“sterta” Kod odpowiedzi

sterta

# Heap Sort in python


  def heapify(arr, n, i):
      # Find largest among root and children
      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 root is not largest, swap with largest and continue heapifying
      if largest != i:
          arr[i], arr[largest] = arr[largest], arr[i]
          heapify(arr, n, largest)
  
  
  def heapSort(arr):
      n = len(arr)
  
      # Build max heap
      for i in range(n//2, -1, -1):
          heapify(arr, n, i)
  
      for i in range(n-1, 0, -1):
          # Swap
          arr[i], arr[0] = arr[0], arr[i]
  
          # Heapify root element
          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='')
Bored Bat

sterta

#include<iostream>
#include<cmath>

using namespace std;

int find_min_element_index(int a[] , int element , int left_child , int right_child){
	if(a[element] <= a[left_child] && a[element] <= a[right_child])
		return element;

	if(a[left_child] <= a[element] && a[left_child] <= a[right_child])
		return left_child;

	if(a[right_child] <= a[element] && a[right_child] <= a[left_child])
		return right_child;
}

int check_heap(int a[] , int n){

	int second_last_level = (int)log2(n);

	int check_elements_upto_index = pow( 2 , second_last_level+1)-2;
	for(int i=0; i<=check_elements_upto_index; i++){

		if(2*i+1 <= n-1 || 2*i+2 <= n-1){
				if(2*i+1 <= n-1 && 2*i+2 <= n-1){
					if(a[i] <= a[2*i+1] && a[i] <= a[2*i+2])
					 	continue;
					else
						return 0;
				}
				else if(2*i+1 <= n-1){
						if(a[i] <= a[2*i+1])
							continue;
						else
							return 0;
				}
				else{
						if(a[i] <= a[2*i+2])
							continue;
						else
							return 0;
				}
			}
			else{
			   break;
			}
	}
	return 1;
}

void heapify(int a[] , int n){
	int heap_flag = 0;
	while(heap_flag == 0){
		int level = (int)log2(n);
		int ending_index_at_corresponding_level = pow(2 ,level+1)-2;
		for(int i = ending_index_at_corresponding_level;i >= 0 ;i--){
					if(2*i+1 <= n-1 || 2*i+2 <= n-1){
						if(2*i+1 <= n-1 && 2*i+2 <= n-1){
				                    int min_index = find_min_element_index(a , i , 2*i+1 , 2*i+2);
							 		if(min_index == i){
							 			continue;
									}
									else{
										int temp = a[min_index];
										a[min_index] = a[i];
										a[i] = temp;
									}
						}
						else if( 2*i+1 <= n-1){
								if(a[i] <= a[2*i+1])
									continue;
								else{
										int temp = a[i];
										a[i] = a[2*i+1];
										a[2*i+1] = temp;
									}
						}
						else{
								if(a[i] <= a[2*i+2])
									continue;
								else{
										int temp = a[i];
										a[i] = a[2*i+2];
										a[2*i+2] = temp;
								}
						}
					}
		}

		heap_flag = check_heap(a , n);
		if(heap_flag == 1){
			cout << a[0] <<", ";
			int temp = a[0];
			a[0] = a[n-1];
			a[n-1] = temp;
			n = n-1;
		}
		if(n==1){
			cout <<a[0] <<", ";
			break;
		}

		heap_flag = check_heap(a , n);
	}
}


int main(){
	int list[] = {6,8,7,9,1,4,3,2,5,0};
	cout<<endl<<"List of Elements before sort: ";
	for(int i = 0; i<10; i++)
        cout<<list[i]<<", ";
	cout <<endl<<endl<<"Sorted Output as Follows : ";
	heapify(list , 10);
	cout<<endl;
}
Grieving Gazelle

SORP SORP

package sort

type MaxHeap struct {
	slice    []Comparable
	heapSize int
	indices  map[int]int
}

func buildMaxHeap(slice0 []int) MaxHeap {
	var slice []Comparable
	for _, i := range slice0 {
		slice = append(slice, Int(i))
	}
	h := MaxHeap{}
	h.Init(slice)
	return h
}

func (h *MaxHeap) Init(slice []Comparable) {
	if slice == nil {
		slice = make([]Comparable, 0)
	}

	h.slice = slice
	h.heapSize = len(slice)
	h.indices = make(map[int]int)
	h.Heapify()
}

func (h MaxHeap) Heapify() {
	for i, v := range h.slice {
		h.indices[v.Idx()] = i
	}
	for i := h.heapSize / 2; i >= 0; i-- {
		h.heapifyDown(i)
	}
}

func (h *MaxHeap) Pop() Comparable {
	if h.heapSize == 0 {
		return nil
	}

	i := h.slice[0]
	h.heapSize--

	h.slice[0] = h.slice[h.heapSize]
	h.updateidx(0)
	h.heapifyDown(0)

	h.slice = h.slice[0:h.heapSize]
	return i
}

func (h *MaxHeap) Push(i Comparable) {
	h.slice = append(h.slice, i)
	h.updateidx(h.heapSize)
	h.heapifyUp(h.heapSize)
	h.heapSize++
}

func (h MaxHeap) Size() int {
	return h.heapSize
}

func (h MaxHeap) Update(i Comparable) {
	h.slice[h.indices[i.Idx()]] = i
	h.heapifyUp(h.indices[i.Idx()])
	h.heapifyDown(h.indices[i.Idx()])
}

func (h MaxHeap) updateidx(i int) {
	h.indices[h.slice[i].Idx()] = i
}

func (h MaxHeap) heapifyUp(i int) {
	if i == 0 {
		return
	}
	p := i / 2

	if h.slice[i].More(h.slice[p]) {
		h.slice[i], h.slice[p] = h.slice[p], h.slice[i]
		h.updateidx(i)
		h.updateidx(p)
		h.heapifyUp(p)
	}
}

func (h MaxHeap) heapifyDown(i int) {
	l, r := 2*i+1, 2*i+2
	max := i

	if l < h.heapSize && h.slice[l].More(h.slice[max]) {
		max = l
	}
	if r < h.heapSize && h.slice[r].More(h.slice[max]) {
		max = r
	}
	if max != i {
		h.slice[i], h.slice[max] = h.slice[max], h.slice[i]
		h.updateidx(i)
		h.updateidx(max)
		h.heapifyDown(max)
	}
}

type Comparable interface {
	Idx() int
	More(interface{}) bool
}
type Int int

func (a Int) More(b interface{}) bool {
	return a > b.(Int)
}
func (a Int) Idx() int {
	return int(a)
}

func HeapSort(slice []int) []int {
	h := buildMaxHeap(slice)
	for i := len(h.slice) - 1; i >= 1; i-- {
		h.slice[0], h.slice[i] = h.slice[i], h.slice[0]
		h.heapSize--
		h.heapifyDown(0)
	}

	res := []int{}
	for _, i := range h.slice {
		res = append(res, int(i.(Int)))
	}
	return res
}
gocrazygh

Kapła Znaczenie nazwy

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.
Worried Wildebeest

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