std::vector<std::pair<int, int> > maxPoints ; 编译错误
时间: 2024-06-02 11:03:38 浏览: 18
std::vector<std::pair<int, int>> maxPoints; 是一个存储了一对整数的向量容器。编译错误可能是由于以下几个原因导致的:
1. 缺少头文件:确保你包含了正确的头文件。对于std::vector和std::pair,你需要包含< vector >和< utility >头文件。
2. 命名空间错误:确保你在使用std::vector和std::pair之前使用了"using namespace std;"或者在使用时加上"std::"前缀。
3. 模板参数错误:确保你在std::vector的尖括号中提供了正确的模板参数。在这种情况下,你需要提供std::pair<int, int>作为模板参数。
4. 语法错误:检查你的代码是否存在其他语法错误,例如拼写错误、缺少分号等。
如果你能提供更多的错误信息或者代码片段,我可以帮助你更详细地解决问题。
相关问题
n, k = map(int, input().split())points = set()for i in range(n): x, y = map(int, input().split()) points.add((x, y))dp = [[0] * (max(p[1] for p in points) + 2) for _ in range(max(p[0] for p in points) + 2)]for x, y in points: dp[x][y] = 1for i in range(max(p[0] for p in points), 0, -1): for j in range(max(p[1] for p in points), 0, -1): if (i, j) not in points: dp[i][j] = max(dp[i+1][j], dp[i][j+1])ans = max(max(row) for row in dp)print(ans) 转C++
以下是将 Python 代码转换为等效的 C++ 代码:
```c++
#include <iostream>
#include <set>
#include <vector>
#include <algorithm>
using namespace std;
int main()
{
int n, k;
cin >> n >> k;
set<pair<int, int>> points;
for (int i = 0; i < n; i++)
{
int x, y;
cin >> x >> y;
points.insert({x, y});
}
int max_x = max_element(points.begin(), points.end(), [](auto &a, auto &b) { return a.first < b.first; })->first;
int max_y = max_element(points.begin(), points.end(), [](auto &a, auto &b) { return a.second < b.second; })->second;
vector<vector<int>> dp(max_x + 2, vector<int>(max_y + 2));
for (const auto &p : points)
dp[p.first][p.second] = 1;
for (int i = max_x; i >= 1; i--)
{
for (int j = max_y; j >= 1; j--)
{
if (!points.count({i, j}))
{
dp[i][j] = max(dp[i + 1][j], dp[i][j + 1]);
}
}
}
int ans = *max_element(dp[1].begin() + 1, dp[1].end());
cout << ans << endl;
return 0;
}
```
C++模拟退火实现多点动态规划
C++模拟退火算法实现多点动态规划的代码如下所示:
```cpp
#include <iostream>
#include <cmath>
#include <vector>
#include <algorithm>
using namespace std;
// 计算两点之间的距离
double distance(pair<int, int> p1, pair<int, int> p2) {
int dx = p1.first - p2.first;
int dy = p1.second - p2.second;
return sqrt(dx * dx + dy * dy);
}
// 计算路径的总长度
double calculateDistance(vector<pair<int, int>>& points, vector<int>& path) {
double totalDistance = 0.0;
for (int i = 0; i < path.size() - 1; i++) {
totalDistance += distance(points[path[i]], points[path[i + 1]]);
}
return totalDistance;
}
// 模拟退火算法求解多点动态规划
vector<int> simulatedAnnealing(vector<pair<int, int>>& points) {
int n = points.size();
vector<int> currentPath(n);
for (int i = 0; i < n; i++) {
currentPath[i] = i;
}
random_shuffle(currentPath.begin(), currentPath.end());
double currentDistance = calculateDistance(points, currentPath);
double temperature = 1000.0;
double coolingRate = 0.999;
while (temperature > 0.1) {
vector<int> newPath = currentPath;
int swapIndex1 = rand() % n;
int swapIndex2 = rand() % n;
swap(newPath[swapIndex1], newPath[swapIndex2]);
double newDistance = calculateDistance(points, newPath);
double deltaDistance = newDistance - currentDistance;
if (deltaDistance < 0 || exp(-deltaDistance / temperature) > (double)rand() / RAND_MAX) {
currentPath = newPath;
currentDistance = newDistance;
}
temperature *= coolingRate;
}
return currentPath;
}
int main() {
vector<pair<int, int>> points = {{0, 0}, {1, 2}, {3, 4}, {5, 6}, {7, 8}};
vector<int> path = simulatedAnnealing(points);
cout << "Optimal path: ";
for (int i = 0; i < path.size(); i++) {
cout << path[i] << " ";
}
cout << endl;
cout << "Optimal distance: " << calculateDistance(points, path) << endl;
return 0;
}
```
这段代码实现了一个简单的多点动态规划问题的模拟退火算法。首先,我们定义了一个计算两点之间距离的函数`distance`,然后定义了一个计算路径总长度的函数`calculateDistance`。接下来,我们使用模拟退火算法来求解最优路径,其中包括初始化路径、计算当前路径长度、设置初始温度和冷却率等步骤。最后,我们输出了求解得到的最优路径和最优距离。