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Python tool for automation of running and post-processing multiple CFD simulations, generating colour map representing wind comfort categories based on simulation results and historical weather data.

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lampssy/wind-microclimate

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Table of Contents
  1. About The Project
  2. Getting Started
  3. Usage
  4. Roadmap
  5. Contributing
  6. License
  7. Contact
  8. Acknowledgments

About The Project

Product Name Screen Shot

Automated new project setup using GitHub Actions.

GitHub Actions execute:

  • cookiectter for setting up the new repository
  • flake8 and mypy to check code styling
  • pytest for testing
  • tox for running tests in various environments

Steps to set up the project:

  1. Click the big green button Use this template or click here.
  2. Enter a Repository name and click Create repository from template
  3. In the a new repository, complete the project setup by editing the cookiecutter.json file.
  4. Hit cmd + S and then Enter to perform a commit (the commit message doesn't really matter).
  5. Wait for Setup Repository Action to complete.

That's it, easy isn't it?

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Built With

This section should list any major frameworks/libraries used to bootstrap your project. Leave any add-ons/plugins for the acknowledgements section. Here are a few examples.

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Getting Started

This is an example of how you may give instructions on setting up your project locally. To get a local copy up and running follow these simple example steps.

Prerequisites

This is an example of how to list things you need to use the software and how to install them.

  • npm
    npm install npm@latest -g

Installation

Below is an example of how you can instruct your audience on installing and setting up your app. This template doesn't rely on any external dependencies or services.

  1. Get a free API Key at https://example.com
  2. Clone the repo
    git clone https://github.com/your_username_/Project-Name.git
  3. Install NPM packages
    npm install
  4. Enter your API in config.js
    const API_KEY = 'ENTER YOUR API';

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Usage

Use this space to show useful examples of how a project can be used. Additional screenshots, code examples and demos work well in this space. You may also link to more resources.

For more examples, please refer to the Documentation

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Roadmap

  • Add Changelog
  • Add back to top links
  • Add Additional Templates w/ Examples
  • Add "components" document to easily copy & paste sections of the readme
  • Multi-language Support
    • Chinese
    • Spanish

See the open issues for a full list of proposed features (and known issues).

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Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

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License

Distributed under the MIT License. See LICENSE.txt for more information.

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Contact

{{cookiecutter.author}} - {{cookiecutter.email}}

Project Link: https://github.com/{{cookiecutter.user_name}}/{{cookiecutter.repo_name}}

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Acknowledgments

Use this space to list resources you find helpful and would like to give credit to. I've included a few of my favorites to kick things off!

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About

Python tool for automation of running and post-processing multiple CFD simulations, generating colour map representing wind comfort categories based on simulation results and historical weather data.

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