In this guide we will provide 4. Median of Two Sorted Arrays LeetCode Solution with best time and space complexity. The solution to Median of Two Sorted Arrays problem is provided in various programming languages like C++, Java and python. This will be helpful for you if you are preparing for placements, hackathon, interviews or practice purposes. The solutions provided here are very easy to follow and with detailed explanations.
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
Complexity Analysis
Time Complexity: O(\log\min(m, n))
Space Complexity: O(1)
4. Median of Two Sorted Arrays LeetCode Solution in C++
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) / 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;
}
}; /* code provided by PROGIEZ */
4. Median of Two Sorted Arrays LeetCode Solution in Java
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) / 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();
}
} // code provided by PROGIEZ
4. Median of Two Sorted Arrays LeetCode Solution in Python
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) // 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 #code by PROGIEZ
