#! /usr/bin/env python
# -*- coding: utf-8 -*-
# author: Crise
# date: 27/07/20

"""
题目描述：
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)

"""


class Solution:
    def FindGreatestSumOfSubArray(self, array):
        # write code here
        if len(array) == 0:
            return 0

        max_num = array[0]
        continuous_sum = 0
        for num in array:
            if continuous_sum > 0:
                continuous_sum += num
            else:
                continuous_sum = num
            max_num = max(continuous_sum, max_num)

        return max_num


if __name__ == "__main__":
    array = [6, -3, -2, 7, -15, 1, 2, 2]
    print(Solution().FindGreatestSumOfSubArray(array))

a28147c11ed5d6fbc6e6c5bd132d145aa0a065cb
<mask token>

<mask token>


class Solution:
    <mask token>


<mask token>

<mask token>


class Solution:

    def FindGreatestSumOfSubArray(self, array):
        if len(array) == 0:
            return 0
        max_num = array[0]
        continuous_sum = 0
        for num in array:
            if continuous_sum > 0:
                continuous_sum += num
            else:
                continuous_sum = num
            max_num = max(continuous_sum, max_num)
        return max_num


<mask token>

<mask token>


class Solution:

    def FindGreatestSumOfSubArray(self, array):
        if len(array) == 0:
            return 0
        max_num = array[0]
        continuous_sum = 0
        for num in array:
            if continuous_sum > 0:
                continuous_sum += num
            else:
                continuous_sum = num
            max_num = max(continuous_sum, max_num)
        return max_num


if __name__ == '__main__':
    array = [6, -3, -2, 7, -15, 1, 2, 2]
    print(Solution().FindGreatestSumOfSubArray(array))

#! /usr/bin/env python
# -*- coding: utf-8 -*-
# author: Crise
# date: 27/07/20

"""
题目描述：
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)

"""


class Solution:
    def FindGreatestSumOfSubArray(self, array):
        # write code here
        if len(array) == 0:
            return 0

        max_num = array[0]
        continuous_sum = 0
        for num in array:
            if continuous_sum > 0:
                continuous_sum += num
            else:
                continuous_sum = num
            max_num = max(continuous_sum, max_num)

        return max_num


if __name__ == "__main__":
    array = [6, -3, -2, 7, -15, 1, 2, 2]
    print(Solution().FindGreatestSumOfSubArray(array))
