opar <- par(ask = dev.interactive(orNone = TRUE))
cat("******************************************************\n",
"We give here an example of management of an object of \n",
"ltraj",
"\n******************************************************\n")
###############################################
###
### Example 1: preparing the "ltraj" from raw data
data(puechabon)
locs <- puechabon$locs
locs[1:4,]
xy <- locs[,c("X","Y")]
### Conversion of the date to the format POSIX
da <- as.character(locs$Date)
da <- as.POSIXct(strptime(as.character(locs$Date),"%y%m%d"))
## object of class "ltraj"
(ltr <- as.ltraj(xy, da, id = locs$Name))
## look at the data:
ltr
## the data are not regular: see the distribution of dt (in hours)
## according to the date
is.regular(ltr)
plotltr(ltr, "dt/3600/24")
## First, note that Chou is monitored two successive summers
## Now, cut the trajectory of Chou into two summers
foo <- function(dt) {
return(dt> (100*3600*24))
}
## The function foo returns TRUE if dt is longer than 100 days
## We use it to cut ltr:
l2 <- cutltraj(ltr, "foo(dt)", nextr = TRUE)
l2
plot(l2, perani = FALSE)
## Now, look again at the time lag:
plotltr(l2, "dt/3600/24")
## The relocations have been collected daily, and there are many
## missing values
## We set the missing values in this trajectory. We first
## set the reference date: the hour should be exact (i.e. minutes=0):
refda <- strptime("00:00", "%H:%M")
refda
## Set the missing values
l3 <- setNA(l2, refda, 1, units = "day")
## look at the data:
l3
## The trajectory is now regular, but there is a lot of
## missing values!!
summaryNAltraj(l3)
## Are the missing values randomly distributed in the trajectory?
runsNAltraj(l3)
## yes, it seems so...
## Trajectory is ready for the analysis
cat("*******************************************************\n",
"The deeply commented source for this demo can be found in the file:\n",
file.path(system.file(package = "adehabitat"), "demo", "managltraj.r\n"),
"Examples of analysis are given in demo(analysisltraj)\n",
"******************************************************\n")
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