| public GetLayerBiasActivation ( int l ) : double | ||
| l | int | The layer. |
| 리턴 | double | |
private void DrawNeuralNetPair(Diagram diagram, out List<ShapeNode>[] nodes, BasicNetwork neuralNet)
{
if (diagram.Items.Count > 0)
diagram.ClearAll();
ProcessPair pp = cbProcessPair.SelectedItem as ProcessPair;
TemplXML.FormData form = ConvertDataArrayToXml(templ, trainingData[pp.Pair].InputArray);
double dx = 400;
double rastNode = 30;
double startYF = 50;
double startX = dx + 50; // + (neuralNet.LayerCount - 1) * 300;
double startY = 50;
double diam = 30;
double startYMax = startY;
nodes = new List<ShapeNode>[neuralNet.LayerCount];
string label = "null";
graphPairLinkInput = new List<DiagramLink>(neuralNet.Flat.LayerCounts[neuralNet.LayerCount - 1]);
for (int i = neuralNet.LayerCount - 1; i >= 0; i--)
{
List<ShapeNode> curN = new List<ShapeNode>();
for (int j = 0; j < neuralNet.Flat.LayerCounts[i]; j++)
{
ShapeNode tmp = DiagramHelper.CreateNode(diagram, startX, startY, diam, diam, j.ToString());
tmp.MouseLeftButtonDown += nodeSelected_MouseLeftButtonDown;
curN.Add(tmp);
if (i == neuralNet.LayerCount - 1 && j < neuralNet.InputCount)
{
ShapeNode q = DiagramHelper.CreateNode(Shapes.Rectangle, diagram, startX - dx - 200, startY - 10, 200, 50, form.Values[j].Field.Title);
if (form.Values[j] is TemplXML.FormDataValueNumber)
{
var tmpF = form.Values[j] as TemplXML.FormDataValueNumber;
label = string.Format("{0}", tmpF.Value);
}
else
{
var tmpF = form.Values[j] as TemplXML.FormDataValueSelect;
label = tmpF.Value.Title;
}
var tmpLink = DiagramHelper.CreateLink(diagram, q, tmp, label);
tmpLink.MouseLeftButtonDown += linkSelect_MouseLeftButtonDown;
graphPairLinkInput.Add(tmpLink);
}
startY += diam + rastNode;
}
nodes[i] = curN;
startX += dx;
if (startYMax < startY) startYMax = startY;
if (i != 0)
startY = startYMax / 2 - neuralNet.Flat.LayerCounts[i - 1] * (rastNode + diam) / 2;
}
string tmpWeigth;
int countN;
for (int i = neuralNet.LayerCount - 1; i > 0; i--)
{
countN = countN = neuralNet.Flat.LayerCounts[i - 1];
if (i - 1 == neuralNet.LayerCount - 2 && neuralNet.GetLayerBiasActivation(i - 1) > 0)
countN -= 1;
for (int x = 0; x < neuralNet.Flat.LayerCounts[i]; x++)
{
for (int y = 0; y < countN; y++)
{
tmpWeigth = neuralNet.GetWeight(neuralNet.LayerCount - i - 1, x, y).ToString("F4");
var link = DiagramHelper.CreateLink(diagram, nodes[i][x], nodes[i - 1][y], tmpWeigth);
link.MouseLeftButtonDown += linkSelect_MouseLeftButtonDown;
}
}
}
}
/// <summary>
/// Craete a freeform network from a basic network.
/// </summary>
/// <param name="network">The basic network to use.</param>
public FreeformNetwork(BasicNetwork network)
{
if (network.LayerCount < 2)
{
throw new FreeformNetworkError(
"The BasicNetwork must have at least two layers to be converted.");
}
// handle each layer
IFreeformLayer previousLayer = null;
for (int currentLayerIndex = 0;
currentLayerIndex < network
.LayerCount;
currentLayerIndex++)
{
// create the layer
IFreeformLayer currentLayer = _layerFactory.Factor();
// Is this the input layer?
if (_inputLayer == null)
{
_inputLayer = currentLayer;
}
// Add the neurons for this layer
for (int i = 0; i < network.GetLayerNeuronCount(currentLayerIndex); i++)
{
// obtain the summation object.
