/// <summary>
/// Finds fundamental frequency: calculates spectrogram, finds peaks, analyzes
/// and refines frequency by diff sample values.
/// </summary>
/// <param name="x">The sounds samples data</param>
/// <param name="sampleRate">The sound sample rate</param>
/// <param name="minFreq">The min useful frequency</param>
/// <param name="maxFreq">The max useful frequency</param>
/// <returns>Found frequency, 0 - otherwise</returns>
internal static double FindFundamentalFrequency(double[] x, int sampleRate, double minFreq, double maxFreq)
{
double[] spectr = FftAlgorithm.Calculate(x);
int usefullMinSpectr = Math.Max(0,
(int)(minFreq * spectr.Length / sampleRate));
int usefullMaxSpectr = Math.Min(spectr.Length,
(int)(maxFreq * spectr.Length / sampleRate) + 1);
// find peaks in the FFT frequency bins
const int PeaksCount = 5;
int[] peakIndices;
peakIndices = FindPeaks(spectr, usefullMinSpectr, usefullMaxSpectr - usefullMinSpectr,
PeaksCount);
if (Array.IndexOf(peakIndices, usefullMinSpectr) >= 0)
{
// lowest usefull frequency bin shows active
// looks like is no detectable sound, return 0
return(0);
}
// select fragment to check peak values: data offset
const int verifyFragmentOffset = 0;
// ... and half length of data
int verifyFragmentLength = (int)(sampleRate / minFreq);
// trying all peaks to find one with smaller difference value
double minPeakValue = Double.PositiveInfinity;
int minPeakIndex = 0;
int minOptimalInterval = 0;
for (int i = 0; i < peakIndices.Length; i++)
{
int index = peakIndices[i];
int binIntervalStart = spectr.Length / (index + 1), binIntervalEnd = spectr.Length / index;
int interval;
double peakValue;
// scan bins frequencies/intervals
ScanSignalIntervals(x, verifyFragmentOffset, verifyFragmentLength,
binIntervalStart, binIntervalEnd, out interval, out peakValue);
if (peakValue < minPeakValue)
{
minPeakValue = peakValue;
minPeakIndex = index;
minOptimalInterval = interval;
}
}
return((double)sampleRate / minOptimalInterval);
}
// Находим фундаментальную частоту: вычисляем спектрограмму, находим пики, анализируем
//х - звуковые сэмплы
//sampleRate частота семплирования
//minFreq минимальная полезная частота
//maxFreq максимальная полезная частота
//returns Найденная частота, 0 - в противном случае
internal static double FindFundamentalFrequency(double[] x, int sampleRate, double minFreq, double maxFreq)
{
double[] spectr = FftAlgorithm.Calculate(x);
int usefullMinSpectr = Math.Max(0,
(int)(minFreq * spectr.Length / sampleRate));
int usefullMaxSpectr = Math.Min(spectr.Length,
(int)(maxFreq * spectr.Length / sampleRate) + 1);
// находим пики частот по БПФ
const int PeaksCount = 5;
int[] peakIndices;
peakIndices = FindPeaks(spectr, usefullMinSpectr, usefullMaxSpectr - usefullMinSpectr,
PeaksCount);
if (Array.IndexOf(peakIndices, usefullMinSpectr) >= 0)
{
//
// если звука не будет - вернет 0
return(0);
}
// выбирает фрагмент для регистрации пиковых значений: смещение данных
const int verifyFragmentOffset = 0;
// ... и половина длины данных
int verifyFragmentLength = (int)(sampleRate / minFreq);
// перебираем все пики для поиска одного с наименьшим отличием от других
double minPeakValue = Double.PositiveInfinity;
int minPeakIndex = 0;
int minOptimalInterval = 0;
for (int i = 0; i < peakIndices.Length; i++)
{
int index = peakIndices[i];
int binIntervalStart = spectr.Length / (index + 1), binIntervalEnd = spectr.Length / index;
int interval;
double peakValue;
// сканирование частот/интервалов
ScanSignalIntervals(x, verifyFragmentOffset, verifyFragmentLength,
binIntervalStart, binIntervalEnd, out interval, out peakValue);
if (peakValue < minPeakValue)
{
minPeakValue = peakValue;
minPeakIndex = index;
minOptimalInterval = interval;
}
}
return((double)sampleRate / minOptimalInterval);
}
protected override void ProcessData(short[] data)
{
foreach (short[] portion in windowBuffer.Process(data))
{
for (int i = 0; i < buffer.Length; i++)
{
buffer[i] = portion[i];
}
double[] spectr = FftAlgorithm.Calculate(buffer);
owner.OnSpectrographData(new SpectrographDataEventArgs(spectr));
}
}
