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For a sequence of m addition, union, or find operations on a disjoint-set forest with n nodes, the total time required is O(mα(n)), where α(n) is the extremely slow-growing inverse Ackermann function. Although disjoint-set forests do not guarantee this time per operation, each operation rebalances the structure (via tree compression) so that ...
The pseudocode below determines the lowest common ancestor of each pair in P, given the root r of a tree in which the children of node n are in the set n.children. For this offline algorithm, the set P must be specified in advance. It uses the MakeSet, Find, and Union functions of a disjoint-set data structure.
Next, use a disjoint-set data structure, with a set of vertices for each component, to keep track of which vertices are in which components. Creating this structure, with a separate set for each vertex, takes V operations and O(V) time. The final iteration through all edges performs two find operations and possibly one union operation per edge.
The implementation listed as Implementation of Disjoint-set Forests in C++, by Bo Tian seems not to update the path (it dont do path compression) which is the hole point. — Preceding unsigned comment added by 85.164.124.173 17:57, 20 July 2011 (UTC) I've removed the C++ links, as the code was poor quality.
A constructor is a function or an expression that produces a value of the tagged union type, given a tag and a value of the corresponding type. Mathematically, tagged unions correspond to disjoint or discriminated unions, usually written using +. Given an element of a disjoint union A + B, it is possible to determine whether it came from A or B.
The following example shows how Suurballe's algorithm finds the shortest pair of disjoint paths from A to F. Figure A illustrates a weighted graph G. Figure B calculates the shortest path P 1 from A to F (A–B–D–F). Figure C illustrates the shortest path tree T rooted at A, and the computed distances from A to every vertex (u).
Jeffery Westbrook and Robert Tarjan (1992) [4] developed an efficient data structure for this problem based on disjoint-set data structures. Specifically, it processes n vertex additions and m edge additions in O(m α(m, n)) total time, where α is the inverse Ackermann function. This time bound is proved to be optimal.
An efficient implementation using a disjoint-set data structure can perform each union and find operation on two sets in nearly constant amortized time (specifically, (()) time; () < for any plausible value of ), so the running time of this algorithm is essentially proportional to the number of walls available to the maze.