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Use FFT for calculating AKF

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Flamefire committed 2014-04-29 19:58:35 +02:00
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PitchTracker/FFT/FFT.cpp
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/**********************************************************************
FFT.cpp
Dominic Mazzoni
September 2000
*******************************************************************//*!
\file FFT.cpp
\brief Fast Fourier Transform routines.
This file contains a few FFT routines, including a real-FFT
routine that is almost twice as fast as a normal complex FFT,
and a power spectrum routine when you know you don't care
about phase information.
Some of this code was based on a free implementation of an FFT
by Don Cross, available on the web at:
http://www.intersrv.com/~dcross/fft.html
The basic algorithm for his code was based on Numerican Recipes
in Fortran. I optimized his code further by reducing array
accesses, caching the bit reversal table, and eliminating
float-to-double conversions, and I added the routines to
calculate a real FFT and a real power spectrum.
*//*******************************************************************/
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include "FFT.h"
#include "RealFFTf.h"
void DeinitFFT()
{
// Deallocate any unused RealFFTf tables
CleanupFFT();
}
/*
* Real Fast Fourier Transform
*
*/
void RealFFT(int NumSamples, float *RealIn, float *RealOut, float *ImagOut)
{
// Remap to RealFFTf() function
int i;
HFFT hFFT = GetFFT(NumSamples);
float *pFFT = new float[NumSamples];
// Copy the data into the processing buffer
for(i=0; i<NumSamples; i++)
pFFT[i] = RealIn[i];
// Perform the FFT
RealFFTf(pFFT, hFFT);
// Copy the data into the real and imaginary outputs
for(i=1;i<(NumSamples/2);i++) {
RealOut[i]=pFFT[hFFT->BitReversed[i] ];
ImagOut[i]=pFFT[hFFT->BitReversed[i]+1];
}
// Handle the (real-only) DC and Fs/2 bins
RealOut[0] = pFFT[0];
RealOut[i] = pFFT[1];
ImagOut[0] = ImagOut[i] = 0;
// Fill in the upper half using symmetry properties
for(i++ ; i<NumSamples; i++) {
RealOut[i] = RealOut[NumSamples-i];
ImagOut[i] = -ImagOut[NumSamples-i];
}
delete [] pFFT;
ReleaseFFT(hFFT);
}
/*
* InverseRealFFT
*
* This function computes the inverse of RealFFT, above.
* The RealIn and ImagIn is assumed to be conjugate-symmetric
* and as a result the output is purely real.
* Only the first half of RealIn and ImagIn are used due to this
* symmetry assumption.
*/
void InverseRealFFT(int NumSamples, float *RealIn, float *ImagIn, float *RealOut)
{
// Remap to RealFFTf() function
int i;
HFFT hFFT = GetFFT(NumSamples);
float *pFFT = new float[NumSamples];
// Copy the data into the processing buffer
for(i=0; i<(NumSamples/2); i++)
pFFT[2*i ] = RealIn[i];
if(ImagIn == NULL) {
for(i=0; i<(NumSamples/2); i++)
pFFT[2*i+1] = 0;
} else {
for(i=0; i<(NumSamples/2); i++)
pFFT[2*i+1] = ImagIn[i];
}
// Put the fs/2 component in the imaginary part of the DC bin
pFFT[1] = RealIn[i];
// Perform the FFT
InverseRealFFTf(pFFT, hFFT);
// Copy the data to the (purely real) output buffer
ReorderToTime(hFFT, pFFT, RealOut);
delete [] pFFT;
ReleaseFFT(hFFT);
}
void RealInverseRealFFT(int NumSamples, float *In, float *Out){
// Remap to RealFFTf() function
int i;
HFFT hFFT = GetFFT(NumSamples);
float *pFFT = new float[NumSamples];
// Copy the data into the processing buffer
pFFT[0] = In[0];
for(i=1; i<NumSamples/2; i++){
pFFT[i] = In[i];
pFFT[NumSamples - i] = In[i];
}
pFFT[NumSamples/2] = In[NumSamples/2];
// Perform the FFT
RealFFTf(pFFT, hFFT);
// Copy the data into the output
for(i=1;i<NumSamples/2;i++) {
Out[i]=pFFT[hFFT->BitReversed[i]];
}
// Handle the (real-only) DC
Out[0] = pFFT[0];
delete [] pFFT;
ReleaseFFT(hFFT);
}
/*
* PowerSpectrum
*
* This function computes the same as RealFFT, above, but
* adds the squares of the real and imaginary part of each
* coefficient, extracting the power and throwing away the
* phase.
