这是一个面试问题。您需要设计一个包含整数值的堆栈，以便getMinimum（）函数返回堆栈中的最小元素。
例如：考虑以下示例
case #1 5 --> TOP 1 4 6 2 When getMinimum() is called it should return 1, which is the minimum element in the stack. case #2 stack.pop() stack.pop() Note: Both 5 and 1 are poped out of the stack. So after this, the stack looks like, 4 --> TOP 6 2 When getMinimum() is called is should return 2 which is the minimum in the stack.
制约性：
答案 0 :(得分：171)
编辑：这不符合“恒定空间”约束 - 它基本上使所需空间加倍。我非常怀疑有一个没有这样做的解决方案，但没有在某处破坏运行时的复杂性（例如制作push / pop O（n））。请注意，这不会更改所需空间的复杂度，例如如果你有一个具有O（n）空间要求的堆栈，那么它仍然是O（n）只是具有不同的常数因子。
非恒定空间解决方案
保持“重复”堆栈“堆栈中所有值的最小值”。弹出主堆栈时，也会弹出最小堆栈。当您按下主堆栈时，按下新元素或当前最小值，以较低者为准。然后getMinimum()实现为minStack.peek()。
所以使用你的例子，我们有：
Real stack Min stack
5 --> TOP 1
1 1
4 2
6 2
2 2
弹出两次后，你得到：
Real stack Min stack
4 2
6 2
2 2
如果这还不够，请告诉我。当你理解它时它很简单，但最初可能需要一点点头痛：）
（当然缺点是它会占用空间要求的两倍。但执行时间不会受到太大影响 - 即它的复杂程度仍然相同。）
编辑：有一种变化略微繁琐，但总的来说有更好的空间。我们仍然有最小堆栈，但是当我们从主堆栈弹出的值等于最小堆栈上的值时，我们只会弹出它。当推入主堆栈的值小于或等于到当前最小值时，我们只推送到最小堆栈。这允许重复最小值。 getMinimum()仍然只是一个偷看行动。例如，采用原始版本并再次推送1，我们得到：
Real stack Min stack
1 --> TOP 1
5 1
1 2
4
6
2
从两个堆栈弹出上面的pop，因为1 == 1，离开：
Real stack Min stack
5 --> TOP 1
1 2
4
6
2
再次弹出仅从主堆栈中弹出，因为5＆gt; 1：
Real stack Min stack
1 1
4 2
6
2
弹出再次弹出两个堆栈，因为1 == 1：
Real stack Min stack
4 2
6
2
这最终会导致相同的最坏情况空间复杂度（原始堆栈的两倍），但如果我们很少得到“新的最小值或相等”，则会有更好的空间使用。
编辑：这是皮特邪恶计划的实施。我没有彻底测试过，但我认为没关系：）using System.Collections.Generic;
public class FastMinStack<T>
{
private readonly Stack<T> stack = new Stack<T>();
// Could pass this in to the constructor
private readonly IComparer<T> comparer = Comparer<T>.Default;
private T currentMin;
public T Minimum
{
get { return currentMin; }
}
public void Push(T element)
{
if (stack.Count == 0 ||
comparer.Compare(element, currentMin) <= 0)
{
stack.Push(currentMin);
stack.Push(element);
currentMin = element;
}
else
{
stack.Push(element);
}
}
public T Pop()
{
T ret = stack.Pop();
if (comparer.Compare(ret, currentMin) == 0)
{
currentMin = stack.Pop();
}
return ret;
}
}
答案 1 :(得分：41)
添加一个字段以保持最小值，并在Pop（）和Push（）期间更新它。这样getMinimum（）将是O（1），但Pop（）和Push（）将不得不做更多的工作。
如果弹出最小值，Pop（）将为O（n），否则它们仍将是O（1）。根据Stack实现，调整Push（）的大小变为O（n）。
这是一个快速实现
public sealed class MinStack {
private int MinimumValue;
private readonly Stack<int> Stack = new Stack<int>();
public int GetMinimum() {
if (IsEmpty) {
throw new InvalidOperationException("Stack is empty");
}
return MinimumValue;
}
public int Pop() {
var value = Stack.Pop();
if (value == MinimumValue) {
MinimumValue = Stack.Min();
}
return value;
}
public void Push(int value) {
if (IsEmpty || value < MinimumValue) {
MinimumValue = value;
}
Stack.Push(value);
}
private bool IsEmpty { get { return Stack.Count() == 0; } }
}
答案 2 :(得分：16)
public class StackWithMin {
int min;
int size;
int[] data = new int[1024];
public void push ( int val ) {
if ( size == 0 ) {
data[size] = val;
min = val;
} else if ( val < min) {
data[size] = 2 * val - min;
min = val;
assert (data[size] < min);
} else {
data[size] = val;
}
++size;
// check size and grow array
}
public int getMin () {
return min;
}
public int pop () {
--size;
int val = data[size];
if ( ( size > 0 ) && ( val < min ) ) {
int prevMin = min;
min += min - val;
return prevMin;
} else {
return val;
}
}
public boolean isEmpty () {
return size == 0;
}
public static void main (String...args) {
StackWithMin stack = new StackWithMin();
for ( String arg: args )
stack.push( Integer.parseInt( arg ) );
while ( ! stack.isEmpty() ) {
int min = stack.getMin();
int val = stack.pop();
System.out.println( val + " " + min );
}
System.out.println();
}
}
它显式地存储当前最小值，如果最小值发生变化，而不是按下该值，则推送一个值与新最小值的另一侧相同（如果min = 7并且你按5，它会推3 （5- | 7-5 | = 3）并将min设置为5;如果你然后在min为5时弹出3它会看到弹出的值小于min，所以将程序反转为新的min得到7，然后返回前一分钟）。任何不会引起变化的值当前最小值都大于当前最小值，你可以用一些东西来区分改变最小值的值和不改变最小值的值。
在使用固定大小整数的语言中，您从值的表示中借用了一些空间，因此它可能会下溢并且断言将失败。但除此之外，它是恒定的额外空间，所有操作仍然是O（1）。
基于链接列表的堆栈有其他可以借用的地方，例如在C中是下一个指针的最低有效位，或者在Java中是链接列表中对象的类型。对于Java，这意味着与连续堆栈相比，使用的空间更多，因为每个链接都有对象开销：
public class LinkedStackWithMin {
private static class Link {
final int value;
final Link next;
Link ( int value, Link next ) {
this.value = value;
this.next = next;
}
int pop ( LinkedStackWithMin stack ) {
stack.top = next;
return value;
}
}
private static class MinLink extends Link {
MinLink ( int value, Link next ) {
super( value, next );
}
int pop ( LinkedStackWithMin stack ) {
stack.top = next;
int prevMin = stack.min;
stack.min = value;
return prevMin;
}
}
Link top;
int min;
public LinkedStackWithMin () {
}
public void push ( int val ) {
if ( ( top == null ) || ( val < min ) ) {
top = new MinLink(min, top);
min = val;
} else {
top = new Link(val, top);
}
}
public int pop () {
return top.pop(this);
}
public int getMin () {
return min;
}
public boolean isEmpty () {
return top == null;
}
在C中，开销不存在，你可以借用下一个指针的lsb：
typedef struct _stack_link stack_with_min;
typedef struct _stack_link stack_link;
struct _stack_link {
size_t next;
int value;
};
stack_link* get_next ( stack_link* link )
{
return ( stack_link * )( link -> next & ~ ( size_t ) 1 );
}
bool is_min ( stack_link* link )
{
return ( link -> next & 1 ) ! = 0;
}
void push ( stack_with_min* stack, int value )
{
stack_link *link = malloc ( sizeof( stack_link ) );
link -> next = ( size_t ) stack -> next;
if ( (stack -> next == 0) || ( value == stack -> value ) ) {
link -> value = stack -> value;
link -> next |= 1; // mark as min
} else {
link -> value = value;
}
stack -> next = link;
}
etc.;
然而，这些都不是真正的O（1）。它们在实践中不需要更多空间，因为它们利用这些语言中数字，对象或指针的表示形式的漏洞。但是使用更紧凑的表示的理论机器将需要在每种情况下将额外的位添加到该表示。
答案 3 :(得分：12)
我找到了一个解决方案，它满足了所有提到的限制条件（恒定时间操作）和恒定额外空间。
这个想法是存储最小值和输入数之间的差异，如果最小值不再是最小值，则更新最小值。
代码如下：
public class MinStack {
long min;
