Exponential noise functions based on simplex noise. More...

#include <noise.h>

Inheritance diagram for ExponentialSimplexNoise:

Public Member Functions
double	Value (const Vector2 &) const
	Compute the expoential simplex noise at a given point.

virtual ScalarField2	Sample (const Array2 &) const
	Create a discrete scalar field by sampling a given domain.

Protected Member Functions
double	Exponential (const double &) const
	Approximates an exponentially distribution from a uniform.

Protected Member Functions inherited from SimplexNoise2
	SimplexNoise2 ()
	Empty.

	~SimplexNoise2 ()
	Empty.

double	Value (const Vector2 &) const
	Compute the simplex noise at a given point.

double	K () const
	Return the global Lipschitz constant of the noise.

Protected Member Functions inherited from AnalyticScalarField2
Matrix	Local (const Vector2 &) const
	Compute the local neighborhood in the one-ring aroung a point.

	AnalyticScalarField2 (bool=true)
	Constructor.

virtual Vector2	Gradient (const Vector2 &) const
	Compute the gradient of the field.

virtual Matrix2	Hessian (const Vector2 &) const
	Compute the hessian at a given point.

bool	Inside (const double &) const
	Check if the value is considered as inside or outside.

void	Curvature (const Vector2 &, double &, double &) const
	Compute the gaussian and mean curvatures.

virtual Box2	GetBox () const
	Return the bounding box.

Additional Inherited Members
Protected Attributes inherited from AnalyticScalarField2
bool	sign = true
	Sign convention, used for normal computation.

Box2	box = Box2::Infinity
	Domain, set as infinite for base class.

Static Protected Attributes inherited from SimplexNoise2
static const Vector2	grad2 [8]
	Array of gradients.

static const int	perm [512]
	Permutation table, 256 entries duplicated once to avoid modulo computations.

static const double	G2 = (3.0 - sqrt(3.0)) / 6.0
	Unskew factors for planar case.

Static Protected Attributes inherited from AnalyticScalarField2
static const double	epsilon = 1e-6
	\epsilon; value for partial derivatives

Detailed Description

Exponential noise functions based on simplex noise.

Member Function Documentation

double ExponentialSimplexNoise::Exponential ( const double & x ) const

protected

Approximates an exponentially distribution from a uniform.

Parameters

x	Should be in unit interval

ScalarField2 AnalyticScalarField2::Sample ( const Array2 & a ) const

virtual

Create a discrete scalar field by sampling a given domain.

Parameters

a Domain.

double ExponentialSimplexNoise::Value ( const Vector2 & p ) const

virtual

Compute the expoential simplex noise at a given point.

Parameters

p Point.