sgsim 1.3.2

Python Package for Simulation and Analysis of Ground Motions

SGSIM: Python Package for Simulation and Analysis of Ground Motions

SGSIM is a Python package that provides two main capabilities:

1. Simulation of earthquake ground motions using a site-compatible stochastic method [1].
2. Processing and analysis of ground motions, including filtering, trimming, and calculating various intensity measures (e.g., PGA, SA, FAS, etc.).

Table of Contents

• Features and Installation
• User Guide
• License
• Contact
• References

Features and Installation

See the Documentation.

Installation

Stable release (recommended):

Install the latest stable version from PyPI:

pip install sgsim

Development version:

To use the latest development version (not guaranteed to be stable), install directly from the GitHub repository:

pip install git+https://github.com/Sajad-Hussaini/sgsim.git

Note: The PyPI version is recommended for most users. The GitHub version may include experimental or untested changes.

User Guide

The full documentation, including examples and the complete API reference, is available at sgsim.readthedocs.io.

License

SGSIM is released under the MIT License.
See the LICENSE file for the full text.

Contact

For any questions, assistance, suggestions, or requests to implement additional Intensity Measures (IMs), please feel free to contact:

S.M. Sajad Hussaini
📧 [e-mail]

Please include "SGSIM" in the subject line for a quicker response.

Support the Project

If you find this package useful, contributions to help maintain and improve it, are always appreciated.

References

Please cite the following references for any formal study:

[1] Primary Reference
BROADBAND STOCHASTIC SIMULATION OF EARTHQUAKE GROUND MOTIONS WITH MULTIPLE STRONG PHASES WITH AN APPLICATION TO THE 2023 KAHRAMANMARAS, TURKEY (TÜRKIYE), EARTHQUAKE
DOI: https://doi.org/10.1177/87552930251331981
(Journal of Earthquake Spectra)

[2] SGSIM Package
SGSIM: Python Package for Simulation and Analysis of Ground Motions
DOI: https://doi.org/10.5281/zenodo.14565922