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ebd1d37e74
libcm/vop/cmVectOpsTemplateCode.h
kevin eddc01b445 vop/cmVectOpsTemplateCode/Hdr.h 
Changed fieldWidth and decPlCnt from unsigned to int in PrintF()
Added #ifdef OS_OSX conditional compile around ilaenv_() in LUInverse().
2014-11-18 16:57:44 -08:00

3293 líneas
80 KiB
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#ifdef cmVectOpsTemplateCode_h
void VECT_OP_FUNC(VPrint)( cmRpt_t* rpt, const char* fmt, ... )
{
va_list vl;
va_start(vl,fmt);
if( rpt != NULL )
cmRptVPrintf(rpt,fmt,vl);
else
vprintf(fmt,vl);
va_end(vl);
}
void VECT_OP_FUNC(Printf)( cmRpt_t* rpt, unsigned rowCnt, unsigned colCnt, const VECT_OP_TYPE* sbp, int fieldWidth, int decPlCnt, const char* fmt, unsigned flags )
{
unsigned cci;
unsigned outColCnt = 10;
if( fieldWidth < 0 )
fieldWidth = 10;
if( decPlCnt < 0 )
decPlCnt = 4;
if( outColCnt == -1 )
outColCnt = colCnt;
for(cci=0; cci<colCnt; cci+=outColCnt)
{
unsigned ci0 = cci;
unsigned cn = cci + outColCnt;
unsigned ri;
if(cn > colCnt)
cn = colCnt;
if( colCnt > outColCnt )
{
if( cmIsFlag(flags,cmPrintMatlabLabelsFl) )
VECT_OP_FUNC(VPrint)(rpt,"Columns:%i to %i\n",ci0,cn-1);
else
if( cmIsFlag(flags,cmPrintShortLabelsFl) )
VECT_OP_FUNC(VPrint)(rpt,"%3i: ",ci0);
}
if( rowCnt > 1 )
VECT_OP_FUNC(VPrint)(rpt,"\n");
for(ri=0; ri<rowCnt; ++ri)
{
unsigned ci;
for(ci=ci0; ci<cn; ++ci )
VECT_OP_FUNC(VPrint)(rpt,fmt,fieldWidth,decPlCnt,sbp[ (ci*rowCnt) + ri ]);
if( cn > 0 )
VECT_OP_FUNC(VPrint)(rpt,"\n");
}
}
}
void VECT_OP_FUNC(Print)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* sbp )
{ VECT_OP_FUNC(Printf)(rpt,rn,cn,sbp,cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*f ",cmPrintShortLabelsFl); }
void VECT_OP_FUNC(PrintE)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* sbp )
{ VECT_OP_FUNC(Printf)(rpt,rn,cn,sbp,cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*e ",cmPrintShortLabelsFl); }
void VECT_OP_FUNC(PrintLf)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp, unsigned fieldWidth, unsigned decPlCnt, const char* fmt )
{
VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, fieldWidth, decPlCnt,fmt,cmPrintShortLabelsFl );
}
void VECT_OP_FUNC(PrintL)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp )
{
VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*f ",cmPrintShortLabelsFl );
}
void VECT_OP_FUNC(PrintLE)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp )
{
VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*e ",cmPrintShortLabelsFl );
}
VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityVV)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
{
VECT_OP_TYPE sum = VECT_OP_FUNC(Sum)(sbp,dn);
if( sum == 0 )
sum = 1;
return VECT_OP_FUNC(DivVVS)(dbp,dn,sbp,sum);
}
VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbability)(VECT_OP_TYPE* dbp, unsigned dn)
{ return VECT_OP_FUNC(NormalizeProbabilityVV)(dbp,dn,dbp); }
VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityN)(VECT_OP_TYPE* dbp, unsigned dn, unsigned stride)
{
VECT_OP_TYPE sum = VECT_OP_FUNC(SumN)(dbp,dn,stride);
if( sum == 0 )
return dbp;
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + (dn*stride);
for(; dp < ep; dp+=stride )
*dp /= sum;
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(StandardizeRows)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV )
{
bool uFl = false;
bool sFl = false;
unsigned i;
if( uV == NULL )
{
uV = cmMemAllocZ(VECT_OP_TYPE,drn);
uFl = true;
}
if( sdV == NULL )
{
sdV = cmMemAllocZ(VECT_OP_TYPE,drn);
sFl = true;
}
VECT_OP_FUNC(MeanM)(uV, dbp, drn, dcn, 1 );
VECT_OP_FUNC(VarianceM)(sdV, dbp, drn, dcn, uV, 1 );
for(i=0; i<dcn; ++i)
{
VECT_OP_FUNC(SubVV)(dbp + i * drn, drn, uV );
VECT_OP_FUNC(DivVV)(dbp + i * drn, drn, sdV );
}
if(uFl)
cmMemFree(uV);
if(sFl)
cmMemFree(sdV);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(StandardizeCols)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV )
{
bool uFl = false;
bool sFl = false;
unsigned i;
if( uV == NULL )
{
uV = cmMemAllocZ(VECT_OP_TYPE,dcn);
uFl = true;
}
if( sdV == NULL )
{
sdV = cmMemAllocZ(VECT_OP_TYPE,dcn);
sFl = true;
}
VECT_OP_FUNC(MeanM)(uV, dbp, drn, dcn, 0 );
VECT_OP_FUNC(VarianceM)(sdV, dbp, drn, dcn, uV, 0 );
for(i=0; i<drn; ++i)
{
VECT_OP_FUNC(SubVVNN)(dbp + i, dcn, drn, uV, 1 );
VECT_OP_FUNC(DivVVNN)(dbp + i, dcn, drn, sdV, 1 );
}
if(uFl)
cmMemFree(uV);
if(sFl)
cmMemFree(sdV);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dbp + dn;
for(; dp < ep; ++dp,++sp )
*dp = *sp < 0 ? 0 : *sp;
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
{
VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
VECT_OP_TYPE sum = 0;
while( dbp < dep )
{
sum += *sbp++;
*dbp++ = sum;
}
return rp;
}
VECT_OP_TYPE VECT_OP_FUNC(Mean)( const VECT_OP_TYPE* bp, unsigned n )
{ return VECT_OP_FUNC(Sum)(bp,n)/n; }
VECT_OP_TYPE VECT_OP_FUNC(MeanN)( const VECT_OP_TYPE* bp, unsigned n, unsigned stride )
{ return VECT_OP_FUNC(SumN)(bp,n,stride)/n; }
VECT_OP_TYPE* VECT_OP_FUNC(MeanM)( VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, unsigned dim )
{
unsigned i;
unsigned cn = dim == 0 ? scn : srn;
unsigned rn = dim == 0 ? srn : scn;
unsigned inc = dim == 0 ? srn : 1;
unsigned stride = dim == 0 ? 1 : srn;
unsigned d0 = 0;
for(i=0; i<cn; ++i, d0+=inc)
dp[i] = VECT_OP_FUNC(MeanN)(sp + d0, rn, stride );
return dp;
}
VECT_OP_TYPE* VECT_OP_FUNC(MeanM2)( VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, unsigned dim, unsigned cnt )
{
unsigned i;
unsigned cn = dim == 0 ? scn : srn;
unsigned rn = dim == 0 ? srn : scn;
unsigned inc = dim == 0 ? srn : 1;
unsigned stride = dim == 0 ? 1 : srn;
unsigned d0 = 0;
for(i=0; i<cn; ++i, d0+=inc)
dp[i] = VECT_OP_FUNC(MeanN)(sp + d0, cmMin(rn,cnt), stride );
return dp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Mean2)( VECT_OP_TYPE* dp, const VECT_OP_TYPE* (*srcFuncPtr)(void* arg, unsigned idx ), unsigned D, unsigned N, void* argPtr )
{
unsigned i,n;
const VECT_OP_TYPE* sp;
VECT_OP_FUNC(Zero)(dp,D);
if( N > 1 )
{
n = 0;
for(i=0; i<N; ++i)
if((sp = srcFuncPtr(argPtr,i)) != NULL )
{
VECT_OP_FUNC(AddVV)(dp,D,sp);
++n;
}
VECT_OP_FUNC(DivVS)(dp,D,n);
}
return dp;
}
VECT_OP_TYPE VECT_OP_FUNC(Variance)( const VECT_OP_TYPE* sp, unsigned sn, const VECT_OP_TYPE* avgPtr )
{ return VECT_OP_FUNC(VarianceN)(sp,sn,1,avgPtr); }
VECT_OP_TYPE VECT_OP_FUNC(VarianceN)( const VECT_OP_TYPE* sp, unsigned sn, unsigned stride, const VECT_OP_TYPE* meanPtr )
{
VECT_OP_TYPE mean = 0;
if( sn <= 1 )
return 0;
if( meanPtr == NULL )
mean = VECT_OP_FUNC(MeanN)( sp, sn, stride );
else
mean = *meanPtr;
const VECT_OP_TYPE* ep = sp + (sn*stride);
VECT_OP_TYPE sum = 0;
for(; sp < ep; sp += stride )
sum += (*sp-mean) * (*sp-mean);
return sum / (sn-1);
}
VECT_OP_TYPE* VECT_OP_FUNC(VarianceM)(VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, const VECT_OP_TYPE* avgPtr, unsigned dim )
{
unsigned i;
unsigned cn = dim == 0 ? scn : srn;
unsigned rn = dim == 0 ? srn : scn;
unsigned inc = dim == 0 ? srn : 1;
unsigned stride = dim == 0 ? 1 : srn;
unsigned d0 = 0;
for(i=0; i<cn; ++i, d0+=inc)
dp[i] = VECT_OP_FUNC(VarianceN)(sp + d0, rn, stride, avgPtr==NULL ? NULL : avgPtr+i );
return dp;
}
unsigned VECT_OP_FUNC(NormToMax)( VECT_OP_TYPE* dp, unsigned dn )
{
unsigned i = VECT_OP_FUNC(MaxIndex)(dp,dn,1);
if( i != cmInvalidIdx )
{
VECT_OP_TYPE v = dp[i];
VECT_OP_FUNC(DivVS)(dp,dn,v);
}
return i;
}
unsigned VECT_OP_FUNC(NormToAbsMax)( VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE fact )
{
if( dn == 0 )
return cmInvalidIdx;
unsigned i = 0;
unsigned mi = 0;
VECT_OP_TYPE mx = fabs(dp[0]);
for(i=1; i<dn; ++i)
if( fabs(dp[i])>mx )
{
mi = i;
mx = fabs(dp[i]);
}
VECT_OP_FUNC(MultVS)(dp,dn,fact/mx);
return mi;
}
VECT_OP_TYPE VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha )
{
double sum = 0;
const VECT_OP_TYPE* bp = sp;
const VECT_OP_TYPE* ep = sp + sn;
while( bp < ep )
sum += pow(fabs(*bp++),alpha);
return (VECT_OP_TYPE)pow(sum/sn,1.0/alpha);
}
void VECT_OP_FUNC(GaussCovariance)(VECT_OP_TYPE* yM, unsigned D, const VECT_OP_TYPE* xM, unsigned xN, const VECT_OP_TYPE* uV, const unsigned* selIdxV, unsigned selKey )
{
unsigned i,j,k,n = 0;
VECT_OP_TYPE tV[ D ];
VECT_OP_FUNC(Fill)(yM,D*D,0);
// if the mean was not given - then calculate it
if( uV == NULL )
{
VECT_OP_FUNC(Fill)(tV,D,0);
// sum each row of xM[] into uM[]
for(i=0; i<D; ++i)
{
n = 0;
for(j=0; j<xN; ++j)
if( selIdxV==NULL || selIdxV[j]==selKey )
{
tV[i] += xM[ (j*D) + i ];
++n;
}
}
// form an average from the sum in tV[]
VECT_OP_FUNC(DivVS)(tV,D,n);
uV = tV;
}
for(i=0; i<D; ++i)
for(j=i; j<D; ++j)
{
n = 0;
for(k=0; k<xN; ++k)
if( selIdxV==NULL || selIdxV[k]==selKey)
{
unsigned yi = (i*D)+j;
yM[ yi ] += ((xM[ (k*D)+j ]-uV[j]) * (xM[ (k*D) + i ]-uV[i]));
if( i != j )
yM[ (j*D)+i ] = yM[ yi ];
++n;
}
}
if( n>1 )
VECT_OP_FUNC(DivVS)( yM, D*D, n-1 );
}
void VECT_OP_FUNC(GaussCovariance2)(VECT_OP_TYPE* yM, unsigned D, const VECT_OP_TYPE* (*srcFunc)(void* userPtr, unsigned idx), unsigned xN, void* userPtr, const VECT_OP_TYPE* uV, const unsigned* selIdxV, unsigned selKey )
{
unsigned i,j,k = 0,n;
VECT_OP_TYPE tV[ D ];
const VECT_OP_TYPE* sp;
VECT_OP_FUNC(Fill)(yM,D*D,0);
// if the mean was not given - then calculate it
if( uV == NULL )
{
VECT_OP_FUNC(Fill)(tV,D,0);
n = 0;
// sum each row of xM[] into uM[]
for(i=0; i<xN; ++i)
if( (selIdxV==NULL || selIdxV[i]==selKey) && ((sp=srcFunc(userPtr,i))!=NULL) )
{
VECT_OP_FUNC(AddVV)(tV,D,sp);
++n;
}
// form an average from the sum in tV[]
VECT_OP_FUNC(DivVS)(tV,D,n);
uV = tV;
}
for(i=0; i<xN; ++i)
if( selIdxV==NULL || selIdxV[i]==selKey )
{
// get a pointer to the ith data point
const VECT_OP_TYPE* sV = srcFunc(userPtr,i);
// note: this algorithm works because when a data point element (scalar)
// is multiplied by another data point element those two elements
// are always part of the same data point (vector). Two elements
// from different data points are never multiplied.
