{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Testing with apply, foreach and for loops in R\n", "\n", "Similar to programs like C or C++, in R you can do looping to do some sort of iteration using for, apply and foreach functions. \n", "\n", "1. for: like any other programming, this loops user defined n time to do something\n", "2. apply: similar to for, apply can iterate over row or column to do a user defined task\n", "3. foreach: this function is like for function but, on steroids. Here, we can use parallel computing to perform for loops in parallel. \n", "\n", "To test out the performance of each of the functions, we will use different data sizes to see which performs better. \n", "getRes() function will basically look at a row to see it it meets constraints like if number of '1' in a row is less than or equal to something and if it is then it return 1 else 0. We can use this function against a dataframe to compare the results. \n", " " ] }, { "cell_type": "code", "execution_count": 43, "metadata": {}, "outputs": [], "source": [ "library(dplyr)\n", "library(microbenchmark)" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "getRes = function(combinations) {\n", " row = combinations\n", " one = length(which(row==1))\n", " two = length(which(row==2))\n", " three = length(which(row==3))\n", " if(one <= 6) \n", " {\n", " if(two <= 5)\n", " {\n", " if(three == 1)\n", " {\n", " return(1) \n", " }\n", " else {return(0)}\n", " }\n", " else {return(0)}\n", " }\n", " else {return(0)}\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Apply\n", "Create an apply loop function to run the getRes function. " ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "apply_loop = function (combinations){\n", " x1= as.POSIXct(Sys.time())\n", " res = NULL\n", "\n", " res = apply(combinations,1,getRes)\n", " x2= as.POSIXct(Sys.time())\n", " #return(res)\n", " return(as.difftime(x2-x1, units = \"secs\"))\n", "}\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Foreach\n", "Create an foreach loop function to run the getRes function. " ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Loading required package: iterators\n", "Loading required package: parallel\n" ] } ], "source": [ "library(foreach)\n", "library(doParallel)\n", "library(parallel)\n", "\n", "foreach_loop = function (combinations){\n", " cl <- makeCluster(16)\n", " clusterExport(cl, c(\"getRes\"))\n", " registerDoParallel(cl)\n", "\n", " x1= as.POSIXct(Sys.time())\n", "\n", " res = NULL\n", " res = foreach(i = 1:nrow(combinations), .combine = rbind) %dopar% {\n", " getRes(combinations[i,])\n", " }\n", "\n", " x2= as.POSIXct(Sys.time())\n", "\n", " stopCluster(cl)\n", " #return(res)\n", " return(as.difftime(x2-x1, units = \"secs\"))\n", "}\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## For\n", "Create an for loop function to run the getRes function. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "for_loop = function (combinations){\n", " x1= as.POSIXct(Sys.time())\n", " res=NULL\n", " for(i in 1:nrow(combinations)) {\n", " res[i] = getRes(combinations[i,])\n", " }\n", "\n", " x2= as.POSIXct(Sys.time())\n", " #return(res)\n", " return(as.difftime(x2-x1, units = \"secs\"))\n", "}" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Microbenchmark\n", "Do a microbench study to run all different loops and get some statistics. Microbench will perform 5 iterations. Dplyr package is used to group and summarize the data. " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\n", "
exprmeansdminmaxsize
apply_loop(combinations) 0.005530384 0.005370513 0.000274155 0.013071287 3
