R help - Mar 2011 - Graph many points without hiding some

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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On Wed, Mar 30, 2011 at 10:04 PM, Samuel Dennis <sjdennis3 at 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?
Assume you are plotting variables y1, y2, y3 of the same length
against a common x, and you would like to assign colors say c(1,2,3).
You can automate the randomization of order as follows:

n = length(y1);
y = c(y1, y2, y3);
xx = rep(x, 3);
colors = rep(c(1,2,3), c(n, n, n));

order = sample(c(1:(3*n)));

plot(xx[order], y[order], col= colors[order])

I basically turn the y's into a single vector y with the corresponding
values of x stored in xx and the plotting colors, then randomize the
order using the sample function.

HTH,

Peter

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 <sjdennis3@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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