题目:
Given an array with n integers, you need to find if there are triplets (i, j, k) which satisfies following conditions:
- 0 < i, i + 1 < j, j + 1 < k < n - 1
- Sum of subarrays (0, i - 1), (i + 1, j - 1), (j + 1, k - 1) and (k + 1, n - 1) should be equal.
Example:
Input: [1,2,1,2,1,2,1] Output: True Explanation: i = 1, j = 3, k = 5. sum(0, i - 1) = sum(0, 0) = 1 sum(i + 1, j - 1) = sum(2, 2) = 1 sum(j + 1, k - 1) = sum(4, 4) = 1 sum(k + 1, n - 1) = sum(6, 6) = 1
Note:
- 1 <= n <= 2000.
- Elements in the given array will be in range [-1,000,000, 1,000,000].
思路:
首先想到的是暴力法,那就是三重循环,时间复杂度是O(n^3),空间复杂度是O(n)。不出意料,过不了大数据。
有一种采用空间换时间的做法:我们从中间进行分割,然后在前半部分进行搜索,看看是不是可以找到和相同的划分,如果找到了,就将和加入哈希表中;然后再在后半部分进行搜索,如果找到了和相同的划分并且该和也存在于哈希表中,这说明我们找到了合适的i,j,k,可以将数组划分为和相同的四个部分,返回true。这样时间复杂度就降低成了O(n^2)。
代码:
1、暴力法:
class Solution {
public:
bool splitArray(vector<int>& nums) {
int n = nums.size();
if (n < 7) {
return false;
}
vector<int> sums(n, 0);
sums[0] = nums[0];
for (int i = 1; i < n; ++i) {
sums[i] = sums[i - 1] + nums[i];
}
for (int i = 1; i < n - 1; ++i) {
for (int j = i + 2; j < n - 1; ++j) {
for (int k = j + 2; k < n - 1; ++k) {
int part1 = sums[i - 1]; // [0, i - 1]
int part2 = sums[j - 1] - sums[i]; // [i + 1, j - 1]
int part3 = sums[k - 1] - sums[j]; // [j + 1, k - 1]
int part4 = sums[nums.size() - 1] - sums[k]; // [k + 1, n - 1]
if (part1 == part2 && part2 == part3 && part3 == part4) {
return true;
}
}
}
}
return false;
}
};
2、哈希表法:
class Solution {
public:
bool splitArray(vector<int>& nums) {
int n = nums.size();
if (n < 7) {
return false;
}
vector<int> sums(n, 0);
sums[0] = nums[0];
for (int i = 1; i < n; ++i) {
sums[i] = sums[i - 1] + nums[i];
}
for (int j = 3; j < n - 3; ++j) { // j is the middle cut
unordered_set<int> hash;
for (int i = 1; i < j - 1; ++i) {
if (sums[i - 1] == sums[j - 1] - sums[i]) { // compare [0, i - 1] and [i + 1, j - 1]
hash.insert(sums[i - 1]);
}
}
for (int k = j + 2; k < n - 1; ++k) {
if (sums[n - 1] - sums[k] == sums[k - 1] - sums[j] && hash.count(sums[k - 1] - sums[j])) {
return true;
}
}
}
return false;
}
};