几何中值/交汇点2D实现

Geometric median/meeting point 2D realization

本文关键字:2D 实现 交汇点 何中值      更新时间:2023-10-16

我的程序有一些问题,它目前在查找汇合点时给出了错误的结果。我选择使用geometric median算法来搜索汇合点,如下所述。

我还实现了一个蛮力算法,只是为了比较结果。

源代码对可能的解决方案进行了编辑,纠正我的错误,它有时不适用于>100000点:

#include <vector>
#include <random>
#include <cstdlib>
#include <algorithm>
#include <iostream>
#include <cmath>
using namespace std;
long double ComputeMean(vector<long long> InputData) {
long double rtn = 0;
for (unsigned int i = 0; i < InputData.size(); i++) {
rtn += InputData[i];
}
if(rtn == 0) return rtn;
return rtn/InputData.size();
}
long double CallRecursiveAverage(long double m0, vector<long long> X)  {
long double m1 =0 ;
long double numerator = 0, denominator = 0;
for (unsigned int i = 0; i < X.size(); i++)  {
long double temp =abs((X[i] - m0));
if(X[i]!=0 && temp!=0) {
numerator += X[i] / temp;
}
if(temp!=0) {
denominator += 1 / temp;
}
}
if( denominator != 0 ) {
m1 = numerator / denominator;
}
return m1;
}
long double ComputeReWeightedAverage(vector<long long> InputVector)  {
long double m0 = ComputeMean(InputVector);
long double m1 = CallRecursiveAverage(m0, InputVector);
while (abs(m1 - m0) > 1e-6) {
m0 = m1;
m1 = CallRecursiveAverage(m0, InputVector);
}
return m1;
}
int randomizer(){
int n =(rand() % 1000000 + 1)*(-1 + ((rand() & 1) << 1));
return(n);
}
struct points
{
long double ch;
long long remp;
bool operator<(const points& a) const
{
return ch < a.ch;
}
};
int main () {
long double houses=10;
//    rand() % 100 + 1;
//    cin >> houses;
vector <long long> x;
vector <long long> y;
vector <long long> xr;
vector <long long> yr;
vector <long long> sums;
vector <long long> remp;
long long x0, y0;
long double path = 1e9;
long double sumy = 0;
long double sumx = 0;
long double avgx = 1;
long double avgy = 1;
srand((unsigned)time(NULL));
int rnd;
for(int i = 0; i < houses; i++) {
//        cin>>x0>>y0;
x0 =  randomizer();
x.push_back(x0);
sumx += x0;
y0  =  randomizer();
y.push_back(y0);
sumy += y0;
}
if(sumx!=0)     {
avgx=ComputeReWeightedAverage(x);
} else {
avgx=0;
}
if(sumy!=0)     {
avgy=ComputeReWeightedAverage(y);
} else {
avgy=0;
}
long double  check=1e9;
long double  pathr=0;
int rx, ry;
long double  wpath=1e9;
///brute force////
for(int j = 0; j < houses; j++) {
pathr = 0;
for(int i = 0; i < houses; i++) {
pathr += max(abs(x[i] - x[j]), abs(y[i] - y[j]));
}
if(pathr<wpath)
{
wpath = pathr;
ry=j;
}
}
cout << "nx ="<<x[ry]<<"n";
cout << "y ="<<y[ry]<<"n";
cout << "bruteForce path ="<<wpath<<"nn";
////end brute force///
cout << "avgx ="<<avgx<<"n";
cout << "avgy ="<<avgy<<"n";
vector<points> ch;
for(int j = 0; j < houses; j++) {
remp.push_back(j);
points tb;
tb.ch=max(abs(x[j] - (avgx)), abs(y[j] - (avgy)));
tb.remp=j;
ch.push_back(tb) ;
}
sort(ch.begin(),ch.end());
path =1e9;
for(unsigned int z = 0; z < 10; z++) {
pathr = 0;
for(int i = 0; i < houses; i++) {
pathr += max(abs(x[i] - x[ch[z].remp]), abs(y[i] - y[ch[z].remp]));
}
if(pathr<path)
{
path = pathr;
}
}
cout << "x ="<<x[remp[0]]<<"n";
cout << "y ="<<y[remp[0]]<<"n";
cout << "Weizsfield path ="<<path<<"nn";
if (wpath!=path){ cout <<"ERRROR"<<"n";
cout << "dotsn";
for(int i = 0; i < houses; i++) {
cout << x[i]<<"  "<<y[i]<<"n";
}
cout << "dotsnn";
}
return 0;
}

我的程序哪里出错了?任何帮助都将不胜感激。

EDIT
将最近点的搜索半径更改为几何中值并检查所有点的路径是最佳方法吗?若答案是肯定的,我该如何找到最佳起始半径?

Weiszfeld算法是一种近似几何中值的算法,因此经常偏离蛮力计算的真实中值。

增加搜索半径可能会有所帮助。