6334b34d2c
Added VECT_OP_FUNC()'s MultSumVVS() and SquaredSum(). DSP Wavetable object now transmits 'done' after last sample of the last loop and provides running output of the current audio file index via 'fidx'.
3215 lines
78 KiB
C
3215 lines
78 KiB
C
#ifdef cmVectOpsTemplateCode_h
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void VECT_OP_FUNC(VPrint)( cmRpt_t* rpt, const char* fmt, ... )
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{
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va_list vl;
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va_start(vl,fmt);
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if( rpt != NULL )
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cmRptVPrintf(rpt,fmt,vl);
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else
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vprintf(fmt,vl);
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va_end(vl);
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}
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void VECT_OP_FUNC(Printf)( cmRpt_t* rpt, unsigned rowCnt, unsigned colCnt, const VECT_OP_TYPE* sbp, unsigned fieldWidth, unsigned decPlCnt, const char* fmt, unsigned flags )
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{
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unsigned cci;
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unsigned outColCnt = 10;
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if( fieldWidth < 0 )
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fieldWidth = 10;
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if( decPlCnt < 0 )
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decPlCnt = 4;
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if( outColCnt == -1 )
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outColCnt = colCnt;
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for(cci=0; cci<colCnt; cci+=outColCnt)
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{
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unsigned ci0 = cci;
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unsigned cn = cci + outColCnt;
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unsigned ri;
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if(cn > colCnt)
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cn = colCnt;
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if( colCnt > outColCnt )
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{
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if( cmIsFlag(flags,cmPrintMatlabLabelsFl) )
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VECT_OP_FUNC(VPrint)(rpt,"Columns:%i to %i\n",ci0,cn-1);
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else
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if( cmIsFlag(flags,cmPrintShortLabelsFl) )
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VECT_OP_FUNC(VPrint)(rpt,"%3i: ",ci0);
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}
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if( rowCnt > 1 )
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VECT_OP_FUNC(VPrint)(rpt,"\n");
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for(ri=0; ri<rowCnt; ++ri)
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{
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unsigned ci;
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for(ci=ci0; ci<cn; ++ci )
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VECT_OP_FUNC(VPrint)(rpt,fmt,fieldWidth,decPlCnt,sbp[ (ci*rowCnt) + ri ]);
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if( cn > 0 )
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VECT_OP_FUNC(VPrint)(rpt,"\n");
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}
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}
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}
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void VECT_OP_FUNC(Print)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* sbp )
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{ VECT_OP_FUNC(Printf)(rpt,rn,cn,sbp,cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*f ",cmPrintShortLabelsFl); }
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void VECT_OP_FUNC(PrintE)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* sbp )
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{ VECT_OP_FUNC(Printf)(rpt,rn,cn,sbp,cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*e ",cmPrintShortLabelsFl); }
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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 )
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{
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VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
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VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, fieldWidth, decPlCnt,fmt,cmPrintShortLabelsFl );
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}
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void VECT_OP_FUNC(PrintL)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp )
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{
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VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
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VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*f ",cmPrintShortLabelsFl );
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}
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void VECT_OP_FUNC(PrintLE)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp )
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{
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VECT_OP_FUNC(VPrint)( rpt, "%s\n", label );
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VECT_OP_FUNC(Printf)( rpt, rn, cn, dbp, cmDefaultFieldWidth,cmDefaultDecPlCnt,"%*.*e ",cmPrintShortLabelsFl );
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}
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VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityVV)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
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{
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VECT_OP_TYPE sum = VECT_OP_FUNC(Sum)(sbp,dn);
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if( sum == 0 )
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sum = 1;
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return VECT_OP_FUNC(DivVVS)(dbp,dn,sbp,sum);
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}
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VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbability)(VECT_OP_TYPE* dbp, unsigned dn)
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{ return VECT_OP_FUNC(NormalizeProbabilityVV)(dbp,dn,dbp); }
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VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityN)(VECT_OP_TYPE* dbp, unsigned dn, unsigned stride)
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{
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VECT_OP_TYPE sum = VECT_OP_FUNC(SumN)(dbp,dn,stride);
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if( sum == 0 )
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return dbp;
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VECT_OP_TYPE* dp = dbp;
