void Update()
{
// Real-time
if (realTimeSamples)
{
audioSource.GetSpectrumData(realTimeSpectrum, 0, FFTWindow.BlackmanHarris);
realTimeSpectralFluxAnalyzer.analyzeSpectrum(realTimeSpectrum, audioSource.time);
realTimePlotController.updatePlot(realTimeSpectralFluxAnalyzer.spectralFluxSamples);
}
// Preprocessed
if (preProcessSamples)
{
int indexToPlot = getIndexFromTime(audioSource.time) / 1024;
preProcessedPlotController.updatePlot(preProcessedSpectralFluxAnalyzer.spectralFluxSamples, indexToPlot);
}
/* START MY SHITTY ADDON */
if (backgroundThreadCompleted == true && threeDimensionalSpectrumBuild == false)
{
Debug.Log("calling spectrumBoy to build the thing!");
threeDimensionalSpectrumBuild = true;
Debug.Log(string.Format("threeDimensionalSpectrumBuild = ", threeDimensionalSpectrumBuild));
spectrumBoy.buildSpectrumGraph();
}
if (backgroundThreadCompleted == true && threeDimensionalSpectrumBuild == true)
{
spectrumBoy.updateSpectrumGraph(audioSource.time);
spectrumRealTime.updateRealTimeSpectrumGraph();
}
/* END MY SHITTY ADDON */
}
void Update()
{
// Real-time
if (realTimeSamples && !GetComponent <AudioManipulation>().pausePressed)
{
audioSource.GetSpectrumData(realTimeSpectrum, 0, FFTWindow.BlackmanHarris);
realTimeSpectralFluxAnalyzer.analyzeSpectrum(realTimeSpectrum, audioSource.time);
realTimePlotController.updatePlot(realTimeSpectralFluxAnalyzer.spectralFluxSamples);
}
// Preprocessed
if (preProcessSamples && !GetComponent <AudioManipulation>().pausePressed)
{
int indexToPlot = getIndexFromTime(audioSource.time) / 1024;
preProcessedPlotController.updatePlot(preProcessedSpectralFluxAnalyzer.spectralFluxSamples, indexToPlot);
}
}
void Update()
{
// Real-time
if (realTimeSamples)
{
audioSource.GetSpectrumData(realTimeSpectrum, 0, FFTWindow.BlackmanHarris);
realTimeSpectralFluxAnalyzer.analyzeSpectrum(realTimeSpectrum, audioSource.time);
realTimePlotController.updatePlot(realTimeSpectralFluxAnalyzer.spectralFluxSamples);
}
// Preprocessed
if (preProcessSamples)
{
int indexToPlot = getIndexFromTime(audioSource.time) / 4096;
preProcessedPlotController.updatePlot(preProcessedSpectralFluxAnalyzer.spectralFluxSamples, indexToPlot);
}
}
private void GetSpectrumData(float[] samples)
{
try{
float[] preProcessedSamples = GetOutputData(samples);
Debug.Log("Combine Channels done");
Debug.Log(preProcessedSamples.Length);
// Once we have our audio sample data prepared, we can execute an FFT to return the spectrum data over the time domain
int spectrumSampleSize = 1024;
int iterations = preProcessedSamples.Length / spectrumSampleSize;
FFT fft = new FFT();
fft.Initialize((UInt32)spectrumSampleSize);
Debug.Log(string.Format("Processing {0} time domain samples for FFT", iterations));
double[] sampleChunk = new double[spectrumSampleSize];
for (int i = 0; i < iterations; i++)
{
// Grab the current 1024 chunk of audio sample data
Array.Copy(preProcessedSamples, i * spectrumSampleSize, sampleChunk, 0, spectrumSampleSize);
// Apply our chosen FFT Window
double[] windowCoefs = DSP.Window.Coefficients(DSP.Window.Type.Hanning, (uint)spectrumSampleSize);
double[] scaledSpectrumChunk = DSP.Math.Multiply(sampleChunk, windowCoefs);
double scaleFactor = DSP.Window.ScaleFactor.Signal(windowCoefs);
// Perform the FFT and convert output (complex numbers) to Magnitude
Complex[] fftSpectrum = fft.Execute(scaledSpectrumChunk);
double[] scaledFFTSpectrum = DSPLib.DSP.ConvertComplex.ToMagnitude(fftSpectrum);
