如何在R中绘制分层散点图？

Question

我正在学习R，并希望绘制一个大型数据帧（~55000行）的散点图。我正在使用scatterplot中的car：

library(car) 
d=read.csv("patches.csv", header=T)
scatterplot(energy ~ homogenity | label, data=d, 
    ylab="energy", xlab="homogenity ", 
    main="Scatter Plot", 
    labels=row.names(d))

其中patches.csv包含数据框（下方）

我想以不同的方式显示两个label集。由于数据量很大，绘图非常密集，因此我得到了右下方的结果（主要是红色数据可见）。图像需要一段时间才能渲染，所以在隐藏在最终图表之前，我可以看到黑色标记数据（左下方）。

我可以控制R先用红色绘制数据，还是有更好的方法来实现我的目标？

以下是我的数据示例：

label,channel,x,y,contrast,energy,entropy,homogenity
1,21,460,76,0.991667,0.640399,0.421422,0.939831
1,22,460,76,0.0833333,0.62375,0.364379,0.969445
1,23,460,76,0.129167,0.422908,0.589938,0.935417
1,24,460,76,0,1,0,1
1,25,460,76,0,1,0,1
1,26,460,76,0.0875,0.789627,0.253649,0.967361
1,27,460,76,2.4,0.528516,0.700859,0.845558
1,28,460,76,0.120833,0.562066,0.392998,0.945139
1,29,460,76,0.0125,0.975234,0.0329461,0.99375
1,30,460,76,0,1,0,1
1,31,460,76,0.1625,0.384662,0.5859,0.929861
0,0,483,82,0.404167,0.309505,0.61573,0.947222
0,1,483,82,0.0166667,0.728559,0.221967,0.991667
0,2,483,82,0,1,0,1
0,3,483,82,0.416667,0.327083,0.644057,0.940972
0,4,483,82,0.0208333,0.919054,0.0940364,0.989583
0,5,483,82,0.416667,0.327083,0.644057,0.940972
0,6,483,82,0,1,0,1
0,7,483,82,0.0333333,0.794479,0.192471,0.983333
0,8,483,82,0,1,0,1
0,9,483,82,0,1,0,1
0,10,483,82,0.0208333,0.958984,0.0502502,0.989583

Answer 1

如果您想更改着色的顺序，请将参数col=2:1传递给scatterplot，然后您将在黑色之前绘制红色。您可以使用alpha包中的scales函数使您的点半透明（它采用颜色矢量和Alpha值，使每种颜色的密度不同）。

## More data
d <- data.frame(homogeneity=(x=rnorm(10000, 0.85, sd=0.15)),
                label=factor((lab=1:2)),
                energy=rnorm(10000, lab^1.8*x^2-lab, sd=x))

library(car)
library(scales)         # for alpha
opacity <- c(0.3, 0.1)  # opacity for each color
col <- 1:2              # black then red
scatterplot(energy ~ homogeneity | label, data=d, 
            ylab="energy", xlab="homogenity ", 
            main=paste0(palette()[col], "(", opacity, ")", collapse=","),
            col=alpha(col, opacity),
            labels=row.names(d))

Answer 2

与bunk用alpha说的相似，

如果你有很多分数，那么单个分数的实际识别就不再有意义了。相反，您可能想要表示密度。使用smoothScatter(x,y)并使用通常的points(morex,morey)覆盖突出显示的点。您显然知道如何使用点（与绘图相同的参数），因此您很容易实现，并且您需要的知识非常少。