private void FourierRecord_Click(object sender, EventArgs e)
{
if (!File.Exists("./Sounds/temp.wav"))
{
return;
}
ComplexSignal sComplex = FFTComplex("temp");
Complex[] channel = sComplex.GetChannel(0);
chart2.Series.Clear();
chart2.Series.Add("FFT");
chart2.Series["FFT"].ChartType = SeriesChartType.FastLine;
chart2.Series["FFT"].ChartArea = "ChartArea1";
double[] power = FilterVoiceHz(Accord.Audio.Tools.GetMagnitudeSpectrum(channel));
double[] freqv = FilterVoiceHz(Accord.Audio.Tools.GetFrequencyVector(sComplex.Length, sComplex.SampleRate));
for (int i = 1; i < power.Length; i++)
{
chart2.Series["FFT"].Points.AddXY(freqv[i], power[i]);
}
}
/// <summary>
/// Processes the filter.
/// </summary>
protected override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
if (sourceData.Status != ComplexSignalStatus.Analytic)
{
throw new ArgumentException("Signal must be in analytic form.", "sourceData");
}
SampleFormat format = sourceData.SampleFormat;
int channels = sourceData.Channels;
int length = sourceData.Length;
int samples = sourceData.Samples;
Complex d = new Complex();
unsafe
{
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
for (int i = 0; i < samples; i++, src++, dst++)
{
d.Re = (*dst).Magnitude;
*dst = d;
}
}
}
/// <summary>
/// This method will be called whenever there is a new audio
/// frame to be processed.
/// </summary>
///
void source_NewFrame(object sender, NewFrameEventArgs eventArgs)
{
// We can start by converting the audio frame to a complex signal
ComplexSignal signal = ComplexSignal.FromSignal(eventArgs.Signal);
// If its needed,
if (window != null)
{
// Apply the chosen audio window
signal = window.Apply(signal, 0);
}
// Transform to the complex domain
signal.ForwardFourierTransform();
// Now we can get the power spectrum output and its
// related frequency vector to plot our spectrometer.
Complex[] channel = signal.GetChannel(0);
double[] power = Accord.Audio.Tools.GetPowerSpectrum(channel);
double[] freqv = Accord.Audio.Tools.GetFrequencyVector(signal.Length, signal.SampleRate);
power[0] = 0; // zero DC
float[] g = new float[power.Length];
for (int i = 0; i < power.Length; i++)
{
g[i] = (float)power[i];
}
// Adjust the zoom according to the horizontal and vertical scrollbars.
chart1.RangeX = new DoubleRange(freqv[0], freqv[freqv.Length - 1] / hScrollBar1.Value);
chart1.RangeY = new DoubleRange(0f, Math.Pow(10, -vScrollBar1.Value));
chart1.UpdateWaveform("fft", g);
}
public void createFrequencyArray(ComplexSignal[] tempFrequency, ComplexSignal curComplex, out double[] power, out double[] magnitudes, out double[] freq, out double[] meanPower, out double[] meanMagnitudes)
{
int amountOfSignals = 0;
var length = curComplex.Length / (2 + 1);
double[] tempMeanPower = new double[length];
double[] tempMeanMag = new double[length];
double[] tempPower = { };