scaledFFTSpectrum = DSP.Math.Multiply(scaledFFTSpectrum, scaleFactor);
// These 1024 magnitude values correspond (roughly) to a single point in the audio timeline
float curSongTime = getTimeFromIndex(i) * spectrumSampleSize;
// Send our magnitude data off to our Spectral Flux Analyzer to be analyzed for peaks
preProcessedSpectralFluxAnalyzer.analyzeSpectrum(Array.ConvertAll(scaledFFTSpectrum, x => (float)x), curSongTime);
Debug.Log("Spectrum Analysis done");
Debug.Log("Background Thread Completed");
}
} catch (Exception e) {
Debug.Log(e.ToString());
}
}
public void getFullSpectrumThreaded(Action <float> callback)
{
try
{
// We only need to retain the samples for combined channels over the time domain
float[] preProcessedSamples = new float[this._numTotalSamples];
int numProcessed = 0;
float combinedChannelAverage = 0f;
for (int i = 0; i < _multiChannelSamples.Length; i++)
{
combinedChannelAverage += _multiChannelSamples[i];
// Each time we have processed all channels samples for a point in time, we will store the average of the channels combined
if ((i + 1) % this._numChannels == 0)
{
preProcessedSamples[numProcessed] = combinedChannelAverage / this._numChannels;
numProcessed++;
combinedChannelAverage = 0f;
}
}
//Debug.Log("Combine Channels done");
//Debug.Log(preProcessedSamples.Length);
// Once we have our audio sample data prepared, we can execute an FFT to return the spectrum data over the time domain
int spectrumSampleSize = 1024;
int iterations = preProcessedSamples.Length / spectrumSampleSize;
FFT fft = new FFT();
fft.Initialize((UInt32)spectrumSampleSize);
//Debug.Log(string.Format("Processing {0} time domain samples for FFT", iterations));
double[] sampleChunk = new double[spectrumSampleSize];
for (int i = 0; i < iterations; i++)
{
// Grab the current 1024 chunk of audio sample data
Array.Copy(preProcessedSamples, i * spectrumSampleSize, sampleChunk, 0, spectrumSampleSize);
// Apply our chosen FFT Window
double[] windowCoefs = DSP.Window.Coefficients(DSP.Window.Type.Hanning, (uint)spectrumSampleSize);
double[] scaledSpectrumChunk = DSP.Math.Multiply(sampleChunk, windowCoefs);
double scaleFactor = DSP.Window.ScaleFactor.Signal(windowCoefs);
// Perform the FFT and convert output (complex numbers) to Magnitude
Complex[] fftSpectrum = fft.Execute(scaledSpectrumChunk);
double[] scaledFFTSpectrum = DSPLib.DSP.ConvertComplex.ToMagnitude(fftSpectrum);
scaledFFTSpectrum = DSP.Math.Multiply(scaledFFTSpectrum, scaleFactor);
// These 1024 magnitude values correspond (roughly) to a single point in the audio timeline
float curSongTime = getTimeFromIndex(i) * spectrumSampleSize;
// Send our magnitude data off to our Spectral Flux Analyzer to be analyzed for peaks
_preProcessedSpectralFluxAnalyzer.analyzeSpectrum(Array.ConvertAll(scaledFFTSpectrum, x => (float)x), curSongTime);
callback((i * 100) / iterations);
}
callback(100);
//Debug.Log("Spectrum Analysis done");
//Debug.Log("Background Thread Completed");
_loadComplete = true;
}
catch (Exception e)
{
// Catch exceptions here since the background thread won't always surface the exception to the main thread
Debug.Log(e.ToString());
}
}
void AnalyzeAudio()
{
if (soundFile)
{
//The array for the averaged sample data. (L,R,L,R,L,R are averaged into (L+R)/2, (L+R)/2, (L+R)/2)
float[] preprocessedSamples = new float[numSamples];
int numberOfSamplesProcessed = 0;
float combinedChannelAverage = 0f;
Debug.Log("Starting sample processing...");
for (int i = 0; i < allChannelsSamples.Length; i++)
