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declick.c.new
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declick.c.new
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/*****************************************************************************
* Gnome Wave Cleaner Version 0.19
* Copyright (C) 2001 Jeffrey J. Welty
*
* 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., 59 Temple Place - Suite 330, Boston, MA 02111-1307, USA.
*******************************************************************************/
/* declick.c */
#include <stdio.h>
#include <stdlib.h>
#include <unistd.h>
#include <float.h>
#include "gwc.h"
#include "stat.h"
#undef warning
#define MESCHACH
#ifndef MESCHACH
#include <gsl/gsl_matrix.h>
#include <gsl/gsl_vector.h>
#include <gsl/gsl_permutation.h>
#include <gsl/gsl_linalg.h>
#endif
void fit_cubic(fftw_real data[], int n, fftw_real estimated[]) ;
#define FFT_MAX 8192
double high_pass_filter(fftw_real x[], int N)
{
int i ;
double sum2 = 0.0 ;
double d2x ;
for(i = 1 ; i < N-1 ; i++) {
d2x = x[i-1] - 2.0 * x[i] + x[i+1] ;
sum2 += d2x*d2x ;
}
return sqrt(sum2/( (double)N - 2) ) ;
}
void stats(double x[], int n, double *pMean, double *pStderr, double *pVar, double *pCv, double *pStddev)
{
double sum_wgt = 0.0 ;
double sum = 0.0 ;
double sum2 = 0.0 ;
double wgt ;
int i ;
for(i = 0 ; i < n ; i++) {
wgt = 1./((double)(n-i)) ;
wgt = 1. ;
sum += x[i]*wgt ;
sum2 += x[i]*x[i]*wgt ;
sum_wgt += wgt ;
}
if(sum_wgt > -DBL_MIN && sum_wgt < DBL_MIN) sum_wgt = 10.0*DBL_MIN ;
*pMean = sum / sum_wgt ;
if(n > 1) {
*pVar = (sum2 - 2.0*(*pMean*sum) + *pMean**pMean*sum_wgt) / ((double)n - 1.0) ;
*pStddev = sqrt(*pVar) ;
*pCv = 100.0 * *pStddev / (*pMean+1.e-100) ;
*pStderr = sqrt(*pVar / sum_wgt) ;
} else {
*pVar = 0.0 ;
*pStddev = 0.0 ;
*pCv = 0.0 ;
*pStderr = 0.0 ;
}
} ;
#ifdef UNUSED_FUNCTION_IN_DECLICK
void get_windowed_ps(fftw_real ps[], fftw_real in[], double window_coef[], int FFT_SIZE, rfftw_plan pFor)
{
fftw_real out[FFT_MAX], windowed[FFT_MAX] ;
int k ;
for(k = 0 ; k < FFT_SIZE ; k++) {
windowed[k] = window_coef[k] * in[k] ;
}
rfftw_one(pFor, windowed, out);
for (k = 1; k <= FFT_SIZE/2 ; ++k)
ps[k] = k < FFT_SIZE/2 ? out[k]*out[k] + out[FFT_SIZE-k]*out[FFT_SIZE-k] : out[k]*out[k] ;
}
#endif
void fit_trig_basis(fftw_real data[], int n, fftw_real estimated[], int click_start, int click_end)
{
int leftmin = 0 ;
int leftmax = click_start ;
int rightmax = n-1 ;
int rightmin = click_end+1 ;
#define ORDER 3
#define NPARAMS (ORDER*2+1)
int o ;
double B[ORDER*2+1+1] ;
int i ;
double x[ORDER*2+1] ;
init_reg(ORDER*2+1) ;
for(i = leftmin ; i <= leftmax ; i++) {
double v = (double)(i-leftmin)/(double)n ;
for(o = 0 ; o < ORDER ; o++) {
x[o*2] = cos((o+1)*M_PI*v) ;
x[o*2+1] = sin((o+1)*M_PI*v) ;
}
x[NPARAMS-1] = v ;
sum_reg(x, data[i]) ;
}
for(i = rightmin ; i <= rightmax ; i++) {
double v = (double)(i-leftmin)/(double)n ;
for(o = 0 ; o < ORDER ; o++) {
x[o*2] = cos((o+1)*M_PI*v) ;
x[o*2+1] = sin((o+1)*M_PI*v) ;
}
x[NPARAMS-1] = v ;
