testing on real data! IQOR-875 tree

convert time to seconds. start from df and end up with ordered_cgs

#read from csv iqor data
#df=read.csv("geniqor.csv")

#source("callgroupAttacher.R")
source("PcounterEpochOpt.R")

cgs=cbind(df$calltime, df$cg)
cgs=as.data.frame(cgs)

cgs[,1]=as.POSIXct(cgs[,1])
#cgs[,1]=as.numeric(cgs[,1])


ordered_cgs=cgs[order(cgs$V1),]
#remove(df)
remove(cgs)

ordered_cgs[,1]=(ordered_cgs[,1]-ordered_cgs[1,1])

ordering callgroups

#here we start from ordered_cgs
source("PcounterEpochOpt.R")
callgroups=unique(ordered_cgs[,2])
#callgroups=unique(ordered_cgs[,2])[[1]] ins ome cases

cg=list()

for (j in 1:length(callgroups))
{
  cg[[j]]=ordered_cgs[ordered_cgs$V2==callgroups[j],]
}

cg is a list of all callgroups with seconds.

source("PcounterEpochOpt_simp.R")
source("PcounterEpochOpt.R")
sigm=0.1
time_rates=list()
min_len=Inf
for (j in 1:length(callgroups))
{
  print(j)
  time_rates[[j]]=PcounterEpochOpt_simp(350,cg[[j]]$V1, 7, 30, 0.1, 0.15)[,c(1,5)]
#  time_rates[[j]]=PcounterEpochOpt(350,cg[[j]]$V1, 7, 100, 0.1)[,c(1,5)]
  plot(time_rates[[j]], type='l', col='red')
  min_len=min(length(time_rates[[j]][,1]),min_len)
  print(min_len)
}

[1] 1
[1] 10294
[1] 2

[1] 10214
[1] 3

[1] 10214
[1] 4

[1] 10214

print(paste(min_len," is the final min"))

[1] "10214  is the final min"

for (j in 1:length(callgroups))
{
  time_rates[[j]]=time_rates[[j]][(1:min_len),]
  time_rates[[j]][time_rates[[j]][,2]==0,2]=1 # so zero rates are set to 1
}

#all_rates should have rates for each callgroup
all_rates=time_rates[[1]][,1] #the first column has all the times
for (j in 1:length(callgroups))
{
  all_rates=cbind(all_rates,time_rates[[j]][,2])#and then rate for each callgroup attached as a #column
}
all_bw=cbind(all_rates[,1],all_rates[,-1]/apply(all_rates[,-1],1,sum)) #we get all bandwidths from rates for cgs
for (qq in 1:(length(all_bw[1,])-1)) #attach the rate for all arrival
{
 
  print(qq) 
  interval_idx=findInterval(cg[[qq]][,1],all_bw[,1])
  interval_idx[interval_idx==0]=1
  
  cg[[qq]]=cbind(cg[[qq]],all_bw[interval_idx,-1])
}

[1] 1
[1] 2
[1] 3
[1] 4

sds=vector()
for (oi in 1:5)
{
  cum_sum=list()
  cg_arr_cgname_max_bw=list()
  cp_vec=data.frame()
  count_vec=rep(0,10)
  
  for (ww in 1:(length(all_bw[1,])-1))
  {
    
  cum_sum[[ww]]=cbind(cg[[ww]][,c(1,2)],t(apply(cg[[ww]][,c(-1,-2)],1,cumsum)))
  cg_arr_cgname_max_bw[[ww]]=cbind(cg[[ww]][,c(1,2)],cg[[ww]][,ww+2],cum_sum[[ww]][,ww+2])
  
  
  
  for (o in 1:length(cg_arr_cgname_max_bw[[ww]][,1]))
  {
    minbw=cg_arr_cgname_max_bw[[ww]][o,4]-cg_arr_cgname_max_bw[[ww]][o,3]
    maxbw=cg_arr_cgname_max_bw[[ww]][o,4]
    
    cg_arr_cgname_max_bw[[ww]]$cp[o]=
    runif(1, minbw, maxbw)
  
  
  }
  
  cp_vec=rbind(cg_arr_cgname_max_bw[[ww]][,c(1,5)],cp_vec)
  
  }
  
  kkk=hist(cp_vec[,2],10)
  sds[oi]=sd(kkk$counts)
  #hist(cp_vec[cp_vec[,1]<18000,2],5)
}

mean(sds)

[1] 90.79958

source("decscore.R")
rt=list()
for (h in 1:length(cg_arr_cgname_max_bw))
{
  ff=rep(0,length(cg_arr_cgname_max_bw[[h]][,1]))
  ff=as.data.frame(ff)
  ff$V1 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0  ,0.1))
  ff$V2 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.1,0.2))
  ff$V3 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.2,0.3))
  ff$V4 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.3,0.4))
  ff$V5 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.4,0.5))
  ff$V6 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.5,0.6))
  ff$V7 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.6,0.7))
  ff$V8 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.7,0.8))
  ff$V9 =apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.8,0.9))
  ff$V10=apply(cg_arr_cgname_max_bw[[h]], 1, function(x) decscore((as.numeric(x[4])-as.numeric(x[3])),x[4],0.9,  1))
  rt[[h]]=ff
}
bw_vec=rep(0,11)  
for (h in 1:length(cg_arr_cgname_max_bw))
{
 bw_vec=bw_vec+apply(rt[[h]],2,sum)
}
  
sd(bw_vec[2:11])

[1] 85.95959

plot(bw_vec[2:11])