{
combinedChannelAverage += allChannelsSamples[i];
//for(int j = 0; j < numChannels; j++)
//{
// combinedChannelAverage += allChannelsSamples[i + j];
// numberOfSamplesProcessed++;
//}
//preprecessedSamples[i/numChannels] = combinedChannelAverage / (float)numChannels;
//combinedChannelAverage = 0;
// Each time we have processed all channels samples for a point in time, we will store the average of the channels combined
if ((i + 1) % numChannels == 0)
{
preprocessedSamples[numberOfSamplesProcessed] = combinedChannelAverage / numChannels;
numberOfSamplesProcessed++;
combinedChannelAverage = 0f;
}
}
int specSampSize = 1024;
int iterations = preprocessedSamples.Length / specSampSize;
double[] sampleChunk = new double[specSampSize];
//LomFFT fft = new LomFFT();
FFT fft = new FFT();
fft.Initialize((System.UInt32)specSampSize);
SpectralFluxAnalyzer preproAnalyzer = new SpectralFluxAnalyzer();
for (int i = 0; i < iterations; ++i)
{
System.Array.Copy(preprocessedSamples, i * specSampSize, sampleChunk, 0, specSampSize);
double[] windowCoefs = DSP.Window.Coefficients(DSP.Window.Type.Hanning, (uint)specSampSize);
double[] scaledSpectrumChunk = DSP.Math.Multiply(sampleChunk, windowCoefs);
double scaleFactor = DSP.Window.ScaleFactor.Signal(windowCoefs);
// Perform the FFT and convert output (complex numbers) to Magnitude
System.Numerics.Complex[] fftSpectrum = fft.Execute(scaledSpectrumChunk);
double[] scaledFFTSpectrum = DSP.ConvertComplex.ToMagnitude(fftSpectrum);
scaledFFTSpectrum = DSP.Math.Multiply(scaledFFTSpectrum, scaleFactor);
//old
//fft.FFT(sampleChunk);
float currTime = getTimeFromIndex(i) * specSampSize;
preproAnalyzer.analyzeSpectrum(System.Array.ConvertAll(scaledFFTSpectrum, x => (float)x), currTime); //AnalyzeSpectrum(data...);
}
//foreach(SpectralFluxAnalyzer.SpectralFluxInfo specInfo in preproAnalyzer.spectralFluxSamples)
//{
// if(specInfo.isPeak)
// {
// Debug.Log("Peak at: " + specInfo.time);
// }
//}
importantMoments = null;
importantMoments = new AnimationCurve();
freqCurve = null;
freqCurve = new AnimationCurve();
Debug.Log("Starting graph processing...");
for (int i = 0; i < preproAnalyzer.spectralFluxSamples.Count; i++)
{
if (preproAnalyzer.spectralFluxSamples[i].isPeak)
{
importantMoments.AddKey(preproAnalyzer.spectralFluxSamples[i].time, 1);
freqCurve.AddKey(preproAnalyzer.spectralFluxSamples[i].time, preproAnalyzer.spectralFluxSamples[i].spectralFlux);
}
}
Debug.Log("Done!");
Debug.Log(numberOfSamplesProcessed);
//AudioListener.GetSpectrumData(spectrums, 0, FFTWindow.BlackmanHarris);
//Debug.Log(AudioSettings.outputSampleRate);
}
}
public void getFullSpectrumThreaded() //not used. from https://medium.com/giant-scam/algorithmic-beat-mapping-in-unity-preprocessed-audio-analysis-d41c339c135a . //I find it well visualised, but overly sensitive (doesnt seem to target lower freq, which it should).
{
try {
// We only need to retain the samples for combined channels over the time domain
float[] preProcessedSamples = new float[this.samplesTotal]; //J- check here to see if needs doubling/halving.
int numProcessed = 0;
float combinedChannelAverage = 0f;
for (int i = 0; i < CC.Length; i++)
{
combinedChannelAverage += CC[i];
// Each time we have processed all channels samples for a point in time, we will store the average of the channels combined
if ((i + 1) % 2 == 0) //hard coding here, soz. J-
{
preProcessedSamples[numProcessed] = combinedChannelAverage / 2; //here too (the 2).
