上篇用有限状态机来求解,其实也是进行了一遍扫描,只是我把问题考虑的复杂了。python
对于扫描,我以为首先要问本身3个问题:算法
1. 如何扫描 (这里是遍历数组元素)数组
2. 每次扫描会改变什么 (这里的算法会改变maxendinghere,前一篇的算法是改变状态)spa
3. 改变的东西会对结果有影响么 (maxendinghere若是大于maxsofar,那么maxsofar就被赋值为maxendinghere).net
不一样的考虑问题的方式引入不一样的解决方案,其中的差距太大了!!前一篇我太关注正负号了,致使我采用了序列分段,状态转移的方式去解决问题;这里的解法关注最大和,以及有可能影响最大和的因素,maxsofar和maxendinghere的相对大小。虽然时间复杂度都是O(n),可是,高下立现!code
代码以下(python):get
#!/usr/bin/python def scan(vector): # return (maxsofar, low, high) length = len(vector) maxsofar = 0 maxendinghere = 0 low = 0 high = 0 low2 = 0 high2 = 0 for i in range(0, length): if maxendinghere + vector[i] > 0: maxendinghere = maxendinghere + vector[i] high2 = i+1 else: maxendinghere = 0 low2 = i+1 if maxsofar >= maxendinghere: high = high low = low maxsofar = maxsofar else: high = high2 low = low2 maxsofar = maxendinghere return (maxsofar, low, high) def test(): vector = [-1, -1, -1, -1] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print vector = [1, -1, -1, -1] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print vector = [-1, -1, -1, 1] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print vector = [-1, 2, 3, -4] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print vector = [1, 2, 3, 4] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print vector = [31, -41, 59, 26, -53, 58, 97, -93, -23, 84] (maxsofar, low, high) = scan(vector) print vector print maxsofar, low, high print def main(): test() if __name__ == '__main__': main()
运行结果:class
root@localhost :/home/James/mypro/Python# ./scan.py
[-1, -1, -1, -1]
0 0 0test
[1, -1, -1, -1]
1 0 1遍历
[-1, -1, -1, 1]
1 3 4
[-1, 2, 3, -4]
5 1 3
[1, 2, 3, 4]
10 0 4
[31, -41, 59, 26, -53, 58, 97, -93, -23, 84]
187 2 7
root@localhost :/home/James/mypro/Python#
后记:感受python真的很适合写这种小demo,又快又方便。