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diff --git a/R Scripts/-simulate-infections.R b/R Scripts/-simulate-infections.R
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+library(igraph)
+setwd("/Users/Ben/Documents/Harvard/Fall 2014/CS 284r Social Data Mining/Cascade Project/")
+
+load('Data/dag_dat.RData')
+load('Data/lcc.RData')
+
+n.infections = length(vic_ids)
+n.nodes = (vcount(lcc))
+n.days = as.numeric(max(dag_dat$t2) - min(dag_dat$t1))
+gamma = n.infections/(n.nodes*n.days)
+
+vic = rep(FALSE,n.nodes)
+for(t in 1:n.days){
+  if (t%%1000==0) print(t)
+  infections = which(runif(n.nodes)<gamma)
+  new.infections = infections[vic[infections]==0]
+  vic[new.infections] = t
+}
+
+lcc.sim = lcc
+V(lcc.sim)$vic = vic>0
+V(lcc.sim)$vic_date = vic
+vic_ids.sim =  which(vic>0)
+# save(lcc.sim,vic_ids.sim, file='Data/lcc_sim1b.RData')
+
+#### simulation method 2 ####
+load('Data/dag_dat.RData')
+load('Data/lcc.RData')
+n.infections = length(vic_ids)
+n.days = as.numeric(max(dag_dat$t2) - min(dag_dat$t1))
+lcc.sim = lcc
+V(lcc.sim)$vic_date[vic_ids] = sample(n.days, n.infections, replace=TRUE)
+vic_ids.sim =  which(V(lcc.sim)$vic)
+# save(lcc.sim, vic_ids.sim, file='Data/lcc_sim2a.RData')