private void ComputeAndClassify(double[] arr)
{
double[] magnitudes;
for (int i = 0; i < realIn.Length; i++)
{
realIn[i] = arr[i];
}
Console.WriteLine("FFT");
fft.Execute();
magnitudes = new double[comOut.Length];
for (int i = 0; i < 4000; i++)
{
magnitudes[i] = 10 * Math.Log10((comOut[i].Magnitude / bufferSize) * (comOut[i].Magnitude / bufferSize));
if (10 * Math.Log10((comOut[i].Magnitude / bufferSize) * (comOut[i].Magnitude / bufferSize)) > 40)
{
//Console.WriteLine("Bin: " + i * sampleRate / comOut.Length + " " + 10 * Math.Log10((comOut[i].Magnitude / bufferSize) * (comOut[i].Magnitude / bufferSize)));
}
}
DataSample sample = new DataSample(magnitudes);
Console.WriteLine("Classification");
network.DataClassification(sample);
}
static double[] FFT(WaveFileObject obj, PinnedArray <double> pin, FftwArrayComplex com, FftwPlanRC fft)
{
Console.WriteLine("FFT");
double[] magnitudes;
Console.WriteLine(obj.soundData.Count);
double[] input = new double[obj.soundData.Count + 20286];
Array.Clear(input, 0, input.Length);
obj.soundData.CopyTo(input, 0);
switch (obj.header.channels)
{
case 1:
for (int i = 0; i < pin.Length; i++)
{
pin[i] = input[i];
//Console.Write(pin[i] + " : ");
}
break;
case 2:
for (int i = 0; i < pin.Length; i++)
{
pin[i] = input[i + i];
//Console.WriteLine(pin[i]);
}
break;
default:
break;
}
fft.Execute();
magnitudes = new double[com.Length];
for (int i = 0; i < 4000; i++)
{
magnitudes[i] = 10 * Math.Log10((com[i].Magnitude / inputSize) * (com[i].Magnitude / inputSize));
/*
* if (10 * Math.Log10((com[i].Magnitude / inputSize) * (com[i].Magnitude / inputSize)) > 10)
* {
* Console.WriteLine("Bin: " + i * sampleRate / com.Length + " " + 10 * Math.Log10((com[i].Magnitude / inputSize) * (com[i].Magnitude / inputSize)));
* }
*/
}
Console.WriteLine(com.Length);
Console.WriteLine();
Console.WriteLine("Returning magnitudes");
return(magnitudes);
}