/// <summary>
/// FFT inverse
/// </summary>
/// <param name="data">half-complex frequency series</param>
/// <returns>real time series</returns>
public static double[] Inverse(IEnumerable <double> data)
{
uint numDp = (uint)data.Count();
var trans = data.ToArray();
//buffer
var work = new real_workspace(numDp);
//real_wavetable real = new real_wavetable();
var real = new real_wavetable(numDp);
//transform
var error = halfcomplex_inverse(trans, 1, numDp, real.IntPtr, work.IntPtr);
checkError(error, nameof(Inverse));
return(trans);
}
/// <summary>
/// Example Application - low pass filtering on square wave
/// </summary>
/// <param name="dataPrinter"></param>
/// <returns></returns>
public static double[] Test_Real(Action <double[], string> dataPrinter)
{
const uint n = 101;
double[] data = new double[n];
//build time domain real data
for (int j = 0; j < n; j++)
{
data[j] = 0;
}
for (uint j = n / 3; j < 2 * n / 3; j++)
{
data[j] = 1;
}
//print data
dataPrinter?.Invoke(data, "Input");
//buffer
var work = new real_workspace(n);
//real_wavetable real = new real_wavetable();
var real = new real_wavetable(n);
//transform
var error = real_transform(data, 1, n, real.IntPtr, work.IntPtr);
checkError(error, nameof(Test_Real));
//<<---- TEST ----
//var dataC = new double[data.Length * 2];
//halfcomplex_unpack(data, dataC, 1, n);
//var z = new string[data.Length];
//for (int i = 0; i < data.Length; i++) z[i] = $"{dataC[2 * i]} + {dataC[2 * i + 1]}I";
//---- TEST ---->>
//low pass
for (int j = 11; j < n; j++)
{
data[j] = 0;
}
//<<---- TEST ----
//var dataC = new double[data.Length * 2];
//halfcomplex_unpack(data, dataC, 1, n);
//var z = new string[data.Length];
//for (int i = 0; i < data.Length; i++) z[i] = $"{dataC[2 * i]} + {dataC[2 * i + 1]}I";
//---- TEST ---->>
var hc = new halfcomplex_wavetable(n);
//inverse transform
error = halfcomplex_inverse(data, 1, n, hc.IntPtr, work.IntPtr);
checkError(error, nameof(Test_Real));
//print data
dataPrinter?.Invoke(data, "Output");
//
//work.Dispose();
return(data);
}
