Skip to content
/ rompy Public
forked from rom-py/rompy

Relocatable Ocean Modelling in PYthon (rompy) combines templated cookie-cutter model configuration with various xarray extensions to assist in the setup and evaluation of coastal ocean model

License

Notifications You must be signed in to change notification settings

pbranson/rompy

This branch is 2 commits ahead of, 193 commits behind rom-py/rompy:main.

Folders and files

NameName
Last commit message
Last commit date

Latest commit

Branson, Paul (Environment, IOMRC Crawley)Branson, Paul (Environment, IOMRC Crawley)
Branson, Paul (Environment, IOMRC Crawley)
and
Branson, Paul (Environment, IOMRC Crawley)
Sep 12, 2024
42fc21a · Sep 12, 2024
Jul 22, 2024
Jan 19, 2023
Sep 5, 2024
Jul 22, 2024
Sep 12, 2024
Apr 23, 2021
Aug 29, 2024
Feb 9, 2021
Feb 9, 2021
Feb 9, 2021
Sep 19, 2023
Feb 9, 2021
Jul 3, 2023
Feb 9, 2021
Jun 17, 2023
Sep 12, 2024
Feb 9, 2021
Sep 1, 2024
Feb 9, 2021
Feb 9, 2021

Repository files navigation

title
Relocatable Ocean Modelling in PYthon (rompy)

GitHub Pages

Introduction

Relocatable Ocean Modelling in PYthon (rompy) combines templated cookie-cutter model configuration with various xarray extensions to assist in the setup and evaluation of coastal ocean models, and is intended to simplify their configuration, execution and analysis. This repository also includes Jupyter notebooks that provide examples to illustrate the use of rompy code, create visualisations and provide inline documentation. Currently rompy implements one model class for the SWAN wave model developed by Delft University of Technology. Work is underway on a lightweight wrapper for SCHISM and XBeach.

Documentation

See https://rom-py.github.io/rompy/

About

Relocatable Ocean Modelling in PYthon (rompy) combines templated cookie-cutter model configuration with various xarray extensions to assist in the setup and evaluation of coastal ocean model

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Jupyter Notebook 96.3%
  • Python 3.7%