如何在R中制作渐变色填充时间序列图

Question

如何用渐变色填充下方(sp)线以下的区域？

这个例子是在Inkscape中绘制的 - 但我需要垂直渐变 - 不是水平的.

从零到正的间隔==从白色到红色.

从零到负的间隔==从白色到红色.

有没有可以做到这一点的包？

我编造了一些源数据....

set.seed(1)
x<-seq(from = -10, to = 10, by = 0.25)
data <- data.frame(value = sample(x, 25, replace = TRUE), time = 1:25)
plot(data$time, data$value, type = "n")
my.spline <- smooth.spline(data$time, data$value, df = 15)
lines(my.spline$x, my.spline$y, lwd = 2.5, col = "blue")
abline(h = 0)

Answer 1

这是一种方法,它在很大程度上依赖于几个R空间包.

基本思路是:

• 绘制一个空图,画布将放置后续元素.(首先执行此操作还可以检索后续步骤中所需的绘图用户坐标.)

• 使用矢量化调用来rect()设置背景颜色.获取颜色渐变的细节实际上是这样做的最棘手的部分.

• 在rgeos中使用拓扑函数首先找到图中的闭合矩形,然后找到它们的补码.在背景清洗上用白色填充绘制补色可以覆盖除多边形内的任何地方的颜色,正如您想要的那样.

• 最后,使用plot(..., add=TRUE),lines(),abline()等放下你想的情节,以显示任何其他细节.

library(sp)
library(rgeos)
library(raster)
library(grid)

## Extract some coordinates
x <- my.spline$x
y <- my.spline$y
hh <- 0
xy <- cbind(x,y)

## Plot an empty plot to make its coordinates available
## for next two sections
plot(data$time, data$value, type = "n", axes=FALSE, xlab="", ylab="")

## Prepare data to be used later by rect to draw the colored background
COL <- colorRampPalette(c("red", "white", "red"))(200)
xx <- par("usr")[1:2]
yy <- c(seq(min(y), hh, length.out=100), seq(hh, max(y), length.out=101))

## Prepare a mask to cover colored background (except within polygons)
## (a) Make SpatialPolygons object from plot's boundaries
EE <- as(extent(par("usr")), "SpatialPolygons")
## (b) Make SpatialPolygons object containing all closed polygons
SL1 <- SpatialLines(list(Lines(Line(xy), "A")))
SL2 <- SpatialLines(list(Lines(Line(cbind(c(0,25),c(0,0))), "B")))
polys <- gPolygonize(gNode(rbind(SL1,SL2)))
## (c) Find their difference
mask <- EE - polys

## Put everything together in a plot
plot(data$time, data$value, type = "n")
rect(xx[1], yy[-201], xx[2], yy[-1], col=COL, border=NA)
plot(mask, col="white", add=TRUE)
abline(h = hh)
plot(polys, border="red", lwd=1.5, add=TRUE)
lines(my.spline$x, my.spline$y, col = "red", lwd = 1.5)

Answer 2

这里是baseR中的一种方法,我们用渐变颜色的矩形填充整个绘图区域,然后用白色填充感兴趣区域的反转.

shade <- function(x, y, col, n=500, xlab='x', ylab='y', ...) {
  # x, y: the x and y coordinates
  # col: a vector of colours (hex, numeric, character), or a colorRampPalette
  # n: the vertical resolution of the gradient
  # ...: further args to plot()
  plot(x, y, type='n', las=1, xlab=xlab, ylab=ylab, ...)
  e <- par('usr')
  height <- diff(e[3:4])/(n-1)
  y_up <- seq(0, e[4], height)
  y_down <- seq(0, e[3], -height)
  ncolor <- max(length(y_up), length(y_down))
  pal <- if(!is.function(col)) colorRampPalette(col)(ncolor) else col(ncolor)
  # plot rectangles to simulate colour gradient
  sapply(seq_len(n),
         function(i) {
           rect(min(x), y_up[i], max(x), y_up[i] + height, col=pal[i], border=NA)
           rect(min(x), y_down[i], max(x), y_down[i] - height, col=pal[i], border=NA)
         })
  # plot white polygons representing the inverse of the area of interest
  polygon(c(min(x), x, max(x), rev(x)),
          c(e[4], ifelse(y > 0, y, 0), 
            rep(e[4], length(y) + 1)), col='white', border=NA)     
  polygon(c(min(x), x, max(x), rev(x)),
          c(e[3], ifelse(y < 0, y, 0), 
            rep(e[3], length(y) + 1)), col='white', border=NA)      
  lines(x, y)
  abline(h=0)
  box()  
}

这里有些例子:

xy <- curve(sin, -10, 10, n = 1000)
shade(xy$x, xy$y, c('white', 'blue'), 1000)

或者使用颜色渐变调色板指定颜色:

shade(xy$x, xy$y, heat.colors, 1000)

并且应用于您的数据,尽管我们首先将点插值为更精细的分辨率(如果我们不这样做,则渐变不会紧跟其穿过零的线).

xy <- approx(my.spline$x, my.spline$y, n=1000)
shade(xy$x, xy$y, c('white', 'red'), 1000)