*
* For speed, it does not call RealFFT, but duplicates some
* of its code.
*/
void PowerSpectrum(int NumSamples, float *In, float *Out)
{
// Remap to RealFFTf() function
int i;
HFFT hFFT = GetFFT(NumSamples);
float *pFFT = new float[NumSamples];
// Copy the data into the processing buffer
for(i=0; i<NumSamples; i++)
pFFT[i] = In[i];
// Perform the FFT
RealFFTf(pFFT, hFFT);
// Copy the data into the real and imaginary outputs
for(i=1;i<NumSamples/2;i++) {
Out[i]= (pFFT[hFFT->BitReversed[i] ]*pFFT[hFFT->BitReversed[i] ])
+ (pFFT[hFFT->BitReversed[i]+1]*pFFT[hFFT->BitReversed[i]+1]);
}
// Handle the (real-only) DC and Fs/2 bins
Out[0] = pFFT[0]*pFFT[0];
Out[i] = pFFT[1]*pFFT[1];
delete [] pFFT;
ReleaseFFT(hFFT);
}
PitchTracker/FFT/FFT.h
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/**********************************************************************
FFT.h
Dominic Mazzoni
September 2000
This file contains a few FFT routines, including a real-FFT
routine that is almost twice as fast as a normal complex FFT,
and a power spectrum routine which is more convenient when
you know you don't care about phase information. It now also
contains a few basic windowing functions.
Some of this code was based on a free implementation of an FFT
by Don Cross, available on the web at:
http://www.intersrv.com/~dcross/fft.html
The basic algorithm for his code was based on Numerical Recipes
in Fortran. I optimized his code further by reducing array
accesses, caching the bit reversal table, and eliminating
float-to-double conversions, and I added the routines to
calculate a real FFT and a real power spectrum.
Note: all of these routines use single-precision floats.
I have found that in practice, floats work well until you
get above 8192 samples. If you need to do a larger FFT,
you need to use doubles.
**********************************************************************/
/*
* This is the function you will use the most often.
* Given an array of floats, this will compute the power
* spectrum by doing a Real FFT and then computing the
* sum of the squares of the real and imaginary parts.
* Note that the output array is half the length of the
* input array, and that NumSamples must be a power of two.
*/
void PowerSpectrum(int NumSamples, float *In, float *Out);
/*
* Computes an FFT when the input data is real but you still
* want complex data as output. The output arrays are the
* same length as the input, but will be conjugate-symmetric
* NumSamples must be a power of two.
*/
void RealFFT(int NumSamples,
float *RealIn, float *RealOut, float *ImagOut);
/*
* Computes an Inverse FFT when the input data is conjugate symmetric
* so the output is purely real. NumSamples must be a power of
* two.
* Requires: EXPERIMENTAL_USE_REALFFTF
*/
void InverseRealFFT(int NumSamples,
float *RealIn, float *ImagIn, float *RealOut);
void RealInverseRealFFT(int NumSamples, float *In, float *Out);
void DeinitFFT();
PitchTracker/FFT/License.txt
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Code in this folder is based on Code from Audacity.
License of that code is below:
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PitchTracker/FFT/RealFFTf.cpp
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/*
* Program: REALFFTF.C
* Author: Philip Van Baren
* Date: 2 September 1993
*
* Description: These routines perform an FFT on real data to get a conjugate-symmetric
* output, and an inverse FFT on conjugate-symmetric input to get a real
* output sequence.
*
* This code is for floating point data.
*
* Modified 8/19/1998 by Philip Van Baren
* - made the InitializeFFT and EndFFT routines take a structure
* holding the length and pointers to the BitReversed and SinTable
* tables.
* Modified 5/23/2009 by Philip Van Baren
* - Added GetFFT and ReleaseFFT routines to retain common SinTable
* and BitReversed tables so they don't need to be reallocated
* and recomputed on every call.
