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/*
* _______ _____ _____ _____
* |__ __| | __ \ / ____| __ \
* | | __ _ _ __ ___ ___ ___| | | | (___ | |__) |
* | |/ _` | '__/ __|/ _ \/ __| | | |\___ \| ___/
* | | (_| | | \__ \ (_) \__ \ |__| |____) | |
* |_|\__,_|_| |___/\___/|___/_____/|_____/|_|
*
* -------------------------------------------------------------
*
* TarsosDSP is developed by Joren Six at IPEM, University Ghent
*
* -------------------------------------------------------------
*
* Info: http://0110.be/tag/TarsosDSP
* Github: https://github.com/JorenSix/TarsosDSP
* Releases: http://0110.be/releases/TarsosDSP/
*
* TarsosDSP includes modified source code by various authors,
* for credits and info, see README.
*
*/
/*
* _______ _____ _____ _____
* |__ __| | __ \ / ____| __ \
* | | __ _ _ __ ___ ___ ___| | | | (___ | |__) |
* | |/ _` | '__/ __|/ _ \/ __| | | |\___ \| ___/
* | | (_| | | \__ \ (_) \__ \ |__| |____) | |
* |_|\__,_|_| |___/\___/|___/_____/|_____/|_|
*
* -----------------------------------------------------------
*
* TarsosDSP is developed by Joren Six at
* The Royal Academy of Fine Arts & Royal Conservatory,
* University College Ghent,
* Hoogpoort 64, 9000 Ghent - Belgium
*
* http://tarsos.0110.be/tag/TarsosDSP
* https://github.com/JorenSix/TarsosDSP
* http://tarsos.0110.be/releases/TarsosDSP/
*
*/
/*
* Copyright (c) 2006, Karl Helgason
*
* 2007/1/8 modified by p.j.leonard
*
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* 1. Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* 2. Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials
* provided with the distribution.
* 3. The name of the author may not be used to endorse or promote
* products derived from this software without specific prior
* written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
* IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
* WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
* ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY
* DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
* DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE
* GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
* INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
* IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
* OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN
* IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
*/
package be.tarsos.dsp;
import be.tarsos.dsp.util.fft.FFT;
/**
* Implementation of the Constant Q Transform.
References:
*
* Judith C. Brown,
* Calculation of a constant Q spectral transform, J. Acoust. Soc. Am.,
* 89(1): 425-434, 1991.
*
*
* Judith C. Brown and Miller S. Puckette, An efficient algorithm for the calculation of a constant Q transform, J.
* Acoust. Soc. Am., Vol. 92, No. 5, November 1992
*
*
* Benjamin Blankertz, The Constant Q Transform
*
*
*
* @author Joren Six
* @author Karl Helgason
* @author P.J Leonard
*/
public class ConstantQ implements AudioProcessor {
/**
* The minimum frequency, in Hertz. The Constant-Q factors are calculated
* starting from this frequency.
*/
private final float minimumFrequency ;
/**
* The maximum frequency in Hertz.
*/
private final float maximumFreqency;
/**
* The length of the underlying FFT.
*/
private int fftLength;
/**
* Lists the start of each frequency bin, in Hertz.
*/
private final float[] frequencies;
private final float[][] qKernel;
private final int[][] qKernel_indexes;
/**
* The array with constant q coefficients. If you for
* example are interested in coefficients between 256 and 1024 Hz
* (2^8 and 2^10 Hz) and you requested 12 bins per octave, you
* will need 12 bins/octave * 2 octaves * 2 entries/bin = 48
* places in the output buffer. The coefficient needs two entries
* in the output buffer since they are complex numbers.
*/
private final float[] coefficients;
/**
* The output buffer with constant q magnitudes. If you for example are
* interested in coefficients between 256 and 1024 Hz (2^8 and 2^10 Hz) and
* you requested 12 bins per octave, you will need 12 bins/octave * 2
* octaves = 24 places in the output buffer.
