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makeEdgeDf <- function(amat) {
# all credit goes to Markus Kalisch (kalisch@stat.math.ethz.ch) and Diego Colombo who
# originally implemented this. We borrow this function and
# slightly modified so as to meet our need.
#
# Kalisch, M., Machler, M., Colombo, D., Maathuis, M. H., &
# Buehlmann, P. (2012). Causal inference using graphical models
# with the R package pcalg. Journal of Statistical Software, 47(11), 1-26.
stopifnot(sum(amat) > 0)
e <- which(amat == 1, arr.ind = TRUE)
e.dup <- duplicated(t(apply(e, 1, sort)))
nmb.edges <- sum(!e.dup)
res <- data.frame(xmin = rep(NA, nmb.edges), xmax = rep(NA, nmb.edges),
tail = rep(NA, nmb.edges), head = rep(NA, nmb.edges),
order = rep(NA, nmb.edges), type = rep(1, nmb.edges))
pure.edges <- e[!e.dup, ]
if (length(pure.edges) == 2) {
dim(pure.edges) <- c(1, 2)
}
for (i in 1:dim(pure.edges)[1]) {
if (all(amat[pure.edges[i, 1], pure.edges[i, 2]] == amat[pure.edges[i,
2], pure.edges[i, 1]])) {
res$type[i] <- 0
res$head[i] <- NA
res$tail[i] <- NA
} else {
res$head[i] <- pure.edges[i, 2]
res$tail[i] <- pure.edges[i, 1]
}
}
s.pure.edges <- t(apply(pure.edges, 1, sort))
ii <- order(s.pure.edges[, 1], s.pure.edges[, 2])
res <- res[ii, ]
res$xmin <- s.pure.edges[ii, 1]
res$xmax <- s.pure.edges[ii, 2]
return(res)
}
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