/********************************************************************
* *
- * THIS FILE IS PART OF THE Ogg Vorbis SOFTWARE CODEC SOURCE CODE. *
- * USE, DISTRIBUTION AND REPRODUCTION OF THIS SOURCE IS GOVERNED BY *
- * THE GNU PUBLIC LICENSE 2, WHICH IS INCLUDED WITH THIS SOURCE. *
- * PLEASE READ THESE TERMS DISTRIBUTING. *
+ * THIS FILE IS PART OF THE OggVorbis SOFTWARE CODEC SOURCE CODE. *
+ * USE, DISTRIBUTION AND REPRODUCTION OF THIS LIBRARY SOURCE IS *
+ * GOVERNED BY A BSD-STYLE SOURCE LICENSE INCLUDED WITH THIS SOURCE *
+ * IN 'COPYING'. PLEASE READ THESE TERMS BEFORE DISTRIBUTING. *
* *
- * THE OggSQUISH SOURCE CODE IS (C) COPYRIGHT 1994-2000 *
- * by Monty <monty@xiph.org> and The XIPHOPHORUS Company *
- * http://www.xiph.org/ *
+ * THE OggVorbis SOURCE CODE IS (C) COPYRIGHT 1994-2001 *
+ * by the Xiph.Org Foundation http://www.xiph.org/ *
* *
********************************************************************
- function: train a VQ codebook
- last mod: $Id: vqgen.c,v 1.30 2000/02/21 01:13:00 xiphmont Exp $
+ function: train a VQ codebook
********************************************************************/
#include "vqgen.h"
#include "bookutil.h"
-/* Codebook generation happens in two steps:
+/* Codebook generation happens in two steps:
1) Train the codebook with data collected from the encoder: We use
one of a few error metrics (which represent the distance between a
given data point and a candidate point in the training set) to
divide the training set up into cells representing roughly equal
- probability of occurring.
+ probability of occurring.
2) Generate the codebook and auxiliary data from the trained data set
*/
#define vN(data,i) (data+v->elements*i)
/* default metric; squared 'distance' from desired value. */
-double _dist(vqgen *v,double *a, double *b){
+float _dist(vqgen *v,float *a, float *b){
int i;
int el=v->elements;
- double acc=0.;
+ float acc=0.f;
for(i=0;i<el;i++){
- double val=(a[i]-b[i]);
+ float val=(a[i]-b[i]);
acc+=val*val;
}
return sqrt(acc);
}
-double *_weight_null(vqgen *v,double *a){
+float *_weight_null(vqgen *v,float *a){
return a;
}
void _vqgen_seed(vqgen *v){
long i;
for(i=0;i<v->entries;i++)
- memcpy(_now(v,i),_point(v,i),sizeof(double)*v->elements);
+ memcpy(_now(v,i),_point(v,i),sizeof(float)*v->elements);
+ v->seeded=1;
}
int directdsort(const void *a, const void *b){
- double av=*((double *)a);
- double bv=*((double *)b);
- if(av>bv)return(-1);
- return(1);
+ float av=*((float *)a);
+ float bv=*((float *)b);
+ return (av<bv)-(av>bv);
}
void vqgen_cellmetric(vqgen *v){
- int i,j,k;
- double min=-1.,max=-1.,mean=0.,acc=0.;
+ int j,k;
+ float min=-1.f,max=-1.f,mean=0.f,acc=0.f;
long dup=0,unused=0;
#ifdef NOISY
+ int i;
char buff[80];
- double spacings[v->entries];
+ float spacings[v->entries];
int count=0;
FILE *cells;
sprintf(buff,"cellspace%d.m",v->it);
/* minimum, maximum, cell spacing */
for(j=0;j<v->entries;j++){
- double localmin=-1.;
+ float localmin=-1.;
for(k=0;k<v->entries;k++){
if(j!=k){
- double this=_dist(v,_now(v,j),_now(v,k));
- if(this>0){
