RLE-Compressed Boolean Dyad Matrix
A simple class representing boolean (logical) square matrix run-length encoded in a column-major order.
rlebdm(x, n) as.rlebdm(x, ...) ## S3 method for class 'matrix' as.rlebdm(x, ...) ## S3 method for class 'edgelist' as.rlebdm(x, ...) ## S3 method for class 'network' as.rlebdm(x, ...) ## S3 method for class 'rlebdm' as.matrix(x, ...) ## S3 method for class 'rlebdm' dim(x) ## S3 method for class 'rlebdm' print(x, compact = TRUE, ...) ## S3 method for class 'rlebdm' Ops(e1, e2) ## S3 method for class 'rlebdm' Math(x, ...) ## S3 method for class 'rlebdm' compress(x, ...) ## S3 method for class 'rlebdm' as.edgelist(x, prototype = NULL, ...)
x |
for |
n |
the dimensions of the square matrix represented. |
... |
additional arguments, currently unused. |
compact |
whether to print the matrix compactly (dots and stars) or to print it as a logical matrix. |
e1, e2 |
arguments to the unary ( |
prototype |
an optional network with network attributes that
are transferred to the edgelist and will filter it (e.g., if the
prototype network is given and does not allow self-loops, the
edgelist will not have self-loops either,e ven if the dyad matrix
has non- |
as.rlebdm
: Convert a square matrix of mode coercible to logical
to an
rlebdm
.
as.rlebdm
: Convert an object of class edgelist
to an rlebdm
object
whose cells in the edge list are set to TRUE
and whose other
cells are set to FALSE
.
as.rlebdm
: Convert an object of class network
to an rlebdm
object
whose cells corresponding to extant edges are set to TRUE
and
whose other cells are set to FALSE
.
compress
: Compress the rle
data structure in the
rlebdm
by merging successive runs with identical values.
as.edgelist
: Convert an rlebdm
object to an edgelist
: a two-column
integer matrix giving the cells with TRUE
values.
# From a vector rlebdm(rep(rep(c(0,1),each=3),14)[seq_len(81)], 9) # From a constant rlebdm(1, 3) # Large matrix (overflowing .Machine$integer.max) big <- rlebdm(1, 50000) unclass(big) # Represented as two runs stopifnot(length(big)==50000^2)
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