//called when data for any output pin is requested
public void Evaluate(int SpreadMax)
{
if(!Buffer.IsChanged) return;
int BinSize = Buffer.SliceCount;
double[] freqReal, freqImag;
double[] dataReal = new double[Buffer.SliceCount];
for (int i=0; i<BinSize; i++ ) {
dataReal[i] = Buffer[i];
}
RealFourierTransformation rft = new RealFourierTransformation(); // default convention
rft.TransformForward(dataReal, out freqReal, out freqImag);
FOutput.SliceCount = freqReal.Length;
FOutput.AssignFrom(freqReal);
FOutput2.SliceCount = freqImag.Length;
FOutput2.AssignFrom(freqImag);
FOut.SliceCount = FMag.SliceCount = BinSize/2;
for (int i=1; i <= BinSize/2; i++) {
FMag[i-1] = Math.Sqrt(freqReal[i] * freqReal[i] + freqImag[i] * freqImag[i]);
FOut[i-1] = i * Samplerate[0] / (double) BinSize;
}
}
public void TestWhiteGaussianNoiseIsWhite()
{
for(int z = 0; z < 10; z++) // run test 10 times to be sure
{
IChannelSource source = new WhiteGaussianNoiseSource();
double[] signal = new double[signalLength];
double signalPower = 0d;
for(int i = 0; i < signal.Length; i++)
{
signal[i] = source.ReadNextSample();
signalPower += signal[i] * signal[i];
}
signalPower /= signalLength;
Assert.Less(signalPower, 1.1, "signal power must be less than 1.1");
Assert.Greater(signalPower, 0.9, "signal power must be greater than 0.9");
double[] freqReal, freqImag;
RealFourierTransformation fft = new RealFourierTransformation();
fft.TransformForward(signal, out freqReal, out freqImag);
double spectralPower = 0d;
double[] spectralGroupPower = new double[groupCount];
for(int i = 0, j = 0; i < spectralGroupPower.Length; i++, j += groupLength)
{
double sum = 0d;
for(int k = 0; k < groupLength; k++)
{
double real = freqReal[j + k];
double imag = freqImag[j + k];
sum += real * real + imag * imag;
}
spectralGroupPower[i] = sum / (2 * groupLength);
spectralPower += sum;
Assert.Less(spectralGroupPower[i], 1.4, "spectral power must be less than 1.4 for each group");
Assert.Greater(spectralGroupPower[i], 0.6, "spectral power must be greater than 0.6 for each group");
}
spectralPower /= (2 * signalLength);
Assert.AreEqual(signalPower, spectralPower, 0.0001, "Signal and spectral power must match.");
}
}
public void SetUp()
{
cft = new ComplexFourierTransformation();
rft = new RealFourierTransformation();
}
public void SetUp()
{
_fft = new RealFourierTransformation();
_fft.Convention = TransformationConvention.Default;
}
/// <summary>
/// Construct an FFT with default parameter values
/// </summary>
public FFT()
{
this.fft = new RealFourierTransformation(TransformationConvention.Matlab);
this.SetParametersToDefaultValues();
}
/// <summary>
/// A static transformation method. The length is the nearest power of two that is not greater than the input length.
/// Returns the full result.
/// </summary>
public static IArrayView<double> TransformRaw(IArrayView<double> input, FFTOutputType outputType = FFTOutputType.Power, WindowType windowType = WindowType.Rectangular)
{
int count = input.Count.NearestPowerOfTwo(false);
var fft = new RealFourierTransformation();
double[] window = windowType.Apply(input.Take(count), count).ToArray(), real, imag;
fft.TransformForward(window, out real, out imag);
if (outputType == FFTOutputType.Imaginary)
return imag.AsIArray();
if (outputType == FFTOutputType.Power)
for (int i = 0; i < real.Length; i++)
real[i] = Math.Sqrt(real[i] * real[i] + imag[i] * imag[i]);
return real.AsIArray();
}
