Skip to main content

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

Project description

WMSAN Python Package

DOI

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.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

wmsan-2024.1.3.tar.gz (33.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

wmsan-2024.1.3-py3-none-any.whl (37.6 kB view details)

Uploaded Python 3

File details

Details for the file wmsan-2024.1.3.tar.gz.

File metadata

  • Download URL: wmsan-2024.1.3.tar.gz
  • Upload date:
  • Size: 33.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for wmsan-2024.1.3.tar.gz
Algorithm Hash digest
SHA256 89b1b72997cc616e28649b26c9e5bcf2424f901cd70a41a3737f6b811651960a
MD5 8e7003578b8a1a884d0fa3581bf45777
BLAKE2b-256 c1702db702185d97be714c7a6047364cf606454529eaea7ce462242165025f89

See more details on using hashes here.

File details

Details for the file wmsan-2024.1.3-py3-none-any.whl.

File metadata

  • Download URL: wmsan-2024.1.3-py3-none-any.whl
  • Upload date:
  • Size: 37.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for wmsan-2024.1.3-py3-none-any.whl
Algorithm Hash digest
SHA256 23ef1208ec452c47f87232604e6f8bceb309a5ef48692899652932ceecf11ed7
MD5 c080e95c52c71f545cf3575b9fbc0b6c
BLAKE2b-256 dd5d4241a7fc8332f106d65d0ed34aa1b491f72cb2ae925d1fa44d25766aa215

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page