索引:[LeetCode] Leetcode 题解索引 (C++/Java/Python/Sql)
Github: https://github.com/illuz/leetcode
题目:https://oj.leetcode.com/problems/Median-of-Two-Sorted-Arrays/
代码(github):https://github.com/illuz/leetcode
求两个有序数组的中位数。要求复杂度是 O(log(n + m))。
两种思路:
1. 直接 merge 两个数组,然后求中位数,能过,不过复杂度是 O(n + m)。
2. 用二分的思路去做,这不好想,还要考虑到奇偶。可以转化思维,去求两个有序数组中的第 K 大数,这样就比较好想了。
1. Merge
C++:
class Solution {
public:
double findMedianSortedArrays(int A[], int m, int B[], int n) {
vector C;
int pa = 0, pb = 0; // point of A & B
while (pa < m || pb < n) {
if (pa == m) {
C.push_back(B[pb++]);
continue;
}
if (pb == n) {
C.push_back(A[pa++]);
continue;
}
if (A[pa] > B[pb])
C.push_back(B[pb++]);
else
C.push_back(A[pa++]);
}
if ((n + m)&1)
return C[(n+m)/2];
else
return (C[(n+m)/2 - 1] + C[(n+m)/2]) / 2.0;
}
};
2. 二分
C++:
class Solution {
private:
double findKthSortedArrays(int A[], int m, int B[], int n, int k) {
if (m < n) {
swap(n, m);
swap(A, B);
}
if (n == 0)
return A[k - 1];
if (k == 1)
return min(A[0], B[0]);
int pb = min(k / 2, n), pa = k - pb;
if (A[pa - 1] > B[pb - 1])
return findKthSortedArrays(A, m, B + pb, n - pb, k - pb);
else if (A[pa - 1] < B[pb - 1])
return findKthSortedArrays(A + pa, m - pa, B, n, k - pa);
else
return A[pa - 1];
}
public:
double findMedianSortedArrays(int A[], int m, int B[], int n) {
if ((n + m)&1)
return findKthSortedArrays(A, m, B, n, (n + m) / 2 + 1);
else
return (findKthSortedArrays(A, m, B, n, (n + m) / 2 + 1) +
findKthSortedArrays(A, m, B, n, (n + m) / 2)) / 2.0;
}
};
Java:
public class Solution {
private double findKthSortedArrays(int A[], int astart, int aend,
int B[], int bstart, int bend, int k) {
int m = aend - astart, n = bend - bstart;
if (m < n) {
return findKthSortedArrays(B, bstart, bend, A, astart, aend, k);
}
if (n == 0)
return A[astart + k - 1];
if (k == 1)
return Math.min(A[astart], B[bstart]);
int pb = Math.min(k / 2, n), pa = k - pb;
if (A[astart + pa - 1] > B[bstart + pb - 1])
return findKthSortedArrays(A, astart, aend, B, bstart + pb, bend, k - pb);
else if (A[astart + pa - 1] < B[bstart + pb - 1])
return findKthSortedArrays(A, astart + pa, aend, B, bstart, bend, k - pa);
else
return A[astart + pa - 1];
}
public double findMedianSortedArrays(int A[], int B[]) {
int m = A.length, n = B.length;
if ((n + m) % 2 == 1)
return findKthSortedArrays(A, 0, m, B, 0, n, (n + m) / 2 + 1);
else
return (findKthSortedArrays(A, 0, m, B, 0, n, (n + m) / 2 + 1) +
findKthSortedArrays(A, 0, m, B, 0, n, (n + m) / 2)) / 2.0;
}
}
Python:
class Solution:
def findKthSortedArrays(self, A, B, k):
if len(A) < len(B):
tmp = A
A = B
B = tmp
if len(B) == 0:
return A[k - 1]
if k == 1:
return min(A[0], B[0])
pb = min(k / 2, len(B))
pa = k - pb
if A[pa - 1] > B[pb - 1]:
return self.findKthSortedArrays(A, B[pb:], k - pb)
elif A[pa - 1] < B[pb - 1]:
return self.findKthSortedArrays(A[pa:], B, k - pa)
else:
return A[pa - 1]
# @return a float
def findMedianSortedArrays(self, A, B):
if (len(A) + len(B)) % 2 == 1:
return self.findKthSortedArrays(A, B, (len(A) + len(B)) / 2 + 1)
else:
return (self.findKthSortedArrays(A, B, (len(A) + len(B)) / 2) +
self.findKthSortedArrays(A, B, (len(A) + len(B)) / 2 + 1)) / 2.0