[](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml)
[](https://coveralls.io/github/sandialabs/WecOptTool?branch=main)
# WecOptTool
The Wave Energy Converter Design Optimization Toolbox (WecOptTool) allows users to perform wave energy converter (WEC) device design optimization studies with constrained optimal control.
**NOTE:** If you are looking for the WecOptTool code used in previous published work (MATLAB version) please see [WecOptTool-MATLAB](https://github.com/SNL-WaterPower/WecOptTool-MATLAB).
## Project Information
Refer to [WecOptTool documentation](https://sandialabs.github.io/WecOptTool/) for more information, including project overview, tutorials, theory, and API documentation.
## Getting started
WecOptTool requires Python >= 3.8. Python 3.9 & 3.10 are supported.
It is strongly recommended you create a dedicated virtual environment (e.g., using `conda`, `venv`, etc.) before installing `wecopttool`.
**Option 1** - using `Conda`:
```bash
conda install -c conda-forge wecopttool
```
**Option 2** - using `pip` (requires Fortran compilers on your system):
```bash
pip install wecopttool
```
This approach is not recommended for Windows users since compiling `capytaine` on Windows requires [extra steps](https://github.com/capytaine/capytaine/issues/115).
**Geometry module and tutorials**
To use our geometry examples, including for running the tutorials, you will need to install some additional dependencies.
For the tutorials you will also need to install `jupyter`.
```bash
pip install wecopttool[geometry] jupyter
```
or on a Mac (`Zsh` shell)
```bash
pip install wecopttool\[geometry] jupyter
```
## Tutorials
The tutorials can be found in the `examples` directory and are written as [Jupyter Notebooks](https://jupyter.org/).
To run the tutorials, first download the notebook files and then, from the directory containing the notebooks, run `jupyter notebook`.
Using `git` to obtain the notebooks this can be done by running
```bash
git clone https://github.com/sandialabs/WecOptTool.git
cd WecOptTool/examples
jupyter notebook
```
## Getting help
To report bugs, use WecOptTool's [issues page](https://github.com/sandialabs/WecOptTool/issues).
For general discussion, use WecOptTool's [discussion page](https://github.com/sandialabs/WecOptTool/discussions)
## Contributing
If you are interested in contributing to WecOptTool, see our [contribution guidelines](https://github.com/sandialabs/WecOptTool/blob/main/.github/CONTRIBUTING.md).
Raw data
{
"_id": null,
"home_page": "",
"name": "wecopttool",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.8",
"maintainer_email": "",
"keywords": "",
"author": "Sandia National Laboratories",
"author_email": "",
"download_url": "https://files.pythonhosted.org/packages/68/7a/9f6971e1276264fb130bdafd9f5ddda2deda5415e2efe8f5623eb7a3621a/wecopttool-2.6.0.tar.gz",
"platform": null,
"description": "[](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml)\n[](https://coveralls.io/github/sandialabs/WecOptTool?branch=main)\n\n# WecOptTool\nThe Wave Energy Converter Design Optimization Toolbox (WecOptTool) allows users to perform wave energy converter (WEC) device design optimization studies with constrained optimal control.\n\n**NOTE:** If you are looking for the WecOptTool code used in previous published work (MATLAB version) please see [WecOptTool-MATLAB](https://github.com/SNL-WaterPower/WecOptTool-MATLAB).\n\n## Project Information\nRefer to [WecOptTool documentation](https://sandialabs.github.io/WecOptTool/) for more information, including project overview, tutorials, theory, and API documentation.\n\n## Getting started\nWecOptTool requires Python >= 3.8. Python 3.9 & 3.10 are supported.\nIt is strongly recommended you create a dedicated virtual environment (e.g., using `conda`, `venv`, etc.) before installing `wecopttool`.\n\n**Option 1** - using `Conda`:\n\n```bash\nconda install -c conda-forge wecopttool\n```\n\n**Option 2** - using `pip` (requires Fortran compilers on your system):\n\n```bash\npip install wecopttool\n```\n\nThis approach is not recommended for Windows users since compiling `capytaine` on Windows requires [extra steps](https://github.com/capytaine/capytaine/issues/115).\n\n**Geometry module and tutorials**\n\nTo use our geometry examples, including for running the tutorials, you will need to install some additional dependencies. \nFor the tutorials you will also need to install `jupyter`. \n\n```bash\npip install wecopttool[geometry] jupyter\n```\n\nor on a Mac (`Zsh` shell)\n\n```bash\npip install wecopttool\\[geometry] jupyter\n```\n\n## Tutorials\nThe tutorials can be found in the `examples` directory and are written as [Jupyter Notebooks](https://jupyter.org/).\nTo run the tutorials, first download the notebook files and then, from the directory containing the notebooks, run `jupyter notebook`.\nUsing `git` to obtain the notebooks this can be done by running\n\n```bash\ngit clone https://github.com/sandialabs/WecOptTool.git\ncd WecOptTool/examples\njupyter notebook\n```\n\n## Getting help\nTo report bugs, use WecOptTool's [issues page](https://github.com/sandialabs/WecOptTool/issues).\nFor general discussion, use WecOptTool's [discussion page](https://github.com/sandialabs/WecOptTool/discussions)\n\n## Contributing\nIf you are interested in contributing to WecOptTool, see our [contribution guidelines](https://github.com/sandialabs/WecOptTool/blob/main/.github/CONTRIBUTING.md).\n",
"bugtrack_url": null,
"license": "GNU General Public License v3 (GPLv3)",
"summary": "WEC Design Optimization Toolbox",
"version": "2.6.0",
"project_urls": {
"Documentation": "https://sandialabs.github.io/WecOptTool/"
},
"split_keywords": [],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "6c1e604fe9ce587b286a6ad0fecd6203927bdf232bdfb35765e2f465b6086db3",
"md5": "d1693e153554ff10b0a51b3744c3bb7b",
"sha256": "3cfc228c240c46ac10af8a36265d77739c3235b12bd122f67e41abe6f1ec2a49"
},
"downloads": -1,
"filename": "wecopttool-2.6.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d1693e153554ff10b0a51b3744c3bb7b",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.8",
"size": 50246,
"upload_time": "2023-07-13T20:54:07",
"upload_time_iso_8601": "2023-07-13T20:54:07.052463Z",
"url": "https://files.pythonhosted.org/packages/6c/1e/604fe9ce587b286a6ad0fecd6203927bdf232bdfb35765e2f465b6086db3/wecopttool-2.6.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "687a9f6971e1276264fb130bdafd9f5ddda2deda5415e2efe8f5623eb7a3621a",
"md5": "cb2fab274e773e32c0ce861803730cb6",
"sha256": "900c081ac22e78a7a3660ce2d9d40020e00bde0a53f701cf2b754234e7d0365e"
},
"downloads": -1,
"filename": "wecopttool-2.6.0.tar.gz",
"has_sig": false,
"md5_digest": "cb2fab274e773e32c0ce861803730cb6",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.8",
"size": 68613,
"upload_time": "2023-07-13T20:54:09",
"upload_time_iso_8601": "2023-07-13T20:54:09.032676Z",
"url": "https://files.pythonhosted.org/packages/68/7a/9f6971e1276264fb130bdafd9f5ddda2deda5415e2efe8f5623eb7a3621a/wecopttool-2.6.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-07-13 20:54:09",
"github": false,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"lcname": "wecopttool"
}
JSON