7 files changed, 107 insertions, 16 deletions
diff --git a/R Scripts/analyze-cascades.R b/R Scripts/analyze-cascades.R
index 02f9349..8bbb598 100755
--- a/R Scripts/analyze-cascades.R
+++ b/R Scripts/analyze-cascades.R
@@ -12,9 +12,10 @@ counts = rep(0,max(sizes))
 counts[data$V1] = data$V2
 pl = power.law.fit(counts)
 plot(sizes,counts,log='xy',pch=20,col='#1f78b4',xaxt='n',yaxt='n',
-     xlab='Size of Cascade', ylab='Number of Cascades', main='')
-axis(1,at=c(1,5,10,50,100,500))
-axis(2,at=c(1,10,100,1000))
+     xlab='Size of cascade', ylab='Number of cascades', main='',
+     cex.axis=0.6,cex.lab=0.6)
+axis(1,at=c(1,5,10,50,100,500),cex.axis=0.6)
+axis(2,at=c(1,10,100,1000),cex.axis=0.6)
 
 sizes_pl = displ$new(counts[counts>1])
 est = estimate_xmin(sizes_pl)
diff --git a/R Scripts/arrest-vs-infection-times.R b/R Scripts/arrest-vs-infection-times.R
index 222be3e..7c0bfcf 100644
--- a/R Scripts/arrest-vs-infection-times.R
+++ b/R Scripts/arrest-vs-infection-times.R
@@ -1,6 +1,38 @@
 library(igraph)
-setwd('~/Documents/Cascade Project/Raw Data/')
+setwd('~/Documents/Violence Cascades/Raw Data/')
 
+
+person_verts = get.data.frame(person,'vertices')
+vics = person_verts$vic
+vic_verts = person_verts[vics,14:19]
+first_vics = apply(vic_verts,1,min,na.rm=T)
+
+
+load('arrests.RData')
+arr = arrests[order(arrests$date2),]
+arr = arr[match(unique(arr$ir2),arr$ir2),]
+arr = arr[match(rownames(person_verts),arr$ir2),]
+arr = arr[vics,]
+offset = 16802
+first_arrests = as.numeric(arr$date2) - offset
+
+lag = first_vics - first_arrests
+hist(lag,100,col='')
+h = hist(lag,150,col='#1f78b4',border=NA,axes=T,
+         xlab='',ylab='Frequency',main=NULL)
+box(lwd=1.1)
+
+
+
+
+
+
+
+
+
+
+
+#### OLD VERSION
 ##### Load arrest data
 arrests <- read.csv("2006to2014arrests2.csv", header=T, colClass=c("character"))
 arrests$ir2 <- paste("ir", arrests$ir_no)
@@ -41,3 +73,4 @@ murders = murders[murders$ir2 %in% arrests$ir2,]
 mur_dates = murders$INJURY_DATE
 arrest_dates = sub.arrests$dates[match(murders$ir2, sub.arrests$individuals)]
 sum(mur_dates==arrest_dates)
+
diff --git a/R Scripts/data-exploration.R b/R Scripts/data-exploration.R
index 16e7bba..f8f6892 100755
--- a/R Scripts/data-exploration.R
+++ b/R Scripts/data-exploration.R
@@ -1,6 +1,6 @@
 library(igraph)
 setwd("~/Documents/Violence Cascades/")
-load('Results/hyper-lcc.RData')
+load('Raw Data/lcc.RData')
 
 d = remove.edge.attribute(person,'weight')
 lcc = induced.subgraph(d,which(clusters(d)$membership==which.max(clusters(d)$csize)))
@@ -29,8 +29,8 @@ S
 
 ##### Degree Distribution
 plot(1:max(degree(lcc)),degree.distribution(lcc)[-1]*vcount(lcc),
-     log='xy',col='#377EB8',pch=20,
-     xlab='Degree', ylab='Number of Vertices', main='')
+     log='xy',col='#1f78b4',pch=20,cex.axis=0.6,cex.lab=0.6,
+     xlab='Degree', ylab='Number of vertices', main='')
 pl = power.law.fit(degree.distribution(lcc))
 
 ##### Victims
diff --git a/R Scripts/fit-background.R b/R Scripts/fit-background.R
index a5f935b..49fb64d 100644
--- a/R Scripts/fit-background.R
+++ b/R Scripts/fit-background.R
@@ -30,8 +30,9 @@ res = nls(formula=fit_form, data=infs, start=list(lambda=3, A=2, phi=4))
 co = coef(res); co
 
 plot(t)
-plot(days,counts,pch=20,cex=0.5,col='#1f78b4',
-     xlab='Day',ylab='Number of Infections')
+plot(days,counts,pch=20,cex=0.5,col='#1f78b4',xaxt='n',
+     xlab='',ylab='Number of shootings',cex.axis=0.6,cex.lab=0.6)
 curve(fit(x, lambda=co["lambda"], A=co["A"], phi=co["phi"]), 
       add=TRUE ,lwd=3, col="#1a9850")
+axis(1,at=seq(1,max(days),365),lab=2006:2014,cex.axis=.6)
 
