![lint workflow](https://github.com/noaa-ocs-modeling/OCSMesh/actions/workflows/pylint.yml/badge.svg?branch=main)
![fnc workflow](https://github.com/noaa-ocs-modeling/OCSMesh/actions/workflows/functional_test.yml/badge.svg?branch=main)
![fnc2 workflow](https://github.com/noaa-ocs-modeling/OCSMesh/actions/workflows/functional_test_2.yml/badge.svg?branch=main)

## OCSMesh
OCSMesh is a Python package for processing DEM data into georeferenced
unstructured meshes using different meshing engine libraries.

### Installation
Two ways of installing OCSMesh are described below:

#### Using `conda`
The recommended way to setup the environment for installing OCSMesh is to
use [`conda`](https://docs.conda.io/en/latest/miniconda.html#linux-installers)
with the `environment.yml` file provided in the repo to install
required libraries.

You need to make sure you've installed the mesh engine you'd like to
use (e.g., Triangle or Gmsh).

First you need to download the `environment.yml` file.
```
wget https://raw.githubusercontent.com/noaa-ocs-modeling/OCSMesh/main/environment.yml

conda env create -f environment.yml -n your-env-name
conda activate your-env-name

pip install ocsmesh
```

#### From GitHub repo
You need to make sure you've installed the mesh engine you'd like to
use (e.g., Triangle or Gmsh).

OCSMesh can be installed from the GitHub repository as follows:
```
git clone https://github.com/noaa-ocs-modeling/ocsmesh
cd ocsmesh
pip install .[all]
```

#### Requirements
* 3.10 <= Python
* CMake 
* C/C++ compilers

## How to Cite
```
Title : OCSMesh: a data-driven automated unstructured mesh generation software for coastal ocean modeling
Personal Author(s) : Mani, Soroosh;Calzada, Jaime R.;Moghimi, Saeed;Zhang, Y. Joseph;Myers, Edward;Pe’eri, Shachak;
Corporate Authors(s) : Coast Survey Development Laboratory (U.S.)
Published Date : 2021
Series : NOAA Technical Memorandum NOS CS ; 47
DOI : https://doi.org/10.25923/csba-m072
```
```
Title : OCSMesh and an end-to-end workflow for fully automatic mesh generation with application to compound flood studies
Personal Author(s) : Cassalho, Felicio;Mani, Soroosh;Ye, Fei;Zhang, Y. Joseph;Moghimi, Saeed;
Published Date : Pre-print(2025)
DOI : http://dx.doi.org/10.2139/ssrn.5226658
```

## Disclaimer
This repository is a scientific product and is not official communication of the National Oceanic and Atmospheric Administration, or the United States Department of Commerce. All NOAA GitHub project code is provided on an "as is" basis and the user assumes responsibility for its use. Any claims against the Department of Commerce or Department of Commerce bureaus stemming from the use of this GitHub project will be governed by all applicable Federal law. Any reference to specific commercial products, processes, or services by service mark, trademark, manufacturer, or otherwise, does not constitute or imply their endorsement, recommendation or favoring by the Department of Commerce. The Department of Commerce seal and logo, or the seal and logo of a DOC bureau, shall not be used in any manner to imply endorsement of any commercial product or activity by DOC or the United States Government.
