Re: [R] 2/3d interpolation from a regular grid to another regular grid

From: Scionforbai <scionforbai_at_gmail.com>
Date: Wed, 5 Dec 2007 16:47:34 +0100

> I just read the description in ?Krig in the package fields which says:
> " Fits a surface to irregularly spaced data. "

Yes, that is the most general case. Regular data location is a subset of irregular. Anyway, kriging, just one g, after the name of Danie Krige, the south african statistician who first applied such method for minig survey.

> My problem is simpler

...
> So it is really purely numerical.
...
> I just hoped that R had that already coded ...

Of course R has ... ;) If your grids are really as simple as the example you posted above, and you have a really little variability, all you need is a "moving average", the arithmetic mean of the two nearest points belonging to grid1 and grid2 respectively. I assume that your regularly shaped grids are values stored in matrix objects.

The functions comes from the "diff.default" code (downloading the R source code, I assure, is worth):

my.interp <- function(x, lag = 1)
{

    r <- unclass(x) # don't want class-specific subset methods     i1 <- -1:-lag
    r <- (r[i1] + r[-length(r):-(length(r)-lag+1)])/2     class(r) <- oldClass(x)
    return(r)
}

Finally,

g1 <- apply(grid1val,1,my.interp)
g2 <- apply(grid2val,2,my.interp)

give the interpolations on gridFinal, provided that all gridFinal points are within the grid1 and grid2 ones.

If you want the mean from 4 points, you apply once more with lag=3, cbind/rbind to the result columns/rows o NAs, and you calculate the mean of the points of the two matrixes.
This is the simplest (and quickest) moving average that you can do. For more complicated examples, and for 3d, you have to go a little further, but the principle holds.

ScionForbai



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