Stack<Long> stack;
public MinStack(){
stack = new Stack<>();
}
public void push(int x) {
if (stack.isEmpty()) {
stack.push(0L);
min = x;
} else {
stack.push(x - min); //Could be negative if min value needs to change
if (x < min) min = x;
}
}
public int pop() {
if (stack.isEmpty()) return;
long pop = stack.pop();
if (pop < 0) {
long ret = min
min = min - pop; //If negative, increase the min value
return (int)ret;
}
return (int)(pop + min);
}
public int top() {
long top = stack.peek();
if (top < 0) {
return (int)min;
} else {
return (int)(top + min);
}
}
public int getMin() {
return (int)min;
}
}
信用证转到：https://leetcode.com/discuss/15679/share-my-java-solution-with-only-one-stack
答案 4 :(得分：7)
那么push和pop的运行时限制是什么？如果它们不需要是常数，那么只需计算这两个操作中的最小值（使它们 O （ n ））。否则，我不知道如何通过不断的额外空间来完成这项工作。
答案 5 :(得分：1)
我在这里发布完整的代码，以找到给定堆栈中的最小值和最大值。
时间复杂度为O（1）..
package com.java.util.collection.advance.datastructure;
/**
*
* @author vsinha
*
*/
public abstract interface Stack<E> {
/**
* Placing a data item on the top of the stack is called pushing it
* @param element
*
*/
public abstract void push(E element);
/**
* Removing it from the top of the stack is called popping it
* @return the top element
*/
public abstract E pop();
/**
* Get it top element from the stack and it
* but the item is not removed from the stack, which remains unchanged
* @return the top element
*/
public abstract E peek();
/**
* Get the current size of the stack.
* @return
*/
public abstract int size();
/**
* Check whether stack is empty of not.
* @return true if stack is empty, false if stack is not empty
*/
public abstract boolean empty();
}
package com.java.util.collection.advance.datastructure;
@SuppressWarnings("hiding")
public abstract interface MinMaxStack<Integer> extends Stack<Integer> {
public abstract int min();
public abstract int max();
}
package com.java.util.collection.advance.datastructure;
import java.util.Arrays;
/**
*
* @author vsinha
*
* @param <E>
*/
public class MyStack<E> implements Stack<E> {
private E[] elements =null;
private int size = 0;
private int top = -1;
private final static int DEFAULT_INTIAL_CAPACITY = 10;
public MyStack(){
// If you don't specify the size of stack. By default, Stack size will be 10
this(DEFAULT_INTIAL_CAPACITY);
}
@SuppressWarnings("unchecked")
public MyStack(int intialCapacity){
if(intialCapacity <=0){
throw new IllegalArgumentException("initial capacity can't be negative or zero");
}
// Can't create generic type array
elements =(E[]) new Object[intialCapacity];
}
@Override
public void push(E element) {
ensureCapacity();
elements[++top] = element;
++size;
}
@Override
public E pop() {
E element = null;
if(!empty()) {
element=elements[top];
// Nullify the reference
elements[top] =null;
--top;
--size;
}
return element;
}
@Override
public E peek() {
E element = null;
if(!empty()) {
element=elements[top];
}
return element;
}
@Override
public int size() {
return size;
}
@Override
public boolean empty() {
return size == 0;
}
/**
* Increases the capacity of this <tt>Stack by double of its current length</tt> instance,
* if stack is full
*/
private void ensureCapacity() {
if(size != elements.length) {
// Don't do anything. Stack has space.
} else{
elements = Arrays.copyOf(elements, size *2);
}
}
@Override
public String toString() {
return "MyStack [elements=" + Arrays.toString(elements) + ", size="
+ size + ", top=" + top + "]";
}
}
package com.java.util.collection.advance.datastructure;
/**
* Time complexity will be O(1) to find min and max in a given stack.
* @author vsinha
*
*/
public class MinMaxStackFinder extends MyStack<Integer> implements MinMaxStack<Integer> {
private MyStack<Integer> minStack;
private MyStack<Integer> maxStack;
public MinMaxStackFinder (int intialCapacity){
super(intialCapacity);
minStack =new MyStack<Integer>();
maxStack =new MyStack<Integer>();
}
public void push(Integer element) {
// Current element is lesser or equal than min() value, Push the current element in min stack also.
if(!minStack.empty()) {
if(min() >= element) {
minStack.push(element);
}
} else{
minStack.push(element);
}
// Current element is greater or equal than max() value, Push the current element in max stack also.
if(!maxStack.empty()) {
if(max() <= element) {
maxStack.push(element);
}
} else{
maxStack.push(element);
}
super.push(element);
}
public Integer pop(){
Integer curr = super.pop();
if(curr !=null) {
if(min() == curr) {
minStack.pop();
}
if(max() == curr){
maxStack.pop();
}
}
return curr;
}
@Override
public int min() {
return minStack.peek();
}
@Override
public int max() {
return maxStack.peek();
}
@Override
public String toString() {
return super.toString()+"\nMinMaxStackFinder [minStack=" + minStack + "\n maxStack="
+ maxStack + "]" ;
}
}
// You can use the below program to execute it.
package com.java.util.collection.advance.datastructure;
import java.util.Random;
public class MinMaxStackFinderApp {
public static void main(String[] args) {
MinMaxStack<Integer> stack =new MinMaxStackFinder(10);
Random random =new Random();
for(int i =0; i< 10; i++){
stack.push(random.nextInt(100));
}
System.out.println(stack);
System.out.println("MAX :"+stack.max());
System.out.println("MIN :"+stack.min());
stack.pop();
stack.pop();
stack.pop();
stack.pop();
stack.pop();
System.out.println(stack);
System.out.println("MAX :"+stack.max());
System.out.println("MIN :"+stack.min());
}
}
如果您遇到任何问题，请告诉我
谢谢， 维卡什
答案 6 :(得分：1)
您可以扩展原始堆栈类，只需添加最小跟踪。让原始父类像往常一样处理其他所有内容。
"oElim.fn_confirmar()"答案 7 :(得分：1)
这是我在java中使用喜欢列表的解决方案。
sorted}
答案 8 :(得分：1)
我使用了另一种堆栈。这是实施。
//
// main.cpp
// Eighth
//
// Created by chaitanya on 4/11/13.
