Many documentation string additions and updates.

src/app/cmMidiScoreFollow.h

@@ -5,6 +5,17 @@
 #ifdef __cplusplus
 extern "C" {
 #endif
+  
+  //( { file_desc:"Score follow a MIDI files." kw[score] }
+  //
+  // This function uses a CSV score file generated from cmXScoreTest() to score follow a MIDI file.
+  // Output filesL
+  // - MIDI file with velocities from the score applied to the associated notes in the MIDI file.
+  // - A text file, for use with cmTimeLine, which describes the bar positions as absolute times into the score.
+  // - An SVG file which shows the score match results over time for each note in the score.
+  // - A report file which lists the score match status over time.
+  
+  
 
   enum
   {
@@ -24,6 +35,7 @@ extern "C" {
     const cmChar_t* midiOutFn,       // (optional) midiFn with apply sostenuto and velocities from the score to the MIDI file
     const cmChar_t* tlBarOutFn       // (optional) bar positions sutiable for use in a cmTimeLine description file.
                                   );
+  //)
   
 #ifdef __cplusplus
 }

src/app/cmScoreMatchGraphic.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Implements the functionality of cmMidiScoreFollowMain()." kw[score] }
+
   enum
   {
     kOkSmgRC = cmOkRC,
@@ -34,6 +36,8 @@ extern "C" {
   // from from score into MIDI file and then write the updated MIDI
   // file to 'newMidiFn'.
   cmSmgRC_t cmScoreMatchGraphicUpdateMidiFromScore( cmCtx_t* ctx, cmSmgH_t h, const cmChar_t* newMidiFn );
+
+  //)
   
 #ifdef __cplusplus
 }

src/app/cmXScore.h

@@ -5,6 +5,17 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Process a Music XML score in a variety of ways." kw[score] }
+
+  //$
+  // cmScoreTest() performs a the following functions:
+  // - Parses Music XML files into a text (edit) file.
+  // - The 'edit' file can then be manually edited to modify and add information to the score.
+  // - The modified 'edit' file can then be used to generate a CSV file
+  // suitable for use with cmScore(), a MIDI file which can render the modified score,
+  // and a SVG file which will display the score as a piano roll.
+  //
+  
   enum
   {
     kOkXsRC = cmOkRC,
@@ -73,6 +84,8 @@ extern "C" {
   // Set begMeasNumb to the first measure the to be written to the output csv, MIDI and SVG files.
   // Set begBPM to 0 to use the tempo from the score otherwise set it to the tempo at begMeasNumb.
   cmXsRC_t cmXScoreTest( cmCtx_t* ctx, const cmChar_t* xmlFn, const cmChar_t* reorderFn, const cmChar_t* csvOutFn, const cmChar_t* midiOutFn, const cmChar_t* svgOutFn, bool reportFl, int begMeasNumb, int begBPM, bool svgStandAloneFl, bool svgPanZoomFl, bool damperRptFl );
+
+  //)
   
 #ifdef __cplusplus
 }

src/cmApBuf.c

@@ -1071,7 +1071,12 @@ void cmApBufReport( cmRpt_t* rpt )
   }
 }
 
-/// [cmApBufExample]
+//{ { label:cmApBufExample }
+//(
+// cmApBufTest() demonstrates the audio buffer usage.
+//)
+
+//(
 
 void cmApBufTest( cmRpt_t* rpt )
 {
@@ -1172,6 +1177,7 @@ void cmApBufTest( cmRpt_t* rpt )
   cmApBufFinalize();
 }
 
-/// [cmApBufExample]
+//)
+//}
 
 

src/cmAudioPort.h

@@ -1,4 +1,4 @@
-//( { file_desc: "Cross platform audio device interface." kw:[audio rt] }
+//( { file_desc: "Cross platform audio device interface." kw:[audio rt devices] }
 //
 // This interface provides data declarations for platform dependent 
 // audio I/O functions. The implementation for the functions are

src/cmAudioSys.c

@@ -1157,11 +1157,16 @@ unsigned cmAudioSysSubSystemCount( cmAudioSysH_t h )
 
 //===========================================================================================================================
 //
-//  cmAsTest()
+//  cmAudioSysTest()
 //
 
-/// [cmAudioSysTest]
+//{ { label:cmAudioSysTest }
+//(
+// cmAudioSysTest() demonstrates the audio system usage.
+//)
 
+//(
+ 
 typedef struct 
 {
   double   hz;       // current synth frq
@@ -1463,4 +1468,5 @@ void cmAudioSysTest( cmRpt_t* rpt, int argc, const char* argv[] )
 
 }
 
-/// [cmAudioSysTest]
+//)
+//}

src/cmJson.c

@@ -3994,7 +3994,8 @@ void _cmJsonTestPrint( void* userPtr, const cmChar_t* text )
 //(
 // cmJsonTest() demonstrates some JSON tree operations.
 //)
-//[
+
+//(
 cmJsRC_t cmJsonTest( const char* fn, cmCtx_t* ctx )
 {
   cmJsRC_t      rc  = kOkJsRC;
@@ -4076,5 +4077,5 @@ cmJsRC_t cmJsonTest( const char* fn, cmCtx_t* ctx )
 
   return rc == kOkJsRC ? rc1 : rc;
 }
-//]
+//)
 //}

src/cmKeyboard.h

@@ -5,7 +5,7 @@
 extern "C" {
 #endif
 
-  //( { file_desc:"Query and get keypresses directly from the console." kw:[system] }
+  //( { file_desc:"Query and get keypresses directly from the console." kw:[system devices] }
   
   enum
   {

src/cmMidiPort.h

@@ -5,7 +5,7 @@
 extern "C" {
 #endif
 
-  //(  { file_desc:"Device independent MIDI port related code." kw:[midi]}
+  //(  { file_desc:"Device independent MIDI port related code." kw:[midi devices]}
 
   typedef unsigned cmMpRC_t;
 

src/cmPP_NARG.h

@@ -1,7 +1,8 @@
 #ifndef cmPP_NARG_H
 #define cmPP_NARG_H
 
-
+//( { file_desc:"Var-args argument counter. " kw:[base] }
+//
 // Taken from here:
 // https://groups.google.com/forum/#!topic/comp.std.c/d-6Mj5Lko_s
 // and here:
@@ -43,3 +44,5 @@
          9,8,7,6,5,4,3,2,1,0
 
