AGENS算法c++实现

 cluster二维数组存放数据的编号，每次计算两个簇的距离，找出距离最近的，将其中一个簇的编号加入另一个编号的一维序列中，再将这个编号清除，之后再循环cluster。

#include
#include 
#include 
#include 
using namespace std;
 
struct	Point
{
	double x;
	double y;
};
 
double distance(const Point& a, const Point& b)
{
	double x = a.x - b.x;
	double y = a.y - b.y;
	return sqrt(x * x + y * y);
}
 
vectorint>> agens(const vector& data,int k)
{
	int n = data.size();
	vectorint>> cluster;
	for (int i = 0; i < n; i++)
	{
		cluster.push_back({ i });
	}
 
	while (cluster.size() > k)
	{
		int index_i = 0;
		int index_j = 1;
		double min = distance(data[cluster[0][0]], data[cluster[1][0]]);
		for (int i = 0; i < cluster.size(); i++)						//找出距离最近的两个簇
		{
			for (int j = i + 1; j < cluster.size(); j++)
			{
				double dis = distance(data[cluster[i][0]], data[cluster[j][0]]);	
				if (dis < min)
				{
					index_i = i;
					index_j = j;
					min = dis;
				}
			}
		}
		cluster[index_i].insert(cluster[index_i].end(), cluster[index_j].begin(), cluster[index_j].end());
		cluster.erase(cluster.begin() + index_j);
	}
	return cluster;
 
}
 
vector ReadData(string filename)
{
	vector  data;
	ifstream file(filename);
	if (file.is_open())
	{
		string line;
		while (getline(file, line))
		{
			istringstream iss(line);
			double x, y;
			string token;
			Point point;
			if (getline(iss, token, ',') && istringstream(token) >> point.x &&
				getline(iss, token, ',') && istringstream(token) >> point.y) {
				data.push_back(point);
			}
			/*if (iss >> x >> y)
			{
				data.push_back({ x, y });
			}*/
 
		}
	}
	else
	{
		cout << "open fail";
	}
	file.close();
	return data;
}
int main()
{
	//vector Data = { {1, 1}, {1, 2}, {2, 1}, {2,2}, {3, 4},{3,5} ,{4,4} ,{4,5} };
	vector Data = ReadData("data2.txt");
	int k;
	cin >> k;
	vectorint>> labels;
	labels=agens(Data, k);
	for (const vector<int>& row : labels)
	{
		cout << "{";
		int size = row.size();
		for (int i = 0; i < size; i++)
		{
			cout << row[i] + 1;
			if (i != size - 1)
			{
				cout << ",";
			}
		}
		cout << "}";
	}
 
}

关键在于理解 distance(data[cluster[i][0]], data[cluster[j][0]]);

结果：

数据1：注释部分

数据2：data2.txt