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# Internal function taken directly from rpart.
# SCCS @(#)pred.rpart.s 1.3 09/03/97
#
# Do Rpart predictions given a tree and a matrix of predictors
pred.rpart <- function(fit, x) {
frame <- fit$frame
if(nrow(frame) == 1L) { # handle root-only tree separately
temp <- rep(1, nrow(x))
} else {
nc <- frame[, c('ncompete', 'nsurrogate')]
frame$index <- 1 + c(0, cumsum((frame$var != "<leaf>") +
nc[[1L]] + nc[[2L]]))[-(nrow(frame)+1L)]
frame$index[frame$var == "<leaf>"] <- 0
vnum <- match(dimnames(fit$splits)[[1L]], dimnames(x)[[2L]])
if (any(is.na(vnum)))
stop("Tree has variables not found in new data")
temp <- .C(C_pred_rpart,
as.integer(dim(x)),
as.integer(dim(frame)[1]),
as.integer(dim(fit$splits)),
as.integer(if(is.null(fit$csplit)) rep(0L, 2)
else dim(fit$csplit)),
as.integer(row.names(frame)),
as.integer(unlist(frame[,
c('n', 'ncompete', 'nsurrogate', 'index')])),
as.integer(vnum),
as.double(fit$splits),
as.integer(fit$csplit -2),
as.integer((fit$control)$usesurrogate),
as.double(x),
as.integer(is.na(x)),
where = integer(dim(x)[1]),
NAOK = TRUE)
temp <- temp$where
}
#where gives rownumber in the rpart$frame matrix of the node where
# each observation in x belongs.
names(temp) <- rownames(x)
temp
}
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