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VECT_OP_TYPE* ep = dp + (dn*stride);
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for(; dp < ep; dp+=stride )
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*dp /= sum;
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return dbp;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(StandardizeRows)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV )
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{
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bool uFl = false;
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bool sFl = false;
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unsigned i;
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if( uV == NULL )
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{
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uV = cmMemAllocZ(VECT_OP_TYPE,drn);
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uFl = true;
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}
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if( sdV == NULL )
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{
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sdV = cmMemAllocZ(VECT_OP_TYPE,drn);
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sFl = true;
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}
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VECT_OP_FUNC(MeanM)(uV, dbp, drn, dcn, 1 );
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VECT_OP_FUNC(VarianceM)(sdV, dbp, drn, dcn, uV, 1 );
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for(i=0; i<dcn; ++i)
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{
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VECT_OP_FUNC(SubVV)(dbp + i * drn, drn, uV );
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VECT_OP_FUNC(DivVV)(dbp + i * drn, drn, sdV );
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}
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if(uFl)
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cmMemFree(uV);
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if(sFl)
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cmMemFree(sdV);
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return dbp;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(StandardizeCols)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV )
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{
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bool uFl = false;
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bool sFl = false;
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unsigned i;
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if( uV == NULL )
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{
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uV = cmMemAllocZ(VECT_OP_TYPE,dcn);
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uFl = true;
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}
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if( sdV == NULL )
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{
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sdV = cmMemAllocZ(VECT_OP_TYPE,dcn);
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sFl = true;
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}
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VECT_OP_FUNC(MeanM)(uV, dbp, drn, dcn, 0 );
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VECT_OP_FUNC(VarianceM)(sdV, dbp, drn, dcn, uV, 0 );
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for(i=0; i<drn; ++i)
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{
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VECT_OP_FUNC(SubVVNN)(dbp + i, dcn, drn, uV, 1 );
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VECT_OP_FUNC(DivVVNN)(dbp + i, dcn, drn, sdV, 1 );
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}
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if(uFl)
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cmMemFree(uV);
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if(sFl)
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cmMemFree(sdV);
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return dbp;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
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{
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VECT_OP_TYPE* dp = dbp;
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VECT_OP_TYPE* ep = dbp + dn;
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for(; dp < ep; ++dp,++sp )
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*dp = *sp < 0 ? 0 : *sp;
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return dbp;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
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{
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VECT_OP_TYPE* dep = dbp + dn;
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VECT_OP_TYPE* rp = dbp;
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VECT_OP_TYPE sum = 0;
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while( dbp < dep )
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{
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sum += *sbp++;
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*dbp++ = sum;
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}
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return rp;
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}
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VECT_OP_TYPE VECT_OP_FUNC(Mean)( const VECT_OP_TYPE* bp, unsigned n )
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{ return VECT_OP_FUNC(Sum)(bp,n)/n; }
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VECT_OP_TYPE VECT_OP_FUNC(MeanN)( const VECT_OP_TYPE* bp, unsigned n, unsigned stride )
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{ return VECT_OP_FUNC(SumN)(bp,n,stride)/n; }
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VECT_OP_TYPE* VECT_OP_FUNC(MeanM)( VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, unsigned dim )
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{
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unsigned i;
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unsigned cn = dim == 0 ? scn : srn;
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unsigned rn = dim == 0 ? srn : scn;
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unsigned inc = dim == 0 ? srn : 1;
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unsigned stride = dim == 0 ? 1 : srn;
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unsigned d0 = 0;
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for(i=0; i<cn; ++i, d0+=inc)
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dp[i] = VECT_OP_FUNC(MeanN)(sp + d0, rn, stride );
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return dp;
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}
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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 )
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{
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unsigned i,n;
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const VECT_OP_TYPE* sp;
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VECT_OP_FUNC(Zero)(dp,D);
