[GRASS-stats] Scatterplot "thinning" (points reduction)?

[Markus Neteler]

On Mon, Aug 17, 2009 at 9:33 AM, Roger Bivand<Roger.Bivand at nhh.no> wrote:
> On Sun, 16 Aug 2009, Markus Neteler wrote:
>
>> Hi,
>>
>> I am plotting elevation against temperature and have the problem that
>> including all points leads to heavy slow graphs... Reducing the raster
>> resolution is not a solution since it does not maintain the
>> characteristics
>> of the graph (since GRASS is using nearest neighbor).
>
> One point initially. I'm assuming that you are using a Linux platform - on
> this platform, there is an order of magnitude speedup if you plot on screen
> without "cairo", the default x11 type= - try using type="Xlib", which is
> much faster but not so refined.

(yes, Linux)
I have searched around bit I am not entirely sure to which function
this type parameter belongs.

> Given that, consider the cex= argument for varying symbol size, and maybe
> the pch="." possibility for using a single pt. point. They still all get
> drawn, so there is no time saving, but they may be more visible.

I am currently plotting like this:
plot(data$dem ~ data$raw)
points(data$dem ~ data$filt2, col="yellow", cex=0.5, pch=3)
points(data$dem ~ data$rst, col="green", xlab="LST value [°C]",
ylab="elevation [m]", pch=2)
abline(lm(data$dem ~ data$raw))
abline(lm(data$dem ~ data$filt2), col="yellow")
abline(lm(data$dem ~ data$rst), col="green", xlab="LST value [°C]",
ylab="elevation [m]")

So the backgound (largest) cloud comes in back circles,
the interim (smaller) in yellow crosses with many of them in the circles,
and the upper point could (smallest) in green triangles.
I guess the real problem are the 826896 * 3 points in the plot.

> For very large data sets, consider hexbin() in the hexbin package - I'm not
> sure how best to display three data sets. For single scatterplots, it is
> very powerful. Maybe contours of 2D densities of the extra data sets could
> be overlaid over a base hexbin plot? There is an informative vignette in
> hexbin.

Oh, this is interesting! Thanks,
Markus