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pyCSEP: A Python Toolkit For Earthquake Forecast Developers

William H. Savran, Maximilian J. Werner, Danijel Schorlemmer, & Philip J. Maechling

Published January 29, 2022, SCEC Contribution #11017

For government officials and the public to act on real-time forecasts of earthquakes, the seis-mological community needs to develop confidence in the underlying scientific hypotheses and assess models’ predictive skills. The Collaboratory for the Study of Earthquake Predictabil-ity (CSEP) provides the cyberinfrastructure and computational tools to evaluate earthquake forecasts. pyCSEP is a Python package that contains the following modules: (1) earthquake catalog access and processing, (2) data models for earthquake forecasts, (3) statistical tests for evaluating earthquake forecasts, and (4) visualization routines. pyCSEP can evaluate fore-casts expressed as expected rates in space-magnitude bins, and simulation-based forecasts that produce thousands of synthetic seismicity catalogs. Most importantly, pyCSEP contains community-endorsed implementations of statistical tests to evaluate earthquake forecasts –with a goal of embedding model evaluation into the model development process. The toolkit will facilitate integrating new forecasting models into testing centers, as the models can be built to use well defined file formats and standards provided by pyCSEP.

Key Words
open-source software; earthquake forecasting; model evaluation

Savran, W. H., Werner, M. J., Schorlemmer, D., & Maechling, P. J. (2022). pyCSEP: A Python Toolkit For Earthquake Forecast Developers. Journal of Open Source Software, 7(69). doi: 10.21105/joss.03658. https://joss.theoj.org/papers/10.21105/joss.03658

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