public void CheckOnePointRecombinationFromBest()
{
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
// Act
source.GetParanoid();
source.PushLimitedNexts(1, 3); // crossover points
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.OnePoint);
// Assert
Assert.Equal(result.NeatChromosome[0].Weight, best.NeatChromosome[0].Weight);
for (var i = 1; i < result.NeatChromosome.Count; i++)
{
Assert.Equal(result.NeatChromosome[i].Weight, worst.NeatChromosome[i].Weight);
}
}
}
public void CheckTwoPointRecombinationOfSingleGene()
{
// TODO fix crossover, make this one green
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
// Act
source.GetParanoid();
source.PushLimitedNexts(2, 2); // crossover points
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.TwoPoints);
// Assert
Assert.Equal(result.NeatChromosome[2].Weight, worst.NeatChromosome[2].Weight);
for (var i = 0; i < result.NeatChromosome.Count; i++)
{
if (i == 2)
{
continue;
}
Assert.Equal(result.NeatChromosome[i].Weight, best.NeatChromosome[i].Weight);
}
}
}
public void SimpleNetworkCheck()
{
using (var source = RandomSource.DrillIn())
{
// Arrange
for (var i = 0; i < 10; i++)
{
source.PushNextFloats(0.6f); // identity weights and density chances
}
source.GetParanoid();
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var genome = new Genome(parameters, tracker, false);
var network = new RecurrentNetwork();
#region Network initialization
network.AddNeuron(0, 0);
network.AddNeuron(1, 0);
network.AddNeuron(2, 0);
network.AddNeuron(3, 0);
network.AddNeuron(4, 1);
network.AddConnection(0, 4, 1f);
network.AddConnection(1, 4, 1f);
network.AddConnection(2, 4, 1f);
network.AddConnection(3, 4, 1f);
network.AddConnection(4, 4, 1f);
#endregion
float[] result = null;
for (var i = 0; i < 5; i++)
{
for (var j = 0; j < 3; j++)
{
genome.Network.Sensors[j] = 0.5f;
}
genome.Network.Activate();
result = network.Activate(new[] { 1f, 0.5f, 0.5f, 0.5f });
}
Assert.Equal(result[0], genome.Network.Effectors[0]);
}
}
public void CheckRandomSourceDrillIn()
{
using (var source = RandomSource.DrillIn())
{
// Arrange
// Act
source.GetParanoid();
source.PushNextFloats(1, 2, 3);
// Assert
Assert.Equal(1, Neat.Utils.RandomSource.Next());
Assert.Equal(2, Neat.Utils.RandomSource.Next());
Assert.Equal(3, Neat.Utils.RandomSource.Next());
}
}
public void CheckDisjointsAndEtcAreTakenFromBest()
{
// TODO fix crossover, make this one green
using (var source = RandomSource.DrillIn())
{
// Arrange
var parameters = new NetworkParameters(3, 1)
{
InitialConnectionDensity = 1f
};
var tracker =
new InnovationTracker(NetworkParameters.BiasCount + parameters.SensorCount + parameters.EffectorCount);
var best = new Genome(parameters, tracker, true);
var worst = new Genome(parameters, tracker, true);
best.SplitConnection(1);
// Act
source.GetParanoid();
source.PushLimitedNexts(0, 2); // crossover points - all from worst
source.PushNextBools(true); // start from best
var result = best.Mate(worst, CrossoverType.OnePoint);
// Assert
Assert.Equal(best.NeatChromosome.Count, result.NeatChromosome.Count);
for (var i = 0; i < result.NeatChromosome.Count - 2; i++)
{
var parentGene = Assert.Single(worst.NeatChromosome, g => g.Id == result.NeatChromosome[i].Id);
Assert.Equal(result.NeatChromosome[i].Weight, parentGene.Weight);
}
for (var i = result.NeatChromosome.Count - 2; i < result.NeatChromosome.Count; i++)
{
Assert.Equal(result.NeatChromosome[i].Id, best.NeatChromosome[i].Id);
Assert.Equal(result.NeatChromosome[i].Weight, best.NeatChromosome[i].Weight);
}
}
}
