corrected age to account for each node’s spawn date

1 files changed, 3 insertions, 16 deletions

diff --git a/R Scripts/generate-dag-dat.R b/R Scripts/generate-dag-dat.R
index 660a503..b5f2c3a 100755
--- a/R Scripts/generate-dag-dat.R
+++ b/R Scripts/generate-dag-dat.R
@@ -35,25 +35,12 @@ print(proc.time()-ptm) #3.5 hours
 colnames(dag_dat_all) = c('from','to','t1','t2','dist','w1','w2','w3')
 rownames(dag_dat_all) = NULL
 
+dag_dat_all$spawn1 = hyp_lcc_verts$spawn.date[dag_dat_all$from]
+dag_dat_all$spawn2 = hyp_lcc_verts$spawn.date[dag_dat_all$to]
+
 save(dag_dat_all, file='Results/dag_dat_all.RData')
 write.csv(dag_dat_all, file='Results/dag_dat_all.csv')
 
 dag_dat_vics = dag_dat_all[!is.na(dag_dat_all$t2),]
 save(dag_dat_vics, file='Results/dag_dat_vics.RData')
 write.csv(dag_dat_vics, file='Results/dag_dat_vics.csv')
-
-# analyze min possible infection time
-i = 1
-min_time = 0#rep(Inf,length(unique(dag_dat_vics$to)))
-min_time_dist = 0#rep(Inf,length(unique(dag_dat_vics$to)))
-for(to in unique(dag_dat_vics$to)){
-  rows = which(dag_dat_vics$to==to & dag_dat_vics$dist<2)
-  if(length(rows)>0){
-    min_time[i] = min(dag_dat_vics$t2[rows]-dag_dat_vics$t1[rows])
-    min_time_dist[i] = dag_dat_vics$dist[rows[which.min(dag_dat_vics$t2[rows]-dag_dat_vics$t1[rows])]]
-    i = i + 1
-  }
-}
-median(min_time)
-mean(min_time<100)
-save(min_time_1,min_time_2,min_time_3,file='Results/min_inf_time.RData')