Fix the behavior of get.expanded.adjacency.matrices

In commit e72eff8, the function
`get.expanded.adjacency.matrices` has been refactored. Unfortunately,
the author names have only be extracted from each network individually
instead of globally over all networks. This way, the functionality of
the function has been changed inadvertently. With this commit, we
follow-up on this and restore the previous behavior.

As `get.author.names.from.networks(networks)` now always returns a list,
accessing the first element is necessary (although this was not
necessary in previous implementations).

Moreover, this commit also fixes a wrong test with respect to
get.expanded.adjacency.matrices`.

Signed-off-by: Thomas Bock <bockthom@cs.uni-saarland.de>

tests/test-util-networks-misc.R

@@ -12,6 +12,7 @@
 ## 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
 ##
 ## Copyright 2024 by Leo Sendelbach <s8lesend@stud.uni-saarland.de>
+## Copyright 2024 by Thomas Bock <bockthom@cs.uni-saarland.de>
 ## All Rights Reserved.
 
 
@@ -576,19 +577,6 @@ test_that("getting a sparse adjacency matrix per network, two networks", {
         to = c("Dieter", "Klaus", "Heinz")
         )
     network.in.one = igraph::graph.data.frame(edges, directed = FALSE, vertices = vertices)
-    authors.in.one = sort(c("Heinz", "Dieter", "Klaus"))
-
-    matrix.out.one = Matrix::sparseMatrix(i = c(), j = c(), x = 0, dims = c(length(authors.in.one),
-                                          length(authors.in.one)), repr = "T")
-    rownames(matrix.out.one) = authors.in.one
-    colnames(matrix.out.one) = authors.in.one
-
-    # order these statements so that the second arguments are ordered alphabetically
-    # or use the helper function as used below
-    matrix.out.one["Heinz", "Dieter"] = 1
-    matrix.out.one["Klaus", "Dieter"] = 1
-    matrix.out.one["Dieter", "Heinz"] = 1
-    matrix.out.one["Dieter", "Klaus"] = 1
 
     vertices = data.frame(
         name = c("Klaus", "Tobias"),
@@ -600,14 +588,27 @@ test_that("getting a sparse adjacency matrix per network, two networks", {
         to = c("Tobias")
         )
     network.in.two = igraph::graph.data.frame(edges, directed = FALSE, vertices = vertices)
-    authors.in.two = sort(c("Klaus", "Tobias"))
 
-    matrix.out.two = Matrix::sparseMatrix(i = c(), j = c(), x = 0, dims = c(length(authors.in.two),
-                                          length(authors.in.two)), repr = "T")
-    rownames(matrix.out.two) = authors.in.two
-    colnames(matrix.out.two) = authors.in.two
+    all.authors = sort(c("Heinz", "Dieter", "Klaus", "Tobias"))
+
+    matrix.out.one = Matrix::sparseMatrix(i = c(), j = c(), x = 0, dims = c(length(all.authors),
+                                          length(all.authors)), repr = "T")
+    rownames(matrix.out.one) = all.authors
+    colnames(matrix.out.one) = all.authors
 
-    # order these statements so that the second arguments are ordered alphabetically 
+    # order these statements so that the second arguments are ordered alphabetically
+    # or use the helper function as used below
+    matrix.out.one["Heinz", "Dieter"] = 1
+    matrix.out.one["Klaus", "Dieter"] = 1
+    matrix.out.one["Dieter", "Heinz"] = 1
+    matrix.out.one["Dieter", "Klaus"] = 1
+
+    matrix.out.two = Matrix::sparseMatrix(i = c(), j = c(), x = 0, dims = c(length(all.authors),
+                                          length(all.authors)), repr = "T")
+    rownames(matrix.out.two) = all.authors
+    colnames(matrix.out.two) = all.authors
+
+    # order these statements so that the second arguments are ordered alphabetically
     # or use the helper function as used below
     matrix.out.two["Tobias", "Klaus"] = 1
     matrix.out.two["Klaus", "Tobias"] = 1

util-networks-misc.R

@@ -14,7 +14,7 @@
 ## Copyright 2016-2017 by Sofie Kemper <kemperso@fim.uni-passau.de>
 ## Copyright 2016-2017 by Claus Hunsen <hunsen@fim.uni-passau.de>
 ## Copyright 2016-2018 by Thomas Bock <bockthom@fim.uni-passau.de>
-## Copyright 2020, 2023 by Thomas Bock <bockthom@cs.uni-saarland.de>
+## Copyright 2020, 2023-2024 by Thomas Bock <bockthom@cs.uni-saarland.de>
 ## Copyright 2017 by Angelika Schmid <schmidang@fim.uni-passau.de>
 ## Copyright 2019 by Jakob Kronawitter <kronawij@fim.uni-passau.de>
 ## Copyright 2019-2020 by Anselm Fehnker <anselm@muenster.de>
@@ -169,7 +169,7 @@ get.expanded.adjacency = function(network, authors, weighted = FALSE) {
 }
 
 #' Calculates a sparse adjacency matrix for each network in the list.
-#' All adjacency matrices are expanded in such a way that the use the same set
+#' All adjacency matrices are expanded in such a way that they use the same set
 #' of authors derived from all networks in the list.
 #'
 #' @param networks list of networks
@@ -178,10 +178,9 @@ get.expanded.adjacency = function(network, authors, weighted = FALSE) {
 #' @return the list of adjacency matrices
 get.expanded.adjacency.matrices = function(networks, weighted = FALSE){
 
-    adjacency.matrices = parallel::mclapply(networks, function(network) {
-        active.authors = sort(igraph::V(network)$name)
-        return(get.expanded.adjacency(network = network, authors = active.authors, weighted = weighted))
-    })
+    authors = get.author.names.from.networks(networks)[[1]]
+
+    adjacency.matrices = parallel::mclapply(networks, get.expanded.adjacency, authors, weighted)
 
     return(adjacency.matrices)
 }