Median of Two Sorted Arrays LeetCode Programming Solutions | LeetCode Problem Solutions in C++, Java, & Python [💯Correct]

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LeetCode Programming Solutions | LeetCode Problem Solutions in C++, Java, & Python [💯Correct]

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Hello Programmers/Coders, Today we are going to share solutions to the Programming problems of LeetCode Solutions in C++, Java, & Python. At Each Problem with Successful submission with all Test Cases Passed, you will get a score or marks and LeetCode Coins. And after solving maximum problems, you will be getting stars. This will highlight your profile to the recruiters.

In this post, you will find the solution for the Median of Two Sorted Arrays in C++, Java & Python-LeetCode problem. We are providing the correct and tested solutions to coding problems present on LeetCode. If you are not able to solve any problem, then you can take help from our Blog/website.

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Link for the Problem – Median of Two Sorted Arrays– LeetCode Problem

Median of Two Sorted Arrays– LeetCode Problem

Problem:

Given two sorted arrays nums1 and nums2 of size m and n respectively, return the median of the two sorted arrays.

The overall run time complexity should be O(log (m+n)).

Example 1:

Input: nums1 = [1,3], nums2 = [2]
Output: 2.00000
Explanation: merged array = [1,2,3] and median is 2.

Example 2:

Input: nums1 = [1,2], nums2 = [3,4]
Output: 2.50000
Explanation: merged array = [1,2,3,4] and median is (2 + 3) / 2 = 2.5.

Constraints:

  • nums1.length == m
  • nums2.length == n
  • 0 <= m <= 1000
  • 0 <= n <= 1000
  • 1 <= m + n <= 2000
  • -106 <= nums1[i], nums2[i] <= 106
Median of Two Sorted Arrays– LeetCode Solutions
class Solution {
 public:
  double findMedianSortedArrays(vector<int>& nums1, vector<int>& nums2) {
    const int n1 = nums1.size();
    const int n2 = nums2.size();

    if (n1 > n2)
      return findMedianSortedArrays(nums2, nums1);

    int l = 0;
    int r = n1;

    while (l <= r) {
      const int partition1 = l + (r - l) / 2;
      const int partition2 = (n1 + n2 + 1) / 2 - partition1;
      const int maxLeft1 = partition1 == 0 ? INT_MIN : nums1[partition1 - 1];
      const int maxLeft2 = partition2 == 0 ? INT_MIN : nums2[partition2 - 1];
      const int minRight1 = partition1 == n1 ? INT_MAX : nums1[partition1];
      const int minRight2 = partition2 == n2 ? INT_MAX : nums2[partition2];
      if (maxLeft1 <= minRight2 && maxLeft2 <= minRight1)
        return (n1 + n2) % 2 == 0
                   ? (max(maxLeft1, maxLeft2) + min(minRight1, minRight2)) * 0.5
                   : max(maxLeft1, maxLeft2);
      else if (maxLeft1 > minRight2)
        r = partition1 - 1;
      else
        l = partition1 + 1;
    }

    throw;
  }
};
class Solution {
  public double findMedianSortedArrays(int[] nums1, int[] nums2) {
    final int n1 = nums1.length;
    final int n2 = nums2.length;

    if (n1 > n2)
      return findMedianSortedArrays(nums2, nums1);

    int l = 0;
    int r = n1;

    while (l <= r) {
      final int partition1 = l + (r - l) / 2;
      final int partition2 = (n1 + n2 + 1) / 2 - partition1;
      final int maxLeft1 = partition1 == 0 ? Integer.MIN_VALUE : nums1[partition1 - 1];
      final int maxLeft2 = partition2 == 0 ? Integer.MIN_VALUE : nums2[partition2 - 1];
      final int minRight1 = partition1 == n1 ? Integer.MAX_VALUE : nums1[partition1];
      final int minRight2 = partition2 == n2 ? Integer.MAX_VALUE : nums2[partition2];
      if (maxLeft1 <= minRight2 && maxLeft2 <= minRight1)
        return (n1 + n2) % 2 == 0
            ? (Math.max(maxLeft1, maxLeft2) + Math.min(minRight1, minRight2)) * 0.5
            : Math.max(maxLeft1, maxLeft2);
      else if (maxLeft1 > minRight2)
        r = partition1 - 1;
      else
        l = partition1 + 1;
    }

    throw new IllegalArgumentException();
  }
}
class Solution:
  def findMedianSortedArrays(self, nums1: List[int], nums2: List[int]) -> float:
    n1 = len(nums1)
    n2 = len(nums2)

    if n1 > n2:
      return self.findMedianSortedArrays(nums2, nums1)

    l = 0
    r = n1

    while l <= r:
      partition1 = l + (r - l) // 2
      partition2 = (n1 + n2 + 1) // 2 - partition1
      maxLeft1 = -2**31 if partition1 == 0 else nums1[partition1 - 1]
      maxLeft2 = -2**31 if partition2 == 0 else nums2[partition2 - 1]
      minRight1 = 2**31 - 1 if partition1 == n1 else nums1[partition1]
      minRight2 = 2**31 - 1 if partition2 == n2 else nums2[partition2]
      if maxLeft1 <= minRight2 and maxLeft2 <= minRight1:
        return (max(maxLeft1, maxLeft2) + min(minRight1, minRight2)) * 0.5 if (n1 + n2) % 2 == 0 else max(maxLeft1, maxLeft2)
      elif maxLeft1 > minRight2:
        r = partition1 - 1
      else:
        l = partition1 + 1

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