Answer 3

这是一种骗取ggplot你想要的东西的可怕方法.从本质上讲,我制作了一个巨大的曲线网格.由于无法在单个多边形内设置渐变,因此必须创建单独的多边形,即网格.如果将像素设置得太低,它会很慢.

gen.bar <- function(x, ymax, ypixel) {
  if (ymax < 0) ypixel <- -abs(ypixel)
  else ypixel <-  abs(ypixel)
  expand.grid(x=x, y=seq(0,ymax, by = ypixel))
}

# data must be in x order.
find.height <- function (x, data.x, data.y) {
  base <- findInterval(x, data.x)
  run <- data.x[base+1] - data.x[base]
  rise <- data.y[base+1] - data.y[base]
  data.y[base] + ((rise/run) * (x - data.x[base]))
}

make.grid.under.curve <- function(data.x, data.y, xpixel, ypixel) {
  desired.points <- sort(unique(c(seq(min(data.x), max(data.x), xpixel), data.x)))
  desired.points <- desired.points[-length(desired.points)]

  heights <- find.height(desired.points, data.x, data.y)
  do.call(rbind, 
          mapply(gen.bar, desired.points, heights, 
                 MoreArgs = list(ypixel), SIMPLIFY=FALSE))
}

xpixel = 0.01
ypixel = 0.01
library(scales)
grid <- make.grid.under.curve(data$time, data$value, xpixel, ypixel)
ggplot(grid, aes(xmin = x, ymin = y, xmax = x+xpixel, ymax = y+ypixel, 
                 fill=abs(y))) + geom_rect() 

颜色不是你想要的颜色,但无论如何它可能太慢而不能用于严肃的使用.

Answer 4

使用函数grid和gridSVG包的另一种可能性.

我们通过线性内插生成附加数据点开始,根据由@描述的方法kohske 这里.然后,基本图将由两个单独的多边形组成,一个用于负值,一个用于正值.

在绘制图之后,grid.ls用于显示grobs 的列表,即图的所有构建块.在列表中,我们将(除其他外)找到两个geom_area.polygons; 一个表示值的多边形<= 0,另一个表示值>= 0.

grobs然后使用gridSVG函数操作多边形的填充:使用创建自定义颜色渐变linearGradient,并grobs使用替换填充grid.gradientFill.

这个包的作者之一Simon Potter grob的硕士论文第7章很好地描述了梯度的操纵gridSVG.

library(grid)
library(gridSVG)
library(ggplot2)

# create a data frame of spline values
d <- data.frame(x = my.spline$x, y = my.spline$y)

# create interpolated points
d <- d[order(d$x),]
new_d <- do.call("rbind",
                 sapply(1:(nrow(d) -1), function(i){
                   f <- lm(x ~ y, d[i:(i+1), ])
                   if (f$qr$rank < 2) return(NULL)
                   r <- predict(f, newdata = data.frame(y = 0))
                   if(d[i, ]$x < r & r < d[i+1, ]$x)
                     return(data.frame(x = r, y = 0))
                   else return(NULL)
                 })
)

# combine original and interpolated data
d2 <- rbind(d, new_d)
d2  

# set up basic plot
ggplot(data = d2, aes(x = x, y = y)) +
  geom_area(data = subset(d2, y <= 0)) +
  geom_area(data = subset(d2, y >= 0)) +
  geom_line() +
  geom_abline(intercept = 0, slope = 0) +
  theme_bw()

# list the name of grobs and look for relevant polygons
# note that the exact numbers of the grobs may differ
grid.ls()
# GRID.gTableParent.878
# ...
#   panel.3-4-3-4
# ...
#     areas.gTree.834
#       geom_area.polygon.832 <~~ polygon for negative values
#     areas.gTree.838
#       geom_area.polygon.836 <~~ polygon for positive values

# create a linear gradient for negative values, from white to red
col_neg <- linearGradient(col = c("white", "red"),
                          x0 = unit(1, "npc"), x1 = unit(1, "npc"),
                          y0 = unit(1, "npc"), y1 = unit(0, "npc"))

# replace fill of 'negative grob' with a gradient fill
grid.gradientFill("geom_area.polygon.832", col_neg, group = FALSE)

# create a linear gradient for positive values, from white to red
col_pos <- linearGradient(col = c("white", "red"),
                          x0 = unit(1, "npc"), x1 = unit(1, "npc"),
                          y0 = unit(0, "npc"), y1 = unit(1, "npc"))

# replace fill of 'positive grob' with a gradient fill
grid.gradientFill("geom_area.polygon.836", col_pos, group = FALSE)


# generate SVG output
grid.export("myplot.svg")

您可以轻松地为正多边形和负多边形创建不同的颜色渐变.例如,如果您希望负值从白色变为蓝色,请将col_pos以上内容替换为:

col_pos <- linearGradient(col = c("white", "blue"),
                          x0 = unit(1, "npc"), x1 = unit(1, "npc"),
                          y0 = unit(0, "npc"), y1 = unit(1, "npc"))