static void TestStandardPerceptron()
{
IPerceptron brain = new StandardPerceptron(2, 0.01m, Functions.Activation.BinaryStep, Functions.ActivationDerivatives.BinaryStep);
Dictionary <decimal[], decimal> data = new Dictionary <decimal[], decimal>();
data.Add(new decimal[] { 0, 0 }, 0);
data.Add(new decimal[] { 1, 0 }, 0);
data.Add(new decimal[] { 0, 1 }, 0);
data.Add(new decimal[] { 1, 1 }, 1);
Console.WriteLine("BEFORE TRAINING");
Console.WriteLine($"0, 0 -> {brain.CalculateOutput(new decimal[] { 0, 0 })}");
Console.WriteLine($"1, 0 -> {brain.CalculateOutput(new decimal[] { 1, 0 })}");
Console.WriteLine($"0, 1 -> {brain.CalculateOutput(new decimal[] { 0, 1 })}");
Console.WriteLine($"1, 1 -> {brain.CalculateOutput(new decimal[] { 1, 1 })}");
brain.StartTraining(data, 1000);
Console.WriteLine("AFTER TRAINING");
Console.WriteLine($"0, 0 -> {brain.CalculateOutput(new decimal[] { 0, 0 })}");
Console.WriteLine($"1, 0 -> {brain.CalculateOutput(new decimal[] { 1, 0 })}");
Console.WriteLine($"0, 1 -> {brain.CalculateOutput(new decimal[] { 0, 1 })}");
Console.WriteLine($"1, 1 -> {brain.CalculateOutput(new decimal[] { 1, 1 })}");
Console.ReadKey();
}
static void TestPerceptronParametersDirectVisualization()
{
IPerceptron perceptron = new StandardPerceptron(12, 0, null, null);
foreach (decimal w in perceptron.Weights)
{
Console.WriteLine(w);
}
IDirectParametersVisualizer visualizer = new PerceptronDirectParametersVisualizer(perceptron, DirectParametersVisualizationType.SquareOfRGB);
Bitmap img = visualizer.Visualize();
for (int y = 0; y < img.Height; y++)
{
for (int x = 0; x < img.Width; x++)
{
Color c = img.GetPixel(x, y);
Console.WriteLine($"{x}, {y} = [{c.R}, {c.G}, {c.B}]");
}
}
Console.ReadKey();
}
