Remove all the NaNs from the input raster.

R-package/R/model_opt.r

@@ -42,6 +42,7 @@ model_opt_r <- function(k,
   points <- NULL
   models <- NULL
   oobe <- matrix(NA, nrow = n, ncol = 1)
+  rast <- raster::mask(rast, raster::calc(rast, fun = sum))
   for (j in 1:n) {
     ###Vorbereitung Klassifizierung
     if (j == 1) {
@@ -54,10 +55,10 @@ model_opt_r <- function(k,
       if (sample_type == "regular") {
         pbt <- raster::sampleRegular(raster, size = sample_size, sp = T)
       }
-     f <- which(is.na(pbt@data[1]))
-     if (length(f) != 0) {
-       pbt <- pbt[-f,]
-     }
+     #f <- which(is.na(pbt@data[1]))
+     #if (length(f) != 0) {
+     #  pbt <- pbt[-f,]
+     #}
       set.seed(seed2[k])
       classes <-
         as.factor(sample(c(1:2), size = nrow(pbt), replace = T))