--- /dev/null
+use std::iter::Step;
+use std::marker::PhantomData;
+use std::ops::Bound;
+use std::ops::RangeBounds;
+
+use crate::vec::Idx;
+use crate::vec::IndexVec;
+use smallvec::SmallVec;
+
+#[cfg(test)]
+mod tests;
+
+/// Stores a set of intervals on the indices.
+#[derive(Debug, Clone)]
+pub struct IntervalSet<I> {
+ // Start, end
+ map: SmallVec<[(u32, u32); 4]>,
+ domain: usize,
+ _data: PhantomData<I>,
+}
+
+#[inline]
+fn inclusive_start<T: Idx>(range: impl RangeBounds<T>) -> u32 {
+ match range.start_bound() {
+ Bound::Included(start) => start.index() as u32,
+ Bound::Excluded(start) => start.index() as u32 + 1,
+ Bound::Unbounded => 0,
+ }
+}
+
+#[inline]
+fn inclusive_end<T: Idx>(domain: usize, range: impl RangeBounds<T>) -> Option<u32> {
+ let end = match range.end_bound() {
+ Bound::Included(end) => end.index() as u32,
+ Bound::Excluded(end) => end.index().checked_sub(1)? as u32,
+ Bound::Unbounded => domain.checked_sub(1)? as u32,
+ };
+ Some(end)
+}
+
+impl<I: Idx> IntervalSet<I> {
+ pub fn new(domain: usize) -> IntervalSet<I> {
+ IntervalSet { map: SmallVec::new(), domain, _data: PhantomData }
+ }
+
+ pub fn clear(&mut self) {
+ self.map.clear();
+ }
+
+ pub fn iter(&self) -> impl Iterator<Item = I> + '_
+ where
+ I: Step,
+ {
+ self.iter_intervals().flatten()
+ }
+
+ /// Iterates through intervals stored in the set, in order.
+ pub fn iter_intervals(&self) -> impl Iterator<Item = std::ops::Range<I>> + '_
+ where
+ I: Step,
+ {
+ self.map.iter().map(|&(start, end)| I::new(start as usize)..I::new(end as usize + 1))
+ }
+
+ /// Returns true if we increased the number of elements present.
+ pub fn insert(&mut self, point: I) -> bool {
+ self.insert_range(point..=point)
+ }
+
+ /// Returns true if we increased the number of elements present.
+ pub fn insert_range(&mut self, range: impl RangeBounds<I> + Clone) -> bool {
+ let start = inclusive_start(range.clone());
+ let Some(mut end) = inclusive_end(self.domain, range) else {
+ // empty range
+ return false;
+ };
+ if start > end {
+ return false;
+ }
+
+ loop {
+ // This condition looks a bit weird, but actually makes sense.
+ //
+ // if r.0 == end + 1, then we're actually adjacent, so we want to
+ // continue to the next range. We're looking here for the first
+ // range which starts *non-adjacently* to our end.
+ let next = self.map.partition_point(|r| r.0 <= end + 1);
+ if let Some(last) = next.checked_sub(1) {
+ let (prev_start, prev_end) = &mut self.map[last];
+ if *prev_end + 1 >= start {
+ // If the start for the inserted range is adjacent to the
+ // end of the previous, we can extend the previous range.
+ if start < *prev_start {
+ // Our range starts before the one we found. We'll need
+ // to *remove* it, and then try again.
+ //
+ // FIXME: This is not so efficient; we may need to
+ // recurse a bunch of times here. Instead, it's probably
+ // better to do something like drain_filter(...) on the
+ // map to be able to delete or modify all the ranges in
+ // start..=end and then potentially re-insert a new
+ // range.
+ end = std::cmp::max(end, *prev_end);
+ self.map.remove(last);
+ } else {
+ // We overlap with the previous range, increase it to
+ // include us.
+ //
+ // Make sure we're actually going to *increase* it though --
+ // it may be that end is just inside the previously existing
+ // set.
+ return if end > *prev_end {
+ *prev_end = end;
+ true
+ } else {
+ false
+ };
+ }
+ } else {
+ // Otherwise, we don't overlap, so just insert
+ self.map.insert(last + 1, (start, end));
+ return true;
+ }
+ } else {
+ if self.map.is_empty() {
+ // Quite common in practice, and expensive to call memcpy
+ // with length zero.
