Given two sorted arrays nums1
and nums2
of size m
and n
respectively, return the median of the two sorted arrays.
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.
Example 3:
Input: nums1 = [0,0], nums2 = [0,0] Output: 0.00000
Example 4:
Input: nums1 = [], nums2 = [1] Output: 1.00000
Example 5:
Input: nums1 = [2], nums2 = [] Output: 2.00000
Constraints:
nums1.length == m
nums2.length == n
0 <= m <= 1000
0 <= n <= 1000
1 <= m + n <= 2000
-106 <= nums1[i], nums2[i] <= 106
Follow up: The overall run time complexity should be O(log (m+n))
.
Solution:
double findMedianSortedArrays(int A[], int m, int B[], int n) {
/* A[0, 1, 2, ..., n-1, n] */
/* A[0, 1, 2, ..., m-1, m] */
int k = (m + n + 1) / 2;
double v = (double)FindKth(A, 0, m - 1, B, 0, n - 1, k);
if ((m+n) % 2 == 0) {
int k2 = k+1;
double v2 = (double)FindKth(A, 0, m - 1, B, 0, n - 1, k2);
v = (v + v2) / 2;
}
return v;
}
// find the kth element int the two sorted arrays
// let us say: A[aMid] <= B[bMid], x: mid len of a, y: mid len of b, then wen can know
//
// (1) there will be at least (x + 1 + y) elements before bMid
// (2) there will be at least (m - x - 1 + n - y) = m + n - (x + y +1) elements after aMid
// therefore
// if k <= x + y + 1, find the kth element in a and b, but unconsidering bMid and its suffix
// if k > x + y + 1, find the k - (x + 1) th element in a and b, but unconsidering aMid and its prefix
int FindKth(int A[], int aL, int aR, int B[], int bL, int bR, int k) {
if (aL > aR) return B[bL + k - 1];
if (bL > bR) return A[aL + k - 1];
int aMid = (aL + aR) / 2;
int bMid = (bL + bR) / 2;
if (A[aMid] <= B[bMid]) {
if (k <= (aMid - aL) + (bMid - bL) + 1)
return FindKth(A, aL, aR, B, bL, bMid - 1, k);
else
return FindKth(A, aMid + 1, aR, B, bL, bR, k - (aMid - aL) - 1);
}
else { // A[aMid] > B[bMid]
if (k <= (aMid - aL) + (bMid - bL) + 1)
return FindKth(A, aL, aMid - 1, B, bL, bR, k);
else
return FindKth(A, aL, aR, B, bMid + 1, bR, k - (bMid - bL) - 1);
}
}
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