foreach_loop(combinations)8.803406354 1.063827929 7.817635844 10.580139362 3
for_loop(combinations) 0.002028997 0.003826046 0.000259613 0.008872582 3
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " expr & mean & sd & min & max & size\\\\\n", "\\hline\n", "\t apply\\_loop(combinations) & 0.005530384 & 0.005370513 & 0.000274155 & 0.013071287 & 3 \\\\\n", "\t foreach\\_loop(combinations) & 8.803406354 & 1.063827929 & 7.817635844 & 10.580139362 & 3 \\\\\n", "\t for\\_loop(combinations) & 0.002028997 & 0.003826046 & 0.000259613 & 0.008872582 & 3 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| expr | mean | sd | min | max | size |\n", "|---|---|---|---|---|---|\n", "| apply_loop(combinations) | 0.005530384 | 0.005370513 | 0.000274155 | 0.013071287 | 3 |\n", "| foreach_loop(combinations) | 8.803406354 | 1.063827929 | 7.817635844 | 10.580139362 | 3 |\n", "| for_loop(combinations) | 0.002028997 | 0.003826046 | 0.000259613 | 0.008872582 | 3 |\n", "\n" ], "text/plain": [ " expr mean sd min max \n", "1 apply_loop(combinations) 0.005530384 0.005370513 0.000274155 0.013071287\n", "2 foreach_loop(combinations) 8.803406354 1.063827929 7.817635844 10.580139362\n", "3 for_loop(combinations) 0.002028997 0.003826046 0.000259613 0.008872582\n", " size\n", "1 3 \n", "2 3 \n", "3 3 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mbLoops1 = NULL\n", "combinations = expand.grid(c(1:3))\n", "\n", "mbLoops = function(combinations) {\n", " res = microbenchmark(apply_loop(combinations), foreach_loop(combinations), for_loop(combinations), times=5)\n", "\n", " res1 = res\n", " res1$time = res1$time/1000000000\n", "\n", " mb = res1 %>% group_by(expr) %>% summarise (mean = mean(time)\n", " ,sd = sd(time)\n", " ,min = min(time)\n", " ,max = max(time)\n", " )\n", " mb$size = nrow(combinations)\n", " return(data.frame(mb))\n", " }\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)\n", "mbLoops1" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Increase the data size and run different loops. " ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
exprmeansdminmaxsize
apply_loop(combinations) 0.0003702156 0.0001160650 0.000245072 0.000558146 9
foreach_loop(combinations)8.9235569714 1.0460634556 7.948781962 10.436508331 9
for_loop(combinations) 0.0023198312 0.0003075862 0.002012317 0.002833496 9
apply_loop(combinations) 0.0055303840 0.0053705130 0.000274155 0.013071287 3
foreach_loop(combinations)8.8034063536 1.0638279289 7.817635844 10.580139362 3
for_loop(combinations) 0.0020289966 0.0038260461 0.000259613 0.008872582 3
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " expr & mean & sd & min & max & size\\\\\n", "\\hline\n", "\t apply\\_loop(combinations) & 0.0003702156 & 0.0001160650 & 0.000245072 & 0.000558146 & 9 \\\\\n", "\t foreach\\_loop(combinations) & 8.9235569714 & 1.0460634556 & 7.948781962 & 10.436508331 & 9 \\\\\n", "\t for\\_loop(combinations) & 0.0023198312 & 0.0003075862 & 0.002012317 & 0.002833496 & 9 \\\\\n", "\t apply\\_loop(combinations) & 0.0055303840 & 0.0053705130 & 0.000274155 & 0.013071287 & 3 \\\\\n", "\t foreach\\_loop(combinations) & 8.8034063536 & 1.0638279289 & 7.817635844 & 10.580139362 & 3 \\\\\n", "\t for\\_loop(combinations) & 0.0020289966 & 0.0038260461 & 0.000259613 & 0.008872582 & 3 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| expr | mean | sd | min | max | size |\n", "|---|---|---|---|---|---|\n", "| apply_loop(combinations) | 0.0003702156 | 0.0001160650 | 0.000245072 | 0.000558146 | 9 |\n", "| foreach_loop(combinations) | 8.9235569714 | 1.0460634556 | 7.948781962 | 10.436508331 | 9 |\n", "| for_loop(combinations) | 