2025: d09: ex2: add solution

2025/d08/ex1/ex1.py

@@ -0,0 +1,116 @@
+#!/usr/bin/env python
+
+import collections
+import itertools
+import math
+import sys
+from collections.abc import Iterable
+from typing import Generic, Hashable, NamedTuple, TypeVar
+
+
+class Point(NamedTuple):
+    x: int
+    y: int
+    z: int
+
+
+class UnionFind:
+    _parent: list[int]
+    _rank: list[int]
+
+    def __init__(self, size: int):
+        # Each node is in its own set, making it its own parent...
+        self._parent = list(range(size))
+        # ... And its rank 0
+        self._rank = [0] * size
+
+    def find(self, elem: int) -> int:
+        while (parent := self._parent[elem]) != elem:
+            # Replace each parent link by a link to the grand-parent
+            elem, self._parent[elem] = parent, self._parent[parent]
+        return elem
+
+    def union(self, lhs: int, rhs: int) -> int:
+        lhs = self.find(lhs)
+        rhs = self.find(rhs)
+        # Bail out early if they already belong to the same set
+        if lhs == rhs:
+            return lhs
+        # Always keep `lhs` as the taller tree
+        if self._rank[lhs] < self._rank[rhs]:
+            lhs, rhs = rhs, lhs
+        # Merge the smaller tree into the taller one
+        self._parent[rhs] = lhs
+        # Update the rank when merging trees of approximately the same size
+        if self._rank[lhs] == self._rank[rhs]:
+            self._rank[lhs] += 1
+        return lhs
+
+    def sets(self) -> dict[int, set[int]]:
+        res: dict[int, set[int]] = collections.defaultdict(set)
+        for elem in range(len(self._parent)):
+            res[self.find(elem)].add(elem)
+        return dict(res)
+
+
+# PEP 695 still not supported by MyPy...
+T = TypeVar("T", bound=Hashable)
+
+
+class DisjointSet(Generic[T]):
+    _values: list[T]
+    _to_index: dict[T, int]
+    _sets: UnionFind
+
+    def __init__(self, values: Iterable[T]) -> None:
+        self._values = list(values)
+        self._to_index = {v: i for i, v in enumerate(self._values)}
+        self._sets = UnionFind(len(self._values))
+
+    def find(self, elem: T) -> T:
+        return self._values[self._sets.find(self._to_index[elem])]
+
+    def union(self, lhs: T, rhs: T) -> T:
+        return self._values[self._sets.union(self._to_index[lhs], self._to_index[rhs])]
+
+    def sets(self) -> dict[T, set[T]]:
+        sets = self._sets.sets()
+        return {
+            self._values[r]: {self._values[i] for i in values}
+            for r, values in sets.items()
+        }
+
+
+def solve(input: list[str]) -> int:
+    def parse(input: list[str]) -> list[Point]:
+        return [Point(*map(int, line.split(","))) for line in input]
+
+    def sq_dist(p: Point, other: Point) -> int:
+        return sum(abs(a - b) ** 2 for a, b in zip(p, other))
+
+    def list_connections(boxes: list[Point]) -> list[tuple[Point, Point]]:
+        connections = itertools.combinations(boxes, 2)
+        return sorted(connections, key=lambda con: sq_dist(*con))
+
+    def connect_boxes(boxes: list[Point], n: int = 1000) -> DisjointSet[Point]:
+        connections = list_connections(boxes)
+        sets = DisjointSet(boxes)
+        for a, b in connections[:n]:
+            sets.union(a, b)
+        return sets
+
+    boxes = parse(input)
+    connected = connect_boxes(boxes)
+    circuit_sizes = collections.Counter(
+        {r: len(val) for r, val in connected.sets().items()}
+    )
+    return math.prod(size for _, size in circuit_sizes.most_common(3))
+
+
+def main() -> None:
+    input = sys.stdin.read().splitlines()
+    print(solve(input))
+
+
+if __name__ == "__main__":
+    main()

