public List <Record> GetPredictedCluster(Vector3 pos, Vector3 rot, HashSet <Record[]> origin_clusters, List <Cluster> clusterDes)
{
var exchangeAxis = new ExchangeAxis();
Record[] predicted_cluster = null;
double maxValue = -100;
Debug.Log("现在朝向" + rot);
Coeffecient getCoefficient = new Coeffecient();
int count = 0;
List <Record[]> clusters = origin_clusters.ToList();
foreach (var cluster in clusters)
{
//数据块的距离(暂时按照cluster0计算)
//Vector3 clusterCenterPos = exchangeAxis.ModelIndex_to_unityPos((float)cluster[0].posX, (float)cluster[0].posY, (float)cluster[0].posZ);
Vector3 centerPos = GetCenterPoint(cluster);
Vector3 clusterCenterPos = exchangeAxis.ModelIndex_to_unityPos((float)centerPos.x, (float)centerPos.y, (float)centerPos.z);
double distance = GetDistance(pos, clusterCenterPos);
//偏角
double avertence = GetAvertence(pos, rot, clusterCenterPos);
//兴趣度系数（需改进）
//double coefficient = getCoefficient.GetCoefficeent(cluster);
double coefficient = 0;
double value = coefficient + distance + avertence + clusterDes[count].gaze;
if (distance < 10)
{
predicted_cluster = clusters[clusterDes[count].getMaxProId()];
break;
}
//double value = clusterDes[count].gaze;
count++;
Debug.Log("=====兴趣度系数是" + value + "=====");
//计算每个cluster的interest_value（需改进）加入数量？
//只选取 “一个” 最优的cluster（需改进）
if (value > maxValue)
{
maxValue = value;
predicted_cluster = cluster;
}
}
return(predicted_cluster.ToList());
//List<Record> Unitypos_predicted_cluster = new List<Record>();
//List<Record> oho = predicted_cluster.ToList();
//if (predicted_cluster!=null)
//{
// foreach (var box in predicted_cluster)
// {
// Vector3 pos1 = exchangeAxis.ModelIndex_to_unityPos((float)box.posX, (float)box.posY,(float)box.posZ);
// Vector3 rot1 = new Vector3((float)box.rotX, (float)box.rotY, (float)box.rotZ);
// Unitypos_predicted_cluster.Add(new Record(pos1,rot1));
// }
//}
//return Unitypos_predicted_cluster;
}
public HashSet <Record[]> Dbscan(out List <int> clusterIds, out List <Cluster> clusterDes)
{
HashSet <Record[]> clusters;
Record[] featureData = { };
//List<Record> testPoints = Launcher.instance.history.GetRecords();
List <Record> testPoints = new List <Record>();
using (StreamReader sr = new StreamReader(Application.streamingAssetsPath + "/" + Launcher.instance.GetSceneName + "/history.txt"))
{
string line;
while ((line = sr.ReadLine()) != null)
{
if (line == "")
{
continue;
}
string[] _record = line.Split('=');
string[] liness = _record[1].Split('_');
string[] lines0 = liness[0].Split(',');
string[] lines1 = liness[1].Split(',');
Vector3 tmpPos = new Vector3(float.Parse(lines0[0]), float.Parse(lines0[1]), float.Parse(lines0[2]));
Vector3 tmpRot = new Vector3(float.Parse(lines1[0]), float.Parse(lines1[1]), float.Parse(lines1[2]));
testPoints.Add(new Record(tmpPos, tmpRot));
}
}
List <Record> testPointsIndex = new List <Record>();
var exchangeAxis = new ExchangeAxis();
foreach (var testPoint in testPoints)
{
//Vector3 iIdex =
// exchangeAxis.UnityPos_to_modelIndex(new Vector3((float)testPoint.posX, (float)testPoint.posY, (float)testPoint.posZ));
//testPointsIndex.Add(new Record(iIdex, new Vector3((float)testPoint.rotX, (float)testPoint.rotY, (float)testPoint.rotZ)));
testPointsIndex.Add(new Record(new Vector3((float)testPoint.posX, (float)testPoint.posY, (float)testPoint.posZ),
new Vector3((float)testPoint.rotX, (float)testPoint.rotY, (float)testPoint.rotZ)));
}
//
// string path = Application.streamingAssetsPath + "/" + Launcher.instance.GetSceneName + "/history.txt";
// Debug.Log(path+"---------------------------");
// //读取数据点
// using (StreamReader sr = new StreamReader(path))
// {
// string line;
// while ((line = sr.ReadLine()) != null)
// {
// if (line == "") { continue; }
// line = line.Replace("(", "").Replace(")", "");
// string[] lines = line.Split(',');
// testPoints.Add(newRecord(float.Parse(lines[0]), float.Parse(lines[1]), float.Parse(lines[2])));
// }
// }
/*
* //添加测试点
* for (int i = 0; i < 1000; i++)
* {
* //Test Points
* testPoints.Add(newRecord(1000,2,3));
* testPoints.Add(newRecord(1000,3,3));
* testPoints.Add(newRecord(1000,4,5));
* testPoints.Add(newRecord(1000,1,3));
* testPoints.Add(newRecord(1000,3,1));
*
* testPoints.Add(newRecord(2000,3,3));
* testPoints.Add(newRecord(2000,7,5));
