ERLabPy

ERLab

Extensible and Reproducible Library for the Analysis of Band structures

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erlab provides tools to handle, manipulate, and visualize multidimensional array-like data, with a focus on angle-resolved photoemission spectroscopy (ARPES) experiments.

Key elements are seamlessly integrated with popular scientific Python workflows. A fast native graphical user interface is provided for data exploration and manipulation, allowing users to get started quickly without needing to write code. The library is designed to be flexible and extensible, making it suitable for a wide range of data analysis tasks.

Features

  • Data Loading: Flexible system for various data formats.
  • Data Manipulation: Tools for interpolation, masking, symmetrization, and more.
  • Plotting: Functions for 2D and 3D publication-quality plots.
  • Fitting: Functions for curve fitting, including Fermi-Dirac distributions, MDCs, EDCs, and more.
  • Interactive Visualization: Responsive plotting routines similar to Igor Pro.

Getting Started

Start with the Getting Started guide.

Documentation

Full documentation is available on Read the Docs.

Gallery

Interactive windows support dark mode.

ImageTool in action. Interactive momentum conversion tool. Interactive curve fitting tool. ImageTool manager window. Data explorer window. Periodic table window.

Contributing

We welcome contributions. Report issues to the issue tracker. For questions, visit the Discussions page. To contribute, fork the repository and submit a pull request. See our Contributing page for more information.

License

Licensed under the GPL-3.0 License.

Cite this software

DOI

If you use erlab in your research, citation is appreciated! Citation information for each package version is available on Zenodo.

Project links

Data verified by PyPI on Aug 6, 2026
Data provided by the project maintainers, verified at the time the release was uploaded to PyPI.

Key dates

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  • Released:
Latest release

1 maintainer

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Avatar for kmnhan from gravatar.com kmnhan

Credits

Author: Kimoon Higashihira Han

GitHub Statistics

Data verified by PyPI on Aug 6, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License expression

GPL-3.0-or-later
View SPDX License List

Requires

Python >=3.11

Provides Extra

complete io misc perf viz

Tags

ARPES Condensed Matter Physics

Classifiers

Report project as malware

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