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

source(file.path(root.dir, "code", "R", "etdb.R"))
source(file.path(root.dir, "code", "R", "yieldcurve.R"))
source(file.path(root.dir, "code", "R", "utils.R"))
source(file.path(root.dir, "code", "R", "cds_utils.R"))

workdate <- as.Date("2013-01-24")

MarkitData <- getMarkitIRData(as.Date(workdate))
L1m <- buildMarkitYC(MarkitData, dt = 1/12)
L2m <- buildMarkitYC(MarkitData, dt = 1/6)
L3m <-  buildMarkitYC(MarkitData)
L6m <- buildMarkitYC(MarkitData, dt = 1/2)
L12m <- buildMarkitYC(MarkitData, dt = 1)
setEvaluationDate(as.Date(MarkitData$effectiveasof))

sanitize.column <- function(vec){
  vec <- gsub(",", "", vec)
  index <- grep("\\(", vec)
  for(l in index){
    vec[l] <- -as.numeric(substr(vec[l], 2, nchar(vec[l])-1))
  }
  return( as.numeric(vec) )
}

fields <-  c("Cashflow", "Principal", "Interest")
tranches <- c("COLLAT_REINVEST", "COLLAT_INITIAL")
n.scenarios <- 100
cfdata <- list()
dealnames <- list.files(file.path(root.dir, "Scenarios", paste0("Prices_", workdate)), "*COLLAT_INITIAL-CF-Scen1*")
dealnames <- sapply(strsplit(dealnames, "-"), function(x) x[1])
dealnames <- tolower(unique(dealnames))
flag <- FALSE

for(dealname in dealnames){
  cfdata[[dealname]] <- list()
  r <- matrix(0, n.scenarios, 3)
  colnames(r) <- fields
  sqlstring <- sprintf("select marketvalue from latest_deal_model_numbers where dealname='%s'", dealname)
  mv <- dbGetQuery(dbCon, sqlstring)$marketvalue
  sqlstring <- sprintf("select \"Curr Collat Bal\" from latest_clo_universe where dealname='%s'", dealname)
  currbal <- dbGetQuery(dbCon, sqlstring)$"Curr Collat Bal"
  cfdata[[dealname]]$mv <- mv
  cfdata[[dealname]]$currbal <- currbal
  for(tranche in tranches){
    for(i in 1:n.scenarios){
      filename <- paste0(paste(toupper(dealname), tranche, "CF", paste0("Scen", i), sep="-"), ".txt")
      data <- read.table(file.path(root.dir, "Scenarios", paste0("Prices_", workdate), filename),
                         sep="\t", header=T)
      data <- data[-(1:2),1:4]
      data$Date <- as.Date(data$Date, "%b %d, %Y")
      if(any(is.na(data$Date))){
        sprintf("file: %s is messed up", filename)
        flag <- TRUE
        break
      }
      data <- data[data$Date >= Sys.Date(),]
      DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, data$Date))
      pv <- c()
      for(field in fields){
        data[,field] <- sanitize.column(data[,field])
        pv <- c(pv, crossprod(DC$discounts, data[,field]))
      }
      r[i,] <- pv
    }
    if(flag){
      cfdata[[dealname]] <- NULL
      flag <- FALSE
      break
    }else{
      cfdata[[dealname]][[tranche]]<- r
    }
  }
}


r <- c()
for(dealname in dealnames){
  r <- rbind(r, c(cfdata[[dealname]]$mv, cfdata[[dealname]]$currbal, apply(cfdata[[dealname]]$COLLAT_REINVEST, 2, mean)[1], apply(cfdata[[dealname]]$COLLAT_INITIAL, 2, mean)[1]))
}
colnames(r) <- c("mv", "currbal", "Reinvest", "Initial")
rownames(r) <- dealnames

flag <- FALSE
cusipdata <- list()
for(cusip in cusips){
    r <- rep(0, n.scenarios)
    sqlstring <- sprintf("select curr_balance from cusip_universe where cusip = '%s'", cusip)
    curr_balance <- dbGetQuery(dbCon, sqlstring)$curr_balance
    cusipdata[[cusip]]$currbal <- curr_balance
    for(i in 1:n.scenarios){
        filename <- sprintf("%s-CF-Scen%s.txt", cusip, i)
        data <- read.table(file.path(root.dir, "Scenarios", paste0("Prices_", workdate), filename),
                           sep = "\t", header=T)
        data <- data[-(1:2), 1:4]
        data$Date <- as.Date(data$Date, "%b %d, %Y")
        if(any(is.na(data$Date))){
            sprintf("file: %s is messed up", filename)
            flag <- TRUE
            break
        }
        data <- data[data$Date >= Sys.Date(),]
        DC <- DiscountCurve(L3m$params, L3m$tsQuotes, yearFrac(L3m$params$tradeDate, data$Date))
        data[,"Cashflow"] <- sanitize.column(data[,"Cashflow"])
        pv <- crossprod(DC$discounts, data[, "Cashflow"])
        r[i] <- pv

        if(flag){
            cusipsdata[[cusip]] <- NULL
            flag <- FALSE
            break
        }else{
            cusipdata[[cusip]]$Cashflow <- r
        }
    }
}

prices <- c()
for(cusip in names(cusipdata)){
    prices <- c(prices, mean(cusipdata[[cusip]]$Cashflow)/cusipdata[[cusip]]$currbal)
}
i <- 1
for(cusip in names(cusipdata)){
    cat(cusip, prices[i], "\n")
    i <- i+1
}