 #endif
+
+//)

src/cmPrefix.h

@@ -5,8 +5,9 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Global prefix header for the 'cm' library. Currently empty." kw:[base] }
 
-
+  //)
 
 #ifdef __cplusplus
 }

src/cmProcTest.c

@@ -28,7 +28,6 @@
 #include <time.h> // time()
 
 
-
 void cmTestPrint( cmRpt_t* rpt, const char* fmt, ... )
 {
   va_list vl;

src/cmProcTest.h

@@ -5,10 +5,14 @@
 extern "C" {
 #endif
 
+  //( { file_desc: "Some obsolete test stub functions. See the cmtools project for a complete set of test and example functions." kw:[proc]}
+  
   void cmProcTestNoInit( cmCtx_t* ctx );
   void cmProcTestGnuPlot( cmCtx_t* ctx );
   void cmProcTest( cmCtx_t* ctx );
 
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/cmRptFile.h

@@ -4,6 +4,8 @@
 #ifdef __cplusplus
 extern "C" {
 #endif
+  
+  //( { file_desc: "The cmRptFile provides a cmRpt class which outputs to a file." kw:[base]}
 
   enum
   {
@@ -23,6 +25,8 @@ extern "C" {
     
   cmRpt_t* cmRptFileRpt( cmRptFileH_t h );
 
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/cmSerialPort.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Serial port interface." kw[system devices rt] }
+  
   typedef unsigned cmSeRC_t;
 
   enum
@@ -86,6 +88,8 @@ extern "C" {
 
   cmSeRC_t cmSePortTest(cmCtx_t* ctx);
 
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/cmSvgWriter.h

@@ -5,6 +5,9 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"SVG file writer." kw[file plot] }
+  
+
 enum
 {
   kOkSvgRC = cmOkRC,
@@ -31,6 +34,8 @@ enum
   // Both the CSS file and svg-pan-zoom.min.js should therefore be in the same directory
   // as the output HTML file.
   cmSvgRC_t cmSvgWriterWrite( cmSvgH_t h, const cmChar_t* cssFn, const cmChar_t* outFn, bool standaloneFl, bool panZoomFl );
+
+  //)
   
 #ifdef __cplusplus
 }

src/cmSyncRecd.h

@@ -4,6 +4,8 @@
 #ifdef __cplusplus
 extern "C" {
 #endif
+  
+  //( { file_desc:"Generate time-alignment data between an audio and MIDI file. See cmDspSyncRecd_t." kw[proc] }
 
   enum
   {
@@ -27,7 +29,8 @@ extern "C" {
   
 
   cmSyRC_t cmSyncRecdTest( cmCtx_t* ctx );
-
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/cmVectOpsDocOut.h

