Metadata-Version: 2.1
Name: pyxem
Version: 0.9.2
Summary: Crystallographic Diffraction Microscopy in Python.
Home-page: https://github.com/pyxem/pyxem
Author: Duncan Johnstone
Author-email: dnj23@cam.ac.uk
License: GPLv3
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Development Status :: 4 - Beta
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: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Physics
Requires-Dist: scikit-image (>=0.15.0)
Requires-Dist: matplotlib (>=3.1.1)
Requires-Dist: scikit-learn (>=0.19)
Requires-Dist: hyperspy (>=1.5.2)
Requires-Dist: diffsims

|Travis|_ |AppVeyor|_ |Coveralls|_ |pypi_version|_  |doi|_

.. |Travis| image:: https://travis-ci.org/pyxem/pyxem.svg?branch=master
.. _Travis: https://travis-ci.org/pyxem/pyxem

.. |AppVeyor| image:: https://ci.appveyor.com/api/projects/status/github/pyxem/pyxem?svg=true&branch=master
.. _AppVeyor: https://ci.appveyor.com/project/dnjohnstone/pyxem/branch/master

.. |Coveralls| image:: https://coveralls.io/repos/github/pyxem/pyxem/badge.svg?branch=master
.. _Coveralls: https://coveralls.io/github/pyxem/pyxem?branch=master

.. |pypi_version| image:: http://img.shields.io/pypi/v/pyxem.svg?style=flat
.. _pypi_version: https://pypi.python.org/pypi/pyxem

.. |doi| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.2649351.svg
.. _doi: https://doi.org/10.5281/zenodo.2649351


pyXem is an open-source python library for crystallographic diffraction microscopy.

The package defines objects and functions for the analysis of numerous diffraction patterns and has been primarily developed as a platform for hybrid diffraction-microscopy based on 4D scanning diffraction microscopy data in which a 2D diffraction pattern is recorded at every position in a 2D scan of a specimen.

**Installation instructions, documentation and tutorial examples are available** `here <https://pyxem.github.io/pyxem-website>`__ .

If analysis using pyXem forms a part of published work please cite the DOI at the top of this page.

pyXem is released under the GPL v3 license.


