Odp: For loops in R
Hi r-help-bounces at r-project.org napsal dne 19.01.2010 02:32:45:
Hello Petr. For the random values, I wanted to generate a different random number
for
each element of my velocity matrix. So will this do it? rmat <- matrix(runif(1000), 500,2) rmat2 <- matrix(runif(1000), 500,2) rindex <- sample(1:500, replace=TRUE) #with repetition velocity<-0.4 * velocity + rmat * (pbestsVar - popVar) + rmat2 * (archiveVar[rindex,] - popVar)
AFAICS it seems to do what you want. Basically your rmat and rmat2 will have different numbers from uniform distribution. If you wanted different distribution of random numbers you need to use differend random number generator. See ?rnorm. And repetition means that in your index you can have some rows more times and some rows never. Again only you know if this is desired behaviour. If not use replace=FALSE.
Also, do the apply methods perform better than for loops given the same function? sample: apply(x, fun) and for (i in 1:length(x)) fun(x[i])
In some quite recent R-News (I believe 2009 or 2008) there is an article about loops. And also R-Inferno by P.Burns is worth reading. My opinion is that simple cycles and apply functions are more or less similar. When I want to scan a file and make same plots for each column I use for cycle and in most other cases I use *apply family. If you have nested cycles which work correctly in reasonable time why not use them. But usually vectorised approach can be far quicker and, when you get used to it, clearer. Regards Petr
cheers cjmr -- View this message in context:
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