## File: local_graph.Rd

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r-cran-tidygraph 1.2.0-1
 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081 % Generated by roxygen2: do not edit by hand % Please edit documentation in R/local.R \name{local_graph} \alias{local_graph} \alias{local_size} \alias{local_members} \alias{local_triangles} \alias{local_ave_degree} \alias{local_transitivity} \title{Measures based on the neighborhood of each node} \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{ \item{order}{Integer giving the order of the neighborhood.} \item{mode}{Character constant, it specifies how to use the direction of the edges if a directed graph is analyzed. For \sQuote{out} only the outgoing edges are followed, so all vertices reachable from the source vertex in at most \code{order} steps are counted. For \sQuote{"in"} all vertices from which the source vertex is reachable in at most \code{order} steps are counted. \sQuote{"all"} ignores the direction of the edges. This argument is ignored for undirected graphs.} \item{mindist}{The minimum distance to include the vertex in the result.} \item{weights}{Weight vector. If the graph has a \code{weight} edge attribute, then this is used by default. If this argument is given, then vertex strength (see \code{\link[igraph]{strength}}) is used instead of vertex degree. But note that \code{knnk} is still given in the function of the normal vertex degree. Weights are are used to calculate a weighted degree (also called \code{\link[igraph]{strength}}) instead of the degree.} } \value{ A numeric vector or a list (for \code{local_members}) with elements corresponding to the nodes in the graph. } \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. } \section{Functions}{ \itemize{ \item \code{local_size}: The size of the neighborhood in a given distance from the node. (Note that the node itself is included unless \code{mindist > 0}). Wraps \code{\link[igraph:ego_size]{igraph::ego_size()}}. \item \code{local_members}: The members of the neighborhood of each node in a given distance. Wraps \code{\link[igraph:ego]{igraph::ego()}}. \item \code{local_triangles}: The number of triangles each node participate in. Wraps \code{\link[igraph:count_triangles]{igraph::count_triangles()}}. \item \code{local_ave_degree}: Calculates the average degree based on the neighborhood of each node. Wraps \code{\link[igraph:knn]{igraph::knn()}}. \item \code{local_transitivity}: Calculate the transitivity of each node, that is, the propensity for the nodes neighbors to be connected. Wraps \code{\link[igraph:transitivity]{igraph::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() }