WaLSAtools – Wave Analysis Tools

WaLSAtools is an open-source library for fundamental and advanced wave analysis in 1D signals, images, and multi-dimensional datasets. Designed as a one-stop resource, it empowers researchers across disciplines to extract insights from oscillatory phenomena. WaLSAtools is envisioned as a community-driven starting point — inviting collaboration to refine techniques, develop new methods, and advance discoveries wherever waves and fluctuations play a fundamental role. It encourages transparent, reproducible science by providing validated techniques, detailed documentation, and worked examples.

It currently provides a comprehensive set of analysis techniques, including:

• Fast Fourier Transform (FFT)
• Wavelet Analysis
• Lomb-Scargle Periodogram
• Welch Power Spectral Density
• Empirical Mode Decomposition (EMD)
• Hilbert and Hilbert-Huang Transforms
• k-ω (k-omega) Analysis
• Proper Orthogonal Decomposition (POD)
• Cross-Spectral Analysis

WaLSAtools features an interactive interface for both Python terminals and Jupyter notebooks, simplifying the wave analysis workflow.

For full documentation, see https://WaLSA.tools.

Installation

We strongly recommend installing WaLSAtools inside a new virtual environment to avoid dependency conflicts, especially with pre-installed packages.

For a full setup guide, see the Beginner-Friendly Guide.

Install via PyPI

pip install --upgrade pip
pip install WaLSAtools

Install from Source (GitHub)

git clone https://github.com/WaLSAteam/WaLSAtools.git
cd WaLSAtools/codes/python/
pip install .

For detailed instructions and troubleshooting tips, refer to:

• Installation Guide
• Troubleshooting

Interactive Usage

After installing, launch the interactive interface by running:

from WaLSAtools import WaLSAtools
WaLSAtools

This will open an interactive menu where you can:

• Select an analysis category.
• Choose your data type (1D or 3D).
• Pick an analysis method (FFT, wavelet, EMD, k-omega, POD, etc.).
• View customised calling sequences and parameter hints.

Interactive usage is supported both in standard Python terminals and Jupyter notebooks.

Requirements

WaLSAtools requires Python ≥ 3.8 and automatically installs the following core dependencies:

astropy, IPython, ipywidgets, matplotlib, numba, numpy, pyFFTW, scipy, setuptools, scikit-image, tqdm.

All dependencies are handled automatically during installation.

License

WaLSAtools is licensed under the Apache License, Version 2.0.

Citation

If you use WaLSAtools in your research, please cite:

Jafarzadeh, S., Jess, D. B., Stangalini, M., et al. 2025, Nature Reviews Methods Primers, 5, 21
https://www.nature.com/articles/s43586-025-00392-0

Zenodo DOI: 10.5281/zenodo.14978610

Contributing

We welcome contributions, suggestions, and feedback.

Please check the Contribution Guide, or join our discussions via GitHub Discussions.