// Copyright (c) 2013 cbilgika. All rights reserved.
//
#include <iostream>
#include <limits>
using namespace std;
struct stack
{
int num;
int minnum;
}a[100];
void push(int n,int m,int &top)
{
top++;
if (top>=100) {
cout<<"Stack Full";
cout<<endl;
}
else{
a[top].num = n;
a[top].minnum = m;
}
}
void pop(int &top)
{
if (top<0) {
cout<<"Stack Empty";
cout<<endl;
}
else{
top--;
}
}
void print(int &top)
{
cout<<"Stack: "<<endl;
for (int j = 0; j<=top ; j++) {
cout<<"("<<a[j].num<<","<<a[j].minnum<<")"<<endl;
}
}
void get_min(int &top)
{
if (top < 0)
{
cout<<"Empty Stack";
}
else{
cout<<"Minimum element is: "<<a[top].minnum;
}
cout<<endl;
}
int main()
{
int top = -1,min = numeric_limits<int>::min(),num;
cout<<"Enter the list to push (-1 to stop): ";
cin>>num;
while (num!=-1) {
if (top == -1) {
min = num;
push(num, min, top);
}
else{
if (num < min) {
min = num;
}
push(num, min, top);
}
cin>>num;
}
print(top);
get_min(top);
return 0;
}
输出：
Enter the list to push (-1 to stop): 5
1
4
6
2
-1
Stack:
(5,5)
(1,1)
(4,1)
(6,1)
(2,1)
Minimum element is: 1
试试吧。我认为它回答了这个问题。每对中的第二个元素给出了插入该元素时看到的最小值。
答案 9 :(得分：1)
这是我用O（1）运行的代码。我发布的前一个代码在弹出最小元素时出现问题。我修改了我的代码。这个使用另一个Stack，它在当前推送元素上方保持堆栈中存在的最小元素。
class StackDemo
{
int[] stk = new int[100];
int top;
public StackDemo()
{
top = -1;
}
public void Push(int value)
{
if (top == 100)
Console.WriteLine("Stack Overflow");
else
stk[++top] = value;
}
public bool IsEmpty()
{
if (top == -1)
return true;
else
return false;
}
public int Pop()
{
if (IsEmpty())
{
Console.WriteLine("Stack Underflow");
return 0;
}
else
return stk[top--];
}
public void Display()
{
for (int i = top; i >= 0; i--)
Console.WriteLine(stk[i]);
}
}
class MinStack : StackDemo
{
int top;
int[] stack = new int[100];
StackDemo s1; int min;
public MinStack()
{
top = -1;
s1 = new StackDemo();
}
public void PushElement(int value)
{
s1.Push(value);
if (top == 100)
Console.WriteLine("Stack Overflow");
if (top == -1)
{
stack[++top] = value;
stack[++top] = value;
}
else
{
// stack[++top]=value;
int ele = PopElement();
stack[++top] = ele;
int a = MininmumElement(min, value);
stack[++top] = min;
stack[++top] = value;
stack[++top] = a;
}
}
public int PopElement()
{
if (top == -1)
return 1000;
else
{
min = stack[top--];
return stack[top--];
}
}
public int PopfromStack()
{
if (top == -1)
return 1000;
else
{
s1.Pop();
return PopElement();
}
}
public int MininmumElement(int a,int b)
{
if (a > b)
return b;
else
return a;
}
public int StackTop()
{
return stack[top];
}
public void DisplayMinStack()
{
for (int i = top; i >= 0; i--)
Console.WriteLine(stack[i]);
}
}
class Program
{
static void Main(string[] args)
{
MinStack ms = new MinStack();
ms.PushElement(15);
ms.PushElement(2);
ms.PushElement(1);
ms.PushElement(13);
ms.PushElement(5);
ms.PushElement(21);
Console.WriteLine("Min Stack");
ms.DisplayMinStack();
Console.WriteLine("Minimum Element:"+ms.StackTop());
ms.PopfromStack();
ms.PopfromStack();
ms.PopfromStack();
ms.PopfromStack();
Console.WriteLine("Min Stack");
ms.DisplayMinStack();
Console.WriteLine("Minimum Element:" + ms.StackTop());
Thread.Sleep(1000000);
}
}
答案 10 :(得分：0)
要从Stack中获取MinMin元素。我们必须使用两个堆栈。即堆栈s1和堆栈s2。
---------------------递归地调用步骤2到4 -------------------- ---
如果将新元素添加到堆栈s1中，则从堆栈s2中弹出元素
将新元素与s2比较。哪一个较小，请按s2。
pop（包含min元素）
代码如下：
package Stack;
import java.util.Stack;
public class getMin
{
Stack<Integer> s1= new Stack<Integer>();
Stack<Integer> s2 = new Stack<Integer>();
void push(int x)
{
if(s1.isEmpty() || s2.isEmpty())
{
s1.push(x);
s2.push(x);
}
else
{
s1. push(x);
int y = (Integer) s2.pop();
s2.push(y);
if(x < y)
s2.push(x);
}
}
public Integer pop()
{
int x;
x=(Integer) s1.pop();
s2.pop();
return x;
}
public int getmin()
{
int x1;
x1= (Integer)s2.pop();
s2.push(x1);
return x1;
}
public static void main(String[] args) {
getMin s = new getMin();
s.push(10);
s.push(20);
s.push(30);
System.out.println(s.getmin());
s.push(1);
System.out.println(s.getmin());
}
}
答案 11 :(得分：0)
我有更好的解决方案，时间为 O(1) 且没有额外空间，您需要将元素作为字符串推送为
|-1,-1 |
| 1,1 |
| 2,2 |
| 5,3 |
| 3,3 |
现在你总能通过使用 peek 并检查给定实例的最小值来找到当前实例的最小值。这是没有额外空间的 O(1) 时间
答案 12 :(得分：0)
在这里看到了一个出色的解决方案： https://www.geeksforgeeks.org/design-a-stack-that-supports-getmin-in-o1-time-and-o1-extra-space/
Bellow是我按照算法编写的python代码：
class Node:
def __init__(self, value):
self.value = value
self.next = None
class MinStack:
def __init__(self):
self.head = None
self.min = float('inf')
# @param x, an integer
def push(self, x):
if self.head == None:
self.head = Node(x)
self.min = x
else:
if x >= self.min:
n = Node(x)
n.next = self.head
self.head = n
else:
v = 2 * x - self.min
n = Node(v)
n.next = self.head
self.head = n
self.min = x
# @return nothing
def pop(self):
if self.head:
if self.head.value < self.min:
self.min = self.min * 2 - self.head.value
self.head = self.head.next
# @return an integer
def top(self):
if self.head:
if self.head.value < self.min:
