[−][src]Struct bintrie::BinTrie
Methods
impl BinTrie
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pub fn new() -> Self
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Makes a new trie with a maximum depth
of 8192
.
let trie = BinTrie::new();
pub fn new_depth(depth: u32) -> Self
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Makes a new trie with a given maximum depth
.
let trie = BinTrie::new_depth(128);
pub fn insert<K, F>(&mut self, item: u32, key: K, lookup: F) -> Option<u32> where
K: FnMut(u32) -> bool,
F: FnMut(u32, u32) -> bool,
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K: FnMut(u32) -> bool,
F: FnMut(u32, u32) -> bool,
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.
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]);
pub fn get<K>(&self, key: K) -> Option<u32> where
K: FnMut(u32) -> bool,
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K: FnMut(u32) -> bool,
Perform a lookup for a particular item.
K(n)
- A function that provides the n
th bit for the key.
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);
pub fn items<'a>(
&'a self
) -> impl Iterator<Item = u32> + 'a
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&'a self
) -> impl Iterator<Item = u32> + 'a
Get an iterator over the items added to the trie.
let mut trie = BinTrie::new(); trie.insert(3, |_| false, |_, _| false); assert_eq!(trie.items().collect::<Vec<u32>>(), vec![3]);
pub fn explore<'a, H>(
&'a self,
heuristic: H
) -> impl Iterator<Item = u32> + 'a where
H: IntoHeuristic,
H::Heuristic: 'a,
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&'a self,
heuristic: H
) -> impl Iterator<Item = u32> + 'a where
H: IntoHeuristic,
H::Heuristic: 'a,
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.
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]);
Trait Implementations
impl Default for BinTrie
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impl Clone for BinTrie
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fn clone(&self) -> BinTrie
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fn clone_from(&mut self, source: &Self)
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Performs copy-assignment from source
. Read more
impl Debug for BinTrie
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Auto Trait Implementations
Blanket Implementations
impl<T> From for T
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impl<T, U> Into for T where
U: From<T>,
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U: From<T>,
impl<T> ToOwned for T where
T: Clone,
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T: Clone,
impl<T, U> TryFrom for T where
U: Into<T>,
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U: Into<T>,
type Error = !
try_from
)The type returned in the event of a conversion error.
fn try_from(value: U) -> Result<T, <T as TryFrom<U>>::Error>
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impl<T> Borrow for T where
T: ?Sized,
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T: ?Sized,
impl<T> Any for T where
T: 'static + ?Sized,
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T: 'static + ?Sized,
impl<T> BorrowMut for T where
T: ?Sized,
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T: ?Sized,
fn borrow_mut(&mut self) -> &mut T
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impl<T, U> TryInto for T where
U: TryFrom<T>,
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U: TryFrom<T>,