Class TurbulencePatternRed
- java.lang.Object
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- org.apache.batik.ext.awt.image.rendered.AbstractRed
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- org.apache.batik.ext.awt.image.rendered.TurbulencePatternRed
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- All Implemented Interfaces:
java.awt.image.RenderedImage
,CachableRed
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.
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Field Summary
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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
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Constructor Summary
Constructors Constructor Description 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)
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description 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)
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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
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Constructor Detail
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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-axisbaseFrequencyY
- y-axis base frequency for the noise function along the x-axisnumOctaves
- number of octaves in the noise function. Positive integral value.seed
- starting number for the pseudo random number generatorisFractalNoise
- 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.
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Method Detail
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getBaseFrequencyX
public double getBaseFrequencyX()
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getBaseFrequencyY
public double getBaseFrequencyY()
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getNumOctaves
public int getNumOctaves()
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getSeed
public int getSeed()
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getTile
public java.awt.geom.Rectangle2D getTile()
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isFractalNoise
public boolean isFractalNoise()
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getChannels
public boolean[] getChannels()
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setupSeed
public final int setupSeed(int seed)
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random
public final int random(int seed)
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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.
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