sum_reg(x, data[i]) ;
}
estimate_reg(B) ;
for(i = 0 ; i < ORDER ; i++)
printf("B[%d,%d]=%10lg %10lg\n", i*2+1, i*2+1+1, B[i*2+1], B[i*2+1+1]) ;
printf("B[%d,%d]=%10lg %10lg\n", 0, NPARAMS, B[0], B[NPARAMS]) ;
for(i = leftmin ; i <= rightmax ; i++) {
double v = (double)(i-leftmin)/(double)n ;
estimated[i] = B[0] + B[NPARAMS]*v ;
for(o = 0 ; o < ORDER ; o++) {
estimated[i] += B[o*2+1] * cos((o+1)*M_PI*v) ;
estimated[i] += B[o*2+1+1] * sin((o+1)*M_PI*v) ;
}
}
}
#ifndef MESCHACH
gsl_matrix *gsl_transp(gsl_matrix *m)
{
int i,j,rows,cols ;
gsl_matrix *t ;
rows = m->size1 ;
cols = m->size2 ;
t = gsl_matrix_alloc(cols,rows) ;
for(i = 0 ; i < rows ; i++)
for(j = 0 ; j < cols ; j++)
gsl_matrix_set(t, j, i, gsl_matrix_get(m, i, j)) ;
return t ;
}
gsl_vector *gsl_mv_mlt(gsl_matrix *m, gsl_vector *v)
{
gsl_vector *r ;
int i,j,rows,cols ;
rows = m->size1 ;
cols = m->size2 ;
r = gsl_vector_alloc(cols) ;
for(j = 0 ; j < cols ; j++) {
double x = gsl_matrix_get(m, 0, j)*gsl_vector_get(v,0) ;
for(i = 1 ; i < rows ; i++)
x += gsl_matrix_get(m, i, j)*gsl_vector_get(v,i) ;
gsl_vector_set(r, i, x) ;
}
return r ;
}
gsl_matrix *gsl_m_mlt(gsl_matrix *m1, gsl_matrix *m2)
{
gsl_matrix *r ;
int i,j,k,rows,cols,out_cols ;
rows = m1->size1 ;
cols = m1->size2 ;
out_cols = m2->size2 ;
r = gsl_matrix_alloc(rows,out_cols) ;
for(i = 0 ; i < rows ; i++) {
for(k = 0 ; k < out_cols ; k++) {
double x = gsl_matrix_get(m1, i, 0)*gsl_matrix_get(m2,0,k) ;
for(j = 1 ; j < cols ; j++)
x += gsl_matrix_get(m1, i, j)*gsl_matrix_get(m2,j,k) ;
gsl_matrix_set(r, i, k, x) ;
}
}
return r ;
}
gsl_matrix * gsl_m_inverse(gsl_matrix *m)
{
gsl_matrix *inverse,*ludecomp ;
gsl_permutation *perm ;
int s ;
inverse = gsl_matrix_alloc(m->size1,m->size2) ;
ludecomp = gsl_matrix_alloc(m->size1,m->size2) ;
perm = gsl_permutation_alloc(m->size1) ;
gsl_matrix_memcpy(ludecomp,m) ;
gsl_linalg_LU_decomp(ludecomp,perm,&s) ;
gsl_linalg_LU_invert(ludecomp,perm,inverse) ;
gsl_matrix_free(ludecomp) ;
gsl_permutation_free(perm) ;
return inverse ;
}
#endif
int lsar_sample_restore(fftw_real data[], int firstbad, int lastbad, int siglen)
{
#ifdef MESCHACH
int n_bad = lastbad - firstbad + 1 ;
int autolen = 60 ;
int i, j, rows, cols ;
int rcode ;
gboolean clipped ;
double x[100], auto_coefs[101] ;
static MAT *A=MNULL, *Au=MNULL, *Aut=MNULL, *AutmAu=MNULL, *iAutmAu=MNULL, *final=MNULL ;
/* static MAT *A, *Au, *Aut, *AutmAu, *iAutmAu, *final ; */
static VEC *rhs, *sig, *sig_final ;
//estimate_region(data, firstbad, lastbad, siglen) ;
//return REPAIR_SUCCESS ;
autolen = (siglen-n_bad)/4 ;
//autolen *= 2 ;
if(autolen < 0) {
d_print("Autolen < 0!\n") ;
return REPAIR_FAILURE;
}
if(autolen > 3*n_bad) autolen = 3*n_bad ;
if(autolen > 100) autolen = 100 ;
//g_print("siglen:%d n_bad:%d Autolen:%d\n",siglen,n_bad,autolen) ;
sig = v_get(siglen) ;
A = m_resize(A,siglen-autolen, siglen) ;
Au = m_resize(Au, siglen-autolen, n_bad) ;
for(i = 0 ; i < siglen ; i++)
sig->ve[i] = data[i] ;
init_reg(autolen) ;
for(i = autolen ; i < firstbad ; i++) {
