Assignment 10

due at 23:59 on   +80

Question: Suppose we draw three cards from a shuffled deck of playing cards. What is the probability of getting a straight, a flush, or both?

You should answer this using the probability distribution monad from class on 30 November, save your implementation as a10.hs, and submit it to the dropbox at


In case you’re not familiar, I’ll define all the situations needed here. Playing cards have both a suit and a rank. There are four suits, known as Hearts (\(\heartsuit\)), Spades (\(\spadesuit\)), Clubs (\(\clubsuit\)), and Diamonds (\(\diamondsuit\)). There are thirteen ranks, known as the integers 2 through 10, and then Jack, Queen, King, and Ace. Every combination of suit and rank appears in a deck, so that’s \(4\times13=52\) cards.

When you have a small selection of cards (called a hand), you can recognize patterns in it. A flush means that all the cards in the hand have the same suit. So with three cards, if you drew \(3\heartsuit, 9\heartsuit, A\heartsuit\), that would be a flush. A straight means that all the cards in the hand have consecutive ranks. So with three cards, if you drew \(9\diamondsuit, 10\clubsuit, J\spadesuit\), that would be a straight.

When you draw cards from a deck, you are selecting without replacement. So instead of each draw being an independent probability (one in 52), each draw constrains subsequent ones.

Also, for the purpose of determining straights and flushes, the order in which cards are drawn doesn’t matter. In other words, to get a straight, you don’t need to draw a \(3,4,5\) in that order; you could have drawn \(5,3,4\). It’s still a straight.

We can further illustrate these principles with some numbers. If you were selecting something with a one-in-52 chance, three times independently (with replacement), the probability of any particular outcome would be \({(\frac{1}{52})}^3 = \frac{1}{140,608}\). But since we are not replacing cards into the deck after drawing them, it’s actually \(\frac{1}{52}\times\frac{1}{51}\times\frac{1}{50} = \frac{1}{132,600}\).

Furthermore, since the ordering of the cards you draw isn’t significant, we actually multiply by the number of possible permutations of those three cards. So the chance of any particular set of three cards \(\frac{1}{132,600}\times3! = \frac{1}{132,600}\times6 = \frac{1}{22,100}\).

Implementation tips

You should use custom data types to represent Suit, Rank, and Card. Derive or implement the Show type class to print them. They also should implement Eq and Ord, so you can use them in Set and Map structures.

Create lists of these types, enumerating all of the suits, ranks, and cards:

allSuits :: [Suit]
allRanks :: [Rank]
allCards :: [Card]

Hint: You don’t have to write out 52 different elements for allCards; use a list comprehension! Something like this, assuming your Card type has a Card constructor taking rank and then suit:

allCards = [Card r s | r <- allRanks, s <- allSuits]

So far we’re using lists, but decks and hands are better represented as Set structures. I defined these type aliases – they’re the same thing (a set of cards) but I can use them in signatures to represent which set is the hand vs. the whole deck.

type Deck = S.Set Card
type Hand = S.Set Card

(The S.Set assumes you did import qualified Data.Set as S.) Then you can define the deck as a set and its size will be 52.

deck :: Deck
deck = S.fromList allCards

You can also use S.toList with the oneOf probability operator we defined previously:

ghci> S.size deck
ghci> oneOf (S.toList deck)
Prob {toList = [(Ace of Hearts,1 % 52),(Ace of Clubs,1 % 52),(Ace of
Spades,1 % 52),(Ace of Diamonds,1 % 52),(2 of Hearts,1 % 52),(2 of
Clubs,1 % 52),(2 of Spades,1 % 52),(2 of Diamonds,1 % 52),...
(King of Spades,1 % 52),(King of Diamonds,1 % 52)]}

In the probability distribution, each card is equally likely, with probability \(\frac{1}{52}\).

Central to your calculations will be a definition like this:

drawThreeCards :: Prob Hand

It can use oneOf to draw from the initial deck, and then again to draw from a deck from which the initial card has been removed (S.delete). And then once again. It accumulates the drawn set of cards into a Hand. Use optimize to remove duplicates from the distribution. The result should be triples of cards, each with the probability \(\frac{1}{22,100}\).

ghci> drawThreeCards
Prob {toList = [(fromList [Ace of Hearts,Ace of Clubs,Ace of Spades],1
% 22100),
............lots omitted............
(fromList [King of Clubs,King of Spades,King of Diamonds],1 % 22100)]}

This is a significant amount of computation, and may require a lot of memory, but it was reasonably fast on my laptop. The slowest part is printing out all the results. But whatever you do, don’t try to draw four or more cards! Doing so slowed my computer to a crawl as everything I was doing got swapped out of the main memory. And I killed it before I got a result. This probability monad is flexible, but computing intensive as numbers get large. (It’s basically simulating everything that can happen.)

Now that you’ve got a distribution of all 22,100 three-card hands, you want to look for straights and flushes. I wrote functions with these signatures:

isFlush :: Hand -> Bool
isStraight :: Hand -> Bool

The flush is the easiest. If your Card data type has a selector to extract the suit field (I called mine cardSuit), then you can basically do cardSuit hand. Since the result is a set, each distinct suit in the original hand appears only once. So if the final size of that set is 1, you have a flush! Here’s an illustration in pseudo-interpreter set notation:

  • cardSuit \(\{3\heartsuit,J\diamondsuit,8\clubsuit\}\)\(\{\heartsuit,\diamondsuit,\clubsuit\}\) (not flush)

  • cardSuit \(\{4\heartsuit,A\spadesuit,5\heartsuit\}\)\(\{\heartsuit,\spadesuit\}\) (not flush)

  • cardSuit \(\{2\clubsuit,Q\clubsuit,5\clubsuit\}\)\(\{\clubsuit\}\) (flush!)

Detecting a straight is a little more difficult. You can use cardRank hand to extract only the ranks, and then S.toAscList to put them in ascending order. Then, figure out how to ensure there are three ranks with no gaps.

  • S.toAscList $ cardRank \(\{4\spadesuit,8\spadesuit,5\diamondsuit\}\)[4,5,8] (not a straight)

  • S.toAscList $ cardRank \(\{2\heartsuit,3\clubsuit,2\diamondsuit\}\)[2,3] (not a 3-card straight)

  • S.toAscList $ cardRank \(\{2\heartsuit,4\clubsuit,3\heartsuit\}\)[2,3,4] (straight!)

Finally, I paired these two Boolean results into a custom data type like this:

data Result = Straight | Flush | Both | Neither
  deriving (Show, Eq, Ord)

scoreHand :: Hand -> Result
scoreHand h =
  case (isStraight h, isFlush h) of
    (True, True) -> Both
    (True, False) -> Straight
    (False, True) -> Flush
    (False, False) -> Neither

So you should be able to calculate:

ghci> optimize (scoreHand <$> drawThreeCards)
Prob {toList = [(Straight, XXXXXX),
                (Flush, XXXXXX),
                (Both, XXXXXX),
                (Neither, XXXX)]}

I’m censoring the actual probabilities! What do you get?