Solve Maximum Subarray Problem Using Kadane's Algorithm in Python



When it is required to find the maximum sub array using Kadane’s algorithm, a method is defined that helps find the maximum of the sub array. Iterators are used to keep track of the maximum sub array.

Below is the demonstration of the same −

Example

 Live Demo

def find_max_sub_array(my_list, beg, end):    max_end_at_i = max_seen_till_now = my_list[beg]    max_left_at_i = max_left_till_now = beg    max_right_till_now = beg + 1    for i in range(beg + 1, end):       if max_end_at_i > 0:          max_end_at_i += my_list[i]       else:          max_end_at_i = my_list[i]          max_left_at_i = i       if max_end_at_i > max_seen_till_now:          max_seen_till_now = max_end_at_i          max_left_till_now = max_left_at_i          max_right_till_now = i + 1    return max_left_till_now, max_right_till_now, max_seen_till_now my_list = input('Enter the list of numbers... ') my_list = my_list.split() my_list = [int(x) for x in my_list] beg, end, max_val = find_max_sub_array(my_list, 0, len(my_list)) print('The maximum subarray begins at index {}, ends at index {}'    ' and its sum is {}.'.format(beg, end - 1, max_val))

Output

Enter the list of numbers... 2 5 7 12 6 8 The maximum subarray begins at index 0, ends at index 5 and its sum is 40.

Explanation

  • A method named ‘find_max_sub_array’ is defined that takes three parameters.

  • The maximum sub array within a given range is found.

  • It returns a tuple where the left, right indices of the maximum sub array are returned along with its sum.

  • A loop is used to keep a check on the maximum sub array that ends at index i.

  • This is the maximum of all sub arrays.

  • The method also keeps track of maximum sum of the sub array seen until now, as the loop iterates through the left and right indices.

  • Outside the method, the list of numbers is taken as input by the user.

  • This is passed as a parameter to the method.

  • It is displayed as output on the console.

Updated on: 2021-04-17T12:06:47+05:30

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