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# 连续子数组的最大和

## 题目

https://www.nowcoder.com/practice/459bd355da1549fa8a49e350bf3df484

## 描述

HZ偶尔会拿些专业问题来忽悠那些非计算机专业的同学。今天测试组开完会后,他又发话了:在古老的一维模式识别中,常常需要计算连续子向量的最大和,当向量全为正数的时候,问题很好解决。但是,如果向量中包含负数,是否应该包含某个负数,并期望旁边的正数会弥补它呢？例如:{6,-3,-2,7,-15,1,2,2},连续子向量的最大和为8(从第0个开始,到第3个为止)。给一个数组，返回它的最大连续子序列的和，你会不会被他忽悠住？(子向量的长度至少是1)

## 代码

class Solution:
def FindGreatestSumOfSubArray(self, array):
# write code here
maxSum = None
for i in range(len(array)):
sum = 0
for j in range(i, len(array)):
sum += array[j]
if sum > maxSum:
maxSum = sum
return maxSum

## 代码2

class Solution:
def FindGreatestSumOfSubArray(self, array):
# write code here
maxNum = None
tmpNum = 0
for i in array:
if maxNum == None:
maxNum = i
if tmpNum + i < i:
tmpNum = i
else:
tmpNum += i
if maxNum < tmpNum:
maxNum = tmpNum
return maxNum

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