在r中指定颜色和标签轴的散点图

Question

I have following data and plot:

pos <- rep(1:2000, 20)
xv =c(rep(1:20, each = 2000))
# colrs <- unique(xv)
colrs <- xv # edits 
yv =rnorm(2000*20, 0.5, 0.1)

xv   = lapply(unique(xv), function(x) pos[xv==x])
to.add = cumsum(sapply(xv, max) + 1000)

bp <- c(xv[[1]], unlist(lapply(2:length(xv), function(x) xv[[x]] + to.add[x-1])))
plot (bp,yv, pch = "*", col = colrs)

I have few issues in this plot I could not figure out.

(1) I want to use different color for different group or two different color for different groups (ie xv), but when I tried color function in terms to be beautiful mixture. Although I need to highlight some points (for example bp 4000 to 4500 for example with blue color)

(2) Instead of bp positions I want to put a tick mark and label with the group.

Thank you, appreciate your help.

Edits: with help of the following answer (with slight different approach in case I have unbalanced number in each group will work) I could get the similar plot. But still question remaining regarding colors is what if I want to use two alternate colors in alternate group ?

Answer 1

You can solve your colour issue by repeating the colour index however many times each group has a point plotted, like so:

plot (bp,yv, pch = "*", col = rep(colrs,each=2000))

The default colour palette (see ?palette or palette() ) will wrap around itself and you might want to specify your own to get 20 distinct colours.

To relabel the x axis, try plotting without the axis and then specifying the points and labels manually.

plot (bp,yv, pch = "*", col = rep(colrs,each=2000),xaxt="n")
axis(1,at=seq(1000,58000,3000),labels=1:20)

If you are trying to squeeze a lot of labels in there, you might have to shrink the text ( cex.axis )or spin the labels 90 degrees ( las=2 ).

plot (bp,yv, pch = "*", col = rep(colrs,each=2000),xaxt="n")
axis(1,at=seq(1000,58000,3000),labels=1:20,cex.axis=0.7,las=2)

Result:

Answer 2

One way is you could use a nested ifelse .
I'm still learning R , but one way it could be done would look something like:

plot(whatev$x, whatev$y, col=ifelse(xv<2000,red,ifelse(2000<xv & xv<4000,yellow,blue)))  

You could nest as many of these as you want to have specificity on the colors and the intervals. The ifelse command is of form ifelse(TEST, True, False) .

A simpler way would be to use the unique groups in xv to assign rainbow colors.

colrs=rainbow(length(unique(xv)))  #Or colrs=rainbow(length(xv)) if xv is unique.
plot(whatev$x, whatev$y, col=colrs)

I hope I got all that right. I'm still learning R myself.

Answer 3

I'm going to go out on a limb and guess that your real data are something like 2000 values of things from 20 different groups. For instance, heights of 2000 plants of 20 different species. In such a case, you might want to look at the dotplot() function (or as illustrated below, dotplot.table() ) in the lattice package.

Generate matrix of hypothetical values:

set.seed(1)

myY <- sapply( seq_len(20), function(x) rnorm(2000, x^(1/3)))

Transpose matrix to get groups as rows

myY <- t(myY)

Provide names of groups to matrix:

dimnames(myY)[[1]]<-paste("group", seq_len(nrow(myY)))

Load lattice package

library(lattice)

Generate dotplot

dotplot(myY, horizontal = FALSE, panel = function(x, y, horizontal, ...) {
  panel.dotplot(x = x, y = y, horizontal = horizontal, jitter.x = TRUE,
    col = seq_len(20)[x], pch = "*", cex = 1.5)
  }, scales = list(x = list(rot = 90))
)

Which looks like (with unfortunate y-axis labeling):

Answer 4

Seeing that @JohnCLK is requesting a way of colouring by values on the x axis, I tried these demos in ggplot2 -- each uses a dummy variable that is coded based on values or ranges to be highlighted in the other variables.

So, first set up the data, as in the question:

pos <- rep(1:2000, 20)
xv <- c(rep(1:20, each = 2000))
yv <- (2000*20, 0.5, 0.1)
xv <- lapply(unique(xv), function(x) pos[xv==x])
to.add <- cumsum(sapply(xv, max) + 1000)
bp <- c(xv[[1]], unlist(lapply(2:length(xv), function(x) xv[[x]] + to.add[x-1])))

Then load ggplot2 , prepare a couple of utility functions, and set the default theme:

library("ggplot2")

make.png <- function(p, fName) {
    png(fName, width=640, height=480, units="px")
    print(p)
    dev.off()
}

make.plot <- function(df) {
    p <- ggplot(df, 
                aes(x = bp,
                    y = yv, 
                    colour = highlight))
    p <- p + geom_point()
    p <- p + opts(legend.position = "none")
    return(p)
}

theme_set( theme_bw() )

Draw a plot which highlights values in a defined range on the vertical axis:

# highlight a horizontal band
df <- data.frame(cbind(bp, yv))
df$highlight <- 0
df$highlight[ df$yv >= 0.4 & df$yv < 0.45 ] <- 1
p <- make.plot(df)
print(p)
make.png(p, "demo_horizontal.png")

Next draw a plot which highlights values in a defined range on the x axis, a vertical band:

# highlight a vertical band
df$highlight <- 0
df$highlight[ df$bp >= 38000 & df$bp < 42000 ] <- 1
p <- make.plot(df)
print(p)
make.png(p, "demo_vertical.png")

And finally draw a plot which highlights alternating vertical bands, by x value:

# highlight alternating bands
library("gtools")
alt.band.width <- 2000
df$highlight <- as.integer(df$bp / alt.band.width)
df$highlight <- ifelse(odd(df$highlight), 1, 0)
p <- make.plot(df)
print(p)
make.png(p, "demo_alternating.png")

Hope this helps; it was good practice anyway.