perlin-noise 1.5

Python implementation for Perlin Noise with unlimited coordinates space

Smooth random noise generator
read more https://en.wikipedia.org/wiki/Perlin_noise

noise = PerlinNoise(n_dims=2, octaves=3.5, seed=777)
    n_dims : positive int, optional, default = 1
        space dimension
    octaves : positive float, optional, default = 1
        positive number of sub rectangles in each [0, 1] range
    seed : positive int, optional, default = None
        specific seed with which you want to initialize random generator

Usage examples:

import matplotlib.pyplot as plt
from perlin_noise import PerlinNoise

noise = PerlinNoise(n_dims=2, octaves=2)
xpix = 100
ypix = 100
pic = []
for i in range(xpix):
    row = []
    for j in range(ypix):
        row.append(noise([i/xpix, j/ypix]))
    pic.append(row)

plt.imshow(arr, cmap='gray')
plt.show()

import matplotlib.pyplot as plt
from perlin_noise import PerlinNoise

noise1 = PerlinNoise(n_dims=2, octaves=0.5)
noise2 = PerlinNoise(n_dims=2, octaves=1)
noise3 = PerlinNoise(n_dims=2, octaves=2)
noise4 = PerlinNoise(n_dims=2, octaves=4)

xpix = 100
ypix = 100
pic = []
for i in range(xpix):
    row = []
    for j in range(ypix):
        noise_val =         noise1([i/xpix, j/ypix])
        noise_val += 0.5  * noise2([i/xpix, j/ypix])
        noise_val += 0.25 * noise3([i/xpix, j/ypix])
        noise_val += 0.125* noise4([i/xpix, j/ypix])

        row.append(noise_val)
    pic.append(row)

plt.imshow(pic, cmap='gray')
plt.show()