numProcessed++;
combinedChannelAverage = 0f;
}
}
Debug.Log("Combine Channels done");
Debug.Log(preProcessedSamples.Length);
// Once we have our audio sample data prepared, we can execute an FFT to return the spectrum data over the time domain
int spectrumSampleSize = 1024;
int iterations = preProcessedSamples.Length / spectrumSampleSize;
FFT fft = new FFT();
fft.Initialize((UInt32)spectrumSampleSize);
Debug.Log(string.Format("Processing {0} time domain samples for FFT", iterations));
double[] sampleChunk = new double[spectrumSampleSize];
for (int i = 0; i < iterations; i++)
{
// Grab the current 1024 chunk of audio sample data
Array.Copy(preProcessedSamples, i * spectrumSampleSize, sampleChunk, 0, spectrumSampleSize);
// Apply our chosen FFT Window
double[] windowCoefs = DSP.Window.Coefficients(DSP.Window.Type.Hanning, (uint)spectrumSampleSize);
double[] scaledSpectrumChunk = DSP.Math.Multiply(sampleChunk, windowCoefs);
double scaleFactor = DSP.Window.ScaleFactor.Signal(windowCoefs);
// Perform the FFT and convert output (complex numbers) to Magnitude
System.Numerics.Complex[] fftSpectrum = fft.Execute(scaledSpectrumChunk);
double[] scaledFFTSpectrum = DSPLib.DSP.ConvertComplex.ToMagnitude(fftSpectrum);
scaledFFTSpectrum = DSP.Math.Multiply(scaledFFTSpectrum, scaleFactor);
// These 1024 magnitude values correspond (roughly) to a single point in the audio timeline
float curSongTime = getTimeFromIndex(i) * spectrumSampleSize;
// Send our magnitude data off to our Spectral Flux Analyzer to be analyzed for peaks
preProcessedSpectralFluxAnalyzer.analyzeSpectrum(Array.ConvertAll(scaledFFTSpectrum, x => (float)x), curSongTime);
}
Debug.Log("Spectrum Analysis done");
Debug.Log("Background Thread Completed");
}
catch (Exception e) {
// Catch exceptions here since the background thread won't always surface the exception to the main thread
Debug.Log(e.ToString());
}
}//Not used currently. Copied from giant-scam. Using for reference sporadically.
void Update()
{
// Real-time
if (realTimeSamples)
{
audioSource.GetSpectrumData(realTimeSpectrum, 0, FFTWindow.BlackmanHarris);
realTimeSpectralFluxAnalyzer.analyzeSpectrum(realTimeSpectrum, audioSource.time);
realTimePlotController.updatePlot(realTimeSpectralFluxAnalyzer.spectralFluxSamples);
}
// Preprocessed
if (preProcessSamples)
{
int indexToPlot = getIndexFromTime(audioSource.time) / 1024;
// preProcessedPlotController.updatePlot (preProcessedSpectralFluxAnalyzer.spectralFluxSamples, indexToPlot);
if (songProcessed)
{
if (preProcessedSpectralFluxAnalyzer.spectralFluxSamples[indexToPlot].isPeak) // && audioSource.isPlaying)
{
if (spawnRed)
{
float highOrLow = UnityEngine.Random.Range(0f, 1f);
if (highOrLow > 0.5f)
{
redSpawnEngineLow.GetComponent <SpawnEngine>().onBeat = true;
spawnRed = false;
//Debug.Log("RED cube spawned via beat");
}
else
{
redSpawnEngineHigh.GetComponent <SpawnEngine>().onBeat = true;
spawnRed = false;
}
}
else
{
float highOrLow = UnityEngine.Random.Range(0f, 1f);
if (highOrLow > 0.5f)
{
blueSpawnEngineLow.GetComponent <SpawnEngine>().onBeat = true;
spawnRed = true;
//Debug.Log("BLUE cube spawned via beat");
}
else
{
blueSpawnEngineHigh.GetComponent <SpawnEngine>().onBeat = true;
spawnRed = false;
}
}
}
else
{
blueSpawnEngineLow.GetComponent <SpawnEngine>().onBeat = false;
redSpawnEngineLow.GetComponent <SpawnEngine>().onBeat = false;
blueSpawnEngineHigh.GetComponent <SpawnEngine>().onBeat = false;
redSpawnEngineHigh.GetComponent <SpawnEngine>().onBeat = false;
}
}
}
}