for(j = 0 ; j < autolen ; j++)
x[j] = data[i - autolen + j] ;
sum_reg(x, data[i]) ;
}
for(i = lastbad+autolen+1 ; i < siglen ; i++) {
for(j = 0 ; j < autolen ; j++)
x[j] = data[i - autolen + j] ;
sum_reg(x, data[i]) ;
}
if(estimate_reg(auto_coefs) == 1) {
rcode = SINGULAR_MATRIX ;
} else {
for(i = firstbad ; i <= lastbad ; i++) sig->ve[i] = 0.0 ;
rows = siglen - autolen ;
cols = siglen ;
for(i = 0 ; i < rows ; i++) {
for(j = 0 ; j < autolen ; j++)
A->me[i][i+j]= -auto_coefs[j] ;
A->me[i][i+autolen] = 1. ;
for(j = firstbad ; j <= lastbad ; j++)
Au->me[i][j-firstbad] = A->me[i][j] ;
}
for(j = firstbad ; j <= lastbad ; j++)
sig->ve[j] = 0.0 ;
Aut = m_transp(Au, Aut) ;
rhs = mv_mlt(A,sig,rhs) ;
AutmAu = m_mlt(Aut,Au, AutmAu) ;
iAutmAu = m_inverse(AutmAu, iAutmAu) ;
final = m_mlt(iAutmAu,Aut, final) ;
sig_final = mv_mlt(final,rhs, sig_final) ;
clipped = FALSE ;
for(j = firstbad ; j <= lastbad ; j++) {
double tmp = -sig_final->ve[j-firstbad] ;
if(tmp > 1.0) clipped = TRUE ;
if(tmp < -1.0) clipped = TRUE ;
}
if(clipped == FALSE) {
for(j = firstbad ; j <= lastbad ; j++) {
data[j] = -sig_final->ve[j-firstbad] ;
if(data[j] > 1.0) data[j] = 1.0 ;
if(data[j] < -1.0) data[j] = -1.0 ;
}
}
if(clipped == FALSE)
rcode = REPAIR_SUCCESS ;
else
rcode = REPAIR_CLIPPED ;
}
M_FREE(A) ;
M_FREE(Au) ;
M_FREE(Aut) ;
M_FREE(AutmAu) ;
M_FREE(iAutmAu) ;
M_FREE(final) ;
V_FREE(sig) ;
V_FREE(sig_final) ;
V_FREE(rhs) ;
return rcode ;
#else
int n_bad = lastbad - firstbad + 1 ;
int autolen = 60 ;
int i, j, rows, cols ;
int rcode ;
gboolean clipped ;
double x[100], auto_coefs[101] ;
static gsl_matrix *A, *Au, *Aut, *AutmAu, *iAutmAu, *final ;
static gsl_vector *rhs, *sig, *sig_final ;
//estimate_region(data, firstbad, lastbad, siglen) ;
//return REPAIR_SUCCESS ;
autolen = (siglen-n_bad)/4 ;
//autolen *= 2 ;
if(autolen < 0) {
d_print("Autolen < 0!\n") ;
return REPAIR_FAILURE;
}
if(autolen > 3*n_bad) autolen = 3*n_bad ;
if(autolen > 100) autolen = 100 ;
//g_print("siglen:%d n_bad:%d Autolen:%d\n",siglen,n_bad,autolen) ;
sig = gsl_vector_alloc(siglen) ;
A = gsl_matrix_alloc(siglen-autolen, siglen) ;
Au = gsl_matrix_alloc(siglen-autolen, n_bad) ;
for(i = 0 ; i < siglen ; i++)
gsl_vector_set(sig,i, data[i]) ;
init_reg(autolen) ;
for(i = autolen ; i < firstbad ; i++) {
for(j = 0 ; j < autolen ; j++)
x[j] = data[i - autolen + j] ;
sum_reg(x, data[i]) ;
}
for(i = lastbad+autolen+1 ; i < siglen ; i++) {
for(j = 0 ; j < autolen ; j++)
x[j] = data[i - autolen + j] ;
sum_reg(x, data[i]) ;
}
if(estimate_reg(auto_coefs) == 1) {
rcode = SINGULAR_MATRIX ;
} else {
for(i = firstbad ; i <= lastbad ; i++) gsl_vector_set(sig,i,0.0) ;
rows = siglen - autolen ;
cols = siglen ;
for(i = 0 ; i < rows ; i++) {
for(j = 0 ; j < autolen ; j++)
gsl_matrix_set(A,i,i+j,-auto_coefs[j]) ;
gsl_matrix_set(A,i,i+autolen, 1.) ;
for(j = firstbad ; j <= lastbad ; j++)
gsl_matrix_set(A,i,j-firstbad, gsl_matrix_get(A,i,j)) ;
}
for(j = firstbad ; j <= lastbad ; j++)
gsl_vector_set(sig,j, 0.0) ;
Aut = gsl_transp(Au) ;
