This section shows you how to write a fast loop, and how efficient it is. Five examples will be demonstrated different ways o write the loop for the same purpose which is "sum a large matrix several times", as the following, <ol> <li> "Sum by for 1" -- use <code>for()</code> loop to sum up the matrix by column. <li> "Sum by for 2" -- use <code>for()</code> loop to sum up the matrix by row. <li> "Sum by apply" -- use <code>apply()</code> function to sum up the matrix. <li> "Sum by rowSums" -- use <code>rowSums()</code> internal function to sum up the matrix. <li> "Sum by dyn" -- use "dynamical loading" to load external function to sum up the matrix. </ol> Finally, the computing time of the above methods will be listed. The parallel version of these methods will be demonstrated and compared at the section of "<a href="./Rmpi.html">LAM/MPI/Rmpi</a>". <hr> - Sum by for 1 First, create an R code file "<a href="./example/loop/loop_for_1.r" target="_blank">loop_for_1.r</a>" contains this ``` # File name: loop_for_1.r my.loop <- 20 m.dim <- list(nrow = 200000, ncol = 10) m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol) ret <- 0 start <- Sys.time() for(k in 1 : my.loop){ for (i in 1 : m.dim$nrow){ for (j in 1 : m.dim$ncol){ ret <- ret + m[i, j] } } } Sys.time() - start ``` - Sum by for 2 First, create an R code file "<a href="./example/loop/loop_for_2.r" target="_blank">loop_for_2.r</a>" contains this ``` # File name: loop_for_2.r my.loop <- 20 m.dim <- list(nrow = 200000, ncol = 10) m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol) ret <- 0 start <- Sys.time() for(k in 1 : my.loop){ for (j in 1 : m.dim$ncol){ for (i in 1 : m.dim$nrow){ ret <- ret + m[i, j] } } } Sys.time() - start ``` - Sum by apply And then, create an R code file "<a href="./example/loop/loop_apply.r" target="_blank">loop_apply.r</a>" contains this ``` # File name: loop_apply.r my.loop <- 20 m.dim <- list(nrow = 200000, ncol = 10) m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol) ret <- 0 start <- Sys.time() for(k in 1 : my.loop){ ret <- ret + sum(apply(m, 1, sum)) } Sys.time() - start ``` - Sum by rowSums And then, create an R code file "<a href="./example/loop/loop_rowSums.r" target="_blank">loop_rowSums.r</a>" contains this ``` # File name: loop_rowSums.r my.loop <- 20 m.dim <- list(nrow = 200000, ncol = 10) m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol) ret <- 0 start <- Sys.time() for(k in 1 : my.loop){ ret <- ret + sum(rowSums(m)) } Sys.time() - start ``` - Sum by dyn Create a Fortran code file "<a href="./example/loop/loop_dyn.f" target="_blank">loop_dyn.f</a>" contains this ``` c File name: lood_dyn.f c For dynamical load compile by g77. c SHELL> g77 -c loop_dyn.f ; g77 -shared -o loop_dyn.so loop_dyn.o subroutine dynsum(nrow, ncol, m, ret) integer i, j, nrow, ncol real*8 m(nrow, ncol), ret ret = 0 do j = 1, ncol do i = 1, nrow ret = ret + m(i, j) end do end do return end c Output is a shared library "loop_dyn.so" can called by R. ``` And, create an R code file "<a href="./example/loop/loop_dyn.r" target="_blank">loop_dyn.r</a>" contains this ``` # File name: loop_dyn.r dyn.load("loop_dyn.so") # For Windows will like this # dyn.load("C:/Windows/Desktop/loop_dyn.dll") my.loop <- 20 m.dim <- list(nrow = 200000, ncol = 10) m <- matrix(1, nrow = m.dim$nrow, ncol = m.dim$ncol) ret <- 0 dynsum.f <- function(m) { ret <- .Fortran("dynsum", nrow = nrow(m), ncol = ncol(m), m = as.double(m), ret = as.double(m)) ret$ret } start <- Sys.time() for(k in 1 : my.loop){ ret <- ret + dynsum.f(m) } Sys.time() - start dyn.unload("loop_dyn.so") # For Windows will like this # dyn.unload("C:/Windows/Desktop/loop_dyn.dll") ``` For test, download the example "<a href="./example/loop/loop_dyn.dll" target="_blank">loop_dyn.dll</a>" to "C:\Windows\Desktop\". - Computing time For PIII-1.4G PC, the test computing time as follows, <table cellpadding="5"> <tr> <th bgcolor="#d3dce3"> Sum by Loop <th bgcolor="#d3dce3"> for 1 <th bgcolor="#d3dce3"> for 2 <th bgcolor="#d3dce3"> apply <th bgcolor="#d3dce3"> rowSums <th bgcolor="#d3dce3"> dyn <tr> <th bgcolor="#d3dce3"> Time (secs) <td bgcolor="#dddddd"> 331 <td bgcolor="#dddddd"> 307 <td bgcolor="#dddddd"> 117 <td bgcolor="#dddddd"> 2 <td bgcolor="#dddddd"> 19 </table> - Conclusion Use default internal function. Use external compiled function. Use "apply" to substitute "for loop". See "apply", "lapply", "tapply", "sapply". Use a column-wise data structure in R and Fortran. Use a row-wise data structure in C. --- <div w3-include-html="../preamble_tail_date.html"></div>