wecopttool


Namewecopttool JSON
Version 2.7.0 PyPI version JSON
download
home_pageNone
SummaryWEC Design Optimization Toolbox
upload_time2024-04-01 15:22:30
maintainerNone
docs_urlNone
authorSandia National Laboratories
requires_python>=3.8
licenseGNU General Public License v3 (GPLv3)
keywords
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            [![Test-WecOptTool](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml/badge.svg)](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml)
[![Coverage Status](https://coveralls.io/repos/github/sandialabs/WecOptTool/badge.svg?branch=main)](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
**If you are brand new to Python and/or want detailed installation instructions, [click here](https://github.com/sandialabs/WecOptTool/blob/main/INSTALLATION.md).**

WecOptTool requires Python >= 3.8. Python 3.10 & 3.11 are supported.
It is strongly recommended you create a dedicated virtual environment (e.g., using [`conda`](https://www.anaconda.com/), [`mamba`](https://mamba.readthedocs.io/en/latest/), `venv`, etc.) before installing WecOptTool.

From your dedicated environment, you can install WecOptTool via `conda`, `pip`, or `mamba`:

**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
```

**Option 3** - using `Mamba`:

```bash
mamba install wecopttool
```

**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": null,
    "name": "wecopttool",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.8",
    "maintainer_email": null,
    "keywords": null,
    "author": "Sandia National Laboratories",
    "author_email": null,
    "download_url": "https://files.pythonhosted.org/packages/dc/e5/246ec2cc7746544d0d3fd82c066440802da83dc730ba6c5d67099ba13c23/wecopttool-2.7.0.tar.gz",
    "platform": null,
    "description": "[![Test-WecOptTool](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml/badge.svg)](https://github.com/sandialabs/WecOptTool/actions/workflows/push.yml)\n[![Coverage Status](https://coveralls.io/repos/github/sandialabs/WecOptTool/badge.svg?branch=main)](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\n**If you are brand new to Python and/or want detailed installation instructions, [click here](https://github.com/sandialabs/WecOptTool/blob/main/INSTALLATION.md).**\n\nWecOptTool requires Python >= 3.8. Python 3.10 & 3.11 are supported.\nIt is strongly recommended you create a dedicated virtual environment (e.g., using [`conda`](https://www.anaconda.com/), [`mamba`](https://mamba.readthedocs.io/en/latest/), `venv`, etc.) before installing WecOptTool.\n\nFrom your dedicated environment, you can install WecOptTool via `conda`, `pip`, or `mamba`:\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\n**Option 3** - using `Mamba`:\n\n```bash\nmamba install wecopttool\n```\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": "2.7.0",
    "project_urls": {
        "Documentation": "https://sandialabs.github.io/WecOptTool/"
    },
    "split_keywords": [],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "d4170d54db805e04333d6f74ef4bbfc9b0fc65b06dd32dd01100c853bf6076c5",
                "md5": "6bfafa716dbf6911e89ad5113cde1f93",
                "sha256": "0abc6dd9bf71fbc758ae7efe0de1c658dbcf78019d4db9064cdcfec75a18b31f"
            },
            "downloads": -1,
            "filename": "wecopttool-2.7.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "6bfafa716dbf6911e89ad5113cde1f93",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.8",
            "size": 49629,
            "upload_time": "2024-04-01T15:22:29",
            "upload_time_iso_8601": "2024-04-01T15:22:29.113964Z",
            "url": "https://files.pythonhosted.org/packages/d4/17/0d54db805e04333d6f74ef4bbfc9b0fc65b06dd32dd01100c853bf6076c5/wecopttool-2.7.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "dce5246ec2cc7746544d0d3fd82c066440802da83dc730ba6c5d67099ba13c23",
                "md5": "8fc1416fe3c57cf96422db7caa2bcfc5",
                "sha256": "64613ce9e67271fef629a50a422bc43a502c92c788314c50ceba4e2fe0b76d15"
            },
            "downloads": -1,
            "filename": "wecopttool-2.7.0.tar.gz",
            "has_sig": false,
            "md5_digest": "8fc1416fe3c57cf96422db7caa2bcfc5",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.8",
            "size": 68580,
            "upload_time": "2024-04-01T15:22:30",
            "upload_time_iso_8601": "2024-04-01T15:22:30.908589Z",
            "url": "https://files.pythonhosted.org/packages/dc/e5/246ec2cc7746544d0d3fd82c066440802da83dc730ba6c5d67099ba13c23/wecopttool-2.7.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-04-01 15:22:30",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "wecopttool"
}
        
Elapsed time: 0.19174s