library(RQuantLib)
library(yaml)
library(hash)
library(readr)
library(dplyr)
library(data.table)
library(logging)
basicConfig()
args <- commandArgs(trailingOnly=TRUE)

stopifnot((root.dir <- Sys.getenv("SERENITAS_BASE_DIR")) != "")
tradedate <- if(length(args) >= 1) as.Date(args[1]) else Sys.Date()

source("yieldcurve.R")
source("cds_utils.R")
source("intex_deal_functions.R")
source("optimization.R")
source("interpweights.R")
source("serenitasdb.R")
source("creditIndex.R")
source("tranche_functions.R")
index <- creditIndex("hy37")
index <- set.index.desc(index, tradedate)

calibration.date <- addBusDay(tradedate, -1)
exportYC(calibration.date)
cs <- couponSchedule(IMMDate(calibration.date, noadj=TRUE), index$maturity,
                     "Q", "FLOAT", 0, 0.05, calibration.date)

dm <- 0
sanitize.column <- function(vec){
  vec <- gsub(",", "", vec)
  index <- grep("\\(", vec)
  vec[index] <- unlist(lapply(index, function(l)-as.numeric(substr(vec[l], 2, nchar(vec[l])-1))))
  return(as.numeric(vec))
}

processzipfiles <- function(tradedate=Sys.Date()){
    pricesdir <- file.path(root.dir, "Scenarios", paste0("Prices_", tradedate))
    zipfiles <- file.path(pricesdir, list.files(pricesdir, "*.zip"))
    zipfiles <- zipfiles[order(file.info(zipfiles)$ctime)]
    for(n in seq_along(zipfiles)){
        zip <- zipfiles[n]
        allfiles <- unzip(zip, list=TRUE)$Name
        dealnames <- grep("COLLAT.*Scen100", allfiles, value=TRUE)
        dealnames <- unique(unlist(lapply(strsplit(dealnames, "-"), function(x)x[1])))
        allfiles <- unique(unlist(lapply(strsplit(allfiles, "-"), function(x)x[1])))
        allfiles <- allfiles[!(allfiles=="Total")]
        figis <- setdiff(allfiles, dealnames)
        dealnames <- tolower(dealnames)
        if(n==1){
            dealnames.hash <- hash(dealnames, 1)
            figis.hash <- hash(figis, 1)
        }else{
            for( f in figis){
                figis.hash[f] <- n
            }
            for(d in dealnames){
                dealnames.hash[d] <- n
            }
        }
    }
    return(list(dealnames=dealnames.hash, figis=figis.hash, zipfiles=zipfiles))
}

getconfig <- function(dealname, tradedate){
    configfile <- file.path(root.dir, "Scenarios", paste("Intex curves", tradedate, sep="_"),
                            "csv", paste0(dealname, ".config"))
    if(file.exists(configfile)){
        return(yaml.load_file(configfile))
    }else{
        return(list(reinvflag=TRUE))
    }
}

getdealcf <- function(dealnames, zipfiles, tradedate=Sys.Date()){
    cfdata <- list()
    fields <-  c("Cashflow", "Principal", "Interest")
    n.scenarios <- 100
    indextodealnames <- invert(dealnames)
    for(k in keys(indextodealnames)) {
        zip <- zipfiles[as.numeric(k)]
        tmp <- tempfile(tmpdir="/tmp")
        file.copy(zip, tmp)
        zip <- tmp
        for(dealname in indextodealnames[[k]]) {
            loginfo(paste("processing", dealname))
            dealdata <- getdealdata(dealname, tradedate)
            alldates <- getdealschedule(dealdata, "Monthly")
            config <- getconfig(dealname, tradedate)
            alldates_floored <- ifelse(alldates >= YC$referenceDate, alldates, YC$referenceDate)
            class(alldates_floored) <- "Date"
            df <- data.table(Date = alldates,
                             Discounts = YC$discount(alldates_floored),
                             key="Date")
            cfdata[[dealname]] <- list(mv = dealdata$mv,
                                       currbal = dealdata$"Curr Collat Bal",
                                       principalbal = dealdata$"Principal Bal")

