.. This file is generated by scripts/render_dataset_docs.py. Do not edit by hand. 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 ----------- .. list-table:: :widths: 28 72 :stub-columns: 1 * - 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 - ``seisbench_waveforms`` 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. - `SeisBench paper `_ - `SeisBench repository `_ 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`` .. code-block:: python 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) Related Coverage ~~~~~~~~~~~~~~~~ **Benchmarks:** :doc:`Earthquake Benchmark `, :doc:`SeisBench ` **Representative Models:** :doc:`PhaseNet `, :doc:`EQNet ` 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. Reference --------- - `SeisBench - A Toolbox for Machine Learning in Seismology `_ (`repo `__).