public MedianFilters()
{
_signal = new WhiteNoiseBuilder().OfLength(N).Build();
_filter = new MedianFilter(15);
_filter2 = new MedianFilter2(15);
}
/// <summary>
/// Constructor
/// </summary>
/// <param name="fftSize"></param>
/// <param name="hopSize"></param>
/// <param name="harmonicWinSize"></param>
/// <param name="percussiveWinSize"></param>
/// <param name="masking"></param>
public HarmonicPercussiveSeparator(int fftSize = 2048,
int hopSize = 512,
int harmonicWinSize = 17,
int percussiveWinSize = 17,
HpsMasking masking = HpsMasking.WienerOrder2)
{
_stft = new Stft(fftSize, hopSize);
_medianHarmonic = new MedianFilter2(harmonicWinSize);
_medianPercussive = new MedianFilter2(percussiveWinSize);
switch (masking)
{
case HpsMasking.Binary:
_mask = BinaryMask;
break;
case HpsMasking.WienerOrder1:
_mask = WienerMask1;
break;
default:
_mask = WienerMask2;
break;
}
}
public void TestMedianFiltering()
{
var filter = new MedianFilter2(5);
var input = new[] { 2, 6, 5, 4, 0, 3, 5, 7, 9, 2, 0, 1f };
var expected = new[] { 2, 4, 4, 4, 4, 4, 5, 5, 5, 2, 1, 0f };
var filtered = filter.ApplyTo(new DiscreteSignal(1, input));
Assert.That(filtered.Samples, Is.EqualTo(expected).Within(1e-10));
}
public void TestMedianFilteringDefault()
{
var filter1 = new MedianFilter(); // 9-point median filter (faster implementation for sizes > 10)
var filter2 = new MedianFilter2(); // 9-point median filter
var input = new[] { 1, 6, 5, 2, 8, 1, 9, 5, 4, 2, 3, 4, 6, 7, 4f };
var expected = new[] { 1, 1, 2, 5, 5, 5, 4, 4, 4, 4, 4, 4, 4, 3, 3f };
var filtered1 = filter1.ApplyTo(new DiscreteSignal(1, input));
var filtered2 = filter2.ApplyTo(new DiscreteSignal(1, input));
Assert.Multiple(() =>
{
Assert.That(filtered1.Samples, Is.EqualTo(expected).Within(1e-10));
Assert.That(filtered2.Samples, Is.EqualTo(expected).Within(1e-10));
});
}
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}");
}
