local_graph
Measures based on the neighborhood of each node
These functions wraps a set of functions that all measures quantities of the local neighborhood of each node. They all return a vector or list matching the node position.
Usage
local_size(order = 1, mode = "all", mindist = 0)local_members(order = 1, mode = "all", mindist = 0)
local_triangles()
local_ave_degree(weights = NULL)
local_transitivity(weights = NULL)
Arguments
- order
Integer giving the order of the neighborhood.
- mode
Character constant, it specifies how to use the direction of the edges if a directed graph is analyzed. For ‘out’ only the outgoing edges are followed, so all vertices reachable from the source vertex in at most
order
steps are counted. For ‘"in"’ all vertices from which the source vertex is reachable in at mostorder
steps are counted. ‘"all"’ ignores the direction of the edges. This argument is ignored for undirected graphs.- mindist
The minimum distance to include the vertex in the result.
- weights
Weight vector. If the graph has a
weight
edge attribute, then this is used by default. If this argument is given, then vertex strength (seestrength
) is used instead of vertex degree. But note thatknnk
is still given in the function of the normal vertex degree. Weights are are used to calculate a weighted degree (also calledstrength
) instead of the degree.
Value
A numeric vector or a list (for local_members
) with elements
corresponding to the nodes in the graph.
Functions
local_size
: The size of the neighborhood in a given distance from the node. (Note that the node itself is included unlessmindist > 0
). Wrapsigraph::ego_size()
.local_members
: The members of the neighborhood of each node in a given distance. Wrapsigraph::ego()
.local_triangles
: The number of triangles each node participate in. Wrapsigraph::count_triangles()
.local_ave_degree
: Calculates the average degree based on the neighborhood of each node. Wrapsigraph::knn()
.local_transitivity
: Calculate the transitivity of each node, that is, the propensity for the nodes neighbors to be connected. Wrapsigraph::transitivity()
Examples
# NOT RUN {
# Get all neighbors of each graph
create_notable('chvatal') %>%
activate(nodes) %>%
mutate(neighborhood = local_members(mindist = 1))
# These are equivalent
create_notable('chvatal') %>%
activate(nodes) %>%
mutate(n_neighbors = local_size(mindist = 1),
degree = centrality_degree()) %>%
as_tibble()
# }