if( sV != NULL )
for(j=0; j<D; ++j)
for(k=j; k<D; ++k)
yM[j + k*D] += (sV[j]-uV[j]) * (sV[k]-uV[k]);
}
if( n > 1 )
VECT_OP_FUNC(DivVS)( yM, D*D, n-1 );
// fill in the lower triangle
for(j=0; j<D; ++j)
for(k=j; k<D; ++k)
yM[k + j*D] = yM[j + k*D];
}
bool VECT_OP_FUNC(Equal)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
const VECT_OP_TYPE* ep = s0p + sn;
while( s0p < ep )
if( *s0p++ != *s1p++ )
return false;
return true;
}
bool VECT_OP_FUNC(IsNormal)( const VECT_OP_TYPE* sp, unsigned sn )
{
const VECT_OP_TYPE* ep = sp + sn;
for(; sp<ep; ++sp)
if( !isnormal(*sp) )
return false;
return true;
}
bool VECT_OP_FUNC(IsNormalZ)(const VECT_OP_TYPE* sp, unsigned sn )
{
const VECT_OP_TYPE* ep = sp + sn;
for(; sp<ep; ++sp)
if( (*sp != 0) && (!isnormal(*sp)) )
return false;
return true;
}
unsigned VECT_OP_FUNC(FindNonNormal)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sbp )
{
const VECT_OP_TYPE* sp = sbp;
const VECT_OP_TYPE* ep = sp + dn;
unsigned n = 0;
for(; sp<ep; ++sp)
if( !isnormal(*sp) )
dp[n++] = sp - sbp;
return n;
}
unsigned VECT_OP_FUNC(FindNonNormalZ)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sbp )
{
const VECT_OP_TYPE* sp = sbp;
const VECT_OP_TYPE* ep = sp + dn;
unsigned n = 0;
for(; sp<ep; ++sp)
if( (*sp!=0) && (!isnormal(*sp)) )
dp[n++] = sp - sbp;
return n;
}
unsigned VECT_OP_FUNC(ZeroCrossCount)( const VECT_OP_TYPE* bp, unsigned bn, VECT_OP_TYPE* delaySmpPtr)
{
unsigned n = delaySmpPtr != NULL ? ((*delaySmpPtr >= 0) != (*bp >= 0)) : 0 ;
const VECT_OP_TYPE* ep = bp + bn;
for(; bp<ep-1; ++bp)
if( (*bp >= 0) != (*(bp+1) >= 0) )
++n;
if( delaySmpPtr != NULL )
*delaySmpPtr = *bp;
return n;
}
VECT_OP_TYPE VECT_OP_FUNC(SquaredSum)( const VECT_OP_TYPE* bp, unsigned bn )
{
VECT_OP_TYPE sum = 0;
const VECT_OP_TYPE* ep = bp + bn;
for(; bp < ep; ++bp )
sum += *bp * *bp;
return sum;
}
VECT_OP_TYPE VECT_OP_FUNC(RMS)( const VECT_OP_TYPE* bp, unsigned bn, unsigned wndSmpCnt )
{
const VECT_OP_TYPE* ep = bp + bn;
if( bn==0 )
return 0;
assert( bn <= wndSmpCnt );
double sum = 0;
for(; bp < ep; ++bp )
sum += *bp * *bp;
return (VECT_OP_TYPE)sqrt(sum/wndSmpCnt);
}
VECT_OP_TYPE* VECT_OP_FUNC(RmsV)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* sp, unsigned sn, unsigned wndSmpCnt, unsigned hopSmpCnt )
{
const VECT_OP_TYPE* dep = dp + dn;
const VECT_OP_TYPE* sep = sp + sn;
VECT_OP_TYPE* rp = dp;
for(; dp<dep && sp<sep; sp+=hopSmpCnt)
*dp++ = VECT_OP_FUNC(RMS)( sp, cmMin(wndSmpCnt,sep-sp), wndSmpCnt );
VECT_OP_FUNC(Zero)(dp,dep-dp);
return rp;
}
VECT_OP_TYPE VECT_OP_FUNC(EuclidNorm)( const VECT_OP_TYPE* sp, unsigned sn )
{ return (VECT_OP_TYPE)sqrt( VECT_OP_FUNC(MultSumVV)(sp,sp,sn)); }
/*
From:http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/doc/voicebox/distitpf.html
[nf1,p2]=size(pf1);
p1=p2-1;
nf2=size(pf2,1);
nx= min(nf1,nf2);
r = pf1(1:nx,:)./pf2(1:nx,:);
q = r-log(r);
s = sum( q(:,2:p1),2) + 0.5 * (q(:,1)+q(:,p2))
d= s/p1-1;
*/
VECT_OP_TYPE VECT_OP_FUNC(ItakuraDistance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
VECT_OP_TYPE d = 0;
VECT_OP_TYPE r[ sn ];
VECT_OP_TYPE q[ sn ];
// r = pf1(1:nx,:)./pf2(1:nx,:);
VECT_OP_FUNC(DivVVV)(r,sn,s0p,s1p);
//q=log(r);
VECT_OP_FUNC(LogV)(q,sn,r);
//r = r - q = r - log(r)
VECT_OP_FUNC(SubVV)(r,sn,q);
//r = r - sn = r - log(r) - 1
VECT_OP_FUNC(SubVS)(r,sn,sn);
// d = sum(r);
d = VECT_OP_FUNC(Sum)(r,sn);
return (VECT_OP_TYPE)(d / sn);
//d = log( VECT_OP_FUNC(Sum)(r,sn) /sn );
//d -= VECT_OP_FUNC(Sum)(q,sn)/sn;
return d;
}
VECT_OP_TYPE VECT_OP_FUNC(CosineDistance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
VECT_OP_TYPE d0 = VECT_OP_FUNC(EuclidNorm)(s0p,sn);
VECT_OP_TYPE d1 = VECT_OP_FUNC(EuclidNorm)(s1p,sn);
if( d0 == 0 )
d0 = cmReal_MIN;
if( d1 == 0 )
d1 = cmReal_MIN;
return (VECT_OP_TYPE)(VECT_OP_FUNC(MultSumVV)(s0p,s1p,sn) / (d0 * d1));
}
VECT_OP_TYPE VECT_OP_FUNC(EuclidDistance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
double d = 0;
const VECT_OP_TYPE* sep = s0p + sn;
for(; s0p<sep; ++s0p,++s1p)
d += (*s0p - *s1p) * (*s0p - *s1p);
return (VECT_OP_TYPE)(sqrt(d));
}
VECT_OP_TYPE VECT_OP_FUNC(L1Distance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
double d = 0;
const VECT_OP_TYPE* sep = s0p + sn;
for(; s0p<sep; ++s0p,++s1p)
d += (VECT_OP_TYPE)fabs(*s0p - *s1p);
return d;
}
VECT_OP_TYPE VECT_OP_FUNC(MahalanobisDistance)( const VECT_OP_TYPE* x, unsigned D, const VECT_OP_TYPE* u, const VECT_OP_TYPE* invCovM )
{
VECT_OP_TYPE t[ D ];
VECT_OP_TYPE d[ D ];
// t[] = x[] - u[];
VECT_OP_FUNC(SubVVV)(t,D,x,u);
// d[1,D] = t[1,D] * covM[D,D]
VECT_OP_FUNC(MultVVM)( d, D, t, D, invCovM );
// d = sum(d[].*t[])
VECT_OP_TYPE dist = VECT_OP_FUNC(MultSumVV)(d,t,D);
return (VECT_OP_TYPE)sqrt(dist);
}
VECT_OP_TYPE VECT_OP_FUNC(KL_Distance)( const VECT_OP_TYPE* up, const VECT_OP_TYPE* sp, unsigned sn )
{
VECT_OP_TYPE v[ sn ];
VECT_OP_FUNC(DivVVV)(v,sn,up,sp); // v = up ./ sp
VECT_OP_FUNC(LogV)(v,sn,v); // v = log(v)
VECT_OP_FUNC(MultVV)(v,sn,up); // v *= up;
return VECT_OP_FUNC(Sum)(v,sn); // sum(v)
}
VECT_OP_TYPE VECT_OP_FUNC(KL_Distance2)( const VECT_OP_TYPE* up, const VECT_OP_TYPE* sp, unsigned sn )
{
VECT_OP_TYPE v0[ sn ];
VECT_OP_TYPE v1[ sn ];
VECT_OP_FUNC(NormalizeProbabilityVV)(v0,sn,up);
VECT_OP_FUNC(NormalizeProbabilityVV)(v1,sn,sp);
return VECT_OP_FUNC(KL_Distance)(v0,v1,sn);
}
/// If dv[scn] is non NULL then return the Euclidean distance from sv[scn] to each column of sm[srn,scn].
/// The function returns the index of the closest data point (column) in sm[].
unsigned VECT_OP_FUNC(EuclidDistanceVM)( VECT_OP_TYPE* dv, const VECT_OP_TYPE* sv, const VECT_OP_TYPE* sm, unsigned srn, unsigned scn )
{
unsigned minIdx = cmInvalidIdx;
VECT_OP_TYPE minDist = 0;
unsigned i = 0;
for(; i<scn; ++i )
{
VECT_OP_TYPE dist = VECT_OP_FUNC(EuclidDistance)(sv, sm + (i*srn), srn );
if( dv != NULL )
*dv++ = dist;
if( dist < minDist || minIdx == cmInvalidIdx )
{
minIdx = i;
minDist = dist;
}
}
return minIdx;
}
void VECT_OP_FUNC(DistVMM)( VECT_OP_TYPE* dM, VECT_OP_TYPE* mvV, unsigned* miV, unsigned rn, const VECT_OP_TYPE* s0M, unsigned s0cn, const VECT_OP_TYPE* s1M, unsigned s1cn, VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ), void* userPtr )
{
unsigned i,j,k;
// for each col in s0M[];
for(i=0,k=0; i<s0cn; ++i)
{
VECT_OP_TYPE min_val = VECT_OP_MAX;
unsigned min_idx = cmInvalidIdx;
// for each col in s1M[]
for(j=0; j<s1cn; ++j,++k)
{
// v = distance(s0M[:,i],s1M[:,j]
VECT_OP_TYPE v = distFunc( userPtr, s1M + (j*rn), s0M + (i*rn), rn );
if( dM != NULL )
dM[k] = v; // store distance
// track closest col in s1M[]
if( v < min_val || min_idx==cmInvalidIdx )
{
min_val = v;
min_idx = j;
}
}
if( mvV != NULL )
mvV[i] = min_val;
if( miV != NULL )
miV[i] = min_idx;
}
}
void VECT_OP_FUNC(SelectRandom) ( VECT_OP_TYPE *dM, unsigned* selIdxV, unsigned selIdxN, const VECT_OP_TYPE* sM, unsigned srn, unsigned scn )
{
bool freeFl = false;
unsigned i;
assert( selIdxN != 0 );
// if no selIdxV[] was given then create one
if( selIdxV == NULL )
{
selIdxV = cmMemAlloc( unsigned, selIdxN );
freeFl = true;
}
// select datapoints at random
cmVOU_UniqueRandom(selIdxV,selIdxN,scn);
// copy the data points into the output matrix
if( dM != NULL )
for(i=0; i<selIdxN; ++i)
{
assert( selIdxV[i] < scn );
VECT_OP_FUNC(Copy)( dM + (i*srn), srn, sM + selIdxV[i]*srn );
}
if( freeFl )
cmMemPtrFree(&selIdxV);
}
void VECT_OP_FUNC(_SelectDist)( VECT_OP_TYPE *dM, unsigned* selIdxV, unsigned selIdxN, const VECT_OP_TYPE* sM, unsigned srn, unsigned scn, VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ), void* userPtr, bool avgFl )
{
unsigned i;
unsigned dcn = 0;
bool freeFl = false;
assert( selIdxN > 0 );
if( dM == NULL )
{
dM = cmMemAllocZ( VECT_OP_TYPE, srn*selIdxN );
freeFl = true;
}
// allocate distM[scn,selIdxN] to hold the distances from each selected column to all columns in sM[]
VECT_OP_TYPE* distM = cmMemAllocZ( VECT_OP_TYPE, scn*selIdxN );
// sumV[] is a temp vector to hold the summed distances to from the selected columns to each column in sM[]
VECT_OP_TYPE* sumV = cmMemAllocZ( VECT_OP_TYPE, scn );
// select a random point from sM[] and copy it to the first column of dM[]
cmVOU_Random(&i,1,scn);
VECT_OP_FUNC(Copy)(dM, srn, sM + (i*srn));
if( selIdxV != NULL )
selIdxV[0] = i;
for(dcn=1; dcn<selIdxN; ++dcn)
{
// set distM[scn,dcn] with the dist from dM[dcn,srn] to each column in sM[]
VECT_OP_FUNC(DistVMM)( distM, NULL, NULL, srn, dM, dcn, sM, scn, distFunc, userPtr );
// sum the rows of distM[ scn, dcn ] into sumV[scn]
VECT_OP_FUNC(SumMN)( distM, scn, dcn, sumV );
if( avgFl )
VECT_OP_FUNC(DivVS)( sumV, scn, dcn );
// find the point in sM[] which has the greatest combined distance to all previously selected points.