*/
private final float[] magnitudes;
/**
* The number of bins per octave.
*/
private int binsPerOctave;
/**
* The underlying FFT object.
*/
private FFT fft;
public ConstantQ(float sampleRate, float minFreq, float maxFreq,float binsPerOctave) {
this(sampleRate,minFreq,maxFreq,binsPerOctave,0.001f,1.0f);
}
public ConstantQ(float sampleRate, float minFreq, float maxFreq,float binsPerOctave, float threshold,float spread) {
this.minimumFrequency = minFreq;
this.maximumFreqency = maxFreq;
this.binsPerOctave = (int) binsPerOctave;
// Calculate Constant Q
double q = 1.0 / (Math.pow(2, 1.0 / binsPerOctave) - 1.0) / spread;
// Calculate number of output bins
int numberOfBins = (int) Math.ceil(binsPerOctave * Math.log(maximumFreqency / minimumFrequency) / Math.log(2));
// Initialize the coefficients array (complex number so 2 x number of bins)
coefficients = new float[numberOfBins*2];
// Initialize the magnitudes array
magnitudes = new float[numberOfBins];
// Calculate the minimum length of the FFT to support the minimum
// frequency
float calc_fftlen = (float) Math.ceil(q * sampleRate / minimumFrequency);
// No need to use power of 2 FFT length.
fftLength = (int) calc_fftlen;
//System.out.println(fftLength);
//The FFT length needs to be a power of two for performance reasons:
fftLength = (int) Math.pow(2, Math.ceil(Math.log(calc_fftlen) / Math.log(2)));
// Create FFT object
fft = new FFT(fftLength);
qKernel = new float[numberOfBins][];
qKernel_indexes = new int[numberOfBins][];
frequencies = new float[numberOfBins];
// Calculate Constant Q kernels
float[] temp = new float[fftLength*2];
float[] ctemp = new float[fftLength*2];
int[] cindexes = new int[fftLength];
for (int i = 0; i < numberOfBins; i++) {
float[] sKernel = temp;
// Calculate the frequency of current bin
frequencies[i] = (float) (minimumFrequency * Math.pow(2, i/binsPerOctave ));
// Calculate length of window
int len = (int)Math.min(Math.ceil( q * sampleRate / frequencies[i]), fftLength);
for (int j = 0; j < len; j++) {
double window = -.5*Math.cos(2.*Math.PI*(double)j/(double)len)+.5;; // Hanning Window
// double window = -.46*Math.cos(2.*Math.PI*(double)j/(double)len)+.54; // Hamming Window
window /= len;
// Calculate kernel
double x = 2*Math.PI * q * (double)j/(double)len;
sKernel[j*2] = (float) (window * Math.cos(x));
sKernel[j*2+1] = (float) (window * Math.sin(x));
}
for (int j = len*2; j < fftLength*2; j++) {
sKernel[j] = 0;
}
// Perform FFT on kernel
fft.complexForwardTransform(sKernel);
// Remove all zeros from kernel to improve performance
float[] cKernel = ctemp;
int k = 0;
for (int j = 0, j2 = sKernel.length - 2; j < sKernel.length/2; j+=2,j2-=2)
{
double absval = Math.sqrt(sKernel[j]*sKernel[j] + sKernel[j+1]*sKernel[j+1]);
absval += Math.sqrt(sKernel[j2]*sKernel[j2] + sKernel[j2+1]*sKernel[j2+1]);
if(absval > threshold)
{
cindexes[k] = j;
cKernel[2*k] = sKernel[j] + sKernel[j2];
cKernel[2*k + 1] = sKernel[j + 1] + sKernel[j2 + 1];
k++;
}
}
sKernel = new float[k * 2];
int[] indexes = new int[k];
for (int j = 0; j < k * 2; j++)
sKernel[j] = cKernel[j];
for (int j = 0; j < k; j++)
indexes[j] = cindexes[j];
// Normalize fft output
for (int j = 0; j < sKernel.length; j++)
sKernel[j] /= fftLength;
// Perform complex conjugate on sKernel
for (int j = 1; j < sKernel.length; j += 2)
sKernel[j] = -sKernel[j];
for (int j = 0; j < sKernel.length; j ++)
sKernel[j] = -sKernel[j];
qKernel_indexes[i] = indexes;
qKernel[i] = sKernel;
}
}
/**
* Take an input buffer with audio and calculate the constant Q
* coefficients.
