The RISE WP7 testing group and collaborators, led by Bill Savran from the Southern California Earthquake Center (SCEC), published a research article describing the Python package pyCSEP: a toolkit for earthquake forecast developers. pyCSEP provides open‐source and community-based implementations of useful tools for evaluating probabilistic and simulation-based earthquake forecasts. It also includes earthquake catalogue access and filtering, evaluation methods and visualisation routines.
To showcase how pyCSEP can be used to evaluate earthquake forecasts, the RISE WP7 group has provided a reproducibility package that contains all the components required to re‐create the figures published in their paper about the pyCSEP toolkit. Thus, the accompanying reproducibility package implements the open science strategy of the Collaboratory for the Study of Earthquake Predictability's (CSEP) and provides readers with a worked tutorial of the software.
The Collaboratory for the Study of Earthquake Predictability (CSEP) is an open and global community whose mission is to accelerate earthquake predictability research through rigorous testing of probabilistic earthquake forecast models and prediction algorithms. pyCSEP supports this mission by providing open‐source implementations of useful tools for evaluating earthquake forecasts.
Research article: pyCSEP: A Python Toolkit for Earthquake Forecast Developers
William H. Savran, José A. Bayona, Pablo Iturrieta, Khawaja M. Asim, Han Bao, Kirsty Bayliss, Marcus Herrmann, Danijel Schorlemmer, Philip J. Maechling, Maximilian J. Werner; pyCSEP: A Python Toolkit for Earthquake Forecast Developers. Seismological Research Letters 2022; doi: https://doi.org/10.1785/0220220033
Reproducibility Package for pyCSEP:
Savran, William H., Bayona, José A., Iturrieta, Pablo, Khawaja, Asim M., Bao, Han, Bayliss, Kirsty, Herrmann, Marcus, Danijel Schorlemmer, Maechling, Philip J., & Werner, Maximilian J. (2022). Reproducibility Package for pyCSEP: A Toolkit for Earthquake Forecast Developers (v1.0.0). Zenodo. https://doi.org/10.5281/zenodo.6626265