unsigned maxIdx = VECT_OP_FUNC(MaxIndex)(sumV, scn, 1 );
// copy the point into dM[]
VECT_OP_FUNC(Copy)(dM + (dcn*srn), srn, sM + (maxIdx*srn));
if( selIdxV != NULL )
selIdxV[dcn] = maxIdx;
}
cmMemPtrFree(&distM);
cmMemPtrFree(&sumV);
if( freeFl )
cmMemPtrFree(&dM);
}
void VECT_OP_FUNC(SelectMaxDist)( VECT_OP_TYPE *dM, unsigned* selIdxV, unsigned selIdxN, const VECT_OP_TYPE* sM, unsigned srn, unsigned scn, VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ), void* userPtr )
{ VECT_OP_FUNC(_SelectDist)(dM,selIdxV,selIdxN,sM,srn,scn,distFunc,userPtr,false); }
void VECT_OP_FUNC(SelectMaxAvgDist)( VECT_OP_TYPE *dM, unsigned* selIdxV, unsigned selIdxN, const VECT_OP_TYPE* sM, unsigned srn, unsigned scn, VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ), void* userPtr )
{ VECT_OP_FUNC(_SelectDist)(dM,selIdxV,selIdxN,sM,srn,scn,distFunc,userPtr,true); }
#ifdef CM_VECTOP
VECT_OP_TYPE VECT_OP_FUNC(MultSumVV)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{ return VECT_OP_BLAS_FUNC(dot)(sn, s0p, 1, s1p, 1); }
#else
VECT_OP_TYPE VECT_OP_FUNC(MultSumVV)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
{
VECT_OP_TYPE sum = 0;
const VECT_OP_TYPE* sep = s0p + sn;
while(s0p<sep)
sum += *s0p++ * *s1p++;
return sum;
}
#endif
VECT_OP_TYPE VECT_OP_FUNC(MultSumVS)( const VECT_OP_TYPE* s0p, unsigned sn, VECT_OP_TYPE s1 )
{
VECT_OP_TYPE sum = 0;
const VECT_OP_TYPE* sep = s0p + sn;
while(s0p<sep)
sum += *s0p++ * s1;
return sum;
}
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultVMV)( VECT_OP_TYPE* dbp, unsigned mrn, const VECT_OP_TYPE* mp, unsigned mcn, const VECT_OP_TYPE* vp )
{
VECT_OP_BLAS_FUNC(gemv)( CblasColMajor, CblasNoTrans, mrn, mcn, 1.0, mp, mrn, vp, 1, 0.0, dbp, 1 );
return dbp;
}
#else
VECT_OP_TYPE* VECT_OP_FUNC(MultVMV)( VECT_OP_TYPE* dbp, unsigned mrn, const VECT_OP_TYPE* mp, unsigned mcn, const VECT_OP_TYPE* vp )
{
const VECT_OP_TYPE* dep = dbp + mrn;
VECT_OP_TYPE* dp = dbp;
const VECT_OP_TYPE* vep = vp + mcn;
// for each dest element
for(; dbp < dep; ++dbp )
{
const VECT_OP_TYPE* vbp = vp;
const VECT_OP_TYPE* mbp = mp++;
*dbp = 0;
// for each source vector row and src mtx col
while( vbp < vep )
{
*dbp += *mbp * *vbp++;
mbp += mrn;
}
}
return dp;
}
#endif
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultVVM)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* vp, unsigned vn, const VECT_OP_TYPE* mp )
{
VECT_OP_BLAS_FUNC(gemv)( CblasColMajor, CblasTrans, vn, dn, 1.0, mp, vn, vp, 1, 0.0, dbp, 1 );
return dbp;
}
#else
VECT_OP_TYPE* VECT_OP_FUNC(MultVVM)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* vp, unsigned vn, const VECT_OP_TYPE* mp )
{
unsigned i;
for(i=0; i<dn; ++i)
dbp[i] = VECT_OP_FUNC(MultSumVV)(vp,mp + (i*vn),vn);
return dbp;
}
#endif
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultVMtV)( VECT_OP_TYPE* dbp, unsigned mcn, const VECT_OP_TYPE* mp, unsigned mrn, const VECT_OP_TYPE* vp )
{
VECT_OP_BLAS_FUNC(gemv)( CblasColMajor, CblasTrans, mrn, mcn, 1.0, mp, mrn, vp, 1, 0.0, dbp, 1 );
return dbp;
}
#else
VECT_OP_TYPE* VECT_OP_FUNC(MultVMtV)( VECT_OP_TYPE* dbp, unsigned mcn, const VECT_OP_TYPE* mp, unsigned mrn, const VECT_OP_TYPE* vp )
{
const VECT_OP_TYPE* dep = dbp + mcn;
VECT_OP_TYPE* dp = dbp;
const VECT_OP_TYPE* vep = vp + mrn;
// for each dest element
for(; dbp < dep; ++dbp )
{
const VECT_OP_TYPE* vbp = vp;
*dbp = 0;
// for each source vector row and src mtx col
while( vbp < vep )
*dbp += *mp++ * *vbp++;
}
return dp;
}
#endif
VECT_OP_TYPE* VECT_OP_FUNC(MultDiagVMV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* mp, unsigned mcn, const VECT_OP_TYPE* vp )
{
VECT_OP_TYPE* rp = dbp;
const VECT_OP_TYPE* mep = mp + (dn*mcn);
// for each dest element
for(; mp < mep; mp += dn+1 )
*dbp++ = *vp++ * *mp;
return rp;
}
/*
Fortran Doc: http://www.netlib.org/blas/cgemm.f
C Doc: http://techpubs.sgi.com/library/tpl/cgi-bin/getdoc.cgi?cmd=getdoc&coll=0650&db=man&fname=3%20INTRO_CBLAS
C = alpha * op(A) * op(B) + beta * C
cblas_Xgemm(
order, enum CBLAS_ORDER {CblasRowMajor=101, CblasColMajor=102};
transposeA, enum CBLAS_TRANSPOSE { CblasNoTrans, CblasTrans, CBlasConjTrans }
transposeB,
M, row op(A) and rows C (i.e. rows of A 'after' optional transpose)
N, col op(B) and cols C (i.e. rows of B 'after' optional transpose)
K, col op(A) and rows op(B)
alpha, A scalar
A, pointer to source matrix A
lda, number of rows in A as it is stored in memory (assuming col major order)
B, pointer to source matrix B
ldb, number of rows in B as it is stored in memory (assuming col major order)
beta C scalar
C, pointer to destination matrix C
ldc number of rows in C as it is stored in memory (assuming col major order)
)
*/
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultMMM1)(VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE alpha, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned n, VECT_OP_TYPE beta, unsigned flags )
{
bool t0fl = cmIsFlag(flags,kTransposeM0Fl);
bool t1fl = cmIsFlag(flags,kTransposeM1Fl);
VECT_OP_BLAS_FUNC(gemm)(
CblasColMajor,
t0fl ? CblasTrans : CblasNoTrans,
t1fl ? CblasTrans : CblasNoTrans,
drn, dcn, n,
alpha,
m0, t0fl ? n : drn,
m1, t1fl ? dcn : n,
beta,
dbp, drn );
return dbp;
}
#else
// Not implemented.
#endif
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultMMM2)(VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE alpha, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned n, VECT_OP_TYPE beta, unsigned flags, unsigned dprn, unsigned m0prn, unsigned m1prn )
{
VECT_OP_BLAS_FUNC(gemm)(
CblasColMajor,
cmIsFlag(flags,kTransposeM0Fl) ? CblasTrans : CblasNoTrans,
cmIsFlag(flags,kTransposeM1Fl) ? CblasTrans : CblasNoTrans,
drn, dcn, n,
alpha,
m0, m0prn,
m1, m1prn,
beta,
dbp, dprn );
return dbp;
}
#else
// Not implemented.
#endif
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultMMM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned n )
{
VECT_OP_BLAS_FUNC(gemm)(
CblasColMajor,
CblasNoTrans, CblasNoTrans,
drn, dcn, n,
1.0, m0, drn,
m1, n,
0.0, dbp, drn );
return dbp;
}
#else
VECT_OP_TYPE* VECT_OP_FUNC(MultMMM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned m0cn_m1rn )
{
unsigned i;
for(i=0; i<dcn; ++i)
VECT_OP_FUNC(MultVMV)(dbp+(i*drn),drn,m0,m0cn_m1rn,m1+(i*m0cn_m1rn));
return dbp;
}
#endif
#ifdef CM_VECTOP
VECT_OP_TYPE* VECT_OP_FUNC(MultMMMt)(VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned m0cn_m1rn )
{
VECT_OP_BLAS_FUNC(gemm)( CblasColMajor, CblasNoTrans, CblasTrans,
drn, dcn, m0cn_m1rn,
1.0, m0, drn,
m1, dcn,
0.0, dbp, drn );
return dbp;
}
#else
VECT_OP_TYPE* VECT_OP_FUNC(MultMMMt)(VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* m0, const VECT_OP_TYPE* m1, unsigned m0cn_m1rn )
{
unsigned i,j,k;
VECT_OP_FUNC(Zero)(dbp,drn*dcn);
for(i=0; i<dcn; ++i)
for(j=0; j<drn; ++j)
for(k=0; k<m0cn_m1rn; ++k)
dbp[ i*drn + j ] += m0[ k*drn + j ] * m1[ k*dcn + i ];
return dbp;
}
#endif
VECT_OP_TYPE* VECT_OP_FUNC(PowVS)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE expo )
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp < ep; ++dp )
*dp = (VECT_OP_TYPE)pow(*dp,expo);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(PowVVS)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE expo )
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp < ep; ++dp,++sp )
*dp = (VECT_OP_TYPE)pow(*sp,expo);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(LogV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp )
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp <ep; ++dp,++sbp)
*dp = (VECT_OP_TYPE)log(*sbp);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(AmplToDbVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, VECT_OP_TYPE minDb )
{
VECT_OP_TYPE minVal = pow(10.0,minDb/20.0);
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp<ep; ++dp,++sbp)
*dp = *sbp<minVal ? minDb : 20.0 * log10(*sbp);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(DbToAmplVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp<ep; ++dp,++sbp)
*dp = pow(10.0,*sbp/20.0);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(PowToDbVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, VECT_OP_TYPE minDb )
{
VECT_OP_TYPE minVal = pow(10.0,minDb/10.0);
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp<ep; ++dp,++sbp)
*dp = *sbp<minVal ? minDb : 10.0 * log10(*sbp);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(DbToPowVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
{
VECT_OP_TYPE* dp = dbp;
VECT_OP_TYPE* ep = dp + dn;
for(; dp<ep; ++dp,++sbp)
*dp = pow(10.0,*sbp/10.0);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandSymPosDef)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE* t )
{
unsigned i,j;
bool fl = t == NULL;
if( fl )
t = cmMemAlloc( VECT_OP_TYPE , dn*dn );
do
{
// intialize t[] as a square symetric matrix with random values
for(i=0; i<dn; ++i)
for(j=i; j<dn; ++j)
{
VECT_OP_TYPE v = (VECT_OP_TYPE)rand()/RAND_MAX;
t[ (i*dn) + j ] = v;
if( i != j )
t[ (j*dn) + i ] = v;
}
// square t[] to force the eigenvalues to be positive
VECT_OP_FUNC(MultMMM)(dbp,dn,dn,t,t,dn);
VECT_OP_FUNC(Copy)(t,dn*dn,dbp);
// test that func is positive definite
}while( VECT_OP_FUNC(Chol)(t,dn)==NULL );
if( fl )
cmMemFree(t);
return dbp;
}
// Calculate the determinant of a matrix previously factored by
// the lapack function dgetrf_()
VECT_OP_TYPE VECT_OP_FUNC(LUDet)( const VECT_OP_TYPE* lu, const int_lap_t* ipiv, int rn )
{
VECT_OP_TYPE det1 = 1;
int det2 = 0;
int i;
for(i=0; i<rn; ++i)
{
if( ipiv != NULL && ipiv[i] != (i+1) )
det1 = -det1;
det1 = lu[ (i*rn) + i ] * det1;
if( det1 == 0 )
break;
while( fabs(det1) <= 1 )
{
det1 *= 10;
det2 -= 1;
}
//continue;
while( fabs(det1) >= 10 )
{
det1 /= 10;
det2 += 1;
}
}
// Here's where underflow or overflow might happen.
