用c++写一个一维的DBSCAN算法

好的，以下是一个使用C++实现的一维DBSCAN算法代码：

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

using namespace std;

vector<int> dbscan(vector<double>& data, double eps, int minPts) {
    int n = data.size();
    vector<int> labels(n, 0);
    int clusterId = 1;
    for (int i = 0; i < n; i++) {
        if (labels[i] != 0) continue;
        vector<int> neighbors;
        for (int j = 0; j < n; j++) {
            if (i == j) continue;
            if (abs(data[i] - data[j]) < eps) {
                neighbors.push_back(j);
            }
        }
        if (neighbors.size() >= minPts) {
            labels[i] = clusterId;
            for (int k = 0; k < neighbors.size(); k++) {
                int neighborId = neighbors[k];
                if (labels[neighborId] == -1) {
                    labels[neighborId] = clusterId;
                }
                if (labels[neighborId] != 0) continue;
                labels[neighborId] = clusterId;
                vector<int> newNeighbors;
                for (int j = 0; j < n; j++) {
                    if (neighborId == j) continue;
                    if (abs(data[neighborId] - data[j]) < eps) {
                        newNeighbors.push_back(j);
                    }
                }
                if (newNeighbors.size() >= minPts) {
                    neighbors.insert(neighbors.end(), newNeighbors.begin(), newNeighbors.end());
                }
            }
            clusterId++;
        } else {
            labels[i] = -1;
        }
    }
    return labels;
}

int main() {
    vector<double> data{1.1, 1.2, 1.3, 3.1, 3.2, 3.3, 5.1, 5.2, 5.3};
    double eps = 1.0;
    int minPts = 2;
    vector<int> labels = dbscan(data, eps, minPts);
    for (int i = 0; i < labels.size(); i++) {
        cout << labels[i] << " ";
    }
    cout << endl;
    return 0;
}

该算法接收一个一维数据向量和两个参数，分别是eps和minPts，其中eps是领域半径，minPts是领域内最小点数。该算法将返回一个标签向量，其中每个元素表示对应数据点所属的聚类簇，如果该点为噪声点则标签为-1。