DEV Community

Cover image for AoC Day 3: No Matter How You Slice It
Ryan Palo
Ryan Palo

Posted on

 

AoC Day 3: No Matter How You Slice It

Day three! Our DEV leaderboard is up to 44 people, which is awesome!

Also, check out the much classier cover images for these posts that @aspittel came up with! πŸŽ…πŸ₯‡πŸ’»

Anyways, today's challenge asks us to calculate which cells are or are not overlapped as it gives us a bunch of grid rectangles (x, y, height, width) to plot out.

How did everybody do?

Top comments (42)

Collapse
 
aspittel profile image
Ali Spittel • Edited

Solved last night, refactored this morning! Actually pretty proud of this. Python solution:

import re

with open('input.txt', 'r') as f:
    data = []
    for line in f:
        nums = [int(n) for n in re.findall(r'\d+', line)]
        data.append({'id': nums[0], 'coordinates': [nums[1], nums[2]], 'dimensions': [nums[3], nums[4]]})


def get_coordinates(coordinates, dimensions):
    for x in range(dimensions[0]):
        for y in range(dimensions[1]):
            yield str(x + coordinates[0]) + "," + str(y + coordinates[1])


def get_overlaps(data):
    overlaps = set()
    filled = set()
    for line in data:
        for coord in get_coordinates(line['coordinates'], line['dimensions']):
            if coord in filled:
                overlaps.add(coord)
            else:
                filled.add(coord)
    return overlaps


def no_overlaps(coordinates, dimensions, overlaps):
    for coord in get_coordinates(coordinates, dimensions):
        if coord in overlaps: 
            return False
    return True


def find_no_overlaps(data, overlaps):
    for line in data:
        if no_overlaps(line['coordinates'], line['dimensions'], overlaps):
            return line['id']


overlaps = get_overlaps(data)
# Q1
print(len(overlaps))

# Q2
print(find_no_overlaps(data, overlaps))
Collapse
 
thejessleigh profile image
jess unrein

I love how clean this solution is!

Collapse
 
aspittel profile image
Ali Spittel

Thank you so much -- that means a lot (I've been super sad this morning because somebody was mean about my solution on Twitter).

Thread Thread
 
thejessleigh profile image
jess unrein

πŸ™„People can be the worst sometimes. Sorry you had to deal with that.

Collapse
 
callmetarush profile image
Tarush Nagpal

If someone still doesn't get how to do it, I put up a pretty simple explaination with the code on my repo And here's the matrix that I got!

The matrix

Collapse
 
rpalo profile image
Ryan Palo

Cool visual!

Collapse
 
callmetarush profile image
Tarush Nagpal

Thanks! Love using p5.js

Collapse
 
jbristow profile image
Jon Bristow • Edited

Kotlin Solution

UGH! This one seemed like a reversal, the first part was much harder than the second part.

I started out as I always do when pretending to be a video game developer: swearing loudly because my rectangles were overlapping and I forgot that it's way easier to find out if they're not overlapping.

Then I kept trying to optimize, but that wasn't getting me anywhere. I ended up brute-forcing my way through. This is ugly... maybe 25 seconds to chunk through.

Part 1


typealias Point = Pair<Int, Int>

val Point.x get() = first
val Point.y get() = second

private fun String.parseRect(): Rectangle {
    val result = Regex("""#(\d+) @ (\d+),(\d+): (\d+)x(\d+)""").find(this)
    val groups = result!!.groups
    return Rectangle(
        groups[1]!!.value,
        groups[2]!!.value.toInt(),
        groups[3]!!.value.toInt(),
        groups[4]!!.value.toInt(),
        groups[5]!!.value.toInt()
    )
}

class Rectangle(val id: String, val tl: Point, val br: Point) {
    constructor(id: String, x: Int, y: Int, width: Int, height: Int) :
            this(id, x to y, x + width to y + height)
}

private fun Rectangle.overlaps(b: Rectangle) = when {
    this.id == b.id -> false
    b.br.x <= tl.x || b.tl.x >= br.x -> false
    b.br.y <= tl.y || b.tl.y >= br.y -> false
    else -> true
}

fun Rectangle.intersection(b: Rectangle): Set<Point> =
    (max(tl.x, b.tl.x) until min(br.x, b.br.x)).flatMap { x ->
        (max(tl.y, b.tl.y) until min(br.y, b.br.y)).map { y -> x to y }
    }.toSet()

fun answer1(input: List<String>) =
    input
        .cartesian { a, b -> a.parseRect() to b.parseRect() }
        .filter { (a, b) -> a.overlaps(b) }
        .map { (a, b) -> a.intersection(b) }
        .reduce { set, other -> set.union(other) }
        .count()

Part 2

After calming down a little (rectangles are dumb), I set in to work on the second part. This turned out much simpler. It was just another n2 with an early escape function. Almost identical to yesterday. The key is making sure our find eliminates candidates as fast as possible. Enter none, which returns false as soon as we see an overlap with our current. Yes, I was lazy and just added a quick "same id == no overlap" check instead of making sure I was checking unique pairs. I'm getting sleepy, and the first one frustrated me more than I would have liked.

fun answer2(input: List<String>) =
    input.asSequence()
        .map(String::parseRect)
        .let { rects ->
            rects.find { a -> rects.none(a::overlaps) }?.id
        }
Collapse
 
rpalo profile image
Ryan Palo
#rectanglesaredumb
Collapse
 
jbristow profile image
Jon Bristow

From my pain, your gain! An image of the overlapping areas plotted. waste of rectangles

Collapse
 
thejessleigh profile image
jess unrein

I totally agree that the second part seemed so much easier that the first. It really threw me off.

