最小最大堆是同时实现最小堆和最大堆的一种数据结构。具有以下操作功能：
（1）插入操作（O（logN））；
（2）返回最小值（O（1）），返回最大值（O（1））；
（3）删除最小值（O（logN）），删除最大值（O（logN））。
最小最大堆的根结点是堆中的最小值。把根结点看做是第一层的话，奇数层是最小堆层，也是这些奇数层实现的是最小堆结构，同样，偶数层是最大堆层，偶数层实现最大堆结构。下图为为一最小最大堆
package com.ldl.algorithms.Exercise;
import java.util.Comparator;
import java.util.Iterator;
import java.util.NoSuchElementException;
import com.ldl.algorithms.StdIn;
import com.ldl.algorithms.StdOut;
public class Min_MaxHeap<Key> implements Iterable<Key> {
private Key[] pq; //store items at indices 1 to N
private int N; //number of items on priority queue
private Comparator<Key> comparator; //optional comparator
/**
* Create an empty priority queue with the given initial capacity.
*/
public Min_MaxHeap(int initCapacity) {
pq = (Key[])new Object[initCapacity + 1];
N = 0;
}
/**
* Create an empty priority queue.
*/
public Min_MaxHeap() { this(1); }
/**
* Create an empty priority queue with the given initial capacity,
* using the given comparator.
*/
public Min_MaxHeap(int initCapacity, Comparator<Key> comparator) {
this.comparator = comparator;
pq = (Key[])new Object[initCapacity + 1];
N = 0;
}
/**
* Create an empty priority queue using the given comparator.
*/
public Min_MaxHeap(Comparator<Key> comparator) { this(1, comparator); }
/**
* Create a priority queue with the given items.
* Takes time proportional to the number of items using sink-based heap construction.
*/
public Min_MaxHeap(Key[] keys) {
N = keys.length;
pq = (Key[]) new Object[N + 1];
for(int i = 0; i < N; i++)
pq[i+1] = keys[i];
for(int k = N/2; k>=1; k--)
sink(k);
assert isMin_MaxHeap();
}
/**
* Is the priority queue empty?
*/
public boolean isEmpty() {
return N == 0;
}
/**
* Return the number of items on the priority queue.
*/
public int size(){
return N;
}
/**
* Return the smallest key on the priority queue.
* Throw an exception if no such key exists because the priority queue is empty.
*/
public Key min() {
if(isEmpty()) throw new RuntimeException("Priority queue underflow");
return pq[1];
}
/**
* Return the largest key on the priority queue.
* Throw an exception if no such key exists because the priority queue is empty.
*/
public Key max() {
if(N == 0) throw new RuntimeException("Priority queue underflow");
if(N == 1) return pq[1];
if(N == 2) return pq[2];
return less(1, 2) ? pq[2] : pq[1];
}
/**
* Add a new key to the priority queue.
*/
public void insert(Key x) {
if (N == pq.length - 1) resize(2 * pq.length);
pq[++N] = x;
swim(N);
assert isMin_MaxHeap();
}
/**
* Delete and return the smallest key on the priority queue.
* Throw an exception if no such key exists because the priority queue is empty.
*/
public Key delMin() {
if(N == 0) throw new RuntimeException("Priority queue underflow");
exch(1, N);
Key min = pq[N--];
sink(1);
pq[N+1] = null;
if ((N > 0) && (N == (pq.length - 1) / 4)) resize(pq.length / 2);
assert isMin_MaxHeap();
return min;
}
/**
* Delete and return the largest key on the priority queue.
* Throw an exception if no such key exists because the priority queue is empty.
*/
public Key delMax() {
if(N == 0) throw new RuntimeException("Priority queue underflow");
if(N == 1) return delMin();
if(N == 2) {
Key max =pq[2];
N--;
pq[N+1] = null;
if ((N > 0) && (N == (pq.length - 1) / 4)) resize(pq.length / 2);
return max;
}
int m = less(2, 3) ? 3 : 2;
exch(m, N);
Key max = pq[N--];
sink(m);
pq[N+1] = null;
if ((N > 0) && (N == (pq.length - 1) / 4)) resize(pq.length / 2);
return max;
}
//helper function to double the size of the heap array
private void resize(int capacity) {
Key[] temp = (Key[]) new Object[capacity];
for(int i = 1; i <= N; i++) temp[i] = pq[i];
pq = temp;
}
/***********************************************************************
* Helper functions to restore the heap invariant.
