sparse matrix is now never converted into non-sparse, solving issues_15

.src/R1_code/sub-challenge1/mlrmcl_r4_v2.R

@@ -106,14 +106,25 @@ preProcessing <- function(input,method=c("quantile","pageRank","double"),i,integ
 
 generateFile <- function(graph,weighted=T){
   test3<-get.adjacency(graph,attr = "weight")
-  m<-as.matrix(test3)
-  m.index<-apply(m!=0,1,which,arr.ind=T)
-  # weight<-m[m.index]
+  m.index<-get.adjlist(graph)
+  graph_directed <- as.directed(graph)
+  m.weight <- get.edge.attribute(graph_directed,name = "weight")
+  # m<-as.matrix(test3)
   if (weighted){
-    test<-sapply(1:nrow(m), function(i) m[i,m.index[[i]]])
+    # test<-sapply(1:nrow(m), function(i) m[i,m.index[[i]]])
     temp2<-list()
+    # temp2_t <- list()
+    count <- 1
     for (i in 1:length(m.index)){
-      temp2[[i]]<-c(rbind(as.character(m.index[[i]]),test[[i]]))
+      num_edge_i = length(m.index[[i]])
+      if (num_edge_i == 0){
+        temp2[[i]]<-c(rbind(as.character(m.index[[i]]),numeric(0)))
+      } else{
+        edge_weight_i <- m.weight[count:(count+num_edge_i-1)]
+        # temp2_t[[i]]<-c(rbind(as.character(m.index[[i]]),test[[i]]))
+        temp2[[i]]<-c(rbind(as.character(m.index[[i]]),edge_weight_i))
+        count <- count + num_edge_i
+      }
     }
     fn <- "test.txt"
     if (file.exists(fn)) file.remove(fn)
@@ -129,7 +140,8 @@ generateFile <- function(graph,weighted=T){
 
 }
 
-postProcessing <- function(method=c("random","discard","recluster"),smallest = 3,largest=100,g=graph,b2,c2,i2){
+postProcessing <- function(method=c("random","discard","recluster"),smallest = 3,largest=100,
+                           g=graph,b2,c2,i2){
   result<-read.table("output.txt")
   output<-list()
   # for (i in 1:nrow(unique(result))){