[R] Improvement in Process time

[PIKAL Petr]

Hi

Basically you can define your data frame before the cycle begins (specify total size, populate rows and columns with NA) and only populate it with your results during a cycle.

Or you can use a list for storing results and use do.call to transform it to data frame.

something like this

lll<- vector("list", 10)
for(i in 1:10) lll[[i]] <- rnorm(12)
do.call(cbind, lll)


I wonder if you get better answer without toy example, because there can be other reasons for slow computation.

Cheers
Petr


> -----Original Message-----
> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Amelia
> Marsh via R-help
> Sent: Tuesday, February 02, 2016 1:03 PM
> To: R Help R
> Subject: [R] Improvement in Process time
>
> Dear R forum,
>
> I am running a Particular process 1000 times for different rates. Each
> time the result of the process is getting stored (appended) in a
> data.frame. However, the process is taking unsual time at times more
> than 2 hours. When I had tried to find out the reason for such a long
> process time, I have realized that writing a data.frame is consuming
> lot of time.
>
> Here is an extract of my code
>
> # ---------------------------------------------------------------
>
> tx_discounted <- read.csv('transaction_discounted.csv', na.strings='')
> tx_discounted$id <- as.character(tx_discounted$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$rate, rule = 2))
> })
>
> # ____________________________________________________
>
> ## Actual time consumtion begins from following part
>
> # ____________________________________________________
>
> result <- rbind(result, ddply(tx_discounted, 'id', function(x) {
>
> if(!is.na(x$curve) && x$curve != '') {
> intrate <- curve[[x$curve]](x$maturity_period)
> } else {
> intrate <- subset(instr_rates,
> instrument==as.character(x$instrument))$value
> }
>
> cross_rate <- subset(exch_rates, key==paste(x$currency,
> x$currency_base, sep='_'))$rate
> mtm_bc     <- cross_rate *
> (x$amount/(1+((intrate/100)*(x$maturity_period/x$intbasis))))
>
> return(data.frame(env=env, id=x$id, instrument=x$instrument,
> currency=x$currency, intrate = intrate, maturity_period =
> x$maturity_period,  intbasis = x$intbasis, cross_rate = cross_rate,
> amount=x$amount, mtm_bc=mtm_bc))
> }))
> }
>
>
> # ---------------------------------------------------------------------
> ------
>
> Unfortuantely I can't share the input files. Is there any way I can
> improve the process time.
>
> Regards and thanking in advance
>
> Amelia
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posting-
> guide.html
> and provide commented, minimal, self-contained, reproducible code.

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