diff --git a/R Scripts/plot-crime-data.R b/R Scripts/plot-crime-data.R
new file mode 100644
index 0000000..13800cc
--- /dev/null
+++ b/R Scripts/plot-crime-data.R
@@ -0,0 +1,54 @@
+###################
+# load crime data
+library(xlsx)
+setwd("~/Documents/Violence Cascades/Raw Data/")
+data = read.xlsx('Chicago-crime-data.xlsx',1)
+
+# crime rate
+plot(data$Year,data$Index.Rate.per.100.000,type='l',col='#1f78b4',lwd=2,
+     xlab='',ylab='Rate per 100,000',cex.lab=.6,cex.axis=.6)
+
+# homocide rate
+plot(data$Year,data$Homicide.Rate,type='l',col='#1f78b4',lwd=2,
+     xlab='',ylab='Rate per 100,000',cex.lab=.6,cex.axis=.6)
+
+###################
+# load shootings data
+# for lcc
+load('lcc.RData')
+vic_dates = as.Date(unlist(lcc_verts[,10:15]))
+vic_dates = vic_dates[!is.na(vic_dates)]
+vdh = hist(vic_dates, breaks='months')
+
+plot(vdh$mids,vdh$counts,type='l',col='#1f78b4',lwd=2,
+     xlab='',ylab='Shootings',xaxt='n',cex.lab=.6,cex.axis=.6)
+axis(1,at=vdh$breaks[seq(1,102,12)],
+     lab=2006:2014,cex.axis=.6)
+
+
+# for all recorded shootings
+shootings <- read.csv("shooting-data-withdate2.csv", header = T)
+victims = shootings[shootings$INV_PARTY_TYPE_CD=="VIC",]
+victims = victims[!is.na(victims$IR_NO),]
+victims$ir2 <- paste("ir", victims$IR_NO)
+
+# get murder victim attributes
+murders = read.csv("murder-victims-13nov.csv", header=T)
+murders = murders[!is.na(murders$VICTIM_IR_NO),]
+murders = murders[murders$INJURY_DESCR=="SHOT",]
+murders = murders[match(unique(murders$VICTIM_IR_NO),murders$VICTIM_IR_NO),]
+murders = murders[as.Date(murders$INJURY_DATE,format='%m/%d/%y')>=start_date,]
+murders$ir2 = paste("ir", murders$VICTIM_IR_NO)
+
+# clear nonfatals that led to death
+v = victims[victims$IR_NO %in% murders$VICTIM_IR_NO,]
+rows = c()
+for(i in 1:dim(v)[1]){
+  row = which(rownames(victims)==as.numeric(rownames(v[i,])))
+  m = murders[murders$VICTIM_IR_NO==v$IR_NO[i],]
+  dup = as.Date(v$INCIDENT_DATE[i],format='%m/%d/%y') %in% as.Date(m$INJURY_DATE,format='%m/%d/%y')
+  if(dup==T) rows = c(rows,row)
+}
+victims = victims[-rows,]
+
+vic_dates = c(as.Date(murders$INJURY_DATE,format='%m/%d/%y'),as.Date(victims$INCIDENT_DATE,format='%m/%d/%y'))
+\ No newline at end of file
diff --git a/R Scripts/plot-network.R b/R Scripts/plot-network.R
index 93c48fb..1339dd6 100644
--- a/R Scripts/plot-network.R
+++ b/R Scripts/plot-network.R
@@ -21,5 +21,5 @@ plot(lcc,vertex.size=1,vertex.color=cols,vertex.label=NA,
      layout=layout.drl,edge.color=NA,vertex.frame.color=NA)
 
 # library(rgl)
-rglplot(lcc,vertex.size=1,vertex.color=cols,vertex.label=NA,
-     layout=layout.drl,edge.color=NA,vertex.frame.color=NA)
+# rglplot(lcc,vertex.size=1,vertex.color=cols,vertex.label=NA,
+#      layout=layout.drl,edge.color=NA,vertex.frame.color=NA)
diff --git a/R Scripts/sim-analysis.R b/R Scripts/sim-analysis.R
index e56f575..51659f5 100755
--- a/R Scripts/sim-analysis.R
+++ b/R Scripts/sim-analysis.R
@@ -68,18 +68,20 @@ colnames(simdata)=c('mean.time','med.time','mean.30','mean.100')
 ####### plot simulation data #######
 # mean=662.6, med=488, m30=0.076, m60=0.119, m100=0.167
 d = c(662.6,488,0.076,0.167)
-xlabs = c('Mean time between infections',
-          'Median time between infections',
+xlabs = c('Mean days between infections',
+          'Median days between infections',
           'Infections within 30 days',
           'Infections within 100 days')
+xlims = matrix(c(660,765,475,625,0.03,0.08,0.1,0.18),ncol=2,byrow=T)
 par(mfrow=c(2,2))
 for(i in 1:4){
   data = d[i] 
   sdata = simdata[,i]
-  xl = c(0.99*min(min(sdata),data),1.01*max(max(sdata),data))
+  xl = xlims[i,]
   h = hist(sdata,50,xlim=xl,col='#1f78b4',freq=T,border=NA,axes=F,
-       xlab=xlabs[i],ylab='Relative Frequency',main=NULL)
-  axis(1,at=pretty(xl,5))
+       xlab=xlabs[i],ylab='Relative frequency',main=NULL)
+  if(i %in% c(1,2)) axis(1,at=pretty(xl,5))
+  if(i %in% c(3,4)) axis(1,at=pretty(xl,5),lab=paste(pretty(xl,5)*100,'%',sep=''))
   axis(2,at=pretty(h$counts,3),lab=pretty(h$counts/n,3))
   abline(v=data,lwd=4,col='#e41a1c')
   box(lwd=1.1)