SeisBench¶
Synthetic-backed waveform picking adapter aligned to the SeisBench ecosystem.
Overview¶
SeisBench is the public waveform adapter used by PyHazards for the earthquake picking path.
The current implementation is synthetic-backed, but it preserves the picking task shape, labels, and metrics expected by the shared earthquake evaluator.
At a Glance¶
Provider |
SeisBench ecosystem surfaced through a PyHazards adapter |
|---|---|
Hazard Family |
Earthquake |
Source Role |
Waveform Benchmark |
Coverage |
Benchmark-aligned earthquake phase-picking samples |
Geometry |
Multichannel waveform windows |
Spatial Resolution |
Benchmark-defined waveform channels and sample windows |
Temporal Resolution |
Short waveform windows with phase-pick targets |
Update Cadence |
Generated locally for smoke and benchmark-alignment runs |
Period of Record |
Synthetic-backed benchmark adapter |
Formats |
PyTorch tensors via the dataset registry |
Registry Entry |
|
Data Characteristics¶
Multichannel waveform windows paired with P- and S-arrival sample targets.
Registry-backed benchmark adapter rather than a raw external waveform ingestion path.
Intended for phase-picking validation and smoke tests.
Typical Use Cases¶
PhaseNet and EQNet smoke tests.
Shared earthquake benchmark runs on picking tasks.
Regression checks for waveform-based seismic models.
Access¶
Use the links below to access the upstream source or its public documentation.
PyHazards Usage¶
Use this adapter when you want the public SeisBench-aligned waveform surface exposed by the earthquake benchmark.
Registry Workflow¶
Primary dataset name: seisbench_waveforms
from pyhazards.datasets import load_dataset
data = load_dataset(
"seisbench_waveforms",
micro=True,
channels=3,
length=256,
).load()
train = data.get_split("train")
print(train.inputs.shape, train.targets.shape)
Inspection Workflow¶
This dataset is currently surfaced as a registry-backed benchmark adapter, so there is no standalone inspection CLI documented for it.
Notes¶
This is a synthetic-backed benchmark adapter rather than a full SeisBench ingestion pipeline.