@@ -0,0 +1,990 @@
+//( { file_desc:"Math vector operations." kw:[vop math] }
+//)
+//( { label:misc desc:"Miscellaneous vector operations." kw:[vop] }
+
+// Compute the cummulative sum of sbp[dn]. Equivalent to Matlab cumsum().
+T_t* cmVOT_CumSum(T_t* dbp, unsigned dn, const T_t* sbp ); 
+
+// Returns true if all values in each vector are equal.
+bool          cmVOT_Equal(    const T_t* s0p, const T_t* s1p, unsigned sn );
+
+// Same as Matlab linspace() v[i] = i * (limit-1)/n
+T_t*  cmVOT_LinSpace( T_t* dbp, unsigned dn, T_t base, T_t limit );
+
+//======================================================================================================================
+//)
+
+
+//( { label:Print desc:"Vector printing functions." kw:[vop] }
+// Setting fieldWidth or decPltCnt to to negative values result in fieldWidth == 10 or decPlCnt == 4
+//
+void          cmVOT_Printf( cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp, int fieldWidth, int decPlCnt, const char* fmt, unsigned flags );
+void          cmVOT_Print(  cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp );
+void          cmVOT_PrintE( cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp );
+
+void          cmVOT_PrintLf( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp, unsigned fieldWidth, unsigned decPlCnt, const char* fmt );
+void          cmVOT_PrintL(  const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp );
+void          cmVOT_PrintLE( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const T_t* dbp );
+//======================================================================================================================
+//)
+
+
+//( { label:Normalization desc:"Normalization and standardization functions." kw:[vop] }
+
+// Normalize the vector of proabilities by dividing through by the sum.
+// This leaves the relative proportions of each value unchanged while producing a total probability of 1.0.
+//
+T_t* cmVOT_NormalizeProbabilityVV(T_t* dbp, unsigned dn, const T_t* sbp);
+T_t* cmVOT_NormalizeProbability(T_t* dbp, unsigned dn);
+T_t* cmVOT_NormalizeProbabilityN(T_t* dbp, unsigned dn, unsigned stride);
+//
+// Standardize the columns of the matrix by subtracting the mean and dividing by the standard deviation.
+// uV[dcn] returns the mean of the data and is optional.
+// sdV[dcn] return the standard deviation of the data and is optional.
+T_t* cmVOT_StandardizeRows( T_t* dbp, unsigned drn, unsigned dcn, T_t* uV, T_t* sdV );
+T_t* cmVOT_StandardizeCols( T_t* dbp, unsigned drn, unsigned dcn, T_t* uV, T_t* sdV );
+//
+// Normalize by dividing through by the max. value.
+// dp[] ./= max(dp). Returns the index of the max value.
+unsigned  cmVOT_NormToMax(    T_t* dp, unsigned dn );
+//
+// Normalize by dividing through by the max. absolute value.
+// db[] .*= fact / abs(max(dp));
+unsigned cmVOT_NormToAbsMax(   T_t* dp, unsigned dn, T_t fact );
+//======================================================================================================================
+//)
+
+
+//( { label:"Mean and variance" desc:"Compute mean and variance." kw:[vop] }
+
+T_t  cmVOT_Mean(     const T_t* sp, unsigned sn );
+T_t  cmVOT_MeanN(    const T_t* sp, unsigned sn, unsigned stride  );
+//
+// Take the mean of each column/row of a matrix.
+// Set 'dim' to 0 to return mean of columns else return mean of rows.
+T_t*  cmVOT_MeanM(    T_t* dp, const T_t* sp, unsigned srn, unsigned scn, unsigned dim );
+//
+// Take the mean of the first 'cnt' element of each column/row of a matrix.
+// Set 'dim' to 0 to return mean of columns else return mean of rows.
+// If 'cnt' is greater than the number of elements in the column/row then 'cnt' is
+// reduced to the number of elements in the column/row.
+T_t*  cmVOT_MeanM2(    T_t* dp, const T_t* sp, unsigned srn, unsigned scn, unsigned dim, unsigned cnt );
+//
+// Find the mean of the  data points returned by srcFuncPtr(argPtr,i) and return it in dp[dim].
+// 'dim' is both the size of dp[] and the length of each data point returned by srcFuncPtr().
+// srcFuncPtr() will be called 'cnt' times but it may return NULL on some calls if the associated
+// data point should not be included in the mean calculation.
+T_t*  cmVOT_Mean2(   T_t* dp, const T_t* (*srcFuncPtr)(void* arg, unsigned idx ), unsigned dim, unsigned cnt, void* argPtr );
+//
+// avgPtr is optional - set to NULL to compute the average
+T_t  cmVOT_Variance( const T_t* sp, unsigned sn, const T_t* avgPtr );
+T_t  cmVOT_VarianceN(const T_t* sp, unsigned sn, unsigned stride, const T_t* avgPtr );
+//
+// Set dim=0 to return variance of columns otherwise return variance or rows.
+T_t*  cmVOT_VarianceM(T_t* dp,  const T_t* sp, unsigned srn, unsigned scn, const T_t* avgPtr, unsigned dim );
+//======================================================================================================================
+//)
+
+
+//( { label:"Covariance" desc:"Matrix covariance" kw:[vop] }
+
+// Calculate the sample covariance matrix from a set of Gaussian distributed multidimensional data.
+// sp[dn,scn] is the data set.
+// dn is the dimensionality of the data.
+// scn is the count of data points
+// up[dn] is an optional mean vector. If up == NULL then the mean of the data is calculated internally. 
+// selIdxV[scn] can be used to select a subset of datapoints to process.
+// If selIdxV[] is non-NULL then only columns where selIdxV[i]==selKey will be processed.
+//
+// dp[dn,dn] = covar( sp[dn,scn], u[dn] )
+void  cmVOT_GaussCovariance(T_t* dp, unsigned dn, const T_t* sp, unsigned scn, const T_t* up, const unsigned* selIdxV, unsigned selKey );
+
+// Calculate the sample covariance matrix.
+// dp[ dn*dn ] - output matrix
+// dn - dimensionality of the data
+// srcFuncPtr - User defined function which is called to return a pointer to a data vector at index 'idx'.
+//          The returned data vector must contain 'dn' elements.  The function should return NULL
+//          if the data point associated with 'idx' should not be included in the covariance calculation.
+// sn - count of data vectors 
+// userPtr - User arg. passed to srcFuncPtr.    
+// uV[ dn ] - mean of the data set (optional)
+// Note that this function computes the covariance matrix in 2 serial passes (1 if the mean vector is given)