Collapse
 
quoll profile image
Paula Gearon

I initially thought that I should use my data structure from part one to solve part 2, but while figuring it out I realized that a different structure was much more effective. I like to make my functions for the first and second parts independent anyway, so it didn’t bother me to do it again. And it came out much smaller!

Collapse
 
thejessleigh profile image
jess unrein • Edited

My messy af Python solutions. If I’m feeling energetic later today I’ll clean these up and write a Golang solution and benchmark the 2 :)

Part 1:

import re

def claims(input):
    c = input.read().splitlines()
    side = 1000
    matrix = [["O" for x in range(side)] for y in range (side)]
    idx = r'\d*(,)\d*'
    dim = r'\d*(x)\d*'
    cl = r'(#)\d*'
    for claim in c:
        claimant = int(re.search(cl, claim).group(0)[1:])
        inidicies = [int(i) for i in re.search(idx, claim).group(0).split(',')]
        dimensions = [int(i) for i in re.search(dim, claim).group(0).split('x')]
        x = inidicies[0]
        y = inidicies[1]
        width = dimensions[0]
        height = dimensions[1]
        for _ in range(height):
            for _ in range(width):
                space = matrix[y][x]
                if space == "O":
                    matrix[y][x] = claimant
                else:
                    matrix[y][x] = "X"
                x += 1
            x = inidicies[0]
            y += 1
        check_overlap = 0
    for x in matrix:
        check_overlap += x.count("X")

    return check_overlap

print(claims(open('input.txt', 'r')))

Part 2

import re

def claims(input):
    c = input.read().splitlines()
    side = 1000
    matrix = [["O" for x in range(side)] for y in range (side)]
    idx = r'\d*(,)\d*'
    dim = r'\d*(x)\d*'
    cl = r'(#)\d*'
    all_ids = set()
    overlap_ids = set()
    for claim in c:
        claimant = int(re.search(cl, claim).group(0)[1:])
        all_ids.add(claimant)
        inidicies = [int(i) for i in re.search(idx, claim).group(0).split(',')]
        dimensions = [int(i) for i in re.search(dim, claim).group(0).split('x')]
        x = inidicies[0]
        y = inidicies[1]
        width = dimensions[0]
        height = dimensions[1]
        for _ in range(height):
            for _ in range(width):
                space = matrix[y][x]
                if space == "O":
                    # first claim to this space
                    matrix[y][x] = claimant
                elif space == 'X':
                    # claim overlaps with existing overlapped claim
                    overlap_ids.add(claimant)
                else:
                    # claim overlaps with exactly one preexisting claim
                    overlap_ids.add(claimant)
                    overlap_ids.add(space)
                    matrix[y][x] = "X"
                x += 1
            x = inidicies[0]
            y += 1
    return all_ids.difference(overlap_ids)

print(claims(open('input.txt', 'r')))

github.com/thejessleigh/aoc18/tree...

Collapse
 
quoll profile image
Paula Gearon

I saw someone on the Clojurian's Slack talking about AoC day 3, and made the statement "mutable arrays FTW!" This made me think to try using the core.matrix library. I'm always looking for excuses to get better at using that library, since it can give direct GPU access when doing linear algebra.

Part the First

(ns day3
  (:require [clojure.string :refer [split]]
            [clojure.core.matrix :refer :all]))
(set-current-implementation :ndarray)

(defn lines [input-file]
  (split (slurp input-file) #"\n"))

(defn as-long [s] (Long/parseLong s))

(defn destruct [s]
  (let [[all & params] (re-find #"#(\S+) @ (\d+),(\d+): (\d+)x(\d+)" s)]
    (when all (map as-long params))))

(defn star
  [input-file]
  (let [ll (lines input-file)
        field (new-matrix 1000 1000)]
    (loop [[[id col row w h] & xlines] (map destruct ll)]
      (if-not id
        field
        (let [sm (submatrix field row h col w)]
          (emap! #(if (zero? %) id -1) sm)
          (recur xlines))))
    (ereduce + (eq field -1))))

This uses the same lines function as the last 2 days, and as-long is a trivial wrapping of Java interop so I can map it over the numbers found in each line. I could have just mapped an anonymous function, but I just wish Clojure would include as-long/as-double by default, which is why I named it.

