static void DisplayActivation(double[] weights, int dim, int numData, string filename)
{
InputOutputHandler myInput = new InputOutputHandler(dim, numData, filename);
double[][][] data = myInput.GetInputs();
ANNPerceptron res = new ANNPerceptron();
for (int i = 0; i < data.Length; i++)
{
double activation = res.Result(data[i][0], weights);
//Console.WriteLine("Activation= " + activation.ToString() + " || actual sol= " + data[i][1][0].ToString() + " || single error= " + (activation - data[i][1][0]).ToString());
}
}
static double Error(double[] weights, int dim, int numData, string filename)
{
InputOutputHandler myInput = new InputOutputHandler(dim, numData, filename);
double[][][] data = myInput.GetInputs();
ANNPerceptron res = new ANNPerceptron();
double sumSq = 0;
for (int i = 0; i < data.Length; i++)
{
double activation = res.Result(data[i][0], weights);
//Console.WriteLine(" - activation= " + activation.ToString() + " - actual sol= " + data[i][1][0].ToString());
sumSq += Math.Pow(activation - data[i][1][0], 2);
}
double err = Math.Sqrt((1.0 / data.Length) * sumSq);
return(err);
}
public void WriteOutputs(double[] weights) //writes only output from testing data
{
string[][] csvData = new string[this.numRecs + 4][];
for (int s = 0; s < csvData.Length; s++)
{
csvData[s] = new string[this.dim + 4];
for (int d = 0; d < this.dim + 4; d++)
{
csvData[s][d] = ".";
}
}
csvData[0][0] = this.header;
csvData[1][0] = "Weights:";
Console.WriteLine("--------------------");
ShowVector(csvData[0], true);
ShowVector(csvData[1], true);
for (int d = 0; d < weights.Length; d++)
{
csvData[2][d] = Convert.ToString(weights[d]);
}
Console.WriteLine("--------------------");
ShowVector(csvData[0], true);
ShowVector(csvData[1], true);
ShowVector(csvData[2], true);
for (int d = 0; d < weights.Length; d++)
{
csvData[3][d] = "t" + d.ToString();
}
csvData[3][(this.dim + 4) - 3] = "Predicted";
csvData[3][(this.dim + 4) - 2] = "Actual";
csvData[3][(this.dim + 4) - 1] = "Error";
Console.WriteLine("--------------------");
ShowVector(csvData[0], true);
ShowVector(csvData[1], true);
ShowVector(csvData[2], true);
ShowVector(csvData[3], true);
double[][][] testingData = this.GetTestingData();
ANNPerceptron res = new ANNPerceptron();
for (int d = 0; d < testingData.Length; d++)
{
double activation = res.Result(testingData[d][0], weights);
int x;
for (x = 0; x < this.dim; x++)
{
csvData[d + 4][x] = Convert.ToString(testingData[d][0][x]);
}
x++;
csvData[d + 4][x++] = (activation).ToString("F2");
csvData[d + 4][x++] = (testingData[d][1][0]).ToString();
csvData[d + 4][x] = (Math.Abs(activation - testingData[d][1][0])).ToString("F2");
Console.Write("csvData[{0}] ", d + 4);
ShowVector(csvData[d + 4], true);
}
Console.WriteLine("===================================");
StringBuilder sb = new StringBuilder();
for (int index = 0; index < csvData.Length; index++)
{
ShowVector(csvData[index], true);
sb.AppendLine(string.Join(",", csvData[index]));
}
System.IO.File.WriteAllText(this.outputDir + this.filename, sb.ToString());
}
