2104ce594d7c34aecb0a2f9a4b21c7592e03
MD5 4f2bd0cc2f49615708ccb6854ff0320a
BLAKE2b-256 77175b69eacab0fcf6737ce4c7f949f542ee7e1b66744daff2ed105f834b6052

See more details on using hashes here.

File details

Details for the file pymatgen-4.4.12-cp35-cp35m-macosx_10_6_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-4.4.12-cp35-cp35m-macosx_10_6_x86_64.whl
Algorithm Hash digest
SHA256 c9be2a007c0f1d91497fca5d1a0a4faf0f5d764d208c666518840411954b4cd1
MD5 99cf5bb5bf069489c1349b83c6d0cdf3
BLAKE2b-256 7de1983069a8213e16dce9992e377d1b7a2fd4b3c02cad169f68813c414c5d00

See more details on using hashes here.

File details

Details for the file pymatgen-4.4.12-cp27-cp27m-macosx_10_6_x86_64.whl.

File metadata

File hashes

Hashes for pymatgen-4.4.12-cp27-cp27m-macosx_10_6_x86_64.whl
Algorithm Hash digest
SHA256 ab3e35864292e96cd1aad3845e52199fa216d0ea6782bda0a4b7486e0237210c
MD5 96e9bedfcfc09e342c93ccfd5a855b4c
BLAKE2b-256 5c60f7bc3376f2c3424aa89ba2a7b55cd7943c38b35bd3c51a52fe852812eddd

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page