            if(is.na(dealdata$reinv_end_date)||!config$reinvflag){
                tranches <- "COLLAT"
            }else{
                tranches <- c("COLLAT_INITIAL", "COLLAT_REINVEST")
                if(dealname=="octag11"){
                    tranches <- c("COLLAT_USD_INITIAL", "COLLAT_USD_REINVEST")
                }
            }
            flag <- TRUE
            ct <- list(col_date("%b %d, %Y"),
                       col_character(),
                       col_character(),
                       col_number(), col_skip(), col_skip(),
                       col_skip(), col_skip(), col_skip(),
                       col_skip(), col_skip(), col_skip())
            for(tranche in tranches){
                r <- matrix(0, n.scenarios, 3)
                colnames(r) <- fields
                for(i in 1:n.scenarios) {
                    filename <- paste0(paste(toupper(dealname), tranche, "CF",
                                             paste0("Scen", i), sep="-"), ".txt")
                    conn <- unz(zip, filename)
                    data <- tryCatch(suppressWarnings(read_tsv(conn, col_types= ct, name_repair="minimal")),
                                     error=function(e){
                                         logerror(conditionMessage(e))
                                         NULL})
                    ## browser()
                    ## if (!grepl("Missing column names filled in", warnings())) {
                    ##     data <- NULL
                    ## }
                    if(is.null(data)||nrow(data)<1){
                        loginfo(paste(dealname, i, tranche))
                        break
                        flag <- FALSE
                    }
                    data <- data[-1,]
                    data <- data.table(data, key="Date")
                    data <- tryCatch({
                        data[,`:=`(Cashflow = sanitize.column(Cashflow),
                                   Principal = sanitize.column(Principal))]
                    }, warning=function(w){
                        logwarn(conditionMessage(w))
                        NULL})

                    data <- df[data, roll=TRUE]
                    data$Discounts[is.na(data$Discounts)] <- 1
                    #data$T[is.na(data$T)] <- 0
                    r[i,] <- as.numeric(data[,list(sum(Cashflow*Discounts),
                                                   sum(Principal*Discounts),
                                                   sum(Interest*Discounts))])
                }
                if(flag) {
                    cfdata[[dealname]][[tranche]] <- r
                }
            }
            if(length(cfdata[[dealname]])<2+length(tranches)){##meaning we existed early in the above loop
                cfdata[[dealname]] <- NULL
                next
            }
            cf <- rep(0,n.scenarios)
            for(tranche in tranches){
                cf <- cf+cfdata[[dealname]][[tranche]][,"Cashflow"]
            }
            cf <- cf-min(dealdata$"Principal Bal", 0)
            cfdata[[dealname]]$price <- cf / dealdata$mv
            cfdata[[dealname]]$wapbasis <- (mean(cf) - dealdata$mv) / dealdata$mv
            cfdata[[dealname]] <- tryCatch({cfdata[[dealname]]$weight <-
                                                KLfit(t(cf)/1e8, rep(1/n.scenarios, n.scenarios),
                                                      dealdata$mv/1e8)$weight;
                                            loginfo(paste("done", dealname));
                                            cfdata[[dealname]]},
                                            error = function(e) {
                                                logerror(paste("error computing the weights for deal:", dealname))
                                                NULL
                                            })
        }
        unlink(tmp)
    }
    return( cfdata )
}

gettranche_indicdata <- function(figi, dealname, date) {
    tranche_universe <- tbl(etdb, "tranche_universe")
    r <- tranche_universe %>%
        filter(figi == !!figi) %>%
        collect()
    sqlstr <- "SELECT * FROM historical_dealname_universe($1, $2)"
    r <- tryCatch(dbGetQuery(etdb, sqlstr, params = list(dealname, date)),
                  error = function(w) logerror(w$message))
    return(r %>%
           arrange(desc(curr_attach)) %>%
           mutate(cum_bal = cumsum(curr_balance)) %>%
           filter(figi == !!figi) %>%
           select(figi, curr_balance, orig_balance, spread, curr_attach, cum_bal))
}