- if(v->assigned[k] && (localmin==-1 || this<localmin))
- localmin=this;
- }else{
- if(k<j){
- dup++;
- break;
- }
- }
+ float this=_dist(v,_now(v,j),_now(v,k));
+ if(this>0){
+ if(v->assigned[k] && (localmin==-1 || this<localmin))
+ localmin=this;
+ }else{
+ if(k<j){
+ dup++;
+ break;
+ }
+ }
}
}
if(k<v->entries)continue;
unused++;
continue;
}
-
+
localmin=v->max[j]+localmin/2; /* this gives us rough diameter */
if(min==-1 || localmin<min)min=localmin;
if(max==-1 || localmin>max)max=localmin;
}
fprintf(stderr,"cell diameter: %.03g::%.03g::%.03g (%ld unused/%ld dup)\n",
- min,mean/acc,max,unused,dup);
+ min,mean/acc,max,unused,dup);
#ifdef NOISY
- qsort(spacings,count,sizeof(double),directdsort);
+ qsort(spacings,count,sizeof(float),directdsort);
for(i=0;i<count;i++)
fprintf(cells,"%g\n",spacings[i]);
fclose(cells);
-#endif
+#endif
}
void vqgen_quantize(vqgen *v,quant_meta *q){
- double maxdel;
- double mindel;
+ float maxdel;
+ float mindel;
- double delta;
- double maxquant=((1<<q->quant)-1);
+ float delta;
+ float maxquant=((1<<q->quant)-1);
int j,k;
mindel=maxdel=_now(v,0)[0];
-
+
for(j=0;j<v->entries;j++){
- double last=0.;
+ float last=0.f;
for(k=0;k<v->elements;k++){
if(mindel>_now(v,j)[k]-last)mindel=_now(v,j)[k]-last;
if(maxdel<_now(v,j)[k]-last)maxdel=_now(v,j)[k]-last;
encoded. Loosen the delta slightly to allow for additional error
during sequence quantization */
- delta=(maxdel-mindel)/((1<<q->quant)-1.5);
+ delta=(maxdel-mindel)/((1<<q->quant)-1.5f);
+
+ q->min=_float32_pack(mindel);
+ q->delta=_float32_pack(delta);
- q->min=float24_pack(mindel);
- q->delta=float24_pack(delta);
+ mindel=_float32_unpack(q->min);
+ delta=_float32_unpack(q->delta);
for(j=0;j<v->entries;j++){
- double last=0;
+ float last=0;
for(k=0;k<v->elements;k++){
- double val=_now(v,j)[k];
- double now=rint((val-last-mindel)/delta);
-
+ float val=_now(v,j)[k];
+ float now=rint((val-last-mindel)/delta);
+
_now(v,j)[k]=now;
if(now<0){
- /* be paranoid; this should be impossible */
- fprintf(stderr,"fault; quantized value<0\n");
- exit(1);
+ /* be paranoid; this should be impossible */
+ fprintf(stderr,"fault; quantized value<0\n");
+ exit(1);
}
if(now>maxquant){
- /* be paranoid; this should be impossible */
- fprintf(stderr,"fault; quantized value>max\n");
- exit(1);
+ /* be paranoid; this should be impossible */
+ fprintf(stderr,"fault; quantized value>max\n");
+ exit(1);
}
if(q->sequencep)last=(now*delta)+mindel+last;
}
}
}
-/* much easier :-) */
+/* much easier :-). Unlike in the codebook, we don't un-log log
+ scales; we just make sure they're properly offset. */
void vqgen_unquantize(vqgen *v,quant_meta *q){
long j,k;
- double mindel=float24_unpack(q->min);
- double delta=float24_unpack(q->delta);
+ float mindel=_float32_unpack(q->min);
+ float delta=_float32_unpack(q->delta);
for(j=0;j<v->entries;j++){
- double last=0.;
+ float last=0.f;
for(k=0;k<v->elements;k++){
- double now=_now(v,j)[k]*delta+last+mindel;
- _now(v,j)[k]=now;
+ float now=_now(v,j)[k];
+ now=fabs(now)*delta+last+mindel;
if(q->sequencep)last=now;
