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leetcode 88. Merge Sorted Array(python)

2022-01-29 20:22:54 Wang Daya

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describe

You are given two integer arrays nums1 and nums2, sorted in non-decreasing order, and two integers m and n, representing the number of elements in nums1 and nums2 respectively.

Merge nums1 and nums2 into a single array sorted in non-decreasing order.

The final sorted array should not be returned by the function, but instead be stored inside the array nums1. To accommodate this, nums1 has a length of m + n, where the first m elements denote the elements that should be merged, and the last n elements are set to 0 and should be ignored. nums2 has a length of n.

Example 1:

Input: nums1 = [1,2,3,0,0,0], m = 3, nums2 = [2,5,6], n = 3
Output: [1,2,2,3,5,6]
Explanation: The arrays we are merging are [1,2,3] and [2,5,6].
The result of the merge is [1,2,2,3,5,6] with the underlined elements coming from nums1.	
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Example 2:

Input: nums1 = [1], m = 1, nums2 = [], n = 0
Output: [1]
Explanation: The arrays we are merging are [1] and [].
The result of the merge is [1].
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Example 3:

Input: nums1 = [0], m = 0, nums2 = [1], n = 1
Output: [1]
Explanation: The arrays we are merging are [] and [1].
The result of the merge is [1].
Note that because m = 0, there are no elements in nums1. The 0 is only there to ensure the merge result can fit in nums1.
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Note:

nums1.length == m + n
nums2.length == n
0 <= m, n <= 200
1 <= m + n <= 200
-10^9 <= nums1[i], nums2[j] <= 10^9
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analysis

According to the meaning , Is to give a list of two ordered integers nums1 and nums2 , And give two integers m and n , They represent nums1 and nums2 The length of , The title requires us to merge these two ordered integer lists , Returns a list of integers in ascending order .

The final sorted list does not open up new memory space , It's stored in a list nums1 in . Because it has been agreed in the title nums1 The length of is m + n, The top m Elements represent the valid elements to be merged , after n The elements are set to 0 Just to occupy a seat , take nums2 integrate into nums1 After sorting, you can just put down .

In fact, the idea of this question is relatively simple :

  • When n by 0 When , Express nums1 You don't need to be with nums2 A merger , No matter nums1 What is it , Go straight back to nums1 That's all right.

  • When m by 0 When , Express nums1 It's empty , There are no elements to merge , But you can't directly return to nums2 , Because the title requires that the last thing to return is nums1 , So no matter nums2 How many elements are there , Directly assign to nums1 , And then back again nums1 Can only be

  • from nums1 The last valid element of and nums2 The last valid element of starts the inverse comparison of size :

    • If nums1[m-1] Greater than or equal to nums2[n-1] , Will nums1[m-1] Assign a value to nums1[m+n-1] , meanwhile m Minus one
    • Otherwise it would be nums2[n-1] Assign a value to nums1[m+n-1] , meanwhile n Minus one
  • If nums2 End of traversal first , because nums1 The remaining elements are ordered from the beginning , So leave him alone , But if nums 1 End of traversal first , Probably nums2 There are other elements that have not been traversed , because nums2 The remaining elements are ordered from the beginning , Direct will nums2[:n] Assign a value to nums1[:n] that will do

  • return nums1

answer

class Solution(object):
    def merge(self, nums1, m, nums2, n):
        """
        :type nums1: List[int]
        :type m: int
        :type nums2: List[int]
        :type n: int
        :rtype: None Do not return anything, modify nums1 in-place instead.
        """
        if n == 0: 
            return nums1
        if m == 0: 
            nums1[:n] = nums2[:n]
            return nums1
        while m>0 and n>0:
            if nums1[m-1]>=nums2[n-1]:
                nums1[m+n-1] = nums1[m-1]
                m -= 1
            else:
                nums1[m+n-1] = nums2[n-1]
                n -= 1
        nums1[:n] = nums2[:n]
        return nums1
                
                       	      
		
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Running results

Runtime: 38 ms, faster than 20.56% of Python online submissions for Merge Sorted Array.
Memory Usage: 13.6 MB, less than 16.74% of Python online submissions for Merge Sorted Array.
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Original link :leetcode.com/problems/me…

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