写一段以已知点p为起点的欧式聚类的c++代码

以下是一个简单的以已知点p为起点的欧式聚类的C++代码示例：

#include <iostream>
#include <vector>
#include <cmath>

struct Point {
    double x;
    double y;
};

double calculateDistance(Point p1, Point p2) {
    double dx = p1.x - p2.x;
    double dy = p1.y - p2.y;
    return std::sqrt(dx * dx + dy * dy);
}

std::vector<std::vector<Point>> euclideanClustering(std::vector<Point>& points, double threshold) {
    std::vector<std::vector<Point>> clusters;
    std::vector<bool> visited(points.size(), false);

    for (int i = 0; i < points.size(); ++i) {
        if (visited[i]) {
            continue;
        }

        std::vector<Point> cluster;
        cluster.push_back(points[i]);
        visited[i] = true;

        for (int j = i + 1; j < points.size(); ++j) {
            if (!visited[j] && calculateDistance(points[i], points[j]) <= threshold) {
                cluster.push_back(points[j]);
                visited[j] = true;
            }
        }

        clusters.push_back(cluster);
    }

    return clusters;
}

int main() {
    std::vector<Point> points = {{1.0, 2.0}, {2.0, 3.0}, {3.0, 4.0}, {5.0, 6.0}, {6.0, 7.0}, {7.0, 8.0}};
    double threshold = 2.0;

    std::vector<std::vector<Point>> clusters = euclideanClustering(points, threshold);

    for (const auto& cluster : clusters) {
        std::cout << "Cluster: ";
        for (const auto& point : cluster) {
            std::cout << "(" << point.x << ", " << point.y << ") ";
        }
        std::cout << std::endl;
    }

    return 0;
}

该代码定义了一个Point结构体来表示二维平面上的点，calculateDistance函数用于计算两个点之间的欧式距离，euclideanClustering函数实现了欧式聚类算法，接受一个点的向量和一个阈值作为输入，并返回一个二维向量，其中每个子向量表示一个聚类。main函数中定义了一些点和阈值，并调用euclideanClustering函数进行聚类，并打印每个聚类的点。