# [R] How to speed up int2bin conversion?

jim holtman jholtman at gmail.com
Thu Dec 1 14:46:39 CET 2011

```If we assume that you are just convert 8 bits, here is one way with a
table lookup.  If more than 8 bits, just partition the data and
repeat.  This sets up a mapping table one time for the lookup.  Does
1M in 0.3 seconds on my computer; is this fast enough?

> # initialize a matrix with 8 bit binary values
> # one time
> require(bitops)
> b2c <- character(256)
> for (i in 0:255){
+     b2c[i + 1] <- sprintf("%1d%1d%1d%1d%1d%1d%1d%1d"
+         , bitAnd(i, 0x80) != 0
+         , bitAnd(i, 0x40) != 0
+         , bitAnd(i, 0x20) != 0
+         , bitAnd(i, 0x10) != 0
+         , bitAnd(i, 0x8) != 0
+         , bitAnd(i, 0x4) != 0
+         , bitAnd(i, 0x2) != 0
+         , bitAnd(i, 0x1) != 0
+         )
+ }
>
> # create vector with 1M values
> x <- as.integer(1:1e6)
>
> int2bin <- function(val)
+ {
+     b2c[bitAnd(val, 0xff) + 1]
+ }
>
> system.time(int2bin(x))
user  system elapsed
0.31    0.00    0.32

On Thu, Dec 1, 2011 at 7:14 AM, Jonas Jägermeyr <jonasjae at pik-potsdam.de> wrote:
> Dear R-help members,
>
> I'm processing a large amount of MODIS data where quality assessment
> information is stored as an integer value for each pixel. I have to
> converted this number to an 8 digit binary flag to get access to the
> stored quality code (e.g. in2bin(165,8) = 1 0 1 0 0 1 0 1).
>
> Unfortunately, I did not manage to find a package providing a fast
> function to do so. I need to run this on millions of pixels and thus
> wrote the following function.
>
> int2bin <- function(x,ndigits){
>     base <- array(NA, dim=c(length(x), ndigits))
>     for(q in 1:ndigits){
>           base[, ndigits-q+1] <- (x %% 2)
>           x <- (x %/% 2)
>       }
>     bin<- apply(base,1,paste,collapse="")
>     return(bin)
> }
>
> Since it is still slow, I have to find a way to express this more
> elegantly. I'd really appreciate any help.
>
> Thanking you, with best regards
>
> Jonas Jägermeyr
>
> Potsdam Institute for Climate Impact Research
> Research Domain II
>
>        [[alternative HTML version deleted]]
>
>
> ______________________________________________
> R-help at r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> and provide commented, minimal, self-contained, reproducible code.
>

--
Jim Holtman
Data Munger Guru

What is the problem that you are trying to solve?
Tell me what you want to do, not how you want to do it.

```