Add eulerian path algos

NAMESPACE

@@ -180,6 +180,7 @@ export(edge_is_loop)
 export(edge_is_multiple)
 export(edge_is_mutual)
 export(edge_is_to)
+export(edge_rank_eulerian)
 export(ends_with)
 export(everything)
 export(filter)
@@ -200,6 +201,7 @@ export(graph_is_complete)
 export(graph_is_connected)
 export(graph_is_dag)
 export(graph_is_directed)
+export(graph_is_eulerian)
 export(graph_is_forest)
 export(graph_is_isomorphic_to)
 export(graph_is_simple)
@@ -504,6 +506,8 @@ importFrom(igraph,edge_connectivity)
 importFrom(igraph,ego)
 importFrom(igraph,ego_size)
 importFrom(igraph,eigen_centrality)
+importFrom(igraph,eulerian_cycle)
+importFrom(igraph,eulerian_path)
 importFrom(igraph,girth)
 importFrom(igraph,gorder)
 importFrom(igraph,graph_attr)
@@ -513,6 +517,8 @@ importFrom(igraph,graph_from_data_frame)
 importFrom(igraph,graph_from_edgelist)
 importFrom(igraph,graph_from_incidence_matrix)
 importFrom(igraph,gsize)
+importFrom(igraph,has_eulerian_cycle)
+importFrom(igraph,has_eulerian_path)
 importFrom(igraph,hub_score)
 importFrom(igraph,induced_subgraph)
 importFrom(igraph,is.directed)

NEWS.md

@@ -23,6 +23,8 @@
   igraph
 * `graph_mean_dist()` now supports edge weights through a new `weights` argument
 * Added `to_largest_component()` morpher
+* Added `graph_is_eulerian()` and `edge_rank_eulerian()` for eulerian path 
+  calculations
 
 # tidygraph 1.2.3
 

R/edge_rank.R

@@ -0,0 +1,36 @@
+#' Calculate edge ranking
+#'
+#' This set of functions tries to calculate a ranking of the edges in a graph so
+#' that edges sharing certain topological traits are in proximity in the
+#' resulting order.
+#'
+#' @param cyclic should the eulerian path start and end at the same node
+#'
+#' @return An integer vector giving the position of each edge in the ranking
+#'
+#' @rdname edge_rank
+#' @name edge_rank
+#'
+#' @examples
+#' graph <- create_notable('meredith') %>%
+#'   activate(edges) %>%
+#'   mutate(rank = edge_rank_eulerian())
+#'
+NULL
+
+#' @describeIn edge_rank Calculcate ranking as the visit order of a eulerian
+#' path or cycle. If no such path or cycle exist it will return a vector of
+#' `NA`s
+#' @importFrom igraph eulerian_path eulerian_cycle
+#' @export
+edge_rank_eulerian <- function(cyclic = FALSE) {
+  expect_edges()
+  alg <- if (cyclic) eulerian_cycle else eulerian_path
+  rlang::try_fetch({
+      compress_rank(match(focus_ind(.G(), 'edges'), alg(.G())$epath))
+    },
+    error = function(...) {
+      rep_len(NA_integer_, length(focus_ind(.G(), 'edges')))
+    }
+  )
+}

R/graph_types.R

@@ -5,8 +5,8 @@
 #' properties and will all return a logical scalar.
 #'
 #' @param graph The graph to compare structure to
-#'
 #' @param method The algorithm to use for comparison
+#' @param cyclic should the eulerian path start and end at the same node
 #'
 #' @param ... Arguments passed on to the comparison methods. See
 #' [igraph::is_isomorphic_to()] and [igraph::is_subgraph_isomorphic_to()]
@@ -86,3 +86,14 @@ graph_is_isomorphic_to <- function(graph, method = 'auto', ...) {
 graph_is_subgraph_isomorphic_to <- function(graph, method = 'auto', ...) {
   is_subgraph_isomorphic_to(.G(), graph, method, ...)
 }
+#' @describeIn graph_types Can all the edges in the graph be reaches by a single
+#' path or cycle that only goes through each edge once
+#' @importFrom igraph has_eulerian_cycle has_eulerian_path
+#' @export
+graph_is_eulerian <- function(cyclic = FALSE) {
+  if (cyclic) {
+    has_eulerian_cycle(.G())
+  } else {
+    has_eulerian_path(.G())
+  }
+}

_pkgdown.yml

@@ -111,6 +111,7 @@ reference:
       for topological features such as which nodes they link, etc.
     contents:
       - edge_is_mutual
+      - edge_rank_eulerian
   - title: Graph measures
     desc: >
       The graph under investigation can also have properties of its own that can