rhs = gsl_mv_mlt(A,sig) ;
AutmAu = gsl_m_mlt(Aut,Au) ;
iAutmAu = gsl_m_inverse(AutmAu) ;
final = gsl_m_mlt(iAutmAu,Aut) ;
sig_final = gsl_mv_mlt(final,rhs) ;
clipped = FALSE ;
for(j = firstbad ; j <= lastbad ; j++) {
double tmp = -gsl_vector_get(sig_final,j-firstbad) ;
if(tmp > 1.0) clipped = TRUE ;
if(tmp < -1.0) clipped = TRUE ;
}
if(clipped == FALSE) {
for(j = firstbad ; j <= lastbad ; j++) {
double tmp = -gsl_vector_get(sig_final,j-firstbad) ;
if(data[j] > 1.0) data[j] = 1.0 ;
if(data[j] < -1.0) data[j] = -1.0 ;
}
}
if(clipped == FALSE)
rcode = REPAIR_SUCCESS ;
else
rcode = REPAIR_CLIPPED ;
}
gsl_matrix_free(A) ;
gsl_matrix_free(Au) ;
gsl_matrix_free(Aut) ;
gsl_matrix_free(AutmAu) ;
gsl_matrix_free(iAutmAu) ;
gsl_matrix_free(final) ;
gsl_vector_free(sig) ;
gsl_vector_free(sig_final) ;
gsl_vector_free(rhs) ;
return rcode ;
#endif
}
#define DECLICK_CUBIC 0x01
#define DECLICK_LSAR 0x02
int declick_a_click(struct sound_prefs *p, long first_sample, long last_sample, int channel_mask)
{
long n_samples = last_sample - first_sample + 1;
long first ;
int ch, k, last ;
int click_start, click_end ;
int repair_method ;
int FFT_SIZE ;
int result = REPAIR_FAILURE ;
fftw_real estimated[FFT_MAX*3], window_coef[FFT_MAX] ;
fftw_real data[2][FFT_MAX] ;
/* choose a repair strategy based on the length of the click */
if(n_samples < 1) {
d_print("Whoa there, trying to declick %d samples!\n", n_samples) ;
return 1 ;
} else if(n_samples < 6) {
/* cubic function -- interpolation */
first = first_sample-4 ;
if(first < 0) first = 0 ;
last = last_sample+4 ;
if(last > p->n_samples-1) last = p->n_samples-1 ;
repair_method = DECLICK_CUBIC ;
} else {
/* LSAR */
first = first_sample-200;
if(first < 0) first = 0 ;
last = last_sample+200;
if(last > p->n_samples-1) last = p->n_samples-1 ;
repair_method = DECLICK_LSAR ;
}
repair_method = DECLICK_LSAR ;
FFT_SIZE = last-first+1 ;
read_fft_real_wavefile_data(data[0], data[1], first, last) ;
save_undo_data( first, last, p, FALSE) ;
/* compute click starting and ending positions in the buffer data_all */
click_start = first_sample-first ;
click_end = last_sample-first ;
for(k = 0 ; k < FFT_SIZE ; k++) {
window_coef[k] = blackman(k, FFT_SIZE) ;
window_coef[k] = 1.0 ;
}
for(ch = 0 ; ch < 2 ; ch++) {
if(channel_mask & (ch+1)) {
if(repair_method == DECLICK_CUBIC) {
fit_cubic(data[ch], FFT_SIZE, estimated) ;
/* fit_trig_basis(data_all[ch], FFT_SIZE*3, windowed, click_start, click_end) ; */
/* merge results back into sample data based on window function */
for(k = 0 ; k < FFT_SIZE ; k++) {
double w = window_coef[k] ;
w = blackman(k, FFT_SIZE) ;
w = blackman_hybrid(k, click_end-click_start+2, FFT_SIZE) ;
data[ch][k] = (1.0-w) * data[ch][k] + w*estimated[k+FFT_SIZE] ;
}
} else
result = lsar_sample_restore(data[ch], click_start, click_end, FFT_SIZE) ;
}
}
write_fft_real_wavefile_data(data[0], data[1], first, last) ;
return result ;
}
/* bj 10/2002
* WINDOW_SIZE = number of data points to read at a time
* WINDOW_OVERLAP = number of data points to overlap between windows
