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Python Scripts for Repeating Earthquake Analysis

Authors: Gao, Dawei;

Python Scripts for Repeating Earthquake Analysis

Abstract

This repository provides Python scripts and example input files for the identification and analysis of repeating earthquakes (repeaters), with emphasis on hypocenter-repeaters and centroid-repeaters. It includes tools for hypocenter/centroid-repeater identification, nearest neighbor testing, circular statistics analysis, and rupture similarity index (RSI) analysis. The files included are listed below: RepeaterCatalog.xlsx: Repeater catalog identified using an assumed stress drop of 38 MPa, used for circular statistics analysis and RSI calculation. Input_sequence.xlsx: Example input file for nearest neighbor test (NNT) and hypocenter/centroid-repeater analysis. HypocenterRepeater_Identification.py: Script for identifying hypocenter-repeaters, defined here as co-located large and small earthquake pairs (CLSEPs). CentroidRepeater_Identification.py: Script for centroid-repeater identification. NNT.py: Script for nearest neighbor test (NNT). Circular_Statistics_Analysis_with_MC.py: Script for circular statistics analysis. RSI_analysis_with_MC.py: Script for rupture similarity index (RSI) analysis. These scripts were developed to support the analysis of rupture repeatability and spatial characteristics of repeating earthquakes.

Keywords

Repeating earthquakes

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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Average