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library(igraph)
setwd("~/Documents/Violence Cascades/")
load('Results/hyper-lcc.RData')
vic_ids = which(V(hyp_lcc)$vic==1)
n.infections = length(vic_ids)
n.days = max(hyp_lcc_verts$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$dob[vic_ids]),'%Y'))
# nbrs = neighborhood(graph, nodes=vic_ids, order=1)
load('Results/vic-nbrs.RData')
n = 150
mean.time = matrix(0,1,n)
med.time = matrix(0,1,n)
mean.50 = matrix(0,1,n)
mean.100 = matrix(0,1,n)
n.vicpairs = matrix(0,1,n)
hyp_lcc = upgrade_graph(hyp_lcc)
ptm = proc.time()
for(q in 1:n){
if (q%%250==0) print(paste('run:',q))
graph = hyp_lcc
vics = vic_ids
sim.dates = rep(0,length(vic_ids))
for(y in unique(birthyears)){
year_ids = which(birthyears==y)
if (length(year_ids)>1) sim.dates[year_ids] = sample(inf.dates[year_ids])
}
# {vics = vic_ids; sim.dates = inf.dates} # data
vic.time = rep(NA,14885)
idx = 1
for (i in 1:n.infections){
u = vics[i]
nbhd = nbrs[[i]]
nbhd = intersect(vic_ids,nbhd)
nbhd = nbhd[u<nbhd] # only looks at pairs with u<v to avoid double-counting
nbhd = setdiff(nbhd,u)
nbhd = nbhd[hyp_lcc_verts$ir_no[u] != hyp_lcc_verts$ir_no[nbhd]] # don't count infections of the same person
if (length(nbhd)==0) next
tu = sim.dates[i]
tvs = sim.dates[match(nbhd,vic_ids)]
vic.time[idx:(idx+length(nbhd)-1)] = abs(tu-tvs)
idx = idx + length(nbhd)
}
n.vicpairs[q] = length(vic.time)
mean.time[q] = mean(vic.time)
med.time[q] = median(vic.time)
mean.50[q] = mean(vic.time<=50)
mean.100[q] = mean(vic.time<=100)
# decay.rate[sim,q] = getDecayRate(vic.time) #get lm of histogram. or maybe just cor?
}
print(proc.time()-ptm)
####### plot simulation data #######
data = 634 # 774.5483, 634, 0.07252472, 0.1176774
simdata = med.time
xl = c(0.9*min(min(simdata),data),1.1*max(max(simdata),data))
yl = c(0,max(hist(simdata,15)$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)
abline(v=data,lwd=4,col='red')
##### inf dates histogram
dates = c(V(lcc)$fatal_date[!is.na(V(lcc)$fatal_date)],
V(lcc)$nonfatal_date_1[!is.na(V(lcc)$nonfatal_date_1)],
V(lcc)$nonfatal_date_2[!is.na(V(lcc)$nonfatal_date_2)],
V(lcc)$nonfatal_date_3[!is.na(V(lcc)$nonfatal_date_3)],
V(lcc)$nonfatal_date_4[!is.na(V(lcc)$nonfatal_date_4)],
V(lcc)$nonfatal_date_5[!is.na(V(lcc)$nonfatal_date_5)])
dates = as.Date(dates)
hist(dates, breaks='months',freq=T,col='lightblue',format='%m/%Y',
xlab='Month',ylab='Number of Shootings',main='')
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