scikit-ued 0.5.8

Collection of algorithms and functions for ultrafast electron diffraction

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 install the latest development version from Github:

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

Each version is tested against Python 3.5 and 3.6. If you are using a different version, tests can be run using the standard library’s unittest module.

Dependencies for scikit-ued (e.g. spglib) require compilation. Windows users should minimally have the Visual Studio Build Tools installed. Don’t forget to update setuptools to the latest version to avoid common problems involving C-extensions on Windows:

python -m pip install --upgrade setuptools

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

Optional dependencies

While it is not strictly required, the Fourier transform routines from pyfftw will be preferred If pyfftw is installed.

For displaying diffraction images using the skued.diffshow function, PyQtGraph and PyQt5 are both required.

Related projects

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

Streaming operations on NumPy arrays are available in the npstreams package.

Citations

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

[1]

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 MIT License. For more details, see LICENSE.txt.