Automatic linking to C docs

CONTRIBUTING.md

@@ -154,11 +154,7 @@ pak::pak("igraph/igraph.r2cdocs")
 [roxygen2](https://roxygen2.r-lib.org/), and run `devtools::document()` or `make
 igraph` to update the `.Rd` files.
 
-- Links to C docs are added using the cdocs tag, for instance:
-
-```
-#' @cdocs igraph_assortativity
-```
+- Links to C docs are added automatically thanks to the igraph.r2cdocs's roclet.
 
 ### Maintaining igraph.r2cdocs
 

DESCRIPTION

@@ -81,7 +81,7 @@ Config/testthat/start-first: aaa-auto, vs-es, scan, vs-operators, weakref,
     watts.strogatz.game
 Encoding: UTF-8
 Roxygen: list(markdown = TRUE, roclets = c("collate", "rd", "namespace",
-    "igraph.r2cdocs::cdocs_roclet", "devtag::dev_roclet"), packages =
+    "igraph.r2cdocs::docs_rd", "devtag::dev_roclet"), packages =
     "igraph.r2cdocs")
 RoxygenNote: 7.3.3.9000
 SystemRequirements: libxml2 (optional), glpk (>= 4.57, optional)

R/assortativity.R

@@ -160,7 +160,6 @@ assortativity.degree <- function(graph, directed = TRUE) {
 #'
 #' # BA model, tends to be dissortative
 #' assortativity_degree(sample_pa(10000, m = 4))
-#' @cdocs igraph_assortativity
 assortativity <- function(
   graph,
   values,
@@ -240,7 +239,6 @@ assortativity_legacy <- function(
 #'   with [as.integer()].
 #' @rdname assortativity
 #' @export
-#' @cdocs igraph_assortativity_nominal
 assortativity_nominal <- function(
   graph,
   types,
@@ -257,7 +255,6 @@ assortativity_nominal <- function(
 
 #' @rdname assortativity
 #' @export
-#' @cdocs igraph_assortativity_degree
 assortativity_degree <- function(graph, directed = TRUE) {
   assortativity_degree_impl(
     graph = graph,

R/bipartite.R

@@ -226,7 +226,6 @@ bipartite_projection <- function(
 
 #' @rdname bipartite_projection
 #' @export
-#' @cdocs igraph_bipartite_projection_size
 bipartite_projection_size <- function(graph, types = NULL) {
   bipartite_projection_size_impl(
     graph = graph,
@@ -283,7 +282,6 @@ bipartite_projection_size <- function(graph, types = NULL) {
 #' bipartite_mapping(g3)
 #' @family bipartite
 #' @export
-#' @cdocs igraph_is_bipartite
 bipartite_mapping <- function(graph) {
   is_bipartite_impl(
     graph = graph

R/centrality.R

@@ -1291,7 +1291,6 @@ eigen_defaults <- function() {
 #' eigen_centrality(g)
 #' @family centrality
 #' @export
-#' @cdocs igraph_eigenvector_centrality
 eigen_centrality <- function(
   graph,
   directed = FALSE,
@@ -1371,7 +1370,6 @@ eigen_centrality <- function(
 #' strength(g)
 #' @family centrality
 #' @export
-#' @cdocs igraph_strength
 strength <- function(
   graph,
   vids = V(graph),
@@ -1429,7 +1427,6 @@ strength <- function(
 #' diversity(g3)
 #' @family centrality
 #' @export
-#' @cdocs igraph_diversity
 diversity <- function(graph, weights = NULL, vids = V(graph)) {
   diversity_impl(
     graph = graph,
@@ -1497,7 +1494,6 @@ diversity <- function(graph, weights = NULL, vids = V(graph)) {
 #' g2 <- make_ring(10)
 #' hits_scores(g2)
 #' @family centrality
-#' @cdocs igraph_hub_and_authority_scores
 hits_scores <- function(
   graph,
   ...,
@@ -1681,7 +1677,6 @@ hub_score <- function(
 #' page_rank(g3, personalized = reset)$vector
 #' @family centrality
 #' @export
-#' @cdocs igraph_personalized_pagerank
 page_rank <- function(
   graph,
   algo = c("prpack", "arpack"),
@@ -1749,7 +1744,6 @@ page_rank <- function(
 #' harmonic_centrality(g2, mode = "out")
 #' harmonic_centrality(g %du% make_full_graph(5), mode = "all")
 #'
-#' @cdocs igraph_harmonic_centrality_cutoff
 harmonic_centrality <- function(
   graph,
   vids = V(graph),

