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#ifndef _FFTANALYZER
#define _FFTANALYZER
#ifndef M_PI
#define M_PI 3.14159265358979323846 /* pi */
#endif
class FFTOctaveAnalyzer {
public:
//FFT fft; // a reference to the FFT instance
float samplingRate; // sampling rate in Hz (needed to calculate frequency spans)
int nSpectrum; // number of spectrum bins in the fft
int nAverages; // number of averaging bins here
int nAveragesPerOctave; // number of averages per octave as requested by user
float spectrumFrequencySpan; // the "width" of an fft spectrum bin in Hz
float firstOctaveFrequency; // the "top" of the first averaging bin here in Hz
float averageFrequencyIncrement; // the root-of-two multiplier between averaging bin frequencies
float * averages; // the actual averages
float * peaks; // peaks of the averages, aka "maxAverages" in other implementations
int * peakHoldTimes; // how long to hold THIS peak meter? decay if == 0
int peakHoldTime; // how long do we hold peaks? (in fft frames)
float peakDecayRate; // how quickly the peaks decay: 0f=instantly .. 1f=not at all
int * spe2avg; // the mapping between spectrum[] indices and averages[] indices
// the fft's log equalizer() is no longer of any use (it would be nonsense to log scale
// the spectrum values into log-sized average bins) so here's a quick-and-dirty linear
// equalizer instead:
float linearEQSlope; // the rate of linear eq
float linearEQIntercept; // the base linear scaling used at the first averaging bin
// the formula is: spectrum[i] * (linearEQIntercept + i * linearEQSlope)
// so.. note that clever use of it can also provide a "gain" control of sorts
// (fe: set intercept to 2f and slope to 0f to double gain)
void setup(float samplingRate, int nBandsInTheFFT, int nAveragesPerOctave);
void calculate(float * fftData);
};
#endif
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