Examples

Below are links to a variety of example workflows help you get started with using SeisBench to optimise your ML workflows.

Dataset basics

An introduction to the SeisBench dataset API.

Model basics

Get orientated with SeisBench models, learning how to load them and deploy to seismic streams.

Generator pipelines

Use the in-built generator functionality in SeisBench to enhance your ML processing workflows.

Deploy ML pickers

Rapidly deploy ML models integrated in SeisBench to seismic streams.

Using DeepDenoiser

Denoising seismic waveform streams with DeepDenoiser in SeisBench.

Picking depth phases and determining earthquake depth

Determining earthquake hypocentral depth using depth phase in SeisBench.

Training ML models on seismic data

Get started with training deep learning routines (PhaseNet) on a benchmark seismic dataset in SeisBench.

Creating a dataset

Learn how to create a dataset in SeisBench, using build-in functions and the obspy FDSN client as data source.

Building an event catalog with GaMMA

Learn how to create an event catalog from raw waveforms and the metadata using SeisBench and the GaMMA associator.

Building an event catalog with PyOcto

Learn how to create an event catalog from raw waveforms and the metadata using SeisBench and the PyOcto associator.