I wrote two articles on my blog about this project, the first one is about the generation of 2D noise while the second one is about the generation of 3D noise, feel free to read them!
You can find implementations using numba here.
A fast and simple perlin noise generator using numpy.
You can install this package via:
pip install git+https://github.com/skyl4b/perlyn.git
from perlyn import (
generate_fractal_noise,
generate_perlin_noise,
)The function generate_perlin_noise generates a N dimensional texture of Perlin noise. Its parameters are:
shape: shape of the generated array (tuple of N ints)resolution: number of periods of noise to generate along each axis (tuple of N ints)tileable: if the noise should be tileable along each axis (tuple of N bools, defaults to False)- seed : seed / Generator for RNG reproducibility.
Note: shape must be a multiple of resolution in each axis.
The function generate_fractal_noise combines several octaves of Perlin noise to make fractal noise. Its parameters are:
shape: shape of the generated array (tuple of N ints)res: number of periods of noise to generate along each axis (tuple of N 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 N bools)- seed : seed / Generator for RNG reproducibility.
Note: shape must be a multiple of lacunarity^(octaves-1)*resolution in each axis.
Note these snippets require matplotlib.
import matplotlib.pyplot as plt
import numpy as np
from perlyn import (
generate_perlin_noise,
generate_fractal_noise,
)
noise = generate_perlin_noise((256, 256), (8, 8), seed=42)
plt.imshow(noise, cmap='gray', interpolation='lanczos')
plt.colorbar()
noise_fractal = generate_fractal_noise((256, 256), (8, 8), 5, seed=42)
plt.figure()
plt.imshow(noise, cmap='gray', interpolation='lanczos')
plt.colorbar()
plt.show()
import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from perlyn import generate_fractal_noise
noise = generate_fractal_noise(
(32, 256, 256),
(1, 4, 4),
4,
tileable=(True, False, False),
seed=42,
)
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()import matplotlib.pyplot as plt
import matplotlib.animation as animation
import numpy as np
from perlyn import generate_perlin_noise
noise = generate_perlin_noise(
(32, 256, 256), (1, 4, 4), tileable=(True, False, False), seed=42,
)
fig = plt.figure()
plt.axis("off")
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()