public void HyperNormalize()
{
double[] values = hyper_normalizer.GetValues();
double min = values[0];
double max = values[0];
foreach (var value in values)
{
Assert.GreaterOrEqual(value, -1);
Assert.LessOrEqual(value, 1);
if (min > value)
{
min = value;
}
if (max < value)
{
max = value;
}
}
MyAssert.CloseTo(min * DataNormalizer.SAFE_KOEFF, -1, 0.025);
MyAssert.CloseTo(max * DataNormalizer.SAFE_KOEFF, 1, 0.025);
}
public void TestCanSetAnswer()
{
Neuron n = new Neuron();
n.Connect(new BiasNeuron(), 1);
InputNeuron input = new InputNeuron();
n.Connect(input, 1);
n.SetWeight(0, 1);
input.Input = 1;
var desired = 1 / (1 + Math.Pow(Math.E, -2));
n.SetAnswer(desired);
n.PropagateBackwards();
MyAssert.CloseTo(n.GetDelta(), 0);
/*
* 1. If answer was set, than calculate like last layer,
* otherwise require theta and delta.
* 2. In back prop every layer calculates it's values and
* sets theta+delta for every connected neuron.
*/
}
public void TestDerivative()
{
//Fails with square error function
NNetwork n = NNetwork.SigmoidNetwork(new int[] { 2, 2, 1 });
n.RandomizeWeights(-1, 10);
Random random = new Random();
double x;
double y;
double z;
x = random.NextDouble();
y = random.NextDouble();
z = some_function(x, y);
n.SetInput(new double[] { x, y });
n.SetAnswers(new double[] { z });
n.BackPropagate();
double[] ders = n.Derivatives();
double[] ests = n.Estimation(0.0001);
for (int i = 0; i < ders.Length; i++)
{
MyAssert.CloseTo(ders[i], ests[i], 0.0001);
}
}
public void TestXNORAuto()
{
NNetwork n = XorNetwork();
double[] input = new double[] { 0, 0 };
n.SetInput(input);
double[] output = n.GetOutput();
MyAssert.CloseTo(output[0], 1);
input = new double[] { 0, 1 };
n.SetInput(input);
output = n.GetOutput();
MyAssert.CloseTo(output[0], 0);
input = new double[] { 1, 0 };
n.SetInput(input);
output = n.GetOutput();
MyAssert.CloseTo(output[0], 0);
input = new double[] { 1, 1 };
n.SetInput(input);
output = n.GetOutput();
MyAssert.CloseTo(output[0], 1);
}
public void TestParseFile()
{
double[] entries = parser.ParseFile(path_cola);
Assert.AreEqual(1272, entries.Length);
MyAssert.CloseTo(29.33, entries[entries.Length - 1]);
}