gettranchecf <- function(params, cfdata, dist, tradedate=Sys.Date()){
    tranchedata <- list()
    figis <- keys(params$figis)
    dealnames <- dealnamefromfigi(figis)
    figis <- figis[dealnames %in% names(cfdata)]
    dealnames <- dealnames[dealnames %in% names(cfdata)]
    n.scenarios <- 100
    intexfields <-  c("Cashflow", "Principal", "Interest", "Balance",
                      "Accum Interest Shortfall")
    fields <-  c("Cashflow", "Principal", "Interest", "wal", "duration")
    for(i in 1:length(figis)){
        figi <- figis[i]
        loginfo(paste("processing", figi))
        zip <- params$zipfiles[params$figis[[figi]]]
        dealname <- dealnames[i]
        dealdata <- getdealdata(dealname, tradedate)
        alldates <- getdealschedule(dealdata, "Monthly", bdc = "Following")
        alldates_floored <- ifelse(alldates >= YC$referenceDate, alldates, YC$referenceDate)
        class(alldates_floored) <- "Date"
        T <- yearFrac(YC$referenceDate, alldates)
        df <- data.table(Date=alldates_floored,
                         Discounts=YC$discount(alldates_floored),
                         T=T, key="Date")
        r <- matrix(0, n.scenarios, 5)
        colnames(r) <- fields
        indicdata <- gettranche_indicdata(figi, dealname, tradedate)
        flag <- TRUE
        ct <- list(col_date("%b %d, %Y"),
                   col_number(),
                   col_number(),
                   col_number(), col_number(), col_number(),
                   col_skip(), col_skip())
        for(j in 1:n.scenarios){
            filename <- sprintf("%s-CF-Scen%s.txt", figi, j)
            conn <- unz(zip, filename)
            data <- tryCatch(suppressWarnings(read_tsv(conn, col_types=ct, name_repair="minimal")),
                             error=function(e){
                                 logerror(conditionMessage(e))
                                 NULL})
            if(is.null(data)||nrow(data)<=2){
                loginfo(paste(figi, "Scenario", j))
                flag <- FALSE
                break
            }
            data <- data[-1,]
            data <- data.table(data, key="Date")
            data[,Balance:=pmax(Balance-`Accum Interest Shortfall`, 0)]
            r[j,] <- as.numeric(df[data, roll=TRUE][,list(Cashflow=temp <- sum(Cashflow*Discounts),
                                             Principal=sum(Principal*Discounts),
                                             Interest=sum(Interest*Discounts),
                                             wal=sum(-diff(Balance)*T[-1])/indicdata$curr_balance,
                                             duration=if(temp==0) 0 else sum(Cashflow * Discounts * T)/temp)])
        }
        tranche.pv <- if(indicdata$curr_balance == 0) {
                          r[,"Cashflow"] / indicdata$orig_balance
                      } else {
                          r[,"Cashflow"] / indicdata$curr_balance
                      }
        if(flag) {
            tranchedata[[figi]] <- list(currbal=indicdata$curr_balance,
                                        spread=indicdata$spread,
                                        Cashflow=crossprod(cfdata[[dealname]]$weight, r[,"Cashflow"]),
                                        wal = crossprod(cfdata[[dealname]]$weight, r[,"wal"]),
                                        duration = crossprod(cfdata[[dealname]]$weight, r[,"duration"]),
                                        price = 100 * crossprod(tranche.pv, cfdata[[dealname]]$weight),
                                        delta = compute.delta(dist, cfdata[[dealname]], tranche.pv),
                                        mvoc = (cfdata[[dealname]]$mv+cfdata[[dealname]]$principalbal)/
                                            indicdata$cum_bal-1,
                                        mvcoverage = 1+(cfdata[[dealname]]$mv+cfdata[[dealname]]$principalbal-indicdata$cum_bal)/indicdata$curr_balance,
                                        fields=r)
            loginfo(paste("done", figi))
        }
    }

    return(tranchedata)
}

compute.delta <- function(indexdist, dealdata, tranche.pv, K1=0, K2=1){
    dealweight <- dealdata$weight
    dealprice <- dealdata$price
    nT <- dim(indexdist$L)[2]
    Ngrid <- dim(indexdist$L)[1]
    scenariosl <- matrix(0, length(dealweight), nT)
    scenariosr <- matrix(0, length(dealweight), nT)
    for(t in 1:nT){
        scenariosl[,t] <- interpvalues(indexdist$L[,t], seq(0, 1, length=Ngrid), dealweight)
        ## numerical artefact, but we want scenariosr[i,] + scenariosl[i,] <= 1 at all times
        scenariosr[,t] <- pmin(interpvalues(indexdist$R[,t], seq(0, 1, length=Ngrid), dealweight),
                               1-scenariosl[,t])
    }
    ## we assume the index is fully funded - need to be changed depending
    ## on how we fund the swaps (hence floating coupon instead of fixed)
    indexpv <- c()
    for(i in 1:length(dealweight)){
        indexpv <- c(indexpv, funded.tranche.pv(scenariosl[i,], scenariosr[i,], cs, K1, K2, TRUE))
    }
    ## model1 <- lm(cusip.pv~dealprice, weights=dealweight)
    ## model2 <- lm(dealprice~indexpv, weights=dealweight)
    ## return(model1$coef[2]/model2$coef[2])
    model <- lm(tranche.pv~indexpv, weights=dealweight)
    return( model$coef[2] )
}

