how do i implement heap data structure using c++? [closed] - c++

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Using this simple example of a binary heap. How would i implement this data structure using c++ code.
1
/ \
3 6
/\ /\
5 9 8
Also apart from being able to gain easy access to the max or min values in an array, how is this data structure useful?
the example come from the following link: http://www.algolist.net/Data_structures/Binary_heap

Answer 1

Here is my simplest C++ implementation for heap. The code is well-commented.
/*
Usage:
heap Heap;
Heap.clear();
Heap.insert(value);
Heap.remove();
Heap.print();
*/
struct heap {
int myarray[NN+1]; // myarray to store the numbers as heap, 1 indexed
int n; // the number of nodes in my array
heap() { // constructor
clear(); // we clear the heap
}
void clear() { // initialize the heap
n = 0; // initially there are no nodes in the heap
}
void insert( int K ) { // inserting an element K in the heap
if( n == NN ) { // the heap is full
printf("cannot insert any more element, the heap is full\n");
return;
}
++n; // so, we have a new element, we increased n before adding
// the element because we start from index 1
myarray[n] = K; // inserted the element at the rightmost position
int p = n; // for keeping the current position
while( p > 1 ) { // p = 1 means we are on the root, and its a heap
int pr = p / 2; // pr is the parent of p
if( myarray[pr] > myarray[p] ) { // parent is greater than child
swap( myarray[pr], myarray[p] );
p = pr; // now the new position of the current element is pr
} else break; // otherwise its a heap, so we can stop here
}
}
int remove() { // removing the minimum element from the heap
if( n == 0 ) { // is the heap is empty
printf("The heap is empty, cannot delete.\n");
return -1;
}
int K = myarray[1]; // first element in the heap is the minimum
myarray[1] = myarray[n]; // brought the last element in 1st position
n--; // as we removed one element, now we need to maintain the heap
int p = 1; // as we moved the rightmost element in index 1
while( 2 * p <= n ) { // means p has at least one child, if 2*p > n
// we are sure that p is in the last level
int ch = 2 * p; // contains the index of the child
if( 2 * p + 1 <= n ) { // right child exists
if( myarray[ch] > myarray[ch+1] ) // right child is smaller
// than left child
ch++; // ch contains the index of the right child
}
if( myarray[p] > myarray[ch] ) { // so, current node is larger
// than its child
swap( myarray[p], myarray[ch] );
p = ch; // new position of the current element
} else break; //current node is smaller than its children, so heap
}
return K; // as we stored the minimum element in K
}
void print() { // printing the heap
printf("Number of elements: %d\n", n);
for( int i = 1; i <= n; i++ ) printf("%d ", myarray[i]);
printf("\n");
}
// Time: O(nlogn)
// Extra space: O(1) as we will pass the input array as res here
void heapSort(int* res) {
for(int i = 0, len = n; i < len; ++i) {
res[i] = remove();
}
}
};

Answer 2

I am writing below Java implementation it can help you to write code in c++;
import java.util.Arrays;
/**
* Min heap implementation, also caters to duplicate
*/
public class MinHeap {`
private int capacity = 10;
private int size;
int[] items;
public MinHeap() {
items = new int[capacity];
size = 0;
}
public void ensureExtraCapacity() {
if (size == capacity) {
items = Arrays.copyOf(items, capacity * 2);
capacity *= 2;
}
}
private int getLeftChildIndex(int index) {
return 2 * index + 1;
}
private int getRightChildIndex(int index) {
return 2 * index + 2;
}
private int getParentIndex(int index) {
return (index - 1) / 2;
}
private boolean hasLeftChild(int index) {
return size > getLeftChildIndex(index);
}
private boolean hasRightChild(int index) {
return size > getRightChildIndex(index);
}
private boolean hasParent(int index) {
if(index == 0)
return false;
return getParentIndex(index) >= 0;
}
private int leftChild(int index) {
return items[getLeftChildIndex(index)];
}
private int rightChild(int index) {
return items[getRightChildIndex(index)];
}
private int parent(int index) {
return items[getParentIndex(index)];
}
private void swapValues(int index1, int index2) {
int temp = items[index1];
items[index1] = items[index2];
items[index2] = temp;
}
public int peek() {
if (size == 0) throw new IllegalStateException();
return items[0];
}
public int poll() {
if (size == 0) throw new IllegalStateException();
int polled = items[0];
items[0] = items[size - 1];
size--;
heapifyDown();
return polled;
}
public void add(int item) {
ensureExtraCapacity();
items[size] = item;
size++;
heapifyUp();
}
private void heapifyUp() {
int index = size - 1;
while (hasParent(index) && parent(index) > items[index]) {
swapValues(index, getParentIndex(index));
index = getParentIndex(index);
}
}
private void heapifyDown() {
int index = 0;
while (hasLeftChild(index)) {
int minimumChildIndex = getLeftChildIndex(index);
if (hasRightChild(index) && rightChild(index) < leftChild(index))
minimumChildIndex = getRightChildIndex(index);
if (items[index] < items[minimumChildIndex]) {
break;
} else {
swapValues(index, minimumChildIndex);
}
index = minimumChildIndex;
}
}
/* public void printMinHeap() {
while (size > 0) {
int poll = poll();
System.out.println(poll);
}
}*/
/* public static void main(String[] args) {
MinHeap minHeap = new MinHeap();
minHeap.add(7);
minHeap.add(3);
minHeap.add(4);
minHeap.add(10);
minHeap.add(1);
minHeap.add(15);
minHeap.add(2);
minHeap.add(17);
minHeap.add(1);
minHeap.printMinHeap();
}*/
}