0.0023198312 | 0.0003075862 | 0.002012317 | 0.002833496 | 9 |\n", "| apply_loop(combinations) | 0.0055303840 | 0.0053705130 | 0.000274155 | 0.013071287 | 3 |\n", "| foreach_loop(combinations) | 8.8034063536 | 1.0638279289 | 7.817635844 | 10.580139362 | 3 |\n", "| for_loop(combinations) | 0.0020289966 | 0.0038260461 | 0.000259613 | 0.008872582 | 3 |\n", "\n" ], "text/plain": [ " expr mean sd min max \n", "1 apply_loop(combinations) 0.0003702156 0.0001160650 0.000245072 0.000558146\n", "2 foreach_loop(combinations) 8.9235569714 1.0460634556 7.948781962 10.436508331\n", "3 for_loop(combinations) 0.0023198312 0.0003075862 0.002012317 0.002833496\n", "4 apply_loop(combinations) 0.0055303840 0.0053705130 0.000274155 0.013071287\n", "5 foreach_loop(combinations) 8.8034063536 1.0638279289 7.817635844 10.580139362\n", "6 for_loop(combinations) 0.0020289966 0.0038260461 0.000259613 0.008872582\n", " size\n", "1 9 \n", "2 9 \n", "3 9 \n", "4 3 \n", "5 3 \n", "6 3 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "combinations = expand.grid(c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 9, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 10, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 13, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 20, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "combinations = expand.grid(c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3), c(1:3))\n", "\n", "mbLoops1 = rbind(mbLoops(combinations), mbLoops1)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "View summarized data metrics. Although its hard to make out the difference we can tell apply method was consistently faster compared to the rest of the function loops. " ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/html": [ "\n", "\n", "\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\t\n", "\n", "
exprmeansdminmaxsize
apply_loop(combinations) 1.848387e+00 3.015175e-01 1.471994e+00 2.226259e+00 177147
foreach_loop(combinations)1.756939e+02 4.049650e+00 1.717026e+02 1.804578e+02 177147
for_loop(combinations) 1.222849e+02 2.437452e+00 1.186793e+02 1.252447e+02 177147
apply_loop(combinations) 6.452159e-01 1.307745e-01 4.601797e-01 7.801982e-01 59049
foreach_loop(combinations)6.246728e+01 7.165803e+00 5.700542e+01 7.461992e+01 59049
for_loop(combinations) 3.708779e+01 9.613432e-01 3.541777e+01 3.783785e+01 59049
apply_loop(combinations) 2.185719e-01 8.620030e-02 1.540690e-01 3.656175e-01 19683
foreach_loop(combinations)2.780690e+01 4.613920e+00 2.177694e+01 3.357440e+01 19683
for_loop(combinations) 1.127049e+01 5.266426e-01 1.063290e+01 1.190946e+01 19683
apply_loop(combinations) 5.888674e-02 9.910095e-03 5.019370e-02 6.975744e-02 6561
foreach_loop(combinations)1.352766e+01 7.251917e-01 1.256073e+01 1.418346e+01 6561
for_loop(combinations) 3.338984e+00 1.610815e-01 3.139273e+00 3.567581e+00 6561
apply_loop(combinations) 1.710918e-02 3.091247e-03 1.499721e-02 2.237071e-02 2187
foreach_loop(combinations)1.083804e+01 1.087520e+00 9.656102e+00 1.251217e+01 2187
for_loop(combinations) 1.053878e+00 3.105298e-02 1.022057e+00 1.086726e+00 2187
apply_loop(combinations) 7.342367e-03 2.497263e-03 5.242287e-03 1.052349e-02 729
foreach_loop(combinations)1.078135e+01 2.409862e+00 8.325451e+00 1.378549e+01 729
for_loop(combinations) 3.257564e-01 1.426109e-02 3.101118e-01 3.424846e-01 729
apply_loop(combinations) 2.320430e-03 5.140325e-04 1.909242e-03 3.215429e-03 243
foreach_loop(combinations)8.617141e+00 4.455053e-01 8.162380e+00 9.211201e+00 243
for_loop(combinations) 9.985638e-02 1.557837e-02 8.301563e-02 1.190833e-01 243