My parsing is far more effort than is needed. Someone else pointed out that the regular nature of the input meant that I could just have split the line with: (re-seq #"\d+" s)

I decided to leave mine alone, partly because it's what I came up with, and partly because it's defensive programming. This puzzle is fine, but in the real world my code will one day see a file containing data that breaks simplistic parsing. That's not saying that my code is solid: for instance, I never check if the rectangles are within the 1000x1000 boundaries, but I like to practice at least a little bit of defensive coding.

The loop is destructuring the parse results then iterating until it's done. Then comes the nice part of core.matrix: pulling out a submatrix (the current rectangle) and updating it. The final line uses the nice trick of using eq to represent booleans as 0/1 and adding them. I learnt to count up booleans that way via APL.

Part the Second

(defn star2
  [input-file]
  (let [ll (lines input-file)
        field (new-matrix 1000 1000)]
    (loop [[[id col row w h] & xlines] (map destruct ll) ids #{}]
      (if-not id
        (first ids)
        (let [sm (submatrix field row h col w)
              ids' (ereduce #(if (zero? %2) %1 (disj %1 %2 id)) (conj ids id) sm)]
          (assign! sm id)
          (recur xlines ids'))))))

This part was actually easier, and ran significantly faster!

In an imperative language I would update the elements of the submatrix as I checked for overlaps. I could do that here too, but the code above is just much cleaner.

As it is, it keeps a set of the ids that currently don't overlap. The ereduce step first assumes that the current id won't overlap and adds it to the set. Then it checks if each cell has been written to, and if so it removes from the set the id of that cell, and the id that is being processed right now. Then the assign! updates the whole rectangle with the current id.

I liked using core.matrix here. It forced me to go through the docs to look for useful functions (like eq), and I also learnt some interesting gotchas with the library, which will be valuable to know.

Collapse
 
rpalo profile image
Ryan Palo

Part 1

I really struggled with part 1. Not because I couldn't figure out the problem, or get my code to compile. I had my tests running pretty quickly! But I kept getting the wrong answer! I was on the very precipice of giving up and checking the subreddit when I realized that str.matches(|c| c.is_digit(10)) only finds single digit at a time -- it doesn't build consecutive digits into a single "find." So with input string #1 @ 55,22: 10x10, it was reading this as id: 1, left: 5, top: 5, width: 2, height: 2 and throwing away the rest. πŸ’©

After scratching my head and then bringing in my first external dependency ever in Rust (pretty painless, all things considered) things worked out just fine.

Since the dependency I brought in was just a regex crate, which would be built-in in some languages, I figured that was OK. I wasn't bringing in the find-overlapping-squares crate.

Anyhow, here's part 1:

use regex::Regex;
use std::collections::HashMap;

/// An X, Y grid of Santa's fabric that elves can lay claim to
struct Fabric {
    squares: HashMap<(usize, usize), usize>,
}

/// The data for a rectangular claim an elf makes on a section of fabric
struct Claim {
    id: usize,
    left: usize,
    top: usize,
    width: usize,
    height: usize,
}

impl Fabric {
    fn new() -> Self {
        Self { squares: HashMap::new() }
    }

    /// Increments the amount of claims covering each of the cells inside
    /// the rectangle.
    fn claim(&mut self, claim: &Claim) {
        for x in claim.left..(claim.left + claim.width) {
            for y in claim.top..(claim.top + claim.height) {
                if x > 999 || y > 999 {
                    continue;
                }
                *self.squares.entry((x, y)).or_insert(0) += 1;
            }
        }
    }

    /// Counts how many cells have more than one claim on them
    fn count_conflicts(&self) -> usize {
        self.squares.values().filter(|count| **count >= 2).count()
    }

    /// Counts the total squares claimed
    /// 
    /// A helper function I wrote to help with debugging... #didnthelp
    fn total_squares(&self) -> usize {
        self.squares.iter().count()
    }
}



/// Processes a claim string into an actual Claim
/// 
/// claim string pattern is #<id> @ <left>,<top>: <width>x<height>
/// Since all the numbers are disjoint, we can just match all the 
/// separated numbers in order.
fn process_claim(claim_text: &str) -> Claim {
    // This makes it so we only compile the regex once
    lazy_static! {
        static ref claim_re: Regex = Regex::new(r"#(?P<id>\d+) @ (?P<left>\d+),(?P<top>\d+): (?P<width>\d+)x(?P<height>\d+)").unwrap();
    }

    let claim_parts = claim_re.captures(claim_text).unwrap();
    Claim {
        id: claim_parts["id"].parse().unwrap(),
        left: claim_parts["left"].parse().unwrap(),
        top: claim_parts["top"].parse().unwrap(),
        width: claim_parts["width"].parse().unwrap(),
        height: claim_parts["height"].parse().unwrap(),
    }
}

/// Counts the number of squares with more than one claim on them
pub fn count_conflicting_squares(text: &str) -> usize {
    let mut fabric = Fabric::new();

    for line in text.lines() {
        let claim = process_claim(line);
        fabric.claim(&claim);
    }

    fabric.count_conflicts()
}

Part 2

Actually, for part 1, I didn't even keep track of the ID of the claims -- I just threw that data away! And then I read part two and sat there in sadness for a few minutes.

