Hi:
I can think of a couple: (1) size reduction of the points; (2) alpha
transparency; (3) (1) + (2)
>From your original plot in base graphics, I reduced cex to 0.2 and it didn't
look too bad:
plot(rnorm(x,mean=19),rnorm(x),col=3,xlim=c(16,24), cex = 0.2)
points(rnorm(x,mean=20),rnorm(x),col=1, cex = 0.2)
points(rnorm(x,mean=21),rnorm(x),col=2, cex = 0.2)
AFAIK, base graphics doesn't have alpha transparency available, but the
ggplot2 package does. One approach is to adjust the alpha transparency on
default size points; another is to combine reduced point size with alpha
transparency. Here is your example rehashed for ggplot2.
require(ggplot2)
d <- data.frame(x1 = rnorm(10000, mean = 19), x2 = rnorm(10000, mean = 20),
x3 = rnorm(10000, mean = 21), x = rnorm(10000))
# Basically stacking x1 - x3, creating two new vars named variable and value
dm <- melt(d, id = 'x') # from reshape package, loads with ggplot2
# Alpha transparency is set to a low level with default point size,
# but the colors in the legend are muted by the level of transparency
ggplot(dm, aes(x = x, y = value, colour = variable)) + theme_bw() +
geom_point(alpha = 0.05) +
scale_colour_manual(values = c('x1' = 'black',
'x2' = 'red', 'x3' = 'green'))
# A tradeoff is to reduce the point size and increase alpha a bit, but these
changes will
# also be reflected in the legend.
ggplot(dm, aes(x = x, y = value, colour = variable)) + theme_bw() +
geom_point(alpha = 0.15, size = 1) +
scale_colour_manual(values = c('x1' = 'black',
'x2' = 'red', 'x3' = 'green'))
You may well find the legend to be useless for this example, so to get rid
of it,
ggplot(dm, aes(x = x, y = value, colour = variable)) + theme_bw() +
geom_point(alpha = 0.15, size = 1) +
scale_colour_manual(values = c('x1' = 'black',
'x2' = 'red', 'x3' = 'green')) +
opts(legend.position = 'none')
The nice thing about the ggplot2 graph is that you can adjust the point size
and alpha transparency to your tastes. The default point size is 2 and the
default alpha = 1 (no transparency).
HTH,
Dennis
On Wed, Mar 30, 2011 at 10:04 PM, Samuel Dennis <sjdenn...@gmail.com> wrote:
> I have a very large dataset with three variables that I need to graph using
> a scatterplot. However I find that the first variable gets masked by the
> other two, so the graph looks entirely different depending on the order of
> variables. Does anyone have any suggestions how to manage this?
>
> This code is an illustration of what I am dealing with:
>
> x <- 10000
> plot(rnorm(x,mean=20),rnorm(x),col=1,xlim=c(16,24))
> points(rnorm(x,mean=21),rnorm(x),col=2)
> points(rnorm(x,mean=19),rnorm(x),col=3)
>
> gives an entirely different looking graph to:
>
> x <- 10000
> plot(rnorm(x,mean=19),rnorm(x),col=3,xlim=c(16,24))
> points(rnorm(x,mean=20),rnorm(x),col=1)
> points(rnorm(x,mean=21),rnorm(x),col=2)
>
> despite being identical in all respects except for the order in which the
> variables are plotted.
>
> I have tried using pch=".", however the colours are very difficult to
> discern. I have experimented with a number of other symbols with no real
> solution.
>
> The only way that appears to work is to iterate the plot with a for loop,
> and progressively add a few numbers from each variable, as below. However
> although I can do this simply with random numbers as I have done here, this
> is an extremely cumbersome method to use with real datasets.
>
> plot(1,1,xlim=c(16,24),ylim=c(-4,4),col="white")
> x <- 100
> for (i in 1:100) {
> points(rnorm(x,mean=19),rnorm(x),col=3)
> points(rnorm(x,mean=20),rnorm(x),col=1)
> points(rnorm(x,mean=21),rnorm(x),col=2)
> }
>
> Is there some function in R that could solve this through automatically
> iterating my data as above, using transparent symbols, or something else?
> Is
> there some other way of solving this issue that I haven't thought of?
>
> Thankyou,
>
> Samuel Dennis
>
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>
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