private void AnalyzeCustomLpFilter()
{
var order = 23;
var freq = 0.22;
if (filterParamsDataGrid.RowCount > 0)
{
order = Convert.ToInt32(filterParamsDataGrid.Rows[0].Cells[1].Value);
freq = Convert.ToDouble(filterParamsDataGrid.Rows[1].Cells[1].Value);
}
orderNumeratorTextBox.Text = (order - 1).ToString();
orderDenominatorTextBox.Text = (order - 1).ToString();
_filter = new FirFilter(DesignFilter.FirWinLp(order, freq));
// for double precision and FDA:
//var tf = new TransferFunction(DesignFilter.FirWinLp(order, freq));
//_filter = new FirFilter(tf);
filterParamsDataGrid.RowCount = 2;
filterParamsDataGrid.Rows[0].Cells[0].Value = "order";
filterParamsDataGrid.Rows[0].Cells[1].Value = order;
filterParamsDataGrid.Rows[1].Cells[0].Value = "freq";
filterParamsDataGrid.Rows[1].Cells[1].Value = freq;
}
/// <summary>
/// Does interpolation of <paramref name="signal"/> followed by lowpass filtering.
/// </summary>
/// <param name="signal">Signal</param>
/// <param name="factor">Interpolation factor (e.g. factor=2 if 8000 Hz -> 16000 Hz)</param>
/// <param name="filter">Lowpass anti-aliasing filter</param>
public DiscreteSignal Interpolate(DiscreteSignal signal, int factor, FirFilter filter = null)
{
if (factor == 1)
{
return(signal.Copy());
}
var output = new float[signal.Length * factor];
var pos = 0;
for (var i = 0; i < signal.Length; i++)
{
output[pos] = factor * signal[i];
pos += factor;
}
var lpFilter = filter;
if (filter is null)
{
var filterSize = factor > MinResamplingFilterOrder / 2 ?
2 * factor + 1 :
MinResamplingFilterOrder;
lpFilter = new FirFilter(DesignFilter.FirWinLp(filterSize, 0.5f / factor));
}
return(lpFilter.ApplyTo(new DiscreteSignal(signal.SamplingRate * factor, output)));
}
/// <summary>
/// Decimation preceded by low-pass filtering
/// </summary>
/// <param name="signal"></param>
/// <param name="factor"></param>
/// <param name="filter"></param>
/// <returns></returns>
public DiscreteSignal Decimate(DiscreteSignal signal, int factor, FirFilter filter = null)
{
if (factor == 1)
{
return(signal.Copy());
}
var filterSize = factor > MinResamplingFilterOrder / 2 ?
2 * factor + 1 :
MinResamplingFilterOrder;
var lpFilter = filter;
if (filter == null)
{
lpFilter = new FirFilter(DesignFilter.FirWinLp(filterSize, 0.5f / factor));
signal = lpFilter.ApplyTo(signal);
}
var output = new float[signal.Length / factor];
var pos = 0;
for (var i = 0; i < output.Length; i++)
{
output[i] = signal[pos];
pos += factor;
}
return(new DiscreteSignal(signal.SamplingRate / factor, output));
}
public FirFiltersVersion2Vs5VsZi()
{
_signal = new WhiteNoiseBuilder().OfLength(N).Build();
_filterV5Kernel5 = new FirFilter(DesignFilter.FirWinLp(5, 0.1));
_filterV2Kernel5 = new FirFilterV2(DesignFilter.FirWinLp(5, 0.1));
_filterZiKernel5 = new ZiFilter(DesignFilter.FirWinLp(5, 0.1), new[] { 1.0 });
_filterV5Kernel35 = new FirFilter(DesignFilter.FirWinLp(35, 0.1));
_filterV2Kernel35 = new FirFilterV2(DesignFilter.FirWinLp(35, 0.1));
_filterZiKernel35 = new ZiFilter(DesignFilter.FirWinLp(35, 0.1), new[] { 1.0 });
}
/// <summary>
/// Simple resampling as the combination of interpolation and decimation.
