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GeomPath <- proto(Geom, {
draw_groups <- function(., ...) .$draw(...)
draw <- function(., data, scales, coordinates, arrow = NULL, lineend = "butt", linejoin = "round", linemitre = 1, ..., na.rm = FALSE) {
keep <- function(x) {
# from first non-missing to last non-missing
first <- match(FALSE, x, nomatch = 1) - 1
last <- length(x) - match(FALSE, rev(x), nomatch = 1) + 1
c(
rep(FALSE, first),
rep(TRUE, last - first),
rep(FALSE, length(x) - last))
}
# Drop missing values at the start or end of a line - can't drop in the
# middle since you expect those to be shown by a break in the line
missing <- !complete.cases(data[c("x", "y", "size", "colour",
"linetype")])
kept <- ave(missing, data$group, FUN=keep)
data <- data[kept, ]
if (!all(kept) && !na.rm) {
warning("Removed ", sum(!kept), " rows containing missing values",
" (geom_path).", call. = FALSE)
}
munched <- coordinates$munch(data, scales)
# Silently drop lines with less than two points, preserving order
rows <- ave(seq_len(nrow(munched)), munched$group, FUN = length)
munched <- munched[rows >= 2, ]
if (nrow(munched) < 2) return(zeroGrob())
# Work out whether we should use lines or segments
attr <- ddply(munched, .(group), function(df) {
data.frame(
solid = identical(unique(df$linetype), 1),
constant = nrow(unique(df[, c("alpha", "colour","size", "linetype")])) == 1
)
})
solid_lines <- all(attr$solid)
constant <- all(attr$constant)
if (!solid_lines && !constant) {
stop("geom_path: If you are using dotted or dashed lines",
", colour, size and linetype must be constant over the line",
call.=FALSE)
}
# Work out grouping variables for grobs
n <- nrow(munched)
group_diff <- munched$group[-1] != munched$group[-n]
start <- c(TRUE, group_diff)
end <- c(group_diff, TRUE)
if (!constant) {
with(munched,
segmentsGrob(
x[!end], y[!end], x[!start], y[!start],
default.units="native", arrow = arrow,
gp = gpar(
col = alpha(colour, alpha)[!end],
lwd = size[!end] * .pt, lty = linetype[!end],
lineend = lineend, linejoin = linejoin, linemitre = linemitre
)
)
)
} else {
with(munched,
polylineGrob(
x, y, id = as.integer(factor(group)),
default.units = "native", arrow = arrow,
gp = gpar(
col = alpha(colour, alpha)[start],
lwd = size[start] * .pt, lty = linetype[start],
lineend = lineend, linejoin = linejoin, linemitre = linemitre)
)
)
}
}
draw_legend <- function(., data, ...) {
data$arrow <- NULL
data <- aesdefaults(data, .$default_aes(), list(...))
with(data,
ggname(.$my_name(), segmentsGrob(0.1, 0.5, 0.9, 0.5, default.units="npc",
gp=gpar(col=alpha(colour, alpha), lwd=size * .pt,
lty=linetype, lineend="butt")))
)
}
objname <- "path"
desc <- "Connect observations, in original order"
desc_params <- list(
lineend = "Line end style (round, butt, square)",
linejoin = "Line join style (round, mitre, bevel)",
linemitre = "Line mitre limit (number greater than 1)",
arrow = "Arrow specification, as created by ?arrow"
)
default_stat <- function(.) StatIdentity
required_aes <- c("x", "y")
default_aes <- function(.) aes(colour="black", size=0.5, linetype=1, alpha = 1)
icon <- function(.) linesGrob(c(0.2, 0.4, 0.8, 0.6, 0.5), c(0.2, 0.7, 0.4, 0.1, 0.5))
guide_geom <- function(.) "path"
seealso <- list(
geom_line = "Functional (ordered) lines",
geom_polygon = "Filled paths (polygons)",
geom_segment = "Line segments"
)
examples <- function(.) {
# Generate data
myear <- ddply(movies, .(year), plyr::colwise(mean, .(length, rating)))
p <- ggplot(myear, aes(length, rating))
p + geom_path()
# Add aesthetic mappings
p + geom_path(aes(size = year))
p + geom_path(aes(colour = year))
# Change scale
p + geom_path(aes(size = year)) + scale_size(to = c(1, 3))
# Set aesthetics to fixed value
p + geom_path(colour = "green")
# Control line join parameters
df <- data.frame(x = 1:3, y = c(4, 1, 9))
base <- ggplot(df, aes(x, y))
base + geom_path(size = 10)
base + geom_path(size = 10, lineend = "round")
base + geom_path(size = 10, linejoin = "mitre", lineend = "butt")
# Use qplot instead
qplot(length, rating, data=myear, geom="path")
# Using economic data:
# How is unemployment and personal savings rate related?
qplot(unemploy/pop, psavert, data=economics)
qplot(unemploy/pop, psavert, data=economics, geom="path")
qplot(unemploy/pop, psavert, data=economics, geom="path", size=as.numeric(date))
# How is rate of unemployment and length of unemployment?
qplot(unemploy/pop, uempmed, data=economics)
qplot(unemploy/pop, uempmed, data=economics, geom="path")
qplot(unemploy/pop, uempmed, data=economics, geom="path") +
geom_point(data=head(economics, 1), colour="red") +
geom_point(data=tail(economics, 1), colour="blue")
qplot(unemploy/pop, uempmed, data=economics, geom="path") +
geom_text(data=head(economics, 1), label="1967", colour="blue") +
geom_text(data=tail(economics, 1), label="2007", colour="blue")
# geom_path removes missing values on the ends of a line.
# use na.rm = T to suppress the warning message
df <- data.frame(
x = 1:5,
y1 = c(1, 2, 3, 4, NA),
y2 = c(NA, 2, 3, 4, 5),
y3 = c(1, 2, NA, 4, 5),
y4 = c(1, 2, 3, 4, 5))
qplot(x, y1, data = df, geom = c("point","line"))
qplot(x, y2, data = df, geom = c("point","line"))
qplot(x, y3, data = df, geom = c("point","line"))
qplot(x, y4, data = df, geom = c("point","line"))
# Setting line type vs colour/size
# Line type needs to be applied to a line as a whole, so it can
# not be used with colour or size that vary across a line
x <- seq(0.01, .99, length=100)
df <- data.frame(x = rep(x, 2), y = c(qlogis(x), 2 * qlogis(x)), group = rep(c("a","b"), each=100))
p <- ggplot(df, aes(x=x, y=y, group=group))
# Should work
p + geom_line(linetype = 2)
p + geom_line(aes(colour = group), linetype = 2)
p + geom_line(aes(colour = x))
# Should fail
p + geom_line(aes(colour = x), linetype=2)
}
})
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