-
+ _now(v,j)[k]=now;
}
}
}
-void vqgen_init(vqgen *v,int elements,int aux,int entries,double mindist,
- double (*metric)(vqgen *,double *, double *),
- double *(*weight)(vqgen *,double *)){
+void vqgen_init(vqgen *v,int elements,int aux,int entries,float mindist,
+ float (*metric)(vqgen *,float *, float *),
+ float *(*weight)(vqgen *,float *),int centroid){
memset(v,0,sizeof(vqgen));
+ v->centroid=centroid;
v->elements=elements;
v->aux=aux;
v->mindist=mindist;
v->allocated=32768;
- v->pointlist=malloc(v->allocated*(v->elements+v->aux)*sizeof(double));
+ v->pointlist=_ogg_malloc(v->allocated*(v->elements+v->aux)*sizeof(float));
v->entries=entries;
- v->entrylist=malloc(v->entries*v->elements*sizeof(double));
- v->assigned=malloc(v->entries*sizeof(long));
- v->bias=calloc(v->entries,sizeof(double));
- v->max=calloc(v->entries,sizeof(double));
+ v->entrylist=_ogg_malloc(v->entries*v->elements*sizeof(float));
+ v->assigned=_ogg_malloc(v->entries*sizeof(long));
+ v->bias=_ogg_calloc(v->entries,sizeof(float));
+ v->max=_ogg_calloc(v->entries,sizeof(float));
if(metric)
v->metric_func=metric;
else
else
v->weight_func=_weight_null;
+ v->asciipoints=tmpfile();
+
}
-void vqgen_addpoint(vqgen *v, double *p,double *a){
+void vqgen_addpoint(vqgen *v, float *p,float *a){
+ int k;
+ for(k=0;k<v->elements;k++)
+ fprintf(v->asciipoints,"%.12g\n",p[k]);
+ for(k=0;k<v->aux;k++)
+ fprintf(v->asciipoints,"%.12g\n",a[k]);
+
if(v->points>=v->allocated){
v->allocated*=2;
- v->pointlist=realloc(v->pointlist,v->allocated*(v->elements+v->aux)*
- sizeof(double));
+ v->pointlist=_ogg_realloc(v->pointlist,v->allocated*(v->elements+v->aux)*
+ sizeof(float));
+ }
+
+ memcpy(_point(v,v->points),p,sizeof(float)*v->elements);
+ if(v->aux)memcpy(_point(v,v->points)+v->elements,a,sizeof(float)*v->aux);
+
+ /* quantize to the density mesh if it's selected */
+ if(v->mindist>0.f){
+ /* quantize to the mesh */
+ for(k=0;k<v->elements+v->aux;k++)
+ _point(v,v->points)[k]=
+ rint(_point(v,v->points)[k]/v->mindist)*v->mindist;
}
-
- memcpy(_point(v,v->points),p,sizeof(double)*v->elements);
- if(v->aux)memcpy(_point(v,v->points)+v->elements,a,sizeof(double)*v->aux);
v->points++;
- if(v->points==v->entries)_vqgen_seed(v);
if(!(v->points&0xff))spinnit("loading... ",v->points);
}
-double vqgen_iterate(vqgen *v){
+/* yes, not threadsafe. These utils aren't */
+static int sortit=0;
+static int sortsize=0;
+static int meshcomp(const void *a,const void *b){
+ if(((sortit++)&0xfff)==0)spinnit("sorting mesh...",sortit);
+ return(memcmp(a,b,sortsize));
+}
+
+void vqgen_sortmesh(vqgen *v){
+ sortit=0;
+ if(v->mindist>0.f){
+ long i,march=1;
+
+ /* sort to make uniqueness detection trivial */
+ sortsize=(v->elements+v->aux)*sizeof(float);
+ qsort(v->pointlist,v->points,sortsize,meshcomp);
+
+ /* now march through and eliminate dupes */
+ for(i=1;i<v->points;i++){
+ if(memcmp(_point(v,i),_point(v,i-1),sortsize)){
+ /* a new, unique entry. march it down */
+ if(i>march)memcpy(_point(v,march),_point(v,i),sortsize);
+ march++;
+ }
