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2023/d25/ex1/ex1.py Executable file
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#!/usr/bin/env python
import copy
import random
import sys
from collections import Counter, defaultdict
from typing import cast
Graph = dict[str, Counter[str]]
def solve(input: list[str]) -> int:
def parse(input: list[str]) -> Graph:
res: Graph = defaultdict(Counter)
for line in input:
node, destinations = line.split(": ")
for dest in destinations.split():
res[node][dest] = 1
res[dest][node] = 1
return res
def contract_edge(graph: Graph, s: str, t: str) -> None:
assert s != t # Sanity check
assert s in graph # Sanity check
assert t in graph # Sanity check
# Merge the edges
graph[s] += graph[t]
# Don't count the potential t-s edge
del graph[s][s]
# Remove t from the graph
for other in graph[t].keys():
del graph[other][t]
del graph[t]
# Update the neighbours values
for other, v in graph[s].items():
graph[other][s] = v
# Stoer-Wagner algorithm
def min_cut_exact(graph: Graph) -> tuple[set[str], set[str]]:
def phase(graph: Graph) -> tuple[str, str, int]:
assert len(graph) >= 2 # Sanity check
candidates = set(graph.keys())
start = candidates.pop()
found = [start]
cut_weight: list[int] = []
while candidates:
(weight, node) = max(
(sum(graph[node][other] for other in found), node)
for node in candidates
)
candidates.discard(node)
found.append(node)
cut_weight.append(weight)
return found[-2], found[-1], cut_weight[-1]
partition: set[str] = set()
g = copy.deepcopy(graph)
# Initialize our best weight/parition
best_weight = cast(int, float("inf"))
best_partition = set(partition)
while len(g) > 1:
s, t, w = phase(g)
partition.add(t)
contract_edge(g, s, t)
if w < best_weight:
best_weight = w
best_partition = set(partition)
return best_partition, graph.keys() - best_partition
def min_cut_karger(graph: Graph, target: int) -> tuple[set[str], set[str]]:
assert len(graph) >= 2 # Sanity check
original_edges = [
(source, dest)
for source, destinations in graph.items()
for dest in destinations
if source < dest
]
while True:
g = copy.deepcopy(graph)
contracted = {v: v for v in graph}
while len(g) > 2:
s, t = (contracted[v] for v in random.choice(original_edges))
if s == t:
continue
contract_edge(g, s, t)
# Hacky union-find-ish algorithm, for laziness
for k, v in contracted.items():
if v != t:
continue
contracted[k] = s
# Pick a partition at random here
node = next(iter(g))
# Check that we met our target
if g[node].total() > target:
continue
partition = {n for n, parent in contracted.items() if parent == node}
return partition, graph.keys() - partition
graph = parse(input)
# The exact algorithm is very slow on big graphs, at which point Karger's algorithm is better
if len(graph) < 100:
left, right = min_cut_exact(graph)
else:
left, right = min_cut_karger(graph, 3)
return len(left) * len(right)
def main() -> None:
input = sys.stdin.read().splitlines()
print(solve(input))
if __name__ == "__main__":
main()

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2023/d25/ex2/ex2.py Executable file
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#!/usr/bin/env python
def main() -> None:
print("There is no part two...")
if __name__ == "__main__":
main()

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