I have two files. The first file is a data frame that is simply times in one column and individuals in a second
# [Time] [Individual]
# [1] 1528142 C5A1790
# [2] 1528142 C5A1059
# [3] 1528142 C5A1084
# [4] 1528142 C5A1564
# [5] 1528142 C5A1239
# [6] 1528142 C5A1180
the second is an N X N matrix in which both rows and columns are individuals, including those in the first matrix.
# [C5A1084] [C5A1059] [C5A1790] [C5A1180]
# 1 [C5A1084] 0 0.5 1 0
# 2 [C5A1059] 0.5 0 0 1
# 3 [C5A1790] 1 1 0 0.5
# 4 [C5A1180] 0 1 0.5 0
I need to create a vector containing the row numbers in the matrix at which I can find the individuals from the data frame, and in the order that they are listed in the data frame. For these example data it would be (3,2,1,4).
I tried to use the which()
function as
RingIndex <- which(Matrix$IDcolumn == FrameIDs)
and received the "longer object length is not a multiple of shorter object length" message, presumably because the matrix includes more individuals than the data frame. %in%
and match()
are also returning errors stating that replacement has fewer rows than data.
Following the advice in the comments, I tried
RingIndex <- which(Matrix$IDcolumn %in% FrameIDs)
which successfully returned the correct row numbers, but in ascending order rather than the order of the original data. The match()
function continues to complain of different replacement and original lengths.
What approach could I use to get my vector?
Many thanks!