Noise Class Reference

Perlin noise. More...

#include <noise.h>

Inheritance diagram for Noise:

Public Member Functions
	Noise (bool=false)
	Create a noise function. More...
	~Noise ()
	Empty.
double	At (const Vector &) const
	Compute noise at a given point. More...
Vector	Gradient (const Vector &) const
	Compute noise at a given point in the plane. More...
double	AtGradient (const Vector &, Vector &) const
	Compute the gradient of the noise function at a given point. More...
double	K () const
	Return the global Lipschitz constant of the noise.
Vector	AtVector (const Vector &) const
	Vector version of Perlin-style noise function. More...

Protected Attributes
bool	quintic
	Flag defining interpolation type: either cubic (false) or quintic (true).

Static Protected Attributes
static double	rtable [267]
	Random double table.
static const short	hashTable [4096]
	Hash table.

Detailed Description

Perlin noise.

This class is used as a core class to create various types of fractal noise, such as sums of scaled noises.

See also

SimplexNoise

Constructor & Destructor Documentation

Noise()

Noise::Noise

(

bool

quintic = false

)

Create a noise function.

Parameters

quintic

Flag defining whether quintic interpolation will be used, noise uses cubic interpolation if set to false.

Member Function Documentation

At()

double Noise::At

(

const Vector &

p

)

const

Compute noise at a given point.

Parameters

p

Point.

AtGradient()

double Noise::AtGradient	(	const Vector &	p,
		Vector &	n
	)		const

Compute the gradient of the noise function at a given point.

Note that it is much faster to call this function rather than calling Noise::Gradient() and NoiseAt() consecutively.

Parameters

p	Point.
n	Returned gradient.

Returns

The noise value.

AtVector()

Vector Noise::AtVector

(

const Vector &

p

)

const

Vector version of Perlin-style noise function.

Parameters

p

Point

Gradient()

Vector Noise::Gradient

(

const Vector &

p

)

const

Compute noise at a given point in the plane.

Parameters

p

Point.

Compute the gradient of the noise function at a given point.

Parameters

p

Point.