Add check for empty network in scale-freeness functions

To avoid running into various errors when calculating scale-freeness
for an empty network, check if the network is empty before calculating
scale-freeness and return `NA` right away if the network is empty.

Signed-off-by: Thomas Bock <[email protected]>

util-networks-metrics.R

@@ -217,8 +217,19 @@ metrics.is.smallworld = function(network) {
 #' @param minimum.number.vertices the minimum number of vertices with which
 #'                                a network can be scale free [default: 30]
 #'
-#' @return A dataframe containing the different values, connected to scale-freeness.
+#' @return If the network is empty (i.e., has no vertices), \code{NA}.
+#'         Otherwise, a dataframe containing the different values, connected to scale-freeness.
 metrics.scale.freeness = function(network, minimum.number.vertices = 30) {
+
+    ## check whether the network is empty, i.e., if it has no vertices
+    if (igraph::vcount(network) == 0) {
+        ## print user warning instead of igraph error
+        logging::logwarn("The input network has no vertices. Will return NA right away.")
+
+        ## cancel the execution and return NA
+        return(NA)
+    }
+
     v.degree = sort(igraph::degree(network, mode = "total"), decreasing = TRUE)
 
     ## Power-law fiting
@@ -263,10 +274,15 @@ metrics.scale.freeness = function(network, minimum.number.vertices = 30) {
 #'                                a network can be scale free [default: 30]
 #'
 #' @return \code{TRUE}, if the network is scale free,
-#'         \code{FALSE}, otherwise.
+#'         \code{FALSE}, if it is not scale free,
+#'         \code{NA}, if the network is empty (i.e., has no vertices).
 metrics.is.scale.free = function(network, minimum.number.vertices = 30) {
     df = metrics.scale.freeness(network, minimum.number.vertices)
-    return(df[["KS.p"]] >= 0.05)
+    if (is.single.na(df)) {
+        return(NA)
+    } else {
+        return(df[["KS.p"]] >= 0.05)
+    }
 }
 
 #' Calculate the hierarchy values for a network, i.e., the vertex degrees and the local