2025/d08/ex2/ex2.py

@@ -0,0 +1,108 @@
+#!/usr/bin/env python
+
+import collections
+import itertools
+import sys
+from collections.abc import Iterable
+from typing import Generic, Hashable, NamedTuple, TypeVar
+
+
+class Point(NamedTuple):
+    x: int
+    y: int
+    z: int
+
+
+class UnionFind:
+    _parent: list[int]
+    _rank: list[int]
+
+    def __init__(self, size: int):
+        self._parent = list(range(size))
+        self._rank = [0] * size
+
+    def find(self, elem: int) -> int:
+        while (parent := self._parent[elem]) != elem:
+            elem, self._parent[elem] = parent, self._parent[parent]
+        return elem
+
+    def union(self, lhs: int, rhs: int) -> bool:
+        lhs = self.find(lhs)
+        rhs = self.find(rhs)
+        if lhs == rhs:
+            return False
+        if self._rank[lhs] < self._rank[rhs]:
+            lhs, rhs = rhs, lhs
+        self._parent[rhs] = lhs
+        if self._rank[lhs] == self._rank[rhs]:
+            self._rank[lhs] += 1
+        return True
+
+    def sets(self) -> dict[int, set[int]]:
+        res: dict[int, set[int]] = collections.defaultdict(set)
+        for elem in range(len(self._parent)):
+            res[self.find(elem)].add(elem)
+        return dict(res)
+
+
+# PEP 695 still not supported by MyPy...
+T = TypeVar("T", bound=Hashable)
+
+
+class DisjointSet(Generic[T]):
+    _values: list[T]
+    _to_index: dict[T, int]
+    _sets: UnionFind
+
+    def __init__(self, values: Iterable[T]) -> None:
+        self._values = list(values)
+        self._to_index = {v: i for i, v in enumerate(self._values)}
+        self._sets = UnionFind(len(self._values))
+
+    def find(self, elem: T) -> T:
+        return self._values[self._sets.find(self._to_index[elem])]
+
+    def union(self, lhs: T, rhs: T) -> bool:
+        return self._sets.union(self._to_index[lhs], self._to_index[rhs])
+
+    def sets(self) -> dict[T, set[T]]:
+        sets = self._sets.sets()
+        return {
+            self._values[r]: {self._values[i] for i in values}
+            for r, values in sets.items()
+        }
+
+
+def solve(input: list[str]) -> int:
+    def parse(input: list[str]) -> list[Point]:
+        return [Point(*map(int, line.split(","))) for line in input]
+
+    def sq_dist(p: Point, other: Point) -> int:
+        return sum(abs(a - b) ** 2 for a, b in zip(p, other))
+
+    def list_connections(boxes: list[Point]) -> list[tuple[Point, Point]]:
+        connections = itertools.combinations(boxes, 2)
+        return sorted(connections, key=lambda con: sq_dist(*con))
+
+    def connect_boxes(boxes: list[Point]) -> tuple[Point, Point]:
+        connections = list_connections(boxes)
+        sets = DisjointSet(boxes)
+        num_sets = len(boxes)
+        for a, b in connections:
+            num_sets -= sets.union(a, b)
+            if num_sets == 1:
+                return a, b
+        assert False
+
+    boxes = parse(input)
+    last_connection = connect_boxes(boxes)
+    return last_connection[0].x * last_connection[1].x
+
+
+def main() -> None:
+    input = sys.stdin.read().splitlines()
+    print(solve(input))
+
+
+if __name__ == "__main__":
+    main()

2025/d09/ex1/ex1.py

@@ -0,0 +1,32 @@
+#!/usr/bin/env python
+
+import itertools
+import sys
+from typing import NamedTuple
+
+
+class Point(NamedTuple):
+    x: int
+    y: int
+
+
+def solve(input: list[str]) -> int:
+    def parse(input: list[str]) -> list[Point]:
+        return [Point(*map(int, line.split(","))) for line in input]
+
+    def rectangle_area(p: Point, other: Point) -> int:
+        dx = abs(p.x - other.x)
+        dy = abs(p.y - other.y)
+        return (dx + 1) * (dy + 1)
+
+    tiles = parse(input)
+    return max(rectangle_area(a, b) for a, b in itertools.combinations(tiles, 2))
+
+
+def main() -> None:
+    input = sys.stdin.read().splitlines()
+    print(solve(input))
+
+
+if __name__ == "__main__":
+    main()

2025/d09/ex1/input

@@ -0,0 +1,496 @@
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2025/d09/ex2/ex2.py