*
* @param inputBuffer
* The input buffer with audio.
*
*
*/
public void calculate(float[] inputBuffer) {
fft.forwardTransform(inputBuffer);
for (int i = 0; i < qKernel.length; i++) {
float[] kernel = qKernel[i];
int[] indexes = qKernel_indexes[i];
float t_r = 0;
float t_i = 0;
for (int j = 0, l = 0; j < kernel.length; j += 2, l++) {
int jj = indexes[l];
float b_r = inputBuffer[jj];
float b_i = inputBuffer[jj + 1];
float k_r = kernel[j];
float k_i = kernel[j + 1];
// COMPLEX: T += B * K
t_r += b_r * k_r - b_i * k_i;
t_i += b_r * k_i + b_i * k_r;
}
coefficients[i * 2] = t_r;
coefficients[i * 2 + 1] = t_i;
}
}
/**
* Take an input buffer with audio and calculate the constant Q magnitudes.
* @param inputBuffer The input buffer with audio.
*/
public void calculateMagintudes(float[] inputBuffer) {
calculate(inputBuffer);
for(int i = 0 ; i < magnitudes.length ; i++){
magnitudes[i] = (float) Math.sqrt(coefficients[i*2] * coefficients[i*2] + coefficients[i*2+1] * coefficients[i*2+1]);
}
}
@Override
public boolean process(AudioEvent audioEvent) {
float[] audioBuffer = audioEvent.getFloatBuffer().clone();
if(audioBuffer.length != getFFTlength()){
throw new IllegalArgumentException(String.format("The length of the fft (%d) should be the same as the length of the audio buffer (%d)",getFFTlength(),audioBuffer.length));
}
calculateMagintudes(audioBuffer);
return true;
}
@Override
public void processingFinished() {
// Do nothing.
}
//----GETTERS
/**
* @return The list of starting frequencies for each band. In Hertz.
*/
public float[] getFreqencies() {
return frequencies;
}
/**
* Returns the Constant Q magnitudes calculated for the previous audio
* buffer. Beware: the array is reused for performance reasons. If your need
* to cache your results, please copy the array.
* @return The output buffer with constant q magnitudes. If you for example are
* interested in coefficients between 256 and 1024 Hz (2^8 and 2^10 Hz) and
* you requested 12 bins per octave, you will need 12 bins/octave * 2
* octaves = 24 places in the output buffer.
*/
public float[] getMagnitudes() {
return magnitudes;
}
/**
* Return the Constant Q coefficients calculated for the previous audio
* buffer. Beware: the array is reused for performance reasons. If your need
* to cache your results, please copy the array.
*
* @return The array with constant q coefficients. If you for example are
* interested in coefficients between 256 and 1024 Hz (2^8 and 2^10
* Hz) and you requested 12 bins per octave, you will need 12
* bins/octave * 2 octaves * 2 entries/bin = 48 places in the output
* buffer. The coefficient needs two entries in the output buffer
* since they are complex numbers.
*/
public float[] getCoefficients() {
return coefficients;
}
/**
* @return The number of coefficients, output bands.
*/
public int getNumberOfOutputBands() {
return frequencies.length;
}
/**
* @return The required length the FFT.
*/
public int getFFTlength() {
return fftLength;
}
/**
* @return the number of bins every octave.
*/
public int getBinsPerOctave(){
return binsPerOctave;
}
}