But!

Then I realized that I wouldn't have to come up with an entirely new approach. I could process the claims like normal, and then re-run through the claims and recheck all of their squares, to see if any have all cells with only one claim on them. Yeah, it doubles the run-time, but O(n) is O(n), even if you double it (sort of). Anyways, I'm pretty happy with today's challenge. Especially my top level functions count_conflicting_squares and find_unconflicting_id: I was able to make them abstract enough that they're pretty easy to read and figure out.

impl Fabric {
    /// Checks whether or not a given claim has any overlapping cells
    fn check_overlap(&self, claim: &Claim) -> bool {
        for x in claim.left..(claim.left + claim.width) {
            for y in claim.top..(claim.top + claim.height) {
                if self.squares.get(&(x, y)) != Some(&1) {
                    return true;
                }
            }
        }
        false
    }
}

/// Finds out if a claim in a group of claims doesn't overlap.  Returns
/// the first one that doesn't.
pub fn find_unconflicting_id(text: &str) -> usize {
    let mut fabric = Fabric::new();
    let mut claims: Vec<Claim> = Vec::new();

    // Load all the claims in
    for line in text.lines() {
        let claim = process_claim(line);
        fabric.claim(&claim);
        claims.push(claim);
    }

    // Check them all for overlaps
    for claim in claims {
        if !fabric.check_overlap(&claim) {
            return claim.id;
        }
    }
    return 0;
}
Collapse
 
thejessleigh profile image
jess unrein

I made the exact same mistake with my initial attempt, where I was only grabbing the first digit with my regex. I'm glad it wasn't just me πŸ˜…I was so frustrated because the test input worked, since each number in the test input was only one digit! Sometimes I wish that AoC gave just a little more test data to work with before grabbing your final input.

Collapse
 
rpalo profile image
Ryan Palo

Yes! The first test input kept passing, and then I wrote like 4 or 5 more tests to check different things, and they all passed! But I never checked double-digit numbers. :|

Collapse
 
ikirker profile image
Ian Kirker • Edited

This seemed like a natural job for Fortran!

Part 1

No, really, it has nice array operation and slicing syntax! I've just stretched out a big array, added 1 everywhere there's a claim, and then counted the number of elements where there's an element greater than 1.

program aoc31
      use ISO_FORTRAN_ENV
      implicit none
      integer, dimension(0:1023,0:1023) :: cloth
      logical, dimension(0:1023,0:1023) :: cloth_mask
      integer :: id, cut_x, cut_y, cut_width, cut_height
      integer :: overlaps
      integer :: io_status

      cloth = 0

      io_status = 0

      do
        read (*,*,iostat=io_status) id, cut_x, cut_y, cut_width, cut_height
        if (io_status /= 0) then
          exit
        end if
        cloth(cut_x:cut_x+cut_width-1, cut_y:cut_y+cut_height-1) = &
         cloth(cut_x:cut_x+cut_width-1, cut_y:cut_y+cut_height-1) + 1
      end do

      cloth_mask = (cloth > 1)
      overlaps = count(cloth_mask)

      write(*,*) "Overlaps: ", overlaps
end program aoc31
Part 2

Part 2 was trickier, and I had to use a similar solution to @rpalo , going over each claim again; but then I checked whether the sum of the cut elements was the same as its area to determine whether it was a unique claim. I could have done a similar count-based method to part 1, but I thought of this way first.

program aoc32
      use ISO_FORTRAN_ENV
      implicit none
      integer, dimension(0:1023,0:1023) :: cloth
      logical, dimension(0:1023,0:1023) :: cloth_mask
      integer :: id, cut_x, cut_y, cut_width, cut_height
      integer :: overlaps
      integer :: io_status

      cloth = 0

      io_status = 0

      open (unit=5, file="input.simplified")
      do
        read (5,*,iostat=io_status) id, cut_x, cut_y, cut_width, cut_height
        if (io_status /= 0) then
          exit
        end if
        cloth(cut_x:cut_x+cut_width-1, cut_y:cut_y+cut_height-1) = &
         cloth(cut_x:cut_x+cut_width-1, cut_y:cut_y+cut_height-1) + 1
      end do
      close(5)

      open (unit=5, file="input.simplified")
      do
        read (5,*,iostat=io_status) id, cut_x, cut_y, cut_width, cut_height
        if (io_status /= 0) exit
        if (sum(cloth(cut_x:cut_x+cut_width-1, cut_y:cut_y+cut_height-1)) == &
         cut_width * cut_height) then
         write(*,*) "Unique ID: ", id
         exit
        end if
      end do
      close(5)

end program aoc32

I don't write a lot of Fortran, and peering at about 7 descriptions of how advanced IO worked didn't get me very far, so I used sed to strip out everything that wasn't a number or a space and that made it much more amenable to Fortran's read input preferences.

