lctree

Rust implementation of Link-cut tree: self-balancing data structure to maintain a dynamic forest of (un)rooted trees under the following operations that take O(logn) amortized time:

• link(v, w): creates an edge between nodes v and w.
• cut(v, w): removes the edge between nodes v and w.
• connected(v, w): returns true if nodes v and w are in the same tree.
• path(v, w): performs calculations on a path between nodes v and w.

Usage

This example shows how to link and cut edges:

use lctree::LinkCutTree;

fn main() {
    // We form a link-cut tree for the following forest:
    // (the numbers in parentheses are the weights of the nodes):
    //            a(9)
    //           /    \
    //         b(1)    e(2)
    //        /   \      \
    //      c(8)  d(10)   f(4)
    let mut lctree = LinkCutTree::default();
    let a = lctree.make_tree(9.);
    let b = lctree.make_tree(1.);
    let c = lctree.make_tree(8.);
    let d = lctree.make_tree(10.);
    let e = lctree.make_tree(2.);
    let f = lctree.make_tree(4.);

    lctree.link(b, a);
    lctree.link(c, b);
    lctree.link(d, b);
    lctree.link(e, a);
    lctree.link(f, e);

    // Checking connectivity:
    assert!(lctree.connected(c, f)); // connected

    // Path aggregation:
    // We find the node with max weight on the path between c to f,
    // where a has the maximum weight of 9.0:
    let heaviest_node = lctree.path(c, f);
    assert_eq!(heaviest_node.idx, a);
    assert_eq!(heaviest_node.weight, 9.0);

    // We cut node e from its parent a:
    lctree.cut(e, a);

    // The forest should now look like this:
    //            a(9)
    //           /    
    //         b(1)      e(2)
    //        /   \        \
    //      c(8)  d(10)    f(4)

    // We check connectivity again:
    assert!(!lctree.connected(c, f)); // not connected anymore
}

Advanced usage include operations on paths:

use lctree::{LinkCutTree, FindMax, FindMin, FindSum};

fn main() {
    // We form a link-cut tree from the following rooted tree
    // (the numbers in parentheses are the weights of the nodes):
    //           a(9)
    //           /  \
    //         b(1)  e(2)
    //        /   \    \
    //      c(8)  d(10)  f(4)

    // Use FindMax, FindMin or FindSum, depending on your usage:
    let mut lctree: LinkCutTree<FindSum> = lctree::LinkCutTree::new();
    let a = lctree.make_tree(9.);
    let b = lctree.make_tree(1.);
    let c = lctree.make_tree(8.);
    let d = lctree.make_tree(10.);
    let e = lctree.make_tree(2.);
    let f = lctree.make_tree(4.);

    lctree.link(b, a);
    lctree.link(c, b);
    lctree.link(d, b);
    lctree.link(e, a);
    lctree.link(f, e);

    // We find the sum of the weights on the path between c to f,
    let result = lctree.path(c, f);
    assert_eq!(result.sum, 8. + 1. + 9. + 2. + 4.);
}

use lctree::{LinkCutTree, Path};

#[derive(Copy, Clone)]
pub struct FindXor {
    pub xor: u64,
}

impl Path for FindXor {
    fn default(weight: f64, _: usize) -> Self {
        FindXor {
            xor: weight as u64,
        }
    }

    fn aggregate(&mut self, other: Self) {
        self.xor ^= other.xor;
    }
}

fn main() {
    // We form a link-cut tree from the following rooted tree
    // (the numbers in parentheses are the weights of the nodes):
    //           a(9)
    //           /  \
    //         b(1)  e(2)
    //        /   \    \
    //      c(8)  d(10)  f(4)
    let mut lctree: LinkCutTree<FindXor> = LinkCutTree::new();
    let a = lctree.make_tree(9.);
    let b = lctree.make_tree(1.);
    let c = lctree.make_tree(8.);
    let d = lctree.make_tree(10.);
    let e = lctree.make_tree(2.);
    let f = lctree.make_tree(4.);

    lctree.link(b, a);
    lctree.link(c, b);
    lctree.link(d, b);
    lctree.link(e, a);
    lctree.link(f, e);

    // We find the xor of the weights on the path between c to f,
    let result = lctree.path(c, f);
    assert_eq!(result.xor, 8 ^ 1 ^ 9 ^ 2 ^ 4);
}

Benchmark

The overall running time for performing a number of random operations (link(v, w), cut(v, w), connected(v, w) or findmax(v, w)) on forests of varying sizes (check benchmark details here).

Credits

This crate applies the core concepts and ideas presented in the following sources:

• "A data structure for dynamic trees" by D. Sleator and R. E. TarJan (published in STOC '81).
• Link-cut tree source code by the author D. Sleator.
• MIT's lecture on dynamic graphs: lecture, notes, and source code.
• Helpful blog posts on the concepts of rooted trees, rerooting and splay operations.

License

This project is licensed under the Apache License, Version 2.0 - See the LICENSE.md file for details.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be licensed as above, without any additional terms or conditions.