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) [![DOI badge](https://img.shields.io/badge/DOI-10.1186%2Fs40679--018--0060--y-blue)](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).
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"description": "scikit-ued\n==========\n\n[![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) [![DOI badge](https://img.shields.io/badge/DOI-10.1186%2Fs40679--018--0060--y-blue)](https://doi.org/10.1186/s40679-018-0060-y)\n\nCollection of algorithms and functions for ultrafast electron diffraction. It aims to be a fully-tested package taking advantage of Python's most recent features.\n\nFor examples, see our [tutorials](https://scikit-ued.readthedocs.io/).\n\nAPI Reference\n-------------\n\nThe [API Reference on readthedocs.io](https://scikit-ued.readthedocs.io) provides API-level documentation, as well as tutorials.\n\nInstallation\n------------\n\nscikit-ued is available on PyPI; it can be installed with [pip](https://pip.pypa.io):\n\n python -m pip install scikit-ued\n\nTo also install optional dependencies required to view diffraction images interactively:\n\n python -m pip install scikit-ued[diffshow]\n\nscikit-ued is also available on the conda-forge channel for the [conda package manager](https://conda.io/docs/):\n\n conda config --add channels conda-forge\n conda install scikit-ued\n\nTo install the latest development version from [Github](https://github.com/LaurentRDC/scikit-ued):\n\n python -m pip install git+https://github.com/LaurentRDC/scikit-ued.git\n\nAfter installing scikit-ued you can use it like any other Python module\nas `skued`.\n\nEach version is tested against **Python 3.7+**. If you are using a\ndifferent version, tests can be run using the `pytest` package.\n\nOptional dependencies\n---------------------\n\nFor displaying diffraction images with interactive contrast using the\n`skued.diffshow` function, PyQtGraph is required.\n\nContributing\n------------\n\nIf you want to contribute to `scikit-ued`, take a look at [`CONTRIBUTING.md`](https://github.com/LaurentRDC/scikit-ued/blob/master/CONTRIBUTING.md).\n\nRelated projects\n----------------\n\nStreaming operations on NumPy arrays are available in the [npstreams package](https://pypi.org/pypi/npstreams).\n\nInteractive exploration of ultrafast electron diffraction data with the [iris-ued package](https://pypi.org/project/iris-ued/).\n\nCrystal structure manipulation (including symmetry-determination) with the [crystals package](https://pypi.org/project/crystals/). (Included\nwith scikit-ued)\n\nA graphical user interface for the dual-tree complex wavelet transform\nbaseline-removal routine is available as a [separate package](https://pypi.org/pypi/dtgui).\n\nCitations\n---------\n\nIf you find this software useful, please consider citing the following\npublication:\n\n> L. P. Ren\u00e9 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)\n\nIf you are using the baseline-removal functionality of scikit-ued,\nplease consider citing the following publication:\n\n> L. P. Ren\u00e9 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).\n\n\nSupport / Report Issues\n-----------------------\n\nAll support requests and issue reports should be [filed on Github as an issue](https://github.com/LaurentRDC/scikit-ued/issues).\n\nLicense\n-------\n\nscikit-ued is made available under the GPLv3 License. For more details,\nsee [LICENSE.txt](https://github.com/LaurentRDC/scikit-ued/blob/master/LICENSE.txt).\n",
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