// This method performs some animations.
private void timer1_Tick(object sender, EventArgs e)
{
if (tabControl1.SelectedTab == tabPage2)
{
// Animate the points.
PointDataSeries ds = chartPlotter1.DataSeries[0] as PointDataSeries;
for (int i = 0; i < ds.Points.Count; i++)
{
PointDataSeries.ChartPoint s = ds.Points[i];
s.Coords.X += (float)((randGen.NextDouble() - 0.5) / 100.0);
s.Coords.Y += (float)((randGen.NextDouble() - 0.5) / 100.0);
ds.Points[i] = s;
}
}
else if (tabControl1.SelectedTab == tabPage1)
{
// Animate the cosine function.
if (++tickCounter == 100)
{
tickCounter = 0;
}
cosFun.Scale = Math.Sin(tickCounter / 50.0 * Math.PI) * 2.0 + 3.0;
}
else if (tabControl1.SelectedTab == tabPage5)
{
if (checkBox3.Checked)
{
MakeNoise();
}
}
}
private void ShowTeachingSet()
{
_teachingSetDataSeries.Points.Clear();
foreach (TeachingSet.Element elem in _teachingSet)
{
PointF pointLocation =
new PointF((float)elem.Inputs[0], (float)elem.Inputs[1]);
int output = (int)((elem.ExpectedOutputs[0] + 1.0) * 127.5);
Color pointColor = Color.FromArgb(output, output, output);
PointDataSeries.ChartPoint chartPoint =
new PointDataSeries.ChartPoint(pointLocation, pointColor, false);
_teachingSetDataSeries.Points.Add(chartPoint);
}
}
private void EvaluateObject()
{
_examinedNeuron.Weights[0] = (double)uiWeight1.Value;
_examinedNeuron.Weights[1] = (double)uiWeight2.Value;
double[] inputs = new double[]
{
(double)uiObject1.Value,
(double)uiObject2.Value
};
double response = _examinedNeuron.Response(inputs);
double strength =
_examinedNeuron.MemoryTraceStrength(StrengthNorm.Euclidean);
Color signalColor;
if (Math.Abs(response) < 0.2 * strength)
{
signalColor = Color.DarkCyan;
}
else if (response < 0)
{
signalColor = Color.Blue;
}
else
{
signalColor = Color.Red;
}
// 8 digits should be enough.
uiResponse.Text = response.ToString("g8");
uiResponse.ForeColor = uiKeyObject.ForeColor = signalColor;
PointF weightsPoint = new PointF(
(float)_examinedNeuron.Weights[0],
(float)_examinedNeuron.Weights[1]);
PointF inputPoint = new PointF(
(float)inputs[0],
(float)inputs[1]);
PointDataSeries.ChartPoint weightsSignal = new PointDataSeries.ChartPoint(
weightsPoint, Color.Green, true);
PointDataSeries.ChartPoint inputSignal = new PointDataSeries.ChartPoint(
inputPoint, signalColor, true);
_chartPoints.Points[0] = weightsSignal;
_chartPoints.Points[1] = inputSignal;
}
private void ShowOnePoint()
{
//{tga to eliminate DrawingLine from last point
if (_lastchartPointIndexOf >= 0)
{
_pointDataSeries.Points.RemoveAt(_lastchartPointIndexOf);
PointDataSeries.ChartPoint chartPointLast =
new PointDataSeries.ChartPoint(new PointF((float)_lastchartPointX, (float)_lastchartPointY),
_lastchartPointColor, false);
_pointDataSeries.Points.Add(chartPointLast);
}
//tga}
double x = _random.NextDouble() * _xScale + _xOffset;
double y = _random.NextDouble() * _yScale + _yOffset;
Color color = _neuronResponseFunction.Compute(x, y);
PointDataSeries.ChartPoint chartPoint =
new PointDataSeries.ChartPoint(new PointF((float)x, (float)y),
color, true);
_pointDataSeries.Points.Add(chartPoint);
//{tga to eliminate DrawingLine from last point
_lastchartPointIndexOf = _pointDataSeries.Points.IndexOf(chartPoint);
_lastchartPointX = x;
_lastchartPointY = y;
_lastchartPointColor = color;
//tga}
uiPointCoords.Text = String.Format("Point: ({0:g6}, {1:g6})", x, y);
double originalResponse =
_neuronResponseFunction.Neuron.Response(new double[] { x, y });
uiResponse.Text = String.Format("Result: {0:g6}", originalResponse);
uiResponse.ForeColor = color;
}
