static void ExampleUsePlanDirectly()
{
// Use the same arrays for as many transformations as you like.
// If you can use the same arrays for your transformations, this is faster than calling DFT.FFT / DFT.IFFT
using (var timeDomain = new FftwArrayComplex(253))
using (var frequencyDomain = new FftwArrayComplex(timeDomain.GetSize()))
using (var fft = FftwPlanC2C.Create(timeDomain, frequencyDomain, DftDirection.Forwards))
using (var ifft = FftwPlanC2C.Create(frequencyDomain, timeDomain, DftDirection.Backwards))
{
// Set the input after the plan was created as the input may be overwritten
// during planning
for (int i = 0; i < timeDomain.Length; i++)
{
timeDomain[i] = i % 10;
}
// timeDomain -> frequencyDomain
fft.Execute();
for (int i = frequencyDomain.Length / 2; i < frequencyDomain.Length; i++)
{
frequencyDomain[i] = 0;
}
// frequencyDomain -> timeDomain
ifft.Execute();
// Do as many forwards and backwards transformations here as you like
}
}
public static void SetupPlan(int numDpTime)
{
DFT.Wisdom.Import("wisdom.txt");
mTimeBuffer = new FftwArrayComplex(numDpTime);
mFreqBuffer = new FftwArrayComplex(numDpTime);
mPlanFore = FftwPlanC2C.Create(mTimeBuffer, mFreqBuffer, DftDirection.Forwards, PlannerFlags.Measure);
mPlanBack = FftwPlanC2C.Create(mFreqBuffer, mTimeBuffer, DftDirection.Backwards, PlannerFlags.Measure);
}
private static string ProcessMessage(string s, PinnedArray <double> pin, FftwArrayComplex com, FftwPlanRC fft)
{
//Deserialize and then FFTW then return datasample as json string
WFOTransporter wav = JsonConvert.DeserializeObject <WFOTransporter>(s);
WaveFileObject obj = new WaveFileObject(wav);
DataSample sample = new DataSample(FFT(obj, pin, com, fft));
string json = JsonConvert.SerializeObject(sample);
return(json);
}
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);
}
static double calcFreqEnergy(FftwArrayComplex data, int rate)
{
// T a0^2 + T/2 Σcn^2 [n=1~N]
// = T/2(2*a0^2 + Σcn^2)
var len = data.Length;
var T = len / rate;
var energy = (data[0].Magnitude * data[0].Magnitude) * 2; //2*a0^2
for (int i = 1; i < len; i++)
{
energy += data[i].Magnitude * data[i].Magnitude; //Σcn^2
}
energy *= T / 2.0; // T/2
return(energy);
}
public AudioIn(int sampleRate, int device, int bufferSize)
{
if (device > WaveIn.DeviceCount)
{
throw new Exception();
}
this.sampleRate = sampleRate;
this.bufferSize = bufferSize;
audioDataTrue = new short[bufferSize + 20286];
tempOdd = new double[audioDataTrue.Length];
tempTrue = new double[audioDataTrue.Length];
realIn = new PinnedArray <double>(audioDataTrue.Length);
comOut = new FftwArrayComplex(DFT.GetComplexBufferSize(realIn.GetSize()));
fft = FftwPlanRC.Create(realIn, comOut, DftDirection.Forwards);
waveInDevices = WaveIn.DeviceCount;
waveEvent = new WaveInEvent();
waveEvent.DeviceNumber = device;
waveEvent.DataAvailable += OnWaveIn;
channels = WaveIn.GetCapabilities(device).Channels;
waveEvent.WaveFormat = new WaveFormat(sampleRate, 1);
string path = Path.GetDirectoryName(Assembly.GetEntryAssembly().Location) + "/NetworkSave01.json";
// Load Neural network
if (File.Exists(path))
{
Console.WriteLine("exists");
network = NeuralNetwork.LoadNetwork(path);
}
else
{
throw new FileNotFoundException();
}
//network.PrintWeights();
waveEvent.StartRecording();
}
static void Main(string[] args)
{
try
{
TcpClient tcpClient = new TcpClient("127.0.0.1", 10000);
Console.WriteLine("Connected");
StreamReader reader = new StreamReader(tcpClient.GetStream());
StreamWriter writer = new StreamWriter(tcpClient.GetStream());
string s = "";
using (var timeDomain = new PinnedArray <double>(inputSize))
using (var frequencyDomain = new FftwArrayComplex(DFT.GetComplexBufferSize(timeDomain.GetSize())))
using (var fft = FftwPlanRC.Create(timeDomain, frequencyDomain, DftDirection.Forwards))
{
while (!(s = reader.ReadLine()).Equals("Quit") || (s == null))
{
string result = "";
if (IsValidJson(s))
{
result = ProcessMessage(s, timeDomain, frequencyDomain, fft);
}
writer.WriteLine(result);
writer.Flush();
GC.Collect();
}
reader.Close();
writer.Close();
tcpClient.Close();
}
}
catch (Exception e)
{
Console.WriteLine(e);
Console.WriteLine(e.InnerException);
Console.WriteLine(e.Message);
throw;
}
}
static void ExampleR2C()
{
double[] input = new double[97];
var rand = new Random();
for (int i = 0; i < input.Length; i++)
{
input[i] = rand.NextDouble();
}
using (var pinIn = new PinnedArray <double>(input))
using (var output = new FftwArrayComplex(DFT.GetComplexBufferSize(pinIn.GetSize())))
{
DFT.FFT(pinIn, output);
for (int i = 0; i < output.Length; i++)
{
Console.WriteLine(output[i]);
}
}
}
