chore: start deprecation of as_adj() alias of `as_adjacency_matrix(…

…)` (#1524)

R/centrality.R

@@ -673,7 +673,7 @@ arpack_defaults <- function() {
 #' if (require(Matrix)) {
 #'   set.seed(42)
 #'   g <- sample_gnp(1000, 5 / 1000)
-#'   M <- as_adj(g, sparse = TRUE)
+#'   M <- as_adjacency_matrix(g, sparse = TRUE)
 #'   f2 <- function(x, extra = NULL) {
 #'     cat(".")
 #'     as.vector(M %*% x)
@@ -800,7 +800,7 @@ arpack.unpack.complex <- function(vectors, values, nev) {
 #' cor(degree(g), sc)
 #'
 subgraph_centrality <- function(graph, diag = FALSE) {
-  A <- as_adj(graph)
+  A <- as_adjacency_matrix(graph)
   if (!diag) {
     diag(A) <- 0
   }
@@ -860,7 +860,7 @@ subgraph_centrality <- function(graph, diag = FALSE) {
 #'   \item{values}{Numeric vector, the eigenvalues.} \item{vectors}{Numeric
 #'   matrix, with the eigenvectors as columns.}
 #' @author Gabor Csardi \email{csardi.gabor@@gmail.com}
-#' @seealso [as_adj()] to create a (sparse) adjacency matrix.
+#' @seealso [as_adjacency_matrix()] to create a (sparse) adjacency matrix.
 #' @keywords graphs
 #' @examples
 #'
@@ -869,7 +869,7 @@ subgraph_centrality <- function(graph, diag = FALSE) {
 #' spectrum(kite)[c("values", "vectors")]
 #'
 #' ## Double check
-#' eigen(as_adj(kite, sparse = FALSE))$vectors[, 1]
+#' eigen(as_adjacency_matrix(kite, sparse = FALSE))$vectors[, 1]
 #'
 #' ## Should be the same as 'eigen_centrality' (but rescaled)
 #' cor(eigen_centrality(kite)$vector, spectrum(kite)$vectors)
@@ -1361,7 +1361,7 @@ bonpow.dense <- function(graph, nodes = V(graph),
                          rescale = FALSE, tol = 1e-7) {
   ensure_igraph(graph)
 
-  d <- as_adj(graph)
+  d <- as_adjacency_matrix(graph)
   if (!loops) {
     diag(d) <- 0
   }
@@ -1389,7 +1389,7 @@ bonpow.sparse <- function(graph, nodes = V(graph), loops = FALSE,
   vg <- vcount(graph)
 
   ## sparse adjacency matrix
-  d <- as_adj(graph, sparse = TRUE)
+  d <- as_adjacency_matrix(graph, sparse = TRUE)
 
   ## sparse identity matrix
   id <- as(Matrix::Matrix(diag(vg), doDiag = FALSE), "generalMatrix")
@@ -1564,7 +1564,7 @@ alpha.centrality.dense <- function(graph, nodes = V(graph), alpha = 1,
     attr <- NULL
   }
 
-  d <- t(as_adj(graph, attr = attr, sparse = FALSE))
+  d <- t(as_adjacency_matrix(graph, attr = attr, sparse = FALSE))
   if (!loops) {
     diag(d) <- 0
   }
@@ -1605,7 +1605,7 @@ alpha.centrality.sparse <- function(graph, nodes = V(graph), alpha = 1,
     attr <- NULL
   }
 
-  M <- Matrix::t(as_adj(graph, attr = attr, sparse = TRUE))
+  M <- Matrix::t(as_adjacency_matrix(graph, attr = attr, sparse = TRUE))
 
   ## Create an identity matrix
   M2 <- Matrix::sparseMatrix(dims = c(vc, vc), i = 1:vc, j = 1:vc, x = rep(1, vc))

R/conversion.R

@@ -366,10 +366,30 @@ as_adjacency_matrix <- function(graph, type = c("both", "upper", "lower"),
   }
 }
 