// Enable floating point exception handling to trap.
det1 *= pow(10.0,det2);
return det1;
}
// take the inverse of a matrix factored via lapack dgetrf_()
VECT_OP_TYPE* VECT_OP_FUNC(LUInverse)(VECT_OP_TYPE* dp, int_lap_t* ipiv, int drn )
{
int_lap_t ispec = 1;
int_lap_t rn = drn;
int_lap_t n1 = drn;
int_lap_t n2 = drn;
int_lap_t n3 = drn;
int_lap_t n4 = drn;
char funcNameStr[] = {"DGETRI"};
// Calculate the NB factor for LWORK -
// The two args are length of string args 'funcNameStr' and ' '.
// It is not clear how many 'n' args are requred so all are passed set to 'drn'
#ifdef OS_OSX
int nb = ilaenv_(&ispec, funcNameStr, " ", &n1,&n2,&n3,&n4 );
#else
int nb = ilaenv_(&ispec, funcNameStr, " ", &n1,&n2,&n3,&n4, strlen(funcNameStr), 1 );
#endif
VECT_OP_TYPE w[drn * nb]; // allocate working memory
int_lap_t info;
// calculate inv(A) base on LU factorization
VECT_OP_LAP_FUNC(getri_)(&rn,dp,&rn,ipiv,w,&rn,&info);
assert(info==0);
return info ==0 ? dp : NULL;
}
VECT_OP_TYPE VECT_OP_FUNC(DetM)( const VECT_OP_TYPE* sp, unsigned srn )
{
int_lap_t arn = srn;
VECT_OP_TYPE A[ arn * arn ];
int_lap_t ipiv[ arn ];
int_lap_t info;
VECT_OP_FUNC(Copy)(A,arn*arn,sp);
// PLU factor
VECT_OP_LAP_FUNC(getrf_)(&arn,&arn,A,&arn,ipiv,&info);
if( info == 0 )
return VECT_OP_FUNC(LUDet)(A,ipiv,arn);
return 0;
}
VECT_OP_TYPE VECT_OP_FUNC(DetDiagM)( const VECT_OP_TYPE* sp, unsigned srn )
{ return VECT_OP_FUNC(LUDet)(sp,NULL,srn); }
VECT_OP_TYPE VECT_OP_FUNC(LogDetM)( const VECT_OP_TYPE* sp, unsigned srn )
{
cmReal_t det = 0;
unsigned ne2 = srn * srn;
VECT_OP_TYPE U[ne2];
const VECT_OP_TYPE* up = U;
const VECT_OP_TYPE* ep = up + ne2;
VECT_OP_FUNC(Copy)(U,ne2,sp);
VECT_OP_FUNC(Chol)(U,srn);
for(; up<ep; up += (srn+1) )
det += log(*up);
return 2*det;
}
VECT_OP_TYPE VECT_OP_FUNC(LogDetDiagM)( const VECT_OP_TYPE* sp, unsigned srn )
{ return log(VECT_OP_FUNC(DetDiagM)(sp,srn)); }
VECT_OP_TYPE* VECT_OP_FUNC(InvM)( VECT_OP_TYPE* dp, unsigned drn )
{
int_lap_t rn = drn;
int_lap_t ipiv[ rn ];
int_lap_t info;
// PLU factor
VECT_OP_LAP_FUNC(getrf_)(&rn,&rn,dp,&rn,ipiv,&info);
if( info == 0 )
return VECT_OP_FUNC(LUInverse)(dp,ipiv,rn );
return NULL;
}
VECT_OP_TYPE* VECT_OP_FUNC(InvDiagM)( VECT_OP_TYPE* dp, unsigned drn )
{
const VECT_OP_TYPE* dep = dp + (drn*drn);
VECT_OP_TYPE* rp = dp;
for(; dp < dep; dp += drn+1 )
{
*dp = 1.0 / *dp;
// if any element on the diagonal is zero then the
// determinant is zero and the matrix is not invertable
if( *dp == 0 )
break;
}
return dp < dep ? NULL : rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(SolveLS)( VECT_OP_TYPE* A, unsigned an, VECT_OP_TYPE* B, unsigned bcn )
{
int_lap_t aN = an;
int_lap_t bcN = bcn;
int_lap_t ipiv[ an ];
int_lap_t info = 0;
VECT_OP_LAP_FUNC(gesv_)(&aN,&bcN,(VECT_OP_TYPE*)A,&aN,ipiv,B,&aN,&info);
return info == 0 ? B : NULL;
}
VECT_OP_TYPE* VECT_OP_FUNC(Chol)(VECT_OP_TYPE* A, unsigned an )
{
char uplo = 'U';
int_lap_t N = an;
int_lap_t lda = an;
int_lap_t info = 0;
VECT_OP_LAP_FUNC(potrf_(&uplo,&N,(VECT_OP_TYPE*)A,&lda,&info));
return info == 0 ? A : NULL;
}
VECT_OP_TYPE* VECT_OP_FUNC(CholZ)(VECT_OP_TYPE* A, unsigned an )
{
unsigned i,j;
VECT_OP_FUNC(Chol)(A,an);
// zero the lower triangle of A
for(i=0; i<an; ++i)
for(j=i+1; j<an; ++j)
A[ (i*an) + j ] = 0;
return A;
}
VECT_OP_TYPE VECT_OP_FUNC(FracAvg)( double bi, double ei, const VECT_OP_TYPE* sbp, unsigned sn )
{
unsigned bii = cmMax(0,cmMin(sn-1,(unsigned)ceil(bi)));
unsigned eii = cmMax(0,cmMin(sn,(unsigned)floor(ei)+1));
double begW = bii - bi;
double endW = eii - floor(ei);
double cnt = eii - bii;
double sum = (double)VECT_OP_FUNC(Sum)(sbp+bii,eii-bii);
if( begW>0 && bii > 0 )
{
cnt += begW;
sum += begW * sbp[ bii-1 ];
}
if( endW>0 && eii+1 < sn )
{
cnt += endW;
sum += endW * sbp[ eii+1 ];
}
return (VECT_OP_TYPE)(sum / cnt);
}
VECT_OP_TYPE* VECT_OP_FUNC(DownSampleAvg)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
unsigned i = 0;
double fact = (double)sn / dn;
assert( sn >= dn );
for(i=0; dbp < dep; ++i )
*dbp++ = VECT_OP_FUNC(FracAvg)( fact*i, fact*(i+1), sbp, sn );
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(UpSampleInterp)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn )
{
const VECT_OP_TYPE* dep = dbp + dn;
const VECT_OP_TYPE* sep = sbp + sn;
VECT_OP_TYPE* rp = dbp;
double fact = (double)sn / dn;
double phs = 0;
assert( sn <= dn );
while( dbp<dep )
{
if( sbp < sep )
*dbp++ = (VECT_OP_TYPE)((*sbp) + (phs * ((*(sbp+1)) - (*sbp))));
else
*dbp++ = (*(sep-1));
phs += fact;
while( phs > 1.0 )
{
phs -= 1.0;
sbp++;
}
}
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(FitToSize)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn )
{
if( dn == sn )
return VECT_OP_FUNC(Copy)(dbp,dn,sbp);
if( dn < sn )
return VECT_OP_FUNC(DownSampleAvg)(dbp,dn,sbp,sn);
return VECT_OP_FUNC(UpSampleInterp)(dbp,dn,sbp,sn);
}
VECT_OP_TYPE* VECT_OP_FUNC(LinearMap)(VECT_OP_TYPE* dV, unsigned dn, VECT_OP_TYPE* sV, unsigned sn )
{
if( dn == sn )
{
memcpy(dV,sV,dn*sizeof(VECT_OP_TYPE));
return dV;
}
unsigned i,j,k;
// if stretching
if( dn > sn )
{
VECT_OP_TYPE f_n = (VECT_OP_TYPE)dn/sn;
VECT_OP_TYPE f_nn = f_n;
unsigned i_n = floor(f_n);
k = 0;
i = 0;
// for each set of ceiling(dn/sn) dst values
while(1)
{
// repeat floor(dn/sn) src val into dst
for(j=0; j<i_n; ++j,++i)
dV[i] = sV[k];
if( k + 1 == sn )
break;
// interpolate between the cur and nxt source value
VECT_OP_TYPE w = f_nn - floor(f_nn);
dV[i] = sV[k] + w * (sV[k+1]-sV[k]);
++i;
++k;
i_n = floor(f_n - (1.0-w));
f_nn += f_n;
}
}
else // if shrinking
{
VECT_OP_TYPE f_n = (VECT_OP_TYPE)sn/dn;
VECT_OP_TYPE f_nn = f_n;
unsigned i_n = floor(f_n);
k = 0;
i = 0;
VECT_OP_TYPE acc = 0;
// for each seq of ceil(sn/dn) src values
while(1)
{
// accum first floor(sn/dn) src values
for(j=0; j<i_n; ++j,++i)
acc += sV[i];
if( k == dn-1 )
{
dV[k] = acc/f_n;
break;
}
// interpolate frac of last src value
VECT_OP_TYPE w = f_nn - floor(f_nn);
// form avg
dV[k] = (acc + (w*sV[i]))/f_n;
// reload acc with inverse frac of src value
acc = (1.0-w) * sV[i];
++i;
++k;
i_n = floor(f_n-(1.0-w));
f_nn += f_n;
}
}
return dV;
}
VECT_OP_TYPE* VECT_OP_FUNC(Random)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE minVal, VECT_OP_TYPE maxVal )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* dp =dbp;
double fact = (maxVal - minVal)/RAND_MAX;
while( dbp < dep )
*dbp++ = fact * rand() + minVal;
return dp;
}
unsigned* VECT_OP_FUNC(WeightedRandInt)( unsigned *dbp, unsigned dn, const VECT_OP_TYPE* wp, unsigned wn )
{
unsigned i,j;
VECT_OP_TYPE a[ wn ];
// form bin boundaries by taking a cum. sum of the weight values.
VECT_OP_FUNC(CumSum)(a,wn,wp);
for(j=0; j<dn; ++j)
{
// gen a random number from a uniform distribution betwen 0 and the max value from the cumsum.
