private List<String> GetSimilaresDatabaseKmeans(List<Double> descriptoresEntrada)
{
ModeloSimilitudEntities db = new ModeloSimilitudEntities();
List<canciones> ListaCanciones = db.canciones.ToList();
Double[] vectorEntrada = descriptoresEntrada.ToArray();
vectorEntrada = Normalizar(vectorEntrada);
Double[][] matriz = csvtoMatrix("descriptoresNormalizados");
int Nclusters = 7;
KMeans kmeans = new KMeans(Nclusters, Accord.Math.Distance.Chebyshev);
int[] indices = kmeans.Compute(matriz);
int Cluster =kmeans.Nearest(vectorEntrada);
int nroSimilares = 10;
int[] indiceSimilar=new int[nroSimilares];
for(int j=0;j<nroSimilares;j++){
Double distancia = 1000;
for (int i = 0; i < indices.Length; i++)
{
if (!indiceSimilar.Contains(i))
{
if (Cluster == indices[i])
{
Double distanciatemp = Accord.Math.Distance.Chebyshev(vectorEntrada, matriz[i]);
if (distanciatemp < distancia)
{
distancia = distanciatemp;
indiceSimilar[j] = i;
}
}
}
}
}
List<String> listaSimilares = new List<String>();
foreach (int i in indiceSimilar)
{
listaSimilares.Add(ListaCanciones[i].id_spotify.Substring(14));
}
//string select="select * from canciones where energy={0} and liveness={1} and tempo={2} and speechiness={3} and acousticness={4} and loudness={5} and valence={6} and danceability={7} and instrumentalness={8} and key={9}";
//string select2 = "select * from canciones";
//for(int j=0;j<cercanos.Length;j++){
// object[] parameters = new object[10];
// for (int i = 0; i < 10; i++)
// {
// SqlParameter param = new SqlParameter("i", cercanos[j][i]);
// parameters[i] = cercanos[j][i];
// }
// var stores = db.Database.SqlQuery<canciones>(select, parameters).ToList();
// listaSimilares.Add(stores[0].id_spotify);
//}
return listaSimilares;
}
