From 6e366f54707ee72ebbca501735a870a32d63bede Mon Sep 17 00:00:00 2001
From: Francesco Sabatini <francesco.sabatini@idiv.de>
Date: Mon, 30 Nov 2020 18:54:36 +0100
Subject: [PATCH] Fixed bug in A98 optimized
---
code/A98_PredictorsExtract.R | 20 +++++++++++---------
1 file changed, 11 insertions(+), 9 deletions(-)
diff --git a/code/A98_PredictorsExtract.R b/code/A98_PredictorsExtract.R
index 19e18c0..b630aac 100644
--- a/code/A98_PredictorsExtract.R
+++ b/code/A98_PredictorsExtract.R
@@ -25,11 +25,8 @@ PredExtr <- function(x.shp, myfunction=NA, output=NA,
print(paste("output will be:", output))
if(typp=="raster"){ mypredictor <- raster(toextract)} else
mypredictor <- readOGR(toextract)
- colnames(mypredictor@data)
header.shp <- readOGR(x.shp)
crs(mypredictor) <- crs(header.shp) #should be verified beforehand!
-
-
## Divide in chunks if requested
if(chunkn>1 & !is.na(chunk.i)){
@@ -47,14 +44,16 @@ PredExtr <- function(x.shp, myfunction=NA, output=NA,
cl <- makeForkCluster(ncores, outfile="" )
registerDoParallel(cl)
- print("start main foreach loop")
+
if(typp=="raster"){
- out <- foreach(i=1:length(header.shp), .packages=c('raster'), .combine=rbind) %dopar% {
+ print("start main foreach loop")
+ out <- foreach(i=1:length(header.shp), .packages=c('raster'), .combine=rbind) %dopar% {
tmp <- raster::extract(mypredictor, header.shp[i,],
buffer=min(10000, max(250, header.shp@data$lc_ncrt[i])), fun=myfunction)
}
if(!is.na(output)) {write.csv(out, file = output)} else{return(out)}
} else {
+ print("Match sequentially")
out <- sp::over(x=header.shp, y=mypredictor)
i.toassign <- which(is.na(out[,1]))
toassign <- header.shp[i.toassign,]
@@ -67,7 +66,7 @@ PredExtr <- function(x.shp, myfunction=NA, output=NA,
as_Spatial()
} else {
mypredictor.expl <- mypredictor}
-
+ print("start main foreach loop")
nearest <- foreach(i=1:length(toassign), .packages=c('raster'), .combine=rbind) %dopar% {
print(i)
## create a subset of geoentities based on a 5° buffer radius around each target plot.
@@ -84,13 +83,16 @@ PredExtr <- function(x.shp, myfunction=NA, output=NA,
}
)
# find nearest neighbour
- nearest.tmp <- tryCatch(geosphere::dist2Line(toassign[i,], tmp.mypredictor),
- error = function(e){data.frame(i=i, distance=NA, lon=NA, lat=NA,ID=NA)}
+ nearest.tmp <- tryCatch(tmp.mypredictor@data[geosphere::dist2Line(toassign[i,], tmp.mypredictor)[,"ID"],],
+ error = function(e){
+ ee <- myptedictor@data[1,]
+ ee[1,] <- rep(NA, ncol(mypredictor))
+ }
)
return(nearest.tmp)
}
- out[i.toassign,] <- tmp.mypredictor@data[nearest[,"ID"],]
+ out[i.toassign,] <- nearest
}
if(!is.na(output)) {write.csv(out, file = output)} else{return(out)}
}
--
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