Euler problems/81 to 90

Problem 81

Find the minimal path sum from the top left to the bottom right by moving right and down.

Solution:

import Data.List (unfoldr)

columns s = unfoldr f s
    where
        f [] = Nothing
        f xs = Just $ (\(a,b) -> (read a, drop 1 b)) $ break (==',') xs

firstLine ls = scanl1 (+) ls

nextLine pl [] = pl
nextLine pl (n:nl) = nextLine p' nl
    where
        p' = nextCell (head pl) pl n
        nextCell _ [] [] = []
        nextCell pc (p:pl) (n:nl) = pc' : nextCell pc' pl nl
            where pc' = n + min p pc

minSum (p:nl) = last $ nextLine p' nl
    where
        p' = firstLine p

problem_81 c = minSum $ map columns $ lines c

Problem 82

Find the minimal path sum from the left column to the right column.

Solution:

problem_82 = undefined

Problem 83

Find the minimal path sum from the top left to the bottom right by moving left, right, up, and down.

Solution:

A very verbose solution based on the Dijkstra algorithm. Infinity could be represented by any large value instead of the data type Distance. Also, some equality and ordering tests are not really correct. To be semantically correct, I think infinity == infinity should not be True and infinity > infinity should fail. But for this script's purpose it works like this.

import Array (Array, listArray, bounds, inRange, assocs, (!))
import qualified Data.Map as M (fromList, Map, foldWithKey, lookup, null, delete, insert, empty, update)
import Data.List (unfoldr)
import Control.Monad.State (State, execState, get, put)
import Data.Maybe (fromJust, fromMaybe)

type Weight  = Integer

data Distance = D Weight | Infinity
    deriving (Show)

instance Eq Distance where
    (==) Infinity Infinity = True
    (==) (D a) (D b) = a == b
    (==) _ _ = False

instance Ord Distance where
    compare Infinity Infinity = EQ
    compare Infinity (D _) = GT
    compare (D _) Infinity = LT
    compare (D a) (D b) = compare a b

data (Eq n, Num w) => Arc n w = A {node :: n, weight :: w}
    deriving (Show)

type Index   = (Int, Int)
type NodeMap = M.Map Index Distance
type Matrix  = Array Index Weight
type Path    = Arc Index Weight
type PathMap  = M.Map Index [Path]

data Queues = Q {input :: NodeMap, output :: NodeMap, pathMap :: PathMap}
    deriving (Show)

listToMatrix :: [[Weight]] -> Matrix
listToMatrix xs = listArray ((1,1),(cols,rows)) $ concat $ xs
    where
        cols = length $ head xs
        rows = length xs

directions :: [Index]
directions = [(0,-1), (0,1), (-1,0), (1,0)]

add :: (Num a) => (a, a) -> (a, a) -> (a, a)
add (a,b) (a', b') = (a+a',b+b')

arcs :: Matrix -> Index -> [Path]
arcs a idx = do
    d <- directions
    let n = add idx d
    if (inRange (bounds a) n) then
        return $ A n (a ! n)
        else
            fail "out of bounds"

paths :: Matrix -> PathMap
paths a = M.fromList $ map (\(idx,_) -> (idx, arcs a idx)) $ assocs a

nodes :: Matrix -> NodeMap
nodes a = M.fromList $ (\((i,_):xs) -> (i, D (a ! (1,1))):xs) $ map (\(idx,_) -> (idx, Infinity)) $ assocs a

extractMin :: NodeMap -> (NodeMap, (Index, Distance))
extractMin m = (M.delete (fst minNode) m, minNode)
    where
        minNode = M.foldWithKey mini ((0,0), Infinity) m
        mini i' v' (i,v)
            | v' < v    = (i', v')
            | otherwise = (i,v)

dijkstra :: State Queues ()
dijkstra = do
    Q i o am <- get
    let (i', n) = extractMin i
    let o' = M.insert (fst n) (snd n) o
    let i'' = updateNodes n am i'
    put $ Q i'' o' am
    if M.null i'' then return () else dijkstra

updateNodes :: (Index, Distance) -> PathMap -> NodeMap -> NodeMap
updateNodes (i, D d) am nm = foldr f nm ds
    where
        ds = fromJust $ M.lookup i am
        f :: Path -> NodeMap -> NodeMap
        f (A i' w) m = fromMaybe m val
            where
                val = do
                    v <- M.lookup i' m
                    if (D $ d+w) < v then
                        return $ M.update (const $ Just $ D (d+w)) i' m
                        else return m

shortestPaths :: Matrix -> NodeMap
shortestPaths xs = output $ dijkstra `execState` (Q n M.empty a)
    where
        n = nodes xs
        a = paths xs

problem_83 :: [[Weight]] -> Weight
problem_83 xs = jd $ M.lookup idx $ shortestPaths matrix
    where
        matrix = listToMatrix xs
        idx = snd $ bounds matrix
        jd (Just (D d)) = d

Problem 84

In the game, Monopoly, find the three most popular squares when using two 4-sided dice.

Solution:

problem_84 = undefined

Problem 85

Investigating the number of rectangles in a rectangular grid.

Solution:

problem_85 = undefined

Problem 86

Exploring the shortest path from one corner of a cuboid to another.

Solution:

problem_86 = undefined

Problem 87

Investigating numbers that can be expressed as the sum of a prime square, cube, and fourth power?

Solution:

import List

problem_87 = length expressible
    where limit = 50000000
          squares = takeWhile (<limit) (map (^2) primes)
          cubes   = takeWhile (<limit) (map (^3) primes)
          fourths = takeWhile (<limit) (map (^4) primes)
          choices = [[s,c,f] | s <- squares, c <- cubes, f <- fourths]
          unique  = map head . group . sort
          expressible = filter (<limit) . unique . map sum $ choices

Problem 88

Exploring minimal product-sum numbers for sets of different sizes.

Solution:

problem_88 = undefined

Problem 89

Develop a method to express Roman numerals in minimal form.

Solution:

problem_89 = undefined

Problem 90

An unexpected way of using two cubes to make a square.

Solution:

problem_90 = undefined