Hi Markus, Can you sample the original maps with v.random + v.what.rast first? Or, after reading in the raster data into R, only compare every nth cell? You can generate a sequence to index every nth cell like this:
s <- seq(from=1, to=n, by=10) Then, subset your spatial data frame like this: spdf[s,] Another approach would be to use a density estimate in parameter space: library(MASS) x <- rnorm(1000) y <- rnorm(1000) dd <- kde2d(x,y) contour(dd) persp(dd, theta=-30, phi=30, d=5) image(dd) Cheers, Dylan On Sun, Aug 16, 2009 at 10:45 AM, Markus Neteler<[email protected]> 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). > > Since I am plotting in many cases one point almost over the other > a reduction should be reasonable - question is how to do that? > > I am speaking about 3 plots in one graph, say "original", "interim" > and "final" (so, one plot() and two points()). > > Any advice welcome, > Markus > _______________________________________________ > grass-stats mailing list > [email protected] > http://lists.osgeo.org/mailman/listinfo/grass-stats > _______________________________________________ grass-stats mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-stats