Collapse
 
rpalo profile image
Ryan Palo

Woah, this is super cool! The right tool for the right job, huh? 😎 thanks for sharing!

Collapse
 
shahor profile image
Shahor

Here goes my Typescript solution:

import Fs from "fs"
import Path from "path"

const input = Fs.readFileSync(Path.join(__dirname, "input.txt"))
    .toString()
    .split("\n")

interface Range {
    start: number
    end: number
}

interface LineProperties {
    id: string
    rows: Range
    columns: Range
}

type ID = string
interface Pixel {
    ids: ID[]
    hasOverlap: boolean
}

type Coordinates = string

let overlaps = 0
const canvas = new Map<Coordinates, Pixel>()
const idsWithOverlappingStatus: Map<string, boolean> = new Map()

function parseLine(line: string): LineProperties {
    const [
        _ = "",
        id = "",
        columnStart = "",
        rowStart = "",
        width = "",
        height = "",
    ] = line.match(/#(\d+) @ (\d+),(\d+): (\d+)x(\d+)/) || []

    return {
        id,
        columns: {
            start: parseInt(columnStart, 10),
            end: parseInt(columnStart, 10) + parseInt(width, 10),
        },
        rows: {
            start: parseInt(rowStart, 10),
            end: parseInt(rowStart, 10) + parseInt(height, 10),
        },
    }
}

input.forEach(line => {
    const lineProperties: LineProperties = parseLine(line)

    idsWithOverlappingStatus.set(lineProperties.id, false)

    for (
        let row = lineProperties.rows.start;
        row < lineProperties.rows.end;
        row++
    ) {
        for (
            let column = lineProperties.columns.start;
            column < lineProperties.columns.end;
            column++
        ) {
            const coordinnates = `${row}x${column}`
            let pixel: Pixel = { ids: [lineProperties.id], hasOverlap: false }

            // not overlapping yet
            if (canvas.has(coordinnates) === false) {
                canvas.set(coordinnates, pixel)
                continue
            }

            pixel = canvas.get(coordinnates) || pixel
            pixel.ids = [...pixel.ids, lineProperties.id]

            canvas.set(coordinnates, pixel)
            // drop it, it has already been counted
            if (pixel.hasOverlap) {
                continue
            }

            overlaps++
            pixel.ids.forEach(id => idsWithOverlappingStatus.set(id, true))
            canvas.set(coordinnates, {
                ...pixel,
                hasOverlap: true,
            })
        }
    }
})

// part 1
console.log(overlaps)

// part 2
for (const [id, overlapping] of idsWithOverlappingStatus) {
    if (overlapping === false) {
        console.log(id)
        break
    }
}
Collapse
 
carlymho profile image
Carly Ho 🌈

PHP

One of those days when there's a big hint in the name, seems like. The slice/splice functions did the heavy lifting on this one.

Part 1:

<?php
$input = file_get_contents($argv[1]);
$claims = explode("\n", trim($input));
$fabric = array_fill(0, 1000, array_fill(0, 1000, 0));
foreach($claims as $claim) {
  preg_match('/\#[0-9]+ \@ ([0-9]+),([0-9]+): ([0-9]+)x([0-9]+)/', $claim, $data);
  $x = intval($data[1]);
  $y = intval($data[2]);
  $w = intval($data[3]);
  $h = intval($data[4]);

  for ($i = $y; $i < $y+$h; $i++) {
    $slice = array_slice($fabric[$i], $x, $w);
    $slice = array_map(function($x) {
      return $x+1;
    }, $slice);
    array_splice($fabric[$i], $x, $w, $slice);
  }
}

$twoplus = 0;

foreach ($fabric as $row) {
  $claimcounts = array_count_values($row);
  foreach ($claimcounts as $val=>$count) {
    if ($val >= 2) {
      $twoplus += $count;
    }
  }
}
echo $twoplus;
die(1);

Part 2:

<?php
$input = file_get_contents($argv[1]);
$claims = explode("\n", trim($input));
$fabric = array_fill(0, 1000, array_fill(0, 1000, 0));
foreach($claims as $j=>$claim) {
  preg_match('/\#([0-9]+) \@ ([0-9]+),([0-9]+): ([0-9]+)x([0-9]+)/', $claim, $data);
  $claims[$j] = $data;
  $c = $data[1];
  $x = intval($data[2]);
  $y = intval($data[3]);
  $w = intval($data[4]);
  $h = intval($data[5]);

  for ($i = $y; $i < $y+$h; $i++) {
    $slice = array_slice($fabric[$i], $x, $w);
    $slice = array_map(function($x) {
      return $x+1;
    }, $slice);
    array_splice($fabric[$i], $x, $w, $slice);
  }
}

foreach ($claims as $claim) {
  $c = $claim[1];
  $x = $claim[2];
  $y = $claim[3];
  $w = $claim[4];
  $h = $claim[5];

