pyCSEP: A Python Tool-kit for Earthquake Forecast Developers
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 is a software toolkit that provides open-source implementations of useful tools for evaluating earthquake forecasts. pyCSEP contains the following modules for working with probabilistic earthquake forecasts: (1) earthquake catalog access and processing, (2) representations of probabilistic earthquake forecasts, (3) statistical tests for evaluating earthquake forecasts and (4) visualization routines and various other utilities. Most importantly, pyCSEP contains several community-endorsed implementations of statistical tests needed to evaluate earthquake forecasts. pyCSEP can evaluate two types of forecasts: those expressed as expected rates in space-magnitude bins and those specified as sets of simulated catalogs (including candidate models for governmental Operational Earthquake Forecasting). Current efforts include expanding the forecasting class to forecasts defined on quadtree grids, adding evaluation methods such as binary likelihood scores and receiver operating characteristics, including new visualization routines, incorporating a global earthquake reference model and developing a module of earthquake declustering algorithms. We are proud to note that many of these contributions came from members the community. To help new users get familiar with the code and learn the contribution process, we provide several working examples and pages of documentation at https://docs.cseptesting.org. The software can be found on GitHub at https://github.com/SCECCode/pycsep. Our intention is that providing useful tools to earthquake forecast modelers and facilitating an open-source software community will broaden the impact of CSEP, further promote earthquake forecasting research and assist in the development of seismic hazard products.
Session: New Developments in Physics- and Statistics-based Earthquake Forecasting [Poster]
Type: Poster
Room: Evergreen Ballroom
Date: 4/22/2022
Presentation Time: 08:00 AM Pacific
Presenting Author: William H. Savran
Student Presenter: No
Additional Authors
William Savran Presenting Author Corresponding Author wsavran@usc.edu University of Southern California |
Jose Bayona jose.bayona@bristol.ac.uk University of Bristol |
Pablo Iturrieta pciturri@gfz-potsdam.de GFZ Potsdam |
Khawaja Asim khawaja@gfz-potsdam.de GFZ Potsdam |
Han Bao hbrandon@ucla.edu University of California, Los Angeles |
Kirsty Bayliss kirsty.bayliss@ed.ac.uk University of Edinburgh |
Marcus Hermann marcus.herrmann@unina.it University of Naples |
Philip Maechling maechlin@usc.edu University of Southern California |
Maximilian Werner max.werner@bristol.ac.uk University of Bristol |
pyCSEP: A Python Tool-kit for Earthquake Forecast Developers
Category
New Developments in Physics- and Statistics-based Earthquake Forecasting
Description