[Codility] CountTriangles
A zero-indexed array A consisting of N integers is given. A triplet (P, Q, R) is triangular if it is possible to build a triangle with sides of lengths A[P], A[Q] and A[R]. In other words, triplet (P, Q, R) is triangular if 0 ≤ P < Q < R < N and:
- A[P] + A[Q] > A[R],
- A[Q] + A[R] > A[P],
- A[R] + A[P] > A[Q].
For example, consider array A such that:
A[0] = 10 A[1] = 2 A[2] = 5 A[3] = 1 A[4] = 8 A[5] = 12
There are four triangular triplets that can be constructed from elements of this array, namely (0, 2, 4), (0, 2, 5), (0, 4, 5), and (2, 4, 5).
Write a function:
int solution(vector<int> &A);
that, given a zero-indexed array A consisting of N integers, returns the number of triangular triplets in this array.
For example, given array A such that:
A[0] = 10 A[1] = 2 A[2] = 5 A[3] = 1 A[4] = 8 A[5] = 12
the function should return 4, as explained above.
Assume that:
- N is an integer within the range [0..1,000];
- each element of array A is an integer within the range [1..1,000,000,000].
Complexity:
- expected worst-case time complexity is O(N2);
- expected worst-case space complexity is O(N), beyond input storage (not counting the storage required for input arguments).
给定正整数数组A,长度为N,下标从0开始,求(P,Q,R),满足0<=P<Q<R<N 并且 A[P] + A[Q] > A[R], A[Q] + A[R] > A[P], A[P] + A[R] > A[Q]的三元组个数。
数据范围 N [0..1000], 数组元素[1..10^9]。
要求复杂度 时间O(N ^ 2) ,空间 O(1)。
分析: 显然我们不能枚举……我们可以把数组排序 O(NlogN),甚至O(N^2)的排序都可以。然后还是枚举,只不过枚举两条较小的边A[x] , A[y], 然后我们考虑最大边A[z],设想假设我们固定x, 当y变大时A[x] + A[y]也变大,我们需要A[x] + A[y] > A[z], y变大之前的那些z值现在依然也满足条件,所以我们只要接着上次满足条件的最大的z,继续循环就可以了。所以对于同一个x来说,y和z的变化都是O(N)的。总复杂度O(N^2)。
1 // you can use includes, for example: 2 #include <algorithm> 3 4 // you can write to stdout for debugging purposes, e.g. 5 // cout << "this is a debug message" << endl; 6 7 int solution(vector<int> &A) { 8 // write your code in C++11 9 sort(A.begin(), A.end()); 10 int a, b, c; 11 int res = 0; 12 for (a = 0; a < (int)A.size() - 2; ++a) { 13 c = a + 2; 14 for (b = a + 1; b < (int)A.size() - 1; ++b) { 15 for (c = max(c, b + 1); c < A.size() && A[a] + A[b] > A[c]; ++c); 16 res += c - b - 1; 17 } 18 } 19 return res; 20 }