30.23. Union/FIND¶
30.23.1. Union/FIND¶
30.23.1.1. Disjoint Sets and Equivalence Classes¶
Sometimes we have a collection of objects that we want to divide into separate sets.
30.23.1.2. Approach¶
Each object initially is a separate node in its own tree.
When two objects are "equivalent", then add them to the same tree.
Key question: Given two nodes, are they in the same tree?
30.23.1.3. Parent Pointer Implementation¶
30.23.1.4. Union/FIND¶
// General Tree implementation for UNION/FIND class ParPtrTree { private int[] array; // Node array ParPtrTree(int size) { array = new int[size]; // Create node array for (int i=0; i<size; i++) array[i] = -1; // Each node is its own root to start } // Merge two subtrees if they are different void UNION(int a, int b) { int root1 = FIND(a); // Find root of node a int root2 = FIND(b); // Find root of node b if (root1 != root2) // Merge two trees array[root1] = root2; } // Return the root of curr's tree int FIND(int curr) { while (array[curr] != -1) curr = array[curr]; return curr; // Now at root } }
30.23.1.5. Weighted Union¶
A key goal is to keep the depth of nodes as shallow as possible (consistent with efficient processing).
- Weighted Union rule:
- When two trees are union'ed, add one with fewer nodes as a child of the root of the tree with more nodes.
- Depth is \(O(\log n)\)
30.23.1.7. .¶
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