ClusterR with multiple raster stacks

Question

Here is an example that raster library provides for using clusterR and overlay functions:

library(raster)
beginCluster()
r <- raster()
r[] <- 1:ncell(r)
s <- stack(r, r*2, r*3)
f2 <- function(d,e,f) (d + e) / (f * param)
param <- 122
ov <- clusterR(s, overlay, args=list(fun=f2), export='param')

I want to know how to run that function if I have multiple raster stacks:

s <- stack(r, r*2, r*3)
s2 <- stack(r*2, r*3, r*4)
s3 <- stack(r*3, r*4, r*5)

I want something like this (d,e,f in function f2 are each layer in s, s2 and s3):

ov <- clusterR(s,s2,s3, overlay, args=list(fun=f2), export='param')

Answer 1

First I would create a dummy raster layer in your stack holding the paramvalue. Thus, the operations can be vectorized:

p <- 122
rp <- r
rp[] <- p
s <- stack(s, rp)
s2 <- stack(s2, rp)
s3 <- stack(s3, rp)

Then you change your function like this:

f2 <- function(x) (x[[1]] + x[[2]]) / (x[[3]] * x[[4]])

Thus, the layers of the individual stack x are referred to correctly. The 4th layer is the param value (here p)

Then you create a list of layer stacks:

stackList <- list(s, s2, s3)

then you lapply the clusterR function.

ov <- lapply(stackList, function(x){clusterR(x, fun = f2, progress = "text")})

ov will then be a list of your overlaid layers.