apply_loop(combinations) 9.512850e-04 9.314809e-05 8.648040e-04 1.070955e-03 81
foreach_loop(combinations)8.679981e+00 9.159937e-01 7.738644e+00 1.009787e+01 81
for_loop(combinations) 2.897367e-02 4.510389e-03 2.456052e-02 3.390228e-02 81
apply_loop(combinations) 4.961294e-04 5.366293e-05 4.114450e-04 5.598560e-04 27
foreach_loop(combinations)8.584492e+00 1.111153e+00 7.625042e+00 1.049534e+01 27
for_loop(combinations) 6.967276e-03 2.343557e-03 5.693507e-03 1.115007e-02 27
apply_loop(combinations) 3.702156e-04 1.160650e-04 2.450720e-04 5.581460e-04 9
foreach_loop(combinations)8.923557e+00 1.046063e+00 7.948782e+00 1.043651e+01 9
for_loop(combinations) 2.319831e-03 3.075862e-04 2.012317e-03 2.833496e-03 9
apply_loop(combinations) 5.530384e-03 5.370513e-03 2.741550e-04 1.307129e-02 3
foreach_loop(combinations)8.803406e+00 1.063828e+00 7.817636e+00 1.058014e+01 3
for_loop(combinations) 2.028997e-03 3.826046e-03 2.596130e-04 8.872582e-03 3
\n" ], "text/latex": [ "\\begin{tabular}{r|llllll}\n", " expr & mean & sd & min & max & size\\\\\n", "\\hline\n", "\t apply\\_loop(combinations) & 1.848387e+00 & 3.015175e-01 & 1.471994e+00 & 2.226259e+00 & 177147 \\\\\n", "\t foreach\\_loop(combinations) & 1.756939e+02 & 4.049650e+00 & 1.717026e+02 & 1.804578e+02 & 177147 \\\\\n", "\t for\\_loop(combinations) & 1.222849e+02 & 2.437452e+00 & 1.186793e+02 & 1.252447e+02 & 177147 \\\\\n", "\t apply\\_loop(combinations) & 6.452159e-01 & 1.307745e-01 & 4.601797e-01 & 7.801982e-01 & 59049 \\\\\n", "\t foreach\\_loop(combinations) & 6.246728e+01 & 7.165803e+00 & 5.700542e+01 & 7.461992e+01 & 59049 \\\\\n", "\t for\\_loop(combinations) & 3.708779e+01 & 9.613432e-01 & 3.541777e+01 & 3.783785e+01 & 59049 \\\\\n", "\t apply\\_loop(combinations) & 2.185719e-01 & 8.620030e-02 & 1.540690e-01 & 3.656175e-01 & 19683 \\\\\n", "\t foreach\\_loop(combinations) & 2.780690e+01 & 4.613920e+00 & 2.177694e+01 & 3.357440e+01 & 19683 \\\\\n", "\t for\\_loop(combinations) & 1.127049e+01 & 5.266426e-01 & 1.063290e+01 & 1.190946e+01 & 19683 \\\\\n", "\t apply\\_loop(combinations) & 5.888674e-02 & 9.910095e-03 & 5.019370e-02 & 6.975744e-02 & 6561 \\\\\n", "\t foreach\\_loop(combinations) & 1.352766e+01 & 7.251917e-01 & 1.256073e+01 & 1.418346e+01 & 6561 \\\\\n", "\t for\\_loop(combinations) & 3.338984e+00 & 1.610815e-01 & 3.139273e+00 & 3.567581e+00 & 6561 \\\\\n", "\t apply\\_loop(combinations) & 1.710918e-02 & 3.091247e-03 & 1.499721e-02 & 2.237071e-02 & 2187 \\\\\n", "\t foreach\\_loop(combinations) & 1.083804e+01 & 1.087520e+00 & 9.656102e+00 & 1.251217e+01 & 2187 \\\\\n", "\t for\\_loop(combinations) & 1.053878e+00 & 3.105298e-02 & 1.022057e+00 & 1.086726e+00 & 2187 \\\\\n", "\t apply\\_loop(combinations) & 7.342367e-03 & 2.497263e-03 & 5.242287e-03 & 1.052349e-02 & 729 \\\\\n", "\t foreach\\_loop(combinations) & 1.078135e+01 & 2.409862e+00 & 8.325451e+00 & 1.378549e+01 & 729 \\\\\n", "\t for\\_loop(combinations) & 3.257564e-01 & 1.426109e-02 & 3.101118e-01 & 3.424846e-01 & 729 \\\\\n", "\t apply\\_loop(combinations) & 2.320430e-03 & 5.140325e-04 & 1.909242e-03 & 3.215429e-03 & 243 \\\\\n", "\t foreach\\_loop(combinations) & 8.617141e+00 & 4.455053e-01 & 8.162380e+00 & 9.211201e+00 & 243 \\\\\n", "\t for\\_loop(combinations) & 9.985638e-02 & 1.557837e-02 & 8.301563e-02 & 1.190833e-01 & 243 \\\\\n", "\t apply\\_loop(combinations) & 9.512850e-04 & 9.314809e-05 & 8.648040e-04 & 1.070955e-03 & 81 \\\\\n", "\t foreach\\_loop(combinations) & 8.679981e+00 & 9.159937e-01 & 7.738644e+00 & 1.009787e+01 & 81 \\\\\n", "\t for\\_loop(combinations) & 2.897367e-02 & 4.510389e-03 & 2.456052e-02 & 3.390228e-02 & 81 \\\\\n", "\t