added age to sim analysis and updated data generation for new model

1 files changed, 52 insertions, 42 deletions

diff --git a/R Scripts/sim-analysis.R b/R Scripts/sim-analysis.R
index 3960578..5010485 100755
--- a/R Scripts/sim-analysis.R
+++ b/R Scripts/sim-analysis.R
@@ -1,5 +1,5 @@
 library(igraph)
-setwd("~/Documents/Cascade Project/")
+setwd("~/Documents/Violence Cascades/")
 
 load('Results/hyper-lcc.RData')
 vic_ids = which(V(hyp_lcc)$vic==1)
@@ -7,56 +7,66 @@ n.infections = length(vic_ids)
 n.days = max(hyp_lcc_verts$vic.day,na.rm=T) - min(hyp_lcc_verts$vic.day,na.rm=T)
 inf.dates = hyp_lcc_verts$vic.day[vic_ids]
 
+birthyears = as.numeric(format(as.Date(hyp_lcc_verts$dob[vic_ids]),'%Y'))
+
+# nbrs = neighborhood(graph, nodes=vic_ids, order=1)
+load('Results/vic-nbrs.RData')
+
+n = 150
+mean.time = matrix(0,1,n)
+med.time = matrix(0,1,n)
+mean.50 = matrix(0,1,n)
+mean.100 = matrix(0,1,n)
+n.vicpairs = matrix(0,1,n)
+
+hyp_lcc = upgrade_graph(hyp_lcc)
+
 ptm = proc.time()
-n = 1500
-mean.time = matrix(0,3,n)
-med.time = matrix(0,3,n)
-mean.50 = matrix(0,3,n)
-mean.100 = matrix(0,3,n)
-n.vicpairs = matrix(0,3,n)
-for(sim in 1:3){
-  print(paste('sim:',sim))
-  for(q in 1:n){
-    if (q%%250==0) print(paste('run:',q))
-    graph = hyp_lcc
-    if (sim<3) sim.dates = sample(n.days, n.infections, replace=TRUE) # sims 1 + 2
-    if (sim==3) sim.dates = sample(inf.dates) # sim 3
-    if (sim==1) vics = sample(vcount(hyp_lcc), n.infections, replace=FALSE) # sim 1
-    if (sim>1) vics = vic_ids # sims 2 + 3
-    if (sim==0) {vics = vic_ids; sim.dates = inf.dates} # data
-    
-    vic.time = c()
-    for (i in 1:n.infections){
-      u = vics[i]
-      nbhd = unlist(neighborhood(graph, nodes=u, order=1))
-      nbhd = intersect(vic_ids,nbhd)
-      nbhd = setdiff(nbhd,u)
-      nbhd = nbhd[u<nbhd] # only looks at pairs with u<v to avoid double-counting
-      nbhd = nbhd[hyp_lcc_verts$ir_no[u] != hyp_lcc_verts$ir_no[nbhd]] # don't count infections of the same person
-      tu = sim.dates[i]
-      tvs = sim.dates[match(nbhd,vic_ids)]
-      vic.time = c(vic.time,abs(tu-tvs))
-    }
-    n.vicpairs[sim,q] = length(vic.time)
-    mean.time[sim,q] = mean(vic.time)
-    med.time[sim,q] = median(vic.time)
-    mean.50[sim,q] = mean(vic.time<=50)
-    mean.100[sim,q] = mean(vic.time<=100)
-    #     decay.rate[sim,q] = getDecayRate(vic.time) #get lm of histogram. or maybe just cor?
+for(q in 1:n){
+  if (q%%250==0) print(paste('run:',q))
+  graph = hyp_lcc
+  vics = vic_ids
+  
+  sim.dates = rep(0,length(vic_ids))
+  for(y in unique(birthyears)){
+    year_ids = which(birthyears==y)
+    if (length(year_ids)>1) sim.dates[year_ids] = sample(inf.dates[year_ids])
+  }
+#   {vics = vic_ids; sim.dates = inf.dates} # data
+  
+  vic.time = rep(NA,14885)
+  idx = 1
+  for (i in 1:n.infections){
+    u = vics[i]
+    nbhd = nbrs[[i]]
+    nbhd = intersect(vic_ids,nbhd)
+    nbhd = nbhd[u<nbhd] # only looks at pairs with u<v to avoid double-counting
+    nbhd = setdiff(nbhd,u)
+    nbhd = nbhd[hyp_lcc_verts$ir_no[u] != hyp_lcc_verts$ir_no[nbhd]] # don't count infections of the same person
+    if (length(nbhd)==0) next
+    tu = sim.dates[i]
+    tvs = sim.dates[match(nbhd,vic_ids)]
+    vic.time[idx:(idx+length(nbhd)-1)] = abs(tu-tvs)
+    idx = idx + length(nbhd)
   }
+
+  n.vicpairs[q] = length(vic.time)
+  mean.time[q] = mean(vic.time)
+  med.time[q] = median(vic.time)
+  mean.50[q] = mean(vic.time<=50)
+  mean.100[q] = mean(vic.time<=100)
+  #     decay.rate[sim,q] = getDecayRate(vic.time) #get lm of histogram. or maybe just cor?
 }
 print(proc.time()-ptm)
 
 
 ####### plot simulation data #######
-data = 0.1176774 # 774.5483, 634, 0.07252472, 0.1176774
-simdata = mean.100
+data = 634 # 774.5483, 634, 0.07252472, 0.1176774
+simdata = med.time
 xl = c(0.9*min(min(simdata),data),1.1*max(max(simdata),data))
-yl = c(0,max(c(hist(simdata[1,],15)$density,hist(simdata[2,],15)$density,hist(simdata[3,],15)$density)))
-hist(simdata[1,],15,xlim=xl,ylim=yl,col=rgb(0,1,0,1/4),freq=F,
+yl = c(0,max(hist(simdata,15)$density))
+hist(simdata,15,xlim=xl,ylim=yl,col=rgb(0,1,0,1/4),freq=F,
      xlab='Neighbors Infected Within 100 Days', main=NULL)
-hist(simdata[2,],15,col=rgb(0,0,1,1/4),freq=F,add=TRUE)
-hist(simdata[3,],15,col=rgb(1,0,1,1/4),freq=F,add=TRUE)
 abline(v=data,lwd=4,col='red')