【leetcode】689. Maximum Sum of 3 Non-Overlapping Subarrays
题目如下:
In a given array
numsof positive integers, find three non-overlapping subarrays with maximum sum.Each subarray will be of size
k, and we want to maximize the sum of all3*kentries.Return the result as a list of indices representing the starting position of each interval (0-indexed). If there are multiple answers, return the lexicographically smallest one.
Example:
Input: [1,2,1,2,6,7,5,1], 2
Output: [0, 3, 5]
Explanation: Subarrays [1, 2], [2, 6], [7, 5] correspond to the starting indices [0, 3, 5].
We could have also taken [2, 1], but an answer of [1, 3, 5] would be lexicographically larger.Note:
nums.lengthwill be between 1 and 20000.nums[i]will be between 1 and 65535.kwill be between 1 and floor(nums.length / 3).
解题思路:本题如果只要求求出三段子数组的和的最大值,那会简单很多。记total[i]为arr[i:i+k]段的和,dp_left_max[i]为nums[:i]区间内长度为k的子数组的和的最大值,dp_right_max[i]为nums[i:len(nums)]区间内长度为k的子数组的和的最大值,很显然如果中间段的子数组的下标为k,那么可以得到三段和的最大长度的表达:total[i] + dp_left_max[i-k] + dp_right_max[i+k] 。只要遍历数组arr,即可求出最大值。求出后就是计算出左边以及右边最大值出现时的最小下标,这个可以通过二分查找实现。
代码如下:
class Solution(object):
def maxSumOfThreeSubarrays(self, nums, k):
"""
:type nums: List[int]
:type k: int
:rtype: List[int]
"""
count = sum(nums[:k])
total = [count]
total_inx = {}
total_inx[count] = [0]
dp_left_max = [count]
dp_left_max_count = count
for i in range(k, len(nums)):
count -= nums[i - k]
count += nums[i]
total += [count]
total_inx[count] = total_inx.setdefault(count,[]) + [i-k + 1]
dp_left_max_count = max(dp_left_max_count,count)
dp_left_max.append(dp_left_max_count) reverse_num = nums[::-1]
count = sum(reverse_num[:k])
dp_right_max = [count]
dp_right_max_count = count
for i in range(k, len(reverse_num)):
count -= reverse_num[i - k]
count += reverse_num[i]
dp_right_max_count = max(dp_right_max_count,count)
dp_right_max.insert(0,dp_right_max_count) #print total
#print total_inx
#print dp_left_max
#print dp_right_max max_sum = -float('inf')
mid_inx = 0
left_val = 0
right_val = 0
for i in range(k,len(nums)-k-k+1):
count = total[i] + dp_left_max[i-k] + dp_right_max[i+k]
if count > max_sum:
mid_inx = i
left_val = dp_left_max[i-k]
right_val = dp_right_max[i+k]
max_sum = count
#print left_val,mid_inx,right_val left_inx = total_inx[left_val][0]
import bisect
right_inx = bisect.bisect_left(total_inx[right_val],mid_inx+k)
return [left_inx,mid_inx,total_inx[right_val][right_inx]]
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