apply\\_loop(combinations) & 4.961294e-04 & 5.366293e-05 & 4.114450e-04 & 5.598560e-04 & 27 \\\\\n", "\t foreach\\_loop(combinations) & 8.584492e+00 & 1.111153e+00 & 7.625042e+00 & 1.049534e+01 & 27 \\\\\n", "\t for\\_loop(combinations) & 6.967276e-03 & 2.343557e-03 & 5.693507e-03 & 1.115007e-02 & 27 \\\\\n", "\t apply\\_loop(combinations) & 3.702156e-04 & 1.160650e-04 & 2.450720e-04 & 5.581460e-04 & 9 \\\\\n", "\t foreach\\_loop(combinations) & 8.923557e+00 & 1.046063e+00 & 7.948782e+00 & 1.043651e+01 & 9 \\\\\n", "\t for\\_loop(combinations) & 2.319831e-03 & 3.075862e-04 & 2.012317e-03 & 2.833496e-03 & 9 \\\\\n", "\t apply\\_loop(combinations) & 5.530384e-03 & 5.370513e-03 & 2.741550e-04 & 1.307129e-02 & 3 \\\\\n", "\t foreach\\_loop(combinations) & 8.803406e+00 & 1.063828e+00 & 7.817636e+00 & 1.058014e+01 & 3 \\\\\n", "\t for\\_loop(combinations) & 2.028997e-03 & 3.826046e-03 & 2.596130e-04 & 8.872582e-03 & 3 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "| expr | mean | sd | min | max | size |\n", "|---|---|---|---|---|---|\n", "| apply_loop(combinations) | 1.848387e+00 | 3.015175e-01 | 1.471994e+00 | 2.226259e+00 | 177147 |\n", "| foreach_loop(combinations) | 1.756939e+02 | 4.049650e+00 | 1.717026e+02 | 1.804578e+02 | 177147 |\n", "| for_loop(combinations) | 1.222849e+02 | 2.437452e+00 | 1.186793e+02 | 1.252447e+02 | 177147 |\n", "| apply_loop(combinations) | 6.452159e-01 | 1.307745e-01 | 4.601797e-01 | 7.801982e-01 | 59049 |\n", "| foreach_loop(combinations) | 6.246728e+01 | 7.165803e+00 | 5.700542e+01 | 7.461992e+01 | 59049 |\n", "| for_loop(combinations) | 3.708779e+01 | 9.613432e-01 | 3.541777e+01 | 3.783785e+01 | 59049 |\n", "| apply_loop(combinations) | 2.185719e-01 | 8.620030e-02 | 1.540690e-01 | 3.656175e-01 | 19683 |\n", "| foreach_loop(combinations) | 2.780690e+01 | 4.613920e+00 | 2.177694e+01 | 3.357440e+01 | 19683 |\n", "| for_loop(combinations) | 1.127049e+01 | 5.266426e-01 | 1.063290e+01 | 1.190946e+01 | 19683 |\n", "| apply_loop(combinations) | 5.888674e-02 | 9.910095e-03 | 5.019370e-02 | 6.975744e-02 | 6561 |\n", "| foreach_loop(combinations) | 1.352766e+01 | 7.251917e-01 | 1.256073e+01 | 1.418346e+01 | 6561 |\n", "| for_loop(combinations) | 3.338984e+00 | 1.610815e-01 | 3.139273e+00 | 3.567581e+00 | 6561 |\n", "| apply_loop(combinations) | 1.710918e-02 | 3.091247e-03 | 1.499721e-02 | 2.237071e-02 | 2187 |\n", "| foreach_loop(combinations) | 1.083804e+01 | 1.087520e+00 | 9.656102e+00 | 1.251217e+01 | 2187 |\n", "| for_loop(combinations) | 1.053878e+00 | 3.105298e-02 | 1.022057e+00 | 1.086726e+00 | 2187 |\n", "| apply_loop(combinations) | 7.342367e-03 | 2.497263e-03 | 5.242287e-03 | 1.052349e-02 | 729 |\n", "| foreach_loop(combinations) | 1.078135e+01 | 2.409862e+00 | 8.325451e+00 | 1.378549e+01 | 729 |\n", "| for_loop(combinations) | 3.257564e-01 | 1.426109e-02 | 3.101118e-01 | 3.424846e-01 | 729 |\n", "| apply_loop(combinations) | 2.320430e-03 | 5.140325e-04 | 1.909242e-03 | 3.215429e-03 | 243 |\n", "| foreach_loop(combinations) | 8.617141e+00 | 4.455053e-01 | 8.162380e+00 | 9.211201e+00 | 243 |\n", "| for_loop(combinations) | 9.985638e-02 | 1.557837e-02 | 8.301563e-02 | 1.190833e-01 | 243 |\n", "| apply_loop(combinations) | 9.512850e-04 | 9.314809e-05 | 8.648040e-04 | 1.070955e-03 | 81 |\n", "| foreach_loop(combinations) | 8.679981e+00 | 9.159937e-01 | 7.738644e+00 | 1.009787e+01 | 81 |\n", "| for_loop(combinations) | 2.897367e-02 | 4.510389e-03 | 2.456052e-02 | 3.390228e-02 | 81 |\n", "| apply_loop(combinations) | 4.961294e-04 | 5.366293e-05 | 4.114450e-04 | 5.598560e-04 | 27 |\n", "| foreach_loop(combinations) | 8.584492e+00 | 