* (set this to maximum click size you think reasonable)
* HPF_AVE_WING_BASE = number of points about current point (each side)
* to use as baseline rms average
* HPF_AVE_WING_LOCAL = number of points about current point (each side)
* to average to get rms value for current point
* HPF_DATA_WING = number of points about current point (each side)
* required to get rms value for current point
* (only change this if you change the hpf from 2nd
* derivative to something else)
* HPF_DELTA_WIDTH = number of previous points used as base to compare
* current change in hpf. used to detect trailing
* edge of a click
*/
#define WINDOW_SIZE 30000
#define HPF_AVE_WING_BASE 500
#define HPF_AVE_WING_LOCAL 8
#define HPF_DATA_WING 1
#define HPF_DELTA_WIDTH 50
#define WINDOW_OVERLAP 300
#define HPF_AVE_WIDTH_BASE (HPF_AVE_WING_BASE * 2 + 1)
#define HPF_AVE_WIDTH_LOCAL (HPF_AVE_WING_LOCAL * 2 + 1)
#define EXTRA_DATA_WING (HPF_AVE_WING_BASE + HPF_AVE_WING_LOCAL + HPF_DATA_WING)
#define MAX_WINDOW_SIZE (WINDOW_SIZE + EXTRA_DATA_WING * 2)
#define HPF2_AVE_WING_BASE 500
#define HPF2_AVE_WING_LOCAL 4
#define HPF2_DATA_WING 1
#define HPF2_DELTA_WIDTH 50
#define WINDOW_OVERLAP2 300
#define HPF2_AVE_WIDTH_BASE (HPF2_AVE_WING_BASE * 2 + 1)
#define HPF2_AVE_WIDTH_LOCAL (HPF2_AVE_WING_LOCAL * 2 + 1)
#define INC_POS(a,b,c) ( ((a)+(b)+(c)) % (c) )
/* maintain running sum of 2nd derivative rms so that we avoid excessive
* calculation time.
* 1) local rms value across small number of data points (HPF_AVE_WING_LOCAL
* about current point)
* 2) compare local rms value with HPF_AVE_WING_BASE local rms values about
* current point
*
* Also used to get change in hpf near a point (pass in sample=-N as flag)
*
* do_declick runs backward thru data points, so this does too.
* To get first real datapoint, have to run through (HPF_AVE_WIDTH_BASE
* + HPF_AVE_WING_LOCAL) * 2 calculations first in order to fill up
* the hpfl & hpfb arrays with correct rms values
*/
void get_hpf (long sample, fftw_real channel_data[], double *hpf, double *hpf_ave, double *hpf_dev, double *hpf2, double *hpf2_ave, double *hpf2_dev)
{
static double hpfl[HPF_AVE_WIDTH_LOCAL];
static double suml;
static int posl;
static double hpfb[HPF_AVE_WIDTH_BASE];
static double sumb;
static int posb;
long sample2 = sample/2 ;
static double hpfl2[HPF_AVE_WIDTH_LOCAL];
static double suml2;
static int posl2;
static double hpfb2[HPF_AVE_WIDTH_BASE];
static double sumb2;
static int posb2;
/* if real sample, get next hpf value into array */
if (sample >= 0)
{
{
fftw_real *data = &channel_data[sample - (HPF_AVE_WING_BASE+HPF_AVE_WING_LOCAL)];
posl = INC_POS(posl,-1,HPF_AVE_WIDTH_LOCAL);
posb = INC_POS(posb,-1,HPF_AVE_WIDTH_BASE);
/* get updated sum of rms values of actual data points
* and get updated sum of local average of rms values */
suml -= hpfl[posl];
hpfl[posl] = data[-1] - 2. * data[0] + data[1];
hpfl[posl] *= hpfl[posl];
suml += hpfl[posl];
/* bugfix -- thanks Paul Sanders 1/12/2007 */