IInputSummation summation = null;
if (previousLayer != null)
{
summation = _summationFactory.Factor(network
.GetActivation(currentLayerIndex));
}
// add the new neuron
currentLayer.Add(_neuronFactory.FactorRegular(summation));
}
// Fully connect this layer to previous
if (previousLayer != null)
{
ConnectLayersFromBasic(network, currentLayerIndex - 1,
previousLayer, currentLayer);
}
// Add the bias neuron
// The bias is added after connections so it has no inputs
if (network.IsLayerBiased(currentLayerIndex))
{
IFreeformNeuron biasNeuron = _neuronFactory
.FactorRegular(null);
biasNeuron.IsBias = true;
biasNeuron.Activation = network
.GetLayerBiasActivation(currentLayerIndex);
currentLayer.Add(biasNeuron);
}
// update previous layer
previousLayer = currentLayer;
}
// finally, set the output layer.
_outputLayer = previousLayer;
}
private void DrawNeuralNet(Diagram diagram, out List<ShapeNode>[] nodes, BasicNetwork neuralNet)
{
if (diagram.Items.Count > 0)
diagram.ClearAll();
//получение шаблона
InitEvent netInit = cbTrainsLog.SelectedItem as InitEvent;
//TemplXML.FormTemplate templ;
string pathXML = netInit.Path.Replace(".np4", ".xml");
if (!File.Exists(pathXML))
MessageBox.Show("Форма не найдена");
templ = TemplXML.FormTemplate.FromXml(XElement.Load(pathXML));
double dx = 400;
double rastNode = 30;
double startYF = 50;
double startX = dx + 50; // + (neuralNet.LayerCount - 1) * 300;
double startY = 50;
double diam = 30;
double startYMax = startY;
nodes = new List<ShapeNode>[neuralNet.LayerCount];
for (int i = neuralNet.LayerCount - 1 ; i >= 0; i--)
{
List<ShapeNode> curN = new List<ShapeNode>();
for (int j = 0; j < neuralNet.Flat.LayerCounts[i]; j++)
{
ShapeNode tmp = DiagramHelper.CreateNode(diagram, startX, startY, diam, diam, j.ToString());
tmp.MouseLeftButtonDown += nodeSelected_MouseLeftButtonDown;;
curN.Add(tmp);
if (i == neuralNet.LayerCount - 1 && j <neuralNet.InputCount)
{
ShapeNode q = DiagramHelper.CreateNode(Shapes.Rectangle, diagram, startX - dx, startY, 200, 50, templ.Fields[j].Title);
DiagramLink link = DiagramHelper.CreateLink(diagram, q, tmp);
link.MouseLeftButtonDown += linkSelect_MouseLeftButtonDown;
}
startY += diam + rastNode;
}
nodes[i] = curN;
startX += dx;
if (startYMax < startY) startYMax = startY;
if(i != 0)
startY = startYMax / 2 - neuralNet.Flat.LayerCounts[i - 1] * (rastNode + diam) / 2;
}
string tmpWeigth;
int countN;
for (int i = neuralNet.LayerCount - 1; i > 0; i--)
{
countN = countN = neuralNet.Flat.LayerCounts[i - 1];
if (i - 1 == neuralNet.LayerCount - 2 && neuralNet.GetLayerBiasActivation(i - 1) > 0)
countN -= 1;
for (int x = 0; x < neuralNet.Flat.LayerCounts[i]; x++)
{
for (int y = 0; y < countN; y++)
{
tmpWeigth = neuralNet.GetWeight(neuralNet.LayerCount - i - 1, x, y).ToString("F4");
var link = DiagramHelper.CreateLink(diagram, nodes[i][x], nodes[i - 1][y], tmpWeigth);
link.MouseLeftButtonDown += linkSelect_MouseLeftButtonDown;
}
}
}
}