1.111153e+00 | 7.625042e+00 | 1.049534e+01 | 27 |\n", "| for_loop(combinations) | 6.967276e-03 | 2.343557e-03 | 5.693507e-03 | 1.115007e-02 | 27 |\n", "| apply_loop(combinations) | 3.702156e-04 | 1.160650e-04 | 2.450720e-04 | 5.581460e-04 | 9 |\n", "| foreach_loop(combinations) | 8.923557e+00 | 1.046063e+00 | 7.948782e+00 | 1.043651e+01 | 9 |\n", "| for_loop(combinations) | 2.319831e-03 | 3.075862e-04 | 2.012317e-03 | 2.833496e-03 | 9 |\n", "| apply_loop(combinations) | 5.530384e-03 | 5.370513e-03 | 2.741550e-04 | 1.307129e-02 | 3 |\n", "| foreach_loop(combinations) | 8.803406e+00 | 1.063828e+00 | 7.817636e+00 | 1.058014e+01 | 3 |\n", "| for_loop(combinations) | 2.028997e-03 | 3.826046e-03 | 2.596130e-04 | 8.872582e-03 | 3 |\n", "\n" ], "text/plain": [ " expr mean sd min \n", "1 apply_loop(combinations) 1.848387e+00 3.015175e-01 1.471994e+00\n", "2 foreach_loop(combinations) 1.756939e+02 4.049650e+00 1.717026e+02\n", "3 for_loop(combinations) 1.222849e+02 2.437452e+00 1.186793e+02\n", "4 apply_loop(combinations) 6.452159e-01 1.307745e-01 4.601797e-01\n", "5 foreach_loop(combinations) 6.246728e+01 7.165803e+00 5.700542e+01\n", "6 for_loop(combinations) 3.708779e+01 9.613432e-01 3.541777e+01\n", "7 apply_loop(combinations) 2.185719e-01 8.620030e-02 1.540690e-01\n", "8 foreach_loop(combinations) 2.780690e+01 4.613920e+00 2.177694e+01\n", "9 for_loop(combinations) 1.127049e+01 5.266426e-01 1.063290e+01\n", "10 apply_loop(combinations) 5.888674e-02 9.910095e-03 5.019370e-02\n", "11 foreach_loop(combinations) 1.352766e+01 7.251917e-01 1.256073e+01\n", "12 for_loop(combinations) 3.338984e+00 1.610815e-01 3.139273e+00\n", "13 apply_loop(combinations) 1.710918e-02 3.091247e-03 1.499721e-02\n", "14 foreach_loop(combinations) 1.083804e+01 1.087520e+00 9.656102e+00\n", "15 for_loop(combinations) 1.053878e+00 3.105298e-02 1.022057e+00\n", "16 apply_loop(combinations) 7.342367e-03 2.497263e-03 5.242287e-03\n", "17 foreach_loop(combinations) 1.078135e+01 2.409862e+00 8.325451e+00\n", "18 for_loop(combinations) 3.257564e-01 1.426109e-02 3.101118e-01\n", "19 apply_loop(combinations) 2.320430e-03 5.140325e-04 1.909242e-03\n", "20 foreach_loop(combinations) 8.617141e+00 4.455053e-01 8.162380e+00\n", "21 for_loop(combinations) 9.985638e-02 1.557837e-02 8.301563e-02\n", "22 apply_loop(combinations) 9.512850e-04 9.314809e-05 8.648040e-04\n", "23 foreach_loop(combinations) 8.679981e+00 9.159937e-01 7.738644e+00\n", "24 for_loop(combinations) 2.897367e-02 4.510389e-03 2.456052e-02\n", "25 apply_loop(combinations) 4.961294e-04 5.366293e-05 4.114450e-04\n", "26 foreach_loop(combinations) 8.584492e+00 1.111153e+00 7.625042e+00\n", "27 for_loop(combinations) 6.967276e-03 2.343557e-03 5.693507e-03\n", "28 apply_loop(combinations) 3.702156e-04 1.160650e-04 2.450720e-04\n", "29 foreach_loop(combinations) 8.923557e+00 1.046063e+00 7.948782e+00\n", "30 for_loop(combinations) 2.319831e-03 3.075862e-04 2.012317e-03\n", "31 apply_loop(combinations) 5.530384e-03 5.370513e-03 2.741550e-04\n", "32 foreach_loop(combinations) 8.803406e+00 1.063828e+00 7.817636e+00\n", "33 for_loop(combinations) 2.028997e-03 3.826046e-03 2.596130e-04\n", " max size \n", "1 2.226259e+00 177147\n", "2 1.804578e+02 177147\n", "3 1.252447e+02 177147\n", "4 7.801982e-01 59049\n", "5 7.461992e+01 59049\n", "6 3.783785e+01 59049\n", "7 3.656175e-01 19683\n", "8 3.357440e+01 19683\n", "9 1.190946e+01 19683\n", "10 6.975744e-02 6561\n", "11 1.418346e+01 6561\n", "12 3.567581e+00 6561\n", "13 2.237071e-02 2187\n", "14 1.251217e+01 2187\n", "15 1.086726e+00 2187\n", "16 1.052349e-02 729\n", "17 1.378549e+01 729\n", "18 