igraph 2.0.0 compat

thomasp85 · Jan 30, 2024 · d1fc8ba · d1fc8ba
1 parent 4258fdb
commit d1fc8ba
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -18,7 +18,7 @@ BugReports: https://github.com/thomasp85/tidygraph/issues
 Imports: 
     cli,
     dplyr (>= 0.8.5),
-    igraph (>= 1.5.0),
+    igraph (>= 2.0.0),
     lifecycle,
     magrittr,
     pillar,
@@ -45,5 +45,5 @@ LinkingTo:
     cpp11
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 Config/testthat/edition: 3
diff --git a/NAMESPACE b/NAMESPACE
@@ -73,6 +73,8 @@ S3method(sample_n,tbl_graph)
 S3method(select,morphed_tbl_graph)
 S3method(select,tbl_graph)
 S3method(semi_join,tbl_graph)
+S3method(set_graph_data,grouped_tbl_graph)
+S3method(set_graph_data,tbl_graph)
 S3method(slice,morphed_tbl_graph)
 S3method(slice,tbl_graph)
 S3method(slice_head,morphed_tbl_graph)
@@ -461,6 +463,7 @@ importFrom(igraph,add_edges)
 importFrom(igraph,add_vertices)
 importFrom(igraph,adjacent_vertices)
 importFrom(igraph,alpha_centrality)
+importFrom(igraph,arpack_defaults)
 importFrom(igraph,articulation_points)
 importFrom(igraph,as.igraph)
 importFrom(igraph,as_adjacency_matrix)
@@ -537,7 +540,6 @@ importFrom(igraph,has_eulerian_cycle)
 importFrom(igraph,has_eulerian_path)
 importFrom(igraph,hub_score)
 importFrom(igraph,induced_subgraph)
-importFrom(igraph,is.directed)
 importFrom(igraph,is_bipartite)
 importFrom(igraph,is_chordal)
 importFrom(igraph,is_connected)

diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,7 @@
 # tidygraph (development version)
 
 * Fix a bug in `tbl_graph()` when edge `to` and `from` where encoded as factors
+* Secure compitability with igraph 2.0.0
 
 # tidygraph 1.3.0
 

diff --git a/R/arrange.R b/R/arrange.R
@@ -24,11 +24,11 @@ arrange.morphed_tbl_graph <- function(.data, ...) {
 #' @export
 dplyr::arrange
 
-#' @importFrom igraph is.directed as_data_frame
+#' @importFrom igraph is_directed as_data_frame
 permute_edges <- function(graph, order) {
   graph_mod <- as_data_frame(graph, what = 'both')
   graph_mod$edges <- graph_mod$edges[order, ]
-  as_tbl_graph(graph_mod, directed = is.directed(graph))
+  as_tbl_graph(graph_mod, directed = is_directed(graph))
 }
 #' @importFrom igraph permute
 permute_nodes <- function(graph, order) {

diff --git a/R/centrality.R b/R/centrality.R
@@ -61,9 +61,9 @@ centrality_alpha <- function(weights = NULL, alpha = 1, exo = 1, tol = 1e-7, loo
   alpha_centrality(graph = graph, nodes = focus_ind(graph, 'nodes'), alpha = alpha, exo = exo, weights = weights, tol = tol, loops = loops)
 }
 #' @describeIn centrality Wrapper for [igraph::authority_score()]
-#' @importFrom igraph authority_score
+#' @importFrom igraph authority_score arpack_defaults
 #' @export
-centrality_authority <- function(weights = NULL, scale = TRUE, options = igraph::arpack_defaults) {
+centrality_authority <- function(weights = NULL, scale = TRUE, options = arpack_defaults()) {
   expect_nodes()
   weights <- enquo(weights)
   weights <- eval_tidy(weights, .E()) %||% NA
@@ -104,19 +104,19 @@ centrality_closeness <- function(weights = NULL, mode = 'out', normalized = FALS
   closeness(graph = graph, vids = focus_ind(graph, 'nodes'), mode = mode, cutoff = cutoff, weights = weights, normalized = normalized)
 }
 #' @describeIn centrality Wrapper for [igraph::eigen_centrality()]
-#' @importFrom igraph eigen_centrality
+#' @importFrom igraph eigen_centrality arpack_defaults
 #' @export
-centrality_eigen <- function(weights = NULL, directed = FALSE, scale = TRUE, options = igraph::arpack_defaults) {
+centrality_eigen <- function(weights = NULL, directed = FALSE, scale = TRUE, options = arpack_defaults()) {
   expect_nodes()
   weights <- enquo(weights)
   weights <- eval_tidy(weights, .E()) %||% NA
   graph <- .G()
   eigen_centrality(graph = graph, directed = directed, scale = scale, weights = weights, options = options)$vector[focus_ind(graph, 'nodes')]
 }
 #' @describeIn centrality Wrapper for [igraph::hub_score()]
-#' @importFrom igraph hub_score
+#' @importFrom igraph hub_score arpack_defaults
 #' @export
-centrality_hub <- function(weights = NULL, scale = TRUE, options = igraph::arpack_defaults) {
+centrality_hub <- function(weights = NULL, scale = TRUE, options = arpack_defaults()) {
   expect_nodes()
   weights <- enquo(weights)
   weights <- eval_tidy(weights, .E()) %||% NA
@@ -151,7 +151,7 @@ centrality_degree <- function(weights = NULL, mode = 'out', loops = TRUE, normal
   expect_nodes()
   graph <- .G()
   weights <- enquo(weights)
-  weights <- eval_tidy(weights, .E()) %||% NA
+  weights <- eval_tidy(weights, .E())
   if (is.null(weights)) {
     degree(graph = graph, v = focus_ind(graph, 'nodes'), mode = mode, loops = loops, normalized = normalized)
   } else {
@@ -187,11 +187,12 @@ centrality_harmonic <- function(weights = NULL, mode = 'out', normalized = FALSE
 #' @param aggregation The aggregation type to use on the indirect relations to be used in `netrankr::aggregate_positions`
 #' @param ... Arguments to pass on to `netrankr::indirect_relations`
 #' @export
+#' @importFrom igraph is_directed
 centrality_manual <- function(relation = 'dist_sp', aggregation = 'sum', ...) {
   expect_netrankr()
   expect_nodes()
   graph <- .G()
-  if (is.directed(graph)) {
+  if (is_directed(graph)) {
     cli::cli_abort("Centrality measures based on the {.pkg netrankr} package only works on undirected networks")
   }
   rel <- netrankr::indirect_relations(graph, type = relation, ...)

