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Last active Aug 29, 2015
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formattedtable <- function(x, block, group, value) {
# Form a dataframe with the mean values and get a logical matrix of the max values
mean <- setNames(aggregate(x[, value], list(x[, block], x[, group]), mean), c(block, group, "mean"))
# To get the max values need in wide format
mean.wide <- dcast(mean, get(block) ~ get(group), value.var="mean") # get() comes from reshape2, gets string values from variables
colnames(mean.wide)[1] <- block
# Now can get logical matrix of maximum values
# NB: This is taken from xtable_printbold.R
boldmatrix <- matrix(FALSE, ncol = ncol(mean.wide), nrow = nrow(mean.wide))
max <- TRUE
max <- rep(max, length = nrow(mean.wide))
for (i in 1:nrow(mean.wide)) {
mean.widei <- mean.wide[i,]
ok <- sapply(mean.widei, is.numeric)
if (!any(ok)) next
if ([i])) next
imax <- max(unlist(mean.widei[ok]), na.rm = TRUE)
if (!max[i])
imax <- min(unlist(mean.widei[ok]), na.rm = TRUE)
whichmax <- sapply(mean.widei, identical, imax)
boldmatrix[i, whichmax] <- TRUE
# Calculate standard deviation and combine with mean into new data frame
sd <- setNames(aggregate(x[, value], list(x[, block], x[, group]), sd), c(block, group, "sd"))
overall <- merge(mean, sd, by=c(block, group))
# Make a new column with mean +- sd and drop original mean and sd
overall$mean_sd <- sprintf("%.3f $\\pm$%.3f", overall$mean, overall$sd)
overall <- subset(overall, select=-c(mean,sd))
# Cast into wide format
overall.wide <- dcast(overall, get(block) ~ get(group), value.var="mean_sd")
colnames(overall.wide)[1] <- block
# Finally iterate over the boldmatrix and set TRUE values in new dataframe to bold
for (row in 1:nrow(boldmatrix)) {
# Starting at second column as first is blocking factor name
for (col in 2:ncol(boldmatrix)) {
if (isTRUE(boldmatrix[row, col])) {
overall.wide[row,col] <- sprintf("\\textbf{%s}", overall.wide[row,col])
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