public static bool Test_Weights()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 1, 1 }, new double[] { 1.0 }, null);
var result = cut.Calculate(new double[] { 0.5 });
return(Math.Abs(result[0] - 0.5) < 0.001);
}
public static bool Test_MoreWeights_LinearActivation()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 2, 2, 1 }, new double[] { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }, MLPNetwork.Identity);
var result = cut.Calculate(new double[] { 0.5, 0.5 });
return(Math.Abs(result[0] - 2) < 0.001);
}
public void VerifyNetwork()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 1, 1 }, new double[] { 1.0 }, null);
var result = cut.Calculate(new double[] { 0.35 });
Assert.Equal(0.35, result[0]);
}
public static bool Test_ReuseNetwork_Sameresult()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 2, 2, 1 }, new double[] { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }, MLPNetwork.Identity);
var result = cut.Calculate(new double[] { 0.5, 0.5 });
var result2 = cut.Calculate(new double[] { 0.5, 0.5 });
return(Math.Abs(result[0] - result2[0]) < 0.001);
}
public static bool Test_MoreWeights()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 2, 2, 1 }, new double[] { 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 }, null);
var result = cut.Calculate(new double[] { 0.5, 0.5 });
var expected = Math.Tanh(1.0) + Math.Tanh(1.0);
return(Math.Abs(result[0] - expected) < 0.001);
}
public static bool Test_Unwrap_Create_SameResult()
{
var cut = MLPNetwork.CreateMLPNetwork(new int[] { 1, 1 }, new double[] { 1.0 }, null);
var result1 = cut.Calculate(new double[] { 0.5 });
var weights = cut.ExtractWeights();
var cut2 = MLPNetwork.CreateMLPNetwork(new int[] { 1, 1 }, weights, null);
var result2 = cut2.Calculate(new double[] { 0.5 });
return(Math.Abs(result1[0] - result2[0]) < 0.001);
}
