欧式聚类点集,获取分类的点集以及最大点集,少量点集环境下计算效率很好
输入:点集+阈值
输出:分类结构+最大分类集
int EuclideanClustering(std::vector srcPts, float threshold, std::vector>& dstPts, std::vector& maxPts)
{
if (!srcPts.size())
return -1;
dstPts.clear();
float distance2;
while (srcPts.size() > 0)//遍历srcPts所有点塞到分类的vector中
{
std::vector pts;
pts.push_back(srcPts[srcPts.size() - 1]);//返回最后一个并删除
srcPts.pop_back();
int flag;
do
{
flag = 0;
for (size_t i = 0; i < srcPts.size(); i++)
{
for (size_t j = 0; j < pts.size(); j++)
{
distance2 = (srcPts[i] - pts[j]).x*(srcPts[i] - pts[j]).x + (srcPts[i] - pts[j]).y*(srcPts[i] - pts[j]).y;
if (distance2 < threshold*threshold)//如果距离小于阈值,传递过去
{
pts.push_back(srcPts[i]);
srcPts.erase(srcPts.begin() + i);
i--;
flag++;
break;
}
}
}
} while (flag > 0);
dstPts.push_back(pts);
}
//找出最大的聚类
int max_num = 0, max_no = 0;
for (size_t i = 0; i < dstPts.size(); i++)
{
if (max_num < dstPts[i].size())
{
max_num = dstPts[i].size();
max_no = i;
}
}
maxPts = dstPts[max_no];
}