self.min = self.min * 2 - self.head.value
return self.min
else:
return self.head.value
else:
return -1
# @return an integer
def getMin(self):
if self.head:
return self.min
else:
return -1
答案 13 :(得分：0)
using System;
using System.Collections.Generic;
using System.IO;
using System.Linq;
namespace Solution
{
public class MinStack
{
public MinStack()
{
MainStack=new Stack<int>();
Min=new Stack<int>();
}
static Stack<int> MainStack;
static Stack<int> Min;
public void Push(int item)
{
MainStack.Push(item);
if(Min.Count==0 || item<Min.Peek())
Min.Push(item);
}
public void Pop()
{
if(Min.Peek()==MainStack.Peek())
Min.Pop();
MainStack.Pop();
}
public int Peek()
{
return MainStack.Peek();
}
public int GetMin()
{
if(Min.Count==0)
throw new System.InvalidOperationException("Stack Empty");
return Min.Peek();
}
}
}
答案 14 :(得分：0)
我认为您可以在堆栈实现中使用LinkedList。
首次推送值时，将此值设为链表头。
然后每次推送一个值，如果新值<＆lt; head.data，进行预备和操作（这意味着头部成为新值）
如果没有，则进行追加操作。
制作pop（）时，检查min == linkedlist.head.data，如果是，则head = head.next;
这是我的代码。
public class Stack {
int[] elements;
int top;
Linkedlists min;
public Stack(int n) {
elements = new int[n];
top = 0;
min = new Linkedlists();
}
public void realloc(int n) {
int[] tab = new int[n];
for (int i = 0; i < top; i++) {
tab[i] = elements[i];
}
elements = tab;
}
public void push(int x) {
if (top == elements.length) {
realloc(elements.length * 2);
}
if (top == 0) {
min.pre(x);
} else if (x < min.head.data) {
min.pre(x);
} else {
min.app(x);
}
elements[top++] = x;
}
public int pop() {
int x = elements[--top];
if (top == 0) {
}
if (this.getMin() == x) {
min.head = min.head.next;
}
elements[top] = 0;
if (4 * top < elements.length) {
realloc((elements.length + 1) / 2);
}
return x;
}
public void display() {
for (Object x : elements) {
System.out.print(x + " ");
}
}
public int getMin() {
if (top == 0) {
return 0;
}
return this.min.head.data;
}
public static void main(String[] args) {
Stack stack = new Stack(4);
stack.push(2);
stack.push(3);
stack.push(1);
stack.push(4);
stack.push(5);
stack.pop();
stack.pop();
stack.pop();
stack.push(1);
stack.pop();
stack.pop();
stack.pop();
stack.push(2);
System.out.println(stack.getMin());
stack.display();
}
}
答案 15 :(得分：0)
让我们假设我们要处理的堆栈是这样的：
6 , minvalue=2
2 , minvalue=2
5 , minvalue=3
3 , minvalue=3
9 , minvalue=7
7 , minvalue=7
8 , minvalue=8
在以上表示中，堆栈仅由左值构建，而右值的[minvalue]仅出于说明目的而编写，将存储在一个变量中。
实际的问题是，当获取的最小值为最小值时，我们如何才能知道下一个最小元素是什么，而无需遍历堆栈。
例如，在我们的堆栈中，当弹出6个get时，我们知道，这不是最小元素，因为最小元素是2，所以我们可以安全地删除它而无需更新最小值。
但是当我们弹出2时，我们可以看到最小值现在是2，如果弹出该弹出框，则需要将最小值更新为3。
Point1：
现在，如果您仔细观察，我们需要从此特定状态[2，minvalue = 2]生成minvalue = 3。 或者，如果您在堆栈中使用depper，我们需要根据此特定状态[3，minvalue = 3]生成minvalue = 7 或者，如果您在堆栈中使用更多的depper，那么我们需要根据此特定状态[7，minvalue = 7]生成minvalue = 8
在上述3种情况下，您是否注意到一些共同点，我们需要生成的值取决于两个相等的变量。正确。 发生这种情况的原因是，当我们将某个元素推到比当前的最小值小时，然后我们基本上将该元素推入堆栈，并在minvalue中也更新相同的数字。
Point2：
因此，我们基本上是将相同数量的重复项一次存储在堆栈中，一次存储在minvalue变量中。 我们需要集中精力避免这种重复，并在堆栈或最小值中存储一些有用的数据，以生成先前的最小值，如上面的案例所示。
让我们关注当要存储在push中的值小于minmumvalue时，我们应该在堆栈中存储什么。 让我们将变量y命名为，这样我们的堆栈将看起来像这样：
6 , minvalue=2
y1 , minvalue=2
5 , minvalue=3
y2 , minvalue=3
9 , minvalue=7
y3 , minvalue=7
8 , minvalue=8
我将它们重命名为y1，y2，y3，以避免造成混淆，因为它们都具有相同的值。
Point3：
现在，让我们尝试查找y1，y2和y3上的一些约束。
您是否还记得仅在弹出等于最小值的元素时才需要在执行pop（）时更新最小值。
如果我们弹出比最小值大的值，则不必更新最小值。
因此，要触发最小值更新，y1，y2＆y3应该小于相应的最小值。[我们正在避免相等，以避免重复[Point2]]
因此约束为[y 现在让我们返回以填充y，我们需要生成一些值并将y放入push时，记住。
让我们将推入的值设为x，它小于prevMinvalue，而我们将实际推入堆栈的值设为y。
因此很明显，newMinValue = x和y 现在我们需要借助prevMinvalue和x（newMinvalue）来计算y（请记住y可以是小于newMinValue（x）的任何数字，因此我们需要找到一些可以满足约束的数字）。 因此，在推送x时，如果它小于prevMinvalue，则我们推送y [2 * x-prevMinValue]并更新newMinValue = x。 在弹出时，如果堆栈中包含的内容小于minValue，那么这就是我们更新minVAlue的触发条件。
我们必须根据curMinValue和y计算prevMinValue。
y = 2 * curMinValue-prevMinValue [已验证]
prevMinVAlue = 2 * curMinvalue-y。 2 * curMinValue-y是我们现在需要更新为prevMinValue的数字。 同一逻辑的代码在下面以O（1）时间和O（1）空间复杂度共享。Let's do the math:
x < prevMinvalue [Given]
x - prevMinvalue < 0
x - prevMinValue + x < 0 + x [Add x on both side]
2*x - prevMinValue < x
this is the y which we were looking for less than x(newMinValue).
y = 2*x - prevMinValue. 'or' y = 2*newMinValue - prevMinValue 'or' y = 2*curMinValue - prevMinValue [taking curMinValue=newMinValue].
// C++ program to implement a stack that supports
// getMinimum() in O(1) time and O(1) extra space.
#include <bits/stdc++.h>
using namespace std;
// A user defined stack that supports getMin() in
// addition to push() and pop()
struct MyStack
{
stack<int> s;
int minEle;
// Prints minimum element of MyStack
void getMin()
{
if (s.empty())
cout << "Stack is empty\n";
// variable minEle stores the minimum element
// in the stack.
else
cout <<"Minimum Element in the stack is: "
<< minEle << "\n";
}
// Prints top element of MyStack
void peek()
{
if (s.empty())
{
cout << "Stack is empty ";
return;
}
int t = s.top(); // Top element.
cout << "Top Most Element is: ";
// If t < minEle means minEle stores
// value of t.