+// through the 'sn' data points.  
+// The result of this function are identical to the octave cov() function.
+void  cmVOT_GaussCovariance2(T_t* dp, unsigned dn, const T_t* (*srcFuncPtr)(void* userPtr, unsigned idx), unsigned sn, void* userPtr, const T_t* uV, const unsigned* selIdxV, unsigned selKey );
+//======================================================================================================================
+//)
+
+//( { label:"Float point normal" desc:"Evaluate the 'normalness of floating point values." kw:[vop] }
+
+// Returns true if all values are 'normal' according the the C macro 'isnormal'.
+// This function will return false if any of the values are zero.
+bool          cmVOT_IsNormal( const T_t* sp, unsigned sn );
+
+// Returns true if all values are 'normal' or zero according the the C macro 'isnormal'.
+// This function accepts zeros as normal.
+bool          cmVOT_IsNormalZ(const T_t* sp, unsigned sn );
+
+// Set dp[dn] to the indexes of the non-normal numbers in sp[dn].
+// Returns the count of indexes stored in dp[].
+unsigned      cmVOT_FindNonNormal( unsigned* dp, unsigned dn, const T_t* sp );
+unsigned      cmVOT_FindNonNormalZ( unsigned* dp, unsigned dn, const T_t* sp );
+//======================================================================================================================
+//)
+
+
+//( { label:"Measure" desc:"Measure features of a vector." kw:[vop] }
+
+// Successive call to to ZeroCrossCount should preserve the value pointed to by delaySmpPtr.
+unsigned      cmVOT_ZeroCrossCount( const T_t* sp, unsigned n, T_t* delaySmpPtr);
+
+// Calculuate the sum of the squares of all elements in bp[bn]. 
+T_t cmVOT_SquaredSum( const T_t* bp, unsigned bn );
+
+// sn must be <= wndSmpCnt. If sn < wndSmpCnt then sp[sn] is treated as a
+// a partially filled buffer padded with wndSmpCnt-sn zeros.
+// rms = sqrt( sum(sp[1:sn] .* sp[1:sn]) / wndSmpCnt )
+T_t  cmVOT_RMS( const T_t* sp, unsigned sn, unsigned wndSmpCnt );
+
+// This function handles the case were sn is not an integer multiple of 
+// wndSmpCnt or hopSmpCnt.  In this case the function computes zero 
+// padded RMS values for windows which go past the end of sp[sn].
+T_t* cmVOT_RmsV( T_t* dp, unsigned dn, const T_t* sp, unsigned sn, unsigned wndSmpCnt, unsigned hopSmpCnt );
+
+// Return the magnitude (Euclidean Norm) of a vector.
+T_t  cmVOT_EuclidNorm( const T_t* sp, unsigned sn );
+
+T_t  cmVOT_AlphaNorm(const T_t* sp, unsigned sn, T_t alpha );
+
+//======================================================================================================================
+//)
+
+
+
+//( { label:"Distance" desc:"Calculate various vector distances." kw:[vop] }
+
+// Return the Itakura-Saito distance between a modelled power spectrum (up) and another power spectrum (sp).
+T_t cmVOT_ItakuraDistance( const T_t* up, const T_t* sp, unsigned sn );
+
+// Return the cosine distance between two vectors.
+T_t  cmVOT_CosineDistance( const T_t* s0P, const T_t* s1p, unsigned sn );
+
+// Return the Euclidean distance between two vectors
+T_t  cmVOT_EuclidDistance( const T_t* s0p, const T_t* s1p, unsigned sn );
+
+// Return the Manhattan distance between two vectors
+T_t  cmVOT_L1Distance( const T_t* s0p, const T_t* s1p, unsigned sn );
+
+// Return the Mahalanobis distance between a vector and the mean of the distribution.
+// The mean vector could be replaced with another vector drawn from the same distribution in which
+// case the returned value would reflect the distance between the two vectors.
+// 'sn' is the dimensionality of the data.
+// up[D] and invCovM[sn,sn] are the mean and inverse of the covariance matrix of the distribution from 
+// which sp[D] is drawn. 
+T_t  cmVOT_MahalanobisDistance( const T_t* sp, unsigned sn, const T_t* up, const T_t* invCovM );
+
+// Return the KL distance between two probability distributions up[sn] and sp[sn].
+// Since up[] and sp[] are probability distributions they must sum to 1.0.
+T_t cmVOT_KL_Distance( const T_t* up, const T_t* sp, unsigned sn );
+
+// Return the KL distance between a prototype vector up[sn] and another vector sp[sn].
+// This function first normalizes the two vectors to sum to 1.0 before calling
+// cmVOT_KL_Distance(up,sp,sn);
+T_t cmVOT_KL_Distance2( const T_t* up, const T_t* sp, unsigned sn );
+
+
+// Measure the Euclidean distance between a vector and all the columns in a matrix.
+// If dv[scn] is no 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 cmVOT_EuclidDistanceVM( T_t* dv, const T_t* sv, const T_t* sm, unsigned srn, unsigned scn );
+
+// Measure the distance between each column in s0M[ rn, s0cn ] and 
+// each column in s1M[rn, s1cn ]. If dM is non-NULL store the 
+// result in dM[s1cn, s0cn]. The difference between s0M[:,0] and s1M[:,0] 
+// is stored in dM[0,0], the diff. between s0M[:,1] and s1M[:,1] is stored 
+// in dM[1,0], etc.  If mvV[s0cn] is non-NULL then  minV[i] is set with
+// the distance from s0M[:,i] to the nearest column in s1M[]. If miV[s0cn]
+// is non-NULL then it is set with the column index of s1M[] which is
+// closest to s0M[:,i].  In other words mvV[i] gives the distance to column
+// miV[i] from column s0M[:,i].
+// In those cases where the distane from a prototype (centroid) to the data point
+// is not the same as from the data point to the centroid then s1M[] is considered
+// to hold the prototypes and s0M[] is considered to hold the data points.
+// The distance function returns the distance from a prototype 'cV[dimN]' to
+// an datapoint dV[dimN]. 'dimN' is the dimensionality of the data vector
+// and is threfore equal to 'rn'.
+void cmVOT_DistVMM( 
+  T_t*       dM,    // dM[s1cn,s0cn] return distance mtx (optional) 
+  T_t*       mvV,   // mvV[s0cn] distance to closest data point in s0M[]. (optional)
+  unsigned*           miV,   // miV[s0cn] column index into s1M[] of closest data point to s0M[:,i]. (optional)
+  unsigned            rn,    // dimensionality of the data and the row count for s0M[] and s1M[] 
+  const T_t* s0M,   // s0M[rn,s0cn] contains one data point per column
+  unsigned            s0cn,  // count of data points (count of columns in s0M[]
+  const T_t* s1M,   // s1M[rn,s1cn] contains one prototype per column
