VB Savitzky Golay Filtering Example

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Imports System

Imports CenterSpace.NMath.Core

Namespace CenterSpace.NMath.Examples.VisualBasic

  A .NET example in Visual Basic
  Module SavitzkyGolayFilteringExample

    Sub Main()

      Build a Savitzky-Golay filter with a window width of 7, and a 4th degree smoothing polynomial.
      Dim SGF As New SavitzkyGolayFilter(3, 3, 4)

      Make some random noise.
      Dim RND As RandomNumberGenerator = New RandGenUniform()
      Dim Data As New DoubleVector(100, RND)

      Build a noisy sinusoidal signal to filter.
      Dim step_size As Double = 0.1
      Dim X As New DoubleVector(100, 0, step_size)
      Dim sin_x As New DoubleVector(NMathFunctions.Sin(X) + Data.Scale(0.1))

      Filter the signal function
      Dim Z As DoubleVector = SGF.Filter(sin_x)

      Build a vector of a sampled sinc() function and its derivative.
      X = New DoubleVector(100, 0.01, step_size)
      Dim Sinc As New DoubleVector(NMathFunctions.Sin(X) / X)
      Dim derivative_sinc As New DoubleVector(NMathFunctions.Cos(X) / X - NMathFunctions.Sin(X) / (X * X))

      Create a Savitzky-Golay filter for computing the first derivative using a 5th degree polynomial.
      By default the boundaries are smoothed to the edges, if this is not necessary,
      other faster boundary handling options are available.
      SGF = New SavitzkyGolayFilter(3, 3, 5, 1)

      Find the S-G derivatives.
      Dim sg_d_sinc As DoubleVector = SGF.Filter(Sinc)

      Scale the raw derivatives.
      SGF.ScaleDerivative(step_size, sg_d_sinc)

      Look at the mean squared error over the 100 samples, of the SG derivatives.
      Dim mean_sqrd_error As Double = NMathFunctions.Mean(NMathFunctions.Pow(derivative_sinc - sg_d_sinc, 2.0))


      Console.WriteLine("The mean squared error of the Savitzky-Golay derivative estimate of the sinc() function = {0}", mean_sqrd_error)

      Console.WriteLine("Press Enter Key")

    End Sub

  End Module

End Namespace

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