(t < minEle)? cout << minEle: cout << t;
}
// Remove the top element from MyStack
void pop()
{
if (s.empty())
{
cout << "Stack is empty\n";
return;
}
cout << "Top Most Element Removed: ";
int t = s.top();
s.pop();
// Minimum will change as the minimum element
// of the stack is being removed.
if (t < minEle)
{
cout << minEle << "\n";
minEle = 2*minEle - t;
}
else
cout << t << "\n";
}
// Removes top element from MyStack
void push(int x)
{
// Insert new number into the stack
if (s.empty())
{
minEle = x;
s.push(x);
cout << "Number Inserted: " << x << "\n";
return;
}
// If new number is less than minEle
if (x < minEle)
{
s.push(2*x - minEle);
minEle = x;
}
else
s.push(x);
cout << "Number Inserted: " << x << "\n";
}
};
// Driver Code
int main()
{
MyStack s;
s.push(3);
s.push(5);
s.getMin();
s.push(2);
s.push(1);
s.getMin();
s.pop();
s.getMin();
s.pop();
s.peek();
return 0;
}
答案 16 :(得分：0)
我们可以在O（n）时间和O（1）空间复杂度中执行此操作，如下所示：
class MinStackOptimized:
def __init__(self):
self.stack = []
self.min = None
def push(self, x):
if not self.stack:
# stack is empty therefore directly add
self.stack.append(x)
self.min = x
else:
"""
Directly add (x-self.min) to the stack. This also ensures anytime we have a
negative number on the stack is when x was less than existing minimum
recorded thus far.
"""
self.stack.append(x-self.min)
if x < self.min:
# Update x to new min
self.min = x
def pop(self):
x = self.stack.pop()
if x < 0:
"""
if popped element was negative therefore this was the minimum
element, whose actual value is in self.min but stored value is what
contributes to get the next min. (this is one of the trick we use to ensure
we are able to get old minimum once current minimum gets popped proof is given
below in pop method), value stored during push was:
(x - self.old_min) and self.min = x therefore we need to backtrack
these steps self.min(current) - stack_value(x) actually implies to
x (self.min) - (x - self.old_min)
which therefore gives old_min back and therefore can now be set
back as current self.min.
"""
self.min = self.min - x
def top(self):
x = self.stack[-1]
if x < 0:
"""
As discussed above anytime there is a negative value on stack, this
is the min value so far and therefore actual value is in self.min,
current stack value is just for getting the next min at the time
this gets popped.
"""
return self.min
else:
"""
if top element of the stack was positive then it's simple, it was
not the minimum at the time of pushing it and therefore what we did
was x(actual) - self.min(min element at current stage) let's say `y`
therefore we just need to reverse the process to get the actual
value. Therefore self.min + y, which would translate to
self.min + x(actual) - self.min, thereby giving x(actual) back
as desired.
"""
return x + self.min
def getMin(self):
# Always self.min variable holds the minimum so for so easy peezy.
return self.min
答案 17 :(得分：0)
这是Jon Skeets Answer的C ++实现。 它可能不是实现它的最佳方式，但它完全符合它的预期。
class Stack {
private:
struct stack_node {
int val;
stack_node *next;
};
stack_node *top;
stack_node *min_top;
public:
Stack() {
top = nullptr;
min_top = nullptr;
}
void push(int num) {
stack_node *new_node = nullptr;
new_node = new stack_node;
new_node->val = num;
if (is_empty()) {
top = new_node;
new_node->next = nullptr;
min_top = new_node;
new_node->next = nullptr;
} else {
new_node->next = top;
top = new_node;
if (new_node->val <= min_top->val) {
new_node->next = min_top;
min_top = new_node;
}
}
}
void pop(int &num) {
stack_node *tmp_node = nullptr;
stack_node *min_tmp = nullptr;
if (is_empty()) {
std::cout << "It's empty\n";
} else {
num = top->val;
if (top->val == min_top->val) {
min_tmp = min_top->next;
delete min_top;
min_top = min_tmp;
}
tmp_node = top->next;
delete top;
top = tmp_node;
}
}
bool is_empty() const {
return !top;
}
void get_min(int &item) {
item = min_top->val;
}
};
这是班级的驱动程序
int main() {
int pop, min_el;
Stack my_stack;
my_stack.push(4);
my_stack.push(6);
my_stack.push(88);
my_stack.push(1);
my_stack.push(234);
my_stack.push(2);
my_stack.get_min(min_el);
cout << "Min: " << min_el << endl;
my_stack.pop(pop);
cout << "Popped stock element: " << pop << endl;
my_stack.pop(pop);
cout << "Popped stock element: " << pop << endl;
my_stack.pop(pop);
cout << "Popped stock element: " << pop << endl;
my_stack.get_min(min_el);
cout << "Min: " << min_el << endl;
return 0;
}
输出：
Min: 1
Popped stock element: 2
Popped stock element: 234
Popped stock element: 1
Min: 4
答案 18 :(得分：0)
在用户设计对象堆栈中查找最小值的实际实现， 命名：学校
Stack将根据分配给特定地区学校的排名存储Stack in Schools，例如，findMin（）为学校提供入学申请的最大数量，而申请人数最多为由比较者定义，该比较者使用与上一季的学校相关的等级。
The Code for same is below:
package com.practical;
import java.util.Collections;
import java.util.Iterator;
import java.util.LinkedList;
import java.util.List;
import java.util.Stack;
public class CognitaStack {
public School findMin(Stack<School> stack, Stack<School> minStack) {
if (!stack.empty() && !minStack.isEmpty())
return (School) minStack.peek();
return null;
}
public School removeSchool(Stack<School> stack, Stack<School> minStack) {
if (stack.isEmpty())
return null;
School temp = stack.peek();
if (temp != null) {
// if(temp.compare(stack.peek(), minStack.peek())<0){
stack.pop();
minStack.pop();
// }
// stack.pop();
}
return stack.peek();
}
public static void main(String args[]) {
Stack<School> stack = new Stack<School>();
Stack<School> minStack = new Stack<School>();
List<School> lst = new LinkedList<School>();
School s1 = new School("Polam School", "London", 3);
School s2 = new School("AKELEY WOOD SENIOR SCHOOL", "BUCKINGHAM", 4);
School s3 = new School("QUINTON HOUSE SCHOOL", "NORTHAMPTON", 2);
School s4 = new School("OAKLEIGH HOUSE SCHOOL", " SWANSEA", 5);
School s5 = new School("OAKLEIGH-OAK HIGH SCHOOL", "Devon", 1);
School s6 = new School("BritishInter2", "Devon", 7);
lst.add(s1);
lst.add(s2);
lst.add(s3);
lst.add(s4);
lst.add(s5);
lst.add(s6);
Iterator<School> itr = lst.iterator();
while (itr.hasNext()) {
School temp = itr.next();
if ((minStack.isEmpty()) || (temp.compare(temp, minStack.peek()) < 0)) { // minStack.peek().equals(temp)
stack.push(temp);
minStack.push(temp);
} else {
minStack.push(minStack.peek());
stack.push(temp);
}
}
CognitaStack cogStack = new CognitaStack();
System.out.println(" Minimum in Stack is " + cogStack.findMin(stack, minStack).name);
cogStack.removeSchool(stack, minStack);
cogStack.removeSchool(stack, minStack);
System.out.println(" Minimum in Stack is "
+ ((cogStack.findMin(stack, minStack) != null) ? cogStack.findMin(stack, minStack).name : "Empty"));
}
}
学校对象如下：
package com.practical;
import java.util.Comparator;
public class School implements Comparator<School> {
String name;
String location;
int rank;
public School(String name, String location, int rank) {
super();
this.name = name;
this.location = location;
this.rank = rank;
