Description Usage Arguments Value Author(s) Examples
tool.subgraph.search
looks for both upstream and downstream
neighborhoods of given seed node list for a given depth, gets the directed
edge information among seed nodes and their neighbors, obtains statistics
(degrees and strengths) for seed nodes.
1 | tool.subgraph.search(graph, seeds, depth, direction)
|
graph |
a datalist including following components: nodes: N-element array of node names tails: K-element array of node indices heads: K-element array of node indices weights: K-element array of edge weights tail2edge: N-element list of adjacent edge indices head2edge: N-element list of adjacent edge indices outstats: N-row data frame of out-degree node statistics instats: N-row data frame of in-degree node statistics stats: N-row data frame of node statistics |
seeds |
seed nodes' indices |
depth |
the maximum number of links to connect neighbors |
direction |
sets the directionality: use a negative value for dowstream, positive for upstream or zero for undirected |
a data list including seed nodes neighborhood information with following components:
RANK |
indices of neighboring nodes (including seeds) |
LEVEL |
number of edges away from seed |
STRENG |
sum of adjacent edge weights within neighborhood |
DEGREE |
number of adjacent edges within neighborhood |
Ville-Petteri Makinen
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | data(job_kda_analyze)
depth <- 1
direction <- 0
## Take one or multiple center nodes (seeds) to search the neighborhoods:
## e.g. take the first node in the graph as the seed, find its neighborhood:
center.node = job.kda$graph$nodes[1]
## Convert center node (seed) names to indices:
nodes <- job.kda$graph$nodes
ranks <- match(center.node, nodes)
ranks <- ranks[which(ranks > 0)]
## we already know that rank is 1, since we took the first node in the graph
## as an example:
ranks <- as.integer(ranks)
## Find neighbors.
res <- tool.subgraph.search(job.kda$graph, ranks, depth, direction)
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