* - Added Reorder* functions to undo the bit-reversal
*
* Copyright (C) 2009 Philip VanBaren
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; if not, write to the Free Software
* Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
*/
#include <stdlib.h>
#include <stdio.h>
#include <math.h>
#include "RealFFTf.h"
#ifdef EXPERIMENTAL_EQ_SSE_THREADED
#include "RealFFTf48x.h"
#endif
#ifndef M_PI
#define M_PI 3.14159265358979323846 /* pi */
#endif
/*
* Initialize the Sine table and Twiddle pointers (bit-reversed pointers)
* for the FFT routine.
*/
HFFT InitializeFFT(int fftlen)
{
int i;
int temp;
int mask;
HFFT h;
if((h=(HFFT)malloc(sizeof(FFTParam)))==NULL)
{
fprintf(stderr,"Error allocating memory for FFT\n");
exit(8);
}
/*
* FFT size is only half the number of data points
* The full FFT output can be reconstructed from this FFT's output.
* (This optimization can be made since the data is real.)
*/
h->Points = fftlen/2;
if((h->SinTable=(fft_type *)malloc(2*h->Points*sizeof(fft_type)))==NULL)
{
fprintf(stderr,"Error allocating memory for Sine table.\n");
exit(8);
}
if((h->BitReversed=(int *)malloc(h->Points*sizeof(int)))==NULL)
{
fprintf(stderr,"Error allocating memory for BitReversed.\n");
exit(8);
}
for(i=0;i<h->Points;i++)
{
temp=0;
for(mask=h->Points/2;mask>0;mask >>= 1)
temp=(temp >> 1) + (i&mask ? h->Points : 0);
h->BitReversed[i]=temp;
}
for(i=0;i<h->Points;i++)
{
h->SinTable[h->BitReversed[i] ]=(fft_type)-sin(2*M_PI*i/(2*h->Points));
h->SinTable[h->BitReversed[i]+1]=(fft_type)-cos(2*M_PI*i/(2*h->Points));
}
return h;
}
/*
* Free up the memory allotted for Sin table and Twiddle Pointers
*/
void EndFFT(HFFT h)
{
if(h->Points>0) {
free(h->BitReversed);
free(h->SinTable);
}
h->Points=0;
free(h);
}
#define MAX_HFFT 10
static HFFT hFFTArray[MAX_HFFT] = { NULL };
static int nFFTLockCount[MAX_HFFT] = { 0 };
/* Get a handle to the FFT tables of the desired length */
/* This version keeps common tables rather than allocating a new table every time */
HFFT GetFFT(int fftlen)
{
int h,n = fftlen/2;
for(h=0; (h<MAX_HFFT) && (hFFTArray[h] != NULL) && (n != hFFTArray[h]->Points); h++);
if(h<MAX_HFFT) {
if(hFFTArray[h] == NULL) {
hFFTArray[h] = InitializeFFT(fftlen);
nFFTLockCount[h] = 0;
}
nFFTLockCount[h]++;
return hFFTArray[h];
} else {
// All buffers used, so fall back to allocating a new set of tables
return InitializeFFT(fftlen);;
}
}
/* Release a previously requested handle to the FFT tables */
void ReleaseFFT(HFFT hFFT)
{
int h;
for(h=0; (h<MAX_HFFT) && (hFFTArray[h] != hFFT); h++);
if(h<MAX_HFFT) {
nFFTLockCount[h]--;
} else {
EndFFT(hFFT);
}
}
/* Deallocate any unused FFT tables */
void CleanupFFT()
{
int h;
for(h=0; (h<MAX_HFFT); h++) {
if((nFFTLockCount[h] <= 0) && (hFFTArray[h] != NULL)) {
EndFFT(hFFTArray[h]);
hFFTArray[h] = NULL;
}
}
}
/*
* Forward FFT routine. Must call InitializeFFT(fftlen) first!
*
* Note: Output is BIT-REVERSED! so you must use the BitReversed to
* get legible output, (i.e. Real_i = buffer[ h->BitReversed[i] ]
* Imag_i = buffer[ h->BitReversed[i]+1 ] )
* Input is in normal order.
