public Network(double learningrate, double alpha, double mininitweight, double maxinitweight, int numInputNeurons,
int[] hiddenLayerSizes, int numOutputNeurons, bool testHaltEnabled = false, bool testingEnabled = true, bool recordSaveEnabled = true)
{
Console.WriteLine("\n Building neural network...");
if (numInputNeurons < 1 || hiddenLayerSizes.Length < 1 || numOutputNeurons < 1)
{
throw new Exception("Incorrect Network Parameters");
}
Functions.Alpha = alpha;
Synapse.MinInitWeight = mininitweight;
Synapse.MaxInitWeight = maxinitweight;
LearningRate = learningrate;
this.testStrategy = new MeanErrorTest(this);
this.TestHaltEnabled = testHaltEnabled;
this.TestingEnabled = testingEnabled;
this.RecordSaveEnabled = recordSaveEnabled;
Layers = new List <Layer>();
AddFirstLayer(numInputNeurons);
for (int i = 0; i < hiddenLayerSizes.Length; i++)
{
AddNextLayer(new Layer(hiddenLayerSizes[i]));
}
AddNextLayer(new Layer(numOutputNeurons));
SynapsesCount = Synapse.SynapsesCount;
ErrorFunctionChanges = new double[Layers.Count][];
for (int i = 1; i < Layers.Count; i++)
{
ErrorFunctionChanges[i] = new double[Layers[i].Neurons.Count];
}
}
public IEnumerable <UITest> GetTestMethods()
{
Assembly assembly;
try
{
assembly = Assembly.LoadFrom(this.assemblyPath);
}
catch (Exception e)
{
Log.Fatal(e, "There was as issue loading the assembly");
throw e;
}
ITestStrategy testStrategy = this.testStrategy switch
{
TestStrategy.NUnit => new NUnitStrategy(),
_ => new SpecflowPlusStrategy()
};
return(testStrategy.GetTests(assembly));
}
}
public TestContext(ITestStrategy strategy)
{
this.strategy = strategy;
}
