I'm trying use WildlifeDI to extract before and after contact data following the Contact Analysis Workflow. I'm getting no negative values in the contact_timelag column so nothing is being attributed to 'before', and I'm getting quite a few NAs even though I started with just 2 animals and there were two contacts between them. I tried varying the value for pc in conPhase but there was no effect.
Any advice would be appreciated!
Thanks
Emily
Code:
m<-mt_as_move2(t)
o<-GetTO(m)
low<-conProcess(o,dc=2000,tc=144060)
l <- conPhase(low, pc=144060)
l <- conTimelag(l,def='all')
l$dt_lev <- cut(l$contact_timelag, breaks = c(-Inf,-144060,-6060,6060,144060,Inf), labels = c("Other","Before","Contact","After","Other"))
table(l$dt_lev)
Other Before Contact After
65286 0 13 78
summary(l$contact_timelag)
Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
0 7342745 13270913 13397120 19645187 25625193 27713
There is a discrepency in the code on github and the code on CRAN because I was getting an error when submitting my bug fixes to CRAN; so can you use devtools::install_github(jedalong/wildlifeDI) and see if you still get this problem when using the GITHUB code?
Hi Jed,
I'm trying use WildlifeDI to extract before and after contact data following the Contact Analysis Workflow. I'm getting no negative values in the contact_timelag column so nothing is being attributed to 'before', and I'm getting quite a few NAs even though I started with just 2 animals and there were two contacts between them. I tried varying the value for pc in conPhase but there was no effect.
Any advice would be appreciated! Thanks Emily
Code:
m<-mt_as_move2(t) o<-GetTO(m) low<-conProcess(o,dc=2000,tc=144060) l <- conPhase(low, pc=144060) l <- conTimelag(l,def='all') l$dt_lev <- cut(l$contact_timelag, breaks = c(-Inf,-144060,-6060,6060,144060,Inf), labels = c("Other","Before","Contact","After","Other")) table(l$dt_lev) Other Before Contact After 65286 0 13 78 summary(l$contact_timelag) Min. 1st Qu. Median Mean 3rd Qu. Max. NA's 0 7342745 13270913 13397120 19645187 25625193 27713