library(doParallel, quiet = T, warn.conflicts = F)
library(yaml)

hostname <- system("hostname", intern=TRUE)
if(hostname=="debian"){
    registerDoParallel(8)
}else{
    registerDoParallel(4)
}

args <- commandArgs(trailingOnly=TRUE)

stopifnot((root.dir <- Sys.getenv("SERENITAS_BASE_DIR")) != "")
stopifnot((config.dir <- Sys.getenv("SERENITAS_CONFIG_DIR")) !=  "")
source("intex_deal_functions.R")
source("yieldcurve.R")
source("serenitasdb.R")
source("tranche_functions.R")

if(interactive()) {
    tradedate <- as.Date("2020-04-06")
    dealnames <- c("acasl152")
    reinvflags <- c(TRUE)
}else{
    tradedate <- as.Date(args[1])
    if(length(args) >=2){
        argslist <- strsplit(args[-1], ",")
        dealnames <- unlist(lapply(argslist, function(x)x[1]))
        reinvflags <- as.logical(unlist(lapply(argslist, function(x)x[2])))
    }
}

calibration.date <- addBusDay(tradedate, -1)
settledate <- addBusDay(tradedate, 3)
calibration <- read.table(file.path(root.dir, "Scenarios", "Calibration",
                                    paste0("calibration-", calibration.date,".csv")), sep=",", header=T)
Z <- calibration$Z
w <- calibration$w
exportYC(calibration.date)

Ngrid <- 201
support <- seq(0, 1, length = Ngrid)
n.scenarios <- 100
recov.adj <- 1
params <- yaml.load_file(file.path(config.dir, "params.yml"),
                         handlers = list(expr = function(x) eval(parse(text = x))))

for(j in seq_along(dealnames)){
  load(file.path(root.dir, "Scenarios", paste("Portfolios", tradedate, sep="_"),
                 paste(dealnames[j], "RData", sep=".")))
  if(is.na(deal.data$reinv_end_date)){
    reinvflags[j] <- FALSE
  }
  dp <- A$DP
  pp <- A$PP
  dpmod <- MFupdate.prob(Z, w, deal.portfolio$beta, dp)
  ppmod <- MFupdate.prob(-Z, w, deal.portfolio$beta, pp)
  dist.joint <- MFlossdist.prepay.joint(w, Z, deal.portfolio$beta, dp, dpmod, pp, ppmod,
                                        deal.weights, 1-S, Ngrid)
  dist.joint <- pmax(dist.joint, 0)
  distDR <- dist.transform(dist.joint)
  ## compute E(R|D)
  R <- matrix(0, Ngrid, dim(distDR)[1])
  for(t in 1:dim(distDR)[1]){
    R[,t] <- sweep(distDR[t,,], 1, rowSums(distDR[t,,]), "/") %*% support
    R[1,t] <- 0
    if(t >= 2){
      R[,t] <- pmax(R[,t], R[,t-1])
    }
  }

  ## compute scenariosd
  scenariosd <- matrix(0, n.scenarios, dim(distDR)[1])
  scenariosr <- matrix(0, n.scenarios, dim(distDR)[1])
  percentiles <- seq(0, 1, 1/n.scenarios)
  for(t in 1:dim(distDR)[1]){
    D <- rowSums(distDR[t,,])
    Dfun <- splinefun(c(0, cumsum(D)), c(0, support), "hyman")
    Rfun <- approxfun(support, R[,t], rule=2)
    for(i in 1:n.scenarios){
      ## this is roughly E(D|D is in ith percentile)
      ## using trapezoidal approximation
      if(i==1){
        scenariosd[i,t] <- 0.5* Dfun(0.01)
      }else{
        scenariosd[i,t] <- 0.5 * (Dfun((i-1)*0.01)+Dfun(i*0.01))
      }
      if(t>=2 && scenariosd[i,t] < scenariosd[i,t-1]){
        scenariosd[i,t] <- scenariosd[i,t-1]
      }
      scenariosr[i,t] <- Rfun(scenariosd[i,t])
      if(t>=2 && scenariosr[i,t] < scenariosr[i,t-1]){
        scenariosr[i,t] <- scenariosr[i,t-1]
      }
    }
  }

