Data Structure and Algorithms
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  • Data Structure
    • Min Stack
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    • Subarray Sum
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  • Misc
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  • Array and Numbers
    • Merge Sorted Array
    • Merge Two Sorted Arrays
    • Median of two Sorted Arrays
    • Best Time to Buy and Sell Stock
    • Best Time to Buy and Sell Stock II
    • Best Time to Buy and Sell Stock III
    • Maximum Subarray
    • Maximum Subarray II
    • Maximum Subarray III
    • Minimum Subarray
    • Maximum Subarray Difference
    • Subarray Sum
    • Subarray Sum Closest
    • Two Sum
    • 3Sum
    • 3Sum Closest
    • 4Sum
    • k Sum
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    • Partition Array
    • Sort Letters by Case
    • Sort Colors
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    • Interleaving Positive and Negative Numbers
    • Spiral Matrix
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  • Dynamic Programming I
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    • Climbing Stairs
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    • 01 Matrix
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  • Dynamic Programming II
    • Word Break
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  • Binary Tree And Divide Conquer
    • Binary Tree Preorder Traversal*
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    • Maximum Depth of Binary Tree
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    • Balanced Binary Tree
    • Lowest Common Ancestor
    • Binary Tree Maximum Path Sum
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    • Binary Tree Level Order Traversal*
    • Binary Tree Level Order Traversal II
    • Binary Tree Zigzag Level Order Traversal
    • Validate Binary Search Tree
    • Inorder Successor in Binary Search Tree
    • Binary Search Tree Iterator
    • Search Range in Binary Search Tree
    • Insert Node in a Binary Search Tree
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    • Find the kth largest element in the BST
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    • Serialize and Deserialize Binary Tree*
    • Construct Binary Tree from Preorder and Inorder Traversal
    • Convert Sorted Array to Binary Search Tree
    • Unique Binary Search Trees *
    • Unique Binary Search Trees II *
    • Recover Binary Search Tree
    • Same Tree
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    • Path Sum*
    • Path Sum II*
    • Flatten Binary Tree to Linked List
    • Populating Next Right Pointers in Each Node
    • Sum Root to Leaf Numbers
    • Binary Tree Right Side View
    • Count Complete Tree Nodes
    • Invert Binary Tree
    • Binary Tree Paths*
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  1. Array and Numbers

Maximum Subarray Difference

Given an array with integers.

Find two non-overlapping subarrays A and B, which |SUM(A) - SUM(B)| is the largest.

Return the largest difference.

Example

For [1, 2, -3, 1], return 6.

Solution

leftmin - right[i+1] max

leftmax- right[i+ 1] min,

don't do left[i + 1] and make sure right is i + 1

we need to create 4 arary here.

class Solution:
    """
    @param nums: A list of integers
    @return: An integer indicate the value of maximum difference between two
             Subarrays
    """
    def maxDiffSubArrays(self, nums):
        # write your code here
        total = 0 
        n = len(nums)
        p1max = [0] * n
        p2max = [0] * n
        p1min = [0] * n
        p2min = [0] * n

        self.getMaxSubArrays(nums, p1max, p2max)
        self.getMinSubArrays(nums, p1min, p2min)


        for i in range(n - 1):
            total = max(total, abs(p1max[i] - p2min[i + 1]), abs(p1min[i] - p2max[i + 1]))
        return total

    def getMaxSubArrays(self, nums, p1max, p2max):
        n = len(nums)
        maxSum = sys.maxsize * -1 
        sum, minSum = 0, 0 
        for i in range(n):
            sum += nums[i]
            maxSum = max(maxSum, sum - minSum)
            minSum = min(minSum, sum)
            p1max[i] = maxSum
        maxSum = sys.maxsize * -1
        sum, minSum =0, 0
        for i in range(n - 1, -1, -1):
            sum += nums[i]
            maxSum = max(maxSum, sum - minSum)
            minSum = min(minSum, sum)
            p2max[i] = maxSum

    def getMinSubArrays(self,nums, p1min, p2min):
        n = len(nums)
        minSum = sys.maxsize
        sum, maxSum =0, 0
        for i in range(n):
            sum += nums[i]
            minSum = min(minSum, sum - maxSum)
            maxSum = max(maxSum, sum)
            p1min[i] = minSum
        minSum = sys.maxsize
        sum, maxSum = 0, 0
        for i in range(n - 1, -1, -1):
            sum += nums[i]
            minSum = min(minSum, sum - maxSum)
            maxSum = max(maxSum, sum)
            p2min[i] = minSum
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Last updated 4 years ago

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