max heap c++ stl;
// C++ program to show that priority_queue is by
// default a Max Heap
#include <bits/stdc++.h>
using namespace std;
// Driver code
int main ()
{
// Creates a max heap
priority_queue <int> pq;
pq.push(5);
pq.push(1);
pq.push(10);
pq.push(30);
pq.push(20);
// One by one extract items from max heap
while (pq.empty() == false)
{
cout << pq.top() << " ";
pq.pop();
}
return 0;
}min max heap java
// min heap: PriorityQueue implementation from the JDK
PriorityQueue<Integer> prq = new PriorityQueue<>();
// max heap: PriorityQueue implementation WITH CUSTOM COMPARATOR PASSED
// Method 1: Using Collections (recommended)
PriorityQueue<Integer> prq = new PriorityQueue<>(Collections.reverseOrder());
// Method 2: Using Lambda function (may cause Integer Overflow)
PriorityQueue<Integer> prq = new PriorityQueue<>((a, b) -> b - a);minimum and maximum numbers of elements in a heap of height h
Hence the minimum number of nodes possible in a heap of height h is 2h.
Clearly a heap of height h, has the maximum number of elements when its lowest level is completely filled.
In this case the heap is a complete binary tree of height h and hence has 2h+1 -1 nodes.Max Heap Python
def max_heapify(A,k):
l = left(k)
r = right(k)
if l < len(A) and A[l] > A[k]:
largest = l
else:
largest = k
if r < len(A) and A[r] > A[largest]:
largest = r
if largest != k:
A[k], A[largest] = A[largest], A[k]
max_heapify(A, largest)
def left(k):
return 2 * k + 1
def right(i):
return 2 * k + 2
def build_max_heap(A):
n = int((len(A)//2)-1)
for k in range(n, -1, -1):
max_heapify(A,k)
A = [3,9,2,1,4,5]
build_max_heap(A)
print(A)Copyright © 2021 Codeinu
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