+  unsigned            s1cn,  // count of prototypes (count of columns in s1m[]
+  T_t (*distFunc)( void* userPtr, const T_t* cV, const T_t* dV, unsigned dimN ), 
+  void*               userPtr );
+
+//======================================================================================================================
+//)
+
+//( { label:"Select columns" desc:"Select columns based on distance." kw:[vop] }
+
+// Select 'selIdxN' columns from sM[srn,scn].
+// dM[srn,selIdxN] receives copies of the selected columns.
+// selIdxV[selIdxN] receives the column indexes of the selected columns.
+// Both dM[] and selIdxV[] are optional.
+// In each case the first selected point is chosen at random.
+// SelectRandom() then selects the following selIdxN-1 points at random.
+// SelectMaxDist() selects the next selIdxN-1 points by selecting 
+// the point whose combined distance to the previously selected points
+// is greatest. SelectMaxAvgDist() selectes the points whose combined
+// average distance is greatest relative the the previously selected
+// points.
+void cmVOT_SelectRandom(     T_t* dM, unsigned* selIdxV, unsigned selIdxN, const T_t* sM, unsigned srn, unsigned scn );
+void cmVOT_SelectMaxDist(    T_t* dM, unsigned* selIdxV, unsigned selIdxN, const T_t* sM, unsigned srn, unsigned scn, T_t (*distFunc)( void* userPtr, const T_t* s0V, const T_t* s1V, unsigned sn ), void* distUserPtr );
+void cmVOT_SelectMaxAvgDist( T_t* dM, unsigned* selIdxV, unsigned selIdxN, const T_t* sM, unsigned srn, unsigned scn, T_t (*distFunc)( void* userPtr, const T_t* s0V, const T_t* s1V, unsigned sn ), void* distUserPtr ); 
+
+//======================================================================================================================
+//)
+
+//( { label:"Matrix multiplication" desc:"Various matrix multiplication operations." kw:[vop] }
+
+// Return the sum of the products (dot product)
+T_t cmVOT_MultSumVV(  const T_t* s0p, const T_t* s1p, unsigned sn  );
+T_t cmVOT_MultSumVS(  const T_t* s0p, unsigned sn, T_t s );
+
+// Number of elements in the dest vector is expected to be the same 
+// as the number of source matrix rows.
+// mcn gives the number of columns in the source matrix which is 
+//  expected to match the number of elements in the source vector.
+// dbp[dn,1] = mp[dn,mcn] * vp[mcn,1] 
+T_t* cmVOT_MultVMV( T_t* dbp, unsigned dn, const T_t* mp, unsigned mcn, const T_t* vp ); 
+
+// Multiply a row vector with a matrix to produce a row vector. 
+// dbp[1,dn] = v[1,vn] * m[vn,dn]
+T_t* cmVOT_MultVVM( T_t* dbp, unsigned dn, const T_t* vp, unsigned vn, const T_t* mp ); 
+
+// Same as MultVMtV() except M is transposed as part of the multiply.  
+// mrn gives the number of rows in m[] and number of elements in vp[]
+// dpb[dn] = mp[mrn,dn] * vp[mrn]
+T_t* cmVOT_MultVMtV( T_t* dbp, unsigned dn, const T_t* mp, unsigned mrn, const T_t* vp ); 
+
+// Same as MultVMV() but where the matrix is diagonal.
+T_t* cmVOT_MultDiagVMV( T_t* dbp, unsigned dn, const T_t* mp, unsigned mcn, const T_t* vp ); 
+
+// Generalized matrix multiply.
+// If transposition is selected for M0 or M1 then the given dimension represent the size of the matrix 'after' the transposion. 
+// d[drn,dcn] = alpha * op(m0[drn,m0cn_m1rn]) * op(m1[m0cn_m1rn,dcn]) + beta * d[drn,dcn]
+/// See enum { kTranpsoseM0Fl=0x01, kTransposeM1Fl=0x02 } in cmVectOps for flags.
+T_t* cmVOT_MultMMM1(T_t* dbp, unsigned drn, unsigned dcn, T_t alpha, const T_t* m0, const T_t* m1, unsigned m0cn_m1rn, T_t beta, unsigned flags );
+
+// Same a cmVOT_MultMMM1 except allows the operation on a sub-matrix by providing the physical (memory) row count rather than the logical (matrix) row count.
+T_t* cmVOT_MultMMM2(T_t* dbp, unsigned drn, unsigned dcn, T_t alpha, const T_t* m0, const T_t* m1, unsigned m0cn_m1rn, T_t beta, unsigned flags, unsigned dprn, unsigned m0prn, unsigned m1prn );
+
+// d[drn,dcn] = m0[drn,m0cn] * m1[m1rn,dcn] 
+T_t* cmVOT_MultMMM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* m0, const T_t* m1, unsigned m0cn_m1rn );
+
+// same as MultMMM() except second source matrix is transposed prior to the multiply
+T_t* cmVOT_MultMMMt(T_t* dbp, unsigned drn, unsigned dcn, const T_t* m0, const T_t* m1, unsigned m0cn_m1rn );
+
+//======================================================================================================================
+//)
+
+//( { label:"Linear algebra" desc:"Miscellaneous linear algebra operations. Determinant, Inversion, Cholesky decompostion. Linear system solver." kw:[vop] }
+
+// Initialize dbp[dn,dn] as a square symetric positive definite matrix using values
+// from a random uniform distribution. This is useful for initializing random 
+// covariance matrices as used by multivariate Gaussian distributions
+// If t is non-NULL it must point to a block of scratch memory of t[dn,dn].
+// If t is NULL then scratch memory is internally allocated and deallocated.
+T_t* cmVOT_RandSymPosDef( T_t* dbp, unsigned dn, T_t* t );
+
+
+// Compute the determinant of any square matrix.
+T_t  cmVOT_DetM(    const T_t* sp, unsigned srn );
+
+// Compute the determinant of a diagonal matrix.
+T_t  cmVOT_DetDiagM(    const T_t* sp, unsigned srn);
+
+// Compute the log determinant of any square matrix.
+T_t  cmVOT_LogDetM(    const T_t* sp, unsigned srn );
+
+// Compute the log determinant of a diagonal matrix.
+T_t  cmVOT_LogDetDiagM(    const T_t* sp, unsigned srn);
+
+
+// Compute the inverse of a square matrix.  Returns NULL if the matrix is not invertable.
+// 'drn' is the dimensionality of the data.
+T_t* cmVOT_InvM(    T_t* dp, unsigned drn );
+
+// Compute the inverse of a diagonal matrix. Returns NULL if the matrix is not invertable.
+T_t* cmVOT_InvDiagM(    T_t* dp, unsigned drn );
+
+// Solve a linear system of the form AX=B where A[an,an] is square. 
+// Since A is square B must have 'an' rows.
+// Result is returned in B.
+// Returns a pointer to B on success or NULL on fail.
+// NOTE: Both A and B are overwritten by this operation.
+T_t* cmVOT_SolveLS( T_t* A, unsigned an, T_t* B, unsigned bcn ); 
+
+// Perform a Cholesky decomposition of the square symetric matrix U[un,un].
+// The factorization has the form: A=U'TU.
+// If the factorization is successful A is set to U and a pointer to A is returned.
