Question on load_occ

[RafP2021]

Dears,
I have to signal that SSDM seems unable to operate after updating to the latest version of R.

The problem might be due to something that clashes with how the function load_occ() internally works.

Here below I post what I get, no matter how I try to set up the .csv file containing the occurrences:

> load_occ(Env = Env, file = "occu.csv", Xcol = "Longitude", Ycol = "Latitude", Spcol = "species")
Occurrences loading 
Error in xtfrm.data.frame(x) : not possible xtfrm the data frame

Please note that the above written "occu.csv" is the saved "Occurrences" object provided by default in SSDM, so it must be forcefully complying with the csv setting requirements (which however are very flexible).

Unfortunately I am not able to fully understand the point where the native code of load_occ() recalls xtfrm and crashes. I notice that it uses read.csv2() to upload the file, but then I have not enough knowledge of R to spot where and how it handles it as a dataframe.

Thank you for any suggestions you may have in addressing this issue.

[sylvainschmitt]

Dear @RafP2021 ,

Please:

• Use reproducible examples for bugs. In your case I just run the example from load_occ using ?load_occ under R 4.4.1 and it worked perfectly
• Use appropriate title for issues a bit more precociously, because in this case you re a bit over alerting when you have a local issue
• Check the way you saved the csv file in your case because I suspect the error came from their

Sylvain

[RafP2021]

Dear Sylvain,
Thank you very much for your answer, and please excuse me for the excessively alarming title. In the end, I was able to understand the issue: the specification of the separator is basically mandatory, simply because the function uses read.csv2() to load the csv file so it made an assumption (sep = ; ) that was not in line with the format of my .csv list. Here's the fixed script:

Occurrences <- load_occ( path = "C:/Desktop/SSDM/Models_for_species1/workdir/", Env = Env, file = "species1_occurrences.csv", sep = ",", Xcol = "X", Ycol = "Y", Spcol = "species", GeoRes = TRUE, reso = max(res(Env@layers[[1]])), verbose = TRUE, GUI = FALSE )