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Src/Plugins/Visualization/vis_milk2/fft.cpp
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Src/Plugins/Visualization/vis_milk2/fft.cpp
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/*
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LICENSE
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-------
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Copyright 2005-2013 Nullsoft, Inc.
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All rights reserved.
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Redistribution and use in source and binary forms, with or without modification,
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are permitted provided that the following conditions are met:
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* Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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* Redistributions in binary form must reproduce the above copyright notice,
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this list of conditions and the following disclaimer in the documentation
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and/or other materials provided with the distribution.
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* Neither the name of Nullsoft nor the names of its contributors may be used to
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endorse or promote products derived from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
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IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND
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FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
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CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
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DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER
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IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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*/
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#include <math.h>
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#include <memory.h>
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#include "fft.h"
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#define PI 3.141592653589793238462643383279502884197169399f
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#define SafeDeleteArray(x) { if (x) { delete [] x; x = 0; } }
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/*****************************************************************************/
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FFT::FFT()
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{
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NFREQ = 0;
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envelope = 0;
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equalize = 0;
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bitrevtable = 0;
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cossintable = 0;
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temp1 = 0;
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temp2 = 0;
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}
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/*****************************************************************************/
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FFT::~FFT()
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{
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CleanUp();
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}
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/*****************************************************************************/
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void FFT::Init(int samples_in, int samples_out, int bEqualize, float envelope_power)
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{
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// samples_in: # of waveform samples you'll feed into the FFT
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// samples_out: # of frequency samples you want out; MUST BE A POWER OF 2.
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// bEqualize: set to 1 if you want the magnitude of the basses and trebles
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// to be roughly equalized; 0 to leave them untouched.
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// envelope_power: set to -1 to disable the envelope; otherwise, specify
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// the envelope power you want here. See InitEnvelopeTable for more info.
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CleanUp();
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m_samples_in = samples_in;
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NFREQ = samples_out*2;
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InitBitRevTable();
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InitCosSinTable();
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if (envelope_power > 0)
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InitEnvelopeTable(envelope_power);
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if (bEqualize)
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InitEqualizeTable();
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temp1 = new float[NFREQ];
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temp2 = new float[NFREQ];
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}
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/*****************************************************************************/
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void FFT::CleanUp()
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{
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SafeDeleteArray(envelope);
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SafeDeleteArray(equalize);
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SafeDeleteArray(bitrevtable);
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SafeDeleteArray(cossintable);
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SafeDeleteArray(temp1);
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SafeDeleteArray(temp2);
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}
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/*****************************************************************************/
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void FFT::InitEqualizeTable()
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{
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int i;
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float scaling = -0.02f;
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float inv_half_nfreq = 1.0f/(float)(NFREQ/2);
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equalize = new float[NFREQ/2];
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for (i=0; i<NFREQ/2; i++)
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equalize[i] = scaling * logf( (float)(NFREQ/2-i)*inv_half_nfreq );
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}
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/*****************************************************************************/
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void FFT::InitEnvelopeTable(float power)
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{
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// this precomputation is for multiplying the waveform sample
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// by a bell-curve-shaped envelope, so we don't see the ugly
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// frequency response (oscillations) of a square filter.
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// a power of 1.0 will compute the FFT with exactly one convolution.
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// a power of 2.0 is like doing it twice; the resulting frequency
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// output will be smoothed out and the peaks will be "fatter".
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// a power of 0.5 is closer to not using an envelope, and you start
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// to get the frequency response of the square filter as 'power'
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// approaches zero; the peaks get tighter and more precise, but
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// you also see small oscillations around their bases.
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int i;
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float mult = 1.0f/(float)m_samples_in * 6.2831853f;
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envelope = new float[m_samples_in];
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if (power==1.0f)
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for (i=0; i<m_samples_in; i++)
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envelope[i] = 0.5f + 0.5f*sinf(i*mult - 1.5707963268f);
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else
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for (i=0; i<m_samples_in; i++)
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envelope[i] = powf(0.5f + 0.5f*sinf(i*mult - 1.5707963268f), power);
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}
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/*****************************************************************************/
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void FFT::InitBitRevTable()
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{
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int i,j,m,temp;
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bitrevtable = new int[NFREQ];
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for (i=0; i<NFREQ; i++)
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bitrevtable[i] = i;
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for (i=0,j=0; i < NFREQ; i++)
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{
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if (j > i)
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{
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temp = bitrevtable[i];
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bitrevtable[i] = bitrevtable[j];
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bitrevtable[j] = temp;
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}
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m = NFREQ >> 1;
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while (m >= 1 && j >= m)
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{
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j -= m;
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m >>= 1;
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}
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j += m;
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}
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}
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/*****************************************************************************/
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void FFT::InitCosSinTable()
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{
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int i,dftsize,tabsize;
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float theta;
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dftsize = 2;
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tabsize = 0;
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while (dftsize <= NFREQ)
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{
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tabsize++;
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dftsize <<= 1;
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}
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cossintable = new float[tabsize][2];
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dftsize = 2;
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i = 0;
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while (dftsize <= NFREQ)
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{
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theta = (float)(-2.0f*PI/(float)dftsize);
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cossintable[i][0] = (float)cosf(theta);
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cossintable[i][1] = (float)sinf(theta);
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i++;
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dftsize <<= 1;
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}
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}
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/*****************************************************************************/
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void FFT::time_to_frequency_domain(float *in_wavedata, float *out_spectraldata)
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{
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// Converts time-domain samples from in_wavedata[]
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// into frequency-domain samples in out_spectraldata[].