if(length(args)>=2){
    figis <- args[-1]
    dealnames <- unique(dealnamefromfigi(figis))
}else{
    params <- processzipfiles(tradedate)
}

if(interactive()) {
    options(error=recover)
}

cfdata <- getdealcf(params$dealnames, params$zipfiles, tradedate)

## load dist into the environment
load(file.path(root.dir, "Scenarios", "Calibration", sprintf("marketdata-%s.RData", calibration.date)))
tranchedata <- gettranchecf(params, cfdata, dist, tradedate)
save.dir <- file.path(root.dir, "Scenarios", paste0("Prices_", tradedate))
save(tranchedata, cfdata, file=file.path(save.dir, "cashflows.RData"),
     compress="xz")

## upload wapbasis
sqlstring <- paste0("UPDATE et_deal_model_numbers SET ",
                    "wapbasis = $1 WHERE dealname= $2 AND updatedate = $3")
for(dealname in names(cfdata)){
    r <- tryCatch(dbSendQuery(etdb, sqlstring, params = list(cfdata[[dealname]]$wapbasis*100,
                                                             dealname,
                                                             tradedate)),
                  error = function(w) {
                      logerror(w$message)
                  })
    dbClearResult(r)
}

## upload model data
dawndb <- dbConn("dawndb")
for(figi in names(tranchedata)){
    sqlstring <- paste0("SELECT updatedate from et_tranche_model_numbers",
                        " WHERE figi=$1")
    sqldata <- tryCatch(dbGetQuery(etdb, sqlstring, params=list(figi)),
                        error = function(w) logerror(w$message))
    columns <- c("price", "wal", "duration", "delta", "mvoc", "mvcoverage")
    values <- tranchedata[[figi]][match(columns, names(tranchedata[[figi]]))]
    if(nrow(sqldata) && (tradedate %in% as.Date(sqldata$updatedate))) {
        params <- c(values, figi, as.character(tradedate))
        sqlstring <- paste0("UPDATE et_tranche_model_numbers SET price=$1, wal=$2, duration=$3,",
                            "delta=$4, mvoc=$5, mvcoverage=$6 WHERE figi=$7 and updatedate=$8")

    }else{
        params <- c(list(figi=figi, updatedate=as.character(tradedate)), values)
        sqlstring <- sprintf("INSERT INTO et_tranche_model_numbers(%s) VALUES(%s)",
                             paste(names(params), collapse=","),
                             paste(paste0("$", 1:length(params)), collapse=","))
    }
    names(params) <-  NULL
    r <- tryCatch(dbSendQuery(etdb, sqlstring, params=params),
                  error = function(e) logerror(e$message))
    dbClearResult(r)
    identifier <- tryCatch(dbGetQuery(dawndb, "SELECT identifier from securities WHERE figi=$1",
                                      params=list(figi)),
                           error = function(e) logerror(e$message))
    identifier <- if(nrow(identifier)>0) identifier$identifier else NULL
    if(!is.null(identifier)) {
        if(nrow(sqldata) && (tradedate %in% as.Date(sqldata$updatedate))) {
            params <- c(values[1:4], identifier, as.character(tradedate))
            sqlstring <- paste0("UPDATE risk_numbers SET model_price=$1, wal=$2, duration=$3,",
                                "index_delta='HY',delta=$4 WHERE identifier=$5 and date=$6")
        } else {
            sqlstring <- paste0("INSERT INTO risk_numbers(identifier, date, index_delta,",
                                "model_price, wal, duration, delta) ",
                                "VALUES($1, $2, $3, $4, $5, $6, $7)")
            params <- c(identifier, as.character(tradedate), 'HY', values[1:4])
        }
        names(params) <- NULL
        r <- tryCatch(dbSendQuery(dawndb, sqlstring, params=params),
                      error = function(w) logerror(w$message))
        dbClearResult(r)
    }
}
dbDisconnect(dawndb)