This repository contains a growing collection of worked, reproducible examples demonstrating how to access and analyse seismic data from the University of Melbourne and partner networks using modern Python-based workflows.
The primary aim is educational and illustrative: to show how data can be accessed, processed, and interpreted, rather than to provide a monolithic analysis framework.
Seismic waveform and metadata from the University of Melbourne network are now available via an FDSN web service. This repository is intended to provide clear, executable examples that demonstrate how to:
- discover stations and waveforms via FDSN
- download and handle waveform data
- apply automated phase picking
- perform simple event-level analyses
These examples are designed to be easily adapted for teaching, training, and exploratory research.
Each exXX/ directory is intended to be a self-contained example, including:
- a Jupyter notebook
- any required waveform, metadata, or auxiliary files
- minimal external dependencies beyond standard Python seismology tools
Example 01 demonstrates a simple end-to-end workflow for a local earthquake, including:
- accessing waveform and station metadata via FDSN
- automated phase picking
- inspection and export of picks
- preliminary event location
The examples primarily rely on standard Python scientific and seismological packages, including:
numpymatplotlibobspyseisbench
Exact imports and setup are documented within each notebook.
This repository is aimed at:
- students learning practical seismological workflows
- researchers new to FDSN-based data access
- collaborators looking for concrete, reproducible examples
The examples are intentionally explicit and verbose, prioritising clarity over conciseness.