Thanks heaps for all your help, sorry for the late reply, I'm a bit
overwhelmed by all the possibilities here!

My variables have different lengths which makes automated randomisation
difficult Peter, although not impossible. Thanks for the suggestion of 3D
graphs Nick, I'm not sure how I can make it work with this particular
project but I'll keep it in mind for the future.

I'll try to get this working with transparancy in base graphics (thanks
Claudia and Greg), but if that doesn't cut it I'll have to learn ggplot2 -
which looks like a good idea anyway as I am very impressed with what it can
do. Thankyou Dennis in particular for translating my code into ggplot, this
will be a great help as I get started.

Samuel


On 1 April 2011 05:07, Greg Snow <Greg.Snow@imail.org> wrote:

> Just a note, Base graphics does support transparency as long as the device
> plotting to supports it.
>
> --
> Gregory (Greg) L. Snow Ph.D.
> Statistical Data Center
> Intermountain Healthcare
> greg.snow@imail.org
> 801.408.8111
>
>
> > -----Original Message-----
> > From: r-help-bounces@r-project.org [mailto:r-help-bounces@r-
> > project.org] On Behalf Of Dennis Murphy
> > Sent: Thursday, March 31, 2011 1:36 AM
> > To: Samuel Dennis
> > Cc: R-help@r-project.org
> > Subject: Re: [R] Graph many points without hiding some
> >
> > 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
> > >
> > >        [[alternative HTML version deleted]]
> > >
> > > ______________________________________________
> > > R-help@r-project.org mailing list
> > > https://stat.ethz.ch/mailman/listinfo/r-help
> > > PLEASE do read the posting guide
> > > http://www.R-project.org/posting-guide.html
> > > and provide commented, minimal, self-contained, reproducible code.
> > >
> >
> >       [[alternative HTML version deleted]]
> >
> > ______________________________________________
> > R-help@r-project.org mailing list
> > https://stat.ethz.ch/mailman/listinfo/r-help
> > PLEASE do read the posting guide http://www.R-project.org/posting-
> > guide.html
> > and provide commented, minimal, self-contained, reproducible code.
>

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