  $arr = array();

  for ($i = $y; $i < $y+$h; $i++) {
    $slice = array_slice($fabric[$i], $x, $w);
    array_push($arr, array_product($slice));
  }

  if (array_product($arr) == 1) {
    echo $c;
    break;
  }
}
die(1);
Collapse
 
r0f1 profile image
Florian Rohrer

Part 1

import numpy as np

with open("input.txt") as f:
    claims = []
    for line in f:
        _, _, coords, dim = line.split()
        x, y = coords.split(",")[0], coords.split(",")[1][:-1]
        a, b = dim.split("x")
        claims.append((int(x), int(y), int(a), int(b)))

max_x = max(t[0]+t[2]+1 for t in claims)
max_y = max(t[1]+t[3]+1 for t in claims)

fabric = np.zeros((max_x, max_y), dtype=int)
for x, y, a, b in claims:
    fabric[x:x+a, y:y+b] += 1

print(len(fabric[fabric > 1]))

Part 2

candidates = set(list(range(len(claims))))

fabric = np.zeros((max_x, max_y), dtype=int)
for i, (x, y, a, b) in enumerate(claims):
    f = fabric[x:x+a, y:y+b]
    uniques = np.unique(f)
    if list(uniques) != [0]:
        for u in uniques:
            candidates.discard(u)
        candidates.discard(i)
    fabric[x:x+a, y:y+b] = i

print(candidates.pop()+1)
Collapse
 
niorad profile image
Antonio Radovcic • Edited

My solution (Elixir) for the first part was:

  • Make a list of every data-point's coords and size [((x,y), (w,h)), ...]
  • Transform each entry to a list of coords (all coords of this rect) [(x,y), ...], so now I have a list of lists with w * h coordinate-pairs
  • Concatenate all lists into one, so now I have a huge list of every occupied field.
  • Count every coordinate in a map, %{(x,y) => count, (x,y) => count, ...}
  • Throw out every entry where count < 2
  • Count entries in resulting list

Takes about a second. The first version used lists and list-diffing to find duplicates, but this took minutes to compute. Maps were much faster at this size (hundeds of thousands of entries).

I should mention I'm just learning Elixir, so this is not to be understood as "good code" or "knows what he's doing".

Here's the code:

defmodule Ac3 do
  def doit do
    filly =
      getFilledList()
      |> Enum.reduce(%{}, &count/2)

    :maps.filter(fn _, v -> v != 0 end, filly)
    |> Enum.reduce(0, fn i, acc -> acc + 1 end)
    |> IO.inspect()
  end

  def count(item, acc) do
    acc
    |> Map.update(item, 0, &(&1 + 1))
  end

  def getFilledList() do
    File.stream!("input.txt")
    |> Enum.to_list()
    |> Enum.map(&String.trim_trailing/1)
    |> Enum.map(&parse/1)
    |> Enum.map(&to_coords/1)
    |> Enum.reduce([], fn i, acc -> i ++ acc end)
  end

  def to_coords(unit) do
    x = elem(elem(unit, 0), 0)
    y = elem(elem(unit, 0), 1)
    x2 = x + elem(elem(unit, 1), 0) - 1
    y2 = y + elem(elem(unit, 1), 1) - 1
    fill(x, y, x, y, x2, y2)
  end

  def fill(x, y, _x1, _y1, x2, y2) when x === x2 and y === y2 do
    [{x, y}]
  end

  def fill(x, y, x1, y1, x2, y2) when x < x2 do
    [{x, y} | fill(x + 1, y, x1, y1, x2, y2)]
  end

  def fill(x, y, x1, y1, x2, y2) when x === x2 do
    [{x, y} | fill(x1, y + 1, x1, y1, x2, y2)]
  end

  def parse(str) do
    {
      unwrap(Enum.at(split(str), 3)),
      unwrap(Enum.at(split(str), 5))
    }
  end

  def split(str) do
    String.split(str, [" ", ":", "#"])
  end

  def unwrap(str) do
    {
      str
      |> String.split([",", "x"])
      |> Enum.at(0)
      |> String.to_integer(),
      str
      |> String.split([",", "x"])
      |> Enum.at(1)
      |> String.to_integer()
    }
  end
end

Ac3.doit()

Collapse
 
rpalo profile image
Ryan Palo

Cool! Thanks for sharing!

Just a heads up, you can put the word β€œelixir” immediately after the opening triple backtick, and your code will show up with syntax highlighting. 😁

Collapse
 
yordiverkroost profile image
Yordi Verkroost • Edited

Solution in Elixir below.

It took me a while to figure out the best way to store the fabric because matrices are not really a thing in Elixir. And it's a bit harder for me (coming from an OOP background), as everything is immutable in a functional language like Elixir. A mindset switch is necessary sometimes.

