org.apache.batik.ext.awt.image.rendered
Class TurbulencePatternRed

java.lang.Object
  |
  +--org.apache.batik.ext.awt.image.rendered.AbstractRed
        |
        +--org.apache.batik.ext.awt.image.rendered.TurbulencePatternRed

All Implemented Interfaces:

CachableRed, java.awt.image.RenderedImage

public final class TurbulencePatternRed

extends AbstractRed

This class creates a RenderedImage in conformance to the one defined for the feTurbulence filter of the SVG specification. What follows is my high-level description of how the noise is generated. This is not contained in the SVG spec, just the algorithm for doing it. This is provided in the hope that someone will figure out a clever way to accelerate parts of the function. gradient contains a long list of random unit vectors. For each point we are to generate noise for we do two things. first we use the latticeSelector to 'co-mingle' the integer portions of x and y (this allows us to have a one-dimensional array of gradients that appears 2 dimensional, by using the co-mingled index). We do this for [x,y], [x+1,y], [x,y+1], and [x+1, y+1], this gives us the four gradient vectors that surround the point (b00, b10, ...) Next we construct the four vectors from the grid points (where the gradient vectors are defined) [these are rx0, rx1, ry0, ry1]. We then take the dot product between the gradient vectors and the grid point vectors (this gives the portion of the grid point vector that projects along the gradient vector for each grid point). These four dot projects are then combined with linear interpolation. The weight factor for the linear combination is the result of applying the 's' curve function to the fractional part of x and y (rx0, ry0). The S curve function get's it's name because it looks a bit like as 'S' from 0->1.

Fields inherited from class org.apache.batik.ext.awt.image.rendered.AbstractRed

bounds, cm, minTileX, minTileY, numXTiles, numYTiles, props, sm, srcs, tileGridXOff, tileGridYOff, tileHeight, tileWidth

Constructor Summary

TurbulencePatternRed(double baseFrequencyX, double baseFrequencyY, int numOctaves, int seed, boolean isFractalNoise, java.awt.geom.Rectangle2D tile, java.awt.geom.AffineTransform txf, java.awt.Rectangle devRect, java.awt.color.ColorSpace cs, boolean alpha)

Method Summary

java.awt.image.WritableRaster	copyData(java.awt.image.WritableRaster dest) Generates a Perlin noise pattern into dest Raster.
double	getBaseFrequencyX()
double	getBaseFrequencyY()
boolean[]	getChannels()
int	getNumOctaves()
int	getSeed()
java.awt.geom.Rectangle2D	getTile()
boolean	isFractalNoise()
int	random(int seed)
int	setupSeed(int seed)

Methods inherited from class org.apache.batik.ext.awt.image.rendered.AbstractRed

copyBand, copyToRaster, getBounds, getColorModel, getData, getData, getDependencyRegion, getDirtyRegion, getHeight, getMinTileX, getMinTileY, getMinX, getMinY, getNumXTiles, getNumYTiles, getProperty, getPropertyNames, getSampleModel, getSources, getTile, getTileGridXOffset, getTileGridYOffset, getTileHeight, getTileWidth, getWidth, getXTile, getYTile, init, init, makeTile, updateTileGridInfo

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

TurbulencePatternRed

public TurbulencePatternRed(double baseFrequencyX,
                            double baseFrequencyY,
                            int numOctaves,
                            int seed,
                            boolean isFractalNoise,
                            java.awt.geom.Rectangle2D tile,
                            java.awt.geom.AffineTransform txf,
                            java.awt.Rectangle devRect,
                            java.awt.color.ColorSpace cs,
                            boolean alpha)

Parameters:

baseFrequencyX - x-axis base frequency for the noise function along the x-axis

baseFrequencyY - y-axis base frequency for the noise function along the x-axis

numOctaves - number of octaves in the noise function. Positive integral value.

seed - starting number for the pseudo random number generator

isFractalNoise - defines whether the filter performs a fractal noise or a turbulence function.

tile - defines the tile size. May be null if stitchTiles is false. Otherwise, should not be null.

txf - The affine transform from device to user space.

cs - The Colorspace to output.

alpha - True if the data should have an alpha channel.

Method Detail

getBaseFrequencyX

public double getBaseFrequencyX()

getBaseFrequencyY

public double getBaseFrequencyY()

getNumOctaves

public int getNumOctaves()

getSeed

public int getSeed()

getTile

public java.awt.geom.Rectangle2D getTile()

isFractalNoise

public boolean isFractalNoise()

getChannels

public boolean[] getChannels()

setupSeed

public final int setupSeed(int seed)

random

public final int random(int seed)

copyData

public java.awt.image.WritableRaster copyData(java.awt.image.WritableRaster dest)

Generates a Perlin noise pattern into dest Raster.

Parameters:

dest - Raster to fill with the pattern.