+ spinnit("eliminating density... ",v->points-i);
+ }
+
+ /* we're done */
+ fprintf(stderr,"\r%ld training points remining out of %ld"
+ " after density mesh (%ld%%)\n",march,v->points,march*100/v->points);
+ v->points=march;
+
+ }
+ v->sorted=1;
+}
+
+float vqgen_iterate(vqgen *v,int biasp){
long i,j,k;
- long biasable;
- double fdesired=(double)v->points/v->entries;
- long desired=fdesired;
- long desired2=desired*2;
+ float fdesired;
+ long desired;
+ long desired2;
- double asserror=0.;
- double meterror=0.;
- double *new=malloc(sizeof(double)*v->entries*v->elements);
- long *nearcount=malloc(v->entries*sizeof(long));
- double *nearbias=malloc(v->entries*desired2*sizeof(double));
+ float asserror=0.f;
+ float meterror=0.f;
+ float *new;
+ float *new2;
+ long *nearcount;
+ float *nearbias;
#ifdef NOISY
char buff[80];
FILE *assig;
sprintf(buff,"bias%d.m",v->it);
bias=fopen(buff,"w");
#endif
-
+
if(v->entries<2){
fprintf(stderr,"generation requires at least two entries\n");
exit(1);
}
+ if(!v->sorted)vqgen_sortmesh(v);
+ if(!v->seeded)_vqgen_seed(v);
+
+ fdesired=(float)v->points/v->entries;
+ desired=fdesired;
+ desired2=desired*2;
+ new=_ogg_malloc(sizeof(float)*v->entries*v->elements);
+ new2=_ogg_malloc(sizeof(float)*v->entries*v->elements);
+ nearcount=_ogg_malloc(v->entries*sizeof(long));
+ nearbias=_ogg_malloc(v->entries*desired2*sizeof(float));
+
/* fill in nearest points for entry biasing */
- /*memset(v->bias,0,sizeof(double)*v->entries);*/
+ /*memset(v->bias,0,sizeof(float)*v->entries);*/
memset(nearcount,0,sizeof(long)*v->entries);
memset(v->assigned,0,sizeof(long)*v->entries);
- biasable=0;
- for(i=0;i<v->points;i++){
- double *ppt=v->weight_func(v,_point(v,i));
- double firstmetric=v->metric_func(v,_now(v,0),ppt)+v->bias[0];
- double secondmetric=v->metric_func(v,_now(v,1),ppt)+v->bias[1];
- long firstentry=0;
- long secondentry=1;
- int biasflag=1;
+ if(biasp){
+ for(i=0;i<v->points;i++){
+ float *ppt=v->weight_func(v,_point(v,i));
+ float firstmetric=v->metric_func(v,_now(v,0),ppt)+v->bias[0];
+ float secondmetric=v->metric_func(v,_now(v,1),ppt)+v->bias[1];
+ long firstentry=0;
+ long secondentry=1;
+
+ if(!(i&0xff))spinnit("biasing... ",v->points+v->points+v->entries-i);
+
+ if(firstmetric>secondmetric){
+ float temp=firstmetric;
+ firstmetric=secondmetric;
+ secondmetric=temp;
+ firstentry=1;
+ secondentry=0;
+ }
- if(!(i&0xff))spinnit("biasing... ",v->points+v->points+v->entries-i);
+ for(j=2;j<v->entries;j++){
+ float thismetric=v->metric_func(v,_now(v,j),ppt)+v->bias[j];
+ if(thismetric<secondmetric){
+ if(thismetric<firstmetric){
+ secondmetric=firstmetric;
+ secondentry=firstentry;
+ firstmetric=thismetric;
+ firstentry=j;
+ }else{
+ secondmetric=thismetric;
+ secondentry=j;
+ }
+ }
+ }
- if(firstmetric>secondmetric){
- double temp=firstmetric;
- firstmetric=secondmetric;
- secondmetric=temp;
- firstentry=1;
- secondentry=0;
- }
-
- for(j=2;j<v->entries;j++){
- double thismetric=v->metric_func(v,_now(v,j),ppt)+v->bias[j];
- if(thismetric<secondmetric){
- if(thismetric<firstmetric){
