leetcode147median-of-two-sorted-arrays
题目描述
are two sorted arrays A and B of size m and n respectively. Find the
median of the two sorted arrays. The overall run time complexity should
be O(log (m+n)).
输入
[],[1]
/归并数组,但是不需要完全估计,只需要合并到中位数即可
//但是,如果m+n为偶数,那么返回中间两个值的平均数
class Solution {
public:
double findMedianSortedArrays(int A[], int m, int B[], int n) {
int mid=(m+n)/2+1;
int a=0;
int b=0;
int result;
int result2=0;
for(int i=0;i<mid;i++){
//复杂度为(m+n)/2+1,也就是m+n
if (b>=n || (a<m && A[a]<B[b])){
result=result2;
result2=A[a];
a++;
}
else {
result=result2;
result2=B[b];
b++;
}
}
if ((m+n)%2==0) return double(result+result2)/2.0;
return result2;
}
};
/*
** 获取两个数组的中位数
*/
public double findMedianSortedArrays(int[] A, int[] B) {
int m = A.length;//数组A的长度
int n = B.length;//数组B的长度
int l = (m+n+1)/2;
int r = (m+n+2)/2;
/*取两个数的平均值,即适用于总长度m+n是奇数的情况,也适用于是偶数的情况。
* 奇数时,两次调用所获得的值相等;
偶数时,两次调用所获得的值不等。中位数即为两个值的平均值*/
return (getKth(A,0,B,0,l)+getKth(A,0,B,0,r))/2.0;
}
/*获取数组A和数组B结合后的第k小元素(即中位数)
* s1:数组A当前的开始下标
* s2:数组B当前的开始下标
*/
private int getKth(int[] A, int s1, int[] B, int s2, int k){
if(A.length==0){//1.数组A为空,返回数组B的中位数
return B[s2+k-1];
}
if(B.length==0){//2.数组B为空,返回数组A的中位数
return A[s1+k-1];
}
if(k==1){
return Math.min(A[s1],B[s2]);
}
//4.A和B都有多个元素
/*在数组A中找到第k/2小元素a,在数组B中找到第k/2小元素b,
**1)如果a和b相等,那么第k小元素就是a或者b了,
**2)如果a小于b,那么总体的第k小元素不可能在a的第k/2小元素之前,那么就可以将其舍弃了
**3)反之如果a大于b,也就可以舍弃b的第k/2小之前的元素了。*/
int mida = Integer.MAX_VALUE;
int midb = Integer.MAX_VALUE;
if(s1+k/2-1<A.length){
mida = A[s1+k/2-1];
}
if(s2+k/2-1<B.length){
midb = B[s2+k/2-1];
}
if(mida<midb){//去除A中小的部分,继续递归寻找
return getKth(A,s1+k/2,B,s2,k-k/2);
}else{//即mina>minb 去除B中小的部分,继续递归寻找
return getKth(A,s1,B,s2+k/2,k-k/2);
}
}
class Solution: def findMedianSortedArrays(self , A , B ): # write code here arr = sorted(A + B) if len(arr)%2 == 1: return (arr[(len(arr)/2)]*1.0) if len(arr)%2 == 0: return ((arr[(len(arr)/2)] + arr[((len(arr)/2)-1)])/2.0)leetcode147median-of-two-sorted-arrays的更多相关文章
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