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scikit-ued

version 0.4.7

Collection of algorithms and functions for ultrafast electron diffraction

Download: http://github.com/LaurentRDC/scikit-ued
Homepage: http://scikit-ued.readthedocs.io
PyPI: http://pypi.python.org/pypi/scikit-ued
People: Laurent P. Ren\xe9 de Cotret

Description

scikit-ued
==========

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:target: https://ci.appveyor.com/project/LaurentRDC/scikit-ued
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:alt: PyPI Version

Collection of algorithms and functions for ultrafast electron diffraction.

Getting Started with scikit-ued
-------------------------------

scikit-ued is available on PyPI; it can be installed with `pip <https://pip.pypa.io>`_.::

python -m pip 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

Each version is tested against Python 3.5 and 3.6. If you are using a different version, tests can be run
using the standard library's `unittest` module.

After installing scikit-ued you can use it like any other Python module as :code:`skued`.

Citations
---------

If you are using the :code:`skued.baseline` subpackage, consider citing the following publication:

.. [#] L. P. Ren\xc3\xa9 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.

API Reference
-------------

The `API Reference on readthedocs.io <http://scikit-ued.readthedocs.io>`_ provides API-level documentation.

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 MIT License. For more details, see `LICENSE.txt <https://github.com/LaurentRDC/scikit-ued/blob/master/LICENSE.txt>`_.

Installation

PyPI

You can download the latest distribution from PyPI here: http://pypi.python.org/pypi/scikit-ued

Using pip

You can install scikit-ued for yourself from the terminal by running:

pip install --user scikit-ued

If you want to install it for all users on your machine, do:

pip install scikit-ued
On Linux, do sudo pip install scikit-ued.

If you don't yet have the pip tool, you can get it following these instructions.

This package was discovered in PyPI.