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#' Connect observations.
#'
#' \code{geom_path()} connects the observations in the order in which they appear
#' in the data. \code{geom_line()} connects them in order of the variable on the
#' x axis. \code{geom_step()} creates a stairstep plot, highlighting exactly
#' when changes occur.
#'
#' @section Aesthetics:
#' \Sexpr[results=rd,stage=build]{animint2:::rd_aesthetics("geom", "path")}
#'
#' @inheritParams layer
#' @inheritParams geom_point
#' @param lineend Line end style (round, butt, square)
#' @param linejoin Line join style (round, mitre, bevel)
#' @param linemitre Line mitre limit (number greater than 1)
#' @param arrow Arrow specification, as created by \code{\link[grid]{arrow}}
#' @seealso
#' \code{\link{geom_polygon}}: Filled paths (polygons);
#' \code{\link{geom_segment}}: Line segments
#' @export
#' @examples
#' # geom_line() is suitable for time series
#' ggplot(economics, aes(date, unemploy)) + geom_line()
#' ggplot(economics_long, aes(date, value01, colour = variable)) +
#' geom_line()
#'
#' # geom_step() is useful when you want to highlight exactly when
#' # the y value chanes
#' recent <- economics[economics$date > as.Date("2013-01-01"), ]
#' ggplot(recent, aes(date, unemploy)) + geom_line()
#' ggplot(recent, aes(date, unemploy)) + geom_step()
#'
#' # geom_path lets you explore how two variables are related over time,
#' # e.g. unemployment and personal savings rate
#' m <- ggplot(economics, aes(unemploy/pop, psavert))
#' m + geom_path()
#' m + geom_path(aes(colour = as.numeric(date)))
#'
#' # Changing parameters ----------------------------------------------
#' ggplot(economics, aes(date, unemploy)) +
#' geom_line(colour = "red")
#'
#' # Use the arrow parameter to add an arrow to the line
#' # See ?arrow for more details
#' c <- ggplot(economics, aes(x = date, y = pop))
#' c + geom_line(arrow = arrow())
#' c + geom_line(
#' arrow = arrow(angle = 15, ends = "both", type = "closed")
#' )
#'
#' # 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")
#'
#' # NAs break the 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)
#' )
#' ggplot(df, aes(x, y1)) + geom_point() + geom_line()
#' ggplot(df, aes(x, y2)) + geom_point() + geom_line()
#' ggplot(df, aes(x, y3)) + geom_point() + geom_line()
#'
#' \donttest{
#' # 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.out = 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))
#' # These work
#' p + geom_line(linetype = 2)
#' p + geom_line(aes(colour = group), linetype = 2)
#' p + geom_line(aes(colour = x))
#' # But this doesn't
#' should_stop(p + geom_line(aes(colour = x), linetype=2))
#' }
geom_path <- function(mapping = NULL, data = NULL,
stat = "identity", position = "identity",
...,
lineend = "butt",
linejoin = "round",
linemitre = 1,
arrow = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomPath,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
lineend = lineend,
linejoin = linejoin,
linemitre = linemitre,
arrow = arrow,
na.rm = na.rm,
...
)
)
}
#' @rdname animint2-gganimintproto
#' @format NULL
#' @usage NULL
#' @export
GeomPath <- gganimintproto("GeomPath", Geom,
required_aes = c("x", "y"),
default_aes = aes(colour = "black", size = 0.5, linetype = 1, alpha = NA),
handle_na = function(data, params) {
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 <- !stats::complete.cases(data[c("x", "y", "size", "colour",
"linetype")])
kept <- stats::ave(missing, data$group, FUN = keep)
data <- data[kept, ]
if (!all(kept) && !params$na.rm) {
warning("Removed ", sum(!kept), " rows containing missing values",
" (geom_path).", call. = FALSE)
}
data
},
draw_panel = function(data, panel_scales, coord, arrow = NULL,
lineend = "butt", linejoin = "round", linemitre = 1,
na.rm = FALSE) {
if (!anyDuplicated(data$group)) {
message_wrap("geom_path: Each group consists of only one observation. ",
"Do you need to adjust the group aesthetic?")