R/centralization.R

@@ -314,7 +314,6 @@ NULL
 #' g1 <- make_star(10, mode = "undirected")
 #' centr_eigen(g0)$centralization
 #' centr_eigen(g1)$centralization
-#' @cdocs igraph_centralization
 centralize <- function(scores, theoretical.max = 0, normalized = TRUE) {
   centralization_impl(
     scores = scores,
@@ -362,7 +361,6 @@ centralize <- function(scores, theoretical.max = 0, normalized = TRUE) {
 #' centr_clo(g, mode = "all")$centralization
 #' centr_betw(g, directed = FALSE)$centralization
 #' centr_eigen(g, directed = FALSE)$centralization
-#' @cdocs igraph_centralization_degree
 centr_degree <- function(
   graph,
   mode = c("all", "out", "in", "total"),
@@ -511,7 +509,6 @@ centr_betw <- function(graph, directed = TRUE, normalized = TRUE) {
 #' centr_betw(g, normalized = FALSE)$centralization %>%
 #'   `/`(centr_betw_tmax(g))
 #' centr_betw(g, normalized = TRUE)$centralization
-#' @cdocs igraph_centralization_betweenness_tmax
 centr_betw_tmax <- function(graph = NULL, nodes = 0, directed = TRUE) {
   centralization_betweenness_tmax_impl(
     graph = graph,
@@ -556,7 +553,6 @@ centr_betw_tmax <- function(graph = NULL, nodes = 0, directed = TRUE) {
 #' centr_clo(g, mode = "all")$centralization
 #' centr_betw(g, directed = FALSE)$centralization
 #' centr_eigen(g, directed = FALSE)$centralization
-#' @cdocs igraph_centralization_closeness
 centr_clo <- function(
   graph,
   mode = c("out", "in", "all", "total"),
@@ -593,7 +589,6 @@ centr_clo <- function(
 #' centr_clo(g, normalized = FALSE)$centralization %>%
 #'   `/`(centr_clo_tmax(g))
 #' centr_clo(g, normalized = TRUE)$centralization
-#' @cdocs igraph_centralization_closeness_tmax
 centr_clo_tmax <- function(
   graph = NULL,
   nodes = 0,
@@ -655,7 +650,6 @@ centr_clo_tmax <- function(
 #' g1 <- make_star(10, mode = "undirected")
 #' centr_eigen(g0)$centralization
 #' centr_eigen(g1)$centralization
-#' @cdocs igraph_centralization_eigenvector_centrality
 centr_eigen <- function(
   graph,
   directed = FALSE,
@@ -707,7 +701,6 @@ centr_eigen <- function(
 #' centr_eigen(g, normalized = FALSE)$centralization %>%
 #'   `/`(centr_eigen_tmax(g))
 #' centr_eigen(g, normalized = TRUE)$centralization
-#' @cdocs igraph_centralization_eigenvector_centrality_tmax
 centr_eigen_tmax <- function(
   graph = NULL,
   nodes = 0,

R/cliques.R

@@ -238,7 +238,6 @@ clique.number <- function(graph) {
 #'
 #' # Check that all returned vertex sets are indeed cliques
 #' all(sapply(max_cliques(g), function (c) is_clique(g, c)))
-#' @cdocs igraph_cliques
 cliques <- function(graph, min = 0, max = 0) {
   cliques_impl(
     graph = graph,
@@ -249,7 +248,6 @@ cliques <- function(graph, min = 0, max = 0) {
 