VECT_OP_TYPE rv = (VECT_OP_TYPE)rand() * a[wn-1] / RAND_MAX;
// find the bin the rv falls into
for(i=0; i<wn-1; ++i)
if( rv <= a[i] )
{
dbp[j] = i;
break;
}
if(i==wn-1)
dbp[j]= wn-1;
}
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGauss)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE mean, VECT_OP_TYPE var )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
// The code below implements the Box-Muller uniform to
// Gaussian distribution transformation. In rectangular
// coordinates this transform is defined as:
// y1 = sqrt( - 2.0 * log(x1) ) * cos( 2.0*M_PI*x2 )
// y2 = sqrt( - 2.0 * log(x1) ) * sin( 2.0*M_PI*x2 )
//
while( dbp < dep )
*dbp++ = sqrt( -2.0 * log((VECT_OP_TYPE)rand()/RAND_MAX)) * cos(2.0*M_PI*((VECT_OP_TYPE)rand()/RAND_MAX)) * var + mean;
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* varV )
{
VECT_OP_TYPE* rp = dbp;
const VECT_OP_TYPE* dep = dbp + dn;
while( dbp < dep )
VECT_OP_FUNC(RandomGauss)( dbp++, 1, *meanV++, *varV++ );
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussM)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* varV )
{
unsigned i;
for(i=0; i<cn; ++i)
VECT_OP_FUNC(RandomGaussV)( dbp+(i*rn), rn, meanV, varV );
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussDiagM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* covarM )
{
unsigned i,j;
for(i=0; i<dcn; ++i)
for(j=0; j<drn; ++j)
VECT_OP_FUNC(RandomGauss)(dbp + (i*drn)+j, 1, meanV[j], covarM[ (j*drn) + j]);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussNonDiagM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* covarM, VECT_OP_TYPE* t )
{
bool fl = t == NULL;
if( fl )
t = cmMemAlloc(VECT_OP_TYPE, drn * drn );
VECT_OP_FUNC(Copy)(t,drn*drn,covarM);
if( VECT_OP_FUNC(CholZ)(t,drn) == NULL )
{
// Cholesky decomposition failed - should try eigen analysis next
// From octave mvnrnd.m
// [E,Lambda]=eig(Sigma);
// if (min(diag(Lambda))<0),error('Sigma must be positive semi-definite.'),end
// U = sqrt(Lambda)*E';
assert(0);
}
/*
unsigned i,j;
for(i=0; i<drn; ++i)
{
for(j=0; j<drn; ++j)
printf("%f ",t[ (j*drn) + i]);
printf("\n");
}
*/
VECT_OP_FUNC(RandomGaussNonDiagM2)(dbp,drn,dcn,meanV,t);
if(fl)
cmMemFree(t);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussNonDiagM2)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* uM )
{
unsigned i;
for(i=0; i<dcn; ++i)
{
VECT_OP_TYPE r[ drn ];
VECT_OP_FUNC(RandomGauss)(r,drn,0,1); // r = randn(drn,1);
VECT_OP_FUNC(MultVVM)( dbp+(i*drn),drn,r,drn,uM); // dbp[:i] = r * uM;
VECT_OP_FUNC(AddVV)( dbp+(i*drn),drn,meanV); // dbp[:,i] += meanV;
}
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussMM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanM, const VECT_OP_TYPE* varM, unsigned K )
{
unsigned k;
unsigned D = drn;
unsigned N = dcn/K;
for(k=0; k<K; ++k)
VECT_OP_FUNC(RandomGaussM)( dbp + (k*N*D), drn, N, meanM + (k*D), varM + (k*D) );
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(CircleCoords)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE x, VECT_OP_TYPE y, VECT_OP_TYPE varX, VECT_OP_TYPE varY )
{
unsigned i;
for(i=0; i<dn; ++i)
{
double a = 2.0*M_PI*i/(dn-1);
dbp[ i ] = (VECT_OP_TYPE)(varX * cos(a) + x);
dbp[ i+dn ] = (VECT_OP_TYPE)(varY * sin(a) + y);
}
return dbp;
}
unsigned VECT_OP_FUNC(SynthSine)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
{
const VECT_OP_TYPE* dep = dbp + dn;
double rps = 2.0*M_PI*hz/srate;
while( dbp < dep )
*dbp++ = (VECT_OP_TYPE)sin( rps * phase++ );
return phase;
}
unsigned VECT_OP_FUNC(SynthCosine)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
{
const VECT_OP_TYPE* dep = dbp + dn;
double rps = 2.0*M_PI*hz/srate;
while( dbp < dep )
*dbp++ = (VECT_OP_TYPE)cos( rps * phase++ );
return phase;
}
unsigned VECT_OP_FUNC(SynthSquare)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt )
{
const VECT_OP_TYPE* dep = dbp + dn;
if( otCnt > 0 )
{
unsigned i;
// initialize the buffer with the fundamental
VECT_OP_FUNC(SynthSine)( dbp, dn, phase, srate, hz );
otCnt *= 2;
// sum in each additional harmonic
for(i=3; i<otCnt; i+=2)
{
VECT_OP_TYPE* dp = dbp;
double rps = 2.0 * M_PI * i * hz / srate;
unsigned phs = phase;
double g = 1.0/i;
while( dp < dep )
*dp++ += (VECT_OP_TYPE)(g * sin( rps * phs++ ));
}
}
return phase + (dep - dbp);
}
unsigned VECT_OP_FUNC(SynthTriangle)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt )
{
const VECT_OP_TYPE* dep = dbp + dn;
if( otCnt > 0 )
{
unsigned i;
// initialize the buffer with the fundamental
VECT_OP_FUNC(SynthCosine)( dbp, dn, phase, srate, hz );
otCnt *= 2;
// sum in each additional harmonic
for(i=3; i<otCnt; i+=2)
{
VECT_OP_TYPE* dp = dbp;
double rps = 2.0 * M_PI * i * hz / srate;
unsigned phs = phase;
double g = 1.0/(i*i);
while( dp < dep )
*dp++ += (VECT_OP_TYPE)(g * cos( rps * phs++ ));
}
}
return phase + (dep - dbp);
}
unsigned VECT_OP_FUNC(SynthSawtooth)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt )
{
const VECT_OP_TYPE* dep = dbp + dn;
if( otCnt > 0 )
{
unsigned i;
// initialize the buffer with the fundamental
VECT_OP_FUNC(SynthSine)( dbp, dn, phase, srate, hz );
// sum in each additional harmonic
for(i=2; i<otCnt; ++i)
{
VECT_OP_TYPE* dp = dbp;
double rps = 2.0 * M_PI * i * hz / srate;
unsigned phs = phase;
double g = 1.0/i;
while( dp < dep )
*dp++ += (VECT_OP_TYPE)(g * sin( rps * phs++ ));
}
VECT_OP_FUNC(MultVS)(dbp,dn,2.0/M_PI);
}
return phase + (dep - dbp);
}
unsigned VECT_OP_FUNC(SynthPulseCos)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt )
{
const VECT_OP_TYPE* dep = dbp + dn;
if( otCnt > 0 )
{
unsigned i;
// initialize the buffer with the fundamental
VECT_OP_FUNC(SynthCosine)( dbp, dn, phase, srate, hz );
// sum in each additional harmonic
for(i=1; i<otCnt; ++i)
{
VECT_OP_TYPE* dp = dbp;
double rps = 2.0 * M_PI * i * hz / srate;
unsigned phs = phase;
while( dp < dep )
*dp++ += (VECT_OP_TYPE)cos( rps * phs++ );
}
VECT_OP_FUNC(MultVS)(dbp,dn,1.0/otCnt);
}
return phase + (dep - dbp);
}
unsigned VECT_OP_FUNC(SynthImpulse)( VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
{
const VECT_OP_TYPE* dep = dbp + dn;
double pi2 = 2.0*M_PI;
double rps = pi2*hz/srate;
double v0,v1 = fmod( rps * phase, pi2);
if( dbp == dep )
return phase;
// the phase is set to zero when the first output should be a 1
if( phase == 0 )
{
*dbp++ = 1;
++phase;
}
while( dbp < dep )
{
// the phase vector will always be increasing
// the modulus of the phase vector will wrap with frequency 'hz'
v0 = fmod( rps * phase++, pi2 );
// notice when wrapping occurs
*dbp++ = (VECT_OP_TYPE)(v0 < v1);
v1 = v0;
}
// check if the next output should be a 1
// (this eliminates the problem of not having access to v1 on the next call to this function
if( fmod( rps * phase, pi2 ) < v1 )
phase = 0;
return phase;
}
VECT_OP_TYPE VECT_OP_FUNC(SynthPinkNoise)( VECT_OP_TYPE* dbp, unsigned n, VECT_OP_TYPE delaySmp )
{
const VECT_OP_TYPE* dep = dbp + n;
VECT_OP_TYPE tmp[ n ];
VECT_OP_FUNC(Random)(tmp,n,-1.0,1.0);
VECT_OP_TYPE* sp = tmp;
VECT_OP_TYPE reg = delaySmp;
for(; dbp < dep; ++sp)
{
*dbp++ = (*sp + reg)/2.0;
reg = *sp;
}
return *sp;
}
VECT_OP_TYPE* VECT_OP_FUNC(LinSpace)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE base, VECT_OP_TYPE limit )
{
unsigned i = 0;
for(; i<dn; ++i)
dbp[i] = base + i*(limit-base)/(dn-1);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(LinearToDb)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE mult )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
while( dbp < dep )
*dbp++ = (VECT_OP_TYPE)(mult * log10( VECT_OP_EPSILON + *sp++ ));
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(dBToLinear)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE mult )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
while( dbp < dep )
*dbp++ = (VECT_OP_TYPE)pow(10.0, *sp++ / mult );
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(AmplitudeToDb)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
{ return VECT_OP_FUNC(LinearToDb)(dbp,dn,sp,20.0); }
VECT_OP_TYPE* VECT_OP_FUNC(PowerToDb)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
{ return VECT_OP_FUNC(LinearToDb)(dbp,dn,sp,10.0); }
VECT_OP_TYPE* VECT_OP_FUNC(dBToAmplitude)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
{ return VECT_OP_FUNC(dBToLinear)( dbp,dn,sp,20); }
VECT_OP_TYPE* VECT_OP_FUNC(dBToPower)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
{ return VECT_OP_FUNC(dBToLinear)( dbp,dn,sp,10); }
unsigned VECT_OP_FUNC(SynthPhasor)(VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
{
const VECT_OP_TYPE* dep = dbp + dn;
while( dbp < dep )
*dbp++ = (VECT_OP_TYPE)fmod( (hz * phase++)/srate, 1.0 );
return phase;
}
VECT_OP_TYPE VECT_OP_FUNC(KaiserBetaFromSidelobeReject)( double sidelobeRejectDb )
{
double beta;
if( sidelobeRejectDb < 13.26 )
sidelobeRejectDb = 13.26;
else
if( sidelobeRejectDb > 120.0)
sidelobeRejectDb = 120.0;
if( sidelobeRejectDb < 60.0 )
beta = (0.76609 * pow(sidelobeRejectDb - 13.26,0.4)) + (0.09834*(sidelobeRejectDb-13.26));
else
beta = 0.12438 * (sidelobeRejectDb + 6.3);
return (VECT_OP_TYPE)beta;
}
VECT_OP_TYPE VECT_OP_FUNC(KaiserFreqResolutionFactor)( double sidelobeRejectDb )
{ return (6.0 * (sidelobeRejectDb + 12.0))/155.0; }
VECT_OP_TYPE* VECT_OP_FUNC(Kaiser)( VECT_OP_TYPE* dbp, unsigned n, double beta )
{
bool zeroFl = false;
int M = 0;
double den = cmBessel0(beta); // wnd func denominator
