my solution:
class Solution {
public:
int reversePairs(vector<int>& nums) {
int length=nums.size();
int count=;
for (int i=;i<length;i++)
{
for(int j=i+;j<length;j++)
{
if(nums[i]>2*nums[j])
count++;
}
}
return count;
}
};
wrong answer :
because 2147483647*2 is -2 (int) , only 33bit can represent
int | 4 byte | 32 bit |
2147483647--2147483647 signed 0-4294967295 unsigned |
long | 4 byte | 32 bit | (在 32 位机器上与int 相同) |
double | 8 byte | 64 bit | 1.79769e+308 ~ 2.22507e-308 |
float | 4 byte | 32 bit | 3.40282e+038 ~ 1.17549e-038 |
long double | 12 byte | 96 bit | 1.18973e+4932 ~ 3.3621e-4932 |
then i change the type to double:
class Solution {
public:
int reversePairs(vector<int>& nums) {
int length=nums.size();
int count=;
double a;
for (int i=;i<length;i++)
{
for(int j=i+;j<length;j++)
{
a=(double)*nums[j];
if(nums[i]>a)
count++;
}
}
return count;
}
};
wrong:
because the if the maxmise length is 50000, the process will lead to time exceed .
对于这类问题,一种很好的解法就是拆分数组来解决子问题,通过求解小问题来求解大问题。
有两类拆分方法:
- 顺序重现(sequential recurrence relation):T(i, j) = T(i, j - 1) + C
- C就是处理最后一个数字的子问题,找 T(i, j - 1)中的reverse pairs, T(i, j-1) 有序,只需要找大于2*nums[j]的数。 二分查找已经不满足条件了,只能使用Binary indexed tree 来实现。BIT的存储方式不是数组对应一一存入,而是有的对应存入,有的存若干个数字之和,其设计的初衷是在O(lgn)时间复杂度内完成求和运算。
- 分割重现(Partition Recurrence relation):T(i, j) = T(i, m) + T(m+1, j) + C
- C为合并两个部分的子问题。MergeSort的思想就是把数组对半拆分为子数组,柴刀最小的数组后开始排序,然后一层一层返回,得到有序的数组。时间复杂度O(nlogn)
class Solution {
public:
int reversePairs(vector<int>& nums) {
return mergeSort(nums, , nums.size() - );
}
int mergeSort(vector<int>& nums, int left, int right) {
if (left >= right) return ;
int mid = left + (right - left) / ;
int res = mergeSort(nums, left, mid) + mergeSort(nums, mid + , right);
for (int i = left, j = mid + ; i <= mid; ++i) {
while (j <= right && nums[i] / 2.0 > nums[j]) ++j;
res += j - (mid + );
}
sort(nums.begin() + left, nums.begin() + right + );
return res;
}
};
归并排序 MergeSort 和BIT可以解决,BST和 binary search不行
https://discuss.leetcode.com/topic/79227/general-principles-behind-problems-similar-to-reverse-pairsBST (binary search tree)
BIT (binary indexed tree)