On Mon, 17 Aug 2009, Markus Neteler wrote:
On Mon, Aug 17, 2009 at 9:33 AM, Roger Bivand<[email protected]> 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.
In x11() to open the screen graphics device - by default it opens by
itself with type="cairo" when needed, you you have to open it manually
with the non-default type, or use use X11.options() to have the
automatically opened devices used "Xlib". Generally, "cairo" is
preferable, but slower. I'd probably leave "cairo", and use hexbin()
instead.
Roger
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
--
Roger Bivand
Economic Geography Section, Department of Economics, Norwegian School of
Economics and Business Administration, Helleveien 30, N-5045 Bergen,
Norway. voice: +47 55 95 93 55; fax +47 55 95 95 43
e-mail: [email protected]
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