v1.2.1 - Compatibility Patch

What's New:

• Restored backward compatibility with Python 3.8 and 3.9 by replacing | operator with typing.Optional.

About this Software:

• A high-performance, JAX-accelerated Python framework designed for Bayesian seismic source inversion and uncertainty quantification. It supports seismic intensity data from Japan (JMA Shindo), USA (MMI), and Europe (EMS-98) for both macroseismic and instrumental observations. It fully accounts for uncertainties in both the measured data and the theoretical model (GMPE) following the approach of Tarantola (2005). By leveraging JAX for massive parallelization, it allows for near-instantaneous evaluation on CPU, GPU, or TPU, making it ideal for both real-time seismology and the analysis of historical earthquakes.
• It is supplemented by a software tool for the reading and querying the SQLite database with a processed subset of the J-SHIS seismic hazard data (NIED). This database is used for automated Vs30 retrieval for sites in Japan without direct measurements. This Software tool is a supplement to SQLite database in https://doi.org/10.5281/zenodo.19379171

Environment & Dependencies:

• Validated for Python 3.12
• JAX, NumPy, Matplotlib, Pandas, Geopandas, SQLAlchemy, requests, shapely, psutil
• Standardized Python source code according to PEP8 guidelines by using Flake8

v1.2 - Europe Patch

What's New:

• Multi-Scale Support: Added regional support for European Macroseismic Scale (EMS-98) specifically calibrated for Switzerland (Cauzzi et al., 2015) and Mediterranean/Italy (Bindi et al., 2011).
• Official Color Schemes: Implemented high-fidelity color palettes following national and international standards: JMA Shindo (2020+), USGS ShakeMap v3.5 (MMI/EMS-98), and the Swiss Seismological Service (SED) standard (EMS-98).

About this Software:

• A high-performance, JAX-accelerated Python framework designed for Bayesian seismic source inversion and uncertainty quantification. It supports seismic intensity data from Japan (JMA Shindo), USA (MMI), and Europe (EMS-98) for both macroseismic and instrumental observations. It fully accounts for uncertainties in both the measured data and the theoretical model (GMPE) following the approach of Tarantola (2005). By leveraging JAX for massive parallelization, it allows for near-instantaneous evaluation on CPU, GPU, or TPU, making it ideal for both real-time seismology and the analysis of historical earthquakes.
• It is supplemented by a software tool for the reading and querying the SQLite database with a processed subset of the J-SHIS seismic hazard data (NIED). This database is used for automated Vs30 retrieval for sites in Japan without direct measurements. This Software tool is a supplement to SQLite database in https://doi.org/10.5281/zenodo.19379171

Environment & Dependencies:

• Validated for Python 3.12
• JAX, NumPy, Matplotlib, Pandas, Geopandas, SQLAlchemy, requests, shapely, psutil
• Standardized Python source code according to PEP8 guidelines by using Flake8

v1.1 - Japan & Global Support

What's New:

• Multi-Scale Support: Added support for Modified Mercalli Intensity (MMI) and European Macroseismic Scale (EMS-98) alongside the JMA Shindo scale, enabling global applicability.
• Modular Architecture: Refactoring of the codebase into specialized modules (geodata.py, constants.py, plotting.py, etc.) for improved maintainability and cleaner integration.
• Robust Data Handling: Enhanced input validation and automated Vs30 retrieval via a dedicated SQL interface.

About this Software:

• A high-performance, JAX-accelerated Python framework designed for Bayesian seismic source inversion and uncertainty quantification. It supports seismic intensity data from Japan (JMA Shindo), USA (MMI), and Europe (EMS-98) for both macroseismic and instrumental observations. It fully accounts for uncertainties in both the measured data and the theoretical model (GMPE) following the approach of Tarantola (2005). By leveraging JAX for massive parallelization, it allows for near-instantaneous evaluation on CPU, GPU, or TPU, making it ideal for both real-time seismology and the analysis of historical earthquakes.
• It is supplemented by a software tool for the reading and querying the SQLite database with a processed subset of the J-SHIS seismic hazard data (NIED). This database is used for automated Vs30 retrieval for sites in Japan without direct measurements. This Software tool is a supplement to SQLite database in https://doi.org/10.5281/zenodo.19379171

Environment & Dependencies:

• Validated for Python 3.12
• JAX, NumPy, Matplotlib, Pandas, Geopandas, SQLAlchemy, requests, shapely, psutil
• Standardized Python source code according to PEP8 guidelines by using Flake8

v1.0 - Initial Release

What's New:

• Initial Release

About this Software:

• A high-performance Python framework designed for Bayesian inversion of earthquake epicenters and moment magnitudes specifically tailored for the Japanese JMA instrumental seismic intensity (Shindo) scale. It fully accounts for uncertainties in both the measured data (seismic intensity) and the theoretical model (GMPE) following Tarantola (2005). By leveraging JAX for massive parallelization, it allows for near-instantaneous evaluation on both CPU and GPU, making it ideal for both real-time modern seismology and the processing of historical earthquakes.
• It is supplemented by a software tool for the reading and querying the SQLite database with a processed subset of the J-SHIS seismic hazard data (NIED). This database is used for automated Vs30 retrieval for sites in Japan without direct measurements. This Software tool is a supplement to SQLite database in https://doi.org/10.5281/zenodo.19379171

Environment & Dependencies:

• Validated for Python 3.12
• JAX, NumPy, Matplotlib, Pandas, Geopandas, SQLAlchemy, requests, shapely, psutil
• Standardized Python source code according to PEP8 guidelines by using Flake8