**********************************************************************/
private void sink(int k) {
if(isMin(k)) sinkMin(k);
else sinkMax(k);
}
private void sinkMin(int k) {
if(2*k <= N) {
int m;
if(4*k > N) {
if(N == 2*k) m = 2*k;
else m = less(2*k, 2*k+1) ? 2*k : 2*k+1;
if(less(m, k)) exch(m, k);
}
else {
m = 4*k;
for(int i = 4*k+1; i <= N && i < 4*k+4; i++)
if(less(i, m)) m = i;
if(less(m, k)) {
exch(m, k);
if(less(m/2, m)) exch(m/2, m);
sinkMin(m);
}
}
}
}
private void sinkMax(int k) {
if(2*k <= N) {
int m;
if(4*k > N) {
if(N == 2*k) m = 2*k;
else m = less(2*k, 2*k+1) ? 2*k+1 : 2*k;
if(less(k, m)) exch(m, k);
}
else {
m = 4*k;
for(int i = 4*k+1; i <= N && i < 4*k+4; i++)
if(less(m, i)) m = i;
if(less(k, m)) {
exch(m, k);
if(less(m, m/2)) exch(m/2, m);
sinkMax(m);
}
}
}
}
private void swim(int k) {
if(isMin(k)) {
if(k > 1 && less(k/2, k)) {
exch(k, k/2);
swimMax(k/2);
}
else swimMin(k);
}
else {
if(k > 1 && less(k, k/2)) {
exch(k, k/2);
swimMin(k/2);
}
else swimMax(k);
}
}
private void swimMin(int k) {
if(k/4 > 0 && less(k, k/4)) {
exch(k, k/4);
swimMin(k/4);
}
}
private void swimMax(int k) {
if(k/4 > 0 && less(k/4, k)) {
exch(k, k/4);
swimMax(k/4);
}
}
private boolean less(int i, int j) {
if (comparator == null) {
return ((Comparable<Key>) pq[i]).compareTo(pq[j]) < 0;
}
else {
return comparator.compare(pq[i], pq[j]) < 0;
}
}
private void exch(int i, int j) {
Key swap = pq[i];
pq[i] = pq[j];
pq[j] = swap;
}
// is node k is on min level?
private boolean isMin(int k) {
double r = Math.log((double)(k + 1)) / Math.log(2.0);
int floor = (int)Math.ceil(r);
return (floor & 1) == 1;
}
// is pq[1..N] a min-max heap?
private boolean isMin_MaxHeap() {
return isMin_MaxHeap(1);
}
// is subtree of pq[1..N] rooted at k a min-max heap?
private boolean isMin_MaxHeap(int k) {
if (k > N) return true;
int left = 2*k, right = 2*k + 1;
if(isMin(k)) {
if (left <= N && less(left, k)) return false;
if (right <= N && less(right, k)) return false;
}
else {
if (left <= N && less(k, left)) return false;
if (right <= N && less(k, right)) return false;
}
return isMin_MaxHeap(left) && isMin_MaxHeap(right);
}
/***********************************************************************
* Iterators
**********************************************************************/
/**
* Return an iterator that iterates over all of the keys on the priority queue
* in ascending order.
* <p>
* The iterator doesn't implement <tt>remove()</tt> since it's optional.
*/
public Iterator<Key> iterator() { return new Min_MaxHeapIterator(); }
private class Min_MaxHeapIterator implements Iterator<Key> {
// create a new pq
private Min_MaxHeap<Key> copy;
// add all items to copy of heap
// takes linear time since already in heap order so no keys move
public Min_MaxHeapIterator() {
if(comparator == null) copy = new Min_MaxHeap<Key>(size());
else copy = new Min_MaxHeap<Key>(size(), comparator);
for(int i = 1; i <= N; i++)
copy.insert(pq[i]);
}
public boolean hasNext() {return !copy.isEmpty();}
public void remove() { throw new UnsupportedOperationException(); }
public Key next() {
if (!hasNext()) throw new NoSuchElementException();
return copy.delMin();
}
}
/**
* A test client.
*/
public static void main(String[] args) {
Min_MaxHeap<String> pq = new Min_MaxHeap<String>();
while (!StdIn.isEmpty()) {
String item = StdIn.readString();
if (!item.equals("+") && !item.equals("-")) pq.insert(item);
else if (!pq.isEmpty() && item.equals("+")) StdOut.print(pq.delMax() + " ");
else if (!pq.isEmpty() && item.equals("-")) StdOut.print(pq.delMin() + " ");
}
}
}
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