static void Main(string[] args)
{
int epochcount = 6000;
int logPointC = 4000;
/*basic XOR test in few updates
* O - O \
* X O
* O - O /
* */
NeuralDataSet dataForLearning = CreateNewData(1);
NeuralNetwork.NeuralNetwork neuralNetwork = new NeuralNetwork.NeuralNetwork(new int[] { 40 }, 2, 1);
DateTime time = DateTime.Now;
neuralNetwork.Initialise();
neuralNetwork.StudySpeed = 0.1;
neuralNetwork.studyMoment = 0.1;
neuralNetwork.RandomiseWeights();
neuralNetwork.SetDataSet(dataForLearning);
string log = neuralNetwork.StudyHyperbola(epochcount, logPointC);
TimeSpan dif = DateTime.Now - time;
Console.WriteLine("Initialising and studiing for {1} epoches succesful, time spent: {0}", dif.ToString(), epochcount);
System.IO.StreamWriter writer = new StreamWriter("C:\\Users\\Aleksandr\\Desktop\\log.csv", false);
writer.WriteLine(log);
writer.Close();
TestNN(neuralNetwork);
Console.ReadKey();
}
/// <summary>
/// Create a new manager based on a repository available as an XML stream (e.g. StreamReader or StringReader).
/// </summary>
/// <param name="reader">A TextReader that maps e.g. to a readable file stream.</param>
/// <returns>The manager instance bound to the loaded repository.</returns>
public static Manager ReadRepository(TextReader reader)
{
NeuralDataSet database = new NeuralDataSet();
database.ReadXml(reader, System.Data.XmlReadMode.IgnoreSchema);
return(new Manager(database));
}
static NeuralDataSet CreateNewData(int repitTimes)
{
Double[] d1 = new double[] { 0, 0 };
double[] do1 = new double[] { 0 };
Double[] d2 = new double[] { 0, 1 };
double[] do2 = new double[] { 1 };
Double[] d3 = new double[] { 1, 0 };
double[] do3 = new double[] { 1 };
Double[] d4 = new double[] { 1, 1 };
double[] do4 = new double[] { 0 };
NeuralDataSet data = new NeuralDataSet()
{
Inputs = new double[repitTimes * 4][],
ExpectedResult = new double[repitTimes * 4][]
};
for (int i = 0; i < (repitTimes); i++)
{
data.Inputs[i] = d1;
data.ExpectedResult[i] = do1;
}
for (int i = repitTimes; i < (repitTimes * 2); i++)
{
data.Inputs[i] = d2;
data.ExpectedResult[i] = do2;
}
for (int i = repitTimes * 2; i < (repitTimes * 3); i++)
{
data.Inputs[i] = d3;
data.ExpectedResult[i] = do3;
}
for (int i = repitTimes * 3; i < (repitTimes * 4); i++)
{
data.Inputs[i] = d4;
data.ExpectedResult[i] = do4;
}
return(data);
}
/// <summary>
/// Create a manager with an empty repository.
/// </summary>
public Manager()
{
database = new NeuralDataSet();
}
/// <summary>
/// Create a manager with the passed repository.
/// </summary>
/// <param name="repository">The repository to work with.</param>
public Manager(NeuralDataSet repository)
{
database = repository;
}
/// <summary>
/// Create a manager with an empty repository.
