Hard
Maximize Alternating Sum Using Swaps — Python
Full explanation · Time O(n + s) · Space O(n + s)
# Time: O(n + s)
# Space: O(n + s)
import random
# bfs, flood fill, quick select
class Solution(object):
def maxAlternatingSum(self, nums, swaps):
"""
:type nums: List[int]
:type swaps: List[List[int]]
:rtype: int
"""
def nth_element(nums, n, compare=lambda a, b: a < b):
def tri_partition(nums, left, right, target, compare):
mid = left
while mid <= right:
if nums[mid] == target:
mid += 1
elif compare(nums[mid], target):
nums[left], nums[mid] = nums[mid], nums[left]
left += 1
mid += 1
else:
nums[mid], nums[right] = nums[right], nums[mid]
right -= 1
return left, right
left, right = 0, len(nums)-1
while left <= right:
pivot_idx = random.randint(left, right)
pivot_left, pivot_right = tri_partition(nums, left, right, nums[pivot_idx], compare)
if pivot_left <= n <= pivot_right:
return
elif pivot_left > n:
right = pivot_left-1
else: # pivot_right < n.
left = pivot_right+1
def bfs(u):
q = []
if lookup[u]:
return q
lookup[u] = True
q.append(u)
for u in q:
for v in adj[u]:
if lookup[v]:
continue
lookup[v] = True
q.append(v)
return q
adj = [[] for _ in xrange(len(nums))]
for i, j in swaps:
adj[i].append(j)
adj[j].append(i)
lookup = [False]*len(adj)
result = sum(nums)
for u in xrange(len(nums)):
g = bfs(u)
if not g:
continue
l = sum(i%2 for i in g)
arr = [nums[i] for i in g]
nth_element(arr, l)
result -= 2*sum(arr[i] for i in xrange(l))
return result