*hpf = (suml > 0.0) ? sqrt(suml/(HPF_AVE_WIDTH_LOCAL-2)) : 0.0 ;
sumb -= hpfb[posb];
hpfb[posb] = *hpf;
sumb += *hpf;
*hpf_ave = sumb / HPF_AVE_WIDTH_BASE;
/* hpf of current point was read in a while back;
* retrieve that value now */
*hpf = hpfb[INC_POS(posb,HPF_AVE_WING_BASE,HPF_AVE_WIDTH_BASE)];
}
{
fftw_real *data = &channel_data[sample - (HPF2_AVE_WING_BASE+HPF2_AVE_WING_LOCAL)];
posl2 = INC_POS(posl2,-1,HPF2_AVE_WIDTH_LOCAL);
posb2 = INC_POS(posb2,-1,HPF2_AVE_WIDTH_BASE);
/* get updated sum of rms values of actual data points
* and get updated sum of local average of rms values */
suml2 -= hpfl2[posl2];
hpfl2[posl2] = data[-1] - 2. * data[0] + data[1];
hpfl2[posl2] *= hpfl2[posl2];
suml2 += hpfl2[posl2];
/* bugfix -- thanks Paul Sanders 1/12/2007 */
*hpf2 = (suml2 > 0.0) ? sqrt(suml2/(HPF2_AVE_WIDTH_LOCAL-2)) : 0.0 ;
sumb2 -= hpfb2[posb2];
hpfb2[posb2] = *hpf2;
sumb2 += *hpf2;
*hpf2_ave = sumb2 / HPF2_AVE_WIDTH_BASE;
/* hpf of current point was read in a while back;
* retrieve that value now */
*hpf2 = hpfb2[INC_POS(posb2,HPF2_AVE_WING_BASE,HPF2_AVE_WIDTH_BASE)];
}
}
/* negative sample; get change in hpf */
else
{
{
int posF, pos0, n = -sample;
double x = 0, sumx = 0, sumx2 = 0;
pos0 = INC_POS(posb,HPF_AVE_WING_BASE+n,HPF_AVE_WIDTH_BASE);
while (sample < 0)
{
posF = INC_POS(pos0,-2,HPF_AVE_WIDTH_BASE);
x = hpfb[posF] - hpfb[pos0];
sumx += x;
sumx2 += x*x;
pos0 = INC_POS(pos0,-1,HPF_AVE_WIDTH_BASE);
sample++;
}
*hpf = x; /* last value in x is value at "current" position */
*hpf_ave = sumx / n;
*hpf_dev = sqrt((sumx2 - sumx*sumx/n)/(n-1));
}
{
int posF, pos0, n = -sample2;
double x = 0, sumx = 0, sumx2 = 0;
pos0 = INC_POS(posb2,HPF2_AVE_WING_BASE+n,HPF2_AVE_WIDTH_BASE);
while (sample < 0)
{
posF = INC_POS(pos0,-2,HPF2_AVE_WIDTH_BASE);
x = hpfb2[posF] - hpfb2[pos0];
sumx += x;
sumx2 += x*x;
pos0 = INC_POS(pos0,-1,HPF2_AVE_WIDTH_BASE);
sample++;
}
*hpf2 = x; /* last value in x is value at "current" position */
*hpf2_ave = sumx / n;
*hpf2_dev = sqrt((sumx2 - sumx*sumx/n)/(n-1));
}
}
}
/* bj 10/2002 end, but several changes in do_declick also */
char *do_declick(struct sound_prefs *p, long first_sample, long last_sample, int channel_mask, double sensitivity, int repair,
struct click_data *clicks, int iterate_flag, int leave_click_marks)
{
extern int declick_detector_type ;
if(declick_detector_type == FFT_DETECT)
return do_declick_fft(p,first_sample,last_sample,channel_mask,sensitivity,repair,clicks,iterate_flag,leave_click_marks) ;
else
return do_declick_hpf(p,first_sample,last_sample,channel_mask,sensitivity,repair,clicks,iterate_flag,leave_click_marks) ;
}
#define DECLICK_MAX_FFT 128
char *do_declick_fft(struct sound_prefs *p, long first_sample, long last_sample, int channel_mask, double sensitivity, int repair,
struct click_data *clicks, int iterate_flag, int leave_click_marks)
{
static char results_buf[200] ;
long window_first ;
long i,k ;
int FFT_SIZE = 64 ;
int n_repaired[2] , n_this_pass ;
int n_not_repaired[2] ;
char max_exceeded_notice = 0 ;
