public void Hessian___Gradient___Calculation___Test()
{
int accuracy = 15;
/*
* function obliczanie_hesjan_gradient()
* clear();
* inp = [-1 -1;-1 1; 1 -1];
* dout = [1;0;0];
* topo = [3 1 2 4 1 2 3];
* ww = [1 1 1 1 1 1 1];
* act = [2 0];
* gain = [1 1];
* param = [3 2 1 7 2];
* iw = [1 4 8];
* format long;
*
* [gradient,hessian] = Hessian(inp,dout,topo,ww,act,gain,param,iw);
* fprintf('Otrzymany gradient:\n');
* disp(gradient);
* fprintf('\nOtrzymany hesjan:\n');
* disp(hessian);
*
* % To jest otrzymywane
* % Otrzymany gradient:
* % -0.839948683228052
* % 2.319597374905329
* % 2.319597374905329
* % -2.000000000000000
* % 5.523188311911530
* % 5.523188311911531
* % 6.889667569278484
* %
* %
* % Otrzymany hesjan:
* % Columns 1 through 6
* %
* % 1.058270685684809 -0.705513790456539 -0.705513790456539 2.519846049684157 -1.679897366456105 -1.679897366456105
* % -0.705513790456539 1.058270685684809 0.352756895228269 -1.679897366456105 2.519846049684157 0.839948683228052
* % -0.705513790456539 0.352756895228269 1.058270685684809 -1.679897366456105 0.839948683228052 2.519846049684157
* % 2.519846049684157 -1.679897366456105 -1.679897366456105 6.000000000000000 -4.000000000000000 -4.000000000000000
* % -1.679897366456105 2.519846049684157 0.839948683228052 -4.000000000000000 6.000000000000000 2.000000000000000
* % -1.679897366456105 0.839948683228052 2.519846049684157 -4.000000000000000 2.000000000000000 6.000000000000000
* % -0.639700008449225 1.279400016898449 1.279400016898449 -1.523188311911530 3.046376623823059 3.046376623823059
* %
* % Column 7
* %
* % -0.639700008449225
* % 1.279400016898449
* % 1.279400016898449
* % -1.523188311911530
* % 3.046376623823059
* % 3.046376623823059
* % 3.480153950315843
* end
*/
Input input = new Input(3, 2);//inp = [-1 -1;-1 1; 1 -1];
input[0, 0] = -1;
input[0, 1] = -1;
input[1, 0] = -1;
input[1, 1] = 1;
input[2, 0] = 1;
input[2, 1] = -1;
Output output = new Output(3, 1);//dout = [1;0;0];
output[0, 0] = 1;
output[1, 0] = 0;
output[2, 0] = 0;
NetworkInfo info = new NetworkInfo();//param = [3 2 1 7 2];
info.ni = 2;
info.nn = 2;
info.no = 1;
info.np = 3;
info.nw = 7;
VectorHorizontal vh = new VectorHorizontal(3);
vh[0, 0] = 2;
vh[0, 1] = 1;
vh[0, 2] = 1;
Topography topo = Topography.Generate(TopographyType.BMLP, vh);//topo = [3 1 2 4 1 2 3];
//w C# indeksy są od zera a nie od 1 więc wszystko o 1 w dół przestawione jest
Assert.AreEqual(2, topo[0]);
Assert.AreEqual(0, topo[1]);
Assert.AreEqual(1, topo[2]);
Assert.AreEqual(3, topo[3]);
Assert.AreEqual(0, topo[4]);
Assert.AreEqual(1, topo[5]);
Assert.AreEqual(2, topo[6]);
Weights weights = new Weights(info.nw); //w = [1 1 1 1 1 1 1];
weights.FillWithNumber(1); //załatwione
Activation act = new Activation(2); //act = [2 0];
act[0] = 2;
act[1] = 0;
Gain gain = new Gain(2);//gain = [1 1];
gain[0] = 1;
gain[1] = 1;
