这里最好的方法是在数据对象中添加一列来表示点的颜色，然后通过过滤更新它的部分。

data<- read.table('sample_data.txtt', header=TRUE, row.name=1)
# Create new column filled with default colour
data$Colour="black"
# Set new column values to appropriate colours
data$Colour[data$col_name2>=3]="red"
data$Colour[data$col_name2<=1]="blue"
# Plot all points at once, using newly generated colours
plot(data$col_name1,data$col_name2, ylim=c(0,5), col=data$Colour, ylim=c(0,10))

它应该是明确的如何适应这一点与更多的颜色和条件的情节。

同样，只指定ifelse()两次也可以：

plot(pos,cn, col= ifelse(cn >= 3, "red", ifelse(cn <= 1,"blue", "black")), ylim = c(0, 10))

最好使用cut（）创建一个新的因子变量，我也使用ggplot2添加了一些选项。

df <- data.frame(
  X1=seq(0, 5, by=0.001),
  X2=rnorm(df$X1, mean = 3.5, sd = 1.5)
)

# Create new variable for plotting
df$Colour <- cut(df$X2, breaks = c(-Inf, 1, 3, +Inf), 
                 labels = c("low", "medium", "high"), 
                 right = FALSE)

### Base Graphics

plot(df$X1, df$X2, 
     col = df$Colour, ylim = c(0, 10), xlab = "POS", 
     ylab = "CS", main = "Plot Title", pch = 21)

plot(df$X1,df$X2, 
     col = df$Colour, ylim = c(0, 10), xlab = "POS", 
     ylab = "CS", main = "Plot Title", pch = 19, cex = 0.5)

# Using `with()` 

with(df, 
     plot(X1, X2, xlab="POS", ylab="CS", col = Colour, pch=21, cex=1.4)
     )

# Using ggplot2
library(ggplot2)

# qplot()
qplot(df$X1, df$X2, colour = df$Colour)

# ggplot()
p <- ggplot(df, aes(X1, X2, colour = Colour)) 
p <- p + geom_point() + xlab("POS") + ylab("CS")
p

p + facet_grid(Colour~., scales = "free")

这是一种使用阈值和相关颜色的查找表来将颜色Map到感兴趣的变量的方法。

# make a grid 'Grd' of points and number points for side of square 'GrdD'
Grd <- expand.grid(seq(0.5,400.5,10),seq(0.5,400.5,10))
GrdD <- length(unique(Grd$Var1))

# Add z-values to the grid points
Grd$z <- rnorm(length(Grd$Var1), mean = 10, sd =2)

# Make a vector of thresholds 'Brks' to colour code z 
Brks <- c(seq(0,18,3),Inf)

# Make a vector of labels 'Lbls' for the colour threhsolds
Lbls <- Lbls <- c('0-3','3-6','6-9','9-12','12-15','15-18','>18')

# Make a vector of colours 'Clrs' for to match each range
Clrs <- c("grey50","dodgerblue","forestgreen","orange","red","purple","magenta")

# Make up lookup dataframe 'LkUp' of the lables and colours 
LkUp <- data.frame(cbind(Lbls,Clrs),stringsAsFactors = FALSE)

# Add a new variable 'Lbls' the grid dataframe mapping the labels based on z-value
Grd$Lbls <- as.character(cut(Grd$z, breaks = Brks, labels = Lbls))

# Add a new variable 'Clrs' to the grid dataframe based on the Lbls field in the grid and lookup table
Grd <- merge(Grd,LkUp, by.x = 'Lbls')

# Plot the grid using the 'Clrs' field for the colour of each point
plot(Grd$Var1,
     Grd$Var2,
     xlim = c(0,400),
     ylim = c(0,400),
     cex = 1.0,
     col = Grd$Clrs,
     pch = 20,
     xlab = 'mX',
     ylab = 'mY',
     main = 'My Grid',
     axes = FALSE,
     labels = FALSE,
     las = 1
)

axis(1,seq(0,400,100))
axis(2,seq(0,400,100),las = 1)
box(col = 'black')

legend("topleft", legend = Lbls, fill = Clrs, title = 'Z')