3. EQcorrscan tutorials¶
Welcome to EQcorrscan - this package is designed to compute earthquake detections using a paralleled matched-filter network cross-correlation routine, and analyse the results.
Before continuing with this tutorial please check that you have installed all the pre-requisite modules, as not all will be installed by the setup.py file. The list of these is in the Introduction section of this documentation.
|bright_lights:||A brightness based template detection routine;|
|template_gen:||A series of routines to generate templates for match-filter detection from continuous or cut data, with pick-times either defined manually, or defined in event files;|
|match_filter:||The main matched-filter routines, this is split into several smaller functions to allow python-based parallel-processing;|
|subspace:||Subspace detection routine based on Harris (2006).|
|lag_calc:||Routines for calculating optimal lag-times for events detected by the match-filter routine, these lags can then be used to define new picks for high accuracy re-locations.|
Some other high-level functions are included in the utils sub-module and are documented here with tutorials:
|mag_calc:||Simple local magnitude calculation and high-precision relative moment calculation using singular-value decomposition.|
|clustering:||Routines for clustering earthquakes based on a range of metircs using agglomorative clustering methods.|
The utils sub-module contains useful, but small functions. These functions are rarely cpu intensive, but perform vital operations, such as reading Seisan s-files (sfile_util), finding peaks in noisy data (findpeaks), converting a seisan database to hypoDD formatted files and computing cross-correlations between detections for HypoDD (a double difference relocation software) (catalog_to_dd), calculating magnitudes (mag_calc), clustering detections (clustering), stacking detections (stacking), making pretty plots (plotting), and processing seismic data in the same way repeatedly using Obspy‘s functionality (pre_processing).
What follows is an expanding set of tutorials that should take you through some of the key functionality of the EQcorrscan package.