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.
The API Reference on readthedocs.io provides API-level documentation, as well as tutorials.
scikit-ued is available on PyPI; it can be installed with pip:
python -m pip install scikit-ued
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+git://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 3.6. If you are using a different version, tests can be run using the standard library's unittest module.
While it is not strictly required, the Fourier transform routines from pyfftw will be preferred If
pyfftw is installed.
For displaying diffraction images with interactive contrast using the skued.diffshow function, PyQtGraph is required.
Streaming operations on NumPy arrays are available in the npstreams package.
Interactive exploration of ultrafast electron diffraction data with the iris-ued package.
A graphical user interface for the dual-tree complex wavelet transform baseline-removal routine is available as a separate package.
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.
All support requests and issue reports should be filed on Github as an issue.
scikit-ued is made available under the MIT License. For more details, see LICENSE.txt.