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diff --git a/R Scripts/find-cascades.R b/R Scripts/find-cascades.R
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+library(igraph)
+setwd("~/Documents/Cascade Project/")
+load('Results/hyper-lcc.RData')
+load('Results/dag_dat_vics.RData')
+source('Scripts/temporal.R')
+# source('Scripts/homophily.R')
+source('Scripts/structural.R')
+
+vic_ids = which(V(hyp_lcc)$vic==TRUE)
+
+#### Initialize model parameters
+alpha = 1/5
+# gamma = 0.3
+delta = 0.1
+beta = 9.955713e-6
+
+##### Get weights
+# find max n days where infection possible given alpha
+edges = dag_dat_vics
+# edges = edges[(edges$t2-edges$t1)<300,]
+
+p_t = temporal(edges$t1, edges$t2, alpha)
+p_s = structural(delta, edges$dist)
+p = p_s * p_t
+p_tilde = 1 - p_s + p_s * temporal(edges$t1, edges$t2+1, alpha)
+weights = p/p_tilde
+
+##### Find transmission edges
+# load('Results/lm-probs.RData')
+# names = attr(lm.probs,'names')
+# probs = as.numeric(lm.probs)
+# betas = probs[match(hyp_lcc_verts$ir_no[edges$to],names)]
+# betas = 0.055
+thresh = beta/(1-beta)
+
+realized = c()
+# edges = edges[weights>thresh,]
+# weights = weights[weights>thresh]
+for (u in vic_ids){
+  max_prob = -1
+  max_edge = NULL
+  Ei = which(edges$to==u)
+  for(i in Ei){
+    if(weights[i]>thresh){
+      prob = p[i] * prod(p_tilde[setdiff(Ei,i)])
+      if(prob>max_prob){
+        max_prob = prob
+        max_edge = i
+      }
+    }
+  }
+  realized = c(realized, max_edge)
+}
+#   if (length(Ei)>0){
+#     max_edge = Ei[which.max(weights[Ei])] # how to deal with ties????
+#     realized = c(realized, max_edge)
+#   }
+
+##### Create forest of cascades
+# dag is all of the victim nodes but with only transmission edges, or don't index by vic_ids
+dag = graph.data.frame(edges[realized,1:2], directed=TRUE, vertices=hyp_lcc_verts[vic_ids,])
+dag = set.edge.attribute(dag,'weight',value=weights[realized])
+table(clusters(dag)$csize)
+
+t=table(clusters(dag)$csize)
+sizes = as.numeric(attr(t,'name'))
+counts = as.numeric(t)
+plot(sizes,counts,log='xy',type='o',lwd=3)
+n.seeds = sum(counts)
+n.nodes = sum(sizes*counts) # for vics case is just length(vic_ids)
+n.infections = n.nodes-n.seeds
+
+# dag = graph.edgelist(as.matrix(edges[realized,1:2]))