Wtransform.sim {fields}R Documentation

Simulates a 2-d random wavelet field

Description

Generates a Gaussian field using quadratic W transform basis functions.

Usage

Wtransform.sim(D, cut.min=16)

Arguments

D A matrix the same size as the image with the variances of the wavelet coefficients.
cut.min Coarsest level of resolution in wavelet expansion this set the number of smooth basis functions.

Details

The simulation is easy just an inverse transform applied to weighted independent normals. The tricky part is getting all the values of D in the right places. See plot.coef to plot out the elements of D to check them and also Wtransform.D to fill D from variances that are fixed at each level of resolution.

Value

A matrix image of the random field

Side Effects

See Also

Wtransfrom.image, W.image.cov

Examples

# 
#Fill to look like Gaussian. 
# 
 wght <- c(1., 0.05, 1e-07, 1e-09, 1e-11, 1e-14) 
D<- Wtransform.D(32,32, wght, cut.min=4)$D 
set.panel( 2,2)
for ( k in 1:4){
look<- Wtransform.sim( D, cut.min=4) 
image( look)
}
set.panel( 1,1)


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