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https://github.com/williamyang98/3d-cellular-automata
3D Cellular Automata in Browser
https://github.com/williamyang98/3d-cellular-automata
3d-cellular-automata cellular-automata realtime-rendering
Last synced: 7 days ago
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3D Cellular Automata in Browser
- Host: GitHub
- URL: https://github.com/williamyang98/3d-cellular-automata
- Owner: williamyang98
- License: mit
- Created: 2020-05-18T12:21:52.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2024-04-21T14:16:44.000Z (7 months ago)
- Last Synced: 2024-04-22T06:23:21.775Z (7 months ago)
- Topics: 3d-cellular-automata, cellular-automata, realtime-rendering
- Language: JavaScript
- Homepage:
- Size: 13.4 MB
- Stars: 45
- Watchers: 3
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# 3D Cellular Automata
[](https://github.com/williamyang98/3D-Cellular-Automata/actions/workflows/gh-pages-deploy.yml)
[Live Demo](http://williamyang98.github.io/3D-Cellular-Automata) of website here.
[](http://youtu.be/-sCSQcG2hZM "3D Cellular Automata")
This is based on the youtube video by Softology. The article written by them can be found [here](https://softologyblog.wordpress.com/2019/12/28/3d-cellular-automata-3/), and their video linked below.
[](http://youtu.be/dQJ5aEsP6Fs "3D Cellular Automata")
## Explanation
Cellular automata involves updating a 3D grid of cells based on specific rules.
1. Depending on the number of surrounding cells it can either:
- Resurrect a dead cell
- Kill a living cell
2. Cells which have died will decay in multiple steps from alive to dead called the refractory period. Here the cell is:
- Unable to be resurrected
- Unable to be killed
- Gradually goes from alive (1.0) to dead (0.0) in increments
3. We can count the number of surrounding cells differently
- Moore neighbourhood considers all surrounding 26 cells
- Von Neumann neighbourhood considers the directly adjacent 6 cells
Using these rules we can get interesting patterns.
A more detailed explanation can be found [here](https://softologyblog.wordpress.com/2019/12/28/3d-cellular-automata-3/) at Softology's article.
## Instructions
1. Press run to begin the simulation.
2. You can pause, reset, and randomise the simulation.
3. In the rules panel you can change it to a different cellular automata rule in realtime by clicking on them.
4. In the randomiser panel, you can change how the world is populated.
- Radius absolute places a blob in the middle with radius in blocks.
- Radius relative places a blob in the middle with radius as a fraction of maximum radius.
5. To change how the world is rendered you can change the parameters in the graphics panel.
- You can select different colouring schemes.
- Update the shader parameters in realtime.
- To speed up the simulation you can disable rendering and re-enable it later.
6. Use the size controls panel to adjust the width, length and height of the simulation.
- For large sizes this can become very computationally and memory intensive.
- For a 1024x1024x1024 with 1.07 billion cells it will use 4.29GB of VRAM.
- VRAM usage = 4xyz bytes.
- The volume data is stored in two 3D textures with red and green 1 byte channels.
The simulation is computed and rendered using webgl shaders. Therefore having a more powerful graphics card will enable higher simulation speeds.
## Gallery
## Default rules
| | | |
|:---:|:---:|:---:|
| 445 | 678 678 | Amoeba |
| 
| 
| 
|
| Builder 1 | Builder 2 | Clouds 1 |
| 
| 
| 
|
| Crystal Growth 1 | Crystal Growth 2 | Pyroclastic |
| 
| 
| 
|
| Slow Decay | Spikey Growth |
| 
| 
|
## Combining rules
You can also switch between the rules while it is running, which can create interesting patterns.
| | |
|:---:|:---:|
| Crystal Growth 1 to Crystal Growth 2 | 445 to Crystal Growth 1 |
| 
| 
|
## Build instructions
1. Clone the repository and cd into it
2. npm install
3. npm run start