wmsan 2026.0.0

Compute seismic sources of ambient noise using wave model hindcast outputs.

WMSAN Python Package

Description

This package is built to help computation of seismic ambient noise source maps and other products based on the WAVEWATCHIII hindcast output.

Documentation

A detailed documentation is available on this page.

Contents

ww3-source-maps/
|-- LICENSE
|-- pyproject.toml
|-- README.md
|-- mkdocs.yml
|-- docs/
|-- site/
|-- src/
│   └── wmsan/
│       ├── readWW31.py
│       ├── read_hs_p2l.py
│       ├── subfunctions_body_waves.py
│       ├── subfunctions_rayleigh_waves.py
│       └── synthetics.py
│       └── wmsan_to_noisi.py
│       └── temporal_variation.py
│       └── synthetic_CCF.ipynb
│
|-- notebooks/
|   └── body_waves/
│       ├── amplification_coeff.ipynb
│       └── microseismic_sources.ipynb
│       └── synthetic_CCF.ipynb
│       └── temporal_variations.ipynb
│   └── rayleigh_waves/
│       ├── amplification_coeff.ipynb
│       ├── microseismic_sources.ipynb
│       ├── spectrograms.ipynb
│       ├── rayleigh_source.ipynb
│       └── synthetic_CCF.ipynb
│       └── wmsan_to_noisi.ipynb
│       └── temporal_variations.ipynb
|-- data/
│   ├── C.nc
│   ├── cP.nc
│   ├── cS.nc
│   ├── longuet_higgins.txt
│   ├── stations_pair.txt
│   └── ww3.07121700.dpt

• src/ : contains all Python scripts and subfunctions.
• notebooks/ : contains Jupyter Notebooks with detailed examples on how to use this package. Rayleigh waves and body waves are separated.
• data/: contains additional files used in computation.

Installation

PyPI

The package is available on PyPI.

Create an environment and install

• if you use Conda environments:

  conda create --name wmsan
  conda activate wmsan
  python3 -m pip install wmsan
  

  to deactivate your environment:

  conda deactivate
  

• otherwise

  python3 -m venv venv
  source venv/bin/activate
  python3 -m pip install wmsan
  

  to deactivate your environment:

  deactivate
  

From Source

1. Clone the repository

   cd path_to_your_wmsan_directory/
   git clone https://gricad-gitlab.univ-grenoble-alpes.fr/tomasetl/ww3-source-maps.git 
   cd ww3-source-maps/
   

2. Create an environment and install

• if you use Conda environments:

  conda create --name wmsan
  conda activate wmsanj
  pip install .
  

  to deactivate your environment:

  conda deactivate
  

• otherwise

  python3 -m venv venv
  source venv/bin/activate
  python3 -m pip install .
  

  to deactivate your environment:

  deactivate
  

Dependencies

• numpy
• matplotlib
• cartopy
• xarray
• netCDF4
• obspy
• datetime
• scipy
• pandas
• dask
• ipykernel
• pyproj
• h5py
• tqdm
• notebook
• dask
• scikit-learn For noisi only

Where should I start ?

Architecture of WMSAN Python Package

How to Cite WMSAN ?

• Tomasetto, L., Boué, P., Ardhuin, F., Stutzman, E., Xu, Z., De Plaen, R., & Stehly, L. (2024). WMSAN Python Package: From Oceanic Forcing to Synthetic Cross-correlations of Microseismic Noise. EathArXiv.