public static void ConverttoTreeView(TreeView t, Neural_Models.NeuralNetwork nn)
{
//reset Previous Drawing
t.Nodes.Clear();
TreeNode root = new TreeNode("NeuralNetwork");
nn.Layers.ForEach((layer) =>
{
//Define Layer Node
TreeNode Layernode = new TreeNode("Layer");
layer.Neurons.ForEach((neuron) =>
{
//Define Neuron Node
TreeNode nnode = new TreeNode("Neuron");
nnode.Nodes.Add("Bias: " + neuron.Bias.ToString());
nnode.Nodes.Add("Delta: " + neuron.Delta.ToString());
nnode.Nodes.Add("Traning Value: " + neuron.TrainingValue.ToString());
//but before Augmenting the neuron
//define neuron's subobjects now:
//FOREACH Neuron, Define Synapses
neuron.Synapses.ForEach((synapse) =>
{
//FOREACH Synapse, define the weight!
//define a synapse on the treeView
TreeNode synnode = new TreeNode("Synapse");
//Add weight on the synapse
synnode.Nodes.Add("Weight: " + synapse.Weight.ToString());
//Finally, Augment the synapse object to the tree
synnode.Nodes.Add(synnode);
});
//Finally, Augment Neuron to the Layer !
Layernode.Nodes.Add(nnode);
});
//Finally, Augment the Layer to the root !
root.Nodes.Add(Layernode);
});
//Finally, Augment the root to the Treeview!
t.Nodes.Add(root);
}
public static void ToPictureBox(PictureBox p, Neural_Models.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];
// TODO: optionally draw Synapsess between neurons
//for (int d = 0; d < neuron.Synapses.Count; d++)
//{
//};
g.FillEllipse(Brushes.WhiteSmoke, x, y, neuronWidth, neuronWidth);
g.DrawEllipse(Pens.Gray, x, y, neuronWidth, neuronWidth);
g.DrawString(neuron.TrainingValue.ToString("0.00"), new Font("Arial", fontSize), Brushes.Black, x + 2, y + (neuronWidth / 2) - 5);
x += neuronDistance;
}
;
y += layerDistance;
}
;
p.Image = b;
}
