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Update 0416. 分割等和子集.md

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Original file line number	Diff line number	Diff line change
`@@ -73,14 +73,17 @@ $dp[w] = \begin{cases} dp[w] & w < nums[i - 1] \cr max \lbrace dp[w], dp[w - num`
`73`	`73`
`74`	`74`	```Python
`75`	`75`	`class Solution:`
`76`		`- def zeroOnePackOptimization(self, weight: [int], value: [int], W: int):`
	`76`	`+ def zeroOnePack(self, weight: [int], value: [int], W: int):`
`77`	`77`	`size = len(weight)`
`78`	`78`	`dp = [0 for _ in range(W + 1)]`
`79`	`79`
	`80`	`+ # 枚举前 i 种物品`
`80`	`81`	`for i in range(1, size + 1):`
	`82`	`+ # 逆序枚举背包装载重量(避免状态值错误)`
`81`	`83`	`for w in range(W, weight[i - 1] - 1, -1):`
	`84`	`+ # dp[w] 取「前 i - 1 件物品装入载重为 w 的背包中的最大价值」与「前 i - 1 件物品装入载重为 w - weight[i - 1] 的背包中,再装入第 i - 1 物品所得的最大价值」两者中的最大值`
`82`	`85`	`dp[w] = max(dp[w], dp[w - weight[i - 1]] + value[i - 1])`
`83`		`-`
	`86`	`+`
`84`	`87`	`return dp[W]`
`85`	`88`
`86`	`89`	`def canPartition(self, nums: List[int]) -> bool:`
`@@ -89,7 +92,7 @@ class Solution:`
`89`	`92`	`return False`
`90`	`93`
`91`	`94`	`target = sum_nums // 2`
`92`		`- return self.zeroOnePackOptimization(nums, nums, target) == target`
	`95`	`+ return self.zeroOnePack(nums, nums, target) == target`
`93`	`96`	```
`94`	`97`
`95`	`98`	`### 思路 1:复杂度分析`

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