Scott,
you may want to have a look at gstat::idw0 , which expresses the idw
problem in a hand full of expressions, essentially
idw0 = function (data, newdata, y, idp = 2) {
s = coordinates(data)
s0 = coordinates(newdata)
D = 1/(spDists(s0, s)^idp)
sumD = apply(D, 1, sum)
D
Hello, I am trying to get inverse distance weights to estimate values on a
regular grid from a set of data points, over a sequence of times. The
locations of the data points don't vary with time, but their values will with
each instance, and in general some are NA. I want to determine the
Also take a look at using raster:: clusterR() in combination with calc()
to use multiple cores. This works well if your your calculation function
does not require neighboring cells.
--Mel.
On 04/07/2017 09:50 AM, Benjamin Leutner wrote:
You could stick to the native raster format (grd), in
You could stick to the native raster format (grd), in which case calc()
writes to your final file directly.
Of course that doesn't change the file size issue, but saves you the
translation step to geotiff.
For the file size you could consider restricting the datatype to integer
(see