+ self.map.push((start, end));
+ } else {
+ self.map.insert(next, (start, end));
+ }
+ return true;
+ }
+ }
+ }
+
+ pub fn contains(&self, needle: I) -> bool {
+ let needle = needle.index() as u32;
+ let last = match self.map.partition_point(|r| r.0 <= needle).checked_sub(1) {
+ Some(idx) => idx,
+ None => {
+ // All ranges in the map start after the new range's end
+ return false;
+ }
+ };
+ let (_, prev_end) = &self.map[last];
+ needle <= *prev_end
+ }
+
+ pub fn superset(&self, other: &IntervalSet<I>) -> bool
+ where
+ I: Step,
+ {
+ // FIXME: Performance here is probably not great. We will be doing a lot
+ // of pointless tree traversals.
+ other.iter().all(|elem| self.contains(elem))
+ }
+
+ pub fn is_empty(&self) -> bool {
+ self.map.is_empty()
+ }
+
+ /// Returns the maximum (last) element present in the set from `range`.
+ pub fn last_set_in(&self, range: impl RangeBounds<I> + Clone) -> Option<I> {
+ let start = inclusive_start(range.clone());
+ let Some(end) = inclusive_end(self.domain, range) else {
+ // empty range
+ return None;
+ };
+ if start > end {
+ return None;
+ }
+ let last = match self.map.partition_point(|r| r.0 <= end).checked_sub(1) {
+ Some(idx) => idx,
+ None => {
+ // All ranges in the map start after the new range's end
+ return None;
+ }
+ };
+ let (_, prev_end) = &self.map[last];
+ if start <= *prev_end { Some(I::new(std::cmp::min(*prev_end, end) as usize)) } else { None }
+ }
+
+ pub fn insert_all(&mut self) {
+ self.clear();
+ self.map.push((0, self.domain.try_into().unwrap()));
+ }
+
+ pub fn union(&mut self, other: &IntervalSet<I>) -> bool
+ where
+ I: Step,
+ {
+ assert_eq!(self.domain, other.domain);
+ let mut did_insert = false;
+ for range in other.iter_intervals() {
+ did_insert |= self.insert_range(range);
+ }
+ did_insert
+ }
+}
+
+/// This data structure optimizes for cases where the stored bits in each row
+/// are expected to be highly contiguous (long ranges of 1s or 0s), in contrast
+/// to BitMatrix and SparseBitMatrix which are optimized for
+/// "random"/non-contiguous bits and cheap(er) point queries at the expense of
+/// memory usage.
+#[derive(Clone)]
+pub struct SparseIntervalMatrix<R, C>
+where
+ R: Idx,
+ C: Idx,
+{
+ rows: IndexVec<R, IntervalSet<C>>,
+ column_size: usize,
+}
+
+impl<R: Idx, C: Step + Idx> SparseIntervalMatrix<R, C> {
+ pub fn new(column_size: usize) -> SparseIntervalMatrix<R, C> {
+ SparseIntervalMatrix { rows: IndexVec::new(), column_size }
+ }
+
+ pub fn rows(&self) -> impl Iterator<Item = R> {
+ self.rows.indices()
+ }
+
+ pub fn row(&self, row: R) -> Option<&IntervalSet<C>> {
+ self.rows.get(row)
+ }
+
+ fn ensure_row(&mut self, row: R) -> &mut IntervalSet<C> {
+ self.rows.ensure_contains_elem(row, || IntervalSet::new(self.column_size));
+ &mut self.rows[row]
+ }
+
+ pub fn union_row(&mut self, row: R, from: &IntervalSet<C>) -> bool
+ where
+ C: Step,
+ {
+ self.ensure_row(row).union(from)
+ }
+
+ pub fn union_rows(&mut self, read: R, write: R) -> bool
+ where
+ C: Step,
+ {
+ if read == write || self.rows.get(read).is_none() {
+ return false;
+ }
+ self.ensure_row(write);
+ let (read_row, write_row) = self.rows.pick2_mut(read, write);
+ write_row.union(read_row)
+ }
+
+ pub fn insert_all_into_row(&mut self, row: R) {
+ self.ensure_row(row).insert_all();
+ }
+
+ pub fn insert_range(&mut self, row: R, range: impl RangeBounds<C> + Clone) {
+ self.ensure_row(row).insert_range(range);
+ }
+
+ pub fn insert(&mut self, row: R, point: C) -> bool {
+ self.ensure_row(row).insert(point)
+ }
+
+ pub fn contains(&self, row: R, point: C) -> bool {
+ self.row(row).map_or(false, |r| r.contains(point))
+ }
+}
projects / rustc.git / blobdiff