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if( N > 1 )
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{
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n = 0;
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for(i=0; i<N; ++i)
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if((sp = srcFuncPtr(argPtr,i)) != NULL )
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{
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VECT_OP_FUNC(AddVV)(dp,D,sp);
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++n;
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}
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VECT_OP_FUNC(DivVS)(dp,D,n);
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}
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return dp;
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}
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VECT_OP_TYPE VECT_OP_FUNC(Variance)( const VECT_OP_TYPE* sp, unsigned sn, const VECT_OP_TYPE* avgPtr )
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{ return VECT_OP_FUNC(VarianceN)(sp,sn,1,avgPtr); }
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VECT_OP_TYPE VECT_OP_FUNC(VarianceN)( const VECT_OP_TYPE* sp, unsigned sn, unsigned stride, const VECT_OP_TYPE* meanPtr )
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{
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VECT_OP_TYPE mean = 0;
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if( sn <= 1 )
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return 0;
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if( meanPtr == NULL )
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mean = VECT_OP_FUNC(MeanN)( sp, sn, stride );
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else
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mean = *meanPtr;
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const VECT_OP_TYPE* ep = sp + (sn*stride);
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VECT_OP_TYPE sum = 0;
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for(; sp < ep; sp += stride )
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sum += (*sp-mean) * (*sp-mean);
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return sum / (sn-1);
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}
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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 )
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{
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unsigned i;
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unsigned cn = dim == 0 ? scn : srn;
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unsigned rn = dim == 0 ? srn : scn;
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unsigned inc = dim == 0 ? srn : 1;
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unsigned stride = dim == 0 ? 1 : srn;
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unsigned d0 = 0;
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for(i=0; i<cn; ++i, d0+=inc)
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dp[i] = VECT_OP_FUNC(VarianceN)(sp + d0, rn, stride, avgPtr==NULL ? NULL : avgPtr+i );
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return dp;
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}
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unsigned VECT_OP_FUNC(NormToMax)( VECT_OP_TYPE* dp, unsigned dn )
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{
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unsigned i = VECT_OP_FUNC(MaxIndex)(dp,dn,1);
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if( i != cmInvalidIdx )
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{
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VECT_OP_TYPE v = dp[i];
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VECT_OP_FUNC(DivVS)(dp,dn,v);
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}
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return i;
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}
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VECT_OP_TYPE VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha )
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{
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double sum = 0;
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const VECT_OP_TYPE* bp = sp;
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const VECT_OP_TYPE* ep = sp + sn;
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while( bp < ep )
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sum += pow(fabs(*bp++),alpha);
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return (VECT_OP_TYPE)pow(sum/sn,1.0/alpha);
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}
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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 )
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{
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unsigned i,j,k,n = 0;
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VECT_OP_TYPE tV[ D ];
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VECT_OP_FUNC(Fill)(yM,D*D,0);
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// if the mean was not given - then calculate it
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if( uV == NULL )
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{
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VECT_OP_FUNC(Fill)(tV,D,0);
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// sum each row of xM[] into uM[]
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for(i=0; i<D; ++i)
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{
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n = 0;
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for(j=0; j<xN; ++j)
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if( selIdxV==NULL || selIdxV[j]==selKey )
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{
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tV[i] += xM[ (j*D) + i ];
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++n;
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}
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}
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// form an average from the sum in tV[]
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VECT_OP_FUNC(DivVS)(tV,D,n);
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uV = tV;
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}
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for(i=0; i<D; ++i)
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for(j=i; j<D; ++j)
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{
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n = 0;
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for(k=0; k<xN; ++k)
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if( selIdxV==NULL || selIdxV[k]==selKey)
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{
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unsigned yi = (i*D)+j;
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yM[ yi ] += ((xM[ (k*D)+j ]-uV[j]) * (xM[ (k*D) + i ]-uV[i]));
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if( i != j )
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yM[ (j*D)+i ] = yM[ yi ];
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++n;
