Tara, I think you need to 'rasterize' function

library(raster)

r <- raster(ncol=10, nrow=10)
x <- c(-25, -148, 46, 23, 0, -69)
y <- c(-45, 30, 20, -10, 50, -7)
value <- c(1, 2, 3, 4, 5, 6)

# you can do this:
r1 <- rasterize(cbind(x, y), r, value)
plot(r1)

# or
sp <- SpatialPointsDataFrame(cbind(x,y), data.frame(v=value))
r2 <- rasterize(sp, r, 'v')


# or a more "manual" approach
cells <- cellFromXY(r, cbind(x,y))
r[cells] <- value
# safer would be:
# r[cells[!is.na(cells)]] <- value[!is.na(cells)]

This is not in the Bivand et al book ( which was written before the raster
package was released ).

Robert


On Sat, Sep 17, 2011 at 4:48 PM, Tara Bridwell <tarabridwell@gmail.com>wrote:

> I have a dataset that consists of point coordinates and values
> associated with the points.  I want to be able to grid the values, and
> then do calulations using the values using the various raster
> functions.  I am, however, finding this difficult to do.  I have tried
> a number of functions including rasterize, SpatialGridDataFrame, and
> SpatialGridDataFrame but I think I am missing a bit of the theory
> behind this that I can't seem to piece together. I have the Applied
> Spatial Data Analysis (Bivand) but couldn't seem to find an
> appropriate section.  Here is an example data set:
>
> require(raster)
>
> r <- raster(ncol=10, nrow=10)
>
> r[]=1:ncell(r)
>
> x <- c(-45, 30, 20, -10, 50, -7)
>
> y <- c(-25, -148, 46, 23, 0, -69)
>
> value <- c(1, 2, 3, 4, 5, 6)
>
> coord.plus.value <- cbind(x, y, value)
>
> coord.plus.value_sp <- SpatialPoints(coord.plus.value)
>
> >From here I want to plot 'value' using the raster 'r'.
>
> Suggests on how to do this, as well as thoughts on the basic theory I
> seem to be missing (or where in the Bivand book I should be reading
> that I have missed) would be appreciated.
>
> Thank you,
>
> Tara Bridwell
>
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