Say you have an array for which the ith element is the price of a given stock on day i.

Design an algorithm to find the maximum profit. You may complete at most two transactions.

Note: You may not engage in multiple transactions at the same time (i.e., you must sell the stock before you buy again).

Example 1:

Input: [3,3,5,0,0,3,1,4]
Output: 6
Explanation: Buy on day 4 (price = 0) and sell on day 6 (price = 3), profit = 3-0 = 3.
  Then buy on day 7 (price = 1) and sell on day 8 (price = 4), profit = 4-1 = 3.

Example 2:

Input: [1,2,3,4,5]
Output: 4
Explanation: Buy on day 1 (price = 1) and sell on day 5 (price = 5), profit = 5-1 = 4.
  Note that you cannot buy on day 1, buy on day 2 and sell them later, as you are
  engaging multiple transactions at the same time. You must sell before buying again.

Example 3:

Input: [7,6,4,3,1]
Output: 0
Explanation: In this case, no transaction is done, i.e. max profit = 0.

给定一个元素代表某股票每天价格的数组,最多可以买卖股票2次,还是不能同时有多个交易,买之前要卖出,求最大利润。

两次买卖在时间跨度上不能有重叠(当然第一次的卖出时间和第二次的买入时间可以是同一天)。既然不能有重叠可以将整个序列以任意坐标i为分割点,分割成两部分:

prices[0:n-1] => prices[0:i] + prices[i:n-1],对于这个分割来说,最大收益为两段的最大收益之和。每一段的最大收益用I的解法来做。最大收益是对所有0<=i<=n-1的分割的最大收益取一个最大值。

1. 计算A[0:i]的收益最大值:用minPrice记录i左边的最低价格,用maxLeftProfit记录左侧最大收益
2. 计算A[i:n-1]的收益最大值:用maxPrices记录i右边的最高价格,用maxRightProfit记录右侧最大收益。
3. 最后这两个收益之和便是以i为分割的最大收益。将序列从左向右扫一遍可以获取dp1,从右向左扫一遍可以获取dp2。相加后取最大值即为答案。

时间复杂度O(n), 空间复杂度O(n)

Java:Divide and conquer

public class Solution {
public int maxProfit(int[] prices) {
// find maxProfit for {0, j}, find maxProfit for {j + 1, n - 1}
// find max for {max{0, j}, max{j + 1, n - 1}} if (prices == null || prices.length == 0) {
return 0;
} int maximumProfit = 0;
int n = prices.length; ArrayList<Profit> preMaxProfit = new ArrayList<Profit>(n);
ArrayList<Profit> postMaxProfit = new ArrayList<Profit>(n);
for (int i = 0; i < n; i++) {
preMaxProfit.add(maxProfitHelper(prices, 0, i));
postMaxProfit.add(maxProfitHelper(prices, i + 1, n - 1));
}
for (int i = 0; i < n; i++) {
int profit = preMaxProfit.get(i).maxProfit + postMaxProfit.get(i).maxProfit;
maximumProfit = Math.max(profit, maximumProfit);
}
return maximumProfit;
} private Profit maxProfitHelper(int[] prices, int startIndex, int endIndex) {
int minPrice = Integer.MAX_VALUE;
int maxProfit = 0;
for (int i = startIndex; i <= endIndex; i++) {
if (prices[i] < minPrice) {
minPrice = prices[i];
}
if (prices[i] - minPrice > maxProfit) {
maxProfit = prices[i] - minPrice;
}
}
return new Profit(maxProfit, minPrice);
} public static void main(String[] args) {
int[] prices = new int[]{4,4,6,1,1,4,2,5};
Solution s = new Solution();
System.out.println(s.maxProfit(prices));
}
}; class Profit {
int maxProfit, minPrice;
Profit(int maxProfit, int minPrice) {
this.maxProfit = maxProfit;
this.minPrice = minPrice;
}
}

Java:DP

public class Solution {
public int maxProfit(int[] prices) {
if (prices == null || prices.length <= 1) {
return 0;
} int[] left = new int[prices.length];
int[] right = new int[prices.length]; // DP from left to right;
left[0] = 0;
int min = prices[0];
for (int i = 1; i < prices.length; i++) {
min = Math.min(prices[i], min);
left[i] = Math.max(left[i - 1], prices[i] - min);
} //DP from right to left;
right[prices.length - 1] = 0;
int max = prices[prices.length - 1];
for (int i = prices.length - 2; i >= 0; i--) {
max = Math.max(prices[i], max);
right[i] = Math.max(right[i + 1], max - prices[i]);
} int profit = 0;
for (int i = 0; i < prices.length; i++){
profit = Math.max(left[i] + right[i], profit);
} return profit;
}
}

Python:T:O(n), S: O(n)

class Solution3:
def maxProfit(self, prices):
min_price, max_profit_from_left, max_profits_from_left = float("inf"), 0, []
for price in prices:
min_price = min(min_price, price)
max_profit_from_left = max(max_profit_from_left, price - min_price)
max_profits_from_left.append(max_profit_from_left) max_price, max_profit_from_right, max_profits_from_right = 0, 0, []
for i in reversed(range(len(prices))):
max_price = max(max_price, prices[i])
max_profit_from_right = max(max_profit_from_right, max_price - prices[i])
max_profits_from_right.insert(0, max_profit_from_right) max_profit = 0
for i in range(len(prices)):
max_profit = max(max_profit, max_profits_from_left[i] + max_profits_from_right[i]) return max_profit

Python:

class Solution:
def maxProfit(self, prices):
hold1, hold2 = float("-inf"), float("-inf")
release1, release2 = 0, 0
for i in prices:
release2 = max(release2, hold2 + i)
hold2 = max(hold2, release1 - i)
release1 = max(release1, hold1 + i)
hold1 = max(hold1, -i);
return release2  

