Looping through class ltraj? - r

Question

Apologies if this is not the best forum to inquire this question.
Has anyone been able to loop/iterate though multiple GPS collared individuals that are in class ltraj (adehabitatlt)?
I've been trying to calculate Prox (https://cran.r-project.org/web/packages/wildlifeDI/vignettes/wildlifeDI-vignette.pdf) for multiple individuals but am struggling with how exactly to loop class ltraj because it's different than dataframe (which I'm accustomed to).
Thanks in advance.
install.packages('wildlifeDI', dependencies=TRUE)
library(wildlifeDI)
library(adehabitatLT)
chupacabra <- structure(list(CollarID = structure(c(1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L), .Label = c("A4116F", "A4117M", "A4118F"), class = "factor"),
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"DateTime", "UTM_X", "UTM_Y"), row.names = c(NA, -267L), class = "data.frame")
Commenting out incorrect transformation
# chupacabra$DateTime <-as.POSIXct(strptime(chupacabra$DateTime, format='%m/%d/%Y %H:%M:%S'),origin='1970-01-01')
chupacabra2<-as.ltraj(chupacabra[, c("UTM_X","UTM_Y")], date=chupacabra$DateTime,id=chupacabra$CollarID, typeII=TRUE)
monster1<-chupacabra2[1] #extract the first chupacabra
monster2<-chupacabra2[2] #extract the second chupacabra
proxdf <-Prox(monster1,monster2, tc=0.5*60,dc=210, local =TRUE)
Here's a sample of chupcabras that we've been tracking. We'd like to examine how often they interact with each other. This dataset has 3 individuals (but we have many many more chupcabras) and it is inefficient to pull out the animals/creatures 1 by 1 to calculate proximity. I'd like to do a for loop (for i in unique ID, perhaps) but I don't understand how to do this when the data is in ltraj format. Any assistance would be appreciated.

Answer 1

After removing the harmful code that incorrectly reformatted the DateTime value, I plotted the "trajectory" for the 3 2-animal combinations. Clearly animal1 did not interact with animal 2 since their ranges were disjoint. Animal 1 and animal 3 do appear to interact, since about halfway through their joint sojourns they have the roughly same trajectory:
plot( chupacabra2[[1]]$x, chupacabra2[[1]]$y, type="l",
xlim=range( c(chupacabra2[[1]]$x, chupacabra2[[3]]$x)),
ylim= range(c(chupacabra2[[1]]$y, chupacabra2[[3]]$y)))
lines( chupacabra2[[3]]$x, chupacabra2[[3]]$y, col="red")
This appears in proxdf13 as:
> monster1<-chupacabra2[1]
>
> monster3<-chupacabra2[3]
>
> proxdf13 <-Prox(monster1,monster3, tc=0.5*60,dc=210, local =TRUE)
> proxdf13
date prox
1 2015-06-07 06:01:00 549.074863
2 2015-06-07 07:20:00 104.169909
3 2015-06-07 08:10:00 6.205875
4 2015-06-07 09:05:00 14.409016
5 2015-06-07 09:20:00 11.189309
6 2015-06-07 15:40:00 6.481131
7 2015-06-07 16:25:00 4.259042
8 2015-06-07 17:15:00 10.648210
9 2015-06-07 17:35:00 4.181297
10 2015-06-07 17:41:00 7.574566
So a guess that "interact" (might) means something along the lines of "is within 15 distance units for more than 2 days in succession". So a natural function to consider would be rle:
> rle( proxdf13$prox < 15 )
Run Length Encoding
lengths: int [1:2] 2 8
values : logi [1:2] FALSE TRUE
> RL13 <- rle( proxdf13$prox < 15 )
> max( RL13$lengths [ RL13$values] )
[1] 8
And test whether this is greater than some value, say 2?
So that was the method to handle a single 2way animal-animal combination. The comments of the questioner below suggest I may have lost him in the material that follows. To get the 2way combinations of a sequence use combn:
> combn(1:3, 2)
[,1] [,2] [,3]
[1,] 1 1 2
[2,] 2 3 3
That is a matrix that will be use to generate the index values for pulling two single animal "trajectory" dataframes at a time from the 'ltraj' object using each column separately. When the apply function is used it can "loop" over etiehr rows or columns of a matrix and using 2 as the index value to apply specifieds the columns.
So putting this all together (using apply to loop over the column indices of combn-result to get the two-way combinations):
( max.days.prox <- apply( combn( seq(length(chupacabra2)), 2 ), 2,
# loops over columns of the "combinations matrix"
function(x) {
proxcomb <- Prox( chupacabra2[ x[1] ], chupacabra2[ x[2] ],
tc=0.5*60,dc=210, local =TRUE)
RLcomb <- rle( proxcomb$prox < 15 )
Interact.days <- max( RLcomb$lengths [ RLcomb$values] ) } ) )
# [1] -Inf 8 -Inf
We rbind that to the result to look at the items of interest:
> rbind(combn( seq(length(chupacabra2)), 2 ) , max.days.prox)
[,1] [,2] [,3]
1 1 2
2 3 3
max.days.prox -Inf 8 -Inf
So only the pairing of animal1 and animal3 provided evidence of an interaction. This would generalize to larger instances of ltraj-objects