GiantTree

joined 6 months ago
[–] [email protected] 3 points 1 day ago

Kotlin

A fun and small challenge. First read all locks, transpose their profile and count the #s (-1 for the full row). Then do the same for the keys.

Lastly find all keys for all locks that do not sum to more than 5 with their teeth:

Code


val lockRegex = Regex("""#{5}(\r?\n[.#]{5}){6}""")
val keyRegex = Regex("""([.#]{5}\r?\n){6}#{5}""")

fun parseLocksAndKeys(inputFile: String): Pair<List<IntArray>, List<IntArray>> {
    val input = readResource(inputFile)
    val locks = lockRegex
        .findAll(input)
        .map {
            it
                .value
                .lines()
                .map { line -> line.toList() }
                .transpose()
                .map { line -> line.count { c -> c == '#' } - 1 }
                .toIntArray()
        }
        .toList()

    val keys = keyRegex
        .findAll(input)
        .map {
            it
                .value
                .lines()
                .map { line -> line.toList() }
                .transpose()
                .map { line -> line.count { c -> c == '#' } - 1 }
                .toIntArray()
        }
        .toList()

    return locks to keys
}

fun part1(inputFile: String): String {
    val (locks, keys) = parseLocksAndKeys(inputFile)

    val matches = locks.map { lock ->
        keys.filter { key ->
            for (i in lock.indices) {
                // Make sure the length of the key and lock do not exceed 5
                if (lock[i] + key[i] > 5) {
                    return@filter false
                }
            }
            true
        }
    }
        .flatten()
        .count()

    return matches.toString()
}

Also on GitHub

[–] [email protected] 2 points 4 days ago

Kotlin

I experimented a lot to improve the runtime and now I am happy with my solution. The JVM doesn't optimize code that quickly :)

I have implemented a few optimizations in regards to transformations so that they use arrays directly (The file with the implementations is here)

Code

class Day22 {

    private fun nextSecretNumber(start: Long): Long {
        // Modulo 2^24 is the same as "and" with 2^24 - 1
        val pruneMask = 16777216L - 1L
        // * 64 is the same as shifting left by 6
        val mul64 = ((start shl 6) xor start) and pruneMask
        // / 32 is the same as shifting right by 5
        val div32 = ((mul64 shr 5) xor mul64) and pruneMask
        // * 2048 is the same as shifting left by 11
        val mul2048 = ((div32 shl 11) xor div32) and pruneMask
        return mul2048
    }

    fun part1(inputFile: String): String {
        val secretNumbers = readResourceLines(inputFile)
            .map { it.toLong() }
            .toLongArray()

        repeat(NUMBERS_PER_DAY) {
            for (i in secretNumbers.indices) {
                secretNumbers[i] = nextSecretNumber(secretNumbers[i])
            }
        }

        return secretNumbers.sum().toString()
    }

    fun part2(inputFile: String): String {
        // There is a different sample input for part 2
        val input = if (inputFile.endsWith("sample")) {
            readResourceLines(inputFile + "2")
        } else {
            readResourceLines(inputFile)
        }
        val buyers = input
            .map {
                LongArray(NUMBERS_PER_DAY + 1).apply {
                    this[0] = it.toLong()
                    for (i in 1..NUMBERS_PER_DAY) {
                        this[i] = nextSecretNumber(this[i - 1])
                    }
                }
            }

        // Calculate the prices and price differences for each buyer.
        // The pairs are the price (the ones digit) and the key/unique value of each sequence of differences
        val differences = buyers
            .map { secretNumbers ->
                // Get the ones digit
                val prices = secretNumbers.mapToIntArray {
                    it.toInt() % 10
                }

                // Get the differences between each number
                val differenceKeys = prices
                    .zipWithNext { a, b -> (b - a) }
                    // Transform the differences to a singular unique value (integer)
                    .mapWindowed(4) { sequence, from, _ ->
                        // Bring each byte from -9 to 9 to 0 to 18, multiply by 19^i and sum
                        // This generates a unique value for each sequence of 4 differences
                        (sequence[from + 0] + 9) +
                                (sequence[from + 1] + 9) * 19 +
                                (sequence[from + 2] + 9) * 361 +
                                (sequence[from + 3] + 9) * 6859
                    }

                // Drop the first 4 prices, as they are not relevant (initial secret number price and 3 next prices)
                prices.dropFromArray(4) to differenceKeys
            }

        // Cache to hold the value/sum of each sequence of 4 differences
        val sequenceCache = IntArray(NUMBER_OF_SEQUENCES)
        val seenSequence = BooleanArray(NUMBER_OF_SEQUENCES)

        // Go through each sequence of differences
        // and get their *first* prices of each sequence.
        // Sum them in the cache.
        for ((prices, priceDifferences) in differences) {
            // Reset the "seen" array
            Arrays.fill(seenSequence, false)
            for (index in priceDifferences.indices) {
                val key = priceDifferences[index]
                if (!seenSequence[key]) {
                    sequenceCache[key] += prices[index]
                    seenSequence[key] = true
                }
            }
        }

        return sequenceCache.max().toString()
    }

    companion object {
        private const val NUMBERS_PER_DAY = 2000

        // 19^4, the differences range from -9 to 9 and the sequences are 4 numbers long
        private const val NUMBER_OF_SEQUENCES = 19 * 19 * 19 * 19
    }
}

[–] [email protected] 19 points 5 days ago (1 children)

Was viele vergessen ist, dass die Cookies im Cookie-Banner nur ein Teil der Rechnung sind.

Üblicherweise stimmt man nämlich zusätzlich der Verarbeitung der personenbezogenen Daten zu, welche fast immer maximal intransparent in Bezug auf die tatsächlich erhobenen Daten und der Verarbeitungen sind. Von den Auswirkungen auf die eigene Person ganz zu schweigen.