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maximize-points-after-choosing-k-tasks.py
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61 lines (54 loc) · 2.17 KB
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# Time: O(n)
# Space: O(n)
import random
# quick select, greedy
class Solution(object):
def maxPoints(self, technique1, technique2, k):
"""
:type technique1: List[int]
:type technique2: List[int]
:type k: int
:rtype: int
"""
def nth_element(nums, n, left=0, 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
right = 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
idxs = range(len(technique1))
if k != len(technique1):
nth_element(idxs, k-1, compare=lambda a, b: technique1[a]-technique2[a] > technique1[b]-technique2[b])
return sum(technique1[idxs[i]] if i < k else max(technique1[idxs[i]], technique2[idxs[i]]) for i in xrange(len(technique1)))
# Time: O(nlogn)
# Space: O(n)
# sort, greedy
class Solution2(object):
def maxPoints(self, technique1, technique2, k):
"""
:type technique1: List[int]
:type technique2: List[int]
:type k: int
:rtype: int
"""
idxs = range(len(technique1))
idxs.sort(key=lambda i: technique1[i]-technique2[i], reverse=True)
return sum(technique1[idxs[i]] if i < k else max(technique1[idxs[i]], technique2[idxs[i]]) for i in xrange(len(technique1)))