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mod heuristic;
pub use heuristic::*;
const HIGH: u32 = 0x8000_0000;
use std::slice;
/// Contains a list of 2 children node IDs.
///
/// Each child ID's highest bit indicates if it is an internal node or a
/// leaf node.
///
/// If a child is `0` then it is empty because the root node can never be pointed to.
#[derive(Copy, Clone, Debug, Default)]
struct Internal([u32; 2]);
#[derive(Clone, Debug)]
pub struct BinTrie {
/// The root node is always at index `0`.
internals: Vec<Internal>,
/// The maximum depth to stop at.
depth: u32,
}
impl BinTrie {
/// Makes a new trie with a maximum `depth` of `8192`.
///
/// ```
/// # use bintrie::BinTrie;
/// let trie = BinTrie::new();
/// ```
pub fn new() -> Self {
Default::default()
}
/// Makes a new trie with a given maximum `depth`.
///
/// ```
/// # use bintrie::BinTrie;
/// let trie = BinTrie::new_depth(128);
/// ```
pub fn new_depth(depth: u32) -> Self {
assert!(depth > 0);
Self {
internals: vec![Internal::default()],
depth,
}
}
/// Inserts a number that does not have the most significant bit set.
///
/// `K(n)` - A function that provides the `n`th bit for the key.
/// `F(item, n)` - A function that must be able to look up the nth bit
/// from a previously inserted item.
///
/// Returns `Some` of a replaced leaf if a leaf was replaced, otherwise None.
///
/// ```
/// # use bintrie::BinTrie;
/// let mut trie = BinTrie::new();
/// // Note that the item, the key, and the lookup key all obey the
/// // unsafe requirements.
/// trie.insert(5, |_| false, |_, _| false);
/// assert_eq!(trie.items().collect::<Vec<u32>>(), vec![5]);
/// ```
#[inline(always)]
pub fn insert<K, F>(&mut self, item: u32, mut key: K, mut lookup: F) -> Option<u32>
where
K: FnMut(u32) -> bool,
F: FnMut(u32, u32) -> bool,
{
// Always check that the high bit is not set in the item.
assert!(item & HIGH == 0);
// This unsafe block is only used to allow indexing [u32; 2] by a `1` or `0`.
unsafe {
let mut index = 0;
for i in 0..self.depth - 1 {
let position = if key(i) { 1 } else { 0 };
match *self
.internals
.get_unchecked(index)
.0
.get_unchecked(position)
{
// Empty node encountered.
0 => {
// Insert the item in the empty spot, making sure to set
// its most significant bit to indicate it is a leaf.
*self
.internals
.get_unchecked_mut(index)
.0
.get_unchecked_mut(position) = item | HIGH;
// That's it.
return None;
}
// Leaf node encountered.
m if m & HIGH != 0 => {
// Make an empty node.
let mut new_internal = Internal::default();
// Add the existing `m` to its proper location.
*new_internal
.0
.get_unchecked_mut(if lookup(m & !HIGH, i + 1) { 1 } else { 0 }) = m;
// Get the index of the next internal node.
let new_index = self.internals.len() as u32;
// Panic if we go too high to fit in our indices.
assert!(new_index & HIGH == 0);
// Insert the new internal node onto the internals vector.
self.internals.push(new_internal);
// Insert the new index to the parent node.
*self
.internals
.get_unchecked_mut(index)
.0
.get_unchecked_mut(position) = new_index;
// Fallthrough to the next iteration where it will either
// be expanded or hit the empty leaf node position.
index = new_index as usize;
}
// Internal node encountered.
m => {
// Move to the internal node.
index = m as usize;
}
}
}
// For the last bit we only handle the case that we can insert it.
// If something occupies the space we replace it and return it.
let position = if key(self.depth - 1) { 1 } else { 0 };
let spot = self
.internals
.get_unchecked_mut(index)
.0
.get_unchecked_mut(position);
let old = *spot;
*spot = item | HIGH;
// Check if it was not an empty node.
if old != 0 {
// Return the item that was replaced.
Some(old & !HIGH)
} else {
None
}
}
}
/// Perform a lookup for a particular item.
///
/// `K(n)` - A function that provides the `n`th bit for the key.
///
/// ```
/// # use bintrie::BinTrie;
/// let mut trie = BinTrie::new();
/// let key = |_| false;
/// let lookup = |_, _| false;
/// trie.insert(5, key, lookup);
/// assert_eq!(trie.get(key), Some(5));
/// assert_eq!(trie.get(|_| true), None);
/// ```
#[inline(always)]
pub fn get<K>(&self, mut key: K) -> Option<u32>
where
K: FnMut(u32) -> bool,
{
// This unsafe block is only used to allow indexing [u32; 2] by a `1` or `0`.
unsafe {
let mut index = 0;
for i in 0..self.depth {
match *self
.internals
.get_unchecked(index)
.0
.get_unchecked(if key(i) { 1 } else { 0 })
{
// Empty node encountered.