double[] tempMagnitudes = { };
double[] tempFreq = { };
foreach (ComplexSignal curSig in tempFrequency)
{
frequencyData(curSig, out tempPower, out tempMagnitudes, out tempFreq);
for (int j = 0; j < length; j++)
{
tempMeanPower[j] += tempPower[j];
tempMeanMag[j] += tempPower[j];
}
amountOfSignals++;
}
for (int j = 0; j < length; j++)
{
tempMeanPower[j] /= amountOfSignals;
tempMeanMag[j] /= amountOfSignals;
}
meanPower = tempMeanPower;
meanMagnitudes = tempMeanMag;
power = tempPower;
magnitudes = tempMagnitudes;
freq = tempFreq;
}
void FourierBTClick(object sender, EventArgs e)
{
if (soundList.SelectedItems.Count == 0)
{
return;
}
if (waveWriter != null)
{
return;
}
string sFile = soundList.SelectedItem.ToString();
ComplexSignal sComplex = FFTComplex(sFile);
Complex[] channel = sComplex.GetChannel(0);
chart2.Series.Clear();
chart2.Series.Add("FFT");
chart2.Series["FFT"].ChartType = SeriesChartType.FastLine;
chart2.Series["FFT"].ChartArea = "ChartArea1";
double[] power = FilterVoiceHz(Accord.Audio.Tools.GetMagnitudeSpectrum(channel));
double[] freqv = FilterVoiceHz(Accord.Audio.Tools.GetFrequencyVector(sComplex.Length, sComplex.SampleRate));
for (int i = 1; i < power.Length; i++)
{
chart2.Series["FFT"].Points.AddXY(freqv[i], power[i]);
}
}
void source_NewFrame(object sender, NewFrameEventArgs eventArgs)
{
ComplexSignal signal = ComplexSignal.FromSignal(eventArgs.Signal);
if (hammingWindowToolStripMenuItem.Checked)
{
ComplexSignal c = window.Apply(signal, 0);
signal = c;
}
signal.ForwardFourierTransform();
Complex[] channel = signal.GetChannel(0);
double[] power = Accord.Audio.Tools.GetPowerSpectrum(channel);
double[] freqv = Accord.Audio.Tools.GetFrequencyVector(signal.Length, signal.SampleRate);
power[0] = 0; // zero DC
float[] g = new float[power.Length];
for (int i = 0; i < power.Length; i++)
{
// g[i, 0] = freqv[i];
g[i] = (float)power[i];
}
chart1.RangeX = new DoubleRange(freqv[0], freqv[freqv.Length - 1] / hScrollBar1.Value);
chart1.RangeY = new DoubleRange(0f, Math.Pow(10, -vScrollBar1.Value));
chart1.UpdateWaveform("fft", g);
}
/// <summary>
/// Applies the filter to a windowed signal.
/// </summary>
///
public ComplexSignal[] Apply(params ComplexSignal[] complexSignal)
{
ComplexSignal[] s = new ComplexSignal[complexSignal.Length];
for (int i = 0; i < complexSignal.Length; i++)
s[i] = Apply(complexSignal[i]);
return s;
}
void source_NewFrame(object sender, NewFrameEventArgs eventArgs)
{
// We can start by converting the audio frame to a complex signal
var signal = ComplexSignal.FromSignal(eventArgs.Signal);
// If its needed,
if (window != null)
{
// Apply the chosen audio window
signal = window.Apply(signal, 0);
}
// Transform to the complex domain
signal.ForwardFourierTransform();
// Now we can get the power spectrum output and its
// related frequency vector to plot our spectrometer.