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// The array lengths are the two parameters to Init().
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// The last sample of the output data will represent the frequency
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// that is 1/4th of the input sampling rate. For example,
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// if the input wave data is sampled at 44,100 Hz, then the last
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// sample of the spectral data output will represent the frequency
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// 11,025 Hz. The first sample will be 0 Hz; the frequencies of
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// the rest of the samples vary linearly in between.
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// Note that since human hearing is limited to the range 200 - 20,000
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// Hz. 200 is a low bass hum; 20,000 is an ear-piercing high shriek.
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// Each time the frequency doubles, that sounds like going up an octave.
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// That means that the difference between 200 and 300 Hz is FAR more
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// than the difference between 5000 and 5100, for example!
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// So, when trying to analyze bass, you'll want to look at (probably)
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// the 200-800 Hz range; whereas for treble, you'll want the 1,400 -
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// 11,025 Hz range.
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// If you want to get 3 bands, try it this way:
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// a) 11,025 / 200 = 55.125
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// b) to get the number of octaves between 200 and 11,025 Hz, solve for n:
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// 2^n = 55.125
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// n = log 55.125 / log 2
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// n = 5.785
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// c) so each band should represent 5.785/3 = 1.928 octaves; the ranges are:
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// 1) 200 - 200*2^1.928 or 200 - 761 Hz
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// 2) 200*2^1.928 - 200*2^(1.928*2) or 761 - 2897 Hz
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// 3) 200*2^(1.928*2) - 200*2^(1.928*3) or 2897 - 11025 Hz
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// A simple sine-wave-based envelope is convolved with the waveform
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// data before doing the FFT, to emeliorate the bad frequency response
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// of a square (i.e. nonexistent) filter.
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// You might want to slightly damp (blur) the input if your signal isn't
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// of a very high quality, to reduce high-frequency noise that would
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// otherwise show up in the output.
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int j, m, i, dftsize, hdftsize, t;
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float wr, wi, wpi, wpr, wtemp, tempr, tempi;
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if (!bitrevtable) return;
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//if (!envelope) return;
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//if (!equalize) return;
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if (!temp1) return;
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if (!temp2) return;
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if (!cossintable) return;
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// 1. set up input to the fft
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if (envelope)
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{
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for (i=0; i<NFREQ; i++)
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{
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int idx = bitrevtable[i];
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if (idx < m_samples_in)
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temp1[i] = in_wavedata[idx] * envelope[idx];
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else
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temp1[i] = 0;
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}
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}
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else
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{
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for (i=0; i<NFREQ; i++)
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{
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int idx = bitrevtable[i];
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if (idx < m_samples_in)
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temp1[i] = in_wavedata[idx];// * envelope[idx];
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else
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temp1[i] = 0;
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}
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}
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memset(temp2, 0, sizeof(float)*NFREQ);
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// 2. perform FFT
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float *real = temp1;
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float *imag = temp2;
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dftsize = 2;
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t = 0;
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while (dftsize <= NFREQ)
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{
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wpr = cossintable[t][0];
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wpi = cossintable[t][1];
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wr = 1.0f;
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wi = 0.0f;
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hdftsize = dftsize >> 1;
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for (m = 0; m < hdftsize; m+=1)
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{
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for (i = m; i < NFREQ; i+=dftsize)
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{
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j = i + hdftsize;
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tempr = wr*real[j] - wi*imag[j];
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tempi = wr*imag[j] + wi*real[j];
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real[j] = real[i] - tempr;
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imag[j] = imag[i] - tempi;
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real[i] += tempr;
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imag[i] += tempi;
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}
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wr = (wtemp=wr)*wpr - wi*wpi;
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wi = wi*wpr + wtemp*wpi;
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}
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dftsize <<= 1;
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t++;
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}
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// 3. take the magnitude & equalize it (on a log10 scale) for output
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if (equalize)
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for (i=0; i<NFREQ/2; i++)
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out_spectraldata[i] = equalize[i] * sqrtf(temp1[i]*temp1[i] + temp2[i]*temp2[i]);
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else
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for (i=0; i<NFREQ/2; i++)
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out_spectraldata[i] = sqrtf(temp1[i]*temp1[i] + temp2[i]*temp2[i]);
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}
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/*****************************************************************************/
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