DP Max Subarray Sum¶
Table of Contents¶
- 53. Maximum Subarray (Medium)
- 2606. Find the Substring With Maximum Cost (Medium)
- 1749. Maximum Absolute Sum of Any Subarray (Medium)
- 1191. K-Concatenation Maximum Sum (Medium)
- 918. Maximum Sum Circular Subarray (Medium)
- 2321. Maximum Score Of Spliced Array (Hard)
- 152. Maximum Product Subarray (Medium)
53. Maximum Subarray¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, divide and conquer, dynamic programming
53. Maximum Subarray - Python Solution
from typing import List
# DP Kadane
def maxSubArrayDP(nums: List[int]) -> int:
dp = [0 for _ in range(len(nums))]
dp[0] = nums[0]
maxSum = nums[0]
for i in range(1, len(nums)):
dp[i] = max(
dp[i - 1] + nums[i], # continue the previous subarray
nums[i], # start a new subarray
)
maxSum = max(maxSum, dp[i])
return maxSum
# Greedy
def maxSubArrayGreedy(nums: List[int]) -> int:
max_sum = nums[0]
cur_sum = 0
for num in nums:
cur_sum = max(cur_sum + num, num)
max_sum = max(max_sum, cur_sum)
return max_sum
# Prefix Sum
def maxSubArrayPrefixSum(nums: List[int]) -> int:
prefix_sum = 0
prefix_sum_min = 0
res = float("-inf")
for num in nums:
prefix_sum += num
res = max(res, prefix_sum - prefix_sum_min)
prefix_sum_min = min(prefix_sum_min, prefix_sum)
return res
nums = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
print(maxSubArrayDP(nums)) # 6
print(maxSubArrayGreedy(nums)) # 6
print(maxSubArrayPrefixSum(nums)) # 6
2606. Find the Substring With Maximum Cost¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, hash table, string, dynamic programming
1749. Maximum Absolute Sum of Any Subarray¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, dynamic programming
1191. K-Concatenation Maximum Sum¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, dynamic programming
918. Maximum Sum Circular Subarray¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, divide and conquer, dynamic programming, queue, monotonic queue
918. Maximum Sum Circular Subarray - Python Solution
from collections import deque
from typing import List
# DP - Kadane
def maxSubarraySumCircularKadane(nums: List[int]) -> int:
max_sum = min_sum = nums[0]
max_cur = min_cur = 0
total = 0
for num in nums:
max_cur = max(max_cur + num, num)
min_cur = min(min_cur + num, num)
total += num
max_sum = max(max_sum, max_cur)
min_sum = min(min_sum, min_cur)
return max(max_sum, total - min_sum) if max_sum > 0 else max_sum
# Monotonic Queue
def maxSubarraySumCircularMQ(nums: List[int]) -> int:
n = len(nums)
prefix_sum = [0] * (2 * n + 1)
for i in range(1, 2 * n + 1):
prefix_sum[i] = prefix_sum[i - 1] + nums[(i - 1) % n]
q = deque([0])
max_sum = float("-inf")
for i in range(1, 2 * n + 1):
if q[0] < i - n:
q.popleft()
max_sum = max(max_sum, prefix_sum[i] - prefix_sum[q[0]])
while q and prefix_sum[q[-1]] >= prefix_sum[i]:
q.pop()
q.append(i)
return max_sum
nums = [1, -2, 3, -2]
print(maxSubarraySumCircularKadane(nums)) # 3
print(maxSubarraySumCircularMQ(nums)) # 3
2321. Maximum Score Of Spliced Array¶
-
LeetCode | LeetCode CH (Hard)
-
Tags: array, dynamic programming
152. Maximum Product Subarray¶
-
LeetCode | LeetCode CH (Medium)
-
Tags: array, dynamic programming
152. Maximum Product Subarray - Python Solution
from typing import List
# DP - Kadane
def maxProduct(nums: List[int]) -> int:
n = len(nums)
dp_max = [0 for _ in range(n)]
dp_min = [0 for _ in range(n)]
dp_max[0] = nums[0]
dp_min[0] = nums[0]
max_product = nums[0]
for i in range(1, n):
dp_max[i] = max(
nums[i],
nums[i] * dp_max[i - 1],
nums[i] * dp_min[i - 1],
)
dp_min[i] = min(
nums[i],
nums[i] * dp_max[i - 1],
nums[i] * dp_min[i - 1],
)
max_product = max(max_product, dp_max[i])
return max_product
nums = [2, 3, -2, 4]
print(maxProduct(nums)) # 6