}
@Override
public int hashCode() {
final int prime = 31;
int result = 1;
result = prime * result + ((location == null) ? 0 : location.hashCode());
result = prime * result + ((name == null) ? 0 : name.hashCode());
result = prime * result + rank;
return result;
}
@Override
public boolean equals(Object obj) {
if (this == obj)
return true;
if (obj == null)
return false;
if (getClass() != obj.getClass())
return false;
School other = (School) obj;
if (location == null) {
if (other.location != null)
return false;
} else if (!location.equals(other.location))
return false;
if (name == null) {
if (other.name != null)
return false;
} else if (!name.equals(other.name))
return false;
if (rank != other.rank)
return false;
return true;
}
public String getName() {
return name;
}
public void setName(String name) {
this.name = name;
}
public String getLocation() {
return location;
}
public void setLocation(String location) {
this.location = location;
}
public int getRank() {
return rank;
}
public void setRank(int rank) {
this.rank = rank;
}
public int compare(School o1, School o2) {
// TODO Auto-generated method stub
return o1.rank - o2.rank;
}
}
class SchoolComparator implements Comparator<School> {
public int compare(School o1, School o2) {
return o1.rank - o2.rank;
}
}
此示例包含以下内容： 1.用户定义对象的堆栈实现，这里是School 2.使用要比较的对象的所有字段的hashcode（）和equals（）方法的实现 3.我们为获取堆栈包含操作的场景的实际实现是按O（1）
的顺序答案 19 :(得分：0)
**The task can be acheived by creating two stacks:**
import java.util.Stack;
/*
*
* Find min in stack using O(n) Space Complexity
*/
public class DeleteMinFromStack {
void createStack(Stack<Integer> primary, Stack<Integer> minStack, int[] arr) {
/* Create main Stack and in parallel create the stack which contains the minimum seen so far while creating main Stack */
primary.push(arr[0]);
minStack.push(arr[0]);
for (int i = 1; i < arr.length; i++) {
primary.push(arr[i]);
if (arr[i] <= minStack.peek())// Condition to check to push the value in minimum stack only when this urrent value is less than value seen at top of this stack */
minStack.push(arr[i]);
}
}
int findMin(Stack<Integer> secStack) {
return secStack.peek();
}
public static void main(String args[]) {
Stack<Integer> primaryStack = new Stack<Integer>();
Stack<Integer> minStack = new Stack<Integer>();
DeleteMinFromStack deleteMinFromStack = new DeleteMinFromStack();
int[] arr = { 5, 5, 6, 8, 13, 1, 11, 6, 12 };
deleteMinFromStack.createStack(primaryStack, minStack, arr);
int mimElement = deleteMinFromStack.findMin(primaryStack, minStack);
/** This check for algorithm when the main Stack Shrinks by size say i as in loop below */
for (int i = 0; i < 2; i++) {
primaryStack.pop();
}
System.out.println(" Minimum element is " + mimElement);
}
}
/*
here in have tried to add for loop wherin the main tack can be shrinked/expaned so we can check the algorithm */
答案 20 :(得分：0)
这是我用O（1）运行的代码。在这里，我使用向量对，其中包含推送的值，并且还包含最小值，直到此推送值。
这是我的C ++实现版本。
vector<pair<int,int> >A;
int sz=0; // to keep track of the size of vector
class MinStack
{
public:
MinStack()
{
A.clear();
sz=0;
}
void push(int x)
{
int mn=(sz==0)?x: min(A[sz-1].second,x); //find the minimum value upto this pushed value
A.push_back(make_pair(x,mn));
sz++; // increment the size
}
void pop()
{
if(sz==0) return;
A.pop_back(); // pop the last inserted element
sz--; // decrement size
}
int top()
{
if(sz==0) return -1; // if stack empty return -1
return A[sz-1].first; // return the top element
}
int getMin()
{
if(sz==0) return -1;
return A[sz-1].second; // return the minimum value at sz-1
}
};
答案 21 :(得分：0)
class FastStack {
private static class StackNode {
private Integer data;
private StackNode nextMin;
public StackNode(Integer data) {
this.data = data;
}
public Integer getData() {
return data;
}
public void setData(Integer data) {
this.data = data;
}
public StackNode getNextMin() {
return nextMin;
}
public void setNextMin(StackNode nextMin) {
this.nextMin = nextMin;
}
}
private LinkedList<StackNode> stack = new LinkedList<>();
private StackNode currentMin = null;
public void push(Integer item) {
StackNode node = new StackNode(item);
if (currentMin == null) {
currentMin = node;
node.setNextMin(null);
} else if (item < currentMin.getData()) {
StackNode oldMinNode = currentMin;
node.setNextMin(oldMinNode);
currentMin = node;
}
stack.addFirst(node);
}
public Integer pop() {
if (stack.isEmpty()) {
throw new EmptyStackException();
}
StackNode node = stack.peek();
if (currentMin == node) {
currentMin = node.getNextMin();
}
stack.removeFirst();
return node.getData();
}
public Integer getMinimum() {
if (stack.isEmpty()) {
throw new NoSuchElementException("Stack is empty");
}
return currentMin.getData();
}
}
答案 22 :(得分：0)
这里的Jon Skeet's answer中解释的PHP实现是稍微好一点的空间复杂度实现，以获得O（1）中的最大堆栈。
<?php
/**
* An ordinary stack implementation.
*
* In real life we could just extend the built-in "SplStack" class.
*/
class BaseIntegerStack
{
/**
* Stack main storage.
*
* @var array
*/
private $storage = [];
// ------------------------------------------------------------------------
// Public API
// ------------------------------------------------------------------------
/**
* Pushes to stack.
*
* @param int $value New item.
*
* @return bool
*/
public function push($value)
{
return is_integer($value)
? (bool) array_push($this->storage, $value)
: false;
}
/**
* Pops an element off the stack.
*
* @return int
*/
public function pop()
{
return array_pop($this->storage);
}
/**
* See what's on top of the stack.
*
* @return int|bool
*/
public function top()
{
return empty($this->storage)
? false
: end($this->storage);
}
// ------------------------------------------------------------------------
// Magic methods
// ------------------------------------------------------------------------
/**
* String representation of the stack.
*
* @return string
*/
public function __toString()
{
return implode('|', $this->storage);
}
} // End of BaseIntegerStack class
/**
* The stack implementation with getMax() method in O(1).
*/
class Stack extends BaseIntegerStack
{
/**
* Internal stack to keep track of main stack max values.
*
* @var BaseIntegerStack
*/
private $maxStack;
/**
* Stack class constructor.
*
* Dependencies are injected.
*
* @param BaseIntegerStack $stack Internal stack.
*
* @return void
*/
public function __construct(BaseIntegerStack $stack)
{
$this->maxStack = $stack;
}
// ------------------------------------------------------------------------
// Public API
// ------------------------------------------------------------------------
/**
* Prepends an item into the stack maintaining max values.
*
* @param int $value New item to push to the stack.
*
* @return bool
*/
public function push($value)
{
if ($this->isNewMax($value)) {
$this->maxStack->push($value);
}
parent::push($value);
}
/**
* Pops an element off the stack maintaining max values.