Index iw = Index.Find(ref topo);//iw = [1 4 8];
//ta sama sytuacja, indeksy od 0 startują
Assert.AreEqual(0, iw[0]);
Assert.AreEqual(3, iw[1]);
Assert.AreEqual(7, iw[2]);
Console.WriteLine("Testowanie obliczania gradientu i macierzy hesjana");
Console.WriteLine("Użyte dane:");
Console.WriteLine("\nDane wejściowe:");
Console.WriteLine(input.MatrixToString());
Console.WriteLine("\nDane wyjściowe:");
Console.WriteLine(output.MatrixToString());
Console.WriteLine("\nWagi;");
Console.WriteLine(weights.MatrixToString());
Console.WriteLine("\nTopologia:");
Console.WriteLine(topo.MatrixToString());
Console.WriteLine("\nIndeksy topologii:");
Console.WriteLine(iw.MatrixToString());
Console.WriteLine("\nFunkcje aktywacji:");
Console.WriteLine(act.MatrixToString());
Console.WriteLine("\nWzmocnienia (gains):");
Console.WriteLine(gain.MatrixToString());
Console.WriteLine("\nParametry (param):");
Console.WriteLine(info.ToString());
Hessian hess = new Hessian(ref info);
hess.Compute(ref info, ref input, ref output, ref topo, weights, ref act, ref gain, ref iw);
var g = hess.GradientMat;
var h = hess.HessianMat;
Console.WriteLine("\nSprawdzanie gradientu z dokładnością do 15 miejsc po przecinku");
var matG = new double[] { -0.839948683228052, 2.319597374905329, 2.319597374905329, -2.000000000000000, 5.523188311911530, 5.523188311911531, 6.889667569278484 };
/*
* % Otrzymany gradient:
* % -0.839948683228052
* % 2.319597374905329
* % 2.319597374905329
* % -2.000000000000000
* % 5.523188311911530
* % 5.523188311911531
* % 6.889667569278484
*/
for (int i = 0; i < matG.Length; i++)
{
Console.WriteLine(string.Format("NBN C#: {0}\tMatLab NBN: {1}\t{2}", Math.Round(g[i, 0], accuracy), matG[i], Math.Round(g[i, 0], accuracy) == matG[i] ? "OK" : "źle"));
}
Assert.AreEqual(-0.839948683228052, Math.Round(g[0, 0], accuracy));
Assert.AreEqual(2.319597374905329, Math.Round(g[1, 0], accuracy));
Assert.AreEqual(2.319597374905329, Math.Round(g[2, 0], accuracy));
Assert.AreEqual(-2.000000000000000, Math.Round(g[3, 0], accuracy));
Assert.AreEqual(5.523188311911530, Math.Round(g[4, 0], accuracy));
Assert.AreEqual(5.523188311911531, Math.Round(g[5, 0], accuracy));
Assert.AreEqual(6.889667569278484, Math.Round(g[6, 0], accuracy));
Console.WriteLine("\nSprawdzanie macierzy hesjana\nPorównania z dokładnością do 15 miejsc po przecinku");
MatrixMB matH = new MatrixMB(7, 7);
//col 1
matH[0, 0] = 1.058270685684809;
matH[1, 0] = -0.705513790456539;
matH[2, 0] = -0.705513790456539;
matH[3, 0] = 2.519846049684157;
matH[4, 0] = -1.679897366456105;
matH[5, 0] = -1.679897366456105;
matH[6, 0] = -0.639700008449225;
//col 2
matH[0, 1] = -0.705513790456539;
matH[1, 1] = 1.058270685684809;
matH[2, 1] = 0.352756895228269;
matH[3, 1] = -1.679897366456105;
matH[4, 1] = 2.519846049684157;
matH[5, 1] = 0.839948683228052;
matH[6, 1] = 1.279400016898449;
//col 3
