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https://github.com/pvigier/perlin-numpy
A fast and simple perlin noise generator using numpy
https://github.com/pvigier/perlin-numpy
noise numpy perlin perlin-noise
Last synced: 8 days ago
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A fast and simple perlin noise generator using numpy
- Host: GitHub
- URL: https://github.com/pvigier/perlin-numpy
- Owner: pvigier
- License: mit
- Created: 2018-05-19T10:00:13.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2024-02-10T21:47:35.000Z (9 months ago)
- Last Synced: 2024-10-09T13:13:31.253Z (28 days ago)
- Topics: noise, numpy, perlin, perlin-noise
- Language: Python
- Homepage: https://pvigier.github.io/2018/06/13/perlin-noise-numpy.html
- Size: 6.19 MB
- Stars: 296
- Watchers: 6
- Forks: 46
- Open Issues: 9
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# perlin-numpy
I wrote two articles on my blog about this project, the [first one](https://pvigier.github.io/2018/06/13/perlin-noise-numpy.html) is about the generation of 2D noise while the [second one](https://pvigier.github.io/2018/11/02/3d-perlin-noise-numpy.html) is about the generation of 3D noise, feel free to read them!
You can find implementations using [numba](https://numba.pydata.org/) [here](https://github.com/pvigier/perlin-numpy/issues/9).
## Description
A fast and simple perlin noise generator using numpy.
## Installation
You can install this package via:
```
pip3 install git+https://github.com/pvigier/perlin-numpy
```
## Usage
```python
from perlin_numpy import (
generate_fractal_noise_2d, generate_fractal_noise_3d,
generate_perlin_noise_2d, generate_perlin_noise_3d
)
```
### 2D noise
The function `generate_perlin_noise_2d` generates a 2D texture of perlin noise. Its parameters are:
* `shape`: shape of the generated array (tuple of 2 ints)
* `res`: number of periods of noise to generate along each axis (tuple of 2 ints)
* `tileable`: if the noise should be tileable along each axis (tuple of 2 bools)
Note: `shape` must be a multiple of `res`
The function `generate_fractal_noise_2d` combines several octaves of 2D perlin noise to make 2D fractal noise. Its parameters are:
* `shape`: shape of the generated array (tuple of 2 ints)
* `res`: number of periods of noise to generate along each axis (tuple of 2 ints)
* `octaves`: number of octaves in the noise (int)
* `persistence`: scaling factor between two octaves (float)
* `lacunarity`: frequency factor between two octaves (float)
* `tileable`: if the noise should be tileable along each axis (tuple of 2 bools)
Note: `shape` must be a multiple of `lacunarity^(octaves-1)*res`
### 3D noise
The function `generate_perlin_noise_3d` generates a 3D texture of perlin noise. Its parameters are:
* `shape`: shape of the generated array (tuple of 3 ints)
* `res`: number of periods of noise to generate along each axis (tuple of 3 ints)
* `tileable`: if the noise should be tileable along each axis (tuple of 3 bools)
Note: `shape` must be a multiple of `res`
The function `generate_fractal_noise_2d` combines several octaves of 3D perlin noise to make 3D fractal noise. Its parameters are:
* `shape`: shape of the generated array (tuple of 3 ints)
* `res`: number of periods of noise to generate along each axis (tuple of 3 ints)
* `octaves`: number of octaves in the noise (int)
* `persistence`: scaling factor between two octaves (float)
* `lacunarity`: frequency factor between two octaves (float)
* `tileable`: if the noise should be tileable along each axis (tuple of 3 bools)
Note: `shape` must be a multiple of `lacunarity^(octaves-1)*res`
## Recipes
Note these snippets require [matplotlib](https://matplotlib.org/).
### 2D Perlin and Fractal Noise
```python
import matplotlib.pyplot as plt
import numpy as np
from perlin_numpy import (
generate_perlin_noise_2d, generate_fractal_noise_2d
)
np.random.seed(0)
noise = generate_perlin_noise_2d((256, 256), (8, 8))
plt.imshow(noise, cmap='gray', interpolation='lanczos')
plt.colorbar()
np.random.seed(0)
noise = generate_fractal_noise_2d((256, 256), (8, 8), 5)
plt.figure()
plt.imshow(noise, cmap='gray', interpolation='lanczos')
plt.colorbar()
plt.show()
```
### 3D Fractal Noise
```python
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from perlin_numpy import generate_fractal_noise_3d
np.random.seed(0)
noise = generate_fractal_noise_3d(
(32, 256, 256), (1, 4, 4), 4, tileable=(True, False, False)
)
fig = plt.figure()
images = [
[plt.imshow(
layer, cmap='gray', interpolation='lanczos', animated=True
)]
for layer in noise
]
animation_3d = animation.ArtistAnimation(fig, images, interval=50, blit=True)
plt.show()
```
### 3D Perlin Noise
```python
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from perlin_numpy import generate_perlin_noise_3d
np.random.seed(0)
noise = generate_perlin_noise_3d(
(32, 256, 256), (1, 4, 4), tileable=(True, False, False)
)
fig = plt.figure()
images = [
[plt.imshow(
layer, cmap='gray', interpolation='lanczos', animated=True
)]
for layer in noise
]
animation_3d = animation.ArtistAnimation(fig, images, interval=50, blit=True)
plt.show()
```