*
* @return int
*/
public function pop()
{
$popped = parent::pop();
if ($popped == $this->maxStack->top()) {
$this->maxStack->pop();
}
return $popped;
}
/**
* Finds the maximum of stack in O(1).
*
* @return int
* @see push()
*/
public function getMax()
{
return $this->maxStack->top();
}
// ------------------------------------------------------------------------
// Internal helpers
// ------------------------------------------------------------------------
/**
* Checks that passing value is a new stack max or not.
*
* @param int $new New integer to check.
*
* @return boolean
*/
private function isNewMax($new)
{
return empty($this->maxStack) OR $new > $this->maxStack->top();
}
} // End of Stack class
// ------------------------------------------------------------------------
// Stack Consumption and Test
// ------------------------------------------------------------------------
$stack = new Stack(
new BaseIntegerStack
);
$stack->push(9);
$stack->push(4);
$stack->push(237);
$stack->push(5);
$stack->push(556);
$stack->push(15);
print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n\n";
print "Pop: {$stack->pop()}\n";
print "Pop: {$stack->pop()}\n\n";
print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n\n";
print "Pop: {$stack->pop()}\n";
print "Pop: {$stack->pop()}\n\n";
print "Stack: $stack\n";
print "Max: {$stack->getMax()}\n";
// Here's the sample output:
//
// Stack: 9|4|237|5|556|15
// Max: 556
//
// Pop: 15
// Pop: 556
//
// Stack: 9|4|237|5
// Max: 237
//
// Pop: 5
// Pop: 237
//
// Stack: 9|4
// Max: 9
答案 23 :(得分：0)
class MyStackImplementation{
private final int capacity = 4;
int min;
int arr[] = new int[capacity];
int top = -1;
public void push ( int val ) {
top++;
if(top <= capacity-1){
if(top == 0){
min = val;
arr[top] = val;
}
else if(val < min){
arr[top] = arr[top]+min;
min = arr[top]-min;
arr[top] = arr[top]-min;
}
else {
arr[top] = val;
}
System.out.println("element is pushed");
}
else System.out.println("stack is full");
}
public void pop () {
top--;
if(top > -1){
min = arr[top];
}
else {min=0; System.out.println("stack is under flow");}
}
public int min(){
return min;
}
public boolean isEmpty () {
return top == 0;
}
public static void main(String...s){
MyStackImplementation msi = new MyStackImplementation();
msi.push(1);
msi.push(4);
msi.push(2);
msi.push(10);
System.out.println(msi.min);
msi.pop();
msi.pop();
msi.pop();
msi.pop();
msi.pop();
System.out.println(msi.min);
}
}
答案 24 :(得分：0)
struct Node {
let data: Int
init(_ d:Int){
data = d
}
}
struct Stack {
private var backingStore = [Node]()
private var minArray = [Int]()
mutating func push(n:Node) {
backingStore.append(n)
minArray.append(n.data)
minArray.sort(>)
minArray
}
mutating func pop() -> Node? {
if(backingStore.isEmpty){
return nil
}
let n = backingStore.removeLast()
var found = false
minArray = minArray.filter{
if (!found && $0 == n.data) {
found = true
return false
}
return true
}
return n
}
func min() -> Int? {
return minArray.last
}
}
答案 25 :(得分：0)
我找到了这个解决方案here
struct StackGetMin {
void push(int x) {
elements.push(x);
if (minStack.empty() || x <= minStack.top())
minStack.push(x);
}
bool pop() {
if (elements.empty()) return false;
if (elements.top() == minStack.top())
minStack.pop();
elements.pop();
return true;
}
bool getMin(int &min) {
if (minStack.empty()) {
return false;
} else {
min = minStack.top();
return true;
}
}
stack<int> elements;
stack<int> minStack;
};
答案 26 :(得分：0)
#include<stdio.h>
struct stack
{
int data;
int mindata;
}a[100];
void push(int *tos,int input)
{
if (*tos > 100)
{
printf("overflow");
return;
}
(*tos)++;
a[(*tos)].data=input;
if (0 == *tos)
a[*tos].mindata=input;
else if (a[*tos -1].mindata < input)
a[*tos].mindata=a[*tos -1].mindata;
else
a[*tos].mindata=input;
}
int pop(int * tos)
{
if (*tos <= -1)
{
printf("underflow");
return -1;
}
return(a[(*tos)--].data);
}
void display(int tos)
{
while (tos > -1)
{
printf("%d:%d\t",a[tos].data,a[tos].mindata);
tos--;
}
}
int min(int tos)
{
return(a[tos].mindata);
}
int main()
{
int tos=-1,x,choice;
while(1)
{
printf("press 1-push,2-pop,3-mindata,4-display,5-exit ");
scanf("%d",&choice);
switch(choice)
{
case 1: printf("enter data to push");
scanf("%d",&x);
push(&tos,x);
break;
case 2: printf("the poped out data=%d ",pop(&tos));
break;
case 3: printf("The min peeped data:%d",min(tos));
break;
case 4: printf("The elements of stack \n");
display(tos);
break;
default: exit(0);
}
}
答案 27 :(得分：0)
public class MinStack<E>{
private final LinkedList<E> mainStack = new LinkedList<E>();
private final LinkedList<E> minStack = new LinkedList<E>();
private final Comparator<E> comparator;
public MinStack(Comparator<E> comparator)
{
this.comparator = comparator;
}
/**
* Pushes an element onto the stack.
*
*
* @param e the element to push
*/
public void push(E e) {
mainStack.push(e);
if(minStack.isEmpty())
{
minStack.push(e);
}
else if(comparator.compare(e, minStack.peek())<=0)
{
minStack.push(e);
}
else
{
minStack.push(minStack.peek());
}
}
/**
* Pops an element from the stack.
*
*
* @throws NoSuchElementException if this stack is empty
*/
public E pop() {
minStack.pop();
return mainStack.pop();
}
/**
* Returns but not remove smallest element from the stack. Return null if stack is empty.
