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//! # Chronal Coordinates
//!
//! Both parts can be solved with a [BFS](https://en.wikipedia.org/wiki/Breadth-first_search)
//! approach. The bounding box of the coordinates is roughly 300 wide by 300 high so the total
//! complexity would be approximately `O(90,000)`.
//!
//! A much faster approach for both parts is a
//! [sweep line algorithm](https://en.wikipedia.org/wiki/Sweep_line_algorithm). We sweep from
//! top to bottom (minimum y coordinate to maximum y coordinate) computing the area a slice at a
//! time. There are 50 coordinates so the complexity of this approach is much lower at
//! approximately `O(300 * 50) = O(15000)`.
use crate::util::iter::*;
use crate::util::parse::*;
use crate::util::point::*;
pub struct Input {
min_y: i32,
max_y: i32,
points: Vec<Point>,
}
/// Parse points while keeping track of the min and max y coordinates.
pub fn parse(input: &str) -> Input {
let mut min_y = i32::MAX;
let mut max_y = i32::MIN;
let points: Vec<_> = input
.iter_signed()
.chunk::<2>()
.map(|[x, y]| {
min_y = min_y.min(y);
max_y = max_y.max(y);
Point::new(x, y)
})
.collect();
Input { min_y, max_y, points }
}
/// Sweep line approach computing the area of each *finite* coordinate. A coordinate has infinite
/// area if any point on the edge of the bounding box formed by the minimum and maximum x and y
/// coordinates is closest to that coordinate.
///
/// We sort the coordinates in ascending x value then for each row, compare the next coordinate
/// against the head of a stack. This quickly eliminates coordinates that are further away at all
/// points. Interestingly this approach is very similar to the previous [`Day 5`].
///
/// [`Day 5`]: crate::year2018::day05
pub fn part1(input: &Input) -> i32 {
let mut points = input.points.clone();
let mut area = vec![0; points.len()];
let mut finite = vec![true; points.len()];
let mut candidates: Vec<(usize, i32, i32)> = Vec::new();
// Special value for coordinates that are equidistant from nearest neighbour.
let marker = usize::MAX;
// Sorts points left to right so that ranges can be merged.
points.sort_unstable_by_key(|p| p.x);
// Sweep top to bottom.
for row in input.min_y..=input.max_y {
// Left to right.
for (j, &p) in points.iter().enumerate() {
// Manhattan distance is the absolute difference in y coordinates since the x
// coordinate is already identical.
let m1 = (p.y - row).abs();
let x1 = p.x;
loop {
if let Some((i, m0, x0)) = candidates.pop() {
// Compare against the head of the stack.
let delta = m1 - m0;
let width = x1 - x0;
if delta < -width {
// Left coordinate is further away at every points.
// Discard and pop next left coordinate from the stack.
//
// rrrrrrrrrrrrrrrr <-- Considering only this row
// ....R...........
// ................
// ................
// ..L.............
continue;
} else if delta == -width {
// Left coordinate is equal from its center leftwards
// Replace with special marker value.
//
// ...rrrrrrrrrrrrr
// ....R...........
// ................
// ..L.............
candidates.push((marker, m0, x0));
candidates.push((j, m1, x1));
} else if delta == width {
// Right coordinate is equal from its center rightwards.
// Replace with special marker value.
//
// llll............
// ..L.............
// ................
// ....R...........
candidates.push((i, m0, x0));
candidates.push((marker, m1, x1));
} else if delta > width {
// Right coordinate is further away at every point.
// Discard then check next right coordinate from points.
//
// llllllllllllllll
// ..L.............
// ................
// ................
// ....R...........
candidates.push((i, m0, x0));
} else {
// Coordinates split the distance, some points closer to left and others
// closer to right. Add both to candidates.
//
// lllll.rrrrrrrrrr
// .........R......
// ..L.............
// ................