- secondmetric=firstmetric;
- secondentry=firstentry;
- firstmetric=thismetric;
- firstentry=j;
- }else{
- secondmetric=thismetric;
- secondentry=j;
- }
+ j=firstentry;
+ for(j=0;j<v->entries;j++){
+
+ float thismetric,localmetric;
+ float *nearbiasptr=nearbias+desired2*j;
+ long k=nearcount[j];
+
+ localmetric=v->metric_func(v,_now(v,j),ppt);
+ /* 'thismetric' is to be the bias value necessary in the current
+ arrangement for entry j to capture point i */
+ if(firstentry==j){
+ /* use the secondary entry as the threshhold */
+ thismetric=secondmetric-localmetric;
+ }else{
+ /* use the primary entry as the threshhold */
+ thismetric=firstmetric-localmetric;
+ }
+
+ /* support the idea of 'minimum distance'... if we want the
+ cells in a codebook to be roughly some minimum size (as with
+ the low resolution residue books) */
+
+ /* a cute two-stage delayed sorting hack */
+ if(k<desired){
+ nearbiasptr[k]=thismetric;
+ k++;
+ if(k==desired){
+ spinnit("biasing... ",v->points+v->points+v->entries-i);
+ qsort(nearbiasptr,desired,sizeof(float),directdsort);
+ }
+
+ }else if(thismetric>nearbiasptr[desired-1]){
+ nearbiasptr[k]=thismetric;
+ k++;
+ if(k==desired2){
+ spinnit("biasing... ",v->points+v->points+v->entries-i);
+ qsort(nearbiasptr,desired2,sizeof(float),directdsort);
+ k=desired;
+ }
+ }
+ nearcount[j]=k;
}
}
- j=firstentry;
- for(j=0;j<v->entries;j++){
-
- double thismetric,localmetric;
- double *nearbiasptr=nearbias+desired2*j;
- long k=nearcount[j];
-
- localmetric=v->metric_func(v,_now(v,j),ppt);
- /* 'thismetric' is to be the bias value necessary in the current
- arrangement for entry j to capture point i */
- if(firstentry==j){
- /* use the secondary entry as the threshhold */
- thismetric=secondmetric-localmetric;
- }else{
- /* use the primary entry as the threshhold */
- thismetric=firstmetric-localmetric;
- }
+ /* inflate/deflate */
+
+ for(i=0;i<v->entries;i++){
+ float *nearbiasptr=nearbias+desired2*i;
+
+ spinnit("biasing... ",v->points+v->entries-i);
+
+ /* due to the delayed sorting, we likely need to finish it off....*/
+ if(nearcount[i]>desired)
+ qsort(nearbiasptr,nearcount[i],sizeof(float),directdsort);
+
+ v->bias[i]=nearbiasptr[desired-1];
- /* support the idea of 'minimum distance'... if we want the
- cells in a codebook to be roughly some minimum size (as with
- the low resolution residue books) */
-
- if(localmetric>=v->mindist){
-
- /* a cute two-stage delayed sorting hack */
- if(k<desired){
- nearbiasptr[k]=thismetric;
- k++;
- if(k==desired){
- spinnit("biasing... ",v->points+v->points+v->entries-i);
- qsort(nearbiasptr,desired,sizeof(double),directdsort);
- }
-
- }else if(thismetric>nearbiasptr[desired-1]){
- nearbiasptr[k]=thismetric;
- k++;
- if(k==desired2){
- spinnit("biasing... ",v->points+v->points+v->entries-i);
- qsort(nearbiasptr,desired2,sizeof(double),directdsort);
- k=desired;
- }
- }
- nearcount[j]=k;
- }else
- biasflag=0;
- }
- biasable+=biasflag;
- }
-
- /* inflate/deflate */
-
- for(i=0;i<v->entries;i++){
- double *nearbiasptr=nearbias+desired2*i;
-
