public double DistInterNeurone(Neurone n2)
{
double dist = 0;
for (int i = 0; i < poids.Count; i++)
{
dist = dist + (poids[i] - n2.poids[i]) * (poids[i] - n2.poids[i]);
}
return(Math.Sqrt(dist));
}
public CarteSOM(int nbcol, int nblignes, int nbpoids, int valeurmax)
{
this.nbcol = nbcol;
this.nblignes = nblignes;
tab = new Neurone[nbcol, nblignes];
for (int i = 0; i < nbcol; i++)
{
for (int j = 0; j < nblignes; j++)
{
tab[i, j] = new Neurone(nbpoids, valeurmax);
}
}
}
private void button2_Click(object sender, EventArgs e)
{
listclasses.Clear();
// Regroupement pour obtenir 2 classes
SOM.regroupement(lobs, 6);
pen.Color = Color.White;
g.FillRectangle(pen.Brush, 0, 0, bmp.Width, bmp.Height);
// pour chaque x,y de l'image
// créer lobservation x,y
// Pour chaque neurone neur de chaque classe k, trouver le gagnant
// cad trouver le neurone qui minimise neur.calculerreur ( obs)
// Colorer en fct de la classe
List <Color> couleurs = new List <Color> {
Color.Blue, Color.Red, Color.Green, Color.Orange, Color.DeepPink, Color.Purple
};
for (int i = 0; i < bmp.Width; i++)
{
for (int j = 0; j < bmp.Height; j++)
{
Observation obs = new Observation(i, j);
int indexClasse = 0;
Neurone neurChoisit = listclasses[0].GetNeurones()[0];
for (int k = 0; k < listclasses.Count; k++)
{
foreach (Neurone neur in listclasses[k].GetNeurones())
{
if (neur.CalculeErreur(obs) < neurChoisit.CalculeErreur(obs))
{
indexClasse = k;
neurChoisit = neur;
}
}
}
bmp.SetPixel(i, j, couleurs[indexClasse]);
}
}
// Affichage final des 6 classes
int x, y;
pen.Color = Color.Blue;
foreach (Neurone n in listclasses[0].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
pen.Color = Color.Red;
foreach (Neurone n in listclasses[1].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
pen.Color = Color.Green;
foreach (Neurone n in listclasses[2].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
pen.Color = Color.Orange;
foreach (Neurone n in listclasses[3].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
pen.Color = Color.DeepPink;
foreach (Neurone n in listclasses[4].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
pen.Color = Color.Purple;
foreach (Neurone n in listclasses[5].GetNeurones())
{
x = Convert.ToInt32(n.GetPoids(0));
y = Convert.ToInt32(n.GetPoids(1));
g.DrawEllipse(pen, x - 2, y - 2, 4, 4);
}
AfficheDonnees();
pictureBox1.Refresh();
}
public Classe(Neurone neurone)
{
ListNeurones.Add(neurone);
}
