# AoC 2022 Day 18: Lavinator

## Part 1

Given a list of 1x1x1 cubes, determine the total surface area of the cubes.

Sweet. Let’s make a Point3D class to match the earlier Point:

/* ----- A 3D version of the point ----- */
#[derive(Copy, Clone, Debug, Eq, PartialEq, Ord, PartialOrd, Hash)]
pub struct Point3D {
pub x: isize,
pub y: isize,
pub z: isize,
}

type Output = Point3D;

fn add(self, rhs: Self) -> Self::Output {
Point3D::new(self.x + rhs.x, self.y + rhs.y, self.z + rhs.z)
}
}

impl Sub for Point3D {
type Output = Point3D;

fn sub(self, rhs: Self) -> Self::Output {
Point3D::new(self.x - rhs.x, self.y - rhs.y, self.z - rhs.z)
}
}

impl Point3D {
pub const UNITS: [Point3D; 6] = [
Point3D { x: -1, y: 0, z: 0 },
Point3D { x: 1, y: 0, z: 0 },
Point3D { x: 0, y: -1, z: 0 },
Point3D { x: 0, y: 1, z: 0 },
Point3D { x: 0, y: 0, z: -1 },
Point3D { x: 0, y: 0, z: 1 },
];

pub fn new(x: isize, y: isize, z: isize) -> Self {
Point3D { x, y, z }
}

pub fn adjacent_to(self, other: Point3D) -> bool {
let delta = self - other;

delta.x == 0 && delta.y == 0 && delta.z.abs() == 1
|| delta.x == 0 && delta.y.abs() == 1 && delta.z == 0
|| delta.x.abs() == 1 && delta.y == 0 && delta.z == 0
}
}


adjacent_to is something we’ll need just for this problem, but let’s go ahead and write it. Point3D::UNITS is the six unit vectors. We’ll use that to get the six cubes that might touch a given cube

Next, a collection struct of Point3D: Point3DCloud:

#[derive(Debug)]
struct Point3DCloud {
points: HashSet<Point3D>,
}

impl Point3DCloud {
fn contains(&self, p: Point3D) -> bool {
self.points.contains(&p)
}
}

impl<I> From<&mut I> for Point3DCloud
where
I: Iterator<Item = String>,
{
fn from(iter: &mut I) -> Self {
Point3DCloud {
points: iter
.map(|line| {
let (x, y, z) = line
.split(',')
.map(|v| v.parse::<isize>().expect("must be numbers"))
.collect_tuple()
.expect("must have three elements");
Point3D::new(x, y, z)
})
.collect::<HashSet<_>>(),
}
}
}


Easy enough, once again HashSet to contain a bunch of points with arbitrary bounds that is quick to check contains.

That should be enough:

fn part1(filename: &Path) -> String {
let cloud = Point3DCloud::from(&mut iter_lines(filename));

cloud
.points
.iter()
.map(|p| {
Point3D::UNITS
.iter()
.map(|s| !cloud.contains(*p + *s))
.filter(|v| *v)
.count()
})
.sum::<usize>()
.to_string()
}


Elegant. Great the point cloud, than for each point, for each side of that point, if the cube to the side of the point is not itself in the cloud, the side counts for surface area.

I’m not sure that was any easier to read than the code honestly. 😄

## Part 2

The collection of points is hollow. Calculate only the external surface area.

Well that’s neat.

To do this, the first thing I want to do is to create a second set of points: external. For this, I want all points that are ‘outside’ of the cloud. To generate this list, I need Point3DCloud::bounds, a bound outside of the bounds, and to flood fill from that point to fill the bounds.

Once I’ve done that, any points in the flood fill are external, so we can use very nearly the same code as above. If for each cube, for each side, if the next cube on that side is external, this is an external surface.

impl Point3DCloud {
fn bounds(&self) -> (Point3D, Point3D) {
let mut min_bound = Point3D::new(isize::MAX, isize::MAX, isize::MAX);
let mut max_bound = Point3D::new(isize::MIN, isize::MIN, isize::MIN);

self.points.iter().for_each(|p| {
min_bound.x = min_bound.x.min(p.x);
min_bound.y = min_bound.y.min(p.y);
min_bound.z = min_bound.z.min(p.z);

max_bound.x = max_bound.x.max(p.x);
max_bound.y = max_bound.y.max(p.y);
max_bound.z = max_bound.z.max(p.z);
});

(min_bound, max_bound)
}
}

fn part2(filename: &Path) -> String {
let cloud = Point3DCloud::from(&mut iter_lines(filename));
let (mut min_bound, mut max_bound) = cloud.bounds();
min_bound = min_bound - Point3D::new(1, 1, 1);
max_bound = max_bound + Point3D::new(1, 1, 1);

// Calculate all cubes within bounds (expand by one) that are 'external'
// Do this by starting in one corner and flood filling from the bounds inwards
let mut external = HashSet::new();

let mut q = VecDeque::new();
q.push_back(min_bound);

while !q.is_empty() {
let p = q.pop_front().unwrap();

// Ignore points we've already explored
if external.contains(&p) {
continue;
}

// Points in the cloud are not external
if cloud.contains(p) {
continue;
}

// Points out of bounds are ignored
if p.x < min_bound.x
|| p.y < min_bound.y
|| p.z < min_bound.z
|| p.x > max_bound.x
|| p.y > max_bound.y
|| p.z > max_bound.z
{
continue;
}

// Otherwise, mark as external
external.insert(p);

// Check all neighbors
Point3D::UNITS.iter().for_each(|s| q.push_back(p + *s));
}

// Any side adjacent to an external cube is external
cloud
.points
.iter()
.map(|p| {
Point3D::UNITS
.iter()
.map(|s| external.contains(&(*p + *s)))
.filter(|v| *v)
.count()
})
.sum::<usize>()
.to_string()
}


The flood fill should be straight forward enough:

• Create a queue of points, seed it with one point you’re flood filling from
• While the queue isn’t empty, take a point:
• If that point is outside of the bounds, skip it
• If that point has already been scanned (it’s in external) skip it
• If that point is in the cloud, it’s not part of the fill, skip it
• Otherwise, add the point to the flood fill and then for each neighbor:
• Add the neighbor to the queue; note: most of these will be skipped and that’s fine, just so long as we don’t oscillate back and forth

And that’s it. Two parts in much less time than Pressurinator.

## Performance

$./target/release/18-lavinator 1 data/18.txt 4548 took 5.440583ms$ ./target/release/18-lavinator 2 data/18.txt

2588
took 6.8895ms


The runtime is completely bounded by the number of points (for part 1) and the bounds of the points (part 2). Since the shape is very roughly a sphere, it’s pretty quick. I really should visualize this one, it’d be neat. Perhaps I’ll come back to it.

Onward!