Paolo: at a first glance I was persuaded you would perform exploratory analysis between two sets.
The same concepts expressed by Roger Bivand about mapping lattice matrices apply to scatterplots. In case you would perform exploratory analysis on the data I suggest hexagon binning to make quick plots of one var versus another one. Then you could add regression and/or LOWESS lines to the plot: look at: http://cran.r-project.org/web/packages/hexbin/index.html Enjoy! Duccio ------------------------------ > > Message: 3 > Date: Wed, 22 Feb 2012 06:54:32 -0800 (PST) > From: Roger Bivand <roger.biv...@nhh.no> > Subject: [GRASS-user] Re: spgrass6 > To: grass-user@lists.osgeo.org > Message-ID: <1329922472770-4495201.p...@n6.nabble.com> > Content-Type: text/plain; charset=us-ascii > > Just 2k may mean 4 million rectangles. R display is vector, hard-copy, with > some recent support for raster grids when the rectangles are in fact > square. > As has been said, the graphics engine is not designed for fast screen > output, but for scientific statistical graphics. > > spplot uses lattice graphics, which are slower anyway, but analytically > more > powerful. For me running levelplot() - the internals of spplot - on a 2k by > 2k matrix takes 2 seconds, but output to a png file using cairo takes 70 > seconds. > > Using the improved raster graphics handling for square cells with image() > rather than spplot() and useRaster=TRUE - equivalent to > image.SpatialGridDataFrame() and useRasterImage=TRUE with the same matrix > takes 1.2 seconds on x11/cairo. You didn't say which version of R you are > using - the raster graphics facilities have been improved recently. > > Did you try using image() instead of spplot() if your cells are square, and > if rasterImage() is available in your version of R? > > Roger > >
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