private void Window_Loaded(object sender, RoutedEventArgs e)
{
var xMatrix = new Libs.Matrix(new float[, ] {
{ -3.2f, -2.1f, 0.4f, 0.7f, 2f, 2.5f, 2.777f }
});
var yMatrix = new Libs.Matrix(new float[, ] {
{ 10f },
{ -2f },
{ 0f },
{ -7f },
{ 7f },
{ 0f },
{ 0f }
});
var coefs = MeanSquaredErrorApproximation.Approximate(
xMatrix,
yMatrix,
2
);
var points = new List <Point>();
for (float x = -3.2f; x <= 2.777; x += 0.0001f)
{
float y = 0;
for (int c = 0; c < coefs.ToArray().Length; c++)
{
y += coefs[c, 0] * (float)Math.Pow(x, c);
}
points.Add(new Point(x, y));
}
using (var file = System.IO.File.CreateText(System.IO.Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.Desktop), "points.csv")))
{
foreach (var point in points)
{
file.WriteLine(string.Format("{0},{1}", point.X, point.Y));
}
file.Close();
}
DrawGraph(points, Brushes.Green);
var realPoints = new List <Point>();
for (int i = 0; i < xMatrix.Width; i++)
{
realPoints.Add(new Point(xMatrix[0, i], yMatrix[i, 0]));
}
DrawGraph(realPoints, Brushes.Orange);
}
private List <Point> GeneratePoints(Libs.Matrix coefficients)
{
var points = new List <Point>();
for (float x = xMatrix[0, 0]; x <= xMatrix[0, xMatrix.Width - 1]; x += 0.001f)
{
float y = 0;
for (int c = 0; c < coefficients.ToArray().Length; c++)
{
y += coefficients[c, 0] * (float)Math.Pow(x, c);
}
points.Add(new Point(x, y));
}
return(points);
}
private void DemoTable_MSE_Click(object sender, RoutedEventArgs e)
{
CleanDataSources();
float[] xValues = new float[]
{
0, 3.3f, 6.6f, 9.9f
};
float[] yValues = new float[]
{
2.1f, 5.9f, 2.4f, 3.4f
};
var xMatrix = new Libs.Matrix(new float[, ] {
{ 0, 3.3f, 6.6f, 9.9f }
});
var yMatrix = new Libs.Matrix(new float[, ] {
{ 2.1f },
{ 5.9f },
{ 2.4f },
{ 3.4f }
});
var coefs = MeanSquaredErrorApproximation.Approximate(
xMatrix,
yMatrix,
1
);
MnkK1Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(
xMatrix,
yMatrix,
2
);
MnkK2Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(
xMatrix,
yMatrix,
3
);
MnkK3Plotter.ItemsSource = GeneratePoints(coefs);
DrawBasePoints(xValues, yValues);
}
private void DrawMSE_Func()
{
var rank = ChebyshevApproximation.CalculateRank(a, b, step);
var xValues = new Libs.Matrix(ChebyshevApproximation.GenerateX(a, b, step));
var yValues = new Libs.Matrix(new float[rank, 1]);
for (int j = 0; j < yValues.Height; j++)
{
yValues[j, 0] = (float)ApproximatedFunction(xValues[0, j]);
}
var coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 1);
MnkK1Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 2);
MnkK2Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 3);
MnkK3Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 4);
MnkK4Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 5);
MnkK5Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 6);
MnkK6Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 7);
MnkK7Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 8);
MnkK8Plotter.ItemsSource = GeneratePoints(coefs);
coefs = MeanSquaredErrorApproximation.Approximate(xValues, yValues, 9);
MnkK9Plotter.ItemsSource = GeneratePoints(coefs);
}
