Example 1: Heap sort in c++
using namespace std;
void heapify(int arr[], int n, int i)
{
int largest = i;
int l = 2 * i + 1;
int r = 2 * i + 2;
if (l < n && arr[l] > arr[largest])
largest = l;
if (r < n && arr[r] > arr[largest])
largest = r;
if (largest != i) {
swap(arr[i], arr[largest]);
heapify(arr, n, largest);
}
}
void heapSort(int arr[], int n)
{
for (int i = n / 2 - 1; i >= 0; i--)
heapify(arr, n, i);
for (int i = n - 1; i > 0; i--) {
swap(arr[0], arr[i]);
heapify(arr, i, 0);
}
}
void printArray(int arr[], int n)
{
for (int i = 0; i < n; ++i)
cout << arr[i] << " ";
cout << "\n";
}
int main()
{
int arr[] = { 12, 11, 13, 5, 6, 7 };
int n = sizeof(arr) / sizeof(arr[0]);
heapSort(arr, n);
cout << "Sorted array is \n";
printArray(arr, n);
}
Example 2: heap sort
// @see https://www.youtube.com/watch?v=H5kAcmGOn4Q
function heapify(list, size, index) {
let largest = index;
let left = index * 2 + 1;
let right = left + 1;
if (left < size && list[left] > list[largest]) {
largest = left;
}
if (right < size && list[right] > list[largest]) {
largest = right;
}
if (largest !== index) {
[list[index], list[largest]] = [list[largest], list[index]];
heapify(list, size, largest);
}
return list;
}
function heapsort(list) {
const size = list.length;
let index = ~~(size / 2 - 1);
let last = size - 1;
while (index >= 0) {
heapify(list, size, --index);
}
while (last >= 0) {
[list[0], list[last]] = [list[last], list[0]];
heapify(list, --last, 0);
}
return list;
}
heapsort([4, 7, 2, 6, 4, 1, 8, 3]);
Example 3: heapsort
Implementation of heap sort in C++:
using namespace std;
// To heapify a subtree rooted with node i which is
// Heapify:- A process which helps regaining heap properties in tree after removal
void heapify(int A[], int n, int i)
{
int largest = i; // Initialize largest as root
int left_child = 2 * i + 1; // left = 2*i + 1
int right_child = 2 * i + 2; // right = 2*i + 2
// If left child is larger than root
if (left_child < n && A[left_child] > A[largest])
largest = left_child;
// If right child is larger than largest so far
if (right_child < n && A[right_child] > A[largest])
largest = right_child;
// If largest is not root
if (largest != i) {
swap(A[i], A[largest]);
// Recursively heapify the affected sub-tree
heapify(A, n, largest);
}
}
// main function to do heap sort
void heap_sort(int A[], int n)
{
// Build heap (rearrange array)
for (int i = n / 2 - 1; i >= 0; i--)
heapify(A, n, i);
// One by one extract an element from heap
for (int i = n - 1; i >= 0; i--) {
// Move current root to end
swap(A[0], A[i]);
// call max heapify on the reduced heap
heapify(A, i, 0);
}
}
/* A function to print sorted Array */
void printArray(int A[], int n)
{
for (int i = 0; i < n; ++i)
cout << A[i] << " ";
cout << "\n";
}
// Driver program
int main()
{
int A[] = { 22, 19, 3, 25, 26, 7 }; // array to be sorted
int n = sizeof(A) / sizeof(A[0]); // n is size of array
heap_sort(A, n);
cout << "Sorted array is \n";
printArray(A, n);
}
Example 4: heap sort
void heapify(int arr[], int n, int i) {
// Find largest among root, left child and right child
int largest = i;
int left = 2 * i + 1;
int right = 2 * i + 2;
if (left < n && arr[left] > arr[largest])
largest = left;
if (right < n && arr[right] > arr[largest])
largest = right;
// Swap and continue heapifying if root is not largest
if (largest != i) {
swap(&arr[i], &arr[largest]);
heapify(arr, n, largest);
}
}
Example 5: heap sort
def heapify(arr, n, i):
largest = i
l = 2 * i + 1
r = 2 * i + 2
if l < n and arr[i] < arr[l]:
largest = l
if r < n and arr[largest] < arr[r]:
largest = r
if largest != i:
arr[i], arr[largest] = arr[largest], arr[i]
heapify(arr, n, largest)
def heapSort(arr):
n = len(arr)
for i in range(n//2, -1, -1):
heapify(arr, n, i)
for i in range(n-1, 0, -1):
arr[i], arr[0] = arr[0], arr[i]
heapify(arr, i, 0)
arr = [1, 12, 9, 5, 6, 10]
heapSort(arr)
n = len(arr)
print("Sorted array is")
for i in range(n):
print("%d " % arr[i], end='')
Example 6: heap sort name meaning
A sorting algorithm that works by first organizing the data to be sorted into a special type of binary tree called a heap. The heap itself has, by definition, the largest value at the top of the tree.