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# more explanatory name for the function
raw.means.plot <-function(data, col.offset = 2, col.x = 3, col.value = 4, na.rm = FALSE,
avoid.overlap = c("y", "x", "both"), y.factor = 1, y.amount = NULL, x.amount = 0.05,
pch = 21:25, lty = 1:5, bg.b.col = "darkgrey",
bg.f.col = NULL, fg.b.col = "black", fg.f.col = "black",
type = "o", pt.cex = 1, lwd = 1, xlab = "", ylab = "", ylim,
max.offset = 0.2, xaxis = TRUE, x.labels, xaxt = "n", plot = TRUE,
legend = TRUE, mar = NULL, reset.mar = TRUE, l.pos, yjust = 0.5,
l.bty = "n", l.adj = c(0, 0.5), ...)
{
# I somehow like more the idea of using random jitter.
spread.out <- function(x, x.amount) {
dupl <- duplicated(x)
spreadx <- rep(0,length(x))
spreadx[dupl] <- jitter(spreadx[dupl], amount = x.amount)
return(spreadx)
}
addJitter <- function (x, y.factor, y.amount) {
dupl <- duplicated(x)
x[dupl] <- jitter(x[dupl], factor = y.factor, amount = y.amount)
return(x)
}
# I personally more like the spreading on the y-axis, but I totally agree that
# spacing on the x-axis is also totally reasonable.
create.dp <- function(lst, n.x, avoid.overlap, y.factor, y.amount, x.amount) {
ret <- vector("list", 2)
#browser()
if (avoid.overlap[1] %in% c("x", "both"))
ret[[1]] <- rep(1:n.x, vapply(lst, length, 0)) +
unlist(lapply(lst, spread.out, x.amount = x.amount))
else ret[[1]] <- rep(1:n.x, vapply(lst, length, 0))
if (avoid.overlap[1] %in% c("y", "both"))
ret[[2]] <- unlist(lapply(lst, addJitter, y.factor=y.factor, y.amount = y.amount))
else ret[[2]] <- unlist(lst)
return(ret)
}
largs <- c("fill", "border", "angle", "density", "box.lwd",
"box.lty", "box.col", "pt.lwd", "xjust", "x.intersp",
"y.intersp", "text.width", "text.col", "merge", "trace",
"plot", "ncol", "horiz", "title", "inset", "title.col",
"title.adj")
dots <- list(...)
args.to.l <- dots[names(dots) %in% largs]
args.to.p <- dots[!(names(dots) %in% largs)]
if (!is.data.frame(data))
stop("data must be a data.frame")
# I used "any" here as it seems more straightforward
# I notice that you used it in add.ps
if (any(is.na(data[, c(col.offset, col.x)])))
warning("NAs in offset or x column (this produces other warnings).")
# as above
if (na.rm == FALSE)
if (any(is.na(data[, c(col.value)])))
stop("NAs in data column. Try: na.rm = TRUE")
if (!is.factor(data[, col.offset])) {
warning(paste("Converting offset variable (column ",
col.offset, ") to factor.", sep = ""))
data[, col.offset] <- factor(data[, col.offset])
}
if (!is.factor(data[, col.x])) {
warning(paste("Converting x-axis variable (column ",
col.offset, ") to factor.", sep = ""))
data[, col.x] <- factor(data[, col.x])
}
if ((length(levels(data[, col.x])) != length(unique(data[, col.x])))) {
warning(paste("Refactoring x-axis variable (column ",
col.x, ") due to length mismatch.", sep = ""))
data[, col.x] <- factor(data[, col.x])
}
if ((length(levels(data[, col.offset])) != length(unique(data[,
col.offset])))) {
warning(paste("Refactoring offset variable (column ",
col.offset, ") due to length mismatch.", sep = ""))
data[, col.offset] <- factor(data[, col.offset])
}
if (missing(ylim)) {
# I think that range is equivalent to c(min,max) here
ylim <- range(data[, col.value], na.rm = na.rm)
warning(paste("ylim not specified, taken from data: ",
ylim[1], " - ", ylim[2], sep = ""))
}
n.offset <- length(levels(data[, col.offset]))
n.x <- length(levels(data[, col.x]))
if (!(missing(x.labels))) {
if (length(x.labels) < n.x) {
warning("x.labels too short, taking unique(data[,col.x]) as labels at x-axis ticks")
x.labels <- levels(data[, col.x])
}
}
while (length(pch) < n.offset) {
warning("pch vector too short. recycling pch vector.")
