绘制三个函数的运行时间 [英] Plot the run time of three functions

问题描述

我有三个函数执行相同的任务，但方式不同:

I have three functions doing the same task but in a different way:

功能一:

f1 <- function(n) {
  sum = 0
  for(i in 1:n) {
    sum <- sum + a(i)
  }
  return(sum)
}

功能 2:

f4 <- function(n) {
  sum = 0
  for(i in 1:n) {
    sum <- sum + b(i)
  }
  return(sum)
}

功能 3:

f3 <- function(n) {
  #Done using lgamma
  sum = 0
  for(i in 1:n) {
    sum = sum + c(i)
  }
  return(sum)
}

我需要使用 system.time 中的 user 时间在 1 - n 的值范围内绘制这 3 个函数的运行时间.如何在 R 中做到这一点?

I need to plot the runtime of these 3 functions over a range of values 1 - n using user time from system.time. How can this be done in R?

推荐答案

您可以使用 microbenchmark 为您的函数计时，并使用 ggplot2 进行绘图.下面是一个例子:

You could use microbenchmark to time your functions, and ggplot2 to plot. Here is an example:

library(microbenchmark)
library(reshape2)
library(ggplot2)

max_n = 15
results = data.frame(sum_lgamma=numeric(max_n),
                     sum_log_gamma_recursive = numeric(max_n),
                     sum_log_gamma_loop = numeric(max_n),
                     id = seq(max_n))
for(i in 1:max_n)
{
  results$sum_lgamma[i] = median(microbenchmark::microbenchmark(sum_lgamma(i))$time)
  results$sum_log_gamma_loop[i] = median(microbenchmark::microbenchmark(sum_log_gamma_loop(i))$time)
  results$sum_log_gamma_recursive[i] = median(microbenchmark::microbenchmark(sum_log_gamma_recursive(i))$time)
}
results = melt(results, id.vars=c("id"))

ggplot(results, aes(x=id,y=value,color=variable)) + geom_line()

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