@@ -0,0 +1,149 @@
+#!/usr/bin/env python
+
+import itertools
+import sys
+from collections.abc import Iterator
+from typing import NamedTuple
+
+
+class Point(NamedTuple):
+    x: int
+    y: int
+
+
+def solve(input: list[str]) -> int:
+    def parse(input: list[str]) -> list[Point]:
+        return [Point(*map(int, line.split(","))) for line in input]
+
+    def compression_mapping(points: list[Point]) -> dict[Point, Point]:
+        def compress_1d(values: set[int]) -> dict[int, int]:
+            return {val: i for i, val in enumerate(sorted(values))}
+
+        xs = compress_1d({p.x for p in points})
+        ys = compress_1d({p.y for p in points})
+        compress = lambda p: Point(xs[p.x], ys[p.y])
+
+        return {p: compress(p) for p in points}
+
+    def line(p1: Point, p2: Point) -> Iterator[Point]:
+        def inclusive_range_any_order(a: int, b: int) -> Iterator[int]:
+            if a < b:
+                yield from range(a, b + 1)
+            else:
+                yield from range(a, b - 1, -1)
+
+        # Hack-ish work-around to avoid infinite loops
+        if p1 == p2:
+            yield p1
+            return
+
+        xs = inclusive_range_any_order(p1.x, p2.x)
+        ys = inclusive_range_any_order(p1.y, p2.y)
+
+        if p1.x == p2.x:
+            xs = itertools.repeat(p1.x)
+
+        if p1.y == p2.y:
+            ys = itertools.repeat(p1.y)
+
+        yield from map(Point._make, zip(xs, ys))
+
+    def draw_edges(tiles: list[Point]) -> set[Point]:
+        # Close the loop by repeating the first vertex at the end
+        vertices = tiles + [tiles[0]]
+        edges = {p for a, b in itertools.pairwise(vertices) for p in line(a, b)}
+        return edges
+
+    def flood_fill(start: Point, points: set[Point]) -> set[Point]:
+        assert start in points  # Sanity check
+        visited: set[Point] = set()
+        stack = [start]
+        while stack:
+            p = stack.pop()
+            visited.add(p)
+            for dx, dy in (
+                (-1, 0),
+                (1, 0),
+                (0, -1),
+                (0, 1),
+            ):
+                n = Point(p.x + dx, p.y + dy)
+                if n in visited:
+                    continue
+                if n not in points:
+                    continue
+                stack.append(n)
+        return visited
+
+    def fill_tiles(tiles: list[Point]) -> set[Point]:
+        # I'm too lazy to find an interior point to flood-fill to the edges from,
+        # instead fill the exterior and invert the set
+        min_x, max_x = min(p.x for p in tiles), max(p.x for p in tiles)
+        min_y, max_y = min(p.y for p in tiles), max(p.y for p in tiles)
+
+        # Keep a border all around to make sure the flood-fill can reach everywhere
+        all_points = {
+            Point(x, y)
+            for x in range(min_x - 1, max_x + 1 + 1)
+            for y in range(min_y - 1, max_y + 1 + 1)
+        }
+
+        edges = draw_edges(tiles)
+
+        # Pick a corner we know for sure won't be in the polygon
+        start = Point(min_x - 1, min_y - 1)
+
+        # Sever the points inside and outside the polygon, then flood-fill exterior
+        exterior = flood_fill(start, all_points - edges)
+
+        # Return interior/edge points by removing everything that is on the exterior
+        return all_points - exterior
+
+    def rectangle_edges(p: Point, other: Point) -> Iterator[Point]:
+        min_x, max_x = min(p.x, other.x), max(p.x, other.x)
+        min_y, max_y = min(p.y, other.y), max(p.y, other.y)
+
+        c1 = Point(min_x, min_y)
+        c2 = Point(max_x, min_y)
+        c3 = Point(max_x, max_y)
+        c4 = Point(min_x, max_y)
+
+        yield from line(c1, c2)
+        yield from line(c2, c3)
+        yield from line(c3, c4)
+        yield from line(c4, c1)
+
+    def rectangle_area(p: Point, other: Point) -> int:
+        dx = abs(p.x - other.x)
+        dy = abs(p.y - other.y)
+        return (dx + 1) * (dy + 1)
+
+    def inscribed_rectangles(tiles: list[Point]) -> Iterator[tuple[Point, Point]]:
+        inside_tiles = fill_tiles(tiles)
+        yield from (
+            (a, b)
+            for a, b in itertools.combinations(tiles, 2)
+            if all(p in inside_tiles for p in rectangle_edges(a, b))
+        )
+
+    def largest_rectangle_area(tiles: list[Point]) -> int:
+        to_compressed = compression_mapping(tiles)
+        decompress = {v: k for k, v in to_compressed.items()}.__getitem__
+        compressed_tiles = [to_compressed[p] for p in tiles]
+        compressed_rectangles = inscribed_rectangles(compressed_tiles)
+        return max(
+            rectangle_area(decompress(a), decompress(b))
+            for a, b in compressed_rectangles
+        )
+
+    tiles = parse(input)
+    return largest_rectangle_area(tiles)
+
+
+def main() -> None:
+    input = sys.stdin.read().splitlines()
+    print(solve(input))
+
+
+if __name__ == "__main__":
+    main()

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