Metadata-Version: 2.1
Name: brightwind
Version: 2.0.0
Summary: Scripts for wind resource data processing.
Home-page: https://github.com/brightwind-dev/brightwind.git
Author: Stephen Holleran of BrightWind Ltd
Author-email: stephen@brightwindanalysis.com
License: MIT
Download-URL: https://github.com/brightwind-dev/brightwind/archive/v2.0.0.tar.gz
Description: --------------
        ```
             __         _       __    __           _           __
            / /_  _____(_)___  / /_  / /__      __(_)___  ___ / /
           / __ \/ ___/ / __ \/ __ \/ __/ | /| / / / __ \/ __  /
          / /_/ / /  / / /_/ / / / / /_ | |/ |/ / / / / / /_/ /
         /_.___/_/  /_/\__, /_/ /_/\__/ |__/|__/_/_/ /_/\__,_/
                      /____/
         ```
        --------------
        
        <br>
        
        The brightwind python library aims to **empower wind resource analysts** and establish a common **industry standard toolset**.
        
        <br>
        
        ### Documentation
        
        Documentation on how to get setup and use the library can be found at https://brightwind-dev.github.io/brightwind-docs/
        
        <br>
        
        Example usage is shown below via a Jupyter Notebook.
        <br>
        
        <p>
        
        ![demo_image_1](read_me_1.png)
        ![demo_image_2](read_me_2.png)
        </p>
        
        
        
        
        <br>
        
        ##### Features
        The library provides wind analysts with easy to use tools for working with
        meteorological data. It supports loading of meteorological data, averaging,
        filtering, plotting, correlations, shear analysis, long term adjustments, etc.
        The library can export a resulting long term adjusted tab file to be used in
        other software.
        
        <br>
        
        ##### Benefits
        The key benefits to an open-source library is that it provides complete transparency
        and traceability. Anyone in the industry can review any part of the code and suggest changes,
        thus creating a standardised, validated toolkit for the industry.
        
        By default, during an assessment every manipulation or adjustment made to the wind data is
        contained in a single file. This can easily be reviewed and checked by internal reviewers or,
        as the underlying code is open-sourced, there is no reason why this file cannot be sent to
        3rd parties for review thus increasing the effectiveness of a banks due diligence.
        
        <br>
        
        ##### License
        The library is licensed under the MIT license.
        
        <br>
        
        ---
        ### Installation
        
        The library can be installed by using pip install from the command line (for those that have pip installed).
        
        <br>
        
        ```
        C:\Users\Stephen> pip install brightwind
        ```
        
        <br>
        
        For those that do not already have Python or pip, please follow this tutorial,
        [getting started on Windows](https://brightwind-dev.github.io/brightwind-docs/tutorials/getting_started_on_windows.html),
        to get set up.
        
        <br>
        
        ---
        ### Test datasets
        A test dataset is included in this repository and is used to test functions in the code. The source of the dataset is:
        
        <br>
        
        | Dataset            | Source           | Notes  |
        |:------------------ |:-------------|:-----|
        | Demo data          | Anonymous | A modified 2 year met mast dataset in various logger formats along with associated 18-yr MERRA-2 data. |
        
        <br>
        
        ---
        ### Contributing
        If you wish to be involved or find out more please contact stephen@brightwindanalysis.com.
        
        More information can be found in the [contributing.md](https://github.com/brightwind-dev/brightwind/blob/master/contributing.md) section of the website.
        
        <br>
        
Keywords: BRIGHT,WIND,RESOURCE,DATA,ANALYSTS,PROCESSING,WASP,ROSE,WINDFARMER,OPENWIND,WIND PRO,WINDOGRAPHER
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: License :: OSI Approved :: MIT License
Description-Content-Type: text/markdown
