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aoc/year2020/
day14.rs

1//! # Docking Data
2//!
3//! First we parse each mask into 2 `u64` values, `ones` where a bit is set when there is a
4//! corresponding "1" in the mask and `xs` (plural of "x") where a bit is set when there is a
5//! corresponding "X" in the mask. A bit will never be set in the same location in both `ones` and
6//! `xs`. For example:
7//!
8//! ```none
9//!     Mask: 000000000000000000000000000000X1001X
10//!     ones: 000000000000000000000000000000010010
11//!     xs:   000000000000000000000000000000100001
12//! ```
13//!
14//! ## Part One
15//! The memory values are quite sparse, about 500 discrete values in an address range of about 65,000.
16//! This makes a [`FastMap`] a better choice than a large mostly empty array. Storing the correct
17//! value is a straightforward application of the problem rules, expressed as bitwise logic.
18//!
19//! ## Part Two
20//! This part is subtly tricky to solve quickly. The maximum number of Xs in any mask is 9 which
21//! gives 2⁹ = 512 different memory addresses. A brute force solution will work, but there's a much
22//! more elegant approach.
23//!
24//! We treat each address and mask combination as a set. Then by using the
25//! [inclusion-exclusion principle](https://en.wikipedia.org/wiki/Inclusion-exclusion_principle)
26//! we can determine any overlaps with other sets and deduct the correct number of values.
27//!
28//! For example:
29//! ```none
30//!     mask = 0000000000000000000000000000000001XX  // A
31//!     mem[8] = 3
32//!     mask = 00000000000000000000000000000000011X  // B
33//!     mem[8] = 5
34//!     mask = 000000000000000000000000000000000111  // C
35//!     mem[8] = 7
36//! ```
37//! Results in the following address sets:
38//! ```none
39//!    ┌──────────────┐A            Set A: 12 13 14 15
40//!    │ 12 13        │             Set B: 14 15
41//!    │ ┌─────────┐B │             Set C: 15
42//!    │ │ 14      │  │
43//!    │ │ ┌────┐C │  │
44//!    │ │ │ 15 │  │  │
45//!    │ │ └────┘  │  │
46//!    │ └─────────┘  │
47//!    └──────────────┘
48//! ```
49//!
50//! Using the inclusion-exclusion principle the remaining size of A is:
51//! 4 (initial size) - 2 (overlap with B) - 1 (overlap with C) + 1 (overlap between B and C) = 2
52//! If there were any quadruple overlaps we would add those, subtract quintuple, and so on until
53//! there are no more overlaps remaining.
54//!
55//! To calculate the final answer we treat the value as the weight of the set, in this case:
56//! 2 × 3 + 1 × 5 + 1 × 7 = 18
57//!
58//! The complexity of this approach depends on how many addresses overlap. In my input most
59//! addresses overlapped with zero others, a few with one and rarely with more than one.
60//! Benchmarking against the brute force solution showed that this approach is ~90x faster.
61//!
62//! [`FastMap`]: crate::util::hash
63use crate::util::hash::*;
64use crate::util::parse::*;
65
66#[derive(Copy, Clone)]
67pub enum Instruction {
68    Mask { ones: u64, xs: u64 },
69    Mem { address: u64, value: u64 },
70}
71
72impl Instruction {
73    fn mask(pattern: &str) -> Instruction {
74        let (ones, xs) = pattern.bytes().fold((0, 0), |(ones, xs), b| {
75            ((ones << 1) | (b == b'1') as u64, (xs << 1) | (b == b'X') as u64)
76        });
77        Self::Mask { ones, xs }
78    }
79}
80
81struct Set {
82    ones: u64,
83    floating: u64,
84    weight: u64,
85}
86
87impl Set {
88    /// The one bits are from the original address, plus any from the mask, less any that
89    /// overlap with Xs.
90    fn new(address: u64, value: u64, ones: u64, floating: u64) -> Set {
91        Set { ones: (address | ones) & !floating, floating, weight: value }
92    }
93
94    /// Sets are disjoint if any 2 one bits are different and there is no X in either set.
95    ///
96    /// The intersection of two masks looks like:
97    /// ```none
98    ///     First:  0011XXX
99    ///     Second: 0X1X01X
100    ///     Result: 001101X
101    /// ```
102    fn intersect(&self, other: &Set) -> Option<Set> {
103        let disjoint = (self.ones ^ other.ones) & !(self.floating | other.floating);
104
105        (disjoint == 0).then_some(Set {
106            ones: self.ones | other.ones,
107            floating: self.floating & other.floating,
108            weight: 0,
109        })
110    }
111
112    fn size(&self) -> i64 {
113        1 << self.floating.count_ones()
114    }
115}
116
117pub fn parse(input: &str) -> Vec<Instruction> {
118    input
119        .lines()
120        .map(|line| {
121            if line.starts_with("mask") {
122                Instruction::mask(&line[7..])
123            } else {
124                let (address, value) = line[4..].split_once("] = ").unwrap();
125                Instruction::Mem { address: address.unsigned(), value: value.unsigned() }
126            }
127        })
128        .collect()
129}
130
131pub fn part1(input: &[Instruction]) -> u64 {
132    let mut set = 0;
133    let mut keep = 0;
134    let mut memory = FastMap::new();
135
136    for &instruction in input {
137        match instruction {
138            Instruction::Mask { ones, xs } => {
139                set = ones;
140                keep = ones | xs;
141            }
142            Instruction::Mem { address, value } => {
143                memory.insert(address, (value | set) & keep);
144            }
145        }
146    }
147
148    memory.values().sum()
149}
150
151pub fn part2(input: &[Instruction]) -> u64 {
152    let mut ones = 0;
153    let mut floating = 0;
154    let mut sets = Vec::new();
155
156    for &instruction in input {
157        match instruction {
158            Instruction::Mask { ones: next_ones, xs } => {
159                ones = next_ones;
160                floating = xs;
161            }
162            Instruction::Mem { address, value } => {
163                sets.push(Set::new(address, value, ones, floating));
164            }
165        }
166    }
167
168    let mut total = 0;
169    let mut candidates = Vec::new();
170
171    for (i, set) in sets.iter().enumerate() {
172        candidates.extend(sets[(i + 1)..].iter().filter_map(|other| set.intersect(other)));
173
174        let size = set.size() + subsets(set, -1, &candidates);
175
176        total += size as u64 * set.weight;
177        candidates.clear();
178    }
179
180    total
181}
182
183fn subsets(cube: &Set, sign: i64, candidates: &[Set]) -> i64 {
184    let mut total = 0;
185
186    for (i, other) in candidates.iter().enumerate() {
187        if let Some(next) = cube.intersect(other) {
188            total += sign * next.size() + subsets(&next, -sign, &candidates[(i + 1)..]);
189        }
190    }
191
192    total
193}