#define FFT_WINDOW 1000
char level[2][2*FFT_WINDOW+1][DECLICK_MAX_FFT] ;
#ifdef HAVE_FFTW3
FFTW(plan) pLeft, pRight ;
#else /* HAVE_FFTW3 */
rfftw_plan fftw_p ;
#endif /* HAVE_FFTW3 */
fftw_real data[2][2*FFT_WINDOW+1] ;
fftw_real out[2*DECLICK_MAX_FFT] ;
fftw_real window[2*DECLICK_MAX_FFT] ;
fftw_real power_spectrum[2*DECLICK_MAX_FFT] ;
int in_click ;
int window_size = FFT_WINDOW * MIN((p->rate/44100.0),2) ;
int window_step ;
int channel ;
int done = 0 ;
if(last_sample > p->n_samples-20) last_sample = p->n_samples-20 ;
if(first_sample < 20) first_sample = 20 ;
if(first_sample >= last_sample) {
return "Region to small to declick." ;
}
start_timer();
if(repair == FALSE || leave_click_marks == FALSE)
clicks->n_clicks = 0 ;
n_repaired[0] = n_repaired[1] = 0 ;
n_not_repaired[0] = n_not_repaired[1] = 0 ;
window_step = 700 ;
window_size = 801 ;
g_print("Declick_fft first_sample:%ld last_sample:%ld window_size:%d FFT_SIZE:%d\n", first_sample, last_sample, window_size, FFT_SIZE) ;
update_progress_bar(0.0,PROGRESS_UPDATE_INTERVAL,TRUE) ;
#ifdef HAVE_FFTW3
pLeft = FFTW(plan_r2r_1d)(FFT_SIZE, data[0], out, FFTW_R2HC, FFTW_ESTIMATE);
pRight = FFTW(plan_r2r_1d)(FFT_SIZE, data[1], out, FFTW_R2HC, FFTW_ESTIMATE);
#else /* HAVE_FFTW3 */
fftw_p = rfftw_create_plan(FFT_SIZE, FFTW_REAL_TO_COMPLEX, FFTW_ESTIMATE);
#endif /* HAVE_FFTW3 */
for(k = 0 ; k < FFT_SIZE ; k++) {
window[k] = blackman(k,FFT_SIZE) ;
}
for(window_first = first_sample ; !done && window_first < last_sample ; window_first += window_step ) {
int clicks_repaired = 1 ;
int min_sample,max_sample ;
if(window_first + window_size > last_sample) {
window_first = last_sample - window_size ;
done = 1 ;
}
double percentage = (double)(window_first-first_sample)/(double)(last_sample-first_sample) ;
update_progress_bar(percentage,PROGRESS_UPDATE_INTERVAL,FALSE) ;
int istart ;
if(window_first == first_sample) {
istart = 0 ;
} else {
int n_shift = window_size-window_step ;
istart = n_shift ;
for(i=0 ; i < n_shift ; i++) {
int shift_i = i+window_step ;
for(k = 0 ; k < FFT_SIZE/2 ; k++) {
for (channel = 0; channel < 2; channel++) {
level[channel][i][k] = level[channel][shift_i][k] ;
}
}
}
}
for(i=istart ; i < window_size ; i++) {
min_sample = i+window_first-FFT_SIZE/2 ;
min_sample = MAX(0, min_sample) ;
max_sample = min_sample+FFT_SIZE-1 ;
if(max_sample > p->n_samples-1)
max_sample = p->n_samples-1 ;
read_fft_real_wavefile_data(data[0], data[1], min_sample, max_sample) ;
for(k = 0 ; k < FFT_SIZE ; k++) {
data[0][k] *= window[k] ;
data[1][k] *= window[k] ;
}
for (channel = 0; channel < 2; channel++) {
double min_p = 1.e30, max_p = -1.e30 ;
if(! ((channel+1) & channel_mask) ) continue ;
#ifdef HAVE_FFTW3
if (channel == 0)
FFTW(execute)(pLeft);
else
FFTW(execute)(pRight);
#else /* HAVE_FFTW3 */
if (channel == 0)
rfftw_one(fftw_p, data[0], out);
else
rfftw_one(fftw_p, data[1], out);
#endif /* HAVE_FFTW3 */
power_spectrum[0] = out[0]*out[0]; /* DC component */
for (k = 1; k < (FFT_SIZE+1)/2; ++k) /* (k < FFT_SIZE/2 rounded up) */
