if(.Platform$OS.type == "unix"){
  root.dir <- "/home/share/CorpCDOs"
}else{
  root.dir <- "//WDSENTINEL/share/CorpCDOs"
}
options(stringsAsFactors=FALSE)
source(file.path(root.dir, "code", "R", "cds_utils.R"))
source(file.path(root.dir, "code", "R", "cds_functions_generic.R"))
source(file.path(root.dir, "code", "R", "yieldcurve.R"))
source(file.path(root.dir, "code", "R", "optimization.R"))
library(lossdistrib)
load.index("hy21")
load.index("hy19")
n.int <- 250
bps <- 1e-4
attach(GHquad(n.int))

tradedate <- as.Date("2014-05-05")
exportYC(tradedate)
cdsdates <- as.Date(character(0))
for(tenor in paste0(1:5, "y")){
    cdsdates <- c(cdsdates, cdsMaturity(tenor, date=tradedate))
}
cds.cs <- couponSchedule(IMMDate(tradedate), cdsdates[length(cdsdates)], "Q", "FIXED",
                         1, tradedate, IMMDate(tradedate, "prev"))


##build portfolio
buildSC <- function(quote, cs){
    SC <- new("creditcurve",
              recovery=quote$recovery/100,
              startdate=tradedate,
              issuer=as.character(quote$ticker))
    quotes <- data.frame(maturity=cdsdates, upfront = as.numeric(quote[4:8]) * 0.01,
                         running=rep(quote$running*1e-4, 5))
    SC@curve <- cdshazardrate(quotes, SC@recovery, tradedate, cs)
    return( SC )
}

set.singlenamesdata <- function(index, tradedate){
    index.name <- deparse(substitute(index))
    singlenames.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
                                           paste0(index.name, "_singlenames_", tradedate, ".csv")))
    nondefaulted <- singlenames.data[!singlenames.data$ticker %in% index$defaulted,]
    index$portfolio <- c()
    for(i in 1:nrow(nondefaulted)){
        index$portfolio <- c(index$portfolio, buildSC(nondefaulted[i,], cds.cs))
    }
    index$issuerweights <- rep(1/length(index$portfolio), length(index$portfolio))
    index$recov <- sapply(index$portfolio, attr, "recovery")
    assign(index.name, index, envir=parent.env(environment()))
}

## load all the single names data
## calibrate the single names curves
set.singlenamesdata(hy21, tradedate)
set.singlenamesdata(hy19, tradedate)

## load tranche data
set.tranchedata <- function(index, tradedate){
    index.name <- deparse(substitute(index))
    index$tranche.data <- read.csv(file.path(root.dir, "Scenarios", "Calibration",
                                             paste0(index.name, "_tranches_", tradedate, ".csv")), header=TRUE)
    index$indexref <- index$tranche.data$bidRefPrice[1]/100
    index$portfolio.tweaked <- tweakcurves(index$portfolio, index, tradedate)$portfolio
    index$cs <- couponSchedule(IMMDate(tradedate), index$maturity,"Q", "FIXED", 0.05, 0, tradedate,
                               IMMDate(tradedate, "prev"))
    index$defaultprob <- 1-SPmatrix(index$portfolio.tweaked, length(index$cs$dates))
    K <- c(0, 0.15, 0.25, 0.35, 1)
    index$K <- adjust.attachments(K, index$loss, index$factor)
    index$tranche.upf <- index$tranche.data$Mid
    index$tranche.running <- index$tranche.data$Coupon
    ##convert the quotes
    ## - we convert to protection terms x->1-x/100
    ## - we remove accrued x->x-acc
    ## - we weight it by the size of the tranche
    ## - we take the cumsum to convert to 0-5, 0-10, 0-15 quotes, etc...
    ## calibrate the tranches using base correlation
    index$quotes <- cumsum(diff(index$K) *
                           (1-index$tranche.upf/100-cdsAccrued(tradedate, index$tranche.running)))
    assign(index.name, index, envir=parent.env(environment()))
}

set.tranchedata(hy19, tradedate)
set.tranchedata(hy21, tradedate)

## load common parameters
Ngrid <- 201
f <- function(rho, index, N, i){
    temp <- with(index,
                 BClossdistC(defaultprob, issuerweights, recov, rho, Z, w, N))
    return(abs(tranche.pv(temp$L, temp$R, index$cs, 0, index$K[i+1]) + index$quotes[i]))
}

rhovec <- c()
for(i in 1:3){
    rho <- optimize(f, interval=c(0,1), index=hy21, N=Ngrid, i=i)$minimum
    rhovec <- c(rhovec, rho)
}

rhovec <- c(0, rhovec)
K <- c(0, 0.15, 0.25, 0.35, 1)
rhofun <- approxfun(K[-5], rhovec, rule=2)

Kmapped <- rep(0, 3)
for(i in 2:4){
    Kmapped[i-1] <- skewmapping(hy21, rhofun, hy19, K[i], Z, w, 201)$minimum
}