int cnt = n;
int i;
assert( n >= 3 );
// force ele cnt to be odd
if( cmIsEvenU(cnt) )
{
cnt--;
zeroFl = true;
}
// at this point cnt is odd and >= 3
// calc half the window length
M = (int)((cnt - 1.0)/2.0);
double Msqrd = M*M;
for(i=0; i<cnt; i++)
{
double v0 = (double)(i - M);
double num = cmBessel0(beta * sqrt(1.0 - ((v0*v0)/Msqrd)));
dbp[i] = (VECT_OP_TYPE)(num/den);
}
if( zeroFl )
dbp[cnt] = 0.0; // zero the extra element in the output array
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Gaussian)( VECT_OP_TYPE* dbp, unsigned dn, double mean, double variance )
{
int M = dn-1;
double sqrt2pi = sqrt(2.0*M_PI);
unsigned i;
for(i=0; i<dn; i++)
{
double arg = ((((double)i/M) - 0.5) * M);
arg = pow( (double)(arg-mean), 2.0);
arg = exp( -arg / (2.0*variance));
dbp[i] = (VECT_OP_TYPE)(arg / (sqrt(variance) * sqrt2pi));
}
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Hamming)( VECT_OP_TYPE* dbp, unsigned dn )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* dp = dbp;
double fact = 2.0 * M_PI / (dn-1);
unsigned i;
for(i=0; dbp < dep; ++i )
*dbp++ = (VECT_OP_TYPE)(.54 - (.46 * cos(fact*i)));
return dp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Hann)( VECT_OP_TYPE* dbp, unsigned dn )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* dp = dbp;
double fact = 2.0 * M_PI / (dn-1);
unsigned i;
for(i=0; dbp < dep; ++i )
*dbp++ = (VECT_OP_TYPE)(.5 - (.5 * cos(fact*i)));
return dp;
}
VECT_OP_TYPE* VECT_OP_FUNC(HannMatlab)( VECT_OP_TYPE* dbp, unsigned dn )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* dp = dbp;
double fact = 2.0 * M_PI / (dn+1);
unsigned i;
for(i=0; dbp < dep; ++i )
*dbp++ = (VECT_OP_TYPE)(0.5*(1.0-cos(fact*(i+1))));
return dp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Triangle)( VECT_OP_TYPE* dbp, unsigned dn )
{
unsigned n = dn/2;
VECT_OP_TYPE incr = 1.0/n;
VECT_OP_FUNC(Seq)(dbp,n,0,incr);
VECT_OP_FUNC(Seq)(dbp+n,dn-n,1,-incr);
return dbp;
}
VECT_OP_TYPE* VECT_OP_FUNC(GaussWin)( VECT_OP_TYPE* dbp, unsigned dn, double arg )
{
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE* rp = dbp;
int N = (dep - dbp) - 1;
int n = -N/2;
if( N == 0 )
*dbp = 1.0;
else
{
while( dbp < dep )
{
double a = (arg * n++) / (N/2);
*dbp++ = (VECT_OP_TYPE)exp( -(a*a)/2 );
}
}
return rp;
}
VECT_OP_TYPE* VECT_OP_FUNC(Filter)(
VECT_OP_TYPE* y,
unsigned yn,
const VECT_OP_TYPE* x,
unsigned xn,
cmReal_t b0,
const cmReal_t* b,
const cmReal_t* a,
cmReal_t* d,
unsigned dn )
{
int i,j;
VECT_OP_TYPE y0 = 0;
unsigned n = cmMin( yn, xn );
// This is a direct form II algorithm based on the MATLAB implmentation
// http://www.mathworks.com/access/helpdesk/help/techdoc/ref/filter.html#f83-1015962
for(i=0; i<n; ++i)
{
y[i] = (x[i] * b0) + d[0];
y0 = y[i];
for(j=0; j<dn; ++j)
d[j] = (b[j] * x[i]) - (a[j] * y0) + d[j+1];
}
// if fewer input samples than output samples - zero the end of the output buffer
if( yn > xn )
VECT_OP_FUNC(Fill)(y+i,yn-i,0);
return y;
}
VECT_OP_TYPE* VECT_OP_FUNC(FilterFilter)(struct cmFilter_str* f, cmRC_t (*func)( struct cmFilter_str* f, const VECT_OP_TYPE* x, unsigned xn, VECT_OP_TYPE* y, unsigned yn ), const cmReal_t bb[], unsigned bn, const cmReal_t aa[], unsigned an, const VECT_OP_TYPE* x, unsigned xn, VECT_OP_TYPE* y, unsigned yn )
{
int i,j;
int nfilt = cmMax(bn,an);
int nfact = 3*(nfilt-1);
const cmReal_t* a = aa;
const cmReal_t* b = bb;
cmReal_t* m = NULL;
cmReal_t* p;
unsigned zn = (nfilt-1)*(nfilt-1);
unsigned mn = 2*zn; // space for mtx z0 and z1
mn += nfilt; // space for zero padded coeff vector
mn += 2*nfact; // space for begin/end sequences
if( nfact >= xn )
{
return cmOkRC;
}
m = cmMemAllocZ( cmReal_t, mn );
p = m;
cmReal_t* z0 = p;
p += zn;
cmReal_t* z1 = p;
p += zn;
cmReal_t* s0 = p;
p += nfact;
cmReal_t* s1 = p;
p += nfact;
// zero pad the shorter coeff vect
if( bn < nfilt )
{
cmVOR_Copy(p,bn,bb);
b = p;
p += nfilt;
}
else
if( an < nfilt )
{
cmVOR_Copy(p,an,aa);
a = p;
p += nfilt;
}
// z0=eye(nfilt-1)
cmVOR_Identity(z0,nfilt-1,nfilt-1);
// z1=[eye(nfilt-1,nfilt-2); zeros(1,nfilt-1)];
cmVOR_Identity(z1,nfilt-1,nfilt-2);
// z0(:,1) -= a(:)
for(i=0; i<nfilt-1; ++i)
z0[i] -= -a[i+1];
// z0(:,2:end) -= z1;
for(i=1; i<nfilt-1; ++i)
for(j=0; j<nfilt-1; ++j)
z0[ (i*(nfilt-1)) + j ] -= z1[ ((i-1)*(nfilt-1)) + j ];
// z1 = b - (a * b[0])
for(i=1; i<nfilt; ++i)
z1[i-1] = b[i] - (a[i] * b[0]);
// z1 = z0\z1
cmVOR_SolveLS(z0,nfilt-1,z1,1);
// if yn<xn then truncate x.
xn = cmMin(xn,yn);
yn = xn;
// fill in the beginning sequence
for(i=0; i<nfact; ++i)
s0[i] = 2*x[0] - x[ nfact-i ];
// fill in the ending sequence
for(i=0; i<nfact; ++i)
s1[i] = 2*x[xn-1] - x[ xn-2-i ];
cmVOR_MultVVS( z0, nfact, z1, s0[0]);
unsigned pn = cmMin(1024,xn);
//acFilter* f = cmFilterAlloc(c,NULL,b,bn,a,an,pn,z0);
cmFilterInit(f,b,bn,a,an,pn,z0);
const VECT_OP_TYPE* xx = x;
for(j=0; j<2; ++j)
{
unsigned n = pn;
// filter begining sequence
cmFilterExecR(f,s0,nfact,s0,nfact);
// filter middle sequence
for(i=0; i<xn; i+=n)
{
n = cmMin(pn,xn-i);
func(f,xx+i,n,y+i,n);
}
// filter ending sequence
cmFilterExecR(f,s1,nfact,s1,nfact);
// flip all the sequences
cmVOR_Flip(s0,nfact);
cmVOR_Flip(s1,nfact);
VECT_OP_FUNC(Flip)(y,yn);
if( j==0)
{
// swap the begin and end sequences
cmReal_t* t = s0;
s0 = s1;
s1 = t;
xx = y;
cmVOR_MultVVS( z0, nfact, z1, s0[0]);
cmFilterInit(f,b,bn,a,an,pn,z0);
}
}
//cmFilterFree(&f);
cmMemPtrFree(&m);
return y;
}
VECT_OP_TYPE* VECT_OP_FUNC(LP_Sinc)(VECT_OP_TYPE* dp, unsigned dn, double srate, double fcHz, unsigned flags )
{
VECT_OP_TYPE* rp = dp;
int dM = dn % 2; // dM is used to handle odd length windows
int M = (dn - dM)/2;
int Mi = -M;
double signFact = cmIsFlag(flags, kHighPass_LPSincFl) ? -0.5 : 0.5;
double phsFact = 2.0 * M_PI * fcHz / srate;
double sum = 0;
M += dM;
//printf("M=%i Mi=%i sign:%f phs:%f\n",M,Mi,signFact,phsFact);
for(; Mi<M; ++Mi,++dp)
{
double phs = phsFact * Mi;
*dp = Mi == 0 ? 0.5 : signFact * sin(phs)/phs;
sum += *dp;
}
if( cmIsFlag(flags,kNormalize_LPSincFl) )
VECT_OP_FUNC(DivVS)(rp,dn,sum);
return rp;
}
VECT_OP_TYPE VECT_OP_FUNC(ComplexDetect)(const VECT_OP_TYPE* mag0V, const VECT_OP_TYPE* mag1V, const VECT_OP_TYPE* phs0V, const VECT_OP_TYPE* phs1V, const VECT_OP_TYPE* phs2V, unsigned binCnt )
{
double sum = 0;
const VECT_OP_TYPE* ep = mag0V + binCnt;
unsigned i = 0;
for(; mag0V < ep; ++i )
{
// calc phase deviation from expected
double dev_rads = *phs0V++ - (2 * *phs1V++) + *phs2V++;
// map deviation into range: -pi to pi
//double dev_rads1 = mod(dev_rads0 + M_PI, -2*M_PI ) + M_PI;
while( dev_rads > M_PI)
dev_rads -= 2*M_PI;
while( dev_rads < -M_PI)
dev_rads += 2*M_PI;
// convert into rect coord's
double m1r = *mag1V++;
double m0r = *mag0V * cos(dev_rads);
double m0i = *mag0V++ * sin(dev_rads);
// calc the combined amplitude and phase deviation
// sum += hypot( m1 - (m0 * e^(-1*dev_rads)));
sum += hypot( m1r-m0r, -m0i );
}
return (VECT_OP_TYPE)sum;
}
VECT_OP_TYPE* VECT_OP_FUNC(MelMask)( VECT_OP_TYPE* maskMtx, unsigned filterCnt, unsigned binCnt, double srate, unsigned flags )
{
unsigned fi,bi;
double mxh = srate/2.0; // nyquist
double dh = mxh/(binCnt-1) ; // binHz
double mxm = 1127.0 * log( 1.0 + mxh/700.0); // max mel value in Hz
double dm = mxm / (filterCnt+1); // avg mel band hz
double sum = 0;
for(fi=0; fi<filterCnt; ++fi)
{
double m = (fi+1) * dm;
// calc min/center/max frequencies for this band
double minHz = 700.0 * (exp((m-dm)/1127.01048)-1.0);
double ctrHz = 700.0 * (exp( m /1127.01048)-1.0);
double maxHz = 700.0 * (exp((m+dm)/1127.01048)-1.0);
// shift the band min/ctr/max to the nearest bin ctr frequency
if( cmIsFlag(flags,kShiftMelFl) )
{
unsigned i;
i = (unsigned)floor(minHz/dh);
minHz = minHz - (dh*i) < dh*(i+1) - minHz ? dh*i : dh*(i+1);
i = (unsigned)floor(ctrHz/dh);
ctrHz = ctrHz - (dh*i) < dh*(i+1) - ctrHz ? dh*i : dh*(i+1);
i = (unsigned)floor(maxHz/dh);
maxHz = maxHz - (dh*i) < dh*(i+1) - maxHz ? dh*i : dh*(i+1);
}
// calc the height of the triangle - such that all bands have equal area
double a = 2.0/(maxHz - minHz);
for(bi=0; bi<binCnt; ++bi)
{
double h = bi*dh;
unsigned mi = bi*filterCnt + fi;
if( h < minHz || h > maxHz )
maskMtx[mi] = 0;
else
{
if( h <= ctrHz )
maskMtx[mi] = a * (h - minHz)/(ctrHz-minHz);
else
maskMtx[mi] = a * (maxHz - h)/(maxHz-ctrHz);
sum += maskMtx[mi];
}
}
}
if( cmIsFlag(flags,kNormalizeMelFl) )
VECT_OP_FUNC(DivVS)( maskMtx, (filterCnt*binCnt), sum );
return maskMtx;
}
unsigned VECT_OP_FUNC(BarkMap)(unsigned* binIdxV, unsigned* cntV, unsigned bandCnt, unsigned binCnt, double srate )
{
if( bandCnt == 0 )
return 0;
//zwicker & fastl: psychoacoustics 1999, page 159
double bandUprHz[] = { 100, 200, 300, 400, 510, 630, 770, 920, 1080, 1270, 1480, 1720, 2000, 2320, 2700, 3150, 3700, 4400, 5300, 6400, 7700, 9500, 12000, 15500 };
unsigned hn = sizeof(bandUprHz)/sizeof(double);
unsigned i, bi = 0;
bandCnt = cmMin(hn,bandCnt);
binIdxV[0] = 0;
cntV[0] = 1;
for(i=1; bi < bandCnt && i<binCnt; ++i)
{
double hz = srate * i / (2 * (binCnt-1));
if( hz <= bandUprHz[bi] )
cntV[bi]++;
else
{
//printf("%i %i %i %f\n",bi,binIdxV[bi],cntV[bi],bandUprHz[bi]);
++bi;
if( bi < bandCnt )
{
binIdxV[bi] = i;
cntV[bi] = 1;
}
}
}
return bi;
}
VECT_OP_TYPE* VECT_OP_FUNC(TriangleMask)(VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, const VECT_OP_TYPE* ctrHzV, VECT_OP_TYPE binHz, VECT_OP_TYPE stSpread, const VECT_OP_TYPE* lfV, const VECT_OP_TYPE* hfV )