Part one:


defmodule AoC.DayThree.PartOne do
  alias AoC.DayThree.Common

  def main() do
    "lib/day3/input.txt"
    |> Common.read_input()
    |> Common.parse_into_structs()
    |> Common.get_fabric()
    |> Enum.filter(fn {_key, value} -> value > 1 end)
    |> Enum.count()
  end
end

Part two:

defmodule AoC.DayThree.PartTwo do
  alias AoC.DayThree.Common

  def main() do
    claims =
      "lib/day3/input.txt"
      |> Common.read_input()
      |> Common.parse_into_structs()

    fabric = Common.get_fabric(claims)
    find_non_overlapping_claim(fabric, claims)
  end

  defp find_non_overlapping_claim(fabric, claims) do
    Enum.reduce_while(claims, false, fn claim, _ ->
      result_columns =
        Enum.reduce_while((claim.left + 1)..(claim.left + claim.columns), false, fn x, _ ->
          result_rows =
            Enum.reduce_while((claim.top + 1)..(claim.top + claim.rows), false, fn y, _ ->
              if Map.get(fabric, {x, y}) > 1, do: {:halt, false}, else: {:cont, true}
            end)

          if result_rows, do: {:cont, true}, else: {:halt, false}
        end)

      if result_columns, do: {:halt, claim.id}, else: {:cont, false}
    end)
  end
end

Common:

defmodule AoC.DayThree.Common do
  alias AoC.DayThree.Claim

  def read_input(path) do
    path
    |> File.stream!()
    |> Stream.map(&String.trim_trailing/1)
    |> Enum.to_list()
  end

  def get_fabric(claims) do
    Enum.reduce(claims, %{}, fn claim, map ->
      Enum.reduce((claim.left + 1)..(claim.left + claim.columns), map, fn x, acc_x ->
        Enum.reduce((claim.top + 1)..(claim.top + claim.rows), acc_x, fn y, acc_y ->
          Map.update(acc_y, {x, y}, 1, &(&1 + 1))
        end)
      end)
    end)
  end

  def parse_into_structs(input) do
    input
    |> Enum.map(&parse_struct/1)
  end

  defp parse_struct(input) do
    [id, rest] = String.split(input, "@")
    [location, dimension] = String.split(rest, ":")
    [left, top] = String.split(location, ",")
    [columns, rows] = String.split(dimension, "x")

    id =
      id
      |> String.trim("#")
      |> to_integer()

    left =
      left
      |> to_integer()

    top =
      top
      |> to_integer()

    columns =
      columns
      |> to_integer()

    rows =
      rows
      |> to_integer()

    %Claim{id: id, left: left, top: top, columns: columns, rows: rows}
  end

  defp to_integer(input) do
    input
    |> String.trim()
    |> String.to_integer()
  end
end
Collapse
 
rpalo profile image
Ryan Palo

Wow, nice! Elixir really does seem like a big brain shift.

Collapse
 
deciduously profile image
Ben Lovy • Edited

F# again - I think I really like this language.

namespace Day3
open System.Text.RegularExpressions

module util =
  // cell contents are a list of ClaimIds
  let grid size = Array2D.create size size []

  let claimRegex = @"#(?<ClaimNum>[0-9]+) @ (?<xCoord>[0-9]+),(?<yCoord>[0-9]+): (?<rows>[0-9]+)x(?<columns>[0-9]+)"

  let fallsInClaim claimX claimY rows columns gridX gridY =
    (gridX >= claimX && gridX < rows + claimX) && (gridY >= claimY && gridY < columns + claimY)

  // Given a claim string and a grid, return a new grid with the claims added
  let claim s g =
    let matches = Regex.Match(s, claimRegex)
    if matches.Success then
      let claimNum = matches.Groups.["ClaimNum"].Value |> System.Convert.ToInt32
      let claimX = matches.Groups.["xCoord"].Value |> System.Convert.ToInt32
      let claimY = matches.Groups.["yCoord"].Value |> System.Convert.ToInt32
      let rows = matches.Groups.["rows"].Value |> System.Convert.ToInt32
      let columns = matches.Groups.["columns"].Value |> System.Convert.ToInt32
      Array2D.mapi (fun i j cell -> if fallsInClaim claimX claimY rows columns i j then cell @ [claimNum] else cell) g
    else
      g

  let readClaims fileName =
    System.IO.File.ReadLines(fileName) |> List.ofSeq

  let applyClaims fileName =
    let g = grid 1000
    let claims = readClaims fileName
    List.fold (fun accGrid c -> claim c accGrid) g claims
    |> Seq.cast<int list>

module part1 =
  let execute fileName =
    util.applyClaims fileName
    |> Seq.filter (fun el -> List.length el > 1)
    |> Seq.length

module part2 =
  // check if a given claim has any overlaps
  let noOverlaps claim g =
    g |> Seq.filter (fun cell -> List.contains claim cell) |> Seq.forall (fun cell -> List.length cell = 1)

  let execute fileName =
    let claims = util.readClaims fileName
                |> Seq.map (fun el ->
                  let matches = Regex.Match(el, util.claimRegex)
                  matches.Groups.["ClaimNum"].Value |> System.Convert.ToInt32)
                |> List.ofSeq
    let g = util.applyClaims fileName
    List.fold (fun s el -> if noOverlaps el g then s @ [el] else s) [] claims
    |> printfn "%A"
    0

This is very suboptimal - it repeats a ton of work to solve for part two. It applies all the claims and then checks every cell again for every single claim, grabbing cells with no overlaps anywhere in the grid. I'd like to revisit this and see if I can manipulate claims as a whole as opposed to just leaving "claim breadcrumbs" in each cell.

