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  pyCSEP: A Python Toolkit for Earthquake Forecast Developers

Savran, W. H., Bayona, J. A., Iturrieta, P. C., Khawaja, M. A., Bao, H., Bayliss, K., Herrmann, M., Schorlemmer, D., Maechling, P. J., Werner, M. J. (2022): pyCSEP: A Python Toolkit for Earthquake Forecast Developers. - Seismological Research Letters, 93, 2858-2870.
https://doi.org/10.1785/0220220033

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 Creators:
Savran, William H.1, Author
Bayona, José A.1, Author
Iturrieta, Pablo Cristián2, Author              
Khawaja, Muhammad Asim3, Author              
Bao, Han1, Author
Bayliss, Kirsty1, Author
Herrmann, Marcus1, Author
Schorlemmer, Danijel2, Author              
Maechling, Philip J.1, Author
Werner, Maximilian J.1, Author
Affiliations:
1External Organizations, ou_persistent22              
22.6 Seismic Hazard and Risk Dynamics, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146032              
32.1 Physics of Earthquakes and Volcanoes, 2.0 Geophysics, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum, ou_146029              

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 Abstract: 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 re‐create the figures published in this article. We recommend that interested readers work through the reproducibility package alongside this article. By providing useful tools to earthquake forecast modelers and facilitating an open‐source software community, we hope to broaden the impact of the CSEP and further promote earthquake forecasting research.

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Language(s): eng - English
 Dates: 2022-07-272022
 Publication Status: Finally published
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 Identifiers: DOI: 10.1785/0220220033
GFZPOF: p4 T3 Restless Earth
OATYPE: Green Open Access
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Title: Seismological Research Letters
Source Genre: Journal, SCI, Scopus
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Pages: - Volume / Issue: 93 Sequence Number: - Start / End Page: 2858 - 2870 Identifier: CoNE: https://gfzpublic.gfz-potsdam.de/cone/journals/resource/journals447
Publisher: Seismological Society of America (SSA)