diff --git a/R/graph_measures.R b/R/graph_measures.R
@@ -39,9 +39,9 @@ graph_assortativity <- function(attr, in_attr = NULL, directed = TRUE) {
   if (is.numeric(attr)) {
     in_attr <- enquo(in_attr)
     in_attr <- eval_tidy(in_attr, .N(focused = FALSE))
-    assortativity(graph, attr, in_attr, directed)
+    assortativity(graph, values = attr, values.in = in_attr, directed = directed)
   } else {
-    assortativity_nominal(graph, as.factor(attr), directed)
+    assortativity_nominal(graph, types = as.factor(attr), directed = directed)
   }
 }
 #' @describeIn graph_measures Calculate the number of automorphisms of the graph. Wraps [igraph::count_automorphisms()]

diff --git a/R/group.R b/R/group.R
@@ -115,9 +115,9 @@ group_label_prop <- function(weights = NULL, label = NULL, fixed = NULL) {
   desc_enumeration(group)
 }
 #' @describeIn group_graph Group nodes based on the leading eigenvector of the modularity matrix using [igraph::cluster_leading_eigen()]
-#' @importFrom igraph membership cluster_leading_eigen cut_at
+#' @importFrom igraph membership cluster_leading_eigen cut_at arpack_defaults
 #' @export
-group_leading_eigen <- function(weights = NULL, steps = -1, label = NULL, options = igraph::arpack_defaults, n_groups = NULL) {
+group_leading_eigen <- function(weights = NULL, steps = -1, label = NULL, options = arpack_defaults(), n_groups = NULL) {
   expect_nodes()
   weights <- enquo(weights)
   weights <- eval_tidy(weights, .E()) %||% NA

diff --git a/R/node.R b/R/node.R
@@ -28,13 +28,13 @@ node_is_cut <- function() {
   focus_ind(graph, 'nodes') %in% articulation_points(graph)
 }
 #' @describeIn node_types is the node a root in a tree
-#' @importFrom igraph degree is.directed
+#' @importFrom igraph degree is_directed
 #' @export
 node_is_root <- function() {
   expect_nodes()
   graph <- .G()
   node_inds <- focus_ind(graph, 'nodes')
-  if ((!is_tree(graph) && !is_forest(graph)) || !is.directed(graph)) {
+  if ((!is_tree(graph) && !is_forest(graph)) || !is_directed(graph)) {
     return(rep(FALSE, length(node_inds)))
   }
   deg_in <- degree(graph, mode = 'in') == 0
@@ -43,7 +43,7 @@ node_is_root <- function() {
   root[node_inds]
 }
 #' @describeIn node_types is the node a leaf in a tree
-#' @importFrom igraph degree is.directed
+#' @importFrom igraph degree is_directed
 #' @export
 node_is_leaf <- function() {
   expect_nodes()
@@ -52,7 +52,7 @@ node_is_leaf <- function() {
   if ((!is_tree(graph) && !is_forest(graph))) {
     return(rep(FALSE, length(node_inds)))
   }
-  if (is.directed(graph)) {
+  if (is_directed(graph)) {
     deg_in <- degree(graph, mode = 'in') == 0
     deg_out <- degree(graph, mode = 'out') == 0
     leaf <- if (sum(deg_out) > sum(deg_in)) deg_out else deg_in

diff --git a/R/random_walk.R b/R/random_walk.R
@@ -50,15 +50,15 @@ random_walk_rank <- function(n, root = NULL, mode = "out", weights = NULL) {
     if (!quo_is_null(weights)) {
       cli::cli_warn('{.arg weights} is ignored when doing a random walk on nodes')
     }
-    walk <- as.integer(random_walk(graph, root, n, mode))
+    walk <- as.integer(random_walk(graph, root, n, mode = mode))
     len_out <- gorder(graph)
   } else {
     weights <- eval_tidy(weights, .E(focused = FALSE)) %||% NA
-    walk <- as.integer(random_edge_walk(graph, root, n, weights, mode))
+    walk <- as.integer(random_edge_walk(graph, root, n, weights, mode = mode))
     len_out <- gsize(graph)
   }
   res <- rep(list(integer()), len_out)
-  ord <- split(seq_len(n), walk)
+  ord <- split(seq_along(walk), walk)
   res[as.integer(names(ord))] <- ord
   res[focus_ind(graph, active(graph))]
 }
diff --git a/R/reroute.R b/R/reroute.R
@@ -32,7 +32,7 @@ reroute <- function(.data, from = NULL, to = NULL, subset = NULL) {
 }
 #' @export
 #' @importFrom rlang enquo eval_tidy
-#' @importFrom igraph is.directed
+#' @importFrom igraph is_directed
 reroute.tbl_graph <- function(.data, from = NULL, to = NULL, subset = NULL) {
   .register_graph_context(.data)
   expect_edges()
@@ -54,7 +54,7 @@ reroute.tbl_graph <- function(.data, from = NULL, to = NULL, subset = NULL) {
   .data <- tbl_graph(
     nodes = as_tibble(.data, active = 'nodes'),
     edges = edges,
-    directed = is.directed(.data)
+    directed = is_directed(.data)
   ) %gr_attr% .data
   active(.data) <- 'edges'
   .data

diff --git a/R/tbl_graph.R b/R/tbl_graph.R
@@ -199,6 +199,7 @@ as_tbl_graph.tbl_graph <- function(x, ...) {
 set_graph_data <- function(x, value, active) {
   UseMethod('set_graph_data')
 }
+#' @export
 set_graph_data.tbl_graph <- function(x, value, active = NULL) {
   if (is.null(active)) active <- active(x)
   switch(
@@ -208,6 +209,7 @@ set_graph_data.tbl_graph <- function(x, value, active = NULL) {
     cli::cli_abort('Unknown active element: {.val {active}}. Only nodes and edges supported')
   )
 }
+#' @export
 set_graph_data.grouped_tbl_graph <- function(x, value, active = NULL) {
   x <- NextMethod()
   apply_groups(x, value)

diff --git a/man/centrality.Rd b/man/centrality.Rd
diff --git a/man/focus.Rd b/man/focus.Rd
diff --git a/man/group_graph.Rd b/man/group_graph.Rd
diff --git a/man/map_bfs.Rd b/man/map_bfs.Rd
diff --git a/man/map_bfs_back.Rd b/man/map_bfs_back.Rd
diff --git a/man/map_dfs.Rd b/man/map_dfs.Rd
diff --git a/man/map_dfs_back.Rd b/man/map_dfs_back.Rd
diff --git a/tests/testthat/test-random-walk.R b/tests/testthat/test-random-walk.R
@@ -1,7 +1,7 @@
 test_that("random_walk_rank returns correct data", {
   set.seed(1)
   node_walk <- create_notable('zachary') |>
-    mutate(walk_rank = random_walk_rank(30, 5)) |>
+    mutate(walk_rank = random_walk_rank(29, 5)) |>
     pull(walk_rank)
 
   edge_walk <- create_notable('zachary') |>
@@ -13,9 +13,9 @@ test_that("random_walk_rank returns correct data", {
   expect_length(edge_walk, 78)
   expect_type(node_walk, 'list')
   expect_type(edge_walk, 'list')
-  expect_equal(node_walk[[5]], c(1, 12))
-  expect_equal(node_walk[[2]], integer())
+  expect_equal(node_walk[[5]], c(1, 5, 7))
+  expect_equal(node_walk[[3]], integer())
   expect_equal(edge_walk[[1]], integer())
   skip_on_cran()
-  expect_equal(edge_walk[[36]], 1:4)
+  expect_equal(edge_walk[[4]], c(1, 18))
 })