/// </summary>
public Manager()
{
database = new NeuralDataSet();
}
private NeuralDataSet.TrainingItemRow[] SelectTrainingItemsFromTrainingSet(NeuralDataSet.TrainingSetsRow trainingSet)
{
return (NeuralDataSet.TrainingItemRow[])database.TrainingItem.Select("tiFK_trainingset = " + trainingSet.trID);
}
private void AppendNeuronsToNeuronMap(Hashtable map, NeuralDataSet.NeuronsRow[] rows, Layer layer)
{
for(int i=0;i<rows.Length;i++)
map.Add(rows[i].neID,layer[i]);
}
private NeuralDataSet.NeuronsRow[] SelectNeuronsFromLayer(NeuralDataSet.LayersRow layer)
{
return (NeuralDataSet.NeuronsRow[])database.Neurons.Select("neFK_layer = " + layer.laID);
}
private NeuralDataSet.LayersRow[] SelectLayersFromNetwork(NeuralDataSet.NetworksRow network)
{
return (NeuralDataSet.LayersRow[])database.Layers.Select("laFK_network = " + network.nwID);
}
private void SaveTrainingSet(NeuralDataSet.TrainingSetsRow trainingSetRow)
{
NeuralDataSet.SynapsesRow[] synapseRows = SelectSynapsesFromNetwork(currentNetworkRow);
for(int i=0;i<synapseRows.Length;i++)
database.TrainingItem.AddTrainingItemRow(trainingSetRow,synapseRows[i],((Synapse)currentSynapseMap[synapseRows[i].syID]).Weight);
}
private void SaveNetworkStructureAsCurrent(NeuralDataSet.NetworksRow networkRow, Network network)
{
Hashtable neuronInvMap = new Hashtable();
currentNeuronMap = new Hashtable();
currentSynapseMap = new Hashtable();
Layer layer = network.FirstLayer;
SaveLayerAsCurrent(neuronInvMap,layer,networkRow);
while(layer.TargetLayer != null)
{
layer = layer.TargetLayer;
SaveLayerAsCurrent(neuronInvMap,layer,networkRow);
}
foreach(Neuron neuron in neuronInvMap.Keys)
foreach(Synapse synapse in neuron.SourceSynapses)
{
NeuralDataSet.SynapsesRow row = database.Synapses.AddSynapsesRow((NeuralDataSet.NeuronsRow)neuronInvMap[synapse.SourceNeuron],(NeuralDataSet.NeuronsRow)neuronInvMap[neuron],networkRow);
currentSynapseMap.Add(row.syID,synapse);
}
}
private void SaveLayerAsCurrent(Hashtable neuronInvMap, Layer layer, NeuralDataSet.NetworksRow networkRow)
{
NeuralDataSet.LayersRow layerRow = database.Layers.AddLayersRow(networkRow,layer.Title);
for(int i=0;i<layer.Count;i++)
{
NeuralDataSet.NeuronsRow row = database.Neurons.AddNeuronsRow(layerRow);
neuronInvMap.Add(layer[i],row);
currentNeuronMap.Add(row.neID,layer[i]);
}
}
private void SaveLayer(Hashtable neuronInvMap, Layer layer, NeuralDataSet.NetworksRow networkRow)
{
NeuralDataSet.LayersRow layerRow = database.Layers.AddLayersRow(networkRow,layer.Title);
for(int i=0;i<layer.Count;i++)
neuronInvMap.Add(layer[i],database.Neurons.AddNeuronsRow(layerRow));
}
private void LoadTrainingSet(NeuralDataSet.TrainingSetsRow trainingSetRow)
{
NeuralDataSet.TrainingItemRow[] itemRows = SelectTrainingItemsFromTrainingSet(trainingSetRow);
for(int i=0;i<itemRows.Length;i++)
((Synapse)currentSynapseMap[itemRows[i].tiFK_synapse]).Weight = itemRows[i].ti_weight;
}
/// <summary>
/// Create a manager with the passed repository.
/// </summary>
/// <param name="repository">The repository to work with.</param>
public Manager(NeuralDataSet repository)
{
database = repository;
}
private NeuralDataSet.SynapsesRow[] SelectSynapsesFromNetwork(NeuralDataSet.NetworksRow network)
{
return (NeuralDataSet.SynapsesRow[])database.Synapses.Select("syFK_network = " + network.nwID);
}
/// <summary>
/// Create a new manager based on a repository available as an XML stream (e.g. StreamReader or StringReader).
/// </summary>
/// <param name="reader">A TextReader that maps e.g. to a readable file stream.</param>
/// <returns>The manager instance bound to the loaded repository.</returns>
public static Manager ReadRepository(TextReader reader)
{
NeuralDataSet database = new NeuralDataSet();
database.ReadXml(reader,System.Data.XmlReadMode.IgnoreSchema);
return new Manager(database);
}
