private IEnumerable <ClusterObjects> ConverterDados()
{
var dados = new List <ClusterObjects>();
foreach (var usuario in _usuariosPesquisa)
{
var cluster = new ClusterObjects()
{
Id = usuario.Id,
Genero = usuario.Genero,
DataNascimento = usuario.DataNascimento,
IdIdiomaOrigem = usuario.IdiomaOrigem.Id,
IdIdiomaParaAprender = usuario.IdiomaParaAprender.Id,
IdIdiomaFluenteSecundario = usuario.IdiomaFluenteSecundario.Id,
IdAreaEstudoDominioGeral = usuario.AreaEstudoDominioGeral.Id,
IdAreaEstudoDominioEspecifica = usuario.AreaEstudoDominioEspecifica.Id,
IdAreaEstudoParaAprenderGeral = usuario.AreaEstudoParaAprenderGeral.Id,
IdAreaEstudoParaAprenderEspecifico = usuario.AreaEstudoParaAprenderEspecifico.Id,
TipoIteracao = usuario.TipoIteracao
};
}
dados.Add(InverterPreferenciasParaPesquisa());
return(dados);
}
public static List <ClusterObjects> ExtractClusterFromIEPF(List <PolarPointRssiExtended> ptList, List <PolarPointRssiExtended> ptIEPF)
{
List <ClusterObjects> list_of_clusters = new List <ClusterObjects>();
/// Maybe sort
for (int i = 0; i < ptIEPF.Count - 2; i += 2)
{
ClusterObjects cluster = new ClusterObjects(ptList.GetRange(ptList.IndexOf(ptIEPF[i]), ptList.IndexOf(ptIEPF[i + 1]) - ptList.IndexOf(ptIEPF[i])));
list_of_clusters.Add(cluster);
}
return(list_of_clusters);
}
/// <summary>
/// Detect and return a list of Clusters point in pointList
/// </summary>
/// <param name="pointsList"></param>
/// <param name="thresold"></param>
/// <param name="mininum_amount_of_points"></param>
/// <returns></returns>
public static List <ClusterObjects> DetectClusterOfPoint(List <PolarPointRssiExtended> pointsList, double thresold, int mininum_amount_of_points = 5)
{
/// ABD Stand for Adaptative breakpoint Detection
List <ClusterObjects> listOfClusters = new List <ClusterObjects>();
ClusterObjects cluster = new ClusterObjects();
int i;
for (i = 1; i < pointsList.Count - 1; i++)
{
PolarPointRssiExtended point_n_minus_1 = pointsList[i - 1];
PolarPointRssiExtended point_n_plus_1 = pointsList[i + 1];
PolarPointRssiExtended point_n = pointsList[i];
//double dist_n_minus_1 = point_n_minus_1.Distance;
//double delta_theta = Math.Abs(point_n_minus_1.Angle - point_n.Angle);
//double lambda = point_n_plus_1.Angle - point_n_minus_1.Angle;
double ABD_Thresold = thresold; // dist_n_minus_1 * (Math.Sin(delta_theta) / Math.Sin(lambda - delta_theta));
double distance_between_point = Toolbox.Distance(point_n, point_n_minus_1);
if (distance_between_point < ABD_Thresold)
{
cluster.points.Add(point_n);
}
else
{
if (Toolbox.Distance(point_n_plus_1, point_n_minus_1) <= 2 * thresold)
{
//cluster.points.Add(point_n);
}
else
{
if (cluster.points.Count() > mininum_amount_of_points)
{
listOfClusters.Add(cluster);
}
cluster = new ClusterObjects();
}
}
}
if (cluster.points.Count() > mininum_amount_of_points)
{
listOfClusters.Add(cluster);
}
return(listOfClusters);
}
public Segment DetectLine(ClusterObjects blob, double thresold, double alignNbr, int moy = 5)
{
List <PolarPointRssi> pointList = blob.points.Select(x => x.Pt).ToList();
List <double> derivate1 = new List <double>();
List <double> derivate2 = new List <double>();
Segment line = new Segment();
int i;
for (i = 0; i < pointList.Count - 1; i++)
{
derivate1.Add(Math.Abs(pointList[i].Distance - pointList[i + 1].Distance));
}
for (i = 0; i < derivate1.Count - 1; i++)
{
derivate2.Add(Math.Abs(derivate1[i] - derivate1[i + 1]));
}
uint nbrOfCurrentAlign = 0;
for (i = 0; i < derivate2.Count - 1; i++)
{
if (derivate2[i] >= 0 && derivate2[i] <= thresold)
{
nbrOfCurrentAlign++;
}
else if (nbrOfCurrentAlign > 0)
{
if (nbrOfCurrentAlign >= alignNbr)
{
return(CreateLineSegment(pointList, moy));
}
nbrOfCurrentAlign = 0;
}
}
if (nbrOfCurrentAlign >= alignNbr)
{
return(CreateLineSegment(pointList, moy));
}
return(line);
}
public Cup DetectCup(ClusterObjects cluster)
{
/// TEMPORARY NEED TO EDIT: ONLY FOR DEBUG PURPOSE
PolarPointRssi begin_point = cluster.points[0].Pt;
PolarPointRssi end_point = cluster.points[cluster.points.Count - 1].Pt;
double lenght_of_cluster = Toolbox.Distance(begin_point, end_point);
if (lenght_of_cluster >= 0.040 && lenght_of_cluster <= 0.08)
{
List <PointD> pointDs = cluster.points.Select(x => Toolbox.ConvertPolarToPointD(x.Pt)).ToList();
double median = 0.80;
double b = cluster.points[(int)(cluster.points.Count() * median)].Pt.Rssi;
double e = cluster.points[(int)(cluster.points.Count() * (1 - median))].Pt.Rssi;
double moyenne = (b + e) / 2;
Color color = Color.White;
if (moyenne >= 9000 && moyenne <= 12000)
{
color = Color.Green;
}
else if (moyenne >= 12000 && moyenne <= 14000)
{
color = Color.Red;
}
else
{
return(new Cup());
}
//Console.WriteLine(moyenne);
PointD center_point = GetMediumPoint(pointDs);
return(new Cup(center_point, 0.065, color));
}
else
{
return(null);
}
}