*
* Output buffer[0] is the DC bin, and output buffer[1] is the Fs/2 bin
* - this can be done because both values will always be real only
* - this allows us to not have to allocate an extra complex value for the Fs/2 bin
*
* Note: The scaling on this is done according to the standard FFT definition,
* so a unit amplitude DC signal will output an amplitude of (N)
* (Older revisions would progressively scale the input, so the output
* values would be similar in amplitude to the input values, which is
* good when using fixed point arithmetic)
*/
void RealFFTf(fft_type *buffer,HFFT h)
{
fft_type *A,*B;
fft_type *sptr;
fft_type *endptr1,*endptr2;
int *br1,*br2;
fft_type HRplus,HRminus,HIplus,HIminus;
fft_type v1,v2,sin,cos;
int ButterfliesPerGroup=h->Points/2;
/*
* Butterfly:
* Ain-----Aout
* \ /
* / \
* Bin-----Bout
*/
endptr1=buffer+h->Points*2;
while(ButterfliesPerGroup>0)
{
A=buffer;
B=buffer+ButterfliesPerGroup*2;
sptr=h->SinTable;
while(A<endptr1)
{
sin=*sptr;
cos=*(sptr+1);
endptr2=B;
while(A<endptr2)
{
v1=*B*cos + *(B+1)*sin;
v2=*B*sin - *(B+1)*cos;
*B=(*A+v1);
*(A++)=*(B++)-2*v1;
*B=(*A-v2);
*(A++)=*(B++)+2*v2;
}
A=B;
B+=ButterfliesPerGroup*2;
sptr+=2;
}
ButterfliesPerGroup >>= 1;
}
/* Massage output to get the output for a real input sequence. */
br1=h->BitReversed+1;
br2=h->BitReversed+h->Points-1;
while(br1<br2)
{
sin=h->SinTable[*br1];
cos=h->SinTable[*br1+1];
A=buffer+*br1;
B=buffer+*br2;
HRplus = (HRminus = *A - *B ) + (*B * 2);
HIplus = (HIminus = *(A+1) - *(B+1)) + (*(B+1) * 2);
v1 = (sin*HRminus - cos*HIplus);
v2 = (cos*HRminus + sin*HIplus);
*A = (HRplus + v1) * (fft_type)0.5;
*B = *A - v1;
*(A+1) = (HIminus + v2) * (fft_type)0.5;
*(B+1) = *(A+1) - HIminus;
br1++;
br2--;
}
/* Handle the center bin (just need a conjugate) */
A=buffer+*br1+1;
*A=-*A;
/* Handle DC bin separately - and ignore the Fs/2 bin
buffer[0]+=buffer[1];
buffer[1]=(fft_type)0;*/
/* Handle DC and Fs/2 bins separately */
/* Put the Fs/2 value into the imaginary part of the DC bin */
v1=buffer[0]-buffer[1];
buffer[0]+=buffer[1];
buffer[1]=v1;
}
/* Description: This routine performs an inverse FFT to real data.
* This code is for floating point data.
*
* Note: Output is BIT-REVERSED! so you must use the BitReversed to
* get legible output, (i.e. wave[2*i] = buffer[ BitReversed[i] ]
* wave[2*i+1] = buffer[ BitReversed[i]+1 ] )
* Input is in normal order, interleaved (real,imaginary) complex data
* You must call InitializeFFT(fftlen) first to initialize some buffers!