*
* testPoints.Add(newRecord(6,2,3));
* testPoints.Add(newRecord(6,3,3));
* testPoints.Add(newRecord(6,4,5));
*
* testPoints.Add(newRecord(3000,1,3));
* testPoints.Add(newRecord(3000,3,1));
* testPoints.Add(newRecord(3000,7,5));
* testPoints.Add(newRecord(3000,3,3));
* }
*/
Debug.Log("Total number of the counts: " + testPoints.Count);
featureData = testPointsIndex.ToArray();
var dbs = new DbscanAlgorithm <Record>((x, y) => Math.Sqrt(((x.posX - y.posX) * (x.posX - y.posX)) + ((x.posY - y.posY) * (x.posY - y.posY)) + ((x.posZ - y.posZ) * (x.posZ - y.posZ))));
clusterIds = new List <int>();
dbs.ComputeClusterDbscan(allPoints: featureData, epsilon: 3, minPts: 15, clusters: out clusters, ref clusterIds);
clusterDes = dbs.GetClusterDes(clusters, clusterIds, Launcher.instance.history.getAllBrowseRecord());
//dbs.ComputeClusterDbscan(allPoints: featureData, epsilon:10, minPts: 40, clusters: out clusters);
Debug.Log("Below is the Result of the DBscan");
//int count1 = 0;
//foreach (Record[] i in clusters)
//{
// Debug.Log("--------Cluster: "+(++count1)+"--------");
// Debug.Log(i[0].posX+" "+i[0].posY+" "+i[0].posZ);
//}
return(clusters);
}
public Cluster GetPredictedCluster(Vector3 pos, Vector3 rot, List <Cluster> clusterNet, List <Record> gazePoints)
{
var exchangeAxis = new ExchangeAxis();
//Record[] predicted_cluster = null;
Cluster predicted_cluster = null;
double maxValue = -100;
Debug.Log("现在朝向" + rot);
Coeffecient getCoefficient = new Coeffecient();
int count = 0;
//List<Record[]> clusters= origin_clusters.ToList();
Dictionary <int, double> _distanceDic = distanceDic(clusterNet, pos);
var minPair = _distanceDic.Keys.Select(x => new { x, y = _distanceDic[x] }).OrderBy(x => x.y).First();
var minId = minPair.x;
var minDis = _distanceDic[minId];
_distanceDic.Remove(minId);
var secPair = _distanceDic.Keys.Select(x => new { x, y = _distanceDic[x] }).OrderBy(x => x.y).First();
var secId = secPair.x;
var secDis = _distanceDic[secId];
if (Math.Abs(minDis - secDis) < 10)
{
if (Math.Abs(GetAvertence(pos, rot, clusterNet[minId].center)) < 0.25)
{
predicted_cluster = clusterNet[minId];
}
else
{
predicted_cluster = clusterNet[secId];
}
}
else
{
foreach (var _cluster in clusterNet)
{
if (_cluster.id == minId)
{
continue;
}
double value = _cluster.gazePro + clusterNet[minId].getPro(_cluster.id) + _cluster.getSilCoe(clusterNet[minId]);
if (value > maxValue)
{
maxValue = value;
predicted_cluster = _cluster;
}
}
}
//foreach (var _cluster in clusterNet)
//{
// //var cluster = _cluster.points;
// //数据块的距离(暂时按照cluster0计算)
// //Vector3 clusterCenterPos = exchangeAxis.ModelIndex_to_unityPos((float)cluster[0].posX, (float)cluster[0].posY, (float)cluster[0].posZ);
// Vector3 centerPos = _cluster.center;
// //Vector3 clusterCenterPos = exchangeAxis.ModelIndex_to_unityPos((float)centerPos.x, (float)centerPos.y, (float)centerPos.z);
// //double distance = GetDistance(pos,clusterCenterPos);
// double distance = GetDistance(pos, centerPos);
// //偏角
// //double avertence = GetAvertence(pos,rot, clusterCenterPos);
// double avertence = GetAvertence(pos, rot, centerPos);
// //兴趣度系数（需改进）
// //double coefficient = getCoefficient.GetCoefficeent(cluster);
// double coefficient = 0;
// double value = coefficient+distance+avertence + clusterNet[count].gaze;
// if(distance<10)
// {
// //predicted_cluster = clusters[clusterNet[count].getMaxProId()];
// predicted_cluster= clusterNet[clusterNet[count].getMaxProId()];
// break;
// }
// //double value = clusterNet[count].gaze;
// count++;
// Debug.Log("=====兴趣度系数是"+value+"=====");
// //计算每个cluster的interest_value（需改进）加入数量？
// //只选取 “一个” 最优的cluster（需改进）
// if (value > maxValue)
// {
// maxValue = value;
// predicted_cluster = _cluster;
// }
//}
return(predicted_cluster);
//List<Record> Unitypos_predicted_cluster = new List<Record>();
//List<Record> oho = predicted_cluster.ToList();
//if (predicted_cluster!=null)
//{
// foreach (var box in predicted_cluster)
// {
// Vector3 pos1 = exchangeAxis.ModelIndex_to_unityPos((float)box.posX, (float)box.posY,(float)box.posZ);
// Vector3 rot1 = new Vector3((float)box.rotX, (float)box.rotY, (float)box.rotZ);
// Unitypos_predicted_cluster.Add(new Record(pos1,rot1));
// }
//}
//return Unitypos_predicted_cluster;
}