Complex[] channel = signal.GetChannel(0);
double[] power = Accord.Audio.Tools.GetPowerSpectrum(channel);
ListOfPowerSpectrum.Add(power);
foreach (double value in power)
{
if (value != 0.0 && value > 1.0E-10)
{
//Console.WriteLine("Index to {0}", ListOfPowerSpectrum.IndexOf(power));
soundsDetectedIndexes.Add(ListOfPowerSpectrum.IndexOf(power));
break;
}
}
}
public float[] EEGToSound(double[] inputData)
{
ComplexSignal cs = Signal.FromArray(inputData, SAMPLE_RATE).ToComplex();
cs.ForwardFourierTransform();
powerSpectrum = Tools.GetPowerSpectrum(cs.GetChannel(0));
Array.ConstrainedCopy(powerSpectrum, 0, shortenedPowerSpectrum, 0, MAX_FREQ);
double maxSignal = shortenedPowerSpectrum.Max();
shortenedPowerSpectrum = shortenedPowerSpectrum.Select(x => x / maxSignal).ToArray();
Array.Sort(shortenedPowerSpectrum, frequencyRange);
Array.ConstrainedCopy(shortenedPowerSpectrum, 0, highestPowers, 0, NUM_MAX_FREQS);
Array.ConstrainedCopy(frequencyRange, 0, highestFrequencies, 0, NUM_MAX_FREQS);
for (int i = 0; i < NUM_MAX_FREQS; i++)
{
double[] sineWave = Generate.Sinusoidal(RECORDING_RATE * SAMPLE_DURATION, RECORDING_RATE, highestFrequencies [i], highestPowers [i]);
outputData = outputData.Zip(sineWave, (x, y) => x + y).ToArray();
}
float[] audioData = outputData.Select <double, float> (x => (float)x).ToArray();
return(audioData);
}
private void testWindow(int length, IWindow window)
{
Complex[,] data = (Complex[, ]) this.data.Clone();
ComplexSignal target = ComplexSignal.FromArray(data, 8000);
Complex[,] samples = target.ToArray();
Assert.IsTrue(data.IsEqual(samples));
ComplexSignal[] windows = target.Split(window, 1);
for (int i = 0; i < windows.Length; i++)
{
int min = System.Math.Min(i + length, samples.Length / 2);
Complex[] segment = windows[i].ToArray().Reshape(1);
Complex[] sub = samples.Submatrix(i, min - 1, null).Reshape(1);
var expected = new Complex[length * 2];
for (int j = 0; j < sub.Length; j++)
{
expected[j] = sub[j];
}
Assert.IsTrue(segment.IsEqual(expected));
}
}
void ProcessBaselinePowerSpectrum()
{
ComplexSignal cs = Signal.FromArray(baselineArray, SAMPLE_RATE).ToComplex();
cs.ForwardFourierTransform();
baselinePowerSpectrum = Tools.GetPowerSpectrum(cs.GetChannel(0));
CubeStateManager.baselineEEG[(int)channelToRecordFrom] = baselineArray.Average();
}
public void GetEnergyTest()
{
ComplexSignal target = ComplexSignal.FromArray(data, 8000);
double expected = 0.5444;
double actual = target.GetEnergy();
Assert.AreEqual(expected, actual, 1e-4);
}
/// <summary>
/// Applies the filter to a windowed signal.
/// </summary>
///
public ComplexSignal[] Apply(params ComplexSignal[] complexSignal)
{
ComplexSignal[] s = new ComplexSignal[complexSignal.Length];
for (int i = 0; i < complexSignal.Length; i++)
{
s[i] = Apply(complexSignal[i]);
}
return(s);
}
public void ComplexSignalConstructorTest()
{
ComplexSignal target = ComplexSignal.FromArray(data, 8000);
Assert.AreEqual(target.Channels, 2);
Assert.AreEqual(target.Length, 8);
Assert.AreEqual(target.Samples, 16);
Assert.AreEqual(target.SampleRate, 8000);
Assert.IsNotNull(target.RawData);
}
/// <summary>
/// Splits a signal using a window
/// </summary>
///
public static ComplexSignal[] Split(this ComplexSignal signal, IWindow window, int step)
{
int n = (int)System.Math.Floor(signal.Length / (double)step);
ComplexSignal[] windows = new ComplexSignal[n];
for (int i = 0; i < n; i++)
{
windows[i] = window.Apply(signal, i * step);
}
return windows;
}
public void ComplexSignalConstructorTest()
{
ComplexSignal target = ComplexSignal.FromArray(data, 8000);
Assert.AreEqual(target.Channels, 2);
Assert.AreEqual(target.Length, 8);
Assert.AreEqual(target.Samples, 16);
Assert.AreEqual(target.SampleRate, 8000);
