[R-sig-Geo] loop memory problem

[Marcel Gangwisch]

Hi Marta,

for your loop:
1) maybe you can first make your calculations and afterwards plot the 
result.
It might be faster this way.

2) maybe you can use the parallel for each loop in order to use the 
whole performance of your cpu

3) loops in R are really slow in general.. you could also think about 
some fancy stuff like some R compiler or Rcpp package

4) in order to analyze your memory consumption, you should have a view 
on your system resources (depending on your OS: task manager (win) or 
htop (linux))

Best regards,
Marcel


On 06.03.2017 12:51, marta azores wrote:
> Hi all the members,
>
> I have an script with a loop. It's working properly with a few points.
> However, when I tried to run all my database 90.000 points, the loop
> stopped each 3.000 points. And it takes 8hours for run 3.000 points.
>
> My computer has 32GB of RAM, intel corei7 6700HQ CPU @ 2.60GHz .
>
> Do you think it can be a memory problem? Is there anyway to make it faster??
>
> Thanks you in advance,
>
> Marta
>
> ####files
> https://drive.google.com/open?id=0BwqSBe1Yq-FBUWVBOUdvaThEU1k
> ##############the script
> library(sp)
> library(gdistance)
> library(rgeos)
> ### define data folder
> path_data<-"C:/Users/Q11/"
>
> #debug test# tormenta1
> tor<- read.table(paste0(path_data,"tormenta1.csv"), header=TRUE, sep=",",
> na.strings="NA", dec=".", strip.white=TRUE)
> #transition layer
> costa6Azo<- raster(paste0(path_data,"costa6Azo_projected.tif"))#wgs84
> transitioncosta6Azo <- transition(costa6Azo, min, directions=16)#porque
> min????
> trCostS16 <- gdistance::geoCorrection(transitioncosta6Azo, type="c")
> #
>
> effortSP_tormentapos_1_1<-as.data.frame(cbind(tor$Lat1,tor$Long1,tor$transect))
>
> str(effortSP_tormentapos_1_1)
> sp::coordinates(effortSP_tormentapos_1_1) <- ~V2+V1
> sp::proj4string(effortSP_tormentapos_1_1) <-CRS("+proj=longlat +datum=WGS84
> +no_defs")
>
> effortSP_tormenta <-sp::spTransform(effortSP_tormentapos_1_1,
> CRS("+proj=utm +zone=26 +ellps=intl +towgs84=-104,167,-38,0,0,0,0 +units=m
> +no_defs"))
>
> #effortSP_tormenta#to keep the same names
> plot(effortSP_tormentapos_1_1,axes=TRUE,add=TRUE)
> # calculating the first segment of the whole sailing path# 10 total points
> tormenta<- gdistance::shortestPath(trCostS16, effortSP_tormenta at coords
> [1,],effortSP_tormenta at coords[2,], output="SpatialLines")
> gLength(tormenta)
> lines(tormenta,col=5)
>
> ### here we start with the for-loop :
> for (i in (seq(2,length(effortSP_tormenta)-1))) { {
>    print(tormenta)
>    nextSegment<- gdistance::shortestPath(trCostS16, effortSP_tormenta at coords
> [i,],effortSP_tormenta at coords[i+1,], output="SpatialLines")
>    # simple addition combines the single spatialline segements
>    tormenta <- nextSegment + tormenta
>    # we plot each new segement
>    lines(nextSegment)
>    gLength(nextSegment)
>
> }}
> ####################################
>
> 	[[alternative HTML version deleted]]
>
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