Squash-me

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Kerollmops 2020-06-09 17:32:25 +02:00
parent 2a6d6a7f69
commit 5d5b827f1a
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@ -4,6 +4,21 @@ const ONE_ATTRIBUTE: u32 = 1000;
const MAX_INDEX: u32 = ONE_ATTRIBUTE - 1;
const MAX_DISTANCE: u32 = 8;
fn index_proximity(lhs: u32, rhs: u32) -> u32 {
if lhs < rhs {
cmp::min(rhs - lhs, MAX_DISTANCE)
} else {
cmp::min(lhs - rhs, MAX_DISTANCE) + 1
}
}
fn positions_proximity(lhs: u32, rhs: u32) -> u32 {
let (lhs_attr, lhs_index) = extract_position(lhs);
let (rhs_attr, rhs_index) = extract_position(rhs);
if lhs_attr != rhs_attr { MAX_DISTANCE }
else { index_proximity(lhs_index, rhs_index) }
}
// Returns the attribute and index parts.
fn extract_position(position: u32) -> (u32, u32) {
(position / ONE_ATTRIBUTE, position % ONE_ATTRIBUTE)
@ -15,6 +30,7 @@ fn construct_position(attr: u32, index: u32) -> u32 {
}
// TODO we should use an sdset::Set for `next_positions`.
// TODO We must not recursively search for the best proximity but return None if proximity is not found.
// Returns the positions to focus that will give the best possible proximity.
fn best_proximity_for(current_position: u32, proximity: u32, next_positions: &[u32]) -> Option<(u32, Vec<u32>)> {
let (current_attr, _) = extract_position(current_position);
@ -108,42 +124,72 @@ fn best_proximity_for(current_position: u32, proximity: u32, next_positions: &[u
pub struct BestProximity {
positions: Vec<Vec<u32>>,
current_proximity: Option<(u32, Vec<(u32, usize)>)>, // where we are
best_proximities: Option<Vec<u32>>,
}
impl BestProximity {
pub fn new(positions: Vec<Vec<u32>>) -> BestProximity {
BestProximity { positions, current_proximity: None }
BestProximity { positions, best_proximities: None }
}
}
impl Iterator for BestProximity {
type Item = (u32, Vec<u32>);
type Item = (u32, Vec<Vec<u32>>);
fn next(&mut self) -> Option<Self::Item> {
let output = Vec::new();
let best_proximity = 0;
match &mut self.best_proximities {
Some(best_proximities) => {
let expected_proximity = best_proximities.iter().sum::<u32>() + 1;
dbg!(expected_proximity);
for (i, positions) in self.positions.iter().enumerate() {
if let Some(next_positions) = self.positions.get(i + 1) {
for x in positions {
let p = next_positions.binary_search(&x);
let y = next_positions.get(p.unwrap_or_else(|p| p));
eprintln!("{:?} gives {:?} ({:?})", x, p, y);
for (i, (win, proximity)) in self.positions.windows(2).zip(best_proximities.iter()).enumerate() {
let (posa, posb) = (&win[0], &win[1]);
dbg!(proximity, posa, posb);
let expected_proximity = proximity + 1;
let best_proximity = posa.iter().filter_map(|pa| {
best_proximity_for(*pa, expected_proximity, posb).map(|res| (*pa, res))
}).min();
dbg!(best_proximity);
}
None
},
None => {
let expected_proximity = 0;
let mut best_results = Vec::new();
for win in self.positions.windows(2) {
let (posa, posb) = (&win[0], &win[1]);
match best_results.last() {
Some((start, _)) => {
// We know from where we must continue searching for the best path.
let (best_proximity, positions) = dbg!(best_proximity_for(*start, expected_proximity, posb).unwrap());
best_results.push((positions[0], best_proximity));
},
None => {
// This is the first loop, we need to find the best start of the path.
let best_proximity = posa.iter().filter_map(|pa| {
best_proximity_for(*pa, expected_proximity, posb).map(|res| (*pa, res))
}).min();
let (pa, (best_proximity, positions)) = best_proximity.unwrap();
// We must save the best start of path we found.
best_results.push((pa, 0));
// And the next associated position along with the proximity between those.
best_results.push((positions[0], best_proximity));
}
}
}
if best_results.is_empty() {
None
} else {
let proximity = best_results.windows(2).map(|ps| positions_proximity(ps[0].0, ps[1].0)).sum::<u32>();
self.best_proximities = Some(best_results.iter().skip(1).map(|(_, p)| *p).collect());
let best_positions = best_results.into_iter().map(|(x, _)| vec![x]).collect();
Some((proximity, best_positions))
}
}
}
// match &mut self.current_proximity {
// Some((_prox, _pos)) => {
// // ...
// },
// None => {
// // ...
// },
// }
Some((best_proximity, output))
}
}
@ -160,15 +206,16 @@ mod tests {
];
let mut iter = BestProximity::new(positions);
assert_eq!(iter.next(), Some((1+2, vec![0, 1, 3]))); // 3
assert_eq!(iter.next(), Some((2+2, vec![2, 1, 3]))); // 4
assert_eq!(iter.next(), Some((3+2, vec![3, 1, 3]))); // 5
assert_eq!(iter.next(), Some((1+5, vec![0, 1, 6]))); // 6
assert_eq!(iter.next(), Some((4+2, vec![4, 1, 3]))); // 6
assert_eq!(iter.next(), Some((2+5, vec![2, 1, 6]))); // 7
assert_eq!(iter.next(), Some((3+5, vec![3, 1, 6]))); // 8
assert_eq!(iter.next(), Some((4+5, vec![4, 1, 6]))); // 9
assert_eq!(iter.next(), None);
assert_eq!(iter.next(), Some((1+2, vec![vec![0], vec![1], vec![3]]))); // 3
eprintln!("------------------");
assert_eq!(iter.next(), Some((2+2, vec![vec![2], vec![1], vec![3]]))); // 4
// assert_eq!(iter.next(), Some((3+2, vec![3, 1, 3]))); // 5
// assert_eq!(iter.next(), Some((1+5, vec![0, 1, 6]))); // 6
// assert_eq!(iter.next(), Some((4+2, vec![4, 1, 3]))); // 6
// assert_eq!(iter.next(), Some((2+5, vec![2, 1, 6]))); // 7
// assert_eq!(iter.next(), Some((3+5, vec![3, 1, 6]))); // 8
// assert_eq!(iter.next(), Some((4+5, vec![4, 1, 6]))); // 9
// assert_eq!(iter.next(), None);
}
#[test]