当大小不同时,我一直试图在ggplot2或网格中以相等的线段间距绘制线。但是我还没有成功,所以我请你帮忙。
在下面的示例中,如何在线段大小不同的情况下使线段之间的绝对间距相等?
我想避免制作自定义的makeContent.myclass
方法来自己控制。
library(ggplot2)
library(grid)
df <- data.frame(
x = c(1:2, 1:2),
y = c(1:2, 2:1),
size = c(1,1,10,10)
)
# In ggplot2
ggplot(df, aes(x, y, size = size, group = size)) +
geom_line(linetype = 2)
# In grid
lines <- polylineGrob(
x = scales::rescale(df$x),
y = scales::rescale(df$y),
id = c(1,1,2,2),
gp = gpar(lty = 2, lwd = c(1, 10))
)
grid.newpage(); grid.draw(lines)
我想要一些类似于插图画家制作的东西。请注意,红线的长度相等。
有什么想法吗?感谢您的阅读!
答案 0 :(得分:6)
这可能不是您在寻找Teunbrand的目的,但是我想您可以将线条转换为一系列沿线条等距分布的细多边形多边形。
此函数采用一系列x和y坐标,并返回虚线(作为单个treeGrob)。根据您的示例,它以归一化的npc坐标返回它。您可以完全控制线宽,破折号长度和折线长度(尽管不是图案)以及颜色。恐怕这些单位有些随意,这与生产标准相差甚远,但这是相当有效的:
segmentify <- function(x, y, linewidth = 1, dash_len = 1,
break_len = 1, col = "black")
{
linewidth <- 0.002 * linewidth
dash_len <- 0.01 * dash_len
break_len <- 0.04 * break_len
if(length(y) != length(x))
stop("x and y must be the same length")
if(!is.numeric(x) | !is.numeric(y))
stop("x and y must be numeric vectors")
if(length(x) < 2)
stop("Insufficient x, y pairs to make line.")
x <- scales::rescale(x)
y <- scales::rescale(y)
n_dashes <- 0
skip_len <- break_len + dash_len
df <- list()
for(i in seq_along(x)[-1])
{
x_diff <- x[i] - x[i - 1]
y_diff <- y[i] - y[i - 1]
seg_len <- sqrt(x_diff^2 + y_diff^2)
seg_prop <- skip_len / seg_len
dist_from_start <- n_dashes * skip_len
prop_start <- dist_from_start/seg_len
x_start <- x[i-1] + prop_start * x_diff
y_len <- y_diff * seg_prop
x_len <- x_diff * seg_prop
y_start <- y[i-1] + prop_start * y_diff
n_breaks <- (seg_len - dist_from_start)/skip_len
n_dashes <- (n_dashes + n_breaks) %% 1
n_breaks <- floor(n_breaks)
if(n_breaks)
{
df[[length( df) + 1]] <- data.frame(
x = seq(x_start, x[i], by = x_len),
y = seq(y_start, y[i], by = y_len)
)
df[[length( df)]]$theta <-
atan(rep(y_diff/x_diff, length( df[[length( df)]]$x)))
}
}
df <- do.call(rbind, df)
df$x1 <- df$x + sin( df$theta) * linewidth + cos(df$theta) * dash_len
df$x2 <- df$x + sin( df$theta) * linewidth - cos(df$theta) * dash_len
df$x3 <- df$x - sin( df$theta) * linewidth - cos(df$theta) * dash_len
df$x4 <- df$x - sin( df$theta) * linewidth + cos(df$theta) * dash_len
df$y1 <- df$y - cos( df$theta) * linewidth + sin(df$theta) * dash_len
df$y2 <- df$y - cos( df$theta) * linewidth - sin(df$theta) * dash_len
df$y3 <- df$y + cos( df$theta) * linewidth - sin(df$theta) * dash_len
df$y4 <- df$y + cos( df$theta) * linewidth + sin(df$theta) * dash_len
do.call(grid::grobTree, lapply(seq(nrow(df)), function(i) {
grid::polygonGrob(c(df$x1[i], df$x2[i], df$x3[i], df$x4[i]),
c(df$y1[i], df$y2[i], df$y3[i], df$y4[i]),
gp = gpar(col = "#00000000", lwd = 0, fill = col))
}))
}
使用起来相当简单
set.seed(2)
x <- 1:10
y <- rnorm(10)
grid::grid.newpage()
grid::grid.draw(segmentify(x, y))
在不影响间距的情况下更改线宽就像这样:
grid::grid.newpage()
grid::grid.draw(segmentify(x, y, linewidth = 3))
您可以像这样控制间距和颜色:
grid::grid.newpage()
grid::grid.draw(segmentify(x, y, linewidth = 2, break_len = 0.5, col = "forestgreen"))
答案 1 :(得分:6)
好的,在艾伦(Allan)的鼓励下,我自己画东西并没有那么糟糕,我决定也可以尝试解决这个问题。这样做是我在尝试避免此问题时要避免的事情,但这可能对其他人有所帮助。
我采用的方法略有不同,主要区别在于(1)我们保留折线而不是转换为多边形;(2)我对三角学不太满意,因此我使用approxfun()
来插值line和(3)我们将使用绝对单位而不是相对单位,因此在调整设备大小时不会感到尴尬。
首先,由于我打算在自定义geom函数中使用它,所以我的目标是创建一个grob结构,该结构将易于粘贴到geom的draw方法的末尾。您可以给它一个grob或grob的参数。它更改了grob的类,稍后将变得有用,它删除了linetype参数并添加了破折号和间断信息。
library(grid)
library(scales)
linetypeGrob <- function(x, ..., dashes = 1, breaks = 1) {
if (!inherits(x, "polyline")) {
x <- polylineGrob(x, ...)
