#!/usr/bin/Rscript
require(methods)
library(lossdistrib)

options(warn=2)
args <- commandArgs(trailingOnly=TRUE)

if(.Platform$OS.type == "unix"){
  root.dir <- "/home/share/CorpCDOs"
}else{
  root.dir <- "//WDSENTINEL/share/CorpCDOs"
}

code.dir <- Sys.getenv("CODE_DIR")
if(code.dir==""){
    code.dir<-root.dir
}
source(file.path(code.dir, "code", "R", "yieldcurve.R"))
source(file.path(code.dir, "code", "R", "optimization.R"))
source(file.path(code.dir, "code", "R", "calibration.R"), chdir=TRUE)
source(file.path(code.dir, "code", "R", "mlpdb.R"))

##figure out the tradedate
if(length(args) >= 1){
  tradedate <- as.Date(args[1])
}else{
  tradedate <- addBusDay(Sys.Date(), -1)
}

exportYC(tradedate)
## calibrate HY21
## calibrate the single names curves
n.int <- 250
list2env(GHquad(n.int), envir=parent.frame())
Ngrid <- 201
index <- load.index("hy21", date=tradedate, "5yr", Z, w, Ngrid)
index <- set.singlenamesdata(index, tradedate)
index <- set.tranchedata(index, tradedate)

## load tranche data
n.credit <- length(index$portfolio)
index$cs$coupons <- index$cs$coupons*0.05
##calibrate by modifying the factor distribution
bottomup <- 1:3
topdown <- 2:4

index$w.mod <- w
p <- index$defaultprob
rho <- rep(0.45, n.credit)
result <- matrix(0, 4, n.int)
err <- Inf
errvec <- c()
while(err >0.01){
    Rstoch <- MFrecovery(index, p)
    L <- array(0, dim=c(index$N, n.int, ncol(index$defaultprob)))
    R <- array(0, dim=c(index$N, n.int, ncol(index$defaultprob)))
    for(t in 1:ncol(index$defaultprob)){
        S <- 1 - Rstoch[,,t]
        L[,,t] <- lossdistCZ(p[,t], index$issuerweights, S, index$N, 0, rho, index$Z)
        R[,,t] <- lossdistCZ(p[,t], index$issuerweights, 1-S, index$N, 0, rho, index$Z)
    }
    for(i in 1:n.int){
        result[,i] <- tranche.pvvec(index$K, L[,i,], R[,i,], index$cs)
    }
    ## solve the optimization problem
    program <- KLfit(-result[bottomup,], w, index$tranche.quotes[bottomup])

    err <- 0
    for(i in 1:n.credit){
        for(j in 1:ncol(p)){
            err <- err + abs(crossprod(shockprob(p[i,j], rho[i], Z), program$weight) - index$defaultprob[i,j])
        }
    }
    errvec <- c(errvec, err)

    ## update the new probabilities
    p <- MFupdate.probC(Z, program$weight, rho, index$defaultprob)

    errvec <- c(errvec, err)
    index$w.mod <- program$weight
    cat(err,"\n")
}

dist <- MFdist(index)

write.table(data.frame(Z=Z, w=index$w.mod),
            file=file.path(root.dir, "Scenarios", "Calibration",
            paste0("calibration-", tradedate, ".csv")),
            col.names=T, row.names=F, sep=",")

save(index, dist, file = file.path(root.dir, "Scenarios", "Calibration",
                     paste0("marketdata-", tradedate, ".RData")), compress="xz")