v1.2.2

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: manynet
 Title: Many Ways to Make, Modify, Map, Mark, and Measure Myriad Networks
-Version: 1.2.1
-Date: 2024-10-01
+Version: 1.2.2
+Date: 2024-10-04
 Description: Many tools for making, modifying, mapping, marking, measuring, 
    and motifs and memberships of many different types of networks.
    All functions operate with matrices, edge lists, and 'igraph', 'network', and 'tidygraph' objects,

NAMESPACE

@@ -596,6 +596,7 @@ export(node_is_recovered)
 export(node_kernighanlin)
 export(node_leading_eigen)
 export(node_leiden)
+export(node_leverage)
 export(node_louvain)
 export(node_mode)
 export(node_multidegree)
@@ -616,6 +617,7 @@ export(node_regular_equivalence)
 export(node_richness)
 export(node_roulette)
 export(node_spinglass)
+export(node_stress)
 export(node_strong_components)
 export(node_structural_equivalence)
 export(node_thresholds)
@@ -712,6 +714,7 @@ export(to_blocks)
 export(to_components)
 export(to_correlation)
 export(to_directed)
+export(to_dominating)
 export(to_ego)
 export(to_egos)
 export(to_eulerian)
@@ -835,7 +838,6 @@ importFrom(igraph,delete_vertex_attr)
 importFrom(igraph,delete_vertices)
 importFrom(igraph,diameter)
 importFrom(igraph,distances)
-importFrom(igraph,eccentricity)
 importFrom(igraph,edge_attr)
 importFrom(igraph,edge_attr_names)
 importFrom(igraph,edge_betweenness)

NEWS.md

@@ -1,3 +1,27 @@
+# manynet 1.2.2
+
+## Package
+
+- Updated all tutorials with different themes to make them more distinctive
+- Updated centrality tutorial with gifs
+- Updated visualisation tutorial with a few extras
+
+## Modifying
+
+- Added `to_dominating()` for extracting the dominating tree of a given network
+
+## Mapping
+
+- Reworked `graphr()` to make function more concise and consistent (thanks @henriquesposito)
+  - This allows new functionality and improves debugging moving forward
+
+## Measuring
+
+- Updated closeness centrality documentation
+- Improved `node_eccentricity()` to allow normalisation, appear in closeness documentation
+- Added `node_stress()` as a new betweenness-like centrality measure
+- Added `node_leverage()` as a new degree-like centrality measure
+
 # manynet 1.2.1
 
 ## Making

R/manip_reformed.R

@@ -449,6 +449,7 @@ to_blocks.tbl_graph <- function(.data, membership, FUN = mean){
 #'   - `to_eulerian()` returns only the Eulerian path within some network data.
 #'   - `to_tree()` returns the spanning tree in some network data or, 
 #'   if the data is unconnected, a forest of spanning trees.
+#'   - `to_dominating()` returns the dominating tree of the network
 #' @details
 #'   Not all functions have methods available for all object classes.
 #'   Below are the currently implemented S3 methods:
@@ -651,5 +652,17 @@ to_eulerian.tbl_graph <- function(.data){
 #' @export
 to_tree <- function(.data) {
   .data <- as_igraph(.data)
-  igraph::subgraph.edges(.data, igraph::sample_spanning_tree(.data))
+  out <- igraph::subgraph.edges(.data, igraph::sample_spanning_tree(.data))
+  as_tidygraph(out)
+}
+
+#' @rdname manip_paths 
+#' @param from The index or name of the node from which the path should be traced.
+#' @param direction String, either "out" or "in".
+#' @export
+to_dominating <- function(.data, from, direction = c("out","in")) {
+  direction <- match.arg(direction)
+  .data <- as_igraph(.data)
+  out <- igraph::dominator_tree(.data, root = from, mode = direction)$domtree
+  as_tidygraph(out)
 }

R/mark_ties.R

@@ -79,14 +79,15 @@ tie_is_bridge <- function(.data){
 }
 
 #' @rdname mark_ties
-#' @param from The index or name of the node from which the path should be traced.
+#' @inheritParams manip_paths
 #' @param to The index or name of the node to which the path should be traced.
 #' @param all_paths Whether to return a list of paths or sample just one.
 #'   By default FALSE, sampling just a single path.
 #' @importFrom igraph all_shortest_paths
 #' @examples 
-#' ison_adolescents %>% mutate_ties(route = tie_is_path(from = "Jane", to = 7)) %>% 
-#' graphr(edge_colour = "route")
+#' ison_adolescents %>%
+#'   mutate_ties(route = tie_is_path(from = "Jane", to = 7)) %>% 
+#'   graphr(edge_colour = "route")
 #' @export
 tie_is_path <- function(.data, from, to, all_paths = FALSE){
   if(missing(.data)) {expect_edges(); .data <- .G()}