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

Project description

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 
│   └── 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
        conda install pip
        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/
  1. Create an environment and install
  • if you use Conda environments:
conda create --name wmsan 
conda activate wmsan
conda install pip
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

Where should I start ?

Table representing the differrent paths to Jupyter Notebooks examples and where to find what you wish to compute.

Architecture of WMSAN Python Package

Scheme showing the different codes and Notebooks present in this repository and how they connect.

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