Optimize ts_brownian_motion()

[spsanderson]

Updated Function:

bm <- function(.time = 100, .num_sims = 10, .delta_time = 1./365, 
               .initial_value = 0, .return_tibble = TRUE){
  
  # Tidyeval ----
  num_sims <- as.numeric(.num_sims)
  t <- as.numeric(.time)
  initial_value <- as.numeric(.initial_value)
  delta_time <- as.numeric(.delta_time)
  return_tibble <- as.logical(.return_tibble)
  
  # Matrix of random draws - one for each simulation
  rand_matrix <- matrix(rnorm(t * num_sims, mean = 0, sd = sqrt(delta_time)),
                        ncol = num_sims, nrow = t)
  colnames(rand_matrix) <- paste0("sim_number ", 1:num_sims)
  
  # Get the Brownian Motion and convert to price paths
  ret <- apply(rbind(rep(initial_value, num_sims), rand_matrix), 2, cumsum)
  
  # Return
  if (return_tibble){
    ret <- ret %>%
      dplyr::as_tibble() %>%
      dplyr::mutate(t = 1:(t+1)) %>%
      dplyr::select(t, dplyr::everything()) %>%
      tidyr::pivot_longer(-t)
  }
  
  return(ret)
}

Examples:

> benchmark(
+   current = {
+     ts_brownian_motion(.num_sims = 500, .time = 100, .delta_time = 1)
+   },
+   new = {
+     bm(.num_sims = 500, .time = 100, .delta_time = 1)
+   },
+   replications = 25,
+   columns = c("test","replications","elapsed","relative","user.self","sys.self"  )
+ ) %>%
+   arrange(relative)
     test replications elapsed relative user.self sys.self
1     new           25    0.49    1.000      0.48     0.00
2 current           25   24.33   49.653     23.83     0.48