power_spectrum[k] = out[k]*out[k] + out[FFT_SIZE-k]*out[FFT_SIZE-k];
if (FFT_SIZE % 2 == 0) /* N is even */
power_spectrum[FFT_SIZE/2] = (out[FFT_SIZE/2]*out[FFT_SIZE/2]); /* Nyquist freq. */
for(k = 1 ; k <= FFT_SIZE/2 ; k++) {
double p = 10.0*log10(power_spectrum[k]) ;
if(p < -127.0) p = -127.0 ;
if(p > 127.0) p = 127.0 ;
if(p > max_p) max_p = p ;
if(p < min_p) min_p = p ;
level[channel][i][k-1] = (char)p ;
}
}
}
for(channel = 0 ; channel < 2 ; channel++) {
double mean_level[FFT_SIZE] ;
double mean_level_r[FFT_SIZE] ;
double mean_level_p[FFT_SIZE] ;
double offset[FFT_WINDOW*2+1] ;
double hgt_sum = 0 ;
double mean, std_err, var, cv, stddev ;
long click_start = 0 ;
int use_new_detector=1 ;
if(! ((channel+1) & channel_mask) ) continue ;
if(use_new_detector) {
double peak_sum_prev = -1 ;
double peak_width_prev = -1.0 ;
double sum_l_prev=0 ;
double sum_r_prev=0 ;
double sum_p_prev=0 ;
double delta_l_prev=0 ;
double delta_r_prev=0 ;
double delta_p_prev=0 ;
double balance_factor_prev=0 ;
for(i = 60 ; i < window_size ; i++) {
double peak_sum=0.0 ;
double peak_width = 0 ;
int j ;
int n_k = 0 ;
int k_start=4 ; /* lowest frequencies don't have good data for detecting clicks */
for(k = k_start ; k < FFT_SIZE/2 ; k++) {
double peak_sum_k = level[channel][i][k] ;
for(j = 1 ; j < 50 ; j++) {
if(j > 2 && level[channel][i-j][k] > level[channel][i-j+2][k]) {
j-- ;
break ;
}
if(j > 2 && level[channel][i+j][k] > level[channel][i+j-2][k]) {
j-- ;
break ;
}
peak_sum_k += level[channel][i-j][k] ;
peak_sum_k += level[channel][i+j][k] ;
}
int width = j*2 ;
mean_level_p[k] = peak_sum_k/((double)width+1.0) ;
int level_width = width ;
if(level_width < 50) level_width = 50 ;
mean_level[k] = 0.0 ;
mean_level_r[k] = 0.0 ;
int n=0 ;
for(; j < level_width ; j++) {
mean_level[k] += level[channel][i-j][k] ;
mean_level_r[k] += level[channel][i+j][k] ;
n += 1 ;
}
mean_level[k] /= (double)n ;
mean_level_r[k] /= (double)n ;
double ml = (mean_level[k]+mean_level_r[k]) / 2.0 ;
/* peak_sum -= mean_level[k]*(width+1) ; */
double tmp = peak_sum_k-(ml+3)*(width+1) ;
if(tmp < 0.0) tmp=0.0 ;
peak_sum += tmp ;
peak_width += width+1 ;
n_k++ ;
}
/* an analysis of mean_levels on left and right sides of peak */
double balance_factor = 1.0 ;
double delta_l=0.0, delta_p=0.0, delta_r=0.0, sum_l=0.0, sum_p=0.0, sum_r=0.0 ;
for(k = k_start ; k < FFT_SIZE/2 ; k++) {
sum_l += mean_level[k] ;
sum_r += mean_level_r[k] ;
sum_p += mean_level_p[k] ;
if(k < FFT_SIZE/2-1) {
delta_l += mean_level[k+1]-mean_level[k] ;
delta_r += mean_level_r[k+1]-mean_level_r[k] ;
delta_p += mean_level_p[k+1]-mean_level_p[k] ;
}
}
/* compute mean peak width */
peak_width /= (double)n_k ;
sum_l /= (double)n_k ;
sum_r /= (double)n_k ;
sum_p /= (double)n_k ;
/* note we are comparing negative values here for the ratio to use */
if(sum_l > sum_r) {
balance_factor=sqrt((sum_l-sum_r+.01)+1) ;
} else {
balance_factor=sqrt((sum_r-sum_l+.01)+1) ;
}
balance_factor = 1./balance_factor ;
peak_sum *= balance_factor ;
if(0 && channel == 0) {