PyGRT: An integrated, efficient C/Python toolkit for theoretical simulation
in layered half-space media

Chinese Document  |  English Document (no longer maintained)

Features

• Dynamic and static responses (displacement, strain, stress, rotation, and related quantities)
• Surface-wave modal analysis (dispersion curves, eigenfunctions, and related quantities)
• Auxiliary modules (Green's functions, kernels, Lamb problem, Okada solution, and more)
• CLI and Python API (modular grt command-line tool and Python interface)
• Actively maintained — see the documentation for modules and tutorials

Quick Install

Pre-built binaries are available for Linux, macOS, and Windows:

pip install pygrt-kit

Then in Python:

import pygrt

PyGRT also provides the grt CLI. Run grt -h to list available modules, and grt <module> -h (e.g., grt greenfn -h) for module-specific usage.

To use the CLI only (without Python), download the pre-built *.tar.gz archive for your platform from GitHub Releases.

(For conda environments, source builds, and troubleshooting, see the installation guide (Chinese)).

Contact

If you have any questions or suggestions, feel free to reach out:

• Email: zhudengda@mail.iggcas.ac.cn
• GitHub Issues: You can also raise an issue directly on GitHub.

Citation

Since PyGRT has been under continuous maintenance and extension during the peer review, its functions have exceeded the scope described in this paper. For detailed usage of each function, please see the documentation.

Zhu, D., Wang, J., Hao, J., Yao, S., Xu, Y., Xu, T., and Yao, Z. (2025). PyGRT: An Efficient and Integrated Python Package for Computing Synthetic Seismograms in a Layered Half‐Space Model. Seismological Research Letters, 97(3), 2138–2153. doi: 10.1785/0220250057

Zhu, D., Xu, T., Hao, J., and Yao, Z. (2025). A Direct Convergence Method for Computing Synthetic Seismograms for a Layered Half‐Space with Sources and Receivers at Close Depths. Bulletin of the Seismological Society of America, 116(2), 576–588. doi: 10.1785/0120250190

Zhu, D., Xu, T., Hao, J., and Yao, Z. (2026). An Adaptive Strategy for Robust and Efficient Computation of Dispersion Curves in a Layered Half-Space, Bulletin of the Seismological Society of America. doi: doi.org/10.1785/0120260071

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