Assert.AreEqual(256, target.NumberOfBytes);
Assert.AreEqual(16, target.InnerData.Length);
Assert.AreEqual(16, target.SampleSize);
Assert.IsNotNull(target.RawData);
}
private static double FindFrequencyCount(int sampleRate, Signal signal, double frequency)
{
ComplexSignal c = signal.ToComplex();
c.ForwardFourierTransform();
double[] freq = Accord.Audio.Tools.GetFrequencyVector(c.Length, sampleRate);
double[] ms = Accord.Audio.Tools.GetMagnitudeSpectrum(c.GetChannel(0));
int idx = freq.Subtract(frequency).Abs().ArgMin();
return(ms[idx]);
}
/// <summary>
/// Splits a signal using a window
/// </summary>
///
public static ComplexSignal[] Split(this ComplexSignal signal, IWindow window, int step)
{
int n = (int)System.Math.Floor(signal.Length / (double)step);
ComplexSignal[] windows = new ComplexSignal[n];
for (int i = 0; i < n; i++)
{
windows[i] = window.Apply(signal, i * step);
}
return(windows);
}
public ComplexSignal FFTComplex(string sFile)
{
WaveDecoder signalwav = new WaveDecoder("./Sounds/" + sFile + ".wav");
Signal sourceSignal = signalwav.Decode();
BlackmanWindow window = new BlackmanWindow(fs);
Signal[] windows = sourceSignal.Split(window, fs);
Signal wSignal = window.Apply(sourceSignal, fs);
ComplexSignal sComplex = wSignal.ToComplex();
sComplex.ForwardFourierTransform();
signalwav.Close();
return(sComplex);
}
/// <summary>
/// Computes (populates) a Spectrogram mapping with values from a signal.
/// </summary>
///
/// <param name="signal">The signal to be windowed in the spectrogram.</param>
///
public void Compute(Signal signal)
{
this.frequencies = FourierTransform2.GetFrequencyVector(windowSize, signal.SampleRate);
Signal[] signals = signal.Split(window: window, stepSize: windowSize);
this.magnitudes = new double[signals.Length][];
for (int i = 0; i < signals.Length; i++)
{
ComplexSignal c = signals[i].ToComplex();
c.ForwardFourierTransform();
this.magnitudes[i] = FourierTransform2.GetMagnitudeSpectrum(c.GetChannel(channel));
}
}
public void waveInput()
{
writeHeaderForARFF();
for (int i = 0; i < audioFileName.Length; i++)
{
string type;
string name;
setTypeAndName(audioFileName[i], out type, out name);
Accord.Audio.Formats.WaveDecoder currentWav = new Accord.Audio.Formats.WaveDecoder(audioFileName[i]);
//Used for time Domain
Signal timeDomain = currentWav.Decode();
//Creates an array of time domain samples for use in calculation of RootMeanSquare aka AverageEnergy
float[] energyArray = new float[timeDomain.Samples];
timeDomain.CopyTo(energyArray);
//average energy for the current wav file
double averageEnergy = Accord.Audio.Tools.RootMeanSquare(energyArray);
//ZCR for the current wav file
double zeroCrossingRate = zeroCrossingRateMethod(timeDomain);
Accord.Audio.Windows.RaisedCosineWindow window = Accord.Audio.Windows.RaisedCosineWindow.Hamming(1024);
Signal[] windows = timeDomain.Split(window, 512);
//Used for Frequency Domain
ComplexSignal[] tempFrequency = windows.Apply(ComplexSignal.FromSignal);
tempFrequency.ForwardFourierTransform();
ComplexSignal curComplex = tempFrequency[0];
double[] power = { };
double[] magnitudes = { };
double[] freq = { };
var length = curComplex.Length / (2 + 1);
double[] meanPower = new double[length];
double[] meanMagnitudes = new double[length];
createFrequencyArray(tempFrequency, curComplex, out power, out magnitudes, out freq, out meanPower, out meanMagnitudes);
//Spectral Centrois for the current wav file
double spectralCentroid = meanMagnitudes.Zip(freq, (m, f) => m * f).Sum() / meanMagnitudes.Sum();
//double spectralCentroid = spectralCentroidMethod(tempFrequency);
//Writes data to arff file
writeARFF(name, averageEnergy, zeroCrossingRate, spectralCentroid, type);
}
