R 具有X轴和Y轴色标的散点图

我尝试用多个点（>150）绘制散点图。目标是在图形的某些区域区分点。我要寻找的是一种在x轴和y轴上有两个色标的方法（每个色标一个）。基本上，我在寻找这样的东西：

每个独特的点应该是各个刻度颜色的混合。到目前为止，我尝试的是使用ggplot的散点图。我试过设置颜色属性，但它会指定自己的坐标。它也不适用于我的限制，因为我必须创建散点图的单独绘图（简而言之，放大了左上角、右上角、左下角、右下角的绘图）。如果我将xlim和ylim设置为我自己喜欢的附加绘图，我得到的只是一个裁剪，这会导致在绘图边缘剪切其他点及其文本。我不能简单地创建一个单独的图，因为我需要点在我的整体图和更具体的图（单色）上是相同的颜色

我将十六进制颜色转换为十进制，然后将特定的十进制颜色添加到一起，然后将其转换回十六进制。理论上，它在x轴上应该是白色到黄色，在y轴上应该是白色到蓝色。随着x和y点的增加，颜色应变得更绿。正如你所看到的，事情并没有那么简单。我还没有遇到过任何可以使用2轴颜色的库

总而言之，我需要能够有两个轴的颜色，以赋予点独特的颜色，并有一种方法来创建额外的绘图，将有确切的一些颜色只是在一个更放大的画布上

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如果有人能提供帮助，我们将不胜感激。

在这里，您有了第一种使用基本图形解决第一个问题的方法（混合两种颜色渐变）

##x轴使用白色->黄色，y轴使用白色->蓝色
选择颜色对不起，我不太精通RGB。如果我想让x轴从白色变为黄色，y轴从白色变为蓝色，我该怎么做呢？谢谢你的帮助。我不明白你为什么想要这样的阴谋。毕竟，您可以两次（通过颜色和位置）表示相同的信息。图形中最感兴趣的部分位于某个位置。通过隔离颜色/区域，很容易查看它。
png("image.png", width = 2000, height = 1500, res = 85);
ggplotXY <- ggplot(scatterPlotData, aes(x=x, y=y, colour=labels, label=labels)) +
geom_point() +
geom_text(hjust=0, vjust=0)
ggplotXY
dev.off()

png("image.png", width = 2000, height = 1500, res = 85);
ggplotXY <- ggplot(scatterPlotData, aes(x=x, y=y, colour=labels, label=labels)) +
geom_point() +
geom_text(hjust=0, vjust=0) +
coord_cartesian(xlim=c(0,100), ylim=c(0, 2.5))
ggplotXY
dev.off()

png("image.png", width = 2000, height = 1500, res = 85);
ggplotXYColor <- ggplot(scatterPlotData, aes(x=x, y=y, label=labels)) +
geom_point(colour=scatterPlotData$scatterPointColour)
ggplotXYColor
dev.off()

  [1] "#2276c6" "#224dd0" "#201893" "#22459f" "#21580f" "#219998" "#201893"
  [8] "#216871" "#22459f" "#201893" "#2276c6" "#22459f" "#22353d" "#201893"
 [15] "#225602" "#21cabe" "#2178d3" "#21eb83" "#21eb83" "#201893" "#201893"
 [22] "#22978b" "#2276c6" "#301054" "#201893" "#301054" "#225e33" "#228f59"
 [29] "#226664" "#220c47" "#21eb83" "#228f59" "#227ef7" "#227ef7" "#226e95"
 [36] "#21c28d" "#22459f" "#228f59" "#223d6e" "#221caa" "#22459f" "#226e95"
 [43] "#225602" "#221caa" "#21d2f0" "#222d0c" "#22459f" "#201893" "#2020c4"
 [50] "#210623" "#21a1c9" "#201893" "#228f59" "#201893" "#201893" "#221caa"
 [57] "#220c47" "#201893" "#22a7ed" "#101893" "#22c080" "#201893" "#2276c6"
 [64] "#201893" "#201893" "#21d2f0" "#222d0c" "#21c28d" "#225602" "#226664"
 [71] "#226e95" "#201893" "#201893" "#21b22b" "#2020c4" "#21cabe" "#21f3b4"
 [78] "#22d0e2" "#201893" "#21c28d" "#21fbe5" "#220c47" "#225602" "#230209"
 [85] "#226664" "#210e55" "#211eb7" "#2170a2" "#201893" "#221caa" "#220c47"
 [92] "#21f3b4" "#21fbe5" "#201893" "#201893" "#201893" "#224dd0" "#247add"
 [99] "#201893" "#23fffc" "#25db1d" "#24188f" "#245a18" "#2449b6" "#24a3d3"
[106] "#201893" "#2451e7" "#24624a" "#24830e" "#2020c4" "#201893" "#201893"
[113] "#25b228" "#25eb80" "#23ced5" "#244185" "#24ed8d" "#243123" "#2449b6"
[120] "#201893" "#273b5e" "#201893" "#264dcd" "#2420c1" "#2578d0" "#264dcd"
[127] "#251eb3" "#22c8b1" "#22c080" "#22f1a7" "#249370" "#251eb3" "#2428f2"
[134] "#2428f2" "#249ba1" "#201893" "#2020c4" "#201893" "#244185" "#2472ac"
[141] "#2449b6" "#247add" "#201893" "#244185" "#243123" "#249370" "#24b435"
[148] "#2020c4" "#248b3f" "#2020c4"

## use white->yellow for the x-axis and white->blue for the y-axis
chooseColors <- function(x, y) {
  x <- 1-x/max(x)
  y <- 1-y/max(y)
  return(rgb(green=y, red=y, blue=x))
}


## example values for the whole range
values <- expand.grid(1:100, 1:100)

## plot it
plot(values, col=chooseColors(values[,1], values[,2]), pch=16)

set.seed(1)
n <- 50
values <- cbind(sample(1:15, size=n, replace=TRUE), sample(1:15, size=n, replace=TRUE))

## plot it
plot(values, col=chooseColors(values[,1], values[,2]), pch=16)