Replace in a list rasters with 'NA' values - r

Question

I have a list of raster files in GeoTIFF files, and I've like to remove each file and if one has more than 50% of NA values.
I wanna delete it from the list my new list (f2). In my code:
library(raster)
# example data
r <- raster(ncol=10, nrow=10)
set.seed(0)
# 10 layers
s <- stack(lapply(1:10, function(i) setValues(r, runif(ncell(r)))))
# set about half the values to NA
s[s < .5] <- NA
#Create GeoTIFF for each layer
sl<-1:10
for (i in 1:length(sl)){
writeRaster(s[[i]],filename=paste(sl[i],sep=""),
format="GTiff",datatype="FLT4S",overwrite=TRUE)
}
#Take images in batch
f <- list.files(getwd(), pattern = ".tif")
ras <- lapply(f,raster)
#Remove from my list when I have more than 50% of cells that are NA
class <- vector()
for (j in 1:length(ras)){
i <- cellStats(is.na(ras[[j]]), sum) # count the NA values in each layer
i <- i/ncell(ras[[j]]) # fraction that is NA
ss <- ras[[j]][[which(i>.5)]] # Select the layers that more than half the cells with values
class<-c(class,ss)
}
Here, I have my problem, the output class has all my images and not the layers that more than 50% of the cells with values
I've like to apply this conditon for:
#Remove target images
f2 <- list.files(getwd(), pattern = ".tif")
f2<- f[f!=class]
ras2 <- lapply(f2,raster)

Answer 1

Your example data
library(raster)
r <- raster(ncol=10, nrow=10)
set.seed(0)
s <- stack(lapply(1:10, function(i) setValues(r, runif(ncell(r)))))
s[s < .5] <- NA
# I skip the file writing bit. But from these files I would make a RasterStack again
#f <- list.files(getwd(), pattern = ".tif")
#ras <- stack(f)
Count the number of cells with NA and divide by the number of cells
f <- freq(s, value=NA) / ncell(s)
# equivalent to cellStats(is.na(s), "mean")
i <- which(f <= 0.5)
i
#layer.2 layer.6 layer.7
# 2 6 7
use these indices to subset the RasterStack
ss <- s[[i]]
If you cannot make a RasterStack from your real data (perhaps the rasters do not align), you can use a list and a loop like this
ras <- as.list(s)
result <- rep(NA, length(ras))
for (i in 1:length(ras)){
result[i] <- freq(ras[[i]], value=NA) / ncell(ras[[i]])
}
# equivalent to
# result <- sapply(1:length(ras), function(i) freq(ras[[i]], value=NA) / ncell(ras[[i]]))
j <- result < 0.5
sras <- ras[j]