public TeacherTester()
{
Logger.Log(this, "App start");
NodeFuncGenerator funcGenerator = new NodeFuncGenerator();
Dictionary<NodeType, double> nodeProbabilityMap = new Dictionary<NodeType, double>()
{
{NodeType.add, 1.0d},
{NodeType.compare, 1.0d},
{NodeType.copy, 0.0d},
{NodeType.inverse, 1.0d},
{NodeType.log, 1.0d},
{NodeType.multiply, 1.0d},
{NodeType.reverse, 1.0d}
};
NodeFactory nodeFactory = new NodeFactory(funcGenerator, nodeProbabilityMap);
List<DataPoint> dataPoints = GenerateSinWaveDataPoints(100, 0.19d);
Network network = new Network(nodeFactory, dataPoints, 1000);
double addRemoveChance = 0.5;
PatchFactory patchFactory = new PatchFactory(network, nodeFactory, addRemoveChance);
NetworkTeacher networkTeacher = new NetworkTeacher(network, patchFactory);
Logger.Log(this, String.Format("initial error: {0}", network.CalculateTrainingSqrError()));
networkTeacher.Teach(
teachingTime: TimeSpan.FromSeconds(10000000.0d),
wantedNoOfNodes: 300,
changesPerPatch: 8,
patchesPerTeachingSerie: 1
);
Logger.Log(this, String.Format("error after learning: {0}", network.CalculateTrainingSqrError()));
Logger.Log(this, "App finish");
Console.ReadKey();
}
/// <summary>
///
/// </summary>
/// <param name="network"></param>
/// <param name="nodeFactory"></param>
/// <param name="addRemoveChance">chance in range <0, 1> - rest is chance of tranformation</param>
public PatchFactory(Network network, NodeFactory nodeFactory, double addRemoveChance)
{
if (addRemoveChance < 0.0d || addRemoveChance > 1.0d)
throw new ArgumentOutOfRangeException("addRemoveChance");
network_ = network;
nodeFactory_ = nodeFactory;
addRemoveChance_ = addRemoveChance;
}
public void SetUp()
{
NodeFuncGenerator nodeFuncGenerator = new NodeFuncGenerator();
NodeFactory nodeFactory = new NodeFactory(
nodeFuncGenerator,
new Dictionary<NodeType, double>() { { NodeType.add, 1.0d } });
network = new Network(
nodeFactory: nodeFactory,
trainingData: new List<DataPoint>()
{
new DataPoint(new List<double>(){2.0d, 2.0d, 2.0d}, 5.0d) //IMPORTANT: TODO: was modified from "new DataPoint(new List<double>(){2.0d, 2.0d}, 5.0d)" - now test can work incorrectly
},
maxHierarchy: 1000
);
patchFactory = new PatchFactory(network, nodeFactory, 1.0d);
networkTeacher = new NetworkTeacher(network, patchFactory);
}
public void SinWaveTrainingTest()
{
NodeFuncGenerator funcGenerator = new NodeFuncGenerator();
Dictionary<NodeType, double> nodeProbabilityMap = new Dictionary<NodeType,double>()
{
{NodeType.add, 1.0d},
{NodeType.compare, 1.0d},
{NodeType.copy, 0.0d},
{NodeType.inverse, 1.0d},
{NodeType.log, 1.0d},
{NodeType.multiply, 1.0d},
{NodeType.reverse, 1.0d}
};
NodeFactory nodeFactory = new NodeFactory(funcGenerator, nodeProbabilityMap);
List<DataPoint> dataPoints = GenerateSinWaveDataPoints(100, 0.35d);
Network network = new Network(nodeFactory, dataPoints, 1000);
double addRemoveChance = 0.5;
PatchFactory patchFactory = new PatchFactory(network, nodeFactory, addRemoveChance);
NetworkTeacher networkTeacher = new NetworkTeacher(network, patchFactory);
networkTeacher.Teach(TimeSpan.FromSeconds(0.1d), 2000, 3, 30);
}
Assert.AreEqual(0, child3.Outputs.Count);
dummyNetwork.UTTestingFoo();
}
