Dear R users, I used to be able to use the package bipartite to calculate network metrics using the function networklevel, but now (with the new version 1.14) I keep getting the error messages below. I don't understand why I am getting these error messages given that colSums is not < 2, and the network isn't that small. I get the same error message ("Web is really too small...") even with larger webs. I also switched to a Mac recently.
> Error in colSums(web) : 'x' must be an array of at least two dimensions In addition: Warning message: In networklevel(m, index = c("nestedness", "connectance", "links per species", : Web is really too small to calculate any reasonable index. You will get the values nonetheless, but I wouldn't put any faith in them! The web I used is: >m [,1] [,2] [,3] [,4] [,5] [,6] [,7] [,8] [,9] [,10] [,11] [,12] [,13] [1,] 7 6 2 2 8 2 5 2 17 8 0 1 3 [2,] 2 1 6 2 1 0 3 2 5 4 0 1 4 [3,] 0 0 0 0 0 0 0 0 0 0 0 0 0 [4,] 3 7 5 11 2 2 6 2 18 8 0 2 4 [5,] 0 0 0 4 2 0 1 1 1 3 0 2 0 [6,] 3 3 0 3 1 1 1 2 8 5 0 0 3 [7,] 0 0 1 0 1 0 0 0 4 1 0 1 1 [8,] 2 0 2 1 1 0 1 0 2 2 0 1 2 [9,] 1 1 0 1 0 1 0 0 6 2 0 1 1 [10,] 2 2 4 7 4 4 3 1 11 8 0 1 2 [,14] [,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22] [,23] [,24] [,25] [1,] 4 0 3 0 2 1 2 9 5 12 8 17 [2,] 4 0 0 0 4 1 2 0 3 4 3 1 [3,] 0 0 0 0 0 0 0 0 0 0 0 0 [4,] 5 0 3 0 1 3 3 8 9 10 4 10 [5,] 1 0 0 0 0 2 0 3 0 1 2 2 [6,] 0 0 1 0 1 1 1 4 1 2 4 5 [7,] 1 0 0 0 0 0 0 2 1 3 4 3 [8,] 0 0 0 0 0 0 0 1 0 0 5 2 [9,] 2 0 1 0 1 0 0 1 0 3 1 4 [10,] 3 0 2 0 1 2 2 3 1 6 0 7 [,26] [,27] [,28] [,29] [,30] [1,] 5 1 3 4 3 [2,] 0 1 1 1 1 [3,] 0 0 0 0 0 [4,] 2 2 2 5 5 [5,] 0 1 1 0 1 [6,] 1 0 2 3 1 [7,] 1 1 0 1 2 [8,] 0 1 0 4 1 [9,] 0 0 1 0 0 [10,] 1 3 0 2 3 Sincerely, Scott Chamberlain Rice University, EEB Dept. [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.