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#' Get closeness centrality values
#'
#' @description
#'
#' Get the closeness centrality values for all nodes in a graph.
#'
#' @inheritParams render_graph
#' @param direction using `all` (the default), the search will ignore edge
#' direction while traversing through the graph. With `out`, measurements
#' of paths will be from a node whereas with `in`, measurements of paths
#' will be to a node.
#'
#' @return A data frame with closeness values for each of the nodes.
#'
#' @examples
#' # Create a random graph using the
#' # `add_gnm_graph()` function
#' graph <-
#' create_graph() %>%
#' add_gnm_graph(
#' n = 10,
#' m = 12,
#' set_seed = 23)
#'
#' # Get closeness values for all nodes
#' # in the graph
#' graph %>% get_closeness()
#'
#' # Add the closeness values to
#' # the graph as a node attribute
#' graph <-
#' graph %>%
#' join_node_attrs(
#' df = get_closeness(.))
#'
#' # Display the graph's node data frame
#' graph %>% get_node_df()
#'
#' @export
get_closeness <- function(
graph,
direction = "all"
) {
# Validation: Graph object is valid
check_graph_valid(graph)
# Ensure that values provided for the
# `direction` argument are from the
# valid options
rlang::arg_match0(direction, c("all", "in", "out"))
# Convert the graph to an igraph object
ig_graph <- to_igraph(graph)
# Get the betweenness scores for each of the
# graph's nodes
if (direction == "all") {
closeness_values <-
igraph::closeness(ig_graph, mode = "all")
}
if (direction == "out") {
closeness_values <-
igraph::closeness(ig_graph, mode = "out")
}
if (direction == "in") {
closeness_values <-
igraph::closeness(ig_graph, mode = "in")
}
# Create df with betweenness scores
data.frame(
id = closeness_values %>%
names() %>%
as.integer(),
closeness = closeness_values,
stringsAsFactors = FALSE)
}
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