3.424846e-01 729\n", "19 3.215429e-03 243\n", "20 9.211201e+00 243\n", "21 1.190833e-01 243\n", "22 1.070955e-03 81\n", "23 1.009787e+01 81\n", "24 3.390228e-02 81\n", "25 5.598560e-04 27\n", "26 1.049534e+01 27\n", "27 1.115007e-02 27\n", "28 5.581460e-04 9\n", "29 1.043651e+01 9\n", "30 2.833496e-03 9\n", "31 1.307129e-02 3\n", "32 1.058014e+01 3\n", "33 8.872582e-03 3" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "mbLoops1 " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Let's plot the data to better visualize how everything looks like. " ] }, { "cell_type": "code", "execution_count": 41, "metadata": {}, "outputs": [ { "data": { "image/png": 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M2Lrfnip4NV/GtwcZOuHpCpPrBT3a+hDf7AHsjg4/f4pgMGaz0tTmZvr6JFrwTr\nvvHumIkZavyS1X4cBwzWoph8/1aX/laTYvHuKtofYL19hxr6jjnww204A40fsWl//xgwWJPi\n93j5t5i8uYqmXh12eNQHZQdeHOCnDb5CuKHtvXDAYBXFrW/219Q8XlpjsC4ef109IJN9YCe6\nW6QriSOszWNu99/LG3X1gEz1gZ3qfpGsYeewVn/Vpa7nsG4+8ATrkTT3imQNeVrDrPacb7p+\ndxW146s7QenqAemBDQEY9jysRXUe1mT+1cV5WOV+1qq6LCiQgajPdAfyIlhANAQLiIZgAdEQ\nLCAaggVEQ7CAaAgWEA3BAqIhWEA0BAuIhmAB0RAsIBqBBgugwQs16T5QLwpnS4JhSC4ZkSuZ\nDUk4uxvOlgTDkFwyIlcyG5JwdjecLQmGIblkRK5kNiTh7G44WxIMQ3LJiFzJbEjC2d1wtiQY\nhuSSEbmS2ZCEs7vhbEkwDMklI3IlsyEJZ3fD2ZJgGJJLRuRKZkMSzu6GsyXBMCSXjMiVzIYk\nnN0NZ0uCYUguGZErmQ1JOLsbzpYEw5BcMiJXMhuScHY3nC0JhiG5ZESuZDYk4exuOFsSDENy\nyYhcyWxIMttdIGaCBURDsIBoCBYQDcECoiFYQDQEC4iGYAHRECwgGoIFREOwgGgIFhANwQKi\nIVhANAQLiIZgAdEIJFiLSTFZrMfeinEUO9Xl2jg8vJiq5eE++cxgpD0uhyFxVwkkWLPq32E6\n9maM4rd2L6yNw8OLqfrdPyCfGoy0x+UwJO4qgQTrp5j8lr+T4mfsDRnDbzE/XKyNw8OLqdrs\n3e4++cxgpD0uxyFxVwkkWItitfnvd/E19oaMYXna7do4PLyYqGUxOzzleWIwkh6X05C4qwQS\nrHnxV579/yMny2J5uFgbh4cXE1Usyv2j85nBSHpcTkPirhJIsPb/HkUQGzO0ebH6LCaL7cXa\nODy8mKjfy51sNRhJj8tpSNxVBGt8891E6qzM+F54RrCuHIPlrhLE/qQ6uK0UxXdZrhfbo/1s\n74VnBOvKcf/cVYLYn1QH9wnr7QvQ2d4LzwjWlbMdy/uuEsT+TBId3Gdsd742Dg8vpmu/d88M\nRurjcr5jWQ9JEPuze0XjL7lXNJ6xvWfVxuHhxXQdJ2zaD0bq43IdrGyHJIhgfVXnjKyKxdgb\nMoZJsX37RHXPqo3Dw4vp2j86nxmM1MfleNDprhJEsFI9K7eVxfY+ta7O88v29OUz+0enM91P\n9kPirhJIsMrp8eXa/Kwn1c5X/yesjcPDi8k6PP95ZjASH5f9kLirhBKsdfXO8rG3YiTbnZ8u\njxf34/DwYkC8LqIAAALdSURBVLIOwXpmMBIfl/qQZH5XCSNYAC0IFhANwQKiIVhANAQLiIZg\nAdEQLCAaggVEQ7CAaAgWEA3BAqIhWEA0BAuIhmAB0RAsIBqCBURDsIBoCBYQDcECoiFYQDQE\nC4iGYAHRECwgGoIFREOwgGgIFhANwQKiIVhANAQLiIZgAdEQLCAaggVEQ7CAaAgWHSgq08X6\n8gerG7+wXkyLYrbc/W6vm0ZS3FnoQLE3+Tu/fnrj/rWe7G+/Fiye4c5CB3bR+ZsVs6brr30W\ns7/q9ou+t4y0CBYdOIRpWqwar7++ffXkce3oiue4w9CBQ3hWxef2v/PNk71FuX+mWL/i8vaH\ny4enlJtvl9Nishxsw4mMYNGBQ4DWxbQsv3bxWRyDdbriYFF8/tV/9xSsefV1drkCqAgWHTge\nMe3q812W39VVu+trVxzMtq8p/pz/7uemU6titi7Xs+LWq4tkTrDowFmwapcun/qdrD63LxKu\natdXM/bzanJrXcz73V5iJVh04CJYf6uv2VmwjlfU/XxNip/jbXavMBa12Sy44o5BB45hqqoz\nOzbnGKPmCP1up7x218+q6XrB4j53DDpwCMz3dmb9s5guV3+1YNWuOL/5fsprE7rJfkpeqbjL\n/YMOnM7DOjzHqwerdsXOvNiduLAuJtVPj73a/MR0O3cIFh04O9O92FTr9zCH9Xd+xc5PUSzX\nmy+zbbg21x97tTlEm/yW5dKkO80Eiw6cvZdwsf/mZ3vEtT2Gql2xd7hm17f6zNWs8T2JsCNY\ndGCfn6/dd5+biz+r7VHSz3QbrNoVB7+fk81137vfPZtqX24i96lXNBMsIBqCBURDsIBoCBYQ\nDcECoiFYQDQEC4iGYAHRECwgGoIFREOwgGgIFhANwQKiIVhANAQLiIZgAdEQLCAaggVEQ7CA\naAgWEA3BAqIhWEA0BAuIhmAB0RAsIBqCBURDsIBoCBYQDcECoiFYQDQEC4jG/0JHNkFKhrXx\nAAAAAElFTkSuQmCC", "text/plain": [ "Plot with title \"Mean of Different Loops Comparison\"" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Adjust plot sizes\n", "options(repr.plot.width=10, repr.plot.height=6)\n", "\n", "plot(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='apply_loop(combinations)')$mean\n", " , type='o'\n", " , col='red'\n", " , pch=19\n", " , ylim = c(0,180)\n", " , ylab=\"Seconds\"\n", " , xlab = \"Data Size\"\n", " , main = \"Mean