protected void OnMouseUp(object sender, MouseEventArgs e)
{
if (e.Button == MouseButtons.Left)
{
choosedinputNeuron = null;
choosedNeuron = null;
net.SetSelection(net.GetNeuronsByRectangle(currentRect));
selectionRectangle = false;
currentRect = new Rectangle();
Refresh();
}
mStatus.UpEvent(e);
}
protected void OnMouseDown(object sender, MouseEventArgs e)
{
mStatus.DownEvent(e);
((Control)sender).Focus();
if (e.Button == MouseButtons.Left)
{
if ((choosedinputNeuron = GetinputByPosition(e.Location)) == null)
{
choosedNeuron = GetNeuronByPosition(e.Location);
}
currentRect.Location = new Point(e.X, e.Y);
selectionRectangle = true;
}
}
protected void OnMouseDoubleClick(object sender, MouseEventArgs e)
{
if (e.Button == MouseButtons.Left)
{
if ((choosedinputNeuron = GetinputByPosition(e.Location)) != null)
{
NeuroninputInformation dlg = new NeuroninputInformation(choosedinputNeuron);
dlg.ShowDialog();
Refresh();
}
else if ((choosedNeuron = GetNeuronByPosition(e.Location)) != null)
{
NeuronInformation dlg = new NeuronInformation(choosedNeuron);
dlg.ShowDialog();
}
}
}
public NeuroninputInformation(NeuronInput ninput)
{
InitializeComponent();
neuroninput = ninput;
inputValueText.Text = neuroninput.value.ToString("0.00");
}
public Sinaps(NeuronInput input)
{
frominput = input;
value = ((float)rand.Next(interval.X, interval.Y)) / multiplier;
// value = 0.2f;
}
public Sinaps(NeuronInput input, Neuron neuron)
{
fromNeuron = neuron;
frominput = input;
value = ((float)rand.Next(interval.X, interval.Y)) / multiplier;
}
private NeuronNet AcceptJson(Root2 root2)
{
NeuronNet net = new NeuronNet();
for (int i = 0; i < root2.inputss.Count; i++)
{
PointF pointF = new PointF();
pointF.X = (float)root2.inputss[i].Position.X;
pointF.Y = (float)root2.inputss[i].Position.Y;
NeuronInput neuron = new NeuronInput((float)root2.inputss[i].value, root2.inputss[i].Name, pointF);
neuron.positionChanged = root2.inputss[i].positionChanged;
neuron.wasPainted = root2.inputss[i].wasPainted;
net.inputss.Add(neuron);
}
for (int i = 0; i < root2.NeuronGroups.Count; i++)
{
NeuronGroup neurongroup = new NeuronGroup();
neurongroup.Neurons = root2.NeuronGroups[i].Neurons;
neurongroup.SecondActivate = root2.NeuronGroups[i].SecondActivate;
neurongroup.SumForSoftMax = (float)root2.NeuronGroups[i].SumForSoftMax;
neurongroup.allNeuronsWasPainted = root2.NeuronGroups[i].allNeuronsWasPainted;
net.NeuronGroups.Add(neurongroup);
}
for (int i = 0; i < root2.studyPairss.Count; i++)
{
StudyPair studyPair = new StudyPair();
for (int j = 0; j < root2.studyPairss[i].inputs.Count; j++)
{
studyPair.inputs.Add((float)root2.studyPairss[i].inputs[j]);
}
for (int j = 0; j < root2.studyPairss[i].quits.Count; j++)
{
studyPair.quits.Add((float)root2.studyPairss[i].quits[j]);
}
for (int j = 0; j < root2.studyPairss[i].realQuits.Count; j++)
{
studyPair.realQuits.Add((float)root2.studyPairss[i].realQuits[j]);
}
net.studyPairss.Add(studyPair);
}
net.E = (float)root2.E;
net.moment = (float)root2.moment;
for (int i = 0; i < root2.errors.Count; i++)
{
PointF pointF = new PointF();
pointF.X = (float)root2.errors[i].X;
pointF.Y = (float)root2.errors[i].Y;
net.errors.Add(pointF);
}
for (int i = 0; i < root2.normalizedErrors.Count; i++)
{
PointF pointF = new PointF();
pointF.X = (float)root2.normalizedErrors[i].X;
pointF.Y = (float)root2.normalizedErrors[i].Y;
net.normalizedErrors.Add(pointF);
}
net.EraCount = root2.EraCount;
net.currentSelection = new NeuronGroup(0);
net.recognitionResults = new List <RecognitionResult>();
net.StudyPairsLoaded = root2.StudyPairsLoaded;
net.InputsSum = (float)root2.InputsSum;
net.allInputsWasPainted = root2.allInputsWasPainted;
net.minError = (float)root2.minError;
net.NormalizeOutputValue = (float)root2.NormalizeOutputValue;
net.biasX = (float[])root2.biasX;
net.biasY = (float[])root2.biasY;
net.scaleX = (float[])root2.scaleX;
net.scaleY = (float[])root2.scaleY;
net.StudyLimit = (float)root2.StudyLimit;
net.AccessChangeNet = root2.AccessChangeNet;
return(net);
}