R/profiling.R

In thozh912/Lab6: Performace code for knapsack problem

#' This function measures performance of code
#' 
#' Some time trials of our code
#' 
#' We use Rprof to find out performance of certain bits of code in this package.
#' We also found out two nested for loops are a little faster than two nested
#' while loops.

profiling <- function(){
  knapsack_matr <- knapsack_gener_matr()
  knapsack_df <- knapsack_generator()
  boz <- function(data){
    for(i in 1:2){
      for(j in 1:1000){
        tag <- data[j,i]
      }
    }
    return(paste("Done"))
  }
  
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  boz(knapsack_matr)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  boz(knapsack_df)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  alt_brute_force_knapsack(knapsack_matr[1:8,], W = 2000, parallel = TRUE)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  brute_force_knapsack(knapsack_matr[1:8,], W = 2000, parallel = TRUE)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  brute_force_knapsack(knapsack_matr[1:15,], W = 2000)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  knapsack_dynamic(knapsack_matr[1:100,], W = 8000)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  greedy_knapsack(knapsack_matr[1:100000,], W = 8000)
  Rprof(NULL)
  summaryRprof(tmp)
  
  
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  alt_brute_force_knapsack(knapsack_df[1:8,], W = 2000, parallel = TRUE)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  brute_force_knapsack(knapsack_df[1:8,], W = 2000, parallel = TRUE)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  brute_force_knapsack(knapsack_df[1:15,], W = 2000)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  knapsack_dynamic(knapsack_df[1:100,], W = 8000)
  Rprof(NULL)
  summaryRprof(tmp)
  
  tmp <- tempfile()
  Rprof(tmp,interval = 0.01)
  greedy_knapsack(knapsack_df[1:100000,], W = 8000)
  Rprof(NULL)
  summaryRprof(tmp)

}