void Calculate()
{
float stepSize = 1f / steps;
Color[] colors = new Color[(steps + 1) * (steps + 1)];
for (int x = 0; x <= steps; x++)
{
for (int y = 0; y <= steps; y++)
{
double res = perceptron.CalculateOutput(new double[] { x *stepSize, y *stepSize });
colors [y * (steps + 1) + x] = new Color(1 - (float)res, (float)res, 0);
}
}
foreach (var ti in perceptron.trainingData.itens)
{
var x = Mathf.FloorToInt((float)ti.input [0] * steps);
var y = Mathf.FloorToInt((float)ti.input [1] * steps);
float res = (float)perceptron.CalculateOutput(new double[] { x *stepSize, y *stepSize }) * 0.5f;
colors [y * (steps + 1) + x] = new Color(0.5f - res, res, 0);
}
Texture2D t2d = new Texture2D(steps + 1, steps + 1);
t2d.SetPixels(colors);
t2d.Apply();
GetComponent <RawImage> ().texture = t2d;
}
public void PerceptronWeightsAreTakenIntoAccount()
{
LayerStructure structure = new LayerStructure(9, new[] { 7 }, 5);
Perceptron perceptron = new Perceptron(GetInitParamsByLayerStructure(structure));
perceptron.FillWeightsRandomly();
float[] inputVector = new[] { 0.44f, 0.354f, 0.667f, 0, 0.454f, 0.48f, 0.456f, 0.44f, 0.456f };
float[] outputVector = perceptron.CalculateOutput(inputVector);
Assert.AreNotEqual(inputVector, outputVector, "Input and output vectors are same");
}
public void PerceptronOutputIsFromZeroToOne()
{
LayerStructure structure = new LayerStructure(9, new[] { 6, 6 }, 5);
Perceptron perceptron = new Perceptron(GetInitParamsByLayerStructure(structure));
perceptron.FillWeightsRandomly();
float[] inputVector = { 0.44f, 0.354f, 0.667f, 0, 0.454f, 0.48f, 0.456f, 0.44f, 0.456f };
float[] outputVector = perceptron.CalculateOutput(inputVector);
int correctValuesCount = outputVector.Count(value => value > 0 && value <= 1);
Assert.AreEqual(outputVector.Count(), correctValuesCount);
}
void OnProjectileIsThrown(Projectitle0327 projectile)
{
double result = perceptron.CalculateOutput(projectile.color, projectile.shape);
if (result == 0)
{
m_rigidBody.isKinematic = false;
m_animator.SetTrigger("Crouch");
}
else
{
m_rigidBody.isKinematic = true;
}
perceptron.AcquireKnowledge(projectile.name, projectile.result, projectile.color, projectile.shape);
}
public void TestPerceptron_PositiveInput_TrueResult(string filePath)
{
Assert.AreEqual(1, _neuron.CalculateOutput(filePath));
}
