struct SuperSimplexNoise3D

Structure

SuperSimplexNoise3D

A type of three-dimensional gradient noise (sometimes called Perlin noise), suitable for texturing arbitrary three-dimensional objects.

Three-dimensional super-simplex noise generally looks somewhat better visually than its two-dimensional counterpart, but runs about 20% slower.

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Symbols

Initializers

init(amplitude:Double, frequency:Double, seed:Int = 0)

Creates an instance with the given amplitude, frequency, and random seed values. Creating an instance generates a new pseudo-random permutation table for that instance, and a new instance does not need to be regenerated to sample the same procedural noise field.

The given amplitude is adjusted internally to produce output approximately within the range of -amplitude ... amplitude, however this is not strictly guaranteed.

Instance methods

func evaluate(_ x:Double, _ y:Double) -> Double

Evaluates the super-simplex noise field at the given x, y coordinates, supplying 0 for the missing z coordinate.

func evaluate(_ x:Double, _ y:Double, _ z:Double) -> Double

Evaluates the super-simplex noise field at the given coordinates.

func evaluate(_ x:Double, _ y:Double, _ z:Double, _:Double) -> Double

Evaluates the super-simplex noise field at the given coordinates. The fourth coordinate is ignored.

func sample_area(width:Int, height:Int) -> [(Double, Double, Double)]

Evaluates the noise field over the given area, starting from the origin, and extending over the first quadrant, taking unit steps in both directions. Although the x and y coordinates are returned, the output vector is guaranteed to be in row-major order.

func sample_area_saturated_to_u8(width:Int, height:Int, offset:Double = 0.5) -> [UInt8]

Evaluates the noise field over the given area, starting from the origin, and extending over the first quadrant, storing the values in a row-major array of samples. The samples are clamped, but not scaled, to the range 0 ... 255.

Relationships

Conforms to

Noise