+// Note that the lower triangle of A is not overwritten. See CholZ().
+// If the factorization fails NULL is returned.
+T_t* cmVOT_Chol(T_t* A, unsigned an );
+
+// Same as Chol() but sets the lower triangle of U to zero. 
+// This is equivalent ot the Matlab version.
+T_t* cmVOT_CholZ(T_t* U, unsigned un );
+
+// Calculate the best fit line: b0 + b1*x_i through the points x_i,y_i.
+// Set x to NULL if it uses sequential integers [0,1,2,3...]
+void cmVOT_Lsq1(const T_t* x, const T_t* y, unsigned n, T_t* b0, T_t* b1 );
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Stretch/Shrink" desc:"Stretch or shrink a vector by resampling." kw:[vop] }
+
+// Return the average value of the contents of sbp[] between two fractional indexes
+T_t  cmVOT_FracAvg( double bi, double ei, const T_t* sbp, unsigned sn );
+
+// Shrinking function - Decrease the size of sbp[] by averaging blocks of values into single values in dbp[]
+T_t* cmVOT_DownSampleAvg( T_t* dbp, unsigned dn, const T_t* sbp, unsigned sn );
+
+// Stretching function - linear interpolate between points in sbp[] to fill dbp[] ... where dn > sn
+T_t* cmVOT_UpSampleInterp( T_t* dbp, unsigned dn, const T_t* sbp, unsigned sn );
+
+// Stretch or shrink the sbp[] to fit into dbp[]
+T_t* cmVOT_FitToSize( T_t* dbp, unsigned dn, const T_t* sbp, unsigned sn );
+
+// Stretch or shrink sV[] to fit into dV[] using a simple linear mapping.
+// When stretching (sn<dn) each source element is repeated dn/sn times
+// and the last fraction position is interpolated.  When shrinking 
+// (sn>dn) each dest value is formed by the average of sequential segments
+// of sn/dn source elements. Fractional values are used at the beginning
+// and end of each segment.
+T_t* cmVOT_LinearMap(T_t* dV, unsigned dn, T_t* sV, unsigned sn );
+
+//======================================================================================================================
+//)
+
+//( { label:"Random number generation" desc:"Generate random numbers." kw:[vop] }
+
+// Generate a vector of uniformly distributed random numbers in the range minVal to maxVal.
+T_t* cmVOT_Random( T_t* dbp, unsigned dn, T_t minVal, T_t maxVal );
+
+// Generate dn random numbers integers between 0 and wn-1 based on a the relative 
+// weights in wp[wn].  Note thtat the weights do not have to sum to 1.0.
+unsigned*  cmVOT_WeightedRandInt( unsigned* dbp, unsigned dn, const T_t* wp, unsigned wn );
+
+// Generate a vector of normally distributed univariate random numbers 
+T_t* cmVOT_RandomGauss(  T_t* dbp, unsigned dn, T_t mean, T_t var );
+
+// Generate a vector of normally distributed univariate random numbers where each value has been drawn from a 
+// seperately parameterized Gaussian distribution. meanV[] and varV[] must both contain dn velues.
+T_t* cmVOT_RandomGaussV( T_t* dbp, unsigned dn, const T_t* meanV, const T_t* varV );
+
+// Generate a matrix of multi-dimensional random values. Each column represents a single vector value and each row contains a dimension.
+// meanV[] and varV[] must both contain drn elements where each meanV[i],varV[i] pair parameterize one dimensions Gaussian distribution.
+T_t* cmVOT_RandomGaussM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* meanV, const T_t* varV );
+T_t* cmVOT_RandomGaussDiagM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* meanV, const T_t* diagCovarM );
+
+// Generate a matrix of multivariate random values drawn from a normal distribution.
+// The dimensionality of the values are 'drn'.
+// The count of returned values is 'dcn'.
+// meanV[drn] and covarM[drn,drn] parameterize the normal distribution.
+// The covariance matrix must be symetric and positive definite. 
+// t[(drn*drn) ] points to scratch memory or is set to NULL if the function should
+//   allocate the memory internally.
+// Based on octave function mvrnd.m.
+T_t* cmVOT_RandomGaussNonDiagM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* meanV, const T_t* covarM, T_t* t );
+
+// Same as RandomGaussNonDiagM() except requires the upper trianglular 
+// Cholesky factor of the covar matrix in 'uM'. 
+T_t* cmVOT_RandomGaussNonDiagM2( T_t* dbp, unsigned drn, unsigned dcn, const T_t* meanV, const T_t* uM );
+
+
+// Generate a matrix of N*K multi-dimensional data points.
+// Where D is the dimensionality of the data. (D == drn).
+// K is the number of multi-dimensional PDF's (clusters).
+// N is the number of data points to generate per cluster. 
+// dbp[ D, N*K ] contains the returned data point. 
+// The first N columns is associated with the cluster 0, 
+// the next N columns is associated with cluster 1, ...
+// meanM[ D, K ] and varM[D,K] parameterize the generating PDF.s for each cluster
+T_t* cmVOT_RandomGaussMM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* meanM, const T_t* varM, unsigned K );
+
+
+// Evaluate the univariate normal distribution defined by 'mean' and 'stdDev'.
+T_t* cmVOT_GaussPDF( T_t* dbp, unsigned dn, const T_t* sbp, T_t mean, T_t stdDev );
+
+// 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].  D is the dimensionality of the data. N is the number of
+// data points to evaluate and values to return in yV[N]. 
+// Set diagFl to true if covarM is diagonal.
+// The function fails and returns false if the covariance matrix is singular.
+bool cmVOT_MultVarGaussPDF( T_t* yV, const T_t* xM, const T_t* meanV, const T_t* covarM, unsigned D, unsigned N, bool diagFl );
+
+// Same as multVarGaussPDF[] except takes the inverse covar mtx invCovarM[D,D] 
+// and log determinant of covar mtx. 
+// Always returns yV[].
+T_t* cmVOT_MultVarGaussPDF2( T_t* yV, const T_t* xM, const T_t* meanV, const T_t* invCovarM, T_t logDet, unsigned D, unsigned N, bool diagFl );
+
+// Same as multVarGaussPDF[] except uses a function to obtain the data vectors.
+// srcFunc() can filter the data points by returning NULL if the data vector at frmIdx should
+// not be evaluated against the PDF. In this case yV[frmIdx] will be set to 0.
+T_t* cmVOT_MultVarGaussPDF3( 
+  T_t*       yV, 
+  const T_t* (*srcFunc)(void* funcDataPtr, unsigned frmIdx ),
+  void*               funcDataPtr,
+  const T_t* meanV, 
+  const T_t* invCovarM, 
+  T_t        logDet, 
+  unsigned            D, 
+  unsigned            N, 
+  bool                diagFl );
+
