Methods for dealing with sparse geometry binary predicate lists
Methods for dealing with sparse geometry binary predicate lists
## S3 method for class 'sgbp' print(x, ..., n = 10, max_nb = 10) ## S3 method for class 'sgbp' t(x) ## S3 method for class 'sgbp' as.matrix(x, ...) ## S3 method for class 'sgbp' dim(x)
x |
object of class |
... |
ignored |
n |
integer; maximum number of items to print |
max_nb |
integer; maximum number of neighbours to print for each item |
sgbp are sparse matrices, stored as a list with integer vectors holding the ordered TRUE indices of each row. This means that for a dense, m x n matrix Q and a list L, if Q[i,j] is TRUE then j is an element of L[[i]]. Reversed: when k is the value of L[[i]][j], then Q[i,k] is TRUE.
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