Collection of algorithms and functions for ultrafast electron scattering
[![Windows Build Status](https://img.shields.io/appveyor/ci/LaurentRDC/scikit-ued/master.svg)](https://ci.appveyor.com/project/LaurentRDC/scikit-ued) [![Documentation Build Status](https://readthedocs.org/projects/scikit-ued/badge/?version=master)](http://scikit-ued.readthedocs.io) [![PyPI Version](https://img.shields.io/pypi/v/scikit-ued.svg)](https://pypi.org/project/scikit-ued/) [![Conda-forge Version](https://img.shields.io/conda/vn/conda-forge/scikit-ued.svg)](https://anaconda.org/conda-forge/scikit-ued) ![Supported Python Versions](https://img.shields.io/pypi/pyversions/scikit-ued.svg)
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](https://scikit-ued.readthedocs.io/).
The [API Reference on readthedocs.io](https://scikit-ued.readthedocs.io) provides API-level documentation, as well as tutorials.
scikit-ued is available on PyPI; it can be installed with [pip](https://pip.pypa.io):
python -m pip install scikit-ued
scikit-ued is also available on the conda-forge channel for the [conda package manager](https://conda.io/docs/):
conda config –add channels conda-forge conda install scikit-ued
To install the latest development version from [Github](https://github.com/LaurentRDC/scikit-ued):
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.
For displaying diffraction images with interactive contrast using the skued.diffshow function, PyQtGraph is required.
If you find this software useful, please consider citing the following publication:
> L. P. RenÃ© 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)
If you are using the baseline-removal functionality of scikit-ued, please consider citing the following publication:
> L. P. RenÃ© 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](https://doi.org/10.1063/1.4972518).
Support / Report Issues
All support requests and issue reports should be [filed on Github as an issue](https://github.com/LaurentRDC/scikit-ued/issues).
scikit-ued is made available under the MIT License. For more details, see [LICENSE.txt](https://github.com/LaurentRDC/scikit-ued/blob/master/LICENSE.txt).
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size scikit_ued-2.0.5-py3-none-any.whl (100.3 kB)||File type Wheel||Python version py3||Upload date||Hashes View|
|Filename, size scikit-ued-2.0.5.tar.gz (88.9 kB)||File type Source||Python version None||Upload date||Hashes View|
Hashes for scikit_ued-2.0.5-py3-none-any.whl