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected unsafe override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
int length = sourceData.Length;
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
for (int i = 0; i < length - 1; i++, src++, dst++)
{
double re = src[i + 1].Real - src[i].Real;
// Retain only if difference is positive
*dst = (re > 0) ? new Complex(re, 0) : Complex.Zero;
}
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected unsafe override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
int length = sourceData.Length;
Complex* src = (Complex*)sourceData.Data.ToPointer();
Complex* dst = (Complex*)destinationData.Data.ToPointer();
for (int i = 0; i < length - 1; i++, src++, dst++)
{
double re = src[i + 1].Real - src[i].Real;
// Retain only if difference is positive
*dst = (re > 0) ? new Complex(re, 0) : Complex.Zero;
}
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
int samples = sourceData.Samples;
unsafe
{
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
Complex *comb = (Complex *)combSignal.Data.ToPointer();
for (int i = 0; i < samples; i++, src++, dst++, comb++)
{
*dst = new Complex((src[0] * comb[0]).Magnitude, 0);
}
}
}
public void ComplexSignalConstructor()
{
UnmanagedMemoryStream sourceStream = Properties.Resources.Grand_Piano___Fazioli___major_A_middle;
MemoryStream destinationStream = new MemoryStream();
// Create a decoder for the source stream
WaveDecoder sourceDecoder = new WaveDecoder(sourceStream);
// Decode the signal in the source stream
Signal sourceSignal = sourceDecoder.Decode();
int length = (int)Math.Pow(2, 12);
RaisedCosineWindow window = RaisedCosineWindow.Hamming(length);
Assert.AreEqual(length, window.Length);
Signal[] windows = sourceSignal.Split(window, 1024);
Assert.AreEqual(windows.Length, 172);
foreach (var w in windows)
{
Assert.AreEqual(length, w.Length);
}
ComplexSignal[] complex = windows.Apply(ComplexSignal.FromSignal);
for (int i = 0; i < complex.Length - 1; i++)
{
ComplexSignal c = complex[i];
Assert.AreEqual(2, c.Channels);
Assert.AreEqual(92, c.Duration);
Assert.AreEqual(4096, c.Length);
Assert.AreEqual(SampleFormat.Format128BitComplex, c.SampleFormat);
Assert.AreEqual(44100, c.SampleRate);
Assert.AreEqual(ComplexSignalStatus.Normal, c.Status);
}
complex.ForwardFourierTransform();
for (int i = 0; i < complex.Length - 1; i++)
{
ComplexSignal c = complex[i];
Assert.AreEqual(ComplexSignalStatus.FourierTransformed, c.Status);
}
}
public void ComplexSignalConstructor()
{
var sourceStream = SignalTest.GetSignal("a.wav");
MemoryStream destinationStream = new MemoryStream();
// Create a decoder for the source stream
WaveDecoder sourceDecoder = new WaveDecoder(sourceStream);
// Decode the signal in the source stream
Signal sourceSignal = sourceDecoder.Decode();
int length = (int)Math.Pow(2, 12);
RaisedCosineWindow window = RaisedCosineWindow.Hamming(length);
Assert.AreEqual(length, window.Length);
Signal[] windows = sourceSignal.Split(window, 1024);
Assert.AreEqual(windows.Length, 172);
foreach (var w in windows)
{
Assert.AreEqual(length, w.Length);
}
ComplexSignal[] complex = windows.Apply(ComplexSignal.FromSignal);
for (int i = 0; i < complex.Length - 1; i++)
{
ComplexSignal c = complex[i];
Assert.AreEqual(2, c.Channels);
Assert.AreEqual(93, c.Duration.TotalMilliseconds);
Assert.AreEqual(4096, c.Length);
Assert.AreEqual(SampleFormat.Format128BitComplex, c.SampleFormat);
Assert.AreEqual(44100, c.SampleRate);
Assert.AreEqual(ComplexSignalStatus.Normal, c.Status);
}
complex.ForwardFourierTransform();
for (int i = 0; i < complex.Length - 1; i++)
{
ComplexSignal c = complex[i];
Assert.AreEqual(ComplexSignalStatus.FourierTransformed, c.Status);
}
}
/// <summary>
/// Processes the filter.
