"Error in names(tau)..." when estimating speed and distance

[Charlotte Milling]

Hi! I ran into this error when estimating distance travelled:

Error in names(tau) <- tau.names[1:K] : 

  'names' attribute [2] must be the same length as the vector [0]

In addition: Warning message:

In min(dz[dz > 0]) : no non-missing arguments to min; returning Inf

The script worked fine for a different animal over several days, but when I got to this individual, it estimated distance travelled on Day 1, and I got the error on Day 2. 

I have used other functions in the ctmm package with this same dataset without issue, so I'm inclined to think the issue isn't with the data, but I'm at a loss to explain what's happening. 

Any ideas?

Can't tell you how grateful I am for your help!

Charlotte Milling

### Estimate daily movement distance over the duration of the animal wearing the collar

mydata2.tel$day<-cut(mydata2.tel$timestamp, breaks="day")

days<-unique(mydata2.tel$day) #determines how many days the animal was tracked for

res<-list() #Empty list to fill with the results

#Loop over the number of days

for(i in 1:length(days)){

  message("Estimating distance travelled on day ", i, ": ", days[i])

  #Select data for the day in question

  mydata2.tel.SUBSET<-mydata2.tel[which(mydata2.tel$day == days[i]),]

  #Calculate the duration of the sampling period in seconds

  SAMP.TIME<-diff(c(mydata2.tel.SUBSET$t[1],

                     mydata2.tel.SUBSET$t[nrow(mydata2.tel.SUBSET)]))

  #Guesstimate the model for initial parameter values

  GUESS<-ctmm.guess(mydata2.tel, variogram = variogram(mydata2.tel), interactive=F)

  #Turn error on

  GUESS$error<-TRUE

  #Fits the movement model to the day's data

  FITS<-ctmm.fit(mydata2.tel.SUBSET, CTMM=GUESS)

  #Calculate the speed in m/s

  ctmm_speed<-speed(object= mydata2.tel.SUBSET, CTMM= FITS, units = FALSE)

  #Multiply speed (in m/s) by the sample time (in s) to get the estimate distance traveled (in m)

  ctmm_dist<-ctmm_speed*SAMP.TIME

  #Rename the variable

  rownames(ctmm_dist) <- "distance (meters)"

  #Store the results in the list

  x<-c(i, #The day

       ctmm_dist[2], #The ML distance estimate

       ctmm_dist[1], #Min CI

       ctmm_dist[3]) #Max CI

  names(x) <- c("date", "dist.ML", "dist.Min", "dist.Max")

  res[[i]]<-x

}

[Charlotte Milling]

Actually, now that I've sent that, I am wondering if the number of relocations in a given day would trigger that error and cause the for loop to crash (rather than just moving onto day 2)? On the day in question, I only have three relocations for the animal. Perhaps instead of issuing a warning and recording a value of Inf or some other unrealistic number, the entire looped just crashed and did not run for the rest of the days in the dataset? 

[Christen Fleming]

Hi Charlotte,

That's probably the case. I'll look into it further in a couple of days, when I'm finished re-coding the location error class fitting. I should be able to squeeze something better than an error out of 3 locations.

Best,

Chris

[Christen Fleming]

Hi Charlotte,

I made an example case where I took smaller and smaller datasets and ran them through ctmm.guess, ctmm.select, speed, and fixed every error that came up when having only 4,3,2,1 sampled locations. The updates are in the development branch on GitHub. Please tell me if you run into any further issues.

devtools::install_github("ctmm-initiative/ctmm")

Best,

Chris

[Charlotte Milling]

That's great news! Thanks so much for your help!