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IIR_Butterworth_Main.cs
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IIR_Butterworth_Main.cs
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using System;
using System.IO;
using System.Numerics;
using System.Collections.Generic;
using System.Text;
using MathNet.Numerics.LinearAlgebra;
using System.Net.Http.Headers;
using System.Linq;
using MathNet.Numerics;
using Combinatorics;
using Combinatorics.Collections;
using System.Runtime.InteropServices.ComTypes;
namespace IIR_Butterworth_C_Sharp
{
class IIR_Butterworth_Main
{
static void Main(string[] args)
{
IIR_Butterworth_Interface IBI = new IIR_Butterworth_C_Sharp.IIR_Butterworth_Implementation();
double f1 = 30; //High Pass
double f2 = 40; //Low Pass
double sf = 2048; //Sampling frequency
int order_filt = 3; //Order
double Nyquist_F = sf / 2;
double[][] coeff_final = new double[2][];
bool stability_check;
int type_filt = 3;
int coeff_numb = 0;
//Directory where to save the pre-filt and post-filt data
string dir = @"C:\Users\press\OneDrive\Desktop\IIR_Butterworth_C_Sharp";
try
{
//Set the current directory.
Directory.SetCurrentDirectory(dir);
}
catch (DirectoryNotFoundException e)
{
Console.WriteLine("The specified directory does not exist. {0}", e);
}
//Build the signal to be used to test the filter
int length_test_signal = 2047;
double[] test_signal = new double[length_test_signal];
double[] time = new double[length_test_signal];
double freq_data_I = 10;
double freq_data_II = 80;
double[] output_filt_signal = new double[length_test_signal];
for (int kk = 0; kk < length_test_signal; kk++)
{
time[kk] = (double)kk / sf;
test_signal[kk] = Math.Sin(2 * Math.PI * time[kk] * freq_data_I) + Math.Sin(2 * Math.PI * time[kk] * freq_data_II);
}
using (StreamWriter sw = new StreamWriter("Pre_Filtered_data.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(test_signal[hh]));
}
}
using (StreamWriter sw = new StreamWriter("Time_domain.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(time[hh]));
}
}
switch (type_filt)
{
case 0:
coeff_numb = 2 * order_filt + 1;
for (int i = 0; i < 2; i++)
{
coeff_final[i] = new double[coeff_numb];
}
coeff_final = IBI.Lp2bp(f1 / Nyquist_F, f2 / Nyquist_F, order_filt);
stability_check = IBI.Check_stability_iir(coeff_final);
output_filt_signal = IBI.Filter_Data(coeff_final, test_signal);
using (StreamWriter sw = new StreamWriter("Filtered_data.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(output_filt_signal[hh]));
}
}
if (stability_check)
{
Console.Write("The filter is stable");
Console.Write("\n");
}
else
{
Console.Write("The filter is unstable");
Console.Write("\n");
}
for (int kk = 0; kk < 2; kk++)
{
if (kk == 0)
{
Console.Write ("Numerator: ");
}
else
{
Console.Write("Denumerator: ");
}
for (int ll = 0; ll < coeff_numb; ll++)
{
Console.Write(coeff_final[kk][ll]);
Console.Write("\t");
}
Console.Write("\n");
}
break;
case 1:
coeff_numb = 2 * order_filt + 1;
for (int i = 0; i < 2; i++)
{
coeff_final[i] = new double[coeff_numb];
}
coeff_final = IBI.Lp2bs(f1 / Nyquist_F, f2 / Nyquist_F, order_filt);
stability_check = IBI.Check_stability_iir(coeff_final);
output_filt_signal = IBI.Filter_Data(coeff_final, test_signal);
using (StreamWriter sw = new StreamWriter("Filtered_data.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(output_filt_signal[hh]));
}
}
if (stability_check)
{
Console.Write("The filter is stable");
Console.Write("\n");
}
else
{
Console.Write("The filter is unstable");
Console.Write("\n");
}
for (int kk = 0; kk < 2; kk++)
{
if (kk == 0)
{
Console.Write("Numerator: ");
}
else
{
Console.Write("Denumerator: ");
}
for (int ll = 0; ll < coeff_numb; ll++)
{
Console.Write(coeff_final[kk][ll]);
Console.Write("\t");
}
Console.Write("\n");
}
break;
case 2:
coeff_numb = order_filt + 1;
for (int i = 0; i < 2; i++)
{
coeff_final[i] = new double[coeff_numb];
}
coeff_final = IBI.Lp2hp(f1 / Nyquist_F, order_filt);
stability_check = IBI.Check_stability_iir(coeff_final);
output_filt_signal = IBI.Filter_Data(coeff_final, test_signal);
using (StreamWriter sw = new StreamWriter("Filtered_data.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(output_filt_signal[hh]));
}
}
if (stability_check)
{
Console.Write("The filter is stable");
Console.Write("\n");
}
else
{
Console.Write("The filter is unstable");
Console.Write("\n");
}
for (int kk = 0; kk < 2; kk++)
{
if (kk == 0)
{
Console.Write("Numerator: ");
}
else
{
Console.Write("Denumerator: ");
}
for (int ll = 0; ll < coeff_numb; ll++)
{
Console.Write(coeff_final[kk][ll]);
Console.Write("\t");
}
Console.Write("\n");
}
break;
case 3:
coeff_numb = order_filt + 1;
for (int i = 0; i < 2; i++)
{
coeff_final[i] = new double[coeff_numb];
}
coeff_final = IBI.Lp2lp(f2 / Nyquist_F, order_filt);
stability_check = IBI.Check_stability_iir(coeff_final);
output_filt_signal = IBI.Filter_Data(coeff_final, test_signal);
using (StreamWriter sw = new StreamWriter("Filtered_data.txt"))
{
for (int hh = 0; hh < length_test_signal; hh++)
{
sw.WriteLine(Convert.ToString(output_filt_signal[hh]));
}
}
if (stability_check)
{
Console.Write("The filter is stable");
Console.Write("\n");
}
else
{
Console.Write("The filter is unstable");
Console.Write("\n");
}
for (int kk = 0; kk < 2; kk++)
{
if (kk == 0)
{
Console.Write("Numerator: ");
}
else
{
Console.Write("Denumerator: ");
}
for (int ll = 0; ll < coeff_numb; ll++)
{
Console.Write(coeff_final[kk][ll]);
Console.Write("\t");
}
Console.Write("\n");
}
break;
}
}
}
}