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}
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}
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if( n>1 )
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VECT_OP_FUNC(DivVS)( yM, D*D, n-1 );
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}
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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 )
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{
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unsigned i,j,k = 0,n;
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VECT_OP_TYPE tV[ D ];
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const VECT_OP_TYPE* sp;
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VECT_OP_FUNC(Fill)(yM,D*D,0);
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// if the mean was not given - then calculate it
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if( uV == NULL )
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{
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VECT_OP_FUNC(Fill)(tV,D,0);
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n = 0;
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// sum each row of xM[] into uM[]
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for(i=0; i<xN; ++i)
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if( (selIdxV==NULL || selIdxV[i]==selKey) && ((sp=srcFunc(userPtr,i))!=NULL) )
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{
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VECT_OP_FUNC(AddVV)(tV,D,sp);
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++n;
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}
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// form an average from the sum in tV[]
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VECT_OP_FUNC(DivVS)(tV,D,n);
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uV = tV;
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}
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for(i=0; i<xN; ++i)
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if( selIdxV==NULL || selIdxV[i]==selKey )
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{
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// get a pointer to the ith data point
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const VECT_OP_TYPE* sV = srcFunc(userPtr,i);
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// note: this algorithm works because when a data point element (scalar)
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// is multiplied by another data point element those two elements
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// are always part of the same data point (vector). Two elements
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// from different data points are never multiplied.
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if( sV != NULL )
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for(j=0; j<D; ++j)
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for(k=j; k<D; ++k)
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yM[j + k*D] += (sV[j]-uV[j]) * (sV[k]-uV[k]);
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}
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if( n > 1 )
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VECT_OP_FUNC(DivVS)( yM, D*D, n-1 );
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// fill in the lower triangle
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for(j=0; j<D; ++j)
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for(k=j; k<D; ++k)
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yM[k + j*D] = yM[j + k*D];
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}
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bool VECT_OP_FUNC(Equal)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
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{
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const VECT_OP_TYPE* ep = s0p + sn;
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while( s0p < ep )
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if( *s0p++ != *s1p++ )
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return false;
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return true;
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}
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bool VECT_OP_FUNC(IsNormal)( const VECT_OP_TYPE* sp, unsigned sn )
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{
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const VECT_OP_TYPE* ep = sp + sn;
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for(; sp<ep; ++sp)
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if( !isnormal(*sp) )
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return false;
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return true;
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}
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bool VECT_OP_FUNC(IsNormalZ)(const VECT_OP_TYPE* sp, unsigned sn )
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{
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const VECT_OP_TYPE* ep = sp + sn;
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for(; sp<ep; ++sp)
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if( (*sp != 0) && (!isnormal(*sp)) )
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return false;
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return true;
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}
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unsigned VECT_OP_FUNC(FindNonNormal)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sbp )
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{
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const VECT_OP_TYPE* sp = sbp;
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const VECT_OP_TYPE* ep = sp + dn;
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unsigned n = 0;
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for(; sp<ep; ++sp)
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if( !isnormal(*sp) )
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dp[n++] = sp - sbp;
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return n;
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}
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unsigned VECT_OP_FUNC(FindNonNormalZ)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sbp )
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{
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const VECT_OP_TYPE* sp = sbp;
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const VECT_OP_TYPE* ep = sp + dn;
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unsigned n = 0;
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for(; sp<ep; ++sp)
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if( (*sp!=0) && (!isnormal(*sp)) )
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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'
|
|
int nb = ilaenv_(&ispec, funcNameStr, " ", &n1,&n2,&n3,&n4, strlen(funcNameStr), 1 );
|
|
|
|
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(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 cmOkRC;
|
|
|
|
}
|
|
|
|
|
|
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
|
