fix: error if permutation networks are empty (#38)

DESCRIPTION

@@ -53,4 +53,4 @@ Suggests:
 RdMacros: Rdpack
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.1
+RoxygenNote: 7.1.2

R/calc_diff_props.R

@@ -11,8 +11,6 @@ calc_diff_props <- function(adja1, adja2, dissMat1, dissMat2, assoMat1, assoMat2
   isempty1 <- all(adja1[lower.tri(adja1)] == 0)
   isempty2 <- all(adja2[lower.tri(adja2)] == 0)
 
-  if(isempty1 & isempty2) stop("There are no connected nodes in both networks.")
-
   # calculate network properties
   props1 <- calc_props(adjaMat = adja1, dissMat = dissMat1, assoMat = assoMat1, 
                        avDissIgnoreInf = avDissIgnoreInf,
@@ -68,13 +66,11 @@ calc_diff_props <- function(adja1, adja2, dissMat1, dissMat2, assoMat1, assoMat2
   avDiss2_lcc <- props2$avDiss_lcc
 
   if(is.na(avDiss1)){
-    avDiss1 <- 0
-    avDiss1_lcc <- 0
+    avDiss1 <- avDiss1_lcc <- 1
   } 
 
   if(is.na(avDiss2)){
-    avDiss2 <- 0
-    avDiss2_lcc <- 0
+    avDiss2 <- avDiss2_lcc <- 1
   }
 
   diffdiss <- abs(avDiss1 - avDiss2)
@@ -90,13 +86,11 @@ calc_diff_props <- function(adja1, adja2, dissMat1, dissMat2, assoMat1, assoMat2
   avPath2_lcc <- props2$avPath_lcc
 
   if(is.na(avPath1)){
-    avPath1 <- 0
-    avPath1_lcc <- 0
+    avPath1 <- avPath1_lcc <- 1
   } 
 
   if(is.na(avPath2)){
-    avPath2 <- 0
-    avPath2_lcc <- 0
+    avPath2 <- avPath2_lcc <- 1
   }
 
   diffpath <- abs(avPath1 - avPath2)
@@ -112,13 +106,11 @@ calc_diff_props <- function(adja1, adja2, dissMat1, dissMat2, assoMat1, assoMat2
   clustCoef2_lcc <- props2$clustCoef_lcc
 
   if(is.na(clustCoef1)){
-    clustCoef1 <- 0
-    clustCoef1_lcc <- 0
+    clustCoef1 <- clustCoef1_lcc <- 0
   } 
 
   if(is.na(clustCoef2)){
-    clustCoef2 <- 0
-    clustCoef2_lcc <- 0
+    clustCoef2 <- clustCoef2_lcc <- 0
   } 
 
   diffclustcoef <- abs(clustCoef1 - clustCoef2)

R/calc_props.R

@@ -54,19 +54,7 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
                        weightDeg, normDeg, normBetw, normClose, normEigen,
                        centrLCC, jaccard = FALSE, jaccQuant = NULL, 
                        verbose = 0){
-
-  if(isempty){
-    output <- list(clust = NULL, tree = NULL, deg = 0, deg_unnorm = 0,
-                   betw = 0, betw_unnorm = 0, close = 0, close_unnorm = 0,
-                   eigen = 0, eigen_unnorm = 0, lccSize = 0,
-                   avDiss = 0, avDiss_lcc = 0, avPath = 0, avPath_lcc = 0,
-                   vertconnect = 0, vertconnect_lcc = 0, edgeconnect = 0, 
-                   edgeconnect_lcc = 0, clustCoef = 0, clustCoef_lcc = 0,
-                   density = 0, density_lcc = 0, modul = 0, modul_lcc = 0,
-                   pep = 0, pep_lcc = 0,  hubs = NULL, topdeg = NULL, 
-                   topbetw = NULL, topclose = NULL, topeigen = NULL)
-    return(output)
-  }
+
 
   #== Create igraph objects and decompose graph ================================
   # Create graph from adjacency matrix
@@ -78,10 +66,10 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
   net <- igraph::graph_from_adjacency_matrix(adjaMat, weighted=T,
                                              mode="undirected", diag=F)
 
