simulate_card_draw <- function() {
  # Create a deck of 52 cards with values
  # deck <- c(rep(2:10, 4), rep(11, 4), rep(12, 4), rep(13, 4), rep(1, 4))
  deck <- rep(1:13, 4)
  
  # Draw 3 cards randomly from the deck
  drawn_cards <- sample(deck, 3, replace = FALSE)
  
  # Find the card with the lowest value
  # min_card <- min(drawn_cards)
  
  # Create a table of card counts to ensure only the drawn cards are removed
  deck_table <- table(deck)
  
  # Remove the drawn cards (decrease the count of each drawn card)
  for (card in drawn_cards) {
    deck_table[as.character(card)] <- deck_table[as.character(card)] - 1
  }
  
  # Create a new deck from the remaining cards (expand the table back into a vector)
  remaining_deck <- as.integer(rep(names(deck_table), deck_table))
  
  # Identify the position of the first occurrence of the min card in drawn cards
  min_card_index <- which.min(drawn_cards)
  
  # Draw a new card to replace the lowest card
  new_card <- sample(remaining_deck, 1)
  
  # Replace the first occurrence of the lowest card with the new card
  drawn_cards[min_card_index] <- new_card
  
  # Return the sum of the values of the 3 cards
  sum(drawn_cards)
}

# Run the simulation
simulate_card_draw()

## [1] 22

#######################################################

set.seed(123)
simulations <- replicate(10^5, simulate_card_draw())
mean(simulations)

## [1] 24.29939

card_draw_A <- function() {
  deck <- rep(1:13, 4)
  drawn_cards <- sample(deck, 3, replace = FALSE)
  new_deck <- deck
  for(cards in drawn_cards){
    index <- which(cards == new_deck)[1]  
    new_deck <- new_deck[-index]
  }
  min_card_index <- which.min(drawn_cards)
  new_card <- sample(new_deck, 1)
  drawn_cards[min_card_index] <- new_card
  sum(drawn_cards)
}

simulations_A <- replicate(10^5, card_draw_A())
mean(simulations_A)

## [1] 24.2906

card_draw_B <- function() {
  deck <- rep(1:13, 4)
  drawn_cards <- sample(deck, 4, replace = FALSE)
  return(sum(drawn_cards) - min(drawn_cards[1:3]))
}

simulations_B <- replicate(10^5, card_draw_B())
mean(simulations_B)

## [1] 24.27267

library(microbenchmark)
set.seed(12345)
comparison <- microbenchmark(simulate_card_draw(),     # povodne
                             card_draw_A(),   # vymyslene na hodine
                             card_draw_B())   # dostala som po hodine
comparison

## Unit: microseconds
##                  expr  min     lq    mean median     uq   max neval
##  simulate_card_draw() 99.8 102.05 110.548 103.80 111.15 247.4   100
##         card_draw_A() 15.1  16.50  17.774  17.55  18.50  26.1   100
##         card_draw_B()  5.6   6.20   6.988   6.70   7.25  16.5   100

boxplot(comparison)