Metadata-Version: 2.1
Name: sdnoise
Version: 1.0.0
Summary: A Python wrapper for simplex noise functions with analytical derivatives.
Author-email: Oliver John Hitchcock <ojhitchcock@gmail.com>
License: 
        The MIT License (MIT)
        
        Copyright (c) 2020 c0rp3n
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
        copies or substantial portions of the Software.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
        FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
        
Keywords: simplex,noise,procedural
Platform: any
Description-Content-Type: text/markdown
License-File: LICENSE.md

<h1 align="center">
    PySDNoise
</h1>
<p align="center">
    <strong>A Python wrapper for noise functions with derivatives.</strong>
</p>

Python wrapper for [Stefan Gustavson's](https://github.com/stegu) simplex noise
functions with analytical derivates, which can be found
[here](https://github.com/stegu/perlin-noise).

## Status
*This project is still under active development and has not yet reached a stable
version until v1.0.0 So when using this code currently expect random error and
dragons.*

## Usage
```Python
from sdnoise import sdnoise2

n, dx, dy = sdnoise2(25.52, 30.06)
```

## Download
 - https://github.com/open-terra/pysdnoise