- spinnit("biasing... ",v->points+v->entries-i);
-
- /* due to the delayed sorting, we likely need to finish it off....*/
- if(nearcount[i]>desired)
- qsort(nearbiasptr,nearcount[i],sizeof(double),directdsort);
-
- /* desired is the *maximum* bias queue size. If we're using
- minimum distance, we're not interested in the max size... we're
- interested in the biasable number of points */
- {
- long localdesired=(double)biasable/v->entries;
- if(localdesired)
- v->bias[i]=nearbiasptr[localdesired-1];
- else
- v->bias[i]=nearbiasptr[0];
}
+ }else{
+ memset(v->bias,0,v->entries*sizeof(float));
}
/* Now assign with new bias and find new midpoints */
for(i=0;i<v->points;i++){
- double *ppt=v->weight_func(v,_point(v,i));
- double firstmetric=v->metric_func(v,_now(v,0),ppt)+v->bias[0];
+ float *ppt=v->weight_func(v,_point(v,i));
+ float firstmetric=v->metric_func(v,_now(v,0),ppt)+v->bias[0];
long firstentry=0;
if(!(i&0xff))spinnit("centering... ",v->points-i);
for(j=0;j<v->entries;j++){
- double thismetric=v->metric_func(v,_now(v,j),ppt)+v->bias[j];
+ float thismetric=v->metric_func(v,_now(v,j),ppt)+v->bias[j];
if(thismetric<firstmetric){
- firstmetric=thismetric;
- firstentry=j;
+ firstmetric=thismetric;
+ firstentry=j;
}
}
j=firstentry;
-
+
#ifdef NOISY
fprintf(cells,"%g %g\n%g %g\n\n",
_now(v,j)[0],_now(v,j)[1],
ppt[0],ppt[1]);
#endif
- firstmetric-=v->bias[firstentry];
+ firstmetric-=v->bias[j];
meterror+=firstmetric;
- /* set up midpoints for next iter */
- if(v->assigned[j]++){
- for(k=0;k<v->elements;k++)
- vN(new,j)[k]+=ppt[k];
- if(firstmetric>v->max[firstentry])v->max[firstentry]=firstmetric;
+
+ if(v->centroid==0){
+ /* set up midpoints for next iter */
+ if(v->assigned[j]++){
+ for(k=0;k<v->elements;k++)
+ vN(new,j)[k]+=ppt[k];
+ if(firstmetric>v->max[j])v->max[j]=firstmetric;
+ }else{
+ for(k=0;k<v->elements;k++)
+ vN(new,j)[k]=ppt[k];
+ v->max[j]=firstmetric;
+ }
}else{
- for(k=0;k<v->elements;k++)
- vN(new,j)[k]=ppt[k];
- v->max[firstentry]=firstmetric;
+ /* centroid */
+ if(v->assigned[j]++){
+ for(k=0;k<v->elements;k++){
+ if(vN(new,j)[k]>ppt[k])vN(new,j)[k]=ppt[k];
+ if(vN(new2,j)[k]<ppt[k])vN(new2,j)[k]=ppt[k];
+ }
+ if(firstmetric>v->max[firstentry])v->max[j]=firstmetric;
+ }else{
+ for(k=0;k<v->elements;k++){
+ vN(new,j)[k]=ppt[k];
+ vN(new2,j)[k]=ppt[k];
+ }
+ v->max[firstentry]=firstmetric;
+ }
}
}
fprintf(bias,"%g\n",v->bias[j]);
#endif
asserror+=fabs(v->assigned[j]-fdesired);
- if(v->assigned[j])
- for(k=0;k<v->elements;k++)
- _now(v,j)[k]=vN(new,j)[k]/v->assigned[j];
+ if(v->assigned[j]){
+ if(v->centroid==0){
+ for(k=0;k<v->elements;k++)
+ _now(v,j)[k]=vN(new,j)[k]/v->assigned[j];
+ }else{
+ for(k=0;k<v->elements;k++)
+ _now(v,j)[k]=(vN(new,j)[k]+vN(new2,j)[k])/2.f;
+ }
+ }
}
asserror/=(v->entries*fdesired);
fprintf(stderr,"Pass #%d... ",v->it);
fprintf(stderr,": dist %g(%g) metric error=%g \n",
- asserror,fdesired,meterror/v->points);
+ asserror,fdesired,meterror/v->points);
v->it++;
-
+
free(new);
free(nearcount);
free(nearbias);
projects / platform / upstream / libvorbis.git / blobdiff