+  nNodes <- ncol(adjaMat)
+
   # decomposed graph
   dg_net <- igraph::decompose.graph(net)
-
-  nNodes <- ncol(adjaMat)
 
   # size and number of the connected components
   dgcount <- unlist(lapply(dg_net, igraph::vcount))
@@ -91,6 +79,40 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
   dimnames(compSize) <- list(c("size:", "   #:"), rep("", ncol(compSize)))
   compSize <- compSize[, order(compSize[1,], decreasing = TRUE), drop = FALSE]
 
+  if(isempty){
+    emptyvec <- numeric(nNodes)
+    names(emptyvec) <- colnames(adjaMat)
+
+    output <- list()
+
+    output$nComp <- nNodes
+    output$compSize<- compSize 
+    output$lccNames <- names(emptyvec)[1]
+    output$clust <- emptyvec
+    output$tree <- NULL
+    output$clust_lcc <- emptyvec[1]
+    output$tree_lcc <- NULL
+    output$deg <- output$deg_unnorm <- emptyvec
+    output$betw <- output$betw_unnorm <- emptyvec
+    output$close <- output$close_unnorm <- emptyvec
+    output$eigen <- output$eigen_unnorm <- emptyvec
+    output$lccSize <- 1
+    output$lccSizeRel <- 1/nNodes
+    output$avDiss <- output$avDiss_lcc <- 1
+    output$avPath <- output$avPath_lcc <- 1
+    output$vertconnect <- output$vertconnect_lcc <- 0
+    output$edgeconnect <- output$edgeconnect_lcc <- 0
+    output$natConnect <- output$natConnect_lcc <- 0
+    output$clustCoef <- output$clustCoef_lcc <- 0
+    output$density <- output$density_lcc <- 0
+    output$modul <- output$modul_lcc <- 0
+    output$pep <- output$pep_lcc <- 0
+    output$hubs <- output$topdeg <- output$topbetw <- output$topclose <- 
+      output$topeigen <- character(0)
+
+    return(output)
+  }
+
   # Largest connected component (LCC)
   indLCC <- which.max(unlist(lapply(dg_net, function(x) length(igraph::V(x)))))
 
@@ -223,7 +245,7 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
 
 
   #== Shortest paths ===========================================================
-  
+
   if(verbose == 2){
     message("Compute shortest paths ... ", appendLF = FALSE)
   }
@@ -254,7 +276,10 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
 
     ### average dissimilarity
     avDiss <- mean(dissVec, na.rm = TRUE)
+    if(is.na(avDiss)) avDiss <- 1
+
     avDiss_lcc <- mean(dissVec_lcc, na.rm = TRUE)
+    if(is.na(avDiss_lcc)) avDiss_lcc <- 1
 
     # "normalized" shortest paths (units with average dissimilarity)
     if(sPathNorm){
@@ -278,11 +303,11 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
   sPathVec <- sPath[lower.tri(sPath)]
   sPathVec[is.infinite(sPathVec)] <- NA
   avPath <- mean(sPathVec, na.rm = TRUE)
-  if(is.na(avPath)) avPath <- 0
+  if(is.na(avPath)) avPath <- 1
 
   sPathVec_lcc <- sPath_lcc[lower.tri(sPath_lcc)]
   avPath_lcc <- mean(sPathVec_lcc, na.rm = TRUE)
-  if(is.na(avPath_lcc)) avPath_lcc <- 0
+  if(is.na(avPath_lcc)) avPath_lcc <- 1
 
   if(verbose == 2){
     message("Done.")
@@ -338,10 +363,12 @@ calc_props <- function(adjaMat, dissMat, assoMat, avDissIgnoreInf,
     # Complete network
     clustCoef.tmp <- igraph::transitivity(net, type = "barrat")
     clustCoef <- mean(clustCoef.tmp, na.rm = TRUE)
+    if(is.nan(clustCoef)) clustCoef <- 0
 
     # LCC
     clustCoef.tmp <- igraph::transitivity(net_lcc, type = "barrat")
     clustCoef_lcc <- mean(clustCoef.tmp, na.rm = TRUE)
+    if(is.nan(clustCoef_lcc)) clustCoef_lcc <- 0
 
     rm(clustCoef.tmp)
   } else{