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Signal generators" desc:"Generate periodic signals." kw:[vop] }
+
+// The following functions all return the phase of the next value. 
+unsigned      cmVOT_SynthSine(      T_t* dbp, unsigned dn, unsigned phase, double srate, double hz );
+unsigned      cmVOT_SynthCosine(    T_t* dbp, unsigned dn, unsigned phase, double srate, double hz );
+unsigned      cmVOT_SynthSquare(    T_t* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt );
+unsigned      cmVOT_SynthTriangle(  T_t* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt );
+unsigned      cmVOT_SynthSawtooth(  T_t* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt );
+unsigned      cmVOT_SynthPulseCos(  T_t* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt );
+unsigned      cmVOT_SynthImpulse(   T_t* dbp, unsigned dn, unsigned phase, double srate, double hz );
+unsigned      cmVOT_SynthPhasor(    T_t* dbp, unsigned dn, unsigned phase, double srate, double hz ); 
+
+
+// Return value should be passed back via delaySmp on the next call.
+T_t  cmVOT_SynthPinkNoise( T_t* dbp, unsigned dn, T_t delaySmp );
+
+//======================================================================================================================
+//)
+
+//( { label:"Exponential conversion" desc:"pow() and log() functions." kw:[vop] }
+
+// Raise dbp[] to the power 'expon'
+T_t* cmVOT_PowVS(  T_t* dbp, unsigned dn, T_t expon );
+T_t* cmVOT_PowVVS( T_t* dbp, unsigned dn, const T_t* sp, T_t expon );
+
+// Take the natural log of all values in sbp[dn]. It is allowable for sbp point to the same array as dbp=.
+T_t* cmVOT_LogV( T_t* dbp, unsigned dn, const T_t* sbp );
+
+//======================================================================================================================
+//)
+
+//( { label:"dB Conversions" desc:"Convert vectors between dB,linear and power representations." kw:[vop] }
+
+// Convert a magnitude (amplitude) spectrum to/from decibels. 
+// It is allowable for dbp==sbp.
+T_t* cmVOT_AmplToDbVV( T_t* dbp, unsigned dn, const T_t* sbp, T_t minDb );
+T_t* cmVOT_DbToAmplVV( T_t* dbp, unsigned dn, const T_t* sbp);
+
+T_t* cmVOT_PowToDbVV( T_t* dbp, unsigned dn, const T_t* sbp, T_t minDb );
+T_t* cmVOT_DbToPowVV( T_t* dbp, unsigned dn, const T_t* sbp);
+
+T_t* cmVOT_LinearToDb(    T_t* dbp, unsigned dn, const T_t* sp, T_t mult );
+T_t* cmVOT_dBToLinear(    T_t* dbp, unsigned dn, const T_t* sp, T_t mult );
+T_t* cmVOT_AmplitudeToDb( T_t* dbp, unsigned dn, const T_t* sp );
+T_t* cmVOT_PowerToDb(     T_t* dbp, unsigned dn, const T_t* sp );
+T_t* cmVOT_dBToAmplitude( T_t* dbp, unsigned dn, const T_t* sp );
+T_t* cmVOT_dBToPower(     T_t* dbp, unsigned dn, const T_t* sp );
+//======================================================================================================================
+//)
+
+//( { label:"DSP Windows" desc:"DSP windowing functions." kw:[vop] }
+
+T_t  cmVOT_KaiserBetaFromSidelobeReject(  double sidelobeRejectDb );
+T_t  cmVOT_KaiserFreqResolutionFactor( double sidelobeRejectDb );
+T_t* cmVOT_Kaiser(  T_t* dbp, unsigned dn, double beta );
+T_t*	cmVOT_Gaussian(T_t* dbp, unsigned dn, double mean, double variance );
+T_t* cmVOT_Hamming( T_t* dbp, unsigned dn );
+T_t* cmVOT_Hann(    T_t* dbp, unsigned dn );
+T_t* cmVOT_Triangle(T_t* dbp, unsigned dn );
+
+// The MATLAB equivalent Hamming and Hann windows.
+//T_t* cmVOT_HammingMatlab(T_t* dbp, unsigned dn );
+T_t* cmVOT_HannMatlab(   T_t* dbp, unsigned dn );
+
+// Simulates the MATLAB GaussWin function. Set arg to 2.5 to simulate the default arg
+// as used by MATLAB.
+T_t*	cmVOT_GaussWin( T_t* dbp, unsigned dn, double arg );
+//======================================================================================================================
+//)
+
+//( { label:"DSP Filters" desc:"DSP filtering functions." kw:[vop] }
+
+// Direct form II algorithm based on the MATLAB implmentation
+// http://www.mathworks.com/access/helpdesk/help/techdoc/ref/filter.html#f83-1015962
+// The only difference between this function and the equivalent MATLAB filter() function
+// is that the first feedforward coeff is given as a seperate value. The first  b coefficient
+//  in this function is therefore the same as the second coefficient in the MATLAB function.
+//  and the first a[] coefficient (which is generally set to 1.0) is skipped.
+//  Example:
+//  Matlab:         b=[.5 .4 .3]  a=[1 .2 .1]
+//  Equiv:  b0 = .5 b=[   .4 .3]  a=[  .2 .1]; 
+//
+// y[yn] - output vector 
+// x[xn] - input vector. xn must be <= yn. if xn < yn then the end of y[] is set to zero.
+// b0 - signal scale. This can also be seen as b[0] (which is not included in b[])
+// b[dn] - feedforward coeff's b[1..dn-1]
+// a[dn] - feedback coeff's    a[1..dn-1]
+// d[dn+1] - delay registers - note that this array must be one element longer than the coeff arrays.
+// 
+T_t* cmVOT_Filter( T_t* y, unsigned yn, const T_t* x, unsigned xn, cmReal_t b0, const cmReal_t* b, const cmReal_t* a,  cmReal_t* d, unsigned dn );
+
+struct cmFilter_str;
+//typedef cmRC_t (*cmVOT_FiltExecFunc_t)( struct acFilter_str* f,  const T_t* x, unsigned xn, T_t* y, unsigned yn );
+T_t* cmVOT_FilterFilter(struct cmFilter_str* f, cmRC_t (*func)( struct cmFilter_str* f,  const T_t* x, unsigned xn, T_t* y, unsigned yn ), const cmReal_t bb[], unsigned bn, const cmReal_t aa[], unsigned an, const T_t* x, unsigned xn, T_t* y, unsigned yn );
+
+// Compute the coefficients of a low/high pass FIR filter
+// wndV[dn] gives the window function used to truncate the ideal low-pass impulse response.
+// Set wndV to NULL to use a unity window.
+// See enum { kHighPass_LPSincFl=0x01, kNormalize_LPSincFl=0x02 } in cmVectOps.h
+T_t* cmVOT_LP_Sinc(T_t* dp, unsigned dn, const T_t* wndV, double srate, double fcHz, unsigned flags );
+
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Spectral Masking" desc:"A collection of spectral masking functions." kw:[vop] }
+
+// Compute a set of filterCnt mel filter masks for wieghting magnitude spectra consisting of binCnt bins.
+// The spectrum is divided into bandCnt equal bands in the mel domain
+// Each row of the matrix contains the mask for a single filter band consisting of binCnt elements.  
+// See enum{ kShiftMelFl=0x01, kNormalizeMelFl=0x02 } in cmVectOps.h
