https://github.com/laurentrdc/scikit-ued
Collection of algorithms and routines for (ultrafast) electron diffraction and scattering
https://github.com/laurentrdc/scikit-ued
diffraction electron-microscopy python science scikit ultrafast-electron
Last synced: about 1 month ago
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Collection of algorithms and routines for (ultrafast) electron diffraction and scattering
- Host: GitHub
- URL: https://github.com/laurentrdc/scikit-ued
- Owner: LaurentRDC
- License: gpl-3.0
- Created: 2017-04-22T16:22:39.000Z (about 8 years ago)
- Default Branch: master
- Last Pushed: 2025-01-16T16:59:58.000Z (4 months ago)
- Last Synced: 2025-04-03T15:08:45.740Z (about 1 month ago)
- Topics: diffraction, electron-microscopy, python, science, scikit, ultrafast-electron
- Language: Python
- Homepage: http://scikit-ued.readthedocs.io
- Size: 24.2 MB
- Stars: 138
- Watchers: 8
- Forks: 21
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.rst
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
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README
scikit-ued
==========
[](http://scikit-ued.readthedocs.io) [](https://pypi.org/project/scikit-ued/) [](https://anaconda.org/conda-forge/scikit-ued) [](https://doi.org/10.1186/s40679-018-0060-y)
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/).
API Reference
-------------
The [API Reference on readthedocs.io](https://scikit-ued.readthedocs.io) provides API-level documentation, as well as tutorials.
Installation
------------
scikit-ued is available on PyPI; it can be installed with [pip](https://pip.pypa.io):
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](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+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`](https://github.com/LaurentRDC/scikit-ued/blob/master/CONTRIBUTING.md).
Related projects
----------------
Streaming operations on NumPy arrays are available in the [npstreams package](https://pypi.org/pypi/npstreams).
Interactive exploration of ultrafast electron diffraction data with the [iris-ued package](https://pypi.org/project/iris-ued/).
Crystal structure manipulation (including symmetry-determination) with the [crystals package](https://pypi.org/project/crystals/). (Included
with scikit-ued)
A graphical user interface for the dual-tree complex wavelet transform
baseline-removal routine is available as a [separate package](https://pypi.org/pypi/dtgui).
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.](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. 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](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).
License
-------
scikit-ued is made available under the GPLv3 License. For more details,
see [LICENSE.txt](https://github.com/LaurentRDC/scikit-ued/blob/master/LICENSE.txt).