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0053 添加python动态规划解法和动态规划优化解法
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@ -229,6 +229,42 @@ class Solution:
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```
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```
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动态规划
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```python
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class Solution:
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def maxSubArray(self, nums):
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if not nums:
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return 0
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dp = [0] * len(nums) # dp[i]表示包括i之前的最大连续子序列和
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dp[0] = nums[0]
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result = dp[0]
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for i in range(1, len(nums)):
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dp[i] = max(dp[i-1]+nums[i], nums[i]) # 状态转移公式
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if dp[i] > result:
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result = dp[i] # result 保存dp[i]的最大值
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return result
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```
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动态规划优化
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```python
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class Solution:
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def maxSubArray(self, nums: List[int]) -> int:
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max_sum = float("-inf") # 初始化结果为负无穷大,方便比较取最大值
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current_sum = 0 # 初始化当前连续和
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for num in nums:
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# 更新当前连续和
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# 如果原本的连续和加上当前数字之后没有当前数字大,说明原本的连续和是负数,那么就直接从当前数字开始重新计算连续和
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current_sum = max(current_sum+num, num)
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max_sum = max(max_sum, current_sum) # 更新结果
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return max_sum
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```
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### Go
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### Go
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贪心法
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贪心法
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```go
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```go
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