{
unsigned i,j;
VECT_OP_TYPE v0[ bandCnt ];
VECT_OP_TYPE v1[ bandCnt ];
// if no lower/upper band limits were give use a fixed semitone band width
if( lfV==NULL || hfV==NULL)
{
for(i=0; i<bandCnt; ++i)
{
v0[i] = ctrHzV[i] * pow(2.0,-stSpread/12.0);
v1[i] = ctrHzV[i] * pow(2.0, stSpread/12.0);
}
lfV = v0;
hfV = v1;
}
VECT_OP_FUNC(Zero)(maskMtx,bandCnt*binCnt);
// for each band
for(i=0; i<bandCnt; ++i)
{
// calc bin index of first possible bin in this band
// j = (unsigned)floor(lfV[i] / binHz);
double binHz_j = 0;
// for each bin whose ctr frq is <= the band upper limit
for(j=0; j<binCnt; ++j)
{
double v;
// if bin[j] is inside the lower leg of the triangle
if( lfV[i] <= binHz_j && binHz_j <= ctrHzV[i] )
v = (binHz_j - lfV[i]) / cmMax(VECT_OP_MIN, ctrHzV[i] - lfV[i] );
else
// if bin[j] is inside the upper leg of the triangle
if( ctrHzV[i] < binHz_j && binHz_j <= hfV[i] )
v = (hfV[i] - binHz_j) / cmMax(VECT_OP_MIN, hfV[i] - ctrHzV[i] );
else
v = 0;
maskMtx[ (j*bandCnt)+i ] = v;
binHz_j = binHz * (j+1);
}
}
return maskMtx;
}
VECT_OP_TYPE* VECT_OP_FUNC(BarkMask)(VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, double binHz )
{
// -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 (23+1)
VECT_OP_TYPE b[]= {0, 50,150,250,350,450,570,700,840,1000,1170,1370,1600,1850,2150,2500,2900,3400,4000,4800,5800,7000,8500,10500,13500, 15500 };
bandCnt = cmMin(bandCnt,kDefaultBarkBandCnt);
VECT_OP_FUNC(TriangleMask)(maskMtx, bandCnt, binCnt, b+1, binHz, 0, b+0, b+2 );
return maskMtx;
}
VECT_OP_TYPE* VECT_OP_FUNC(TerhardtThresholdMask)(VECT_OP_TYPE* maskV, unsigned binCnt, double srate, unsigned flags )
{
unsigned i;
double c0 = cmIsFlag(flags,kModifiedTtmFl) ? 0.6 : 1.0;
double c1 = cmIsFlag(flags,kModifiedTtmFl) ? 0.5 : 6.5;
maskV[0]=0;
for(i=0; i<binCnt; ++i)
{
double hz = srate * i / (2 * (binCnt-1));
maskV[i] = pow(pow(10,(c0 * -3.64* pow(hz/1000,-0.8) + c1 * exp(-0.6 * pow(hz/1000 - 3.3,2)) - 0.001* pow(hz/1000,4))/20),2);
}
return maskV;
}
VECT_OP_TYPE* VECT_OP_FUNC(ShroederSpreadingFunc)(VECT_OP_TYPE* m, unsigned bandCnt, double srate)
{
int fi,bi;
for(fi=0; fi<bandCnt; ++fi)
for(bi=0; bi<bandCnt; ++bi )
m[ fi + (bi*bandCnt) ] = pow(10,(15.81 + 7.5 * ((fi-bi)+0.474)-17.5*pow(1+pow((fi-bi)+0.474,2),0.5))/10);
return m;
}
VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt )
{
VECT_OP_TYPE* dbp = dp;
double c0 = 1.0/sqrt(filtCnt/2); // row 1-coeffCnt factor
double c1 = c0 * sqrt(2)/2; // row 0 factor
unsigned i,j;
// for each column
for(i=0; i<filtCnt; ++i)
// for each row
for(j=0; j<coeffCnt; ++j)
*dp++ = (j==0 ? c1 : c0) * cos( (0.5 + i) * M_PI * j / filtCnt);
return dbp;
}
unsigned VECT_OP_FUNC(PeakIndexes)( unsigned* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE threshold )
{
unsigned pkCnt = 0;
const unsigned* dep = dbp + dn;
const VECT_OP_TYPE* sep = sbp + sn;
const VECT_OP_TYPE* s2p = sbp;
const VECT_OP_TYPE* s0p = s2p++;
const VECT_OP_TYPE* s1p = s2p++;
while( dbp < dep && s2p < sep )
{
if( (*s0p < *s1p) && (*s1p > *s2p) && (*s1p >= threshold) )
{
*dbp++ = s1p - sbp;
s0p = s2p++;
s1p = s2p++;
++pkCnt;
}
else
{
s0p = s1p;
s1p = s2p++;
}
}
return pkCnt;
}
unsigned VECT_OP_FUNC(BinIndex)( const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE v )
{
const VECT_OP_TYPE* sep = sbp + sn;
const VECT_OP_TYPE* bp = sbp;
sep--;
for(; sbp < sep; ++sbp )
if( *sbp <= v && v < *(sbp+1) )
return sbp - bp;
return cmInvalidIdx;
}
unsigned VECT_OP_FUNC(Kmeans)(
unsigned* classIdxV, // classIdxV[scn] - data point class assignments
VECT_OP_TYPE* centroidM, // centroidM[srn,K] - cluster centroids
unsigned K, // count of clusters
const VECT_OP_TYPE* sM, // sM[srn,scn] source data matrix
unsigned srn, // dimensionality of each data point
unsigned scn, // count of data points
const unsigned* selIdxV, // data subset selection id vector (optional)
unsigned selKey, // data subset selection key (optional)
bool initFromCentroidFl,// true if the starting centroids are in centroidM[]
VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ),
void* userDistPtr
)
{
unsigned D = srn; // data dimensionality
unsigned N = scn; // count of data points to cluster
unsigned iterCnt = 0;
unsigned ki;
unsigned i = 0;
unsigned selN = N;
// if a data point selection vector was given
if( selIdxV != NULL )
{
selN = 0;
for(i=0; i<N; ++i)
{
selN += selIdxV[i]==selKey;
classIdxV[i] = K;
}
}
assert(K<=selN);
// if the numer of datapoints and the number of clusters is the same
// make the datapoints the centroids and return
if( K == selN )
{
ki = 0;
for(i=0; i<N; ++i)
if( selIdxV==NULL || selIdxV[i]==selKey )
{
VECT_OP_FUNC(Copy)(centroidM+(ki*D),D,sM+(i*D));
classIdxV[ki] = ki;
++ki;
}
return 0;
}
// if centroidM[] has not been initialized with the starting centroid vectors.
if( initFromCentroidFl == false )
{
unsigned* kiV = cmMemAlloc( unsigned, N );
// select K unique datapoints at random as the initial centroids
cmVOU_RandomSeq(kiV,N);
for(i=0,ki=0; i<N && ki<K; ++i)
{
if( selIdxV==NULL || selIdxV[ kiV[i] ]==selKey )
{
VECT_OP_FUNC(Copy)( centroidM + (ki*D), D, sM + (kiV[i]*D) );
++ki;
}
}
cmMemPtrFree(&kiV);
}
unsigned* nV = cmMemAllocZ( unsigned,K);
while(1)
{
unsigned changeCnt = 0;
cmVOU_Zero(nV,K);
// for each data point - assign data point to a cluster
for(i=0; i<N; ++i)
if( selIdxV==NULL || selIdxV[i] == selKey )
{
// set ki with the index of the centroid closest to sM[:,i]
VECT_OP_FUNC(DistVMM)( NULL, NULL, &ki, D, sM + (i*srn), 1, centroidM, K, distFunc, userDistPtr );
assert(ki<K);
nV[ki]++;
changeCnt += ( ki != classIdxV[i] );
classIdxV[i] = ki;
}
// if no data points change classes then the centroids have converged
if( changeCnt == 0 )
break;
++iterCnt;
// zero the centroid matrix
VECT_OP_FUNC(Fill)(centroidM, D*K, 0 );
// update the centroids
for(ki=0; ki<K; ++ki)
{
unsigned n = 0;
// sum the all datapoints belonging to class ki
for(i=0; i<N; ++i)
if( classIdxV[i] == ki )
{
VECT_OP_FUNC(AddVV)(centroidM + (ki*D), D, sM + (i*srn) );
++n;
}
// convert the sum to a mean to form the centroid
if( n > 0 )
VECT_OP_FUNC(DivVS)(centroidM + (ki*D), D, n );
}
}
cmVOU_PrintL("class cnt:",NULL,1,K,nV);
cmMemPtrFree(&nV);
return iterCnt;
}
unsigned VECT_OP_FUNC(Kmeans2)(
unsigned* classIdxV, // classIdxV[scn] - data point class assignments
VECT_OP_TYPE* centroidM, // centroidM[srn,K] - cluster centroids
unsigned K, // count of clusters
const VECT_OP_TYPE* (*srcFunc)(void* userPtr, unsigned frmIdx ),
unsigned srn, // dimensionality of each data point
unsigned scn, // count of data points
void* userSrcPtr, // callback data for srcFunc
VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* s0V, const VECT_OP_TYPE* s1V, unsigned sn ),
void* distUserPtr,
int maxIterCnt,
int deltaStopCnt
)
{
unsigned D = srn; // data dimensionality
unsigned N = scn; // count of data points to cluster
unsigned iterCnt = 0;
unsigned ki;
unsigned i = 0;
const VECT_OP_TYPE* sp;
assert(K<N);
deltaStopCnt = cmMax(0,deltaStopCnt);
// nV[K] - class assignment vector
unsigned* nV = cmMemAllocZ( unsigned,2*K);
// roV[K] - read-only flag centroid
// centroids flagged as read-only will not be updated by the clustering routine
unsigned* roV = nV + K;
// copy the read-only flags into roV[K]
for(i=0; i<K; ++i)
roV[i] = classIdxV[i];
while(1)
{
unsigned changeCnt = 0;
cmVOU_Zero(nV,K);
// for each data point - assign data point to a cluster
for(i=0; i<N; ++i)
if((sp = srcFunc(userSrcPtr,i)) != NULL)
{
// set ki with the index of the centroid closest to sM[:,i]
VECT_OP_FUNC(DistVMM)( NULL, NULL, &ki, D, sp, 1, centroidM, K, distFunc, distUserPtr );
assert(ki<K);
// track the number of data points assigned to each centroid
nV[ki]++;
// track the number of data points which change classes
changeCnt += ( ki != classIdxV[i] );
// update the class that this data point belongs to
classIdxV[i] = ki;
}
// if the count of data points which changed classes is less than deltaStopCnt
// then the centroids have converged
if( changeCnt <= deltaStopCnt )
break;
if( maxIterCnt!=-1 && iterCnt>=maxIterCnt )
break;
// track the number of interations required to converge
++iterCnt;
fprintf(stderr,"%i:%i (", iterCnt,changeCnt );
for(i=0; i<K; ++i)
fprintf(stderr,"%i ",nV[i]);
fprintf(stderr,") ");
fflush(stderr);
// update the centroids
for(ki=0; ki<K; ++ki)
if( roV[ki]==0 )
{
unsigned n = 0;
VECT_OP_FUNC(Zero)(centroidM + (ki*D), D );
// sum the all datapoints belonging to class ki
for(i=0; i<N; ++i)
if( classIdxV[i] == ki && ((sp=srcFunc(userSrcPtr,i))!=NULL))
{
VECT_OP_FUNC(AddVV)(centroidM + (ki*D), D, sp );
++n;
}
// convert the sum to a mean to form the centroid
if( n > 0 )
VECT_OP_FUNC(DivVS)(centroidM + (ki*D), D, n );
}
}
cmMemPtrFree(&nV);
return iterCnt;
}
VECT_OP_TYPE* VECT_OP_FUNC(GaussPDF)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, VECT_OP_TYPE mean, VECT_OP_TYPE stdDev )
{
VECT_OP_TYPE* rp = dbp;
const VECT_OP_TYPE* dep = dbp + dn;
VECT_OP_TYPE var = stdDev * stdDev;
VECT_OP_TYPE fact0 = 1.0/sqrt(2*M_PI*var);
VECT_OP_TYPE fact1 = 2.0 * var;
for(; dbp < dep; ++sbp )
*dbp++ = fact0 * exp( -((*sbp-mean)*(*sbp-mean))/ fact1 );
return rp;
}
/// Evaluate a multivariate normal distribution defined by meanV[D] and covarM[D,D]
/// at the data points held in the columns of xM[D,N]. Return the evaluation
/// results in the vector yV[N].
