local_graph {tidygraph} | R Documentation |
Measures based on the neighborhood of each node
Description
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 |
mindist |
The minimum distance to include the vertex in the result. |
weights |
An edge weight vector. For |
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
# 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()