*
* Input buffer[0] is the DC bin, and input buffer[1] is the Fs/2 bin
* - this can be done because both values will always be real only
* - this allows us to not have to allocate an extra complex value for the Fs/2 bin
*
* Note: The scaling on this is done according to the standard FFT definition,
* so a unit amplitude DC signal will output an amplitude of (N)
* (Older revisions would progressively scale the input, so the output
* values would be similar in amplitude to the input values, which is
* good when using fixed point arithmetic)
*/
void InverseRealFFTf(fft_type *buffer,HFFT h)
{
fft_type *A,*B;
fft_type *sptr;
fft_type *endptr1,*endptr2;
int *br1;
fft_type HRplus,HRminus,HIplus,HIminus;
fft_type v1,v2,sin,cos;
int ButterfliesPerGroup=h->Points/2;
/* Massage input to get the input for a real output sequence. */
A=buffer+2;
B=buffer+h->Points*2-2;
br1=h->BitReversed+1;
while(A<B)
{
sin=h->SinTable[*br1];
cos=h->SinTable[*br1+1];
HRplus = (HRminus = *A - *B ) + (*B * 2);
HIplus = (HIminus = *(A+1) - *(B+1)) + (*(B+1) * 2);
v1 = (sin*HRminus + cos*HIplus);
v2 = (cos*HRminus - sin*HIplus);
*A = (HRplus + v1) * (fft_type)0.5;
*B = *A - v1;
*(A+1) = (HIminus - v2) * (fft_type)0.5;
*(B+1) = *(A+1) - HIminus;
A+=2;
B-=2;
br1++;
}
/* Handle center bin (just need conjugate) */
*(A+1)=-*(A+1);
/* Handle DC bin separately - this ignores any Fs/2 component
buffer[1]=buffer[0]=buffer[0]/2;*/
/* Handle DC and Fs/2 bins specially */
/* The DC bin is passed in as the real part of the DC complex value */
/* The Fs/2 bin is passed in as the imaginary part of the DC complex value */
/* (v1+v2) = buffer[0] == the DC component */
/* (v1-v2) = buffer[1] == the Fs/2 component */
v1=0.5f*(buffer[0]+buffer[1]);
v2=0.5f*(buffer[0]-buffer[1]);
buffer[0]=v1;
buffer[1]=v2;
/*
* Butterfly:
* Ain-----Aout
* \ /
* / \
* Bin-----Bout
*/
endptr1=buffer+h->Points*2;
while(ButterfliesPerGroup>0)
{
A=buffer;
B=buffer+ButterfliesPerGroup*2;
sptr=h->SinTable;
while(A<endptr1)
{
sin=*(sptr++);
cos=*(sptr++);
endptr2=B;
while(A<endptr2)
{
v1=*B*cos - *(B+1)*sin;
v2=*B*sin + *(B+1)*cos;
*B=(*A+v1)*(fft_type)0.5;
*(A++)=*(B++)-v1;
*B=(*A+v2)*(fft_type)0.5;
*(A++)=*(B++)-v2;
}
A=B;
B+=ButterfliesPerGroup*2;
}
ButterfliesPerGroup >>= 1;
}
}
void ReorderToFreq(HFFT hFFT, fft_type *buffer, fft_type *RealOut, fft_type *ImagOut)
{
// Copy the data into the real and imaginary outputs
for(int i=1;i<hFFT->Points;i++) {
RealOut[i]=buffer[hFFT->BitReversed[i] ];
ImagOut[i]=buffer[hFFT->BitReversed[i]+1];
}
RealOut[0] = buffer[0]; // DC component
ImagOut[0] = 0;
RealOut[hFFT->Points] = buffer[1]; // Fs/2 component
ImagOut[hFFT->Points] = 0;
}
void ReorderToTime(HFFT hFFT, fft_type *buffer, fft_type *TimeOut)
{
// Copy the data into the real outputs
for(int i=0;i<hFFT->Points;i++) {
TimeOut[i*2 ]=buffer[hFFT->BitReversed[i] ];
TimeOut[i*2+1]=buffer[hFFT->BitReversed[i]+1];
}
}
PitchTracker/FFT/RealFFTf.h
+23
View File
@@ -0,0 +1,23 @@
#ifndef __realfftf_h
#define __realfftf_h
#define fft_type float
typedef struct FFTParamType {
int *BitReversed;
fft_type *SinTable;
int Points;
} FFTParam;
#define HFFT FFTParam *
HFFT InitializeFFT(int);
void EndFFT(HFFT);
HFFT GetFFT(int);
void ReleaseFFT(HFFT);
void CleanupFFT();
void RealFFTf(fft_type *,HFFT);
void InverseRealFFTf(fft_type *,HFFT);
void ReorderToTime(HFFT hFFT, fft_type *buffer, fft_type *TimeOut);
void ReorderToFreq(HFFT hFFT, fft_type *buffer, fft_type *RealOut, fft_type *ImagOut);
#endif
PitchTracker/PitchTracker.vcxproj
+4
View File
@@ -174,6 +174,8 @@
<ClCompile Include="compatibility.cpp" />
<ClCompile Include="dywapitchtrack\dywapitchtrack.cpp" />
