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nsdplot <- xyplot(nsdall ~ zerostart/3600, data=datansd1, col="grey", 				#color for the observed locations
type='b',											# 'b' shows the locations as dots, with a line connecting
												#successive locations. Can also be 'p' for just the locations, or 'l' for just
												#the line between locations
ylab=expression(paste('Net squared displacement ',' ', (km^2))),				#y axis label
xlab="Hours after trip start")
plot(nsdplot)

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Duemmer$NewDate <- as.POSIXct(Duemmer$timestamp, format="%Y-%m-%d %H:%M:%S", origin="1970-01-01")
timediffD <- diff(Duemmer$NewDate)*60*60
Duemmer <- Duemmer [-1,]

Duemmer$timelag <-as.numeric(abs(timediffD))
summary(Duemmer$timelag)
# Duemmer <- subset(Duemmer, Duemmer$timelag < 18000)

Duemmer $Year <- format(Duemmer $NewDate, "%Y")
# Duemmer <- subset(Duemmer, Duemmer $Year != "NA")
Duemmer $YearBurst <- c(paste(Duemmer $trackId, Duemmer $Year, sep="_"))
Duemmer $YearBurst <- as.factor(Duemmer $YearBurst)
str(Duemmer)
summary(Duemmer $YearBurst)
Duemmer <- subset(Duemmer, table(Duemmer $YearBurst)[ Duemmer $YearBurst] > 100)
Duemmer $YearBurst <- factor(Duemmer $YearBurst)

Dd1 <- Duemmer
str(Dd1)
indataD <-Dd1
innamesD <- unique(Dd1$ YearBurst)
innamesD <- innamesD [1:22]
outnamesD <- innamesD

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for (i in 1:length(innamesD)){
  data <- indataD [which(indataD$YearBurst==innamesD[i]),]
  if(dim(data)[1] != 0){
  data.xy = data [c("X", "Y")]
  coordinates(data.xy) <- ~X+Y    
  sppt <- SpatialPointsDataFrame(coordinates(data.xy), data)
  proj4string(sppt) <- CRS("+proj=utm +zone=12 +datum=WGS84")
  write.table(sppt, paste(outnamesD[i], "txt", sep="."), sep="\t", quote=FALSE, row.names=FALSE)
  write.table(paste(outnamesD[i], "txt", sep="."), sep="\t", quote=FALSE, row.names=FALSE, col.names=FALSE, "In_list.txt", append=TRUE)
}}

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 data.xy = data [, c("X", "Y")]

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bsp <- data.frame(X = 1:3, 
                  Y = 2:4,
                  Z = 3:5)
bsp[c("X", "Y")] 
#>   X Y
#> 1 1 2
#> 2 2 3
#> 3 3 4

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library(data.table)
bsp <- data.table(X = 1:3, 
                  Y = 2:4,
                  Z = 3:5)
bsp[c("X", "Y")] 
#> Error in `[.data.table`(bsp, c("X", "Y")): When i is a data.table (or character vector), the columns to join by must be specified using 'on=' argument (see ?data.table), by keying x (i.e. sorted, and, marked as sorted, see ?setkey), or by sharing column names between x and i (i.e., a natural join). Keyed joins might have further speed benefits on very large data due to x being sorted in RAM.

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data <- as.data.frame(data)