}
# must be sorted on group
data <- data[order(data$group), , drop = FALSE]
munched <- coord_munch(coord, data, panel_scales)
# Silently drop lines with less than two points, preserving order
rows <- stats::ave(seq_len(nrow(munched)), munched$group, FUN = length)
munched <- munched[rows >= 2, ]
if (nrow(munched) < 2) return(zeroGrob())
# Work out whether we should use lines or segments
attr <- plyr::ddply(munched, "group", function(df) {
linetype <- unique(df$linetype)
data.frame(
solid = identical(linetype, 1) || identical(linetype, "solid"),
constant = nrow(unique(df[, c("alpha", "colour","size", "linetype")])) == 1
)
})
solid_lines <- all(attr$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$group[-n]
start <- c(TRUE, group_diff)
end <- c(group_diff, TRUE)
if (!constant) {
segmentsGrob(
munched$x[!end], munched$y[!end], munched$x[!start], munched$y[!start],
default.units = "native", arrow = arrow,
gp = gpar(
col = alpha(munched$colour, munched$alpha)[!end],
fill = alpha(munched$colour, munched$alpha)[!end],
lwd = munched$size[!end] * .pt,
lty = munched$linetype[!end],
lineend = lineend,
linejoin = linejoin,
linemitre = linemitre
)
)
} else {
id <- match(munched$group, unique(munched$group))
polylineGrob(
munched$x, munched$y, id = id,
default.units = "native", arrow = arrow,
gp = gpar(
col = alpha(munched$colour, munched$alpha)[start],
fill = alpha(munched$colour, munched$alpha)[start],
lwd = munched$size[start] * .pt,
lty = munched$linetype[start],
lineend = lineend,
linejoin = linejoin,
linemitre = linemitre
)
)
}
},
draw_key = draw_key_path
)
#' @export
#' @rdname geom_path
geom_line <- function(mapping = NULL, data = NULL, stat = "identity",
position = "identity", na.rm = FALSE,
show.legend = NA, inherit.aes = TRUE, ...) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomLine,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
na.rm = na.rm,
...
)
)
}
#' @rdname animint2-gganimintproto
#' @format NULL
#' @usage NULL
#' @export
#' @include geom-path.r
GeomLine <- gganimintproto("GeomLine", GeomPath,
setup_data = function(data, params) {
data[order(data$PANEL, data$group, data$x), ]
}
)
#' @param direction direction of stairs: 'vh' for vertical then horizontal, or
#' 'hv' for horizontal then vertical
#' @export
#' @rdname geom_path
geom_step <- function(mapping = NULL, data = NULL, stat = "identity",
position = "identity", direction = "hv",
na.rm = FALSE, show.legend = NA, inherit.aes = TRUE, ...) {
layer(
data = data,
mapping = mapping,
stat = stat,
geom = GeomStep,
position = position,
show.legend = show.legend,
inherit.aes = inherit.aes,
params = list(
direction = direction,
na.rm = na.rm,
...
)
)
}
#' @rdname animint2-gganimintproto
#' @format NULL
#' @usage NULL
#' @export
#' @include geom-path.r
GeomStep <- gganimintproto("GeomStep", GeomPath,
draw_panel = function(data, panel_scales, coord, direction = "hv") {
data <- plyr::ddply(data, "group", stairstep, direction = direction)
GeomPath$draw_panel(data, panel_scales, coord)
},
pre_process = function(g, g.data, ...) {
datanames <- names(g.data)
g.data <- plyr::ddply(g.data, "group", function(df) stairstep(df))
g$geom <- "path"
return(list(g = g, g.data = g.data))
}
)
# Calculate stairsteps
# Used by \code{\link{geom_step}}
#
# @keywords internal
stairstep <- function(data, direction="hv") {
direction <- match.arg(direction, c("hv", "vh"))
data <- as.data.frame(data)[order(data$x), ]
n <- nrow(data)
if (direction == "vh") {
xs <- rep(1:n, each = 2)[-2*n]
ys <- c(1, rep(2:n, each = 2))
} else {
ys <- rep(1:n, each = 2)[-2*n]
xs <- c(1, rep(2:n, each = 2))
}
data.frame(
x = data$x[xs],
y = data$y[ys],
data[xs, setdiff(names(data), c("x", "y"))]
)
}
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