<ClCompile Include="dywapitchtrack\ptDyWa.cpp" />
<ClCompile Include="FFT\FFT.cpp" />
<ClCompile Include="FFT\RealFFTf.cpp" />
<ClCompile Include="Helper.cpp" />
<ClCompile Include="performous\pitch.cc" />
<ClCompile Include="ptAKF.cpp" />
@@ -183,6 +185,8 @@
<ClInclude Include="compatibility.h" />
<ClInclude Include="dywapitchtrack\dywapitchtrack.h" />
<ClInclude Include="dywapitchtrack\ptDyWa.h" />
<ClInclude Include="FFT\FFT.h" />
<ClInclude Include="FFT\RealFFTf.h" />
<ClInclude Include="Helper.h" />
<ClInclude Include="performous\libda\fft.hpp" />
<ClInclude Include="performous\libda\sample.hpp" />
PitchTracker/PitchTracker.vcxproj.filters
+18
View File
@@ -28,6 +28,12 @@
<Filter Include="Headerdateien\dywapitchtrack">
<UniqueIdentifier>{2a09cee1-51b7-4c24-aa9f-32bec53c3a36}</UniqueIdentifier>
</Filter>
<Filter Include="Quelldateien\FFT">
<UniqueIdentifier>{498f64e2-ff83-41fd-be25-c613750f0e34}</UniqueIdentifier>
</Filter>
<Filter Include="Headerdateien\FFT">
<UniqueIdentifier>{0791b62f-ef8d-40e2-b67e-a6d9dead8720}</UniqueIdentifier>
</Filter>
</ItemGroup>
<ItemGroup>
<ClCompile Include="PitchWrapper.cpp">
@@ -51,6 +57,12 @@
<ClCompile Include="Helper.cpp">
<Filter>Quelldateien</Filter>
</ClCompile>
<ClCompile Include="FFT\FFT.cpp">
<Filter>Quelldateien\FFT</Filter>
</ClCompile>
<ClCompile Include="FFT\RealFFTf.cpp">
<Filter>Quelldateien\FFT</Filter>
</ClCompile>
</ItemGroup>
<ItemGroup>
<ClInclude Include="compatibility.h">
@@ -77,6 +89,12 @@
<ClInclude Include="dywapitchtrack\ptDyWa.h">
<Filter>Headerdateien\dywapitchtrack</Filter>
</ClInclude>
<ClInclude Include="FFT\FFT.h">
<Filter>Headerdateien\FFT</Filter>
</ClInclude>
<ClInclude Include="FFT\RealFFTf.h">
<Filter>Headerdateien\FFT</Filter>
</ClInclude>
</ItemGroup>
<ItemGroup>
<None Include="performous\pitch.hh">
PitchTracker/performous/libda/sample.hpp
-1
View File
@@ -1,7 +1,6 @@
#pragma once
#include <cmath>
#include "../compatibility.h"
/**
* @file sample.hpp Sample format definition and format conversions.
PitchTracker/ptAKF.cpp
+23 -4
View File
@@ -17,8 +17,13 @@
#include "ptAKF.h"
#include <cmath>
#ifdef USE_FFT
#include "FFT/FFT.h"
#endif
static constexpr double BaseToneFrequency = 65.4064; // lowest (half-)tone to analyze (C2 = 65.4064 Hz)
static constexpr double HalftoneBase = 1.05946309436; // 2^(1/12) -> HalftoneBase^12 = 2 (one octave)
int PtAKF::_InitCount = 0;
float* restrict PtAKF::_SamplesPerPeriodPerTone = NULL;
float* restrict PtAKF::_SamplesPerPeriodPerToneFine = NULL;
@@ -41,9 +46,9 @@ PtAKF::PtAKF(unsigned step){
_SamplesPerPeriodPerToneFine[2 * toneIndex + 1] = static_cast<float>(44100.0 / GetFrequencyFromTone(toneIndex + 1./3.)); // samples for a bit above exact frequency
}
_Window = new float[_SampleCt];
double cosMult = 2. * M_PI / (_SampleCt - 1.); //To simplify and speed up
double cosMult = 2. * M_PI / (2 * _SampleCt - 1.); //To simplify and speed up; 2 * _SampleCt because we extend the data by a factor of 2
for (int i = 0; i < _SampleCt; i++) {
_Window[i] = static_cast<float>(0.64 - 0.36 * cos(i * cosMult));
_Window[i] = static_cast<float>(0.54 - 0.46 * cos(i * cosMult));
}
}
_Step = step;
@@ -149,12 +154,20 @@ int PtAKF::_GetNote(float samples[_SampleCt], float* restrict maxVolume, float w
if(maxVolumeL < _VolTreshold)
return -1;
float samplesWindowed[_SampleCt];
float samplesWindowed[_SampleCt * 2];
for(int i = 0; i < _SampleCt; i++){
samplesWindowed[i] = samples[i] * _Window[i];
}
#ifdef USE_FFT
for(int i = _SampleCt; i < _SampleCt * 2; i++){
samplesWindowed[i] = 0.f;
}
float samplesFFT[_SampleCt+1]; // +1 for middle value!
PowerSpectrum(_SampleCt*2, samplesWindowed, samplesFFT);
RealInverseRealFFT(_SampleCt*2, samplesFFT, _AKFValues);
#endif
// Now analyze the samples and get peaks at the most appropriate tones
//Attention: We have a peak at lag 0 that might stretch that far, that we detect a wrong "peak" at _MaxHalfTone
@@ -163,6 +176,7 @@ int PtAKF::_GetNote(float samples[_SampleCt], float* restrict maxVolume, float w
float lastWeight = 1.f;
float maxWeight = 0.f;
//TODO: When using FFT this can be speed up a lot by only checking around the AKF peaks
#pragma omp parallel for schedule(static)
for (int toneIndex = 0; toneIndex <= _MaxHalfTone; toneIndex++){
float curWeight = _AnalyzeByTone(samples, samplesWindowed, toneIndex);
@@ -307,6 +321,10 @@ float PtAKF::_AKFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD){
int samplesPerPeriod = static_cast<int>(samplesPerPeriodD);
float fHigh = samplesPerPeriodD - samplesPerPeriod;
float fLow = 1.0f - fHigh;
#ifdef USE_FFT
float akf2 = _AKFValues[samplesPerPeriod] * fLow + _AKFValues[samplesPerPeriod+1] * fHigh;
return akf2 / (_SampleCt * _SampleCt);
#else
float accumDist = 0; // accumulated distances
@@ -322,10 +340,11 @@ float PtAKF::_AKFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD){
}
return accumDist / _SampleCt;
#endif
}
float PtAKF::_AMDFByTone(float samples[_SampleCt], int toneIndex){
return _AKFBySampleCt(samples, _SamplesPerPeriodPerTone[toneIndex]);
return _AMDFBySampleCt(samples, _SamplesPerPeriodPerTone[toneIndex]);
}
float PtAKF::_AMDFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD){
PitchTracker/ptAKF.h
+9 -4
View File
@@ -13,6 +13,8 @@
# endif
#endif
#define USE_FFT
struct SPeak{
int toneIndex;
float weight;
@@ -55,14 +57,17 @@ private:
float _LastMaxVol;
int _LastTones[_SmoothCt];
int _LastToneIndex;
#ifdef USE_FFT
float _AKFValues[_SampleCt*2];
#endif
int _GetNote(float samples[_SampleCt], float* restrict maxVolume, float weights[_MaxHalfTone+1]);
int _GetSmoothTone();
static float _AnalyzeBySampleCt(float samples[_SampleCt], float samplesWindowed[_SampleCt], float samplesPerPeriodD);
static inline float _AnalyzeByTone(float samples[_SampleCt], float samplesWindowed[_SampleCt], int toneIndex);
static float _AKFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD);
static inline float _AKFByTone(float samples[_SampleCt], int toneIndex);
float _AnalyzeBySampleCt(float samples[_SampleCt], float samplesWindowed[_SampleCt], float samplesPerPeriodD);
inline float _AnalyzeByTone(float samples[_SampleCt], float samplesWindowed[_SampleCt], int toneIndex);
float _AKFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD);
inline float _AKFByTone(float samples[_SampleCt], int toneIndex);
static float _AMDFBySampleCt(float samples[_SampleCt], float samplesPerPeriodD);
static inline float _AMDFByTone(float samples[_SampleCt], int toneIndex);
static inline void InitPeaks(SPeak peaks[_MaxPeaks]);