//Methods public void Run() { MackeyGlassGeneratorSettings modSettings = new MackeyGlassGeneratorSettings(18, 0.1, 0.2); IGenerator generator = new MackeyGlassGenerator(modSettings); int steps = 100; for (int i = 0; i < steps; i++) { Console.WriteLine(generator.Next()); } Console.ReadLine(); generator.Reset(); for (int i = 0; i < steps; i++) { Console.WriteLine(generator.Next()); } Console.ReadLine(); ///* SimpleIFSettings settings = new SimpleIFSettings(1, new RandomValueSettings(15, 15), new RandomValueSettings(0.05, 0.05), new RandomValueSettings(5, 5), new RandomValueSettings(20, 20), 0 ); IActivationFunction af = ActivationFactory.Create(settings, new Random(0)); //*/ TestActivation(af, 800, 0.15, 10, 600); return; }
//Methods public void Run() { //Linear algebra test double[] flatData = { 0.2, 5, 17.3, 1.01, 54, 7, 2.2, 5.5, 12.13, 11.57, 5.71, -85, -70.1, 15, -18.3, 0.3, 42, -6.25, 0.042, 1, 7.75, -81.01, -21.29, 5.44, 0.1, 4, -4.3, 18.01, 7.12, -3.14, -80.1, 24.4, 4.3, 12.03, 2.789, -13 }; Matrix testM = new Matrix(6, 6, flatData); /* * //Inversion test * Matrix resultM = new Matrix(testM); * resultM.SingleThreadInverse(); */ /* * //Transpose test * Matrix resultM = testM.Transpose(); */ /* * //Multiply test * Matrix resultM = Matrix.Multiply(testM, testM); * for (int i = 0; i < resultM.NumOfRows; i++) * { * Console.WriteLine($"{resultM.Data[i][0]}; {resultM.Data[i][1]}; {resultM.Data[i][2]}; {resultM.Data[i][3]}; {resultM.Data[i][4]}; {resultM.Data[i][5]}"); * } */ ; int numOfweights = 4; int xIdx, dIdx = 0; double[][] data = new double[5][]; data[dIdx] = new double[numOfweights]; xIdx = -1; data[dIdx][++xIdx] = 1; //Bias data[dIdx][++xIdx] = 2; data[dIdx][++xIdx] = 1; data[dIdx][++xIdx] = 3; ++dIdx; data[dIdx] = new double[numOfweights]; xIdx = -1; data[dIdx][++xIdx] = 1; //Bias data[dIdx][++xIdx] = 1; data[dIdx][++xIdx] = 3; data[dIdx][++xIdx] = -3; ++dIdx; data[dIdx] = new double[numOfweights]; xIdx = -1; data[dIdx][++xIdx] = 1; //Bias data[dIdx][++xIdx] = -2; data[dIdx][++xIdx] = 4; data[dIdx][++xIdx] = 4; ++dIdx; data[dIdx] = new double[numOfweights]; xIdx = -1; data[dIdx][++xIdx] = 1; //Bias data[dIdx][++xIdx] = -5; data[dIdx][++xIdx] = 7; data[dIdx][++xIdx] = 6; ++dIdx; data[dIdx] = new double[numOfweights]; xIdx = -1; data[dIdx][++xIdx] = 1; //Bias data[dIdx][++xIdx] = 1; data[dIdx][++xIdx] = 12; data[dIdx][++xIdx] = 5; Matrix M = new Matrix(data, true); Vector desired = new Vector(5); dIdx = -1; desired.Data[++dIdx] = 8; desired.Data[++dIdx] = 13; desired.Data[++dIdx] = 5; desired.Data[++dIdx] = 7; desired.Data[++dIdx] = 10; Vector weights = Matrix.RidgeRegression(M, desired, 0); //Display results for (int i = 0; i < data.Length; i++) { double result = 0; for (int j = 0; j < weights.Length; j++) { result += data[i][j] * weights[j]; } Console.WriteLine($"Computed {result}, Desired {desired.Data[i]}"); } for (int i = 0; i < weights.Length; i++) { Console.WriteLine($"Weight[{i}] = {weights[i]}"); } Console.WriteLine(); //QRD QRD decomposition = new QRD(M); Matrix B = new Matrix(desired.Length, 1, desired.Data); Matrix W = decomposition.Solve(B); //Display results for (int i = 0; i < data.Length; i++) { double result = 0; for (int j = 0; j < W.Data.Length; j++) { result += data[i][j] * W.Data[j][0]; } Console.WriteLine($"Computed {result}, Desired {desired.Data[i]}"); } for (int i = 0; i < W.Data.Length; i++) { Console.WriteLine($"Weight[{i}] = {W.Data[i][0]}"); } ; //TimeSeriesGenerator.SaveTimeSeriesToCsvFile("MackeyGlass_big.csv", "Value", TimeSeriesGenerator.GenMackeyGlassTimeSeries(16000), CultureInfo.InvariantCulture); MackeyGlassGeneratorSettings modSettings = new MackeyGlassGeneratorSettings(18, 0.1, 0.2); IGenerator generator = new MackeyGlassGenerator(modSettings); int steps = 100; for (int i = 0; i < steps; i++) { Console.WriteLine(generator.Next()); } Console.ReadLine(); generator.Reset(); for (int i = 0; i < steps; i++) { Console.WriteLine(generator.Next()); } Console.ReadLine(); ///* SimpleIFSettings settings = new SimpleIFSettings(1, new RandomValueSettings(15, 15), new RandomValueSettings(0.05, 0.05), new RandomValueSettings(5, 5), new RandomValueSettings(20, 20), 0 ); IActivationFunction af = ActivationFactory.Create(settings, new Random(0)); //*/ TestActivation(af, 800, 0.15, 10, 600); return; }