Merge branch 'main' into next

Author: krlmlr

.github/workflows/R-CMD-check.yaml

@@ -223,8 +223,12 @@ jobs:
         env:
           GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
         run: |
-          # Check status of this workflow
-          state="pending"
+          # Set status to success if job succeeded, failure otherwise
+          if [ "${{ job.status }}" == "success" ]; then
+            state="success"
+          else
+            state="failure"
+          fi
           sha=${{ inputs.ref }}
           if [ -z "${sha}" ]; then
             sha=${{ github.sha }}

.github/workflows/vendor.yaml

@@ -7,7 +7,7 @@ on:
       - "vendor-one.sh"
   workflow_dispatch:
   schedule:
-    - cron: "0 * * * *"
+    - cron: "* 0 * * *"
 
 concurrency:
   group: ${{ github.workflow }}

AGENTS.md

@@ -91,7 +91,11 @@ All new functions must include:
 - A concept so that it exists in the pkgdown reference index
 - An "experimental" badge via `r lifecycle::badge("experimental")`
 
-If exporting a new function from the C library, ensure it is autogenerated and add tests for the `_impl` function.
+If exporting a new function from the C library:
+
+- Ensure it is autogenerated
+- Add tests for the `_impl` function
+- Name all arguments in all calls to the `_impl` function
 
 ## File Structure and Organization
 
@@ -113,9 +117,11 @@ See `tools/README.md` for guidelines on code generation using the Stimulus frame
 
 ### Build Artifacts
 
-Do not commit: `*.dd`, `*.d`, `*.o`, `*.so` files in `src/`, and `tests/testthat/testthat-problems.rds`.
+Do not commit: `*.d`, `*.o`, `*.so` files in `src/`, and `tests/testthat/testthat-problems.rds`.
 These are build artifacts that are regenerated automatically (see `src/README.md` for details on dependency tracking).
 
+Careful with changes to `*.dd`, keep system headers out, only expect changes if new source files are added or their local dependencies change.
+
 ## Testing
 
 - Add test cases for all new functionality

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: igraph
 Title: Network Analysis and Visualization
-Version: 2.2.1.9000
+Version: 2.2.1.9001
 Authors@R: c(
     person("Gábor", "Csárdi", , "[email protected]", role = "aut",
            comment = c(ORCID = "0000-0001-7098-9676")),

R/centralization.R

@@ -481,9 +481,12 @@ centr_betw <- function(graph, directed = TRUE, normalized = TRUE) {
   directed <- as.logical(directed)
   normalized <- as.logical(normalized)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_centralization_betweenness, graph, directed, normalized)
+  res <- centralization_betweenness_impl(
+    graph = graph,
+    directed = directed,
+    normalized = normalized
+  )
 
   res
 }

R/community.R

@@ -984,9 +984,13 @@ modularity_matrix <- function(
   resolution <- as.numeric(resolution)
   directed <- as.logical(directed)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_modularity_matrix, graph, weights, resolution, directed)
+  res <- modularity_matrix_impl(
+    graph = graph,
+    weights = weights,
+    resolution = resolution,
+    directed = directed
+  )
 
   res
 }
@@ -2524,9 +2528,12 @@ cluster_louvain <- function(graph, weights = NULL, resolution = 1) {
   }
   resolution <- as.numeric(resolution)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_community_multilevel, graph, weights, resolution)
+  res <- community_multilevel_impl(
+    graph = graph,
+    weights = weights,
+    resolution = resolution
+  )
   if (igraph_opt("add.vertex.names") && is_named(graph)) {
     res$names <- V(graph)$name
   }
@@ -3055,16 +3062,12 @@ i_compare <- function(
   } else {
     as.numeric(as.factor(comm2))
   }
-  method <- switch(
-    igraph.match.arg(method),
-    vi = 0L,
-    nmi = 1L,
-    split.join = 2L,
-    rand = 3L,
-    adjusted.rand = 4L
+  method <- igraph.match.arg(method)
+  res <- compare_communities_impl(
+    comm1 = comm1,
+    comm2 = comm2,
+    method = method
   )
-  on.exit(.Call(R_igraph_finalizer))
-  res <- .Call(R_igraph_compare_communities, comm1, comm2, method)
   res
 }
 
@@ -3112,8 +3115,10 @@ split_join_distance <- function(comm1, comm2) {
   } else {
     as.numeric(comm2)
   }
-  on.exit(.Call(R_igraph_finalizer))
-  res <- .Call(R_igraph_split_join_distance, comm1, comm2)
+  res <- split_join_distance_impl(
+    comm1 = comm1,
+    comm2 = comm2
+  )
   unlist(res)
 }
 

R/conversion.R

@@ -624,17 +624,14 @@ as_undirected <- function(
 ) {
   # Argument checks
   ensure_igraph(graph)
-  mode <- switch(
-    igraph.match.arg(mode),
-    "collapse" = 1L,
-    "each" = 0L,
-    "mutual" = 2L
-  )
-  edge.attr.comb <- igraph.i.attribute.combination(edge.attr.comb)
+  mode <- igraph.match.arg(mode)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_to_undirected, graph, mode, edge.attr.comb)
+  res <- to_undirected_impl(
+    graph = graph,
+    mode = mode,
+    edge.attr.comb = edge.attr.comb
+  )
 
   res
 }

R/flow.R

@@ -906,17 +906,14 @@ dominator_tree <- function(graph, root, mode = c("out", "in", "all", "total")) {
   }
   root <- as_igraph_vs(graph, root)
 
-  mode <- switch(
-    igraph.match.arg(mode),
-    "out" = 1,
-    "in" = 2,
-    "all" = 3,
-    "total" = 3
-  )
+  mode <- igraph.match.arg(mode)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_dominator_tree, graph, root - 1, mode)
+  res <- dominator_tree_impl(
+    graph = graph,
+    root = root,
+    mode = mode
+  )
   if (igraph_opt("return.vs.es")) {
     res$leftout <- create_vs(graph, res$leftout)
   }

R/hrg.R

@@ -251,9 +251,13 @@ fit_hrg <- function(graph, hrg = NULL, start = FALSE, steps = 0) {
   start <- as.logical(start)
   steps <- as.numeric(steps)
 
-  on.exit(.Call(R_igraph_finalizer))
   # Function call
-  res <- .Call(R_igraph_hrg_fit, graph, hrg, start, steps)
+  res <- hrg_fit_impl(
+    graph = graph,
+    hrg = hrg,
+    start = start,
+    steps = steps
+  )
 
   if (igraph_opt("add.vertex.names") && is_named(graph)) {
     res$names <- V(graph)$name

R/incidence.R

@@ -80,11 +80,12 @@ graph_incidence_build <- function(
 
   # Handle dense unweighted matrices first
   if (!inherits(incidence, "Matrix") && is.null(weighted)) {
-    mode(incidence) <- "double"
-    on.exit(.Call(R_igraph_finalizer))
-
-    mode_num <- switch(mode, "out" = 1, "in" = 2, "all" = 3, "total" = 3)
-    res <- .Call(R_igraph_biadjacency, incidence, directed, mode_num, multiple)
+    res <- biadjacency_impl(
+      incidence = incidence,
+      directed = directed,
+      mode = mode,
+      multiple = multiple
+    )
     return(set_vertex_attr(res$graph, "type", value = res$types))
   }