erlab 3.0.0

Python package for ARPES data analysis and visualization.

ERLabPy

A library that provides a set of tools and utilities to handle, manipulate, and visualize data from condensed matter physics experiments, with a focus on angle-resolved photoemission spectroscopy (ARPES).

ERLabPy is built on top of the popular scientific computing libraries numpy, scipy, and xarray, and is designed to be easy to use and integrate with existing scientific Python workflows so that you can quickly get started with your data analysis. The package is still under development, so if you have any questions or suggestions, please feel free to contact us. We hope you find ERLabPy useful for your research!

ERLabPy is developed and maintained by the electronic structure research laboratory at Korea Advanced Institute of Science and Technology (KAIST).

Features

• Data Loading: A flexible and extensible data loading system is included, capable of handling various data formats.
• Data Manipulation: A set of tools for manipulating and transforming data, including interpolation, masking and symmetrization is provided.
• Plotting: ERLabPy provides many different plotting functions for visualizing image data, including 2D and 3D plots. Publication-quality plots can be generated with minimal effort.
• Fitting: Several functions and models are implemented for fitting various types of data, including broadened Fermi-Dirac distributions, momentum distribution curves (MDCs), and energy distribution curves (EDCs).
• Interactive Data Visualization: ERLabPy includes many interactive plotting routines that resemble panels in Igor Pro that are very responsive and easy to use. See screenshots below.
• Active Development: ERLabPy is actively developed and maintained, with new features and improvements being added regularly.

Screenshots

Most interactive windows support dark mode. Viewing this page from a supported browser with dark mode enabled will show the dark mode screenshots.

Getting Started

To get started, see installation instructions.

Documentation

The full documentation for ERLabPy is available on Read the Docs.

Contributing

ERLabPy is an open-source project and we welcome contributions from the community. If you find any bugs, issues, or have any suggestions, please open an issue here.

If you have any questions or need help with using ERLabPy, please feel free to ask on the Discussions page.

If you would like to add a new feature or fix a bug yourself, we would love to have your contribution. Feel free to fork the repository and submit a pull request with your changes.

For more information on contributing, see our Contributing page.

License

This project is licensed under the terms of the GPL-3.0 License.