TY - JOUR
T1 - pyCSEP
T2 - A Python Toolkit for Earthquake Forecast Developers
AU - Savran, William
AU - Bayona, Jose A
AU - Iturrieta, Pablo
AU - Asim, Khawaja
AU - Bao, Han
AU - Bayliss, Kirsty
AU - Herrmann, Marcus
AU - Schorlemmer, Danijel
AU - Maechling, Philip
AU - Werner, Max
N1 - Publisher Copyright:
© Seismological Society of America.
PY - 2022/7/27
Y1 - 2022/7/27
N2 - 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. pyCSEP is a Python package that contains the following modules: (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 significantly, pyCSEP contains several statistical tests needed to evaluate earthquake forecasts, which can be forecasts expressed as expected earthquake rates in space-magnitude bins or specified as large sets of simulated catalogs (which includes candidate models for governmental operational earthquake forecasting). To showcase how pyCSEP can be used to evaluate earthquake forecasts, we have provided a reproducibility package that contains all the components required to recreate the figures published in this article. We recommend that interested readers work through the reproducibility package alongside this manuscript. By providing useful tools to earthquake forecast modelers and facilitating an open-source software community, we hope to broaden the impact of the Collaboratory for the Study of Earthquake Predictability (CSEP) and further promote earthquake forecasting research.
AB - 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. pyCSEP is a Python package that contains the following modules: (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 significantly, pyCSEP contains several statistical tests needed to evaluate earthquake forecasts, which can be forecasts expressed as expected earthquake rates in space-magnitude bins or specified as large sets of simulated catalogs (which includes candidate models for governmental operational earthquake forecasting). To showcase how pyCSEP can be used to evaluate earthquake forecasts, we have provided a reproducibility package that contains all the components required to recreate the figures published in this article. We recommend that interested readers work through the reproducibility package alongside this manuscript. By providing useful tools to earthquake forecast modelers and facilitating an open-source software community, we hope to broaden the impact of the Collaboratory for the Study of Earthquake Predictability (CSEP) and further promote earthquake forecasting research.
KW - Software development
KW - Reproducibility of results
KW - Earthquake interaction, forecasting, and prediction
KW - Statistical seismology
KW - Probabilistic forecasting
U2 - 10.1785/0220220033
DO - 10.1785/0220220033
M3 - Article (Academic Journal)
SN - 0895-0695
VL - 93
SP - 2858
EP - 2870
JO - Seismological Research Letters
JF - Seismological Research Letters
IS - 5
ER -