*
*/
public E getMinimum()
{
return minStack.peek();
}
@Override
public String toString() {
StringBuilder sb = new StringBuilder();
sb.append("Main stack{");
for (E e : mainStack) {
sb.append(e.toString()).append(",");
}
sb.append("}");
sb.append(" Min stack{");
for (E e : minStack) {
sb.append(e.toString()).append(",");
}
sb.append("}");
sb.append(" Minimum = ").append(getMinimum());
return sb.toString();
}
public static void main(String[] args) {
MinStack<Integer> st = new MinStack<Integer>(Comparators.INTEGERS);
st.push(2);
Assert.assertTrue("2 is min in stack {2}", st.getMinimum().equals(2));
System.out.println(st);
st.push(6);
Assert.assertTrue("2 is min in stack {2,6}", st.getMinimum().equals(2));
System.out.println(st);
st.push(4);
Assert.assertTrue("2 is min in stack {2,6,4}", st.getMinimum().equals(2));
System.out.println(st);
st.push(1);
Assert.assertTrue("1 is min in stack {2,6,4,1}", st.getMinimum().equals(1));
System.out.println(st);
st.push(5);
Assert.assertTrue("1 is min in stack {2,6,4,1,5}", st.getMinimum().equals(1));
System.out.println(st);
st.pop();
Assert.assertTrue("1 is min in stack {2,6,4,1}", st.getMinimum().equals(1));
System.out.println(st);
st.pop();
Assert.assertTrue("2 is min in stack {2,6,4}", st.getMinimum().equals(2));
System.out.println(st);
st.pop();
Assert.assertTrue("2 is min in stack {2,6}", st.getMinimum().equals(2));
System.out.println(st);
st.pop();
Assert.assertTrue("2 is min in stack {2}", st.getMinimum().equals(2));
System.out.println(st);
st.pop();
Assert.assertTrue("null is min in stack {}", st.getMinimum()==null);
System.out.println(st);
}
}
答案 28 :(得分：0)
这是我的实施版本。
struct MyStack {
int element;
int *CurrentMiniAddress;
};
void Push(int value)
{
// Create you structure and populate the value
MyStack S = new MyStack();
S->element = value;
if(Stack.Empty())
{
// Since the stack is empty, point CurrentMiniAddress to itself
S->CurrentMiniAddress = S;
}
else
{
// Stack is not empty
// Retrieve the top element. No Pop()
MyStack *TopElement = Stack.Top();
// Remember Always the TOP element points to the
// minimum element in ths whole stack
if (S->element CurrentMiniAddress->element)
{
// If the current value is the minimum in the whole stack
// then S points to itself
S->CurrentMiniAddress = S;
}
else
{
// So this is not the minimum in the whole stack
// No worries, TOP is holding the minimum element
S->CurrentMiniAddress = TopElement->CurrentMiniAddress;
}
}
Stack.Add(S);
}
void Pop()
{
if(!Stack.Empty())
{
Stack.Pop();
}
}
int GetMinimum(Stack &stack)
{
if(!stack.Empty())
{
MyStack *Top = stack.top();
// Top always points to the minimumx
return Top->CurrentMiniAddress->element;
}
}
答案 29 :(得分：-1)
public interface IMinStack<T extends Comparable<T>> {
public void push(T val);
public T pop();
public T minValue();
public int size();
}
import java.util.Stack;
public class MinStack<T extends Comparable<T>> implements IMinStack<T> {
private Stack<T> stack = new Stack<T>();
private Stack<T> minStack = new Stack<T>();
@Override
public void push(T val) {
stack.push(val);
if (minStack.isEmpty() || val.compareTo(minStack.peek()) < 0)
minStack.push(val);
}
@Override
public T pop() {
T val = stack.pop();
if ((false == minStack.isEmpty())
&& val.compareTo(minStack.peek()) == 0)
minStack.pop();
return val;
}
@Override
public T minValue() {
return minStack.peek();
}
@Override
public int size() {
return stack.size();
}
}
答案 30 :(得分：-1)
我认为只有推动操作受损，就足够了。我的实现包括一堆节点。每个节点都包含数据项，也包含该时刻的最小值。每次执行推送操作时都会更新此最小值。
以下是理解的一些要点：
我使用Linked List实现了堆栈。
指针顶部始终指向最后一个按下的项目。当该堆栈中没有项目时，顶部为NULL。
当按下某个项目时，会分配一个新节点，该节点具有指向前一个堆栈的下一个指针，并且顶部会更新为指向此新节点。
与普通堆栈实现的区别仅在于它在推送期间更新了新节点的成员min。
请查看用C ++实现的代码以供演示。
/*
* Implementation of Stack that can give minimum in O(1) time all the time
* This solution uses same data structure for minimum variable, it could be implemented using pointers but that will be more space consuming
*/
#include <iostream>
using namespace std;
typedef struct stackLLNodeType stackLLNode;
struct stackLLNodeType {
int item;
int min;
stackLLNode *next;
};
class DynamicStack {
private:
int stackSize;
stackLLNode *top;
public:
DynamicStack();
~DynamicStack();
void push(int x);
int pop();
int getMin();
int size() { return stackSize; }
};
void pushOperation(DynamicStack& p_stackObj, int item);
void popOperation(DynamicStack& p_stackObj);
int main () {
DynamicStack stackObj;
pushOperation(stackObj, 3);
pushOperation(stackObj, 1);
pushOperation(stackObj, 2);
popOperation(stackObj);
popOperation(stackObj);
popOperation(stackObj);
popOperation(stackObj);
pushOperation(stackObj, 4);
pushOperation(stackObj, 7);
pushOperation(stackObj, 6);
popOperation(stackObj);
popOperation(stackObj);
popOperation(stackObj);
popOperation(stackObj);
return 0;
}
DynamicStack::DynamicStack() {
// initialization
stackSize = 0;
top = NULL;
}
DynamicStack::~DynamicStack() {
stackLLNode* tmp;
// chain memory deallocation to avoid memory leak
while (top) {
tmp = top;
top = top->next;
delete tmp;
}
}
void DynamicStack::push(int x) {
// allocate memory for new node assign to top
if (top==NULL) {
top = new stackLLNode;
top->item = x;
top->next = NULL;
top->min = top->item;
}
else {
// allocation of memory
stackLLNode *tmp = new stackLLNode;
// assign the new item
tmp->item = x;
tmp->next = top;
// store the minimum so that it does not get lost after pop operation of later minimum
if (x < top->min)
tmp->min = x;
else
tmp->min = top->min;
// update top to new node
top = tmp;
}
stackSize++;
}
int DynamicStack::pop() {
// check if stack is empty
if (top == NULL)
return -1;
stackLLNode* tmp = top;
int curItem = top->item;
top = top->next;
delete tmp;
stackSize--;
return curItem;
}
int DynamicStack::getMin() {
if (top == NULL)
return -1;
return top->min;
}
void pushOperation(DynamicStack& p_stackObj, int item) {
cout<<"Just pushed: "<<item<<endl;
p_stackObj.push(item);
cout<<"Current stack min: "<<p_stackObj.getMin()<<endl;
cout<<"Current stack size: "<<p_stackObj.size()<<endl<<endl;
}
void popOperation(DynamicStack& p_stackObj) {
int popItem = -1;
if ((popItem = p_stackObj.pop()) == -1 )
cout<<"Cannot pop. Stack is empty."<<endl;
else {
cout<<"Just popped: "<<popItem<<endl;
if (p_stackObj.getMin() == -1)
cout<<"No minimum. Stack is empty."<<endl;
else
cout<<"Current stack min: "<<p_stackObj.getMin()<<endl;
cout<<"Current stack size: "<<p_stackObj.size()<<endl<<endl;
}
}
程序的输出如下：
Just pushed: 3
Current stack min: 3
Current stack size: 1
Just pushed: 1
Current stack min: 1
Current stack size: 2
Just pushed: 2
Current stack min: 1
Current stack size: 3
Just popped: 2
Current stack min: 1
Current stack size: 2
Just popped: 1
Current stack min: 3
Current stack size: 1
Just popped: 3
No minimum. Stack is empty.
Current stack size: 0
Cannot pop. Stack is empty.
Just pushed: 4
Current stack min: 4
Current stack size: 1
Just pushed: 7
Current stack min: 4
Current stack size: 2
Just pushed: 6
Current stack min: 4
Current stack size: 3
Just popped: 6
Current stack min: 4
Current stack size: 2
Just popped: 7
Current stack min: 4
Current stack size: 1
Just popped: 4
No minimum. Stack is empty.
Current stack size: 0
Cannot pop. Stack is empty.