/// </summary>
/// <param name="signal"></param>
/// <param name="up"></param>
/// <param name="down"></param>
/// <param name="filter"></param>
/// <returns></returns>
public DiscreteSignal ResampleUpDown(DiscreteSignal signal, int up, int down, FirFilter filter = null)
{
if (up == down)
{
return(signal.Copy());
}
var newSamplingRate = signal.SamplingRate * up / down;
if (up > 20 && down > 20)
{
return(Resample(signal, newSamplingRate, filter));
}
var output = new float[signal.Length * up];
var pos = 0;
for (var i = 0; i < signal.Length; i++)
{
output[pos] = up * signal[i];
pos += up;
}
var lpFilter = filter;
if (filter == null)
{
var factor = Math.Max(up, down);
var filterSize = factor > MinResamplingFilterOrder / 2 ?
8 * factor + 1 :
MinResamplingFilterOrder;
lpFilter = new FirFilter(DesignFilter.FirWinLp(filterSize, 0.5f / factor));
}
var upsampled = lpFilter.ApplyTo(new DiscreteSignal(signal.SamplingRate * up, output));
output = new float[upsampled.Length / down];
pos = 0;
for (var i = 0; i < output.Length; i++)
{
output[i] = upsampled[pos];
pos += down;
}
return(new DiscreteSignal(newSamplingRate, output));
}
private void ApplySettings()
{
_fftSize = int.Parse(fftSizeTextBox.Text);
chunkTimer.Interval = int.Parse(intervalTextBox.Text);
var kernel = DesignFilter.FirWinLp(int.Parse(kernelSizeTextBox.Text), 0.2);
_blockConvolver = new OlaBlockConvolver(kernel, _fftSize);
// or equivalently:
//_blockConvolver = OlaBlockConvolver.FromFilter(new FirFilter(kernel), _fftSize);
_output = new float[_blockConvolver.HopSize * 5];
}
/// <summary>
/// Band-limited resampling
/// </summary>
/// <param name="signal"></param>
/// <param name="newSamplingRate"></param>
/// <param name="filter"></param>
/// <param name="order"></param>
/// <returns></returns>
public DiscreteSignal Resample(DiscreteSignal signal,
int newSamplingRate,
FirFilter filter = null,
int order = 15)
{
if (signal.SamplingRate == newSamplingRate)
{
return(signal.Copy());
}
var g = (float)newSamplingRate / signal.SamplingRate;
var input = signal.Samples;
var output = new float[(int)(input.Length * g)];
if (g < 1 && filter == null)
{
filter = new FirFilter(DesignFilter.FirWinLp(MinResamplingFilterOrder, g / 2));
input = filter.ApplyTo(signal).Samples;
}
var step = 1 / g;
for (var n = 0; n < output.Length; n++)
{
var x = n * step;
for (var i = -order; i < order; i++)
{
var j = (int)Math.Floor(x) - i;
if (j < 0 || j >= input.Length)
{
continue;
}
var t = x - j;
float w = (float)(0.5 * (1.0 + Math.Cos(t / order * Math.PI))); // Hann window
float sinc = (float)MathUtils.Sinc(t); // Sinc function
output[n] += w * sinc * input[j];
}
}
return(new DiscreteSignal(newSamplingRate, output));
}
public FirFiltersVsBlockConvolvers()
{
_signal = new WhiteNoiseBuilder().OfLength(N).Build();
var kernel21 = DesignFilter.FirWinLp(21, 0.1);
_filter21 = new FirFilter(kernel21);
_ola21 = new OlaBlockConvolver(kernel21, 128);
_ols21 = new OlsBlockConvolver(kernel21, 128);
var kernel101 = DesignFilter.FirWinLp(101, 0.1);
_filter101 = new FirFilter(kernel101);
_filter101.KernelSizeForBlockConvolution = 2048;
_ola101 = new OlaBlockConvolver(kernel101, 512);
_ols101 = new OlsBlockConvolver(kernel101, 512);
var kernel315 = DesignFilter.FirWinLp(315, 0.1);
_filter315 = new FirFilter(kernel315);
_filter315.KernelSizeForBlockConvolution = 2048;
_ola315 = new OlaBlockConvolver(kernel315, 2048);
