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scikit-ued

Documentation Build Status PyPI Version Conda-forge Version DOI badge

Collection of algorithms and functions for ultrafast electron diffraction. It aims to be a fully-tested package taking advantage of Python's most recent features.

For examples, see our tutorials.

API Reference

The API Reference on readthedocs.io provides API-level documentation, as well as tutorials.

Installation

scikit-ued is available on PyPI; it can be installed with pip:

python -m pip install scikit-ued

To also install optional dependencies required to view diffraction images interactively:

python -m pip install scikit-ued[diffshow]

scikit-ued is also available on the conda-forge channel for the conda package manager:

conda config --add channels conda-forge
conda install scikit-ued

To install the latest development version from Github:

python -m pip install git+https://github.com/LaurentRDC/scikit-ued.git

After installing scikit-ued you can use it like any other Python module as skued.

Each version is tested against Python 3.7+. If you are using a different version, tests can be run using the pytest package.

Optional dependencies

For displaying diffraction images with interactive contrast using the skued.diffshow function, PyQtGraph is required.

Contributing

If you want to contribute to scikit-ued, take a look at CONTRIBUTING.md.

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.

Crystal structure manipulation (including symmetry-determination) with the crystals package. (Included with scikit-ued)

A graphical user interface for the dual-tree complex wavelet transform baseline-removal routine is available as a separate package.

Citations

If you find this software useful, please consider citing the following publication:

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.

If you are using the baseline-removal functionality of scikit-ued, please consider citing the following publication:

L. P. René de Cotret and B. J. Siwick, A general method for baseline-removal in ultrafast electron powder diffraction data using the dual-tree complex wavelet transform, Struct. Dyn. 4 (2017) DOI: 10.1063/1.4972518.

Support / Report Issues

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

License

scikit-ued is made available under the GPLv3 License. For more details, see LICENSE.txt.