// ................
candidates.push((i, m0, x0));
candidates.push((j, m1, x1));
}
} else {
// Nothing on stack to compare with, push coordinate.
candidates.push((j, m1, x1));
}
break;
}
}
// Any coordinates that are closest to the bounding box edges are infinite.
let left = candidates[0].0;
if left != marker {
finite[left] = false;
}
let right = candidates[candidates.len() - 1].0;
if right != marker {
finite[right] = false;
}
// Only consider finite coordinates.
for window in candidates.windows(3) {
let (_, m0, x0) = window[0];
let (i, m1, x1) = window[1];
let (_, m2, x2) = window[2];
// Skip coordinates where all points are equally distant from their neighbor.
if i != marker {
if row == input.min_y || row == input.max_y {
// All coordinates the are closest to the top or bottom row are infinite.
finite[i] = false;
} else {
// Count points closest to the left, to the right and the coordinate itself.
let left = (x1 - x0 + m0 - m1 - 1) / 2;
let right = (x2 - x1 + m2 - m1 - 1) / 2;
area[i] += left + 1 + right;
}
}
}
candidates.clear();
}
// Find largest area closest to finite coordinate.
(0..points.len()).filter_map(|i| finite[i].then_some(area[i])).max().unwrap()
}
pub fn part2(input: &Input) -> i32 {
part2_testable(input, 10_000)
}
/// Sweep from top to bottom to find the size of the roughly circular area that is less than
/// a specified maximum distance from all other points.
///
/// Finding the center of this circle to act as a starting point is an interesting sub-problem.
/// The two dimensional [geometric median](https://en.wikipedia.org/wiki/Geometric_median) that
/// minimizes the Euclidean distance to all other points has no general closed form formula.
/// The [centroid](https://en.wikipedia.org/wiki/Centroid) is close but not exact as it minimizes
/// the distance *squared*.
///
/// However the Manhattan distance is independent for each axis, so we can instead solve for the
/// one dimensional case. This is the [median](https://en.wikipedia.org/wiki/Median) of each axis.
/// Intuitively this makes sense, as the median has the same number of points on either side,
/// so moving either direction, the increase from half the points is cancelled out by the decrease
/// of the other half of the points.
///
/// The algorithm is:
/// * Find center
/// * Go upwards from center until top edge of circle reached.
/// * For each row of circle, find left and right extents
/// * Add area of row to total, then advance to row below.
pub fn part2_testable(input: &Input, max_distance: i32) -> i32 {
// Sort points in ascending order in order to find median.
let mut xs: Vec<_> = input.points.iter().map(|p| p.x).collect();
xs.sort_unstable();
let mut ys: Vec<_> = input.points.iter().map(|p| p.y).collect();
ys.sort_unstable();
// Find coordinate closest to median point.
let x = xs[xs.len() / 2];
let mut y = ys[ys.len() / 2];
// Calculate minimum distance.
let median = Point::new(x, y);
let mut y_distance: i32 = input.points.iter().map(|o| o.manhattan(median)).sum();
// Find top of region
while y_distance + prev(&ys, y) < max_distance {
y_distance += prev(&ys, y);
y -= 1;
}
let mut left = x;
let mut left_dist = y_distance;
let mut right = x;
let mut right_dist = y_distance;
let mut area = 0;
// Sweep top to bottom.
while y_distance < max_distance {
// Expand moving left edge to the left
while left_dist < max_distance {
left_dist += prev(&xs, left);
left -= 1;
}
// Contract moving left edge to the right
while left_dist >= max_distance {
left_dist += next(&xs, left);
left += 1;
}
// Expand moving right edge to the right
while right_dist < max_distance {
right_dist += next(&xs, right);
right += 1;
}
// Contract moving right edge to the left
while right_dist >= max_distance {
right_dist += prev(&xs, right);
right -= 1;
}
// Move downwards one row.
let next = next(&ys, y);
y_distance += next;
left_dist += next;
right_dist += next;
y += 1;
area += right - left + 1;
}
area
}
/// Calculate the change in distance moving left or up.
fn prev(slice: &[i32], n: i32) -> i32 {
let mut total = 0;
for &s in slice {
if s >= n {
total += 1;
} else {
total -= 1;
}
}
total
}
/// Calculate the change in distance moving down or right.
fn next(slice: &[i32], n: i32) -> i32 {
let mut total = 0;
for &s in slice {
if s <= n {
total += 1;
} else {
total -= 1;
}
}
total
}