0 => {
return None;
}
// Leaf node encountered.
m if m & HIGH != 0 => return Some(m & !HIGH),
// Internal node encountered.
m => {
// Move to the internal node.
index = m as usize;
}
}
}
None
}
}
/// Get an iterator over the items added to the trie.
///
/// ```
/// # use bintrie::BinTrie;
/// let mut trie = BinTrie::new();
/// trie.insert(3, |_| false, |_, _| false);
/// assert_eq!(trie.items().collect::<Vec<u32>>(), vec![3]);
/// ```
pub fn items<'a>(&'a self) -> impl Iterator<Item = u32> + 'a {
Iter::new(self)
}
/// Iterates over the trie while using the `heuristic` to guide iteration.
///
/// This can be used to limit the search space or to guide the search space
/// for a fast constant distance or other spatial heuristic search. This is
/// not capable of directly outputting kNN, and would need to be combined
/// with either a heuristic search that gets everything below a discrete
/// distance and then sorts the output or a search that gets items
/// with a discrete distance and iterates over each distance desired.
///
/// `heuristic` must implement `IntoHeuristic`, which the normal
/// `Heuristic` trait satisfies.
///
/// ```
/// # use bintrie::{BinTrie, FilterHeuristic};
/// let mut trie = BinTrie::new();
/// let lookup = |n, l| match n {
/// 3 => false,
/// 5 => if l == 1 { true } else { false },
/// 7 => if l == 1 { false } else { true },
/// _ => true,
/// };
/// trie.insert(3, |n| lookup(3, n), lookup);
/// trie.insert(5, |n| lookup(5, n), lookup);
/// trie.insert(7, |n| lookup(7, n), lookup);
/// assert_eq!(trie.explore(FilterHeuristic(|n| n)).collect::<Vec<u32>>(), vec![7]);
/// let mut level = 0;
/// // Try and find the 5.
/// assert_eq!(trie.explore(FilterHeuristic(move |n: bool| {
/// level += 1;
/// match level {
/// // Go left.
/// 1 => !n,
/// // Then go right.
/// 2 => n,
/// _ => false,
/// }
/// })).collect::<Vec<u32>>(), vec![5]);
/// ```
pub fn explore<'a, H>(&'a self, heuristic: H) -> impl Iterator<Item = u32> + 'a
where
H: IntoHeuristic,
H::Heuristic: 'a,
{
ExploreIter::new(self, heuristic.into_heuristic())
}
}
impl Default for BinTrie {
fn default() -> Self {
Self {
internals: vec![Internal::default()],
depth: 8192,
}
}
}
struct Iter<'a> {
trie: &'a BinTrie,
indices: Vec<slice::Iter<'a, u32>>,
}
impl<'a> Iter<'a> {
fn new(trie: &'a BinTrie) -> Self {
Self {
trie,
indices: vec![trie.internals[0].0.iter()],
}
}
}
impl<'a> Iterator for Iter<'a> {
type Item = u32;
#[inline(always)]
fn next(&mut self) -> Option<Self::Item> {
loop {
// Get the current slice. If there is none, then we return `None`.
let mut current = self.indices.pop()?;
// Get the next item in the slice or continue the loop if its empty.
let n = if let Some(n) = current.next() {
// Push the slice back.
self.indices.push(current);
n
} else {
continue;
};
// Check what kind of node it is.
match n {
// Empty node
0 => {}
// Leaf node
n if n & HIGH != 0 => {
return Some(n & !HIGH);
}
// Internal node
&n => self.indices.push(self.trie.internals[n as usize].0.iter()),
}
}
}
}
struct ExploreIter<'a, H>
where
H: Heuristic,
{
trie: &'a BinTrie,
indices: Vec<(&'a [u32; 2], H, H::Iter)>,
}
impl<'a, H> ExploreIter<'a, H>
where
H: Heuristic,
{
fn new(trie: &'a BinTrie, heuristic: H) -> Self {
let iter = heuristic.iter();
Self {
trie,
indices: vec![(&trie.internals[0].0, heuristic, iter)],
}
}
}
impl<'a, H> Iterator for ExploreIter<'a, H>
where
H: Heuristic,
{
type Item = u32;
#[inline(always)]
fn next(&mut self) -> Option<Self::Item> {
loop {
// Get the current array, heuristic, and iter.
// If there is none, then we return `None`.
let (array, heuristic, mut iter) = self.indices.pop()?;
// Clone the heuristic before we put it back so we can
// use it when descending further.
let mut next_heuristic = heuristic.clone();
// Get the next item in the array or continue the loop if its empty.
let (choice, n) = if let Some(choice) = iter.next() {
let n = unsafe { array.get_unchecked(if choice { 1 } else { 0 }) };
// Push the state back.
self.indices.push((array, heuristic, iter));
(choice, n)
} else {
continue;
};
// Check what kind of node it is.
match n {
// Empty node
0 => {}
// Leaf node
n if n & HIGH != 0 => {
return Some(n & !HIGH);
}
// Internal node
&n => {
next_heuristic.enter(choice);
let iter = next_heuristic.iter();
self.indices
.push((&self.trie.internals[n as usize].0, next_heuristic, iter))
}
}
}
}
}