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
Pymatgen (Python Materials Genomics) is a robust, open-source Python library for materials analysis. These are some of the main features:
Highly flexible classes for the representation of Element, Site, Molecule, Structure objects.
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.
Powerful analysis tools, including generation of phase diagrams, Pourbaix diagrams, diffusion analyses, reactions, etc.
Electronic structure analyses, such as density of states and band structure.
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:
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.
It is well documented. A fairly comprehensive documentation has been written to help you get to grips with it quickly.
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.
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.
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. Visit materials.sh for instructions on how to use the matsci channel to install pymatgen and other packages.
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.
Our Copyright Policy
Pymatgen uses a shared copyright model. Each contributor maintains copyright over their contributions to pymatgen. But, it is important to note that these contributions are typically only changes to the repositories. Thus, the pymatgen source code, in its entirety is not the copyright of any single person or institution. Instead, it is the collective copyright of the entire pymatgen Development Team. If individual contributors want to maintain a record of what changes/contributions they have specific copyright on, they should indicate their copyright in the commit message of the change, when they commit the change to one of the pymatgen repositories.
With this in mind, the following banner should be used in any source code file to indicate the copyright and license terms:
# Copyright (c) Pymatgen Development Team. # Distributed under the terms of the MIT License.
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
Built Distributions
File details
Details for the file pymatgen-4.7.2.tar.gz.
File metadata
- Download URL: pymatgen-4.7.2.tar.gz
- Upload date:
- Size: 1.5 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | e439b78cc3833a03963c3c3efe349d8a0e52a1550c8a05c56a89aa1b86657436 |
|
| MD5 | 9c3a6e8608671c216e4ef89778646fd6 |
|
| BLAKE2b-256 | 1e521c0b400a711a494cfde89567a0e3a59d59abf8e8fd644b7a9df2915ccf00 |
File details
Details for the file pymatgen-4.7.2-cp36-cp36m-macosx_10_7_x86_64.whl.
File metadata
- Download URL: pymatgen-4.7.2-cp36-cp36m-macosx_10_7_x86_64.whl
- Upload date:
- Size: 1.9 MB
- Tags: CPython 3.6m, macOS 10.7+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | c44c9967a0d6ada85b63e25b5decbd6f0415a66a2ef7ccbb1d1242ab0db6f923 |
|
| MD5 | 33e9502e081591f45701a0915d2638f7 |
|
| BLAKE2b-256 | f5930867d51e30f852dbd225728c9b3542fe50824b93ecc0f8b95f32afbf7398 |
File details
Details for the file pymatgen-4.7.2-cp35-cp35m-win_amd64.whl.
File metadata
- Download URL: pymatgen-4.7.2-cp35-cp35m-win_amd64.whl
- Upload date:
- Size: 1.8 MB
- Tags: CPython 3.5m, Windows x86-64
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 3e05c8f79e898cfbc1da1da77c41946daea9f5e87d9d546b1bb5e097e64bf007 |
|
| MD5 | 4ef616ae70e5d9afa3a03c328ba2f889 |
|
| BLAKE2b-256 | 7414b1bae90db53f3bcc96de7b81c573515630ae8520441d65a9c16159476dca |
File details
Details for the file pymatgen-4.7.2-cp35-cp35m-macosx_10_9_x86_64.whl.
File metadata
- Download URL: pymatgen-4.7.2-cp35-cp35m-macosx_10_9_x86_64.whl
- Upload date:
- Size: 1.8 MB
- Tags: CPython 3.5m, macOS 10.9+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 98515b150a4cc8c4c2bdd489893cf91ee232585823ffba7e3eabfcdd4ccb9048 |
|
| MD5 | ccc159fb2d04a31938d10430781c2dee |
|
| BLAKE2b-256 | fa0b1482cb1d4759fb064b670875c79bb48c35764e0247b02ac2bdb7027c20f5 |
File details
Details for the file pymatgen-4.7.2-cp27-cp27m-macosx_10_6_x86_64.whl.
File metadata
- Download URL: pymatgen-4.7.2-cp27-cp27m-macosx_10_6_x86_64.whl
- Upload date:
- Size: 1.9 MB
- Tags: CPython 2.7m, macOS 10.6+ x86-64
- Uploaded using Trusted Publishing? No
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 | 653540720d15a06a61352bbd6437eca4d117e490f584c9561f31e0678a2fdc71 |
|
| MD5 | 449ca67545c11042bafbc0d215294e80 |
|
| BLAKE2b-256 | 7274ee2a98dc935da055914676d3294cf3642cc466e0d5b7aa5937904d51f804 |