matH[0, 2] = -0.705513790456539;
matH[1, 2] = 0.352756895228269;
matH[2, 2] = 1.058270685684809;
matH[3, 2] = -1.679897366456105;
matH[4, 2] = 0.839948683228052;
matH[5, 2] = 2.519846049684157;
matH[6, 2] = 1.279400016898449;
//col 4
matH[0, 3] = 2.519846049684157;
matH[1, 3] = -1.679897366456105;
matH[2, 3] = -1.679897366456105;
matH[3, 3] = 6.000000000000000;
matH[4, 3] = -4.000000000000000;
matH[5, 3] = -4.000000000000000;
matH[6, 3] = -1.523188311911530;
//col 5
matH[0, 4] = -1.679897366456105;
matH[1, 4] = 2.519846049684157;
matH[2, 4] = 0.839948683228052;
matH[3, 4] = -4.000000000000000;
matH[4, 4] = 6.000000000000000;
matH[5, 4] = 2.000000000000000;
matH[6, 4] = 3.046376623823059;
//col 6
matH[0, 5] = -1.679897366456105;
matH[1, 5] = 0.839948683228052;
matH[2, 5] = 2.519846049684157;
matH[3, 5] = -4.000000000000000;
matH[4, 5] = 2.000000000000000;
matH[5, 5] = 6.000000000000000;
matH[6, 5] = 3.046376623823059;
//col 7
matH[0, 6] = -0.639700008449225;
matH[1, 6] = 1.279400016898449;
matH[2, 6] = 1.279400016898449;
matH[3, 6] = -1.523188311911530;
matH[4, 6] = 3.046376623823059;
matH[5, 6] = 3.046376623823059;
matH[6, 6] = 3.480153950315843;
for (int k = 0; k < h.Cols; k++)
{
Console.WriteLine(string.Format("Kolumna {0}", k + 1));
for (int w = 0; w < h.Rows; w++)
{
decimal dh = Math.Round((decimal)h[w, k], accuracy);
decimal dmh = Math.Round((decimal)matH[w, k], accuracy);
Console.WriteLine(string.Format("NBN C#: {0}\tMatLab NBN: {1}\t{2}", dh, dmh, dh == dmh ? "OK" : "źle"));
}
Console.WriteLine("");
}
for (int k = 0; k < h.Cols; k++)
{
for (int w = 0; w < h.Rows; w++)
{
decimal dh = Math.Round((decimal)h[w, k], accuracy);
decimal dmh = Math.Round((decimal)matH[w, k], accuracy);
Assert.AreEqual(dmh, dh);
}
}
/*
* % Otrzymany hesjan:
* % Columns 1 through 6
* %
* % 1.058270685684809 -0.705513790456539 -0.705513790456539 2.519846049684157 -1.679897366456105 -1.679897366456105
* % -0.705513790456539 1.058270685684809 0.352756895228269 -1.679897366456105 2.519846049684157 0.839948683228052
* % -0.705513790456539 0.352756895228269 1.058270685684809 -1.679897366456105 0.839948683228052 2.519846049684157
* % 2.519846049684157 -1.679897366456105 -1.679897366456105 6.000000000000000 -4.000000000000000 -4.000000000000000
* % -1.679897366456105 2.519846049684157 0.839948683228052 -4.000000000000000 6.000000000000000 2.000000000000000
* % -1.679897366456105 0.839948683228052 2.519846049684157 -4.000000000000000 2.000000000000000 6.000000000000000
* % -0.639700008449225 1.279400016898449 1.279400016898449 -1.523188311911530 3.046376623823059 3.046376623823059
* %
* % Column 7
* %
* % -0.639700008449225
* % 1.279400016898449
* % 1.279400016898449
* % -1.523188311911530
* % 3.046376623823059
* % 3.046376623823059
* % 3.480153950315843
*/
}
public void Test___Error___Calculation___Test()
{
/*
*
*
* Kod testowy matlaba