bool VECT_OP_FUNC(MultVarGaussPDF)( VECT_OP_TYPE* yV, const VECT_OP_TYPE* xM, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* covarM, unsigned D, unsigned N, bool diagFl )
{
VECT_OP_TYPE det0;
// calc the determinant of the covariance matrix
if( diagFl )
// kpl 1/16/11 det0 = VECT_OP_FUNC(LogDetDiagM)(covarM,D);
det0 = VECT_OP_FUNC(DetDiagM)(covarM,D);
else
// kpl 1/16/11 det0 = VECT_OP_FUNC(LogDetM)(covarM,D);
det0 = VECT_OP_FUNC(DetM)(covarM,D);
assert(det0 != 0 );
if( det0 == 0 )
return false;
// calc the inverse of the covariance matrix
VECT_OP_TYPE icM[D*D];
VECT_OP_FUNC(Copy)(icM,D*D,covarM);
VECT_OP_TYPE* r;
if( diagFl )
r = VECT_OP_FUNC(InvDiagM)(icM,D);
else
r = VECT_OP_FUNC(InvM)(icM,D);
if( r == NULL )
return false;
VECT_OP_FUNC(MultVarGaussPDF2)( yV, xM, meanV, icM, det0, D, N, diagFl );
return true;
}
VECT_OP_TYPE* VECT_OP_FUNC(MultVarGaussPDF2)( VECT_OP_TYPE* yV, const VECT_OP_TYPE* xM, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* icM, VECT_OP_TYPE logDet, unsigned D, unsigned N, bool diagFl )
{
unsigned i;
double fact = (-(cmReal_t)D/2) * log(2.0*M_PI) - 0.5*logDet;
for(i=0; i<N; ++i)
{
VECT_OP_TYPE dx[D];
VECT_OP_TYPE t[D];
// dx[] difference between mean and ith data point
VECT_OP_FUNC(SubVVV)(dx,D, xM + (i*D), meanV);
// t[] = dx[] * inv(covarM);
if( diagFl )
VECT_OP_FUNC(MultDiagVMV)(t,D,icM,D,dx);
else
VECT_OP_FUNC(MultVMV)(t,D,icM,D,dx);
// dist = sum(dx[] * t[])
cmReal_t dist = VECT_OP_FUNC(MultSumVV)(t,dx,D);
yV[i] = exp( fact - (0.5*dist) );
}
return yV;
}
VECT_OP_TYPE* VECT_OP_FUNC(MultVarGaussPDF3)(
VECT_OP_TYPE* yV,
const VECT_OP_TYPE* (*srcFunc)(void* funcDataPtr, unsigned frmIdx ),
void* funcDataPtr,
const VECT_OP_TYPE* meanV,
const VECT_OP_TYPE* icM,
VECT_OP_TYPE logDet,
unsigned D,
unsigned N,
bool diagFl )
{
unsigned i;
double fact = (-(cmReal_t)D/2) * log(2.0*M_PI) - 0.5*logDet;
for(i=0; i<N; ++i)
{
VECT_OP_TYPE dx[D];
VECT_OP_TYPE t[D];
const VECT_OP_TYPE* xV = srcFunc( funcDataPtr, i );
if( xV == NULL )
yV[i] = 0;
else
{
// dx[] difference between mean and ith data point
VECT_OP_FUNC(SubVVV)(dx, D, xV, meanV);
// t[] = dx[] * inv(covarM);
if( diagFl )
VECT_OP_FUNC(MultDiagVMV)(t,D,icM,D,dx);
else
VECT_OP_FUNC(MultVMV)(t,D,icM,D,dx);
// dist = sum(dx[] * t[])
cmReal_t dist = VECT_OP_FUNC(MultSumVV)(t,dx,D);
yV[i] = exp( fact - (0.5*dist) );
}
}
return yV;
}
/// stateV[timeN]
/// a[stateN,stateN],
/// b[stateN,timeN]
/// phi[stateN].
void VECT_OP_FUNC(DiscreteViterbi)(unsigned* stateV, unsigned tN, unsigned sN, const VECT_OP_TYPE* phi, const VECT_OP_TYPE* a, const VECT_OP_TYPE* b )
{
unsigned* psiM = cmMemAlloc( unsigned, sN*tN ); // psi[sN,tN]
VECT_OP_TYPE* dV = cmMemAlloc( VECT_OP_TYPE, 2*sN );
VECT_OP_TYPE* d0V = dV;
VECT_OP_TYPE* d1V = dV + sN;
int t,i,j;
// calc the prob of starting in each state given the observations
VECT_OP_FUNC(MultVVV)( d0V, sN, phi, b );
VECT_OP_FUNC(NormalizeProbability)( d0V, sN ); // scale to prevent underflow
// for each time step
for(t=1; t<tN; ++t)
{
// for each possible next state
for(j=0; j<sN; ++j)
{
VECT_OP_TYPE mv = 0;
unsigned mi = 0;
// The following loop could be replaced with these vector op's:
// VECT_OP_TYPE tV[ sN ];
// VECT_OP_TYPE(MultVVV)(tV,sN,d0V,a + (j*sN));
// mi = VECT_OP_TYPE(MaxIndex)(tV,sN);
// mv = tV[mi];
// for each possible prev state
for(i=0; i<sN; ++i)
{
// calc prob of having ended in state i and transitioning to state j
VECT_OP_TYPE v = d0V[i] * a[ i + (j*sN) ];
// track the most likely transition ending in state j
if( v > mv )
{
mv = v;
mi = i;
}
}
// scale the prob of the most likely state by the prob of the obs given that state
d1V[j] = mv * b[ (t*sN) + j ];
// store the most likely previous state given that the current state is j
// (this is the key to understanding the backtracking step below)
psiM[ (t*sN) + j ] = mi;
}
VECT_OP_FUNC(NormalizeProbability)( d1V, sN ); // scale to prevent underflow
// swap d0V and d1V
VECT_OP_TYPE* tmp = d0V;
d0V = d1V;
d1V = tmp;
}
// store the most likely ending state
stateV[tN-1] = VECT_OP_FUNC(MaxIndex)( d0V, sN, 1 );
// given the most likely next step select the most likely previous step
for(t=tN-2; t>=0; --t)
stateV[t] = psiM[ ((t+1)*sN) + stateV[t+1] ];
cmMemPtrFree( &psiM );
cmMemPtrFree( &dV );
}
bool VECT_OP_FUNC(ClipLine2)( VECT_OP_TYPE x0, VECT_OP_TYPE y0, VECT_OP_TYPE x1, VECT_OP_TYPE y1, VECT_OP_TYPE xMin, VECT_OP_TYPE yMin, VECT_OP_TYPE xMax, VECT_OP_TYPE yMax, VECT_OP_TYPE* t0, VECT_OP_TYPE* t1 )
{
VECT_OP_TYPE dx = x1 - x0;
VECT_OP_TYPE dy = y1 - y0;
VECT_OP_TYPE p=0,q=0,r=0;
*t0 = 0.0;
*t1 = 1.0;
unsigned i;
for(i=0; i<4; ++i)
{
switch(i)
{
case 0: p=-dx; q=-(xMin - x0); break; // left
case 1: p= dx; q= (xMax - x0); break; // right
case 2: p=-dy; q=-(yMin - y0); break; // bottom
case 3: p= dy; q= (yMax - y0); break; // top
}
// if parallel to edge i
if( p == 0 )
{
// if entirely outside of window
if( q < 0 )
return false;
continue;
}
r = p/q;
// if travelling right/up
if( p < 0 )
{
// travelling away from x1,y1
if( r > *t1 )
return false;
// update distance on line to point of intersection
if( r > *t0 )
*t0 = r;
}
else // if travelling left/down
{
// travelling away from x1,y1
if( r < *t0 )
return false;
// update distance on line to point of intersection
if( r < *t1 )
*t1 = r;
}
}
return true;
}
/// (Uses the Laing-Barsky clipping algorithm)
/// From: http://www.skytopia.com/project/articles/compsci/clipping.html
bool VECT_OP_FUNC(ClipLine)( VECT_OP_TYPE* x0, VECT_OP_TYPE* y0, VECT_OP_TYPE* x1, VECT_OP_TYPE* y1, VECT_OP_TYPE xMin, VECT_OP_TYPE yMin, VECT_OP_TYPE xMax, VECT_OP_TYPE yMax )
{
VECT_OP_TYPE t0;
VECT_OP_TYPE t1;
if( VECT_OP_FUNC(ClipLine2)(*x0,*y0,*x1,*y1,xMin,yMin,xMax,yMax,&t0,&t1) )
{
VECT_OP_TYPE dx = *x1 - *x0;
VECT_OP_TYPE dy = *y1 - *y0;
*x0 = *x0 + t0*dx;
*x1 = *x0 + t1*dx;
*y0 = *y0 + t0*dy;
*y1 = *y0 + t1*dy;
return true;
}
return false;
}
bool VECT_OP_FUNC(IsLineInRect)( VECT_OP_TYPE x0, VECT_OP_TYPE y0, VECT_OP_TYPE x1, VECT_OP_TYPE y1, VECT_OP_TYPE xMin, VECT_OP_TYPE yMin, VECT_OP_TYPE xMax, VECT_OP_TYPE yMax )
{
VECT_OP_TYPE t0;
VECT_OP_TYPE t1;
return VECT_OP_FUNC(ClipLine2)(x0,y0,x1,y1,xMin,yMin,xMax,yMax,&t0,&t1);
}
VECT_OP_TYPE VECT_OP_FUNC(PtToLineDistance)( VECT_OP_TYPE x0, VECT_OP_TYPE y0, VECT_OP_TYPE x1, VECT_OP_TYPE y1, VECT_OP_TYPE px, VECT_OP_TYPE py)
{
// from:http://en.wikipedia.org/wiki/Distance_from_a_point_to_a_line
double normalLength = sqrt((x1 - x0) * (x1 - x0) + (y1 - y0) * (y1 - y0));
if( normalLength <= 0 )
return 0;
return (VECT_OP_TYPE)fabs((px - x0) * (y1 - y0) - (py - y0) * (x1 - x0)) / normalLength;
}
void VECT_OP_FUNC(Lsq1)(const VECT_OP_TYPE* x, const VECT_OP_TYPE* y, unsigned n, VECT_OP_TYPE* b0, VECT_OP_TYPE* b1 )
{
VECT_OP_TYPE sx = 0;
VECT_OP_TYPE sy = 0;
VECT_OP_TYPE sx_2 = 0;
VECT_OP_TYPE sxy = 0;
unsigned i;
if( x == NULL )
{
for(i=0; i<n; ++i)
{
VECT_OP_TYPE xx = i;
sx += xx;
sx_2 += xx * xx;
sxy += xx * y[i];
sy += y[i];
}
}
else
{
for(i=0; i<n; ++i)
{
sx += x[i];
sx_2 += x[i] * x[i];
sxy += x[i] * y[i];
sy += y[i];
}
}
*b1 = (sxy * n - sx * sy) / (sx_2 * n - sx*sx);
*b0 = (sy - (*b1) * sx) / n;
}
void VECT_OP_FUNC(Interp1)(VECT_OP_TYPE* y1, const VECT_OP_TYPE* x1, unsigned xy1N, const VECT_OP_TYPE* x0, const VECT_OP_TYPE* y0, unsigned xy0N )
{
unsigned i,j;
// for each output value
for(i=0,j=0; i<xy1N; ++i)
{
// x1[] and x0[] are increasing monotonic therefore j should never
// have to decrease
for(; j<xy0N-1; ++j)
{
// if x1[i] is between x0[j] and x0[j+1]
if( x0[j] <= x1[i] && x1[i] < x0[j+1] )
{
// interpolate y0[j] based on the distance beteen x0[j] and x1[i].
y1[i] = y0[j] + (y0[j+1]-y0[j]) * ((x1[i] - x0[j]) / (x0[j+1] - x0[j]));
break;
}
}
if( j == xy0N-1 )
y1[i] = y0[xy0N-1];
}
}
#endif
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