R version 4.5.0 RC (2025-04-04 r88113 ucrt) -- "How About a Twenty-Six"
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Platform: x86_64-w64-mingw32/x64

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> library(ClassDiscovery)
Loading required package: cluster
Loading required package: oompaBase
> suppressWarnings( RNGversion("3.5.3") )
> set.seed(320085)
> # simulate data from two different classes
> d1 <- matrix(rnorm(100*30, rnorm(100, 0.5)), nrow=100, ncol=30, byrow=FALSE)
> d2 <- matrix(rnorm(100*20, rnorm(100, 0.5)), nrow=100, ncol=20, byrow=FALSE)
> dd <- cbind(d1, d2)
> 
> # cluster the data
> hc <- hclust(distanceMatrix(dd, 'pearson'), method='average')
> 
> # make a fake reproducibility matrix
> fraud <- function(x) {
+   new('ClusterTest', result=abs(cor(x)), call=match.call())
+ }
> 
> fake <- fraud(dd)
> summary(fake, digits = 3)
A ClusterTest object.

Call:
	 fraud(x = dd) 

Agreement levels:
    Min.  1st Qu.   Median     Mean  3rd Qu.     Max. 
3.67e-05 6.43e-02 3.53e-01 2.98e-01 5.15e-01 6.70e-01 
> 
> hist(fake)
> 
> image(fake) # let heatmap compute a new dendrogram from the agreements
> 
> image(fake, dendrogram=hc) # use the actual dendrogram from the data
> 
> image(fake, dendrogram=hc, col=blueyellow(64)) # change the colors
> 
> #cleanup
> rm(fake, fraud, hc, dd, d1, d2)
> 
> proc.time()
   user  system elapsed 
    0.5     0.1     0.6