of Different Loops Comparison\"\n", " )\n", "lines(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='foreach_loop(combinations)')$mean \n", " , type='o'\n", " , col='green'\n", " , pch=19\n", " )\n", "lines(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='for_loop(combinations)')$mean\n", " , type='o'\n", " , col='blue'\n", " , pch=19\n", " )\n", "legend(\"topleft\", c(\"apply\", \"foreach\", \"for\"), col = c(\"red\", \"green\",\"blue\"), lty=1, cex=0.8 )" ] }, { "cell_type": "code", "execution_count": 42, "metadata": {}, "outputs": [ { "data": { "image/png": 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"text/plain": [ "Plot with title \"SD of Different Loops Comparison\"" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "#Adjust plot sizes\n", "options(repr.plot.width=10, repr.plot.height=6)\n", "\n", "plot(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='apply_loop(combinations)')$sd\n", " , type='o'\n", " , col='red'\n", " , pch=19\n", " , ylim = c(0,15)\n", " , ylab=\"Seconds\"\n", " , xlab = \"Data Size\"\n", " , main = \"SD of Different Loops Comparison\"\n", " )\n", "lines(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='foreach_loop(combinations)')$sd\n", " , type='o'\n", " , col='green'\n", " , pch=19\n", " )\n", "lines(subset(mbLoops1, expr =='apply_loop(combinations)')$size\n", " , subset(mbLoops1, expr =='for_loop(combinations)')$sd\n", " , type='o'\n", " , col='blue'\n", " , pch=19\n", " )\n", "legend(\"topleft\", c(\"apply\", \"foreach\", \"for\"), col = c(\"red\", \"green\",\"blue\"), lty=1, cex=0.8 )" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "From the above study, we can observe that apply loop was consistently much faster compared to either for or foreach loop. As the data size increases, the time to run also increased linearly in for and foreach loop. On the other hand for apply, there was almost no change in time to run apply loop. " ] }, { "cell_type": "code", "execution_count": 38, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "R version 3.5.1 (2018-07-02)\n", "Platform: x86_64-w64-mingw32/x64 (64-bit)\n", "Running under: Windows 10 x64 (build 14393)\n", "\n", "Matrix products: default\n", "\n", "locale:\n", "[1] LC_COLLATE=English_United States.1252 \n", "[2] LC_CTYPE=English_United States.1252 \n", "[3] LC_MONETARY=English_United States.1252\n", "[4] LC_NUMERIC=C \n", "[5] LC_TIME=English_United States.1252 \n", "\n", "attached base packages:\n", "[1] parallel stats graphics grDevices utils datasets methods \n", "[8] base \n", "\n", "other attached packages:\n", "[1] doParallel_1.0.13 iterators_1.0.10 foreach_1.5.0 \n", "[4] microbenchmark_1.4-4 dplyr_0.7.8 RevoUtils_11.0.1 \n", "[7] RevoUtilsMath_11.0.0\n", "\n", "loaded via a namespace (and not attached):\n", " [1] Rcpp_1.0.0 bindr_0.1.1 magrittr_1.5 \n", " [4] tidyselect_0.2.5 uuid_0.1-2 R6_2.2.2 \n", " [7] rlang_0.3.1 tools_3.5.1 htmltools_0.3.6 \n", "[10] digest_0.6.15 assertthat_0.2.0 tibble_1.4.2 \n", "[13] crayon_1.3.4 bindrcpp_0.2.2 IRdisplay_0.7.0.9000\n", "[16] purrr_0.2.5 repr_0.19.1.9000 codetools_0.2-15 \n", "[19] base64enc_0.1-3 IRkernel_0.8.15.9000 glue_1.3.0 \n", "[22] evaluate_0.12 pbdZMQ_0.3-3 compiler_3.5.1 \n", "[25] pillar_1.3.0 jsonlite_1.5 pkgconfig_2.0.2 " ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "sessionInfo()" ] } ], "metadata": { "kernelspec": { "display_name": "R", "language": "R", "name": "ir" }, "language_info": { "codemirror_mode": "r", "file_extension": ".r", "mimetype": "text/x-r-source", "name": "R", "pygments_lexer": "r", "version": "3.5.1" } }, "nbformat": 4, "nbformat_minor": 2 }