用于同相轴检测和地震属性计算的ObsPy库：为自动分析准备波形
An ObsPy library for event detection and seismic attribute calculation: preparing waveforms for automated analysis
摘要：
我们对观测地震学obspy软件包进行了扩展，以提供一个针对非地震源地震信号处理的精简工具，特别是来自冰川和山体滑坡等变形系统的地震信号。该地震属性库提供以下功能：（1）下载和/或预处理地震波形数据;（2）使用来自一个或多个地震仪的多分量信号来检测和编目震波迹象;以及（3）计算所识别事件的特性（“属性”/“特征”）。该工作流程由三个主要功能控制，这些功能已经过测试，以确定永久性和非永久性部署的地震仪器所预期的数据类型的广度。所选择的STA/LTA类型（短期平均/长期平均）或其他事件检测算法可以应用于波形和实现的用户定义函数，以计算检测到的事件的任何所需特性。代码是用Python 2/3编写的，可以在GitHub上找到，还有详细的文档和工作示例。
英文摘要：
We have implemented an extension for the observational seismology obspy software package to provide a streamlined tool tailored to the processing of seismic signals from non-earthquake sources, in particular those from deforming systems such as glaciers and landslides. This seismic attributes library provides functionality to: (1) download and/or pre-process seismic waveform data; (2) detect and catalogue seismic events using multi-component signals from one or more seismometers; and (3) calculate characteristics ('attributes'/'features') of the identified events. The workflow is controlled by three main functions that have been tested for the breadth of data types expected from permanent and campaign-deployed seismic instrumentation. A selected STA/LTA-type (short-term average/long-term average), or other, event detection algorithm can be applied to the waveforms and user-defined functions implemented to calculate any required characteristics of the detected events. The code is written in Python 2/3 and is available on GitHub together with detailed documentation and worked examples.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