 #' @rdname cliques
 #' @export
-#' @cdocs igraph_largest_cliques
 largest_cliques <- function(graph) {
   largest_cliques_impl(
     graph = graph
@@ -361,7 +359,6 @@ count_max_cliques <- function(graph, min = NULL, max = NULL, subset = NULL) {
 
 #' @rdname cliques
 #' @export
-#' @cdocs igraph_clique_number
 clique_num <- function(graph) {
   clique_number_impl(
     graph = graph
@@ -418,7 +415,6 @@ clique_num <- function(graph) {
 #' weighted_cliques(g, maximal = TRUE)
 #' largest_weighted_cliques(g)
 #' weighted_clique_num(g)
-#' @cdocs igraph_weighted_cliques
 weighted_cliques <- function(
   graph,
   vertex.weights = NULL,
@@ -436,7 +432,6 @@ weighted_cliques <- function(
 }
 #' @export
 #' @rdname cliques
-#' @cdocs igraph_largest_weighted_cliques
 largest_weighted_cliques <- function(graph, vertex.weights = NULL) {
   largest_weighted_cliques_impl(
     graph = graph,
@@ -445,7 +440,6 @@ largest_weighted_cliques <- function(graph, vertex.weights = NULL) {
 }
 #' @export
 #' @rdname cliques
-#' @cdocs igraph_weighted_clique_number
 weighted_clique_num <- function(graph, vertex.weights = NULL) {
   weighted_clique_number_impl(
     graph = graph,
@@ -590,8 +584,6 @@ independence_number <- ivs_size
 
 #' @rdname cliques
 #' @export
-#' @cdocs igraph_maximal_cliques_hist
-#' @cdocs igraph_clique_size_hist
 clique_size_counts <- function(graph, min = 0, max = 0, maximal = FALSE) {
   if (maximal) {
     maximal_cliques_hist_impl(
@@ -620,7 +612,6 @@ clique_size_counts <- function(graph, min = 0, max = 0, maximal = FALSE) {
 #' @keywords graphs
 #' @seealso [make_full_graph()]
 #' @export
-#' @cdocs igraph_is_complete
 #' @examples
 #'
 #' g <- make_full_graph(6, directed = TRUE)
@@ -648,7 +639,6 @@ is_complete <- function(graph) {
 #'   a clique.
 #' @keywords graphs
 #' @export
-#' @cdocs igraph_is_clique
 is_clique <- function(graph, candidate, directed = FALSE) {
   is_clique_impl(
     graph = graph,
@@ -665,7 +655,6 @@ is_clique <- function(graph, candidate, directed = FALSE) {
 #'   independent set.
 #' @keywords graphs
 #' @export
-#' @cdocs igraph_is_independent_vertex_set
 is_ivs <- function(graph, candidate) {
   is_independent_vertex_set_impl(
     graph = graph,

R/coloring.R

@@ -30,7 +30,6 @@
 #' col <- greedy_vertex_coloring(g)
 #' plot(g, vertex.color = col)
 #'
-#' @cdocs igraph_vertex_coloring_greedy
 greedy_vertex_coloring <- function(
   graph,
   heuristic = c("colored_neighbors", "dsatur")

R/community.R

@@ -3196,7 +3196,6 @@ communities <- groups.communities
 #'
 #' @export
 #' @family functions for manipulating graph structure
-#' @cdocs igraph_contract_vertices
 contract <- function(
   graph,
   mapping,
@@ -3252,7 +3251,6 @@ contract <- function(
 #'
 #' @export
 #' @family community
-#' @cdocs igraph_voronoi
 voronoi_cells <- function(
   graph,
   generators,

R/components.R

@@ -256,7 +256,6 @@ decompose <- function(
 #'
 #' @family components
 #' @export
-#' @cdocs igraph_articulation_points
 articulation_points <- function(graph) {
   articulation_points_impl(
     graph = graph
@@ -265,7 +264,6 @@ articulation_points <- function(graph) {
 