}
class(x)[[1]] <- "linetypeGrob"
x$gp$lty <- NULL
x$dashes <- dashes
x$breaks <- breaks
x
}
现在,如上所述,我们将回到课堂上。关于自定义grob类的整洁之处在于,您可以在绘制它们之前就对其进行拦截,以便进行最新更改。为此,我们在网格中的makeContext
函数中编写了一个S3方法,进行了相关更改。我知道这是一个很长的函数,但是我试图通过插入说明我要做什么的注释来使跟踪变得更容易。
makeContext.linetypeGrob <- function(x) {
# Sort out line IDs
id <- x$id
if (is.null(id)) {
if (is.null(x$id.lengths)) {
id <- rep(1L, length(x$x))
} else {
id <- rep(seq_along(x$id.lengths), x$id.lengths)
}
}
# Delete previous line IDs
x$id <- NULL
x$id.lengths <- NULL
# Take dashes and breaks parameters out of the old grob
dashes <- x$dashes
x$dashes <- NULL
breaks <- x$breaks
x$breaks <- NULL
# Convert to absolute units
newx <- convertX(x$x, "mm", TRUE)
newy <- convertY(x$y, "mm", TRUE)
# Express lines as points along a cumulative distances
dist <- sqrt(diff(newx)^2 + diff(newy)^2)
cumdist <- cumsum(c(0, dist))
# Take new lines as a sequence along the cumulative distance
starts <- seq(0, max(cumdist), by = (dashes + breaks))
ends <- seq(dashes, max(cumdist), by = (dashes + breaks))
if (length(ends) == length(starts) - 1) {
# Case when the end actually should have gone beyond `max(cumdist)`
ends <- c(ends, max(cumdist))
}
# Set index for graphical parameters
gp_i <- findInterval(starts, cumdist[cumsum(rle(id)$lengths)]) + 1
# Basically dealing with elbow pieces a bit
# Find mismatches between the original segments that starts and ends fall on
start_id <- findInterval(starts, cumdist)
end_id <- findInterval(ends, cumdist)
mismatch <- which(start_id != end_id)
# Insert elbow pieces
starts <- c(starts, cumdist[end_id[mismatch]])
starts <- starts[{o <- order(starts)}] # Need the order for later
ends <- sort(c(ends, cumdist[end_id[mismatch]]))
# Join elbow pieces
new_id <- seq_along(start_id)
if (length(mismatch)) {
i <- rep_len(1, length(new_id))
i[mismatch] <- 2
new_id <- rep(new_id, i)
}
# Seperate lines with different IDs
keepfun <- approxfun(cumdist, id)
keep <- (keepfun(starts) %% 1) == 0 & (keepfun(ends) %% 1) == 0
# Interpolate x
xfun <- approxfun(cumdist, newx)
x0 <- xfun(starts[keep])
x1 <- xfun(ends[keep])
# Interpolate y
yfun <- approxfun(cumdist, newy)
y0 <- yfun(starts[keep])
y1 <- yfun(ends[keep])
# Expand graphic parameters by new ID
x$gp[] <- lapply(x$gp, function(x){
if (length(x) == 1) {
return(x)
} else {
x[as.integer(gp_i)]
}
})
# Put everything back into the grob
x$x <- unit(as.vector(rbind(x0, x1)), "mm")
x$y <- unit(as.vector(rbind(y0, y1)), "mm")
x$id <- as.vector(rbind(new_id[keep], new_id[keep]))
class(x)[[1]] <- "polyline"
x
}
最后,为了演示它的工作原理,我将使用这个新grob绘制一些虚拟数据。您可能会像绘制普通的折线图一样使用它。
set.seed(100)
x <- c(cumsum(rnorm(10)), cumsum(rnorm(10)))
y <- c(cumsum(rnorm(10)), cumsum(rnorm(10)))
id <- rep(c(1, 2), each = 10)
gp <- gpar(lwd = c(2, 10), lineend = "butt",
col = c("magenta", "blue"))
grob <- linetypeGrob(scales::rescale(x),
scales::rescale(y),
id = id, gp = gp, dashes = 5, breaks = 2)
grid.newpage(); grid.draw(grob)
如果我调整设备的大小,您会看到破折号的长度保持相等: