Benchmarking

library(hermes6)
library(tibble)
library(magrittr)

Comparisons of speed for different Markov Smoking Probabilistic models.

Functions being tested are. Creates list of functions where the name starts with markov. All top level functions should start with this.

function_names <- ls("package:hermes6", pattern = "markov*")
function_names
#>  [1] "markov"                               
#>  [2] "markov_expanded"                      
#>  [3] "markov_expanded_lapply"               
#>  [4] "markov_expanded_lapply_rcpp"          
#>  [5] "markov_expanded_lapply_vectorise"     
#>  [6] "markov_expanded_parallisesmp_foreach" 
#>  [7] "markov_expanded_parallisesmp_furrr"   
#>  [8] "markov_expanded_parallisesmp_mclapply"
#>  [9] "markov_expanded_vectorise"            
#> [10] "markov_expanded_vectorisesmp"         
#> [11] "markov_rcpp"                          
#> [12] "markov_reduced_dimensions"            
#> [13] "markov_vectorisetx"                   
#> [14] "markov_vectorisetxsmp"

func_calls <- lapply(function_names, function(func) call(func))

output <- lapply(function_names, function(func) {
  func_call <- call(func)
  print(func_call)
  out <- system.time(eval(func_call))
  print(out)
  out["elapsed"]
})
#> markov()
#>    user  system elapsed 
#>   8.653   0.056   8.709 
#> markov_expanded()
#>    user  system elapsed 
#>  17.676   0.264  17.942 
#> markov_expanded_lapply()
#>    user  system elapsed 
#>  12.713   0.368  13.082 
#> markov_expanded_lapply_rcpp()
#>    user  system elapsed 
#>   6.621   0.452   7.074 
#> markov_expanded_lapply_vectorise()
#>    user  system elapsed 
#>  11.196   0.464  11.660 
#> markov_expanded_parallisesmp_foreach()
#>    user  system elapsed 
#>   4.969   0.405   9.994 
#> markov_expanded_parallisesmp_furrr()
#> 
#> Attaching package: 'purrr'
#> The following object is masked from 'package:magrittr':
#> 
#>     set_names
#>    user  system elapsed 
#>   5.733   0.104   5.836 
#> markov_expanded_parallisesmp_mclapply()
#>    user  system elapsed 
#>  10.247   0.696   5.838 
#> markov_expanded_vectorise()
#>    user  system elapsed 
#>  13.784   0.356  14.140 
#> markov_expanded_vectorisesmp()
#>    user  system elapsed 
#>   3.764   0.000   3.764 
#> markov_rcpp()
#>    user  system elapsed 
#>   1.095   0.000   1.095 
#> markov_reduced_dimensions()
#>    user  system elapsed 
#>   4.733   0.000   4.733 
#> markov_vectorisetx()
#>    user  system elapsed 
#>   3.333   0.000   3.333 
#> markov_vectorisetxsmp()
#>    user  system elapsed 
#>   3.558   0.000   3.557
names(output) <- function_names

Benchmarking

output_df <- output %>%
  unlist(recursive = FALSE) %>%
  enframe()
output_df
#> # A tibble: 14 x 2
#>    name                                          value
#>    <chr>                                         <dbl>
#>  1 markov.elapsed                                 8.71
#>  2 markov_expanded.elapsed                       17.9 
#>  3 markov_expanded_lapply.elapsed                13.1 
#>  4 markov_expanded_lapply_rcpp.elapsed            7.07
#>  5 markov_expanded_lapply_vectorise.elapsed      11.7 
#>  6 markov_expanded_parallisesmp_foreach.elapsed   9.99
#>  7 markov_expanded_parallisesmp_furrr.elapsed     5.84
#>  8 markov_expanded_parallisesmp_mclapply.elapsed  5.84
#>  9 markov_expanded_vectorise.elapsed             14.1 
#> 10 markov_expanded_vectorisesmp.elapsed           3.76
#> 11 markov_rcpp.elapsed                            1.09
#> 12 markov_reduced_dimensions.elapsed              4.73
#> 13 markov_vectorisetx.elapsed                     3.33
#> 14 markov_vectorisetxsmp.elapsed                  3.56