 #' @rdname articulation_points
 #' @export
-#' @cdocs igraph_bridges
 bridges <- function(graph) {
   bridges_impl(
     graph = graph
@@ -320,7 +318,6 @@ bridges <- function(graph) {
 #' bc <- biconnected_components(g)
 #' @family components
 #' @export
-#' @cdocs igraph_biconnected_components
 biconnected_components <- function(graph) {
   # Function call
   res <- biconnected_components_impl(
@@ -392,7 +389,6 @@ biconnected_components <- function(graph) {
 #' is_biconnected(make_full_graph(2))
 #' @family components
 #' @export
-#' @cdocs igraph_is_biconnected
 is_biconnected <- function(graph) {
   is_biconnected_impl(
     graph = graph

R/conversion.R

@@ -599,7 +599,6 @@ as_edgelist <- function(graph, names = TRUE) {
 #' )
 #' print(ug4, e = TRUE)
 #'
-#' @cdocs igraph_to_directed
 as_directed <- function(
   graph,
   mode = c("mutual", "arbitrary", "random", "acyclic")
@@ -1274,7 +1273,6 @@ as_data_frame <- function(x, what = c("edges", "vertices", "both")) {
 #' which_multiple(g3)
 #' @family conversion
 #' @export
-#' @cdocs igraph_adjlist
 graph_from_adj_list <- function(
   adjlist,
   mode = c("out", "in", "all", "total"),

R/cycles.R

@@ -47,7 +47,6 @@
 #' find_cycle(sample_tree(5))
 #'
 #' @family cycles
-#' @cdocs igraph_find_cycle
 #' @export
 
 find_cycle <- function(graph, mode = c("out", "in", "all", "total")) {
@@ -85,7 +84,6 @@ find_cycle <- function(graph, mode = c("out", "in", "all", "total")) {
 #' simple_cycles(g, mode = "all", min = 2, max = 3) # limit cycle lengths
 #'
 #' @family cycles
-#' @cdocs igraph_simple_cycles
 #' @export
 
 simple_cycles <- function(

R/degseq.R

@@ -139,7 +139,6 @@ is_degseq <- function(out.deg, in.deg = NULL) {
 #' is_degseq(degree(g))
 #' is_graphical(degree(g))
 #' @export
-#' @cdocs igraph_is_graphical
 is_graphical <- function(
   out.deg,
   in.deg = NULL,

R/efficiency.R

@@ -66,7 +66,6 @@
 #' g <- make_graph("zachary")
 #' global_efficiency(g)
 #' average_local_efficiency(g)
-#' @cdocs igraph_global_efficiency
 global_efficiency <- function(graph, weights = NULL, directed = TRUE) {
   global_efficiency_impl(
     graph = graph,
@@ -77,7 +76,6 @@ global_efficiency <- function(graph, weights = NULL, directed = TRUE) {
 
 #' @rdname global_efficiency
 #' @export
-#' @cdocs igraph_local_efficiency
 local_efficiency <- function(
   graph,
   vids = V(graph),
@@ -96,7 +94,6 @@ local_efficiency <- function(
 
 #' @rdname global_efficiency
 #' @export
-#' @cdocs igraph_average_local_efficiency
 average_local_efficiency <- function(
   graph,
   weights = NULL,

R/embedding.R

@@ -101,7 +101,6 @@
 #' embed <- embed_adjacency_matrix(RDP, 5)
 #' @family embedding
 #' @export
-#' @cdocs igraph_adjacency_spectral_embedding
 embed_adjacency_matrix <- function(
   graph,
   no,
@@ -181,7 +180,6 @@ embed_adjacency_matrix <- function(
 #'
 #' @family embedding
 #' @export
-#' @cdocs igraph_dim_select
 dim_select <- function(sv) {
   dim_select_impl(
     sv = sv
@@ -277,7 +275,6 @@ dim_select <- function(sv) {
 #' RDP <- sample_dot_product(lpvs)
 #' embed <- embed_laplacian_matrix(RDP, 5)
 #' @family embedding
-#' @cdocs igraph_laplacian_spectral_embedding
 embed_laplacian_matrix <- function(
   graph,
   no,