private static Dataset ifft1d(final Dataset a, final int n, final int axis) {
Dataset result = null;
Dataset dest = null;
int[] shape;
PositionIterator pi;
int[] pos;
boolean[] hit;
switch (a.getDtype()) {
case Dataset.FLOAT32:
case Dataset.COMPLEX64:
FloatFFT_1D ffft = new FloatFFT_1D(n);
float[] fdata = null;
shape = a.getShape();
shape[axis] = n;
result = new ComplexFloatDataset(shape);
dest = new ComplexFloatDataset(new int[] {n});
fdata = (float[]) dest.getBuffer();
pi = a.getPositionIterator(axis);
pos = pi.getPos();
hit = pi.getOmit();
while (pi.hasNext()) {
Arrays.fill(fdata, 0.f);
a.copyItemsFromAxes(pos, hit, dest);
ffft.complexInverse(fdata, true);
result.setItemsOnAxes(pos, hit, fdata);
}
break;
case Dataset.FLOAT64:
case Dataset.COMPLEX128:
DoubleFFT_1D dfft = new DoubleFFT_1D(n);
double[] ddata = null;
shape = a.getShape();
shape[axis] = n;
result = new ComplexDoubleDataset(shape);
dest = new ComplexDoubleDataset(new int[] {n});
ddata = (double[]) dest.getBuffer();
pi = a.getPositionIterator(axis);
pos = pi.getPos();
hit = pi.getOmit();
while (pi.hasNext()) {
Arrays.fill(ddata, 0.);
a.copyItemsFromAxes(pos, hit, dest);
dfft.complexInverse(ddata, true);
result.setItemsOnAxes(pos, hit, ddata);
}
break;
default:
logger.warn("Non-float dataset not yet supported");
break;
}
return result;
}
private void calculate() {
float[] samples = getSamples();
Window.apply(mWindow, samples);
if (mSampleType == SampleType.REAL) {
mFFT.realForward(samples);
} else {
mFFT.complexForward(samples);
}
dispatch(samples);
}
public static void coupe100(AudioSignal input) {
int fs = input.samplingRate;
int N = input.getLength();
float[] Y = Arrays.copyOf(input.data, 2 * N);
FloatFFT_1D fft = new FloatFFT_1D(N);
fft.realForwardFull(Y);
int threshold = 100 * 2;
Arrays.fill(Y, 0, Math.round(threshold * (float) N / fs), 0);
Arrays.fill(Y, Math.round(2 * N - threshold * (float) N / fs), 2 * N - 1, 0);
fft.complexInverse(Y, true);
for (int i = 0; i < N; i++) {
input.data[i] = Y[2 * i];
}
}
public static List<float[]> deconvol(float[] signal, int fs, int fenetre, int n0) {
int nbfram = signal.length;
int frameparfenetre = Math.round(fs * (float) fenetre / 1000);
int recoupframe = Math.round(frameparfenetre / 2);
float[] hamming = new float[frameparfenetre];
for (int i = 0; i < frameparfenetre; i++) {
hamming[i] = (float) (0.54 - 0.46 * Math.cos(2 * Math.PI * i / (frameparfenetre - 1)));
}
int fftsize = (int) Math.pow(2, Math.ceil(log2(frameparfenetre)));
List<float[]> result = new ArrayList<>();
int end = nbfram - frameparfenetre;
for (int i = 0; i < end; i += frameparfenetre - recoupframe) {
int to = Math.min(i + frameparfenetre - 1, end);
float[] sfen = new float[to - i + 1];
System.arraycopy(signal, i, sfen, 0, sfen.length);
sfen = accentue(sfen);
for (int j = 0; j < sfen.length; j++) {
sfen[j] = sfen[j] * hamming[j];
}
FloatFFT_1D fft = new FloatFFT_1D(sfen.length);
fft.realForward(sfen);
for (int j = 0; j < sfen.length; j++) {
sfen[j] = (float) Math.log(Math.abs(sfen[j]));
}
fft.realInverse(sfen, true);
Arrays.fill(sfen, n0 + 1, sfen.length - 1, 0);
fft.realForward(sfen);
for (int j = 0; j < sfen.length; j++) {
sfen[j] = (float) Math.abs(Math.exp(sfen[j]));
}
result.add(Arrays.copyOfRange(sfen, 2, Math.round(fftsize / 2) - 1));
}
return result;
}
private void processRecordedData() {
mIsProcessing = true;
float[] recordedDataFFT;
recordedDataFFT = FrequencyDetector.convertToFloats(mRecordedData);
fft.realForward(recordedDataFFT);
float[] halfAbsFFT;
halfAbsFFT = FrequencyDetector.absAndHalve(recordedDataFFT);
int[] peaks;
peaks = FrequencyDetector.identifyPeaksAndRemove(halfAbsFFT);
String peakString = "";
for (int e : peaks) peakString += e + " ";
Log.d(TAG, peakString);
int frequency = FrequencyDetector.detectFrequency(peaks);
if (frequency != -1) this.updateStrings(frequency);
mIsProcessing = false;
}