*
* function obliczanie_bledu()
* inp = [-1 -1;-1 1; 1 -1];
* dout = [1;0;0];
* topo = [3 1 2 4 1 2 3];
* w = [1 1 1 1 1 1 1];
* act = [2 0];
* gain = [1 1];
* param = [3 2 1 7 2];
* iw = [1 4 8];
* format long;
* error = calculate_error(inp,dout,topo,w,act,gain,param,iw);
* fprintf('Obliczanie błędu uczenia sieci\nBłąd wynosi: %.20f\n', error);
* %Otrzymany wynik
* %Obliczanie błędu uczenia sieci
* %Błąd wynosi: 13.83283022280404000000
* end
*
*
*/
Input input = new Input(3, 2);//inp = [-1 -1;-1 1; 1 -1];
input[0, 0] = -1;
input[0, 1] = -1;
input[1, 0] = -1;
input[1, 1] = 1;
input[2, 0] = 1;
input[2, 1] = -1;
Output output = new Output(3, 1);//dout = [1;0;0];
output[0, 0] = 1;
output[1, 0] = 0;
output[2, 0] = 0;
NetworkInfo info = new NetworkInfo();//param = [3 2 1 7 2];
info.ni = 2;
info.nn = 2;
info.no = 1;
info.np = 3;
info.nw = 7;
VectorHorizontal vh = new VectorHorizontal(3);
vh[0, 0] = 2;
vh[0, 1] = 1;
vh[0, 2] = 1;
Topography topo = Topography.Generate(TopographyType.BMLP, vh);//topo = [3 1 2 4 1 2 3];
//w C# indeksy są od zera a nie od 1 więc wszystko o 1 w dół przestawione jest
Assert.AreEqual(2, topo[0]);
Assert.AreEqual(0, topo[1]);
Assert.AreEqual(1, topo[2]);
Assert.AreEqual(3, topo[3]);
Assert.AreEqual(0, topo[4]);
Assert.AreEqual(1, topo[5]);
Assert.AreEqual(2, topo[6]);
Weights weights = new Weights(info.nw); //w = [1 1 1 1 1 1 1];
weights.FillWithNumber(1); //załatwione
Activation act = new Activation(2); //act = [2 0];
act[0] = 2;
act[1] = 0;
Gain gain = new Gain(2);//gain = [1 1];
gain[0] = 1;
gain[1] = 1;
Index iw = Index.Find(ref topo);//iw = [1 4 8];
//ta sama sytuacja, indeksy od 0 startują
Assert.AreEqual(0, iw[0]);
Assert.AreEqual(3, iw[1]);
Assert.AreEqual(7, iw[2]);
NetworkError ne = new NetworkError();
var error = ne.CalculateError(ref info, ref input, ref output, ref topo, weights, ref act, ref gain, ref iw);
double errorFromMatLab = 13.83283022280404000000;
Console.WriteLine("Testowanie obliczania błędu");
Console.WriteLine("Użyte dane:");
Console.WriteLine("\nDane wejściowe:");
Console.WriteLine(input.MatrixToString());
Console.WriteLine("\nDane wyjściowe:");
Console.WriteLine(output.MatrixToString());
Console.WriteLine("\nWagi;");
Console.WriteLine(weights.MatrixToString());
Console.WriteLine("\nTopologia:");
Console.WriteLine(topo.MatrixToString());
Console.WriteLine("\nIndeksy topologii:");
Console.WriteLine(iw.MatrixToString());
Console.WriteLine("\nFunkcje aktywacji:");
Console.WriteLine(act.MatrixToString());
Console.WriteLine("\nWzmocnienia (gains):");
Console.WriteLine(gain.MatrixToString());
Console.WriteLine("\nParametry (param):");
Console.WriteLine(info.ToString());
Assert.AreEqual(errorFromMatLab, error);
Console.WriteLine(string.Format("{0} - wynik NBN C#", error));
Console.WriteLine(string.Format("{0} - wynik NBN w MatLabie", errorFromMatLab));
}