1. avoid data frame (from 2nd)
2. ifelse is slower than if () { } else { } (from 1st)
3. aovid using rbind, cbind in loops, predifine a NA array or matrix(from 2nd)
Examples:
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| ## data frame and matrix comparison | |
| > m <- matrix(nrow=2000, ncol =1) | |
| > system.time(for (i in 1:2000) {m[i,1] <- 1}) | |
| user system elapsed | |
| 0 0 0 | |
| > m <- as.data.frame(m) | |
| > system.time(for (i in 1:2000) {m[i,1] <- 1}) | |
| user system elapsed | |
| 0.42 0.00 0.44 | |
| ## ifelse cbind | |
| testifelse <- function(x) { | |
| for(i in 1:x) { | |
| tmp <- paste("out", i) | |
| ifelse(i == 1, out <- tmp, out <- c(out, tmp)) | |
| } | |
| } | |
| testif <- function(x) { | |
| for(i in 1:x) { | |
| tmp <- paste("out", i) | |
| if (i == 1) { | |
| out <- tmp | |
| } else { | |
| out <- c(out, tmp) | |
| } | |
| } | |
| } | |
| > system.time(testifelse(2000)) | |
| user system elapsed | |
| 0.22 0.00 0.22 | |
| > system.time(testif(2000)) | |
| user system elapsed | |
| 0.11 0.00 0.11 | |
| byarray <- function(x) { | |
| out <- matrix(NA, nrow=x, ncol =1) | |
| for(i in 1:x) { | |
| tmp <- paste("out", i) | |
| out[i,1] <- tmp | |
| } | |
| } | |
| > system.time(byarray(2000)) | |
| user system elapsed | |
| 0.06 0.00 0.06 |
