# CGGPplotheat: Heatmap of SG design depth In CollinErickson/CGGP: Composite Grid Gaussian Processes

## Description

The values on the diagonal are largest design depth for that dimension. The off-diagonal values are the largest design depth that both dimensions have been measured at simultaneously. A greater depth means that more points have been measured along that dimension or two-dimensional subspace.

## Usage

 `1` ```CGGPplotheat(CGGP) ```

## Arguments

 `CGGP` CGGP object

## Value

A heat map made from ggplot2

## References

https://stackoverflow.com/questions/14290364/heatmap-with-values-ggplot2

Other CGGP plot functions: `CGGPplotblocks()`, `CGGPplotcorr()`, `CGGPplothist()`, `CGGPplotsamplesneglogpost()`, `CGGPplotslice()`, `CGGPplottheta()`, `CGGPplotvariogram()`, `CGGPvalplot()`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14``` ```# All dimensions should look similar d <- 8 SG = CGGPcreate(d,201) CGGPplotheat(SG) # The first and fourth dimensions are most active and will have greater depth SG <- CGGPcreate(d=5, batchsize=50) f <- function(x) {cos(2*pi*x*3) + exp(4*x)} for (i in 1:1) { SG <- CGGPfit(SG, Y=apply(SG\$design, 1, f)) SG <- CGGPappend(CGGP=SG, batchsize=200) } # SG <- CGGPfit(SG, Y=apply(SG\$design, 1, f)) CGGPplotheat(SG) ```