On 12/01/2011 02:46 PM, jim holtman wrote:
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
0.310.000.32
On Thu, Dec 1, 2011 at 7:14 AM, Jonas Jägermeyr 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
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Great Jim! Thanks a lot. New way of thinking, appreciated.
I also need 16 and 32 bit flags and hence I just added those two lines:
int2bin16<- function(val) {
paste(int2bin(val%/%256),int2bin(val),sep="")
}
int2bin32<- function(val) {
paste(int2bin(val%/%256^3),int2bin(val%/%256^2),int2bin(val%/%256),int2bin(val),sep="")
}
Best,
Jonas Jägermeyr
Potsdam Institute for Climate Impact Research
Research Domain II
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