Metadata-Version: 2.1
Name: RHEED-Learn
Version: 0.1.0
Summary: RHEED-Learn is a Python package for analyzing and visualizing Reflection High-Energy Electron Diffraction (RHEED) data, designed to streamline the processing of thin-film growth data and assist with materials characterization.
Home-page: https://github.com/pyscaffold/pyscaffold/
Author: Yichen Guo
Author-email: yig319@lehigh.edu
License: MIT
Project-URL: Documentation, https://pyscaffold.org/
Platform: any
Classifier: Development Status :: 4 - Beta
Classifier: Programming Language :: Python
Description-Content-Type: text/x-rst; charset=UTF-8
License-File: LICENSE.txt
Requires-Dist: importlib-metadata ; python_version < "3.8"
Provides-Extra: testing
Requires-Dist: setuptools ; extra == 'testing'
Requires-Dist: pytest ; extra == 'testing'
Requires-Dist: pytest-cov ; extra == 'testing'

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===========
RHEED-Learn
===========


    RHEED-Learn is a Python package for analyzing and visualizing Reflection High-Energy Electron Diffraction (RHEED) data, designed to streamline the processing of thin-film growth data and assist with materials characterization.


RHEED-Learn is a dedicated Python package for researchers and scientists working with Reflection High-Energy Electron Diffraction (RHEED) data, commonly used in thin-film growth analysis and materials science. The package provides an array of tools to process, visualize, and analyze RHEED data, making it easier to track film growth dynamics and extract meaningful insights from complex diffraction patterns. With capabilities to handle raw RHEED intensity oscillation data, kinematic analysis, and more, RHEED-Learn allows users to better understand growth modes, surface roughness, and lattice structures in various material systems. This package aims to facilitate reproducible research by offering modular functions, supporting customized analyses, and providing integration with other Python data analysis workflows. Ideal for both routine RHEED characterization and advanced studies, RHEED-Learn empowers researchers to push forward in the field of materials synthesis and thin-film research.


.. _pyscaffold-notes:

Note
====

This project has been set up using PyScaffold 4.6. For details and usage
information on PyScaffold see https://pyscaffold.org/.
