public static void ToTreeView(TreeView t, NeuralNetwork.NeuralNet.NeuralNetwork nn)
{
t.Nodes.Clear();
TreeNode root = new TreeNode("NeuralNetwork");
nn.Layers.ForEach((layer) =>
{
TreeNode lnode = new TreeNode("Layer");
layer.Neurons.ForEach((neuron) =>
{
TreeNode nnode = new TreeNode("Neuron");
nnode.Nodes.Add("Bias: " + neuron.Bias.ToString());
nnode.Nodes.Add("Delta: " + neuron.Delta.ToString());
nnode.Nodes.Add("Value: " + neuron.Value.ToString());
neuron.Dendrites.ForEach((dendrite) =>
{
TreeNode dnode = new TreeNode("Dendrite");
dnode.Nodes.Add("Weight: " + dendrite.Weight.ToString());
nnode.Nodes.Add(dnode);
});
lnode.Nodes.Add(nnode);
});
root.Nodes.Add(lnode);
});
//root.ExpandAll();
t.Nodes.Add(root);
}
public static void ToPictureBox(PictureBox p, NeuralNetwork.NeuralNet.NeuralNetwork nn, int X, int Y)
{
int neuronWidth = 30;
int neuronDistance = 50;
int layerDistance = 50;
int fontSize = 8;
Bitmap b = new Bitmap(p.Width, p.Height);
Graphics g = Graphics.FromImage(b);
g.FillRectangle(Brushes.White, g.ClipBounds);
int y = Y;
for (int l = 0; l < nn.Layers.Count; l++)
{
Layer layer = nn.Layers[l];
int x = X - (neuronDistance * (layer.Neurons.Count / 2));
for (int n = 0; n < layer.Neurons.Count; n++)
{
Neuron neuron = layer.Neurons[n];
for (int d = 0; d < neuron.Dendrites.Count; d++)
{
// TO DO: optionally draw dendrites between neurons
}
;
g.FillEllipse(Brushes.WhiteSmoke, x, y, neuronWidth, neuronWidth);
g.DrawEllipse(Pens.Gray, x, y, neuronWidth, neuronWidth);
g.DrawString(neuron.Value.ToString("0.00"), new Font("Arial", fontSize), Brushes.Black, x + 2, y + (neuronWidth / 2) - 5);
x += neuronDistance;
}
;
y += layerDistance;
}
;
p.Image = b;
}
