Data structure cheat sheet: Difference between revisions
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=== Heap === | === Heap === | ||
A (binary) heap is a complete binary tree that keeps a sepcific condition of its nodes: For a max-heap, <math>A[parent[i]] >= A[i]</math>, for a min-heap, <math>A[parent[i]] <= A[i]</math>. A heap can be used to maintain a priority queue. | A (binary) heap is a complete binary tree that keeps a sepcific condition of its nodes: For a max-heap, <math>A[parent[i]] >= A[i]</math>, for a min-heap, <math>A[parent[i]] <= A[i]</math>. A heap can be used to maintain a priority queue. A heap is often stored as a continous vector. | ||
==== Heapify ==== | ==== Heapify ==== | ||
Revision as of 16:36, 25 October 2020
A quick cheat sheet on common algorithms and data structures:
Linear Structures
Linked Lists
Basic Implementation
String
Related Algorithms
Arrays
Sorting
Tree-based Structures
Binary Tree
Property
Traversal
Heap
A (binary) heap is a complete binary tree that keeps a sepcific condition of its nodes: For a max-heap, , for a min-heap, . A heap can be used to maintain a priority queue. A heap is often stored as a continous vector.
Heapify
void maxheapify(Node* array, int size, int start) {
auto largest = start;
if(start * 2 < size && A[largest] < A[start * 2])
largest = start * 2;
if(start * 2 + 1 < size && A[largest] < A[start * 2 + 1])
largest = start * 2 + 1;
if(largest != start) {
swap(A[start], A[largest]);
maxheapify(A, size, largest);
}
}