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https://github.com/laurentrdc/crystals
Data structures, algorithms, and parsing for crystallography
https://github.com/laurentrdc/crystals
bioinformatics crystal-structure crystallography indexing-algorithms materials-science python3
Last synced: about 2 months ago
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Data structures, algorithms, and parsing for crystallography
- Host: GitHub
- URL: https://github.com/laurentrdc/crystals
- Owner: LaurentRDC
- License: gpl-3.0
- Created: 2018-11-06T18:53:33.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2024-10-23T19:48:47.000Z (2 months ago)
- Last Synced: 2024-10-25T20:18:01.739Z (about 2 months ago)
- Topics: bioinformatics, crystal-structure, crystallography, indexing-algorithms, materials-science, python3
- Language: Python
- Homepage: https://crystals.readthedocs.io/
- Size: 818 KB
- Stars: 42
- Watchers: 8
- Forks: 12
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- License: LICENSE
Awesome Lists containing this project
README
crystals
========
[](https://crystals.readthedocs.io/) [](https://pypi.python.org/pypi/crystals) [](https://anaconda.org/conda-forge/crystals) [](https://doi.org/10.1186/s40679-018-0060-y)
`crystals` is a library of data structure and algorithms to manipulate
abstract crystals in a Pythonic way. `crystals` helps with reading
crystallographic files (like .cif and .pdb), provides access to atomic
positions, scattering utilities, allows for symmetry determination, and
indexing of diffraction peaks. Although `crystals` can be used on its own,
it was made to be integrated into larger projects (like
[scikit-ued](https://github.com/LaurentRDC/scikit-ued)).
Take a look at the [documentation](https://crystals.readthedocs.io/) for
more information and examples.
Installation
------------
`crystals` is available on the Python Package Index:
pip install crystals
For users of the conda package manager, `crystals` is also available
from the conda-forge channel:
conda install -c conda-forge crystals
### From source
`crystals` can also be installed from source:
git clone https://github.com/LaurentRDC/crystals.git
cd crystals
# If you want to use crystals, use `install`
python setup.py install
# If you want to hack crystals, `use develop`
python setup.py develop
You can install the latest development version using `pip` as well:
python -m pip install git+git://github.com/LaurentRDC/crystals.git
To build documentation, you will need a few more packages, listed in
`dev-requirements.txt`. For example, to build documentation from source:
git clone https://github.com/LaurentRDC/crystals.git
cd crystals
pip install -r dev-requirements.txt
python setup.py build_sphinx
Documentation
-------------
The documentation, including user guides as well as detailed reference,
is available here:
Development
-----------
Tests can be run with the `pytest` package:
python -m pytest --pyargs crystals
Some optional tests might be skipped if dependencies are not installed,
e.g. [ASE](https://wiki.fysik.dtu.dk/ase/).
Citations
---------
As this package is a spinoff from `scikit-ued`, please consider citing
the following publication if you find `crystals` useful:
> L. P. René de Cotret, M. R. Otto, M. J. Stern. and B. J. Siwick, *An open-source software ecosystem for the interactive exploration of ultrafast electron scattering data*, Advanced Structural and Chemical Imaging 4:11 (2018) [DOI: 10.1186/s40679-018-0060-y.](https://ascimaging.springeropen.com/articles/10.1186/s40679-018-0060-y)
Underlying algorithms provided by `spglib` are described in the
following publication:
> A. Togo and I. Tanaka, *spglib: a software library for crystal symmetry search*. [https://arxiv.org/abs/1808.01590](https://arxiv.org/abs/1808.01590) (written at version 1.10.4).
Structure parsing from CIF files has been tested for correctness against
CIF2CELL, detailed here:
> Torbjorn Bjorkman, *CIF2Cell: Generating geometries for electronic structure programs*, Computer Physics Communications 182, 1183-1186 (2011) [DOI: 10.1016/j.cpc.2011.01.013](https://doi.org/10.1016/j.cpc.2011.01.013)
Structure parsing from PDB files has been tested for correctness against
`Bio.PDB`, detailed here:
> Hamelryck, T., Manderick, B. *PDB parser and structure class implemented in Python*. Bioinformatics 19: 2308–2310 (2003)
Atomic weights are reported in the following publication:
> Meija, J., Coplen, T., Berglund, M., et al. (2016). *Atomic weights of the elements 2013* (IUPAC Technical Report). Pure and Applied Chemistry, 88(3), pp. 265-291. Retrieved 30 Nov. 2016, [DOI:10.1515/pac-2015-0305](https://doi.org/10.1515/pac-2015-0305)
Covalent radii are reported in the following article:
> Cordero, B. et al. (2008). *Covalent radii revisited*. Dalton Transactions, issue 21, pp. 2832-2838. The Royal Society of Chemistry. [DOI: 10.1039/B801115j](https://dx.doi.org/10.1039/B801115J)
Support / Report Issues
-----------------------
All support requests and issue reports should be [filed on Github as an
issue](https://github.com/LaurentRDC/crystals/issues).
License
-------
`crystals` is made available under the GPLv3 license. For more
details, see [LICENSE](https://github.com/LaurentRDC/crystals/blob/master/LICENSE).
Related projects
----------------
- Streaming operations on NumPy arrays are available in the [npstreams
package](https://pypi.org/pypi/npstreams).
- Interactive exploration of ultrafast electron diffraction data with
the [iris-ued package](https://pypi.org/project/iris-ued/).
- Data structures and algorithms to handle ultrafast electron
scattering data in the [scikit-ued
package](https://pypi.org/project/scikit-ued).