算法训练营Day50(动态规划11)

说明

较难,二刷再仔细打代码

123.买卖股票的最佳时机III  力扣(LeetCode)官网 - 全球极客挚爱的技术成长平台

提醒

这道题一下子就难度上来了,关键在于至多买卖两次,这意味着可以买卖一次,可以买卖两次,也可以不买卖

class Solution:
    def maxProfit(self, prices: List[int]) -> int:
        if len(prices) == 0:
            return 0
        dp = [[0] * 5 for _ in range(len(prices))]
        dp[0][1] = -prices[0]
        dp[0][3] = -prices[0]
        for i in range(1, len(prices)):
            dp[i][0] = dp[i-1][0]
            dp[i][1] = max(dp[i-1][1], dp[i-1][0] - prices[i])
            dp[i][2] = max(dp[i-1][2], dp[i-1][1] + prices[i])
            dp[i][3] = max(dp[i-1][3], dp[i-1][2] - prices[i])
            dp[i][4] = max(dp[i-1][4], dp[i-1][3] + prices[i])
        return dp[-1][4]

188.买卖股票的最佳时机IV  力扣(LeetCode)官网 - 全球极客挚爱的技术成长平台

提醒

本题是123.买卖股票的最佳时机III 的进阶版  

class Solution:
    def maxProfit(self, k: int, prices: List[int]) -> int:
        if len(prices) == 0:
            return 0
        dp = [[0] * (2*k+1) for _ in range(len(prices))]
        for j in range(1, 2*k, 2):
            dp[0][j] = -prices[0]
        for i in range(1, len(prices)):
            for j in range(0, 2*k-1, 2):
                dp[i][j+1] = max(dp[i-1][j+1], dp[i-1][j] - prices[i])
                dp[i][j+2] = max(dp[i-1][j+2], dp[i-1][j+1] + prices[i])
        return dp[-1][2*k]

你可能感兴趣的:(动态规划,算法)