Find Largest Sum Contiguous Subarray
Understanding the Problem
The goal is to find the subarray with the maximum sum in a given array using different methods.
Method 1: Kadane's Algorithm
This method efficiently finds the largest sum contiguous subarray using dynamic programming.
def max_subarray_sum(arr):
max_so_far = arr[0]
max_ending_here = arr[0]
for i in range(1, len(arr)):
max_ending_here = max(arr[i], max_ending_here + arr[i])
max_so_far = max(max_so_far, max_ending_here)
return max_so_far
arr = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
print("Maximum contiguous sum:", max_subarray_sum(arr))
Output:
Maximum contiguous sum: 6
Method 2: Divide and Conquer
This method finds the largest sum subarray by dividing the array into halves recursively.
def max_crossing_sum(arr, l, m, h):
left_sum = float('-inf')
sum = 0
for i in range(m, l - 1, -1):
sum += arr[i]
left_sum = max(left_sum, sum)
right_sum = float('-inf')
sum = 0
for i in range(m + 1, h + 1):
sum += arr[i]
right_sum = max(right_sum, sum)
return max(left_sum + right_sum, left_sum, right_sum)
def max_subarray_sum(arr, l, h):
if l == h:
return arr[l]
m = (l + h) // 2
return max(max_subarray_sum(arr, l, m),
max_subarray_sum(arr, m + 1, h),
max_crossing_sum(arr, l, m, h))
arr = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
n = len(arr)
print("Maximum contiguous sum:", max_subarray_sum(arr, 0, n - 1))
Output:
Maximum contiguous sum: 7
Method 3: Brute Force
This method checks all subarrays and computes their sums to find the maximum sum.
def max_subarray_sum(arr):
max_sum = float('-inf')
for i in range(len(arr)):
current_sum = 0
for j in range(i, len(arr)):
current_sum += arr[j]
max_sum = max(max_sum, current_sum)
return max_sum
arr = [-2, 1, -3, 4, -1, 2, 1, -5, 4]
print("Maximum contiguous sum:", max_subarray_sum(arr))
Output:
Maximum contiguous sum: 6