add.blocks | R Documentation |
add.blocks
shuffles an incidence matrix to have a block structure or planted partition while preserving the row and column sums
add.blocks( I, rowblock = sample(1:2, replace = T, nrow(I)), colblock = sample(1:2, replace = T, ncol(I)), density = 0.5, sorted = FALSE )
I |
An incidence matrix or igraph bipartite graph |
rowblock |
numeric: vector indicating each row node's block membership |
colblock |
numeric: vector indicating each column node's block membership |
density |
numeric: desired within-block density |
sorted |
boolean: if TRUE, return incidence matrix permuted by block |
Stochastic block and planted partition models generate graphs in which the probability that two nodes are connected
depends on whether they are members of the same or different blocks/partitions. Functions such as sample_sbm
can randomly sample from stochastic block models with given probabilities. In contrast add.blocks
adds a block
structure to an existing incidence matrix while preserving the row and column sums. Row nodes' and column nodes'
block memberships are supplied in separate vectors. If block membership vectors are not provided, then nodes are
randomly assigned to two groups.
An incidence matrix or igraph bipartite graph with a block structure
Neal, Z. P., Domagalski, R., and Sagan, B. 2021. Comparing alternatives to the fixed degree sequence model for extracting the backbone of bipartite projections. Scientific Reports, 11, 23929. doi: 10.1038/s41598-021-03238-3
Neal, Z. P. 2022. incidentally: An R package to generate incidence matrices and bipartite graphs. OSF Preprints doi: 10.31219/osf.io/ectms
I <- incidence.from.probability(R = 100, C = 100, P = .1) blocked <- add.blocks(I, density = .7) all(rowSums(I)==rowSums(blocked)) all(colSums(I)==colSums(blocked)) B <- igraph::sample_bipartite(100, 100, p=.1) blocked <- add.blocks(B, density = .7) all(igraph::degree(B)==igraph::degree(blocked))
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