  ## we need to adjust the recovery because intex has some embedded amortization assumptions
  ## that we can't turn off (multiply by recov.adj)
  intexrecov <- matrix(0, n.scenarios, dim(distDR)[1])
  for(i in 1:dim(distDR)[1]){
    if(i==1){
      intexrecov[,i] <- recov.adj * (scenariosr[,i]/scenariosd[,1])
    }else{
      intexrecov[,i] <- recov.adj * (scenariosr[,i] - scenariosr[,i-1])/(scenariosd[,i] - scenariosd[,i-1])
    }
  }
  deal.dates <- getdealschedule(deal.data, "Quarterly")
  deal.dates <- deal.dates[deal.dates>=settledate]
  cdr <- cdrfromscenarios(scenariosd, deal.dates, tradedate)
  ## linear approximation for monthly scenarios
  deal.data <- getdealdata(dealnames[j], tradedate)
  deal.datesmonthly <- getdealschedule(deal.data, "Monthly")
  deal.datesmonthly <- deal.datesmonthly[deal.datesmonthly>=settledate]

  cdrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
  recoverymonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
  scenariosrmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
  scenariosdmonthly <- matrix(0, n.scenarios, length(deal.datesmonthly))
  for(i in 1:n.scenarios){
    cdrmonthly[i,] <- approx(deal.dates, cdr[i,], deal.datesmonthly, rule=2)$y
    recoverymonthly[i,] <- approx(deal.dates, intexrecov[i,], deal.datesmonthly, rule=2)$y
    scenariosrmonthly[i,] <- approx(deal.dates, scenariosr[i,], deal.datesmonthly, rule=2)$y
    scenariosdmonthly[i,] <- approx(deal.dates, scenariosd[i,], deal.datesmonthly, rule=2)$y
  }
  recoverymonthly[90:100,][which(recoverymonthly[90:100,]>1)]  <- 0
  recoverymonthly <- pmin(recoverymonthly, 1)
  recoverymonthly[!is.finite(recoverymonthly)] <- 100

  if(!is.na(deal.data$reinv_end_date) && deal.data$reinv_end_date <= tradedate){
      ## we cap rolling maturity at the current weighted average maturity of the portfolio
      rollingmaturity <- (crossprod(sapply(deal.portfolio$SC, creditcurve.maturity),
                                    deal.portfolio$notional)/sum(deal.portfolio$notional)
                          - as.numeric(tradedate))
  }else{
      rollingmaturity <- params$rollingmaturity
  }

  ## compute reinvestment price
  cdrmonthly.dt <- data.table(date=deal.datesmonthly, t(cdrmonthly), key="date")
  recoverymonthly.dt <- data.table(date=deal.datesmonthly, t(recoverymonthly), key="date")
  if(reinvflags[j]){
      reinvprices <- compute.reinvprices(dealnames[j], cdrmonthly.dt, recoverymonthly.dt,
                                         params, rollingmaturity, tradedate)
  }else{
      reinvprices <- list()
  }

  save.dir <- file.path(root.dir, "Scenarios", paste("Intex curves", tradedate, sep="_"), "csv")
  if(!file.exists(save.dir)){
    dir.create(save.dir, recursive = T)
  }

  write.table(cdrmonthly,
              file= file.path(save.dir, paste0(dealnames[j],"-cdr.csv")),
              row.names=F, col.names=F, sep=",")
  write.table(100 * recoverymonthly,
              file=file.path(save.dir, paste0(dealnames[j],"-recovery.csv")),
              row.names=F, col.names=F, sep=",", na="NaN")
  write.table(reinvprices, file = file.path(save.dir, paste0(dealnames[j], "-reinvprices.csv")),
              row.names=F, col.names=T, sep=",")

  configfile <- file.path(save.dir, paste0(dealnames[j], ".config"))
  config <- list(rollingmat = as.integer(rollingmaturity/365*12),
                 reinvflag = reinvflags[j])
  cat(as.yaml(config), file = configfile)
  save(scenariosd, scenariosr, dist.joint, file=file.path(save.dir, paste0(dealnames[j], ".RData")),
       compress="xz", version=2)

  cat("generated scenarios for:", dealnames[j], "\n")
}