/// </summary>
protected unsafe override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
if (sourceData.Status != ComplexSignalStatus.Analytic)
{
throw new ArgumentException("Signal must be in analytic form.", "sourceData");
}
int samples = sourceData.Samples;
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
for (int i = 0; i < samples; i++, src++, dst++)
{
*dst = new Complex((*dst).Magnitude, 0);
}
}
/// <summary>
/// Applies the filter to a signal.
/// </summary>
///
public ComplexSignal Apply(ComplexSignal complexSignal)
{
// get number of channels and samples
int channels = complexSignal.Channels;
int samples = complexSignal.Length;
// retrieve other information
int rate = complexSignal.SampleRate;
// create new signal of required format
ComplexSignal dstSignal = new ComplexSignal(channels, samples, rate);
// process the filter
ProcessFilter(complexSignal, dstSignal);
// return the processed signal
return(dstSignal);
}
/// <summary>
/// Applies the filter to a signal.
/// </summary>
///
public ComplexSignal Apply(ComplexSignal complexSignal)
{
// get number of channels and samples
int channels = complexSignal.Channels;
int samples = complexSignal.Length;
// retrieve other information
int rate = complexSignal.SampleRate;
// create new signal of required format
ComplexSignal dstSignal = new ComplexSignal(channels, samples, rate);
// process the filter
ProcessFilter(complexSignal, dstSignal);
// return the processed signal
return dstSignal;
}
private void EqualsButton_Click(object sender, EventArgs e)
{
Dictionary <double, string> icorrelation = new Dictionary <double, string>();
if (!Directory.Exists("./Sounds"))
{
return;
}
string[] dir_Sounds = Directory.GetFiles("./Sounds");
double max = 0;
foreach (var sound in dir_Sounds)
{
if (!(sound.Contains("temp.wav")) && (sound.Contains(".wav")))
{
string name = sound.Replace("./Sounds", "").Replace(".wav", "").Replace(((char)92).ToString(), "");
ComplexSignal recordSignal = FFTComplex("temp");
Complex[] recordChannel = recordSignal.GetChannel(0);
ComplexSignal bd = FFTComplex(name);
Complex[] bdchannel = bd.GetChannel(0);
double[] rpower = NormalizeStretch(FilterVoiceHz(Accord.Audio.Tools.GetMagnitudeSpectrum(recordChannel)), 0, 1);
double[] bdpower = NormalizeStretch(FilterVoiceHz(Accord.Audio.Tools.GetMagnitudeSpectrum(bdchannel)), 0, 1);
double corr = ComputeCoeff(bdpower, rpower);
Console.WriteLine(name + ":" + corr);
icorrelation.Add(corr, name);
if (corr >= max)
{
max = corr;
}
}
}
foreach (KeyValuePair <double, string> pair in icorrelation)
{
if (pair.Key == max)
{
MessageBox.Show(pair.Value);
}
}
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
int length = sourceData.Length;
unsafe
{
Complex* src = (Complex*)sourceData.Data.ToPointer();
Complex* dst = (Complex*)destinationData.Data.ToPointer();
Complex d = new Complex();
for (int i = 0; i < length - 1; i++, src++, dst++)
{
d.Re = src[i + 1].Re - src[i].Re;
// Retain only if difference is positive
*dst = (d.Re > 0) ? d : Complex.Zero;
}
}
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
int length = sourceData.Length;
unsafe
{
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
Complex d = new Complex();
for (int i = 0; i < length - 1; i++, src++, dst++)
{
d.Re = src[i + 1].Re - src[i].Re;
// Retain only if difference is positive
*dst = (d.Re > 0) ? d : Complex.Zero;
}
}
}
/// <summary>
/// Splits a signal using the window.
