R Under development (unstable) (2023-12-02 r85657 ucrt) -- "Unsuffered Consequences"
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> #
> # Treble test for class trees with 2 outcomes
> #
> # fit1 and fit1b failed equality because .7 and .3 are not easily represented
> # in binary.  Thus a complelxity param was 4e-17 (basically 0, but enough
> # to cause a split where it shouldn't be). Eric Lunde 2005-08-03
> library(rpart)
> control <- rpart.control(maxsurrogate=0, cp=1e-15, xval=0)
> set.seed(10)
> 
> fit1 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis, 
+               control=control,
+               parms=list(prior=c(.7,.3), 
+                 loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
> wts <- rep(3, nrow(kyphosis))
> fit1b <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis, 
+                control=control,
+ 	       weights=wts,
+                parms=list(prior=c(.7,.3), 
+                  loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
> fit1b$frame$wt   <- fit1b$frame$wt/3
> fit1b$frame$dev  <- fit1b$frame$dev/3
> fit1b$frame$yval2[,2:3] <- fit1b$frame$yval2[,2:3]/3
> fit1b$splits[,3] <- fit1b$splits[,3]/3
> fit1b$variable.importance <- fit1b$variable.importance/3
> all.equal(fit1[-3], fit1b[-3])   #all but the "call"
[1] TRUE
> 
> # Now for a set of non-equal weights
> nn <- nrow(kyphosis)
> pseudo <- double(nn)
> pseudo[1] <- pi/6
> for (i in 2:nn) pseudo[i] <- 4*pseudo[i-1]*(1-pseudo[i-1])
> 
> wts <-  rep(1:7, length=nn)
> temp <- rep(1:nn, wts)             #row replicates
> xgrp <- rep(1:10, length=nn)[order(pseudo)]
> xgrp2<- rep(xgrp, wts)
> 
> # The cp value stops one last split where the two predictors are
> #  completely equal in importance (perfect surrogates), but the
> #  weighted and unweighted pick a different one due to round off error
> tempc <- rpart.control(minsplit=2, xval=xgrp2, maxsurrogate=0, cp=.039)
> #  Direct: replicate rows in the data set, and use unweighted
> fit2 <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis[temp,], 
+                control=tempc, 
+                parms=list(prior=c(.7,.3), 
+                           loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
> #  Weighted
> tempc <- rpart.control(minsplit=2, xval=xgrp, maxsurrogate=0, cp=.039)
> fit2b <- rpart(Kyphosis ~ Age + Number + Start, data=kyphosis, 
+                control=tempc, weights=wts,
+                parms=list(prior=c(.7,.3), 
+                           loss=matrix(c(0,1,2,0),nrow=2,ncol=2)))
> 
> all.equal(fit2$frame[,-2],  fit2b$frame[,-2])  # the "n" component won't match
[1] TRUE
> all.equal(fit2$cptable, fit2b$cptable)
[1] TRUE
> all.equal(fit2$splits[,-1],fit2b$splits[,-1]) 
[1] TRUE
> all.equal(fit2$csplit,    fit2b$csplit)
[1] TRUE
> 
> proc.time()
   user  system elapsed 
   0.17    0.04    0.20