Collapse
 
choroba profile image
E. Choroba

Perl solutions. The first part was easy, just counting how many times each square occurred. The second part was trickier and the naive solution was too slow, so I summoned some regular expressions to help me:

#!/usr/bin/perl
use warnings;
use strict;
use feature qw{ say };

my %grid;
while (<>) {
    my ($x, $y, $w, $h) = /#\d+ @ (\d+),(\d+): (\d+)x(\d+)/;
    for my $j ($y .. $y + $h - 1) {
        for my $i ($x .. $x + $w - 1) {
            ++$grid{"$i $j"};
        }
    }
}

say scalar grep $grid{$_} > 1, keys %grid;
#!/usr/bin/perl
use warnings;
use strict;
use feature qw{ say };

my %grid;
while (<>) {
    my ($id, $x, $y, $w, $h) = /(#\d+) @ (\d+),(\d+): (\d+)x(\d+)/;
    for my $j ($y .. $y + $h - 1) {
        for my $i ($x .. $x + $w - 1) {
            $grid{"$i $j"} .= $id;
        }
    }
}

my $all = join ':', values %grid;
my %uniq;
undef @uniq{ $all =~ /(?:^|:)(#\d+)(?:$|:)/g };
for my $id (keys %uniq) {
    say($id), last if $all !~ /\d$id/ && $all !~ /$id#/;
}
Collapse
 
bjarnemagnussen profile image
Bjarne Magnussen

Puh, that was a tough one for me today. I started out by counting the number of claims for each square on the "canvas" which gave me a correct aswer. However, I later misunderstand part 2 thinking I should find completely unclaimed squares that could be filled out by one claim...

After cheating a little and getting inspirations for solutions I have implemented a Golang solution for today. At least I am happy that I could implement it in Golang without any prior experience using Golang:

Part 1 and 2 together:

package main

import (
    "bufio"
    "fmt"
    "os"
    "regexp"
    "strconv"
)

type coord struct {
    l int
    t int
}

// readLines reads a whole file into memory
// and returns a slice of its lines.
func readLines(path string) ([]string, error) {
    file, err := os.Open(path)
    if err != nil {
        return nil, err
    }
    defer file.Close()

    var lines []string
    scanner := bufio.NewScanner(file)
    for scanner.Scan() {
        lines = append(lines, scanner.Text())
    }
    return lines, scanner.Err()
}

func mapClaims(data []string) (map[coord][]int, map[int][]int) {
    m := make(map[coord][]int)
    claims := make([][]int, len(data))
    overlaps := make(map[int][]int)
    r, _ := regexp.Compile("-?[0-9]+")
    for i, d := range data {
        claimsVal := r.FindAllString(d, -1)
        for _, valStr := range claimsVal {
            val, _ := strconv.Atoi(valStr)
            claims[i] = append(claims[i], val)
        }
        id := claims[i][0]
        startX := claims[i][1]
        startY := claims[i][2]
        width := claims[i][3]
        height := claims[i][4]
        overlaps[id] = []int{}
        for l := startX; l < startX+width; l++ {
            for t := startY; t < startY+height; t++ {
                claimSet := m[coord{l, t}]
                for _, number := range claimSet {
                    overlaps[number] = append(overlaps[number], id)
                    overlaps[id] = append(overlaps[id], number)
                }
                claimSet = append(claimSet, id)
                m[coord{l, t}] = claimSet
            }
        }

    }
    return m, overlaps
}

func main() {
    start := time.Now()
    data, err := readLines("input")
    if err != nil {
        panic(err)
    }

    m, overlaps := mapClaims(data)

    partA := 0
    for _, v := range m {
        if len(v) >= 2 {
            partA++
        }
    }
    fmt.Println(partA)

    partB := []int{}
    for k, v := range overlaps {
        if len(v) == 0 {
            partB = append(partB, k)
        }
    }
    fmt.Println(partB[0])
    elapsed := time.Since(start)
}

Timeless DEV post...

Git Concepts I Wish I Knew Years Ago

The most used technology by developers is not Javascript.

It's not Python or HTML.

It hardly even gets mentioned in interviews or listed as a pre-requisite for jobs.

I'm talking about Git and version control of course.

One does not simply learn git