/// </summary>
///
public virtual unsafe ComplexSignal Apply(ComplexSignal complexSignal, int sampleIndex)
{
Complex[,] resultData = new Complex[Length, complexSignal.Channels];
ComplexSignal result = ComplexSignal.FromArray(resultData, complexSignal.SampleRate);
int channels = result.Channels;
int minLength = System.Math.Min(complexSignal.Length - sampleIndex, Length);
for (int c = 0; c < complexSignal.Channels; c++)
{
Complex *dst = (Complex *)result.Data.ToPointer() + c;
Complex *src = (Complex *)complexSignal.Data.ToPointer() + c + channels * sampleIndex;
for (int i = 0; i < minLength; i++, dst += channels, src += channels)
{
*dst = window[i] * (*src);
}
}
return(result);
}
/// <summary>
/// Processes the filter.
/// </summary>
///
protected override void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData)
{
SampleFormat format = sourceData.SampleFormat;
int channels = sourceData.Channels;
int length = sourceData.Length;
int samples = sourceData.Samples;
unsafe
{
Complex *src = (Complex *)sourceData.Data.ToPointer();
Complex *dst = (Complex *)destinationData.Data.ToPointer();
Complex *comb = (Complex *)combSignal.Data.ToPointer();
Complex d = new Complex();
for (int i = 0; i < samples; i++, src++, dst++, comb++)
{
d.Re = (src[0] * comb[0]).Magnitude;
*dst = d;
}
}
}
int status = 0; ///记录上次情绪状态
//Signal S2;用作第二通道
//ComplexSignal signal;
private void fft_process()
{
S1 = Signal.FromArray(channel1, 250, SampleFormat.Format32BitIeeeFloat); //从浮点数组创建一个新的信号
signal = S1.ToComplex(); //将此信号转换为ComplexSignal信号
signal.ForwardFourierTransform(); //对ComplexSignal信号应用前向快速傅立叶变换
// Now we can get the power spectrum output and its
// related frequency vector to plot our spectrometer.
Complex[] channel = signal.GetChannel(0); //从信号中提取通道
double[] power = Accord.Audio.Tools.GetPowerSpectrum(channel); //计算复杂信号的功率谱
double[] freqv = Accord.Audio.Tools.GetFrequencyVector(signal.Length, signal.SampleRate); //创建均匀间隔的频率向量（假设对称FFT）
power[0] = 0; // zero DC
float[] g = new float[power.Length];
for (int i = 0; i < power.Length; i++)
{
g[i] = (float)power[i];
signal1[i] = g[i] * 1000;
SetpowerCC(g[i]); //输出power的值
SetFrequCC(freqv[i]); //输出freqv的值
}
powerCaculate(); //对小于20hz的部分求和
pictureBox2.Refresh(); //重新绘制Channel1频域图
}
/// <summary> /// Processes the filter. /// </summary> /// protected abstract void ProcessFilter(ComplexSignal sourceData, ComplexSignal destinationData);
/// <summary>
/// Splits a signal using the window.
/// </summary>
///
public virtual ComplexSignal Apply(ComplexSignal complexSignal, int sampleIndex)
{
Complex[,] resultData = new Complex[Length, complexSignal.Channels];
ComplexSignal result = ComplexSignal.FromArray(resultData, complexSignal.SampleRate);
int channels = result.Channels;
int minLength = System.Math.Min(complexSignal.Length - sampleIndex, Length);
unsafe
{
for (int c = 0; c < complexSignal.Channels; c++)
{
Complex* dst = (Complex*)result.Data.ToPointer() + c;
Complex* src = (Complex*)complexSignal.Data.ToPointer() + c + channels * sampleIndex;
for (int i = 0; i < minLength; i++, dst += channels, src += channels)
{
*dst = window[i] * (*src);
}
}
}
return result;
}