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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 };
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|
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unsigned hn = sizeof(bandUprHz)/sizeof(double);
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|
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unsigned i, bi = 0;
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bandCnt = cmMin(hn,bandCnt);
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binIdxV[0] = 0;
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cntV[0] = 1;
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for(i=1; bi < bandCnt && i<binCnt; ++i)
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{
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double hz = srate * i / (2 * (binCnt-1));
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if( hz <= bandUprHz[bi] )
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cntV[bi]++;
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else
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{
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//printf("%i %i %i %f\n",bi,binIdxV[bi],cntV[bi],bandUprHz[bi]);
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++bi;
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if( bi < bandCnt )
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{
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binIdxV[bi] = i;
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cntV[bi] = 1;
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}
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}
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}
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return bi;
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}
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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 )
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{
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unsigned i,j;
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VECT_OP_TYPE v0[ bandCnt ];
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VECT_OP_TYPE v1[ bandCnt ];
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// if no lower/upper band limits were give use a fixed semitone band width
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if( lfV==NULL || hfV==NULL)
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{
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for(i=0; i<bandCnt; ++i)
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{
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v0[i] = ctrHzV[i] * pow(2.0,-stSpread/12.0);
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v1[i] = ctrHzV[i] * pow(2.0, stSpread/12.0);
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}
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lfV = v0;
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hfV = v1;
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}
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VECT_OP_FUNC(Zero)(maskMtx,bandCnt*binCnt);
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// for each band
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for(i=0; i<bandCnt; ++i)
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{
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// calc bin index of first possible bin in this band
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// j = (unsigned)floor(lfV[i] / binHz);
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double binHz_j = 0;
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|
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// for each bin whose ctr frq is <= the band upper limit
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for(j=0; j<binCnt; ++j)
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{
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double v;
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// if bin[j] is inside the lower leg of the triangle
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if( lfV[i] <= binHz_j && binHz_j <= ctrHzV[i] )
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v = (binHz_j - lfV[i]) / cmMax(VECT_OP_MIN, ctrHzV[i] - lfV[i] );
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else
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// if bin[j] is inside the upper leg of the triangle
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if( ctrHzV[i] < binHz_j && binHz_j <= hfV[i] )
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v = (hfV[i] - binHz_j) / cmMax(VECT_OP_MIN, hfV[i] - ctrHzV[i] );
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else
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v = 0;
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maskMtx[ (j*bandCnt)+i ] = v;
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binHz_j = binHz * (j+1);
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}
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}
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return maskMtx;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(BarkMask)(VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, double binHz )
|
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{
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// -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)
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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 };
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|
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bandCnt = cmMin(bandCnt,kDefaultBarkBandCnt);
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|
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VECT_OP_FUNC(TriangleMask)(maskMtx, bandCnt, binCnt, b+1, binHz, 0, b+0, b+2 );
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return maskMtx;
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}
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VECT_OP_TYPE* VECT_OP_FUNC(TerhardtThresholdMask)(VECT_OP_TYPE* maskV, unsigned binCnt, double srate, unsigned flags )
|
|
{
|
|
unsigned i;
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|
|
|
double c0 = cmIsFlag(flags,kModifiedTtmFl) ? 0.6 : 1.0;
|
|
double c1 = cmIsFlag(flags,kModifiedTtmFl) ? 0.5 : 6.5;
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|
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maskV[0]=0;
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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;
|
|
}
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|
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);
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|
|
return m;
|
|
}
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|
|
VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt )
|
|
{
|
|
VECT_OP_TYPE* dbp = dp;
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|
|
|
double c0 = 1.0/sqrt(filtCnt/2); // row 1-coeffCnt factor
|
|
double c1 = c0 * sqrt(2)/2; // row 0 factor
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|
|
|
unsigned i,j;
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|
|
// 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;
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
#endif
|