_ols315 = new OlsBlockConvolver(kernel315, 2048);
}
public void Run()
{
var output2 = new float[_signal.Length];
var output4 = new float[_signal.Length];
var output5 = new float[_signal.Length];
var outputZi = new float[_signal.Length];
var samples = _signal.Samples;
for (var i = 0; i < samples.Length; i++)
{
output4[i] = _filterV4BiQuad.Process(samples[i]);
output5[i] = _filterV5BiQuad.Process(samples[i]);
outputZi[i] = _filterZiBiQuad.Process(samples[i]);
}
var diffAverageV4 = output5.Zip(output4, (o5, o4) => Math.Abs(o5 - o4)).Average();
var diffAverageZi = output5.Zip(outputZi, (o5, zi) => Math.Abs(o5 - zi)).Average();
Console.WriteLine($"Average difference Ver.0.9.5 vs. Ver.0.9.4 : {diffAverageV4}");
Console.WriteLine($"Average difference IirFilter vs. ZiFilter : {diffAverageZi}");
for (var i = 0; i < samples.Length; i++)
{
output4[i] = _filterV4Butterworth6.Process(samples[i]);
output5[i] = _filterV5Butterworth6.Process(samples[i]);
outputZi[i] = _filterZiButterworth6.Process(samples[i]);
}
diffAverageV4 = output5.Zip(output4, (o5, o4) => Math.Abs(o5 - o4)).Average();
diffAverageZi = output5.Zip(outputZi, (o5, zi) => Math.Abs(o5 - zi)).Average();
Console.WriteLine($"Average difference Ver.0.9.5 vs. Ver.0.9.4 : {diffAverageV4}");
Console.WriteLine($"Average difference IirFilter vs. ZiFilter : {diffAverageZi}");
// === MISC ====
var med = new MedianFilter();
var med2 = new MedianFilter2();
var medOut = med.ApplyTo(_signal).Samples;
var medOut2 = med2.ApplyTo(_signal).Samples;
var diffAverageMed = medOut.Zip(medOut, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference MedianFilter vs. MedianFilter2 : {diffAverageMed}");
var ma = new MovingAverageFilter();
var maRec = new MovingAverageRecursiveFilter();
var maOut = ma.ApplyTo(_signal).Samples;
var maRecOut = maRec.ApplyTo(_signal).Samples;
var diffAverageMa = maOut.Zip(maRecOut, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference MovingAverageFilter vs. MovingAverageRecursiveFilter : {diffAverageMa}");
// 32bit vs. 64bit
var fir32 = new FirFilter(DesignFilter.FirWinLp(7, 0.1));
var fir64 = new FirFilter64(DesignFilter.FirWinLp(7, 0.1));
var fir32Out = fir32.ApplyTo(_signal).Samples;
var fir64Out = fir64.ApplyTo(_signal.Samples.ToDoubles());
var diffAverageFir = fir64Out.Zip(fir32Out, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference FirFilter vs. FirFilter64 : {diffAverageFir}");
var iir32 = new IirFilter(_filterV5Butterworth6.Tf);
var iir64 = new IirFilter64(_filterV5Butterworth6.Tf);
var iir32Out = iir32.ApplyTo(_signal).Samples;
var iir64Out = iir64.ApplyTo(_signal.Samples.ToDoubles());
var diffAverageIir = iir64Out.Zip(iir32Out, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference IirFilter vs. IirFilter64 : {diffAverageIir}");
var zi32 = new ZiFilter(_filterV5Butterworth6.Tf);
var zi64 = new ZiFilter64(_filterV5Butterworth6.Tf);
var zi32Out = zi32.ApplyTo(_signal).Samples;
var zi64Out = zi64.ApplyTo(_signal.Samples.ToDoubles());
var diffAverageZis = zi64Out.Zip(zi32Out, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference ZiFilter vs. ZiFilter64 : {diffAverageZis}");
zi32Out = zi32.ZeroPhase(_signal).Samples;
zi64Out = zi64.ZeroPhase(_signal.Samples.ToDoubles());
var diffAverageZiZeroPhase = zi64Out.Zip(zi32Out, (m1, m2) => Math.Abs(m1 - m2)).Average();
Console.WriteLine($"Average difference ZiFilter vs. ZiFilter64 (zero-phase): {diffAverageZiZeroPhase}");
}