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I have written a (fairly naive) function to randomly select a date/time between two specified days

# set start and end dates to sample between day.start <- "2012/01/01" day.end <- "2012/12/31" # define a random date/time selection function rand.day.time <- function(day.start,day.end,size) { dayseq <- seq.Date(as.Date(day.start),as.Date(day.end),by="day") dayselect <- sample(dayseq,size,replace=TRUE) hourselect <- sample(1:24,size,replace=TRUE) minselect <- sample(0:59,size,replace=TRUE) as.POSIXlt(paste(dayselect, hourselect,":",minselect,sep="") ) }

Which results in:

> rand.day.time(day.start,day.end,size=3) [1] "2012-02-07 21:42:00" "2012-09-02 07:27:00" "2012-06-15 01:13:00"

But this seems to be slowing down considerably as the sample size ramps up.

# some benchmarking > system.time(rand.day.time(day.start,day.end,size=100000)) user system elapsed 4.68 0.03 4.70 > system.time(rand.day.time(day.start,day.end,size=200000)) user system elapsed 9.42 0.06 9.49

Is anyone able to suggest how to do something like this in a more efficient manner?

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2 Answers 2

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48

Ahh, another date/time problem we can reduce to working in floats :)

Try this function

R> latemail <- function(N, st="2012/01/01", et="2012/12/31") { + st <- as.POSIXct(as.Date(st)) + et <- as.POSIXct(as.Date(et)) + dt <- as.numeric(difftime(et,st,unit="sec")) + ev <- sort(runif(N, 0, dt)) + rt <- st + ev + } R>

We compute the difftime in seconds, and then "merely" draw uniforms over it, sorting the result. Add that to the start and you're done:

R> set.seed(42); print(latemail(5)) ## round to date, or hour, or ... [1] "2012-04-14 05:34:56.369022 CDT" "2012-08-22 00:41:26.683809 CDT" [3] "2012-10-29 21:43:16.335659 CDT" "2012-11-29 15:42:03.387701 CST" [5] "2012-12-07 18:46:50.233761 CST" R> system.time(latemail(100000)) user system elapsed 0.024 0.000 0.021 R> system.time(latemail(200000)) user system elapsed 0.044 0.000 0.045 R> system.time(latemail(10000000)) ## a few more than in your example :) user system elapsed 3.240 0.172 3.428 R>
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6 Comments

First rule of working with dates and times: always remember that POSIXct is really just a numeric with fractional seconds since theepoch. Dito for Date and fractional days. A lot of problems become a lot easier that way.
The genius of this answer is the st + ev trick -- it's the roundtrip to a POSIXct that is painful, since you need to explicitly specify the origin. Otherwise runif(N, as.POSIXct(st), as.POSIXct(et)) gets you 90% of this; but then you need to as.POSIXct(..., origin="1970-01-01")
Why the sort command when generating a sequence of random values?
I find it preferable to have dates ordered. You can obviously make that optional via a function parameter.
How to keep all the timezones the same?
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2

Something like this will work too. Sorry for the random data frame, I just threw that in there so you could see a plot.

data=as.data.frame(list(ID=1:10, variable=rnorm(10,50,10))) #This function will generate a uniform sample of dates from #within a designated start and end date: rand.date=function(start.day,end.day,data){ size=dim(data)[1] days=seq.Date(as.Date(start.day),as.Date(end.day),by="day") pick.day=runif(size,1,length(days)) date=days[pick.day] } #This will create a new column within your data frame called date: data$date=rand.date("2014-01-01","2014-02-28",data) #and this will order your data frame by date: data=data[order(data$date),] #Finally, you can see how the data looks plot(data$date,data$variable,type="b")
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