[R-SIG-Finance] Discretising intra-day data -- how to get by with less memory?

[Brian G. Peterson]

Ajay Shah wrote:
> I'm using this function to convert intra-day data into a grid with an
> observation each N seconds:
>
>   # This function consumes "z" a zoo object where timestamps are intraday
>   # and a period for discretisation Nseconds.
>   # The key ideas are from this thread:
>   #    https://stat.ethz.ch/pipermail/r-sig-finance/2009q4/005144.html
>   intraday.discretise <- function(z, Nseconds) {
>     toNsec <- function(x) as.POSIXct(Nseconds*ceiling(as.numeric(x)/Nseconds),
>                                    origin = "1970-01-01")
>     d <- aggregate(z, toNsec, tail, 1)
>     # At this point there is one problem: NA records are not created
>     # for blocks of time in which there were no records.
>
>     # To solve this:
>     dreg <- as.zoo(as.ts(d))
>     class(time(dreg)) <- class(time(d))
>
>     dreg
>   }
>
> This works correctly but it's incredibly memory-intensive. I'm running
> out of core in running this for some problems.
>
> Is there a way to write this which would use less RAM?
>
>   
Jeff Ryan, Abe Winter, and I came up with an align.time function a few 
months back:

align.time <- function(x, n=30) {
  structure(unclass(x) + (n - unclass(x) %% n), class=c("POSIXt","POSIXct")) }

x is xts data
n is seconds

Regards,

  - Brian

-- 
Brian G. Peterson
http://braverock.com/brian/
Ph: 773-459-4973
IM: bgpbraverock