https://github.com/benmaier/difflimagg
Diffusion-limited aggregation
https://github.com/benmaier/difflimagg
Last synced: 3 months ago
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Diffusion-limited aggregation
- Host: GitHub
- URL: https://github.com/benmaier/difflimagg
- Owner: benmaier
- License: mit
- Created: 2022-11-05T01:01:05.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2023-10-10T14:30:16.000Z (over 1 year ago)
- Last Synced: 2024-10-11T11:08:01.179Z (8 months ago)
- Language: Python
- Size: 31.3 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Code of conduct: CODE_OF_CONDUCT.md
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README
# DiffLimAgg
Diffusion-limited aggregation in 2D. Simulate, analyze, visualize.
```python
import numpy as np
import DiffLimAgg as dla
from DiffLimAgg.anim import animate
walkers = dla.Walkers2D(N=50_000,
dt=0.01,
box=[0,1,0,1],
initial_positions='random',
position_noise_coefficient=0.0001,
velocity_noise_coefficient=.0001,
)
exp = dla.Experiment(walkers,
walker_radius=0.3*np.sqrt(1/50_000)
)
animate(exp)
```
This generates sth like the following animation. Video compression kinda messed it up but somehow I like it.
https://user-images.githubusercontent.com/10728380/204252790-652efe63-30d5-4fdf-911f-7627dfc69ff4.mp4
## Install
pip install ./DiffLimAgg
`DiffLimAgg` was developed and tested for
* Python 3.6
* Python 3.7
* Python 3.8
So far, the package's functionality was tested on Mac OS X and CentOS only.
## Dependencies
`DiffLimAgg` directly depends on the following packages which will be installed by `pip` during the installation process
* numpy>=1.20
* scipy>=1.9
## License
This project is licensed under the [MIT License](https://github.com/benmaier/DiffLimAgg/blob/main/LICENSE).
Note that this excludes any images/pictures/figures shown here or in the documentation.