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Data structures, algorithms, and parsing for crystallography

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crystals

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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).

Take a look at the documentation 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: https://crystals.readthedocs.io/

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.

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.

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 (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

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

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

Support / Report Issues

All support requests and issue reports should be filed on Github as an issue.

License

crystals is made available under the GPLv3 license. For more details, see LICENSE.

Related projects

  • Streaming operations on NumPy arrays are available in the npstreams package.
  • Interactive exploration of ultrafast electron diffraction data with the iris-ued package.
  • Data structures and algorithms to handle ultrafast electron scattering data in the scikit-ued package.