BEPAD — a benchmark dataset for seismic phase association

A phase associator groups the P and S picks of a seismic network into earthquakes. BEPAD gives thousands of association problems built from real earthquakes and real picks (UTDQuake), with the answer for every pick.

One window (Texas network): (a) earthquakes and stations, (b) every pick at its distance from its earthquake, (c) picks by type. The associator's job is to find which picks belong together.

import bepad

test = bepad.load("test", networks=["tx"], max_windows=20, labels=False)   # 20 Texas test windows
for w in test:                                   # one window = one association problem
    w.picks, w.stations                          # picks (station, P/S, time) and station coordinates
report = bepad.evaluate(predictions, test)       # score your associator

Try it in Colab, nothing to install: get the data · benchmark your associator · train a model.

Share your associator and get on the leaderboard in four commands:

bepad new my-method                                            # template folder
bepad run associators/my-method --split test --out results/my-method
bepad submit results/my-method --code associators/my-method    # opens a Hugging Face pull request

Documentation: https://bepad.readthedocs.io · Data: https://huggingface.co/datasets/ecastillot/BEPAD · Code: https://github.com/ecastillot/BEPAD. Install: pip install bepad (or pip install -e . from this folder; .[dl] for PyTorch, .[build] to rebuild the dataset).

Repository

bepad/            load, evaluate, Associator, leaderboard, torch, plots  (what users need)
bepad/build/      pool, labels, windows, release (how the dataset is built)
configs/          pool.yaml (quality control, split, labels), v0.1.yaml, dev.yaml (scenarios, sizes)
docs/             Read the Docs sources; docs/gallery/ = the code of every figure
associators/      contributed associators, one folder each (pyocto = worked example)
pipeline/         the recipe of a release (SLURM): pool -> release -> baselines (pipeline/README.md)
hf/README.md      Hugging Face dataset card

License and citation

Code: GPL-3.0. Data: the terms of the original providers, as in UTDQuake. Please cite UTDQuake and the network operators of the data you use.