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PhaseNet
========

Overview
--------

``phasenet`` is the first earthquake picking baseline in the staged PyHazards roadmap and is paired with the synthetic waveform dataset for smoke validation.

At a Glance
-----------

.. grid:: 1 2 4 4
   :gutter: 2
   :class-container: catalog-grid

   .. grid-item-card:: Hazard Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Earthquake

      .. container:: catalog-stat-note

         Public catalog grouping used for this model.

   .. grid-item-card:: Maturity
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         Implemented

      .. container:: catalog-stat-note

         Catalog maturity label used on the index page.

   .. grid-item-card:: Tasks
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         1

      .. container:: catalog-stat-note

         Phase Picking

   .. grid-item-card:: Benchmark Family
      :class-card: catalog-stat-card

      .. container:: catalog-stat-value

         :doc:`Earthquake Benchmark </benchmarks/earthquake_benchmark>`

      .. container:: catalog-stat-note

         Primary benchmark-family link used for compatible evaluation coverage.


Description
-----------

``phasenet`` is the first earthquake picking baseline in the staged PyHazards roadmap and is paired with the synthetic waveform dataset for smoke validation.

This initial adapter focuses on the shared waveform-to-pick interface and does not claim exact reproduction of the original PhaseNet training stack.

Benchmark Compatibility
-----------------------

**Primary benchmark family:** :doc:`Earthquake Benchmark </benchmarks/earthquake_benchmark>`

**Mapped benchmark ecosystems:** :doc:`SeisBench </benchmarks/seisbench>`

External References
-------------------

**Paper:** `PhaseNet: A Deep-Neural-Network-Based Seismic Arrival Time Picking Method <https://arxiv.org/abs/1803.03211>`_ | **Repo:** `Repository <https://github.com/AI4EPS/PhaseNet>`__

Registry Name
-------------

Primary entrypoint: ``phasenet``

Supported Tasks
---------------

- Phase Picking

Programmatic Use
----------------

.. code-block:: python

   import torch
   from pyhazards.models import build_model

   model = build_model(
       name="phasenet",
       task="regression",
       in_channels=3,
   )

   picks = model(torch.randn(4, 3, 256))
   print(picks.shape)

Notes
-----

- Outputs are P- and S-arrival sample indices in the current smoke-test adapter.