Memory problem

Dear Sir,

Yes I am using the plyr and in the end I am writing the output to the data.frame. Earlier I had the problem of process time and hence I made some changes in the code and now I am fetching all the required inputs needed for valuation purpose using ddply, store the results in a data.frame and once that is over, I am carrying out the calculations.

Here is part of my R code-

library(plyr)
library(reshape)

tx <- read.csv('transaction_fxdeal.csv')
tx$id  <-  as.character(tx$id)

n        <- max(unique(simulated_exchange$id))

result <- NULL
current  <- 1
rcount   <- 0
current1 <- 1
rcount1  <- 0
current2 <- 1
rcount2  <- 0
for (env in 0:n) {

  if (rcount == 0) rcount <- nrow(subset(simulated_interest, id==env))
  temp <- current+rcount-1
  env_rates  <- simulated_interest[current:temp,]
  env_rates  <- env_rates[order(env_rates$curve, env_rates$day_count), ]
  if (rcount1 == 0)rcount1 <- nrow(subset(simulated_exchange, id==env))
  temp <- current1+rcount1-1
  exch_rates <- simulated_exchange[current1:temp,]
  if (rcount2 == 0)rcount2 <- nrow(subset(simulated_instruments, id==env))
  temp <- current2+rcount2-1
  instr_rates<- simulated_instruments[current2:temp,]
  current <- current+rcount
  current1 <- current1+rcount1
  current2 <- current2+rcount2

  curve       <- daply(env_rates, 'curve', function(x) {
    return(approxfun(x$day_count, x$rate, rule = 2))
  })

result <- rbind(result, ddply(tx, 'id', function(x) {

intrate_from <- curve[[x$currency_from]](x$maturity_from)
intrate_to   <- curve[[x$currency_to]](x$maturity_to)
cross_rate   <- subset(exch_rates, key==paste(x$currency_from_exch, x$currency_to_exch, sep='_'))$rate
base_rate    <- subset(exch_rates, key==paste(x$currency_to_exch, x$currency_base, sep='_'))$rate

return(data.frame(env=env, intrate_from=intrate_from, intrate_to=intrate_to, cross_rate=cross_rate, base_rate=base_rate))

  }))
}

sorted <- result[order(result$id, result$env),]

sorted$currency_from_exch <- rep(tx$currency_from_exch, each = length(unique(sorted$env)))
sorted$currency_to_exch <- rep(tx$currency_to_exch, each = length(unique(sorted$env)))
sorted$currency_base <- rep(tx$currency_base, each = length(unique(sorted$env)))
sorted$transaction_type <- rep(tx$transaction_type, each = length(unique(sorted$env)))
sorted$amount_fromccy <- rep(tx$amount_fromccy, each = length(unique(sorted$env)))
sorted$amount_toccy <- rep(tx$amount_toccy, each = length(unique(sorted$env)))
sorted$intbasis_fromccy <- rep(tx$intbasis_fromccy, each = length(unique(sorted$env)))
sorted$intbasis_toccy <- rep(tx$intbasis_toccy, each = length(unique(sorted$env)))
sorted$maturity_from <- rep(tx$maturity_from, each = length(unique(sorted$env)))
sorted$maturity_to <- rep(tx$maturity_to, each = length(unique(sorted$env)))
sorted$currency_from <- rep(tx$currency_from, each = length(unique(sorted$env))) 
sorted$currency_to <- rep(tx$currency_to, each = length(unique(sorted$env))) 

sorted$from_mtm <- sorted$cross_rate * (sorted$amount_fromccy / ((1 + (sorted$intrate_from/100))^(sorted$maturity_from / sorted$intbasis_fromccy)))

sorted$to_mtm       <- (sorted$amount_toccy   / ((1 + (sorted$intrate_to/100))^(sorted$maturity_to / sorted$intbasis_toccy)))

mtm_base <- function(from_mtm, to_mtm, base_rate)
{
mtm <- (from_mtm + to_mtm)
mtm_bc = mtm*base_rate[1]

return(data.frame(mtm_bc = mtm_bc))
}

sorted1 <- ddply(.data=sorted, .variables = "id", .fun=function(x) mtm_base(from_mtm = x$from_mtm, to_mtm = x$to_mtm, base_rate = x$base_rate))

sorted$mtm <- sorted1$mtm
sorted$mtm_bc <- sorted1$mtm_bc

sorted2 <- ddply(sorted, .(currency_from_exch, id), mutate, change_in_mtm_bc = mtm_bc - mtm_bc[1])

sorted$change_in_mtm_bc <- sorted2$change_in_mtm_bc

sorted <- sorted[order(sorted$id, sorted$env),]

write.csv(data.frame(sorted), file='MC_result_fxdeal.csv', row.names=FALSE)

# ________________________________________________________

# END of Code

With regards

Amelia

Memory problem

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