Title:	Generate Multi-Dimensional Open Simplex Noise
Version:	0.0.2
Description:	Generate 2, 3 or 4-dimensional gradient noise. The noise function is comparable to classic Perlin noise, but with less directional artefacts and lower computational overhead. It can have applications procedural generation or (flow fields) simulations.
License:	GPL (≥ 3)
Encoding:	UTF-8
RoxygenNote:	7.3.2
LinkingTo:	cpp11
Depends:	R (≥ 3.5.0)
Suggests:	gifski, knitr, ragg, rmarkdown, testthat (≥ 3.0.0)
Config/testthat/edition:	3
URL:	https://pepijn-devries.github.io/opensimplex2/, https://github.com/pepijn-devries/opensimplex2/
BugReports:	https://github.com/pepijn-devries/opensimplex2/issues
Language:	en-GB
NeedsCompilation:	yes
Packaged:	2026-03-21 00:26:33 UTC; vries171
Author:	Pepijn de Vries [aut, cre], Marco Ciaramella [aut, cph], KdotJPG [aut, cph]
Maintainer:	Pepijn de Vries <pepijn.devries@outlook.com>
Repository:	CRAN
Date/Publication:	2026-03-25 20:50:12 UTC

opensimplex2: Generate Multi-Dimensional Open Simplex Noise

Description

Generate 2, 3 or 4-dimensional gradient noise. The noise function is comparable to classic Perlin noise, but with less directional artefacts and lower computational overhead. It can have applications procedural generation or (flow fields) simulations.

Author(s)

Maintainer: Pepijn de Vries pepijn.devries@outlook.com (ORCID)

Authors:

• Marco Ciaramella [copyright holder]

• KdotJPG [copyright holder]

See Also

Useful links:

• https://pepijn-devries.github.io/opensimplex2/

• https://github.com/pepijn-devries/opensimplex2/

• Report bugs at https://github.com/pepijn-devries/opensimplex2/issues

Get a 2, 3, or 4 Dimensional Array of Simplex Noise

Description

Create a regular n-dimensional grid with an OpenSimplex2 noise gradient. You can control the noisiness to some degree with the frequency argument. If you want more control, you should use opensimplex_space(), which allows you to create a continuous OpenSimplex noise gradient space, that can be sampled at any arbitrary coordinate.

Usage

opensimplex_noise(type = "S", width, height, depth, slice, frequency = 1)

Arguments

Details

The exact state of the noise gradient space depends on R's internal, random generator. So each time you call opensimplex_space, you will get a, space in a different state. If you want to obtain a reproducible state,, you simply set the random seed with set.seed().

Value

A matrix (in case of two dimensions) or array (in case of more dimensions) of numeric values between -1 and +1. OpenSimplex2 uses gradient tables that ensure that the distribution of values is centred at zero, meaning the "peaks" and "valleys" are statistically balanced.

Examples

mat <- opensimplex_noise("S", 100, 100)
image(mat)

Get a 2, 3, or 4 Dimensional OpenSimplex Noise Gradient Field

Description

Create a continuous OpenSimplex noise gradient space, that can be sampled at any arbitrary coordinate. The gradient has numeric values between -1 and +1. OpenSimplex2 uses gradient tables that ensure that the distribution of values is centred at zero, meaning the "peaks" and "valleys" are statistically balanced.

The exact state of the noise gradient space depends on R's internal, random generator. So each time you call opensimplex_space, you will get a, space in a different state. If you want to obtain a reproducible state,, you simply set the random seed with set.seed().

Usage

opensimplex_space(type = "S", dimensions = 2L)

Arguments

Value

Returns a named list. It has the elements:

• sample: which is a function that will return the simplex noise value (between -1 and +1) at a given coordinate. The function takes the same number of arguments as the value of dimensions. Each argument is a coordinate in the n^th dimension. You can provide multiple coordinates, as long as you provide the same number of coordinates in each dimension.

• dimensions: an integer value indicating the number of dimensions available in this space object.

• type: A character string indicating whether this object uses the fast ("F") or smooth ("S") variant of OpenSimplex2.

• close: which is a function that closes the simplex noise gradient space. In other words, memory used to specify the gradient space is freed, and can no longer be accessed. After closing the space, you can no longer sample it.

Examples

## By setting a random generator seed, the example below becomes reproducible
set.seed(0)

## Open a extra smooth ("S") simplex noise gradient with 3 dimensions:
space <- opensimplex_space("S", 3L)

## Sample it at some random coordinates
space$sample(i = 5*runif(10), j = 10*runif(10), k = 15*runif(10))

## Close it when you are done
space$close()