R - faster alternative to hist(XX, plot=FALSE)$count

Question

I am on the lookout for a faster alternative to R's hist(x, breaks=XXX, plot=FALSE)$count function as I don't need any of the other output that is produced (as I want to use it in an sapply call, requiring 1 million iterations in which this function would be called), e.g.

x = runif(100000000, 2.5, 2.6)
bincounts = hist(x, breaks=seq(0,3,length.out=100), plot=FALSE)$count

Any thoughts?

Answer 1

A first attempt using table and cut:

table(cut(x, breaks=seq(0,3,length.out=100)))

It avoids the extra output, but takes about 34 seconds on my computer:

system.time(table(cut(x, breaks=seq(0,3,length.out=100))))
   user  system elapsed 
 34.148   0.532  34.696 

compared to 3.5 seconds for hist:

system.time(hist(x, breaks=seq(0,3,length.out=100), plot=FALSE)$count)
   user  system elapsed 
  3.448   0.156   3.605

---

Using tabulate and .bincode runs a little bit faster than hist:

tabulate(.bincode(x, breaks=seq(0,3,length.out=100)), nbins=100)

system.time(tabulate(.bincode(x, breaks=seq(0,3,length.out=100))), nbins=100)
   user  system elapsed 
  3.084   0.024   3.107

---

Using tablulate and findInterval provides a significant performance boost relative to table and cut and has an OK improvement relative to hist:

tabulate(findInterval(x, vec=seq(0,3,length.out=100)), nbins=100)

system.time(tabulate(findInterval(x, vec=seq(0,3,length.out=100))), nbins=100)
   user  system elapsed 
  2.044   0.012   2.055