A Generator of Multidimensional Noise

Generation of natural looking noise has many application within simulation, procedural generation, and art, to name a few. The 'ambient' package provides an interface to the 'FastNoise' C++ library and allows for efficient generation of perlin, simplex, worley, cubic, value, and white noise with optional perturbation in either 2, 3, or 4 (in case of simplex and white noise) dimensions.

ambient

ambient is a an R package that provides access to the FastNoise C++ library for generating noise. As such it provides fast generation of perlin, value, cubic, and worley noise in 2 and 3 dimensions, as well as simplex and white noise in 2, 3, and 4 dimensions. Further, it provides pattern generators and other utilities that can be used for modifying and working with noise.

Most of the noise patterns can be generated as fractals as well with support for fbm, billow and rigid-multifractal, and can optionally be pertubed.

There’s not much more to it. If you are in need of a noise generator ambient is your friend, if not you probably shouldn’t care.

Installation

ambient can be installed from CRAN using install.packages('ambient'), or you may get the development version from github using devtools:

# install.packages('pak')
pak::pak("thomasp85/ambient")

Examples

ambient provides a direct interface to the FastNoise functions by requesting a matrix/array of noise values, with a range of settings for pertubation and fractals:

library(ambient)
simplex <- noise_simplex(c(500, 500), pertubation = 'normal', 
                         pertubation_amplitude = 40)
plot(as.raster(normalise(simplex)))

much more powerful, however, is the tidy interface that allows full control of how the values should be calculated and combined:

library(dplyr)

long_grid(x = seq(0, 10, length.out = 1000), 
          y = seq(0, 10, length.out = 1000)) %>% 
  mutate(
    x1 = x + gen_simplex(x, y) / 2, 
    y1 = y + gen_simplex(x, y) / 2,
    worley = gen_worley(x, y, value = 'distance', seed = 5),
    worley_frac = fracture(gen_worley, ridged, octaves = 8, x = x, y = y, 
                           value = 'distance', seed = 5),
    full = blend(normalise(worley), normalise(worley_frac), gen_spheres(x1, y1))
  ) %>% 
  plot(full)