152. Maximum Product Subarray最大乘积子数组/是否连续

[抄题]:

Given an integer array nums, find the contiguous subarray within an array (containing at least one number) which has the largest product.

Example 1:

Input: [2,3,-2,4]
Output: 6
Explanation: [2,3] has the largest product 6.

Example 2:

Input: [-2,0,-1]
Output: 0
Explanation: The result cannot be 2, because [-2,-1] is not a subarray.

[暴力解法]:

时间分析:

空间分析:

[优化后]:

时间分析:

空间分析:

[奇葩输出条件]:

Your input
[2,3,-2,4]
Your answer
24
Expected answer
6

[奇葩corner case]:

[思维问题]:

[英文数据结构或算法,为什么不用别的数据结构或算法]:

记忆化搜索的dp,划分型 kandane

[一句话思路]:

max = Math.max(max, max * nums[i]);是记忆化搜索,能保证全局最优解24;

maxhere = Math.max(Math.max(maxherepre * A[i], minherepre * A[i]), A[i]);

保证二者之间相对较大,只能保证负号之前的局部最优解6

maxherepre = maxhere;
minhere用的是之前存好的maxherepre,不是改变后的maxhere。所以要提前存。

[输入量]:空: 正常情况:特大:特小:程序里处理到的特殊情况:异常情况(不合法不合理的输入):

[画图]:

[一刷]:

[二刷]:

[三刷]:

[四刷]:

[五刷]:

[五分钟肉眼debug的结果]:

[总结]:

minhere用的是之前存好的maxherepre,不是改变后的maxhere。所以要提前存。

[复杂度]:Time complexity: O(n) Space complexity: O(1)

[算法思想:迭代/递归/分治/贪心]:

[关键模板化代码]:

[其他解法]:

[Follow Up]:

[LC给出的题目变变变]:

[代码风格] :

[是否头一次写此类driver funcion的代码] :

[潜台词] :

Local optimal solution

class Solution {
public int maxProduct(int[] nums) {
//cc
if (nums == null || nums.length == 0) return 0; //ini: 5 variables
int maxHere = nums[0];
int minHere = nums[0];
int maxHerePre = nums[0];
int minHerePre = nums[0];
int result = nums[0]; //calculate
for (int i = 1; i < nums.length; i++) {
maxHere = Math.max(Math.max(maxHerePre * nums[i], minHerePre * nums[i]), nums[i]);
minHere = Math.min(Math.min(maxHerePre * nums[i], minHerePre * nums[i]), nums[i]);
maxHerePre = maxHere;
minHerePre = minHere;
result = Math.max(result, maxHere);
} //return
return result;
}
}
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