Simplex noise has been developed by Ken Perlin, the inventor of perlin noise, in order to address some of the shortcomings he saw in perlin noise. Compared to perlin noise, simplex noise has lower computational complexity, making it feasable for dimensions above 3 and has no directional artifacts.

noise_simplex(
dim,
frequency = 0.01,
interpolator = "quintic",
fractal = "fbm",
octaves = 3,
lacunarity = 2,
gain = 0.5,
pertubation = "none",
pertubation_amplitude = 1
)

gen_simplex(x, y = NULL, z = NULL, t = NULL, frequency = 1, seed = NULL, ...)

## Arguments

dim The dimensions (height, width, (and depth, (and time))) of the noise to be generated. The length determines the dimensionality of the noise. Determines the granularity of the features in the noise. How should values between sampled points be calculated? Either 'linear', 'hermite', or 'quintic' (default), ranging from lowest to highest quality. The fractal type to use. Either 'none', 'fbm' (default), 'billow', or 'rigid-multi'. It is suggested that you experiment with the different types to get a feel for how they behaves. The number of noise layers used to create the fractal noise. Ignored if fractal = 'none'. Defaults to 3. The frequency multiplier between successive noise layers when building fractal noise. Ignored if fractal = 'none'. Defaults to 2. The relative strength between successive noise layers when building fractal noise. Ignored if fractal = 'none'. Defaults to 0.5. The pertubation to use. Either 'none' (default), 'normal', or 'fractal'. Defines the displacement (warping) of the noise, with 'normal' giving a smooth warping and 'fractal' giving a more eratic warping. The maximal pertubation distance from the origin. Ignored if pertubation = 'none'. Defaults to 1. Coordinates to get noise value from The seed to use for the noise. If NULL a random seed will be used ignored

## Value

For noise_simplex() a matrix if length(dim) == 2 or an array if length(dim) >= 3. For gen_simplex() a numeric vector matching the length of the input.

Ken Perlin, (2001) Noise hardware. In Real-Time Shading SIGGRAPH Course Notes, Olano M., (Ed.)

## Examples

# Basic use
noise <- noise_simplex(c(100, 100))

plot(as.raster(normalise(noise))) # Using the generator
grid <- long_grid(seq(1, 10, length.out = 1000), seq(1, 10, length.out = 1000))
grid$noise <- gen_simplex(grid$x, grid\$y)
plot(grid, noise) 