Architeuthis

Well my pt1 solution would require something like at least 1.5 petabytes RAM to hold the fully expanded array, so it was back to the drawing board for pt2 😁

Luckily I noticed the numbers produced in every iteration were incredibly repetitive, so I assigned a separate accumulator to each one, and every iteration I only kept the unique numbers and updated the corresponding accumulators with how many times they had appeared, and finally I summed the accumulators.

The most unique numbers in one iteration were 3777, the 75 step execution was basically instant.

edit: other unhinged attempts included building a cache with how many pebbles resulted from a number after x steps that I would start using after reaching the halfway point, so every time I found a cached number I would replace that branch with the final count according to the remaining steps, but I couldn’t think of a way to actually track how many pebbles result downstream from a specific pebble, but at least it got me thinking about tracking something along each pebble.

// F# as usual
// fst and snd are tuple deconstruction helpers

[<TailCall>]
let rec blink (idx:int) (maxIdx:int) (pebbles : (int64*int64) list) =
    if idx = maxIdx
    then pebbles |> List.sumBy snd
    else
        pebbles
        // Expand array
        |> List.collect (fun (pebbleId, pebbleCount) -> 
            let fpb = float pebbleId
            let digitCount = Math.Ceiling(Math.Log(fpb + 1.0,10))      
            match pebbleId with
            | 0L -> [ 1L, pebbleCount ]
            | x when digitCount % 2.0 = 0.0 -> 
                let factor = Math.Pow(10,digitCount/2.0)
                let right = fpb % factor
                let left = (fpb - right) / factor
                [int64 left, pebbleCount; int64 right,pebbleCount]   
            | x -> [ x * 2024L, pebbleCount ])
        // Compress array
        |> List.groupBy fst
        |> List.map (fun (pebbleId, pebbleGroup) -> pebbleId, pebbleGroup |> List.sumBy snd)
        |> blink (idx+1) maxIdx


"./input.example"
|> Common.parse
|> List.map (fun pebble -> pebble,1L)
|> blink 0 25 
|> Global.shouldBe 55312L

"./input.actual"
|> Common.parse
|> List.map (fun pebble -> pebble,1L)
|> blink 0 75 
|> printfn "Pebble count after 75 blinks is %d" 

Yeah basically if you were doing DFS and forgot to check if you’d already visited the next node you were solving for pt2, since the rule about the next node always having a value of +1 compared to the current one was already preventing cyclic paths.

Hardly a groundbreaking implementation but I hadn’t posted actual code in a while so

(* F# - file reading code and other boilerplate omited *)

let mapAllTrails (matrix : int array2d) =
    let rowCount = matrix |> Array2D.length1
    let colCount = matrix |> Array2D.length2

    let rec search (current:int*int) (visited: HashSet<int*int>) (path: (int*int) list) : (int*int) list list= 
        let (row,col) = current
        let currentValue = matrix.[row,col]

        // Remove to solve for 10-2
        visited.Add (row,col) |> ignore

        // If on a 9 return the complete path
        if currentValue = 9 then [List.append path [row,col] ]
        // Otherwise filter for eligible neihboring cells and continue search
        else                    
            [ row-1, col;row, col-1; row, col+1; row+1,col]
            |> List.filter (fun (r,c) -> 
                not (visited.Contains(r,c))
                && r >= 0 && c>=0 && r < rowCount && c < colCount
                && matrix.[r,c]-currentValue = 1 )
            |> List.collect (fun next ->
                [row,col] 
                |> List.append path  
                |> search next visited)

    // Find starting cells, i.e. contain 0
    matrix
    |> Global.matrixIndices
    |> Seq.filter (fun (row,col) -> matrix.[row,col] = 0)
    // Find all trails starting from those cells and flatten the result
    |> Seq.collect (fun trailhead -> search trailhead (HashSet<int*int>()) [])
    

"./input.example"
|> Common.parse 
|> mapAllTrails
|> Seq.length
|> Global.shouldBe 81

"./input.actual"
|> Common.parse 
|> mapAllTrails
|> Seq.length
|> printfn "The sum total of trail rankings is %d"

Used the coordinates of every two same type frequences to create the ilnear equation (y = ax + b) and then fed it all the matrix coordinates to see which belonged to the line. To get the correct number of antinodes I had to check for |y - ax - b| < 0.0001, otherwise I got around 20 too few.

// F#
let isLegit ((total: int64), (calibration : int64 array)) = 

    let rec search (index : int) (acc: int64) =
        let currentValue = calibration.[index]
        
        [Add; Times; Concat] // operators - remove 'Concat' to solve for 7-1
        |> List.exists (fun op -> // List.exists returns true the first time the lambda returns true, so search stops at first true
                match op with // update accumulator
                | Add -> acc + currentValue
                | Times -> acc * currentValue
                | Concat -> int64 (sprintf "%d%d" acc currentValue)
                |> function // stop search on current accumulator value (state) exceeding total, or being just right
                | state when state > total -> false
                | state when state = total && index < (calibration.Length-1) -> false // this was the problem
                | state when state = total && index = (calibration.Length-1) -> true
                | state -> // stop if index exceeds input length, or continue search
                    if index+1 = calibration.Length
                    then false
                    else search (index+1) state
        )
     
    // start search from second element using the first as current sum
    search 1 calibration.[0]

EDIT: total && index < (calibration.Length-1) -> false – i.e. stop if you reach the total before using all numbers, well, also stops you from checking the next operator, So, removing it worked.

Rubber ducking innocent people on the internets works, who knew.