I am trying to calculate local quantiles with the raster R package. But am not able to generate sensible results.
This is a minimal example that produces the odd results:
library(raster)
set.seed(100)
n <- 5
# create a raster object
r <- raster::raster( matrix(rnorm(n^2),n,n))
# create a weight matrix
W <- matrix(1,nrow=3,ncol=3)
# create a weight matrix
rLocalKDE2 <- raster::focal(r,W,fun=stats::quantile,probs=0.3)
The as.matrix function of the two raster images produces:
> as.matrix(r)
[,1] [,2] [,3] [,4] [,5]
[1,] 1.449469 19.5963292 -2.4142891 -1.7028303 -8.851035
[2,] 1.049408 -0.6686213 -0.3880794 0.7489177 -1.282491
[3,] -6.028731 2.3172630 1.2115319 2.0829121 -8.260212
[4,] 0.179009 -6.7879331 3.0286532 2.1160440 -1.006479
[5,] 10.087954 0.5925101 -0.9240929 -1.4685703 3.899903
> as.matrix(rLocalKDE2)
[,1] [,2] [,3] [,4] [,5]
[1,] NA NA NA NA NA
[2,] NA -6.028731 -2.414289 -8.851035 NA
[3,] NA -6.787933 -6.787933 -8.260212 NA
[4,] NA -6.787933 -6.787933 -8.260212 NA
[5,] NA NA NA NA NA
This result seems quite odd, given that
stats::quantile(as.matrix(r)[2:4,2:4],probs=0.3) returns 0.06671944.
I am running R 3.3.1 from brew on OS X 10.11.6 with raster 2.5-8.
Your formulation of the function is not correct, as the probs argument is defined outside the function and passed on as additional argument to focal and ignored. In effect you got the 0 percentile returned. See below for a corrected version:
library(raster)
set.seed(100)
n <- 5
r <- raster::raster( matrix(rnorm(n^2),n,n))
W <- matrix(1,nrow=3,ncol=3)
# create a weight matrix
k <- raster::focal(r, W, fun=function(x) stats::quantile(x,probs=0.3))
as.matrix(k)
[,1] [,2] [,3] [,4] [,5]
[1,] NA NA NA NA NA
[2,] NA -0.1525472 -0.1327071 -0.13270706 NA
[3,] NA -0.1525472 -0.5046161 -0.08247059 NA
[4,] NA -0.1525472 -0.2965709 -0.07162857 NA
[5,] NA NA NA NA NA
>