Largest Sum Contiguous Subarray

Write an efficient Python program to find the sum of contiguous subarray within a one-dimensional array of numbers which has the largest sum.

kadane Algorithm

 

 

 

 

 

 

 

 

 

 

 

Kadane’s Algorithm:

Initialize:
    max_so_far = 0
    max_ending_here = 0

Loop for each element of the array
  (a) max_ending_here = max_ending_here + a[i]
  (b) if(max_ending_here < 0)
            max_ending_here = 0
  (c) if(max_so_far < max_ending_here)
            max_so_far = max_ending_here
return max_so_far
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Explanation:

Simple idea of the Kadane’s algorithm is to look for all positive contiguous segments of the array (max_ending_here is used for this). And keep track of maximum sum contiguous segment among all positive segments (max_so_far is used for this). Each time we get a positive sum compare it with max_so_far and update max_so_far if it is greater than max_so_far

    Lets take the example:
    {-2, -3, 4, -1, -2, 1, 5, -3}

    max_so_far = max_ending_here = 0

    for i=0,  a[0] =  -2
    max_ending_here = max_ending_here + (-2)
    Set max_ending_here = 0 because max_ending_here < 0

    for i=1,  a[1] =  -3
    max_ending_here = max_ending_here + (-3)
    Set max_ending_here = 0 because max_ending_here < 0

    for i=2,  a[2] =  4
    max_ending_here = max_ending_here + (4)
    max_ending_here = 4
    max_so_far is updated to 4 because max_ending_here greater 
    than max_so_far which was 0 till now

    for i=3,  a[3] =  -1
    max_ending_here = max_ending_here + (-1)
    max_ending_here = 3

    for i=4,  a[4] =  -2
    max_ending_here = max_ending_here + (-2)
    max_ending_here = 1

    for i=5,  a[5] =  1
    max_ending_here = max_ending_here + (1)
    max_ending_here = 2

    for i=6,  a[6] =  5
    max_ending_here = max_ending_here + (5)
    max_ending_here = 7
    max_so_far is updated to 7 because max_ending_here is 
    greater than max_so_far

    for i=7,  a[7] =  -3
    max_ending_here = max_ending_here + (-3)
    max_ending_here = 4
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Program for Largest Sum Contiguous Subarray

Python

# Python program to find maximum contiguous subarray

# Function to find the maximum contiguous subarray
from sys import maxint
def maxSubArraySum(a,size):

max_so_far = -maxint - 1
max_ending_here = 0

for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if (max_so_far < max_ending_here):
max_so_far = max_ending_here

if max_ending_here < 0:
max_ending_here = 0
return max_so_far

# Driver function to check the above function
a = [-13, -3, -25, -20, -3, -16, -23, -12, -5, -22, -15, -4, -7]
print "Maximum contiguous sum is", maxSubArraySum(a,len(a))

Output :

Maximum contiguous sum is -3

Above program can be optimized further, if we compare max_so_far with max_ending_here only if max_ending_here is greater than 0.

Program

Python

def maxSubArraySum(a,size):

max_so_far = 0
max_ending_here = 0

for i in range(0, size):
max_ending_here = max_ending_here + a[i]
if max_ending_here < 0:
max_ending_here = 0

# Do not compare for all elements. Compare only
# when max_ending_here > 0
elif (max_so_far < max_ending_here):
max_so_far = max_ending_here

return max_so_far

Time Complexity: O(n)
Algorithmic Paradigm: Dynamic Programming

The implementation handles the case when all numbers in array are negative.

Program

Python

# Python program to find maximum contiguous subarray

def maxSubArraySum(a,size):

max_so_far =a[0]
curr_max = a[0]

for i in range(1,size):
curr_max = max(a[i], curr_max + a[i])
max_so_far = max(max_so_far,curr_max)

return max_so_far

# Driver function to check the above function
a = [-2, -3, 4, -1, -2, 1, 5, -3]
print"Maximum contiguous sum is" , maxSubArraySum(a,len(a))

Output :

Maximum contiguous sum is 7

To print the subarray with the maximum sum, we maintain indices whenever we get the maximum sum.

Program

Python
# Python program to print largest contiguous array sum 

from sys import maxsize

# Function to find the maximum contiguous subarray
# and print its starting and end index
def maxSubArraySum(a,size):

max_so_far = -maxsize - 1
max_ending_here = 0
start = 0
end = 0
s = 0

for i in range(0,size):

max_ending_here += a[i]

if max_so_far < max_ending_here:
max_so_far = max_ending_here
start = s
end = i

if max_ending_here < 0:
max_ending_here = 0
s = i+1

print ("Maximum contiguous sum is %d"%(max_so_far))
print ("Starting Index %d"%(start))
print ("Ending Index %d"%(end))

# Driver program to test maxSubArraySum
a = [-2, -3, 4, -1, -2, 1, 5, -3]
maxSubArraySum(a,len(a))
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Output :

Maximum contiguous sum is 7
Starting index 2
Ending index 6

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