# this makes sure that the pch vector will be long enough
pch <- rep(pch, length.out=n.offset)
}
while (length(lty) < n.offset) {
warning("lty vector too short. recycling lty vector.")
# ditto for the line type
lty <- rep(lty, length.out=n.offset)
}
if (!is.null(bg.b.col)) {
while (length(bg.b.col) < n.offset) {
bg.b.col <- rep(bg.b.col, length.out=n.offset)
}
}
if (!is.null(bg.f.col)) {
while (length(bg.f.col) < n.offset) {
bg.f.col <- rep(bg.f.col, length.out=n.offset)
}
}
if (!is.null(fg.b.col)) {
while (length(fg.b.col) < n.offset) {
fg.b.col <- rep(fg.b.col, length.out=n.offset)
}
}
if (!is.null(fg.f.col)) {
while (length(fg.f.col) < n.offset) {
fg.f.col <- rep(fg.f.col, length.out=n.offset)
}
}
if (missing(x.labels)) {
x.labels <- levels(data[, col.x])
}
orig.mar <- par("mar")
if (legend == TRUE & is.null(mar)) {
mar <- orig.mar
max.l <- max(nchar(levels(data[, col.offset])))
if (max.l < 3)
rb <- 4.2
else if (max.l > 2 & max.l < 5)
rb <- 5
else if (max.l > 4 & max.l < 7)
rb <- 6
else if (max.l > 6 & max.l < 9)
rb <- 7
else rb <- 8
mar[4] <- rb + 0.1
}
if (!plot)
mar <- c(0, 0, 0, 0)
if (!is.null(mar))
res.mar <- par(mar = mar)
nd <- split(data, data[, col.offset])
if (plot) {
do.call("plot", c(list(x = 1, y = 2, xlim = c((1 - max.offset -
0.2), (n.x + max.offset + 0.2)), ylim = ylim, xaxt = xaxt,
type = "n", xlab = xlab, ylab = ylab), args.to.p))
if (n.offset > 1) {
offset.start <- max.offset - ((1 - (n.offset%%2)) *
(max.offset/n.offset))
offset.dist <- max.offset/((n.offset - (n.offset%%2))/2)
}
if (n.offset == 1) {
offset.start <- 0
offset.dist <- 0
}
for (c in 1:n.offset) {
d.c <- nd[[c]]
d.lst <- split(d.c[, col.value], d.c[, col.x])
dp <- create.dp(lst = d.lst, n.x = n.x, avoid.overlap = avoid.overlap, y.factor = y.factor, y.amount = y.amount, x.amount = x.amount)
x <- dp[[1]] - ((offset.start) - ((c - 1) * offset.dist))
y <- dp[[2]]
points(x, y, pch = pch[c], col = bg.b.col[c], bg = bg.f.col[c],
cex = pt.cex)
}
for (c in 1:n.offset) {
d.c <- nd[[c]]
d.lst <- split(d.c[, col.value], d.c[, col.x])
x <- 1:n.x - ((offset.start) - ((c - 1) * offset.dist))
y <- vapply(d.lst, mean, 0, na.rm = na.rm)
lines(x, y, pch = pch[c], type = type, lty = lty[c],
col = fg.b.col[c], bg = fg.f.col[c], cex = pt.cex,
lwd = lwd)
}
if (xaxis == TRUE)
axis(side = 1, at = 1:n.x, labels = x.labels)
}
if (!plot) {
plot(0, 0, type = "n", xlim = c(0, 10), ylim = c(0, 10),
axes = FALSE, ylab = "", xlab = "", mar = c(0, 0,
0, 0))
if (missing(l.pos))
l.pos = c(5, 5)
}
if (legend == TRUE) {
if (n.x == 1) {
if (missing(l.pos)) {
l.pos <- (n.x + 0.45)
l.pos[2] <- (ylim[2] - ((ylim[2] - ylim[1])/2))
}
lty <- NULL
}
else (if (missing(l.pos)) {
l.pos <- (n.x + max.offset + 0.4)
l.pos[2] <- (ylim[2] - ((ylim[2] - ylim[1])/2))
})
do.call("legend", c(list(x = l.pos[1], y = l.pos[2],
levels(data[, col.offset]), pch = pch, lty = lty, col = fg.b.col,
pt.bg = fg.f.col, yjust = yjust, bty = l.bty, adj = l.adj,
xpd = TRUE, pt.cex = pt.cex, lwd = lwd), args.to.l))
}
if (legend == TRUE & reset.mar == TRUE) {
par(mar = res.mar)
}
}
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