C++:DP

class Solution {
public:
int maxProfit(vector<int> &prices) {
if(prices.empty()) return 0;
int n = prices.size();
vector<int> leftProfit(n,0); int maxLeftProfit = 0, minPrice = prices[0];
for(int i=1; i<n; i++) {
if(prices[i]<minPrice)
minPrice = prices[i];
else
maxLeftProfit = max(maxLeftProfit, prices[i]-minPrice);
leftProfit[i] = maxLeftProfit;
} int ret = leftProfit[n-1];
int maxRightProfit = 0, maxPrice = prices[n-1];
for(int i=n-2; i>=0; i--) {
if(prices[i]>maxPrice)
maxPrice = prices[i];
else
maxRightProfit = max(maxRightProfit, maxPrice-prices[i]);
ret = max(ret, maxRightProfit + leftProfit[i]);
} return ret;
}
};

  

类似题目:

[LeetCode] 121. Best Time to Buy and Sell Stock 买卖股票的最佳时间

[LeetCode] 122. Best Time to Buy and Sell Stock II 买卖股票的最佳时间 II

[LeetCode] 188. Best Time to Buy and Sell Stock IV 买卖股票的最佳时间 IV

[LeetCode] 309. Best Time to Buy and Sell Stock with Cooldown 买卖股票的最佳时间有冷却期

All LeetCode Questions List 题目汇总

  

[LeetCode] 123. Best Time to Buy and Sell Stock III 买卖股票的最佳时间 III的更多相关文章

  1. [LeetCode] 122. Best Time to Buy and Sell Stock II 买卖股票的最佳时间 II

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

  2. [LeetCode] 188. Best Time to Buy and Sell Stock IV 买卖股票的最佳时间 IV

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

  3. [LeetCode] Best Time to Buy and Sell Stock IV 买卖股票的最佳时间之四

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

  4. LeetCode 121. Best Time to Buy and Sell Stock (买卖股票的最好时机)

    Say you have an array for which the ith element is the price of a given stock on day i. If you were ...

  5. [LeetCode] Best Time to Buy and Sell Stock with Cooldown 买股票的最佳时间含冷冻期

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

  6. LN : leetcode 123 Best Time to Buy and Sell Stock III

    lc 123 Best Time to Buy and Sell Stock III 123 Best Time to Buy and Sell Stock III Say you have an a ...

  7. [leetcode]123. Best Time to Buy and Sell Stock III 最佳炒股时机之三

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

  8. 122 Best Time to Buy and Sell Stock II 买卖股票的最佳时机 II

    假设有一个数组,它的第 i 个元素是一个给定的股票在第 i 天的价格.设计一个算法来找到最大的利润.你可以完成尽可能多的交易(多次买卖股票).然而,你不能同时参与多个交易(你必须在再次购买前出售股票) ...

  9. Java for LeetCode 123 Best Time to Buy and Sell Stock III【HARD】

    Say you have an array for which the ith element is the price of a given stock on day i. Design an al ...

随机推荐

  1. 正则爬取京东商品信息并打包成.exe可执行程序。

    本文爬取内容,输入要搜索的关键字可自动爬取京东网站上相关商品的店铺名称,商品名称,价格,爬取100页(共100页) 代码如下: import requests import re # 请求头 head ...

  2. 基于源代码为树莓派设备构建 TensorFlow

    本指南为运行 Raspbian 9.0 操作系统的 Raspberry Pi 嵌入式设备构建 TensorFlow.虽然这些说明可能也适用于其他系列的 Raspberry Pi 设备,但它仅针对此文中 ...

  3. LGOJP2051 [AHOI2009]中国象棋

    比较明显的计数dp.不知道为什么被打了状压的tag... 不难发现无论炮放在哪里其实是等价的,需要知道的只有这一列放了一个炮还是两个炮还是还没放,那么可以设\(f[i,j,k]\)表示第\(i\)行, ...

  4. 2019-2020-1 20199301《Linux内核原理与分析》第九周作业

    第八章 进程的切换和系统的一般执行过程 进程的调度实际与进程的切换 ntel定义的中断类型 硬中断:就是CPU的两根引脚(可屏蔽中断和不可屏蔽中断) 软中断/异常:包括除零错误.系统调用.调试断点等在 ...

  5. IN8005 Exercise Session

    Exercise Session for Introductioninto Computer Science(for non Informatics studies, TUM BWL)(IN8005) ...

  6. reshape()函数

    """ 1.当原始数组A[4,6]为二维数组,代表4行6列. A.reshape(-1,8):表示将数组转换成8列的数组,具体多少行我们不知道,所以参数设为-1.用我们的 ...

  7. python的readline() 和readlines()

    .readline() 和 .readlines() 之间的差异是后者一次读取整个文件,象 .read() 一样..readlines() 自动将文件内容分析成一个行的列表,该列表可以由 Python ...

  8. junit4的初级用法

    junit4初级用法: 一:各个标签的意思 1.@Test用来标注测试函数 2.@Before用来标注此函数在每次测试函数运行之前运行(每执行一个@Test之前都要运行一遍@Before) 3.@Af ...

  9. BZOJ 3166: [Heoi2013]Alo 链表+可持久化trie

    链表这个东西非常好用啊 ~ code: #include <bits/stdc++.h> #define N 50010 #define inf 2000400000 #define se ...

  10. rep stos dword ptr es:[edi]

    本文链接:https://blog.csdn.net/ypist/article/details/8467163今天读代码时,忽然跳出如下一条指令==>>汇编代码: rep stos dw ...