Metadata-Version: 2.1
Name: scikit-ued
Version: 2.1.5
Summary: Collection of algorithms and functions for ultrafast electron scattering
Home-page: http://scikit-ued.readthedocs.io
Author: Laurent P. René de Cotret
Author-email: laurent.renedecotret@mail.mcgill.ca
Maintainer: Laurent P. René de Cotret
Maintainer-email: laurent.renedecotret@mail.mcgill.ca
License: GPLv3
Download-URL: http://github.com/LaurentRDC/scikit-ued
Project-URL: Documentation, https://scikit-ued.readthedocs.io/
Project-URL: Source, https://github.com/LaurentRDC/scikit-ued
Description: 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+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 3.7+**. 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).
        
Keywords: ultrafast electron scattering
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Provides-Extra: diffshow