+#' Convert a graph to an adjacency matrix
+#'
+#' `r lifecycle::badge("deprecated")`
+#' We plan to remove `as_adj()` in favor of the more explicitly named
+#' `as_adjacency_matrix()` so please use `as_adjacency_matrix()` instead.
+#'
 #' @export
-#' @rdname as_adjacency_matrix
-as_adj <- as_adjacency_matrix
-
+#' @inheritParams as_adjacency_matrix
+#' @keywords internal
+as_adj <- function(graph, type = c("both", "upper", "lower"),
+                   attr = NULL, edges = deprecated(), names = TRUE,
+                   sparse = igraph_opt("sparsematrices")) {
+
+  lifecycle::deprecate_soft("2.0.4", "as_adj()", "as_adjacency_matrix()")
+
+  as_adjacency_matrix(
+    graph = graph,
+    type = type,
+    attr = attr,
+    edges = edges,
+    names = names,
+    sparse = sparse
+  )
+}
 #' Convert a graph to an edge list
 #'
 #' Sometimes it is useful to work with a standard representation of a
@@ -549,7 +569,7 @@ as_undirected <- function(graph, mode = c("collapse", "each", "mutual"), edge.at
 #' vectors of the adjacency lists are coerced to `igraph.vs`, this can be
 #' a very expensive operation on large graphs.
 #' @author Gabor Csardi \email{csardi.gabor@@gmail.com}
-#' @seealso [as_edgelist()], [as_adj()]
+#' @seealso [as_edgelist()], [as_adjacency_matrix()]
 #' @family conversion
 #' @export
 #' @keywords graphs
@@ -652,7 +672,7 @@ as_adj_edge_list <- function(graph,
 #'   whenever possible, before adding them to the igraph graph.
 #' @return `graph_from_graphnel()` returns an igraph graph object.
 #' @seealso [as_graphnel()] for the other direction,
-#' [as_adj()], [graph_from_adjacency_matrix()],
+#' [as_adjacency_matrix()], [graph_from_adjacency_matrix()],
 #' [as_adj_list()] and [graph_from_adj_list()] for other
 #' graph representations.
 #' @examplesIf rlang::is_installed("graph")
@@ -741,7 +761,7 @@ graph_from_graphnel <- function(graphNEL, name = TRUE, weight = TRUE,
 #' @param graph An igraph graph object.
 #' @return `as_graphnel()` returns a graphNEL graph object.
 #' @seealso [graph_from_graphnel()] for the other direction,
-#' [as_adj()], [graph_from_adjacency_matrix()],
+#' [as_adjacency_matrix()], [graph_from_adjacency_matrix()],
 #' [as_adj_list()] and [graph_from_adj_list()] for
 #' other graph representations.
 #'

R/indexing.R

@@ -196,27 +196,27 @@
     res
   } else if (missing(i) && missing(j)) {
     if (missing(edges)) {
-      as_adj(x, sparse = sparse, attr = attr)
+      as_adjacency_matrix(x, sparse = sparse, attr = attr)
     } else {
-      as_adj(x, sparse = sparse, attr = attr, edges = edges)
+      as_adjacency_matrix(x, sparse = sparse, attr = attr, edges = edges)
     }
   } else if (missing(j)) {
     if (missing(edges)) {
-      as_adj(x, sparse = sparse, attr = attr)[i, , drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr)[i, , drop = drop]
     } else {
-      as_adj(x, sparse = sparse, attr = attr, edges = edges)[i, , drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr, edges = edges)[i, , drop = drop]
     }
   } else if (missing(i)) {
     if (missing(edges)) {
-      as_adj(x, sparse = sparse, attr = attr)[, j, drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr)[, j, drop = drop]
     } else {
-      as_adj(x, sparse = sparse, attr = attr, edges = edges)[, j, drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr, edges = edges)[, j, drop = drop]
     }
   } else {
     if (missing(edges)) {
-      as_adj(x, sparse = sparse, attr = attr)[i, j, drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr)[i, j, drop = drop]
     } else {
-      as_adj(x, sparse = sparse, attr = attr, edges = edges)[i, j, drop = drop]
+      as_adjacency_matrix(x, sparse = sparse, attr = attr, edges = edges)[i, j, drop = drop]
     }
   }
 }

R/stochastic_matrix.R

@@ -54,7 +54,7 @@ get.stochastic <- function(graph, column.wise = FALSE, sparse = igraph_opt("spar
 #' @return A regular matrix or a matrix of class `Matrix` if a
 #'   `sparse` argument was `TRUE`.
 #' @author Gabor Csardi \email{csardi.gabor@@gmail.com}
-#' @seealso [as_adj()]
+#' @seealso [as_adjacency_matrix()]
 #' @export
 #' @keywords graphs
 #' @examples

demo/community.R

@@ -72,7 +72,7 @@ if (require(Matrix)) {
 } else {
   myimage <- image
 }
-A <- as_adj(G)
+A <- as_adjacency_matrix(G)
 myimage(A)
 
 pause()