+// Set kShiftMelFl to shift the mel bands onto the nearest FFT bin.
+// Set kNormalizeMelFl to normalize the combined filters for unity gain.
+T_t* cmVOT_MelMask( T_t* maskMtx, unsigned bandCnt, unsigned binCnt, double srate, unsigned flags );
+
+// Fill binIdxV[bandCnt] and cntV[bandCnt] with a bin to band map.
+// binIdx[] contains the first (minimum) bin index for a given band.
+// cntV[]   contains the count of bins for each band.
+// bandCnt is the number of bark bands to return 
+// The function returns the actual number of bands mapped which will always be <= 23.
+unsigned cmVOT_BarkMap(unsigned* binIdxV, unsigned* cntV, unsigned bandCnt, unsigned binCnt, double srate );
+
+// Calc a set of triangle fitler masks into each row of maskMtx.
+// maskMtx[ bandCnt, binCnt ] - result matrix
+// binHz - freq resolution of the output filters.
+// stSpread - Semi-tone spread above and below each center frequency (stSpread*2) is the total bandwidth. 
+//            (Only used if lowHzV or uprHzV are NULL)
+// lowHz[ bandCnt ] - set of upper frequency limits for each band.
+// ctrHz[ bandCnt ] set to the center value in Hz for each band
+// uprHz[ bandCnt ] - set of lower frequency limits for each band.
+// Note if lowHz[] and uprHz[] are set to NULL then stSpread is used to set the bandwidth of each band.
+T_t* cmVOT_TriangleMask(T_t* maskMtx, unsigned bandCnt, unsigned binCnt, const T_t* ctrHzV, T_t binHz, T_t stSpread, const T_t* lowHzV, const T_t* uprHzV );
+
+// Calculate a set of Bark band triangle filters into maskMtx.
+// Each row of maskMtx contains the filter for one band.
+// maskMtx[ bandCnt, binCnt ]
+// bandCnt - the number of triangle bankds. If bandCnt is > 24 it will be reduced to 24.
+// binCnt - the number of bins in the filters.
+// binHz - the width of each bin in Hz.
+T_t* cmVOT_BarkMask(T_t* maskMtx, unsigned bandCnt, unsigned binCnt, double binHz );
+
+// Terhardt 1979 (Calculating virtual pitch, Hearing Research #1, pp 155-182)
+// See enum { kNoTtmFlags=0, kModifiedTtmFl=0x01 } in cmVectOps.h
+T_t* cmVOT_TerhardtThresholdMask(T_t* maskV, unsigned binCnt,  double srate, unsigned flags);
+
+//Schroeder et al., 1979, JASA, Optimizing digital speech coders by exploiting masking properties of the human ear
+T_t* cmVOT_ShroederSpreadingFunc(T_t* m, unsigned bandCnt, double srate);
+
+//======================================================================================================================
+//)
+
+//( { label:"Machine learning" desc:"K-means clustering and Viterbi algorithms." kw:[vop] }
+
+// Assign each data point to one of k clusters using an expectation-maximization algorithm.
+// k gives the number of clusters to identify
+// Each column of sp[ srn, scn ] contains a multidimensional data point. 
+// srn therefore defines the dimensionality of the data.
+// Each column of centroidV[ srn, k ] is set to the centroid of each of k clusters.
+// classIdxV[ scn ] assigns the index (0 to k-1) of a cluster to each soure data point
+// The function returns the number of iterations required for the EM process to converge.
+// selIdxV[ scn ] is optional and contains a list of id's assoc'd with each column of sM.
+// selKey is a integer value.
+// If selIdxV is non-NULL then only columns of sM[] where selIdxV[] == selKey will be clustered.
+// All columns of sM[] where the associated column in selIdxV[] do not match will be ignored.
+// Set 'initFromCentroidFl' to true if the initial centroids should be taken from centroidM[].
+// otherwise the initial centroids are selected from 'k' random data points in sp[].
+// The distance function distFunc(cV,dV,dN) is called to determine the distance from a 
+// centroid the centroid 'cV[dN]' to a data point 'dV[dN]'. 'dN' is the dimensionality of the
+// feature vector and is therefore equal to 'srn'.
+unsigned cmVOT_Kmeans( 
+  unsigned*           classIdxV, 
+  T_t*       centroidM, 
+  unsigned            k, 
+  const T_t* sp, 
+  unsigned            srn, 
+  unsigned            scn, 
+  const unsigned*     selIdxV, 
+  unsigned            selKey, 
+  bool                initFromCentroidFl,  
+  T_t (*distFunc)( void* userPtr, const T_t* cV, const T_t* dV, unsigned dN ), 
+  void*               userDistPtr ); 
+
+// 'srcFunc() should return NULL if the data point located at 'frmIdx' should not be included in the clustering.
+// Clustering is considered to be complete after 'maxIterCnt' iterations or when
+// 'deltaStopCnt' or fewer data points change class on a single iteration
+unsigned cmVOT_Kmeans2( 
+  unsigned*           classIdxV,         // classIdxV[scn] - data point class assignments
+  T_t*       centroidM,         // centroidM[srn,K] - cluster centroids
+  unsigned            K,                 // count of clusters
+  const T_t* (*srcFunc)(void* userPtr, unsigned frmIdx ),
+  unsigned            srn,               // dimensionality of each data point
+  unsigned            scn,               // count of data points
+  void*               userSrcPtr,        // callback data for srcFunc
+  T_t (*distFunc)( void* userPtr, const T_t* cV, const T_t* dV, unsigned dN ), 
+  void*              userDistPtr,        // arg. to distFunc()
+  int                iterCnt,            // max. number of iterations (-1 to ignore)
+  int                deltaStopCnt);      // if less than deltaStopCnt data points change classes on a given iteration then convergence occurs.
+
+// Determine the most likely state sequece stateV[timeN] given a 
+// transition matrix a[stateN,stateN], 
+// observation probability matrix b[stateN,timeN] and 
+// initial state probability vector phi[stateN].  
+// a[i,j] is the probability of transitioning from state i to state j.
+// b[i,t] is the probability of state i emitting the obj t.
+void cmVOT_DiscreteViterbi(unsigned* stateV, unsigned timeN, unsigned stateN, const T_t* phi, const T_t* a, const T_t* b );
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Graphics" desc:"Graphics related algorithms." kw:[vop] }
+
+// Generate the set of coordinates which describe a circle with a center at x,y.
+// dbp[dn,2] must contain 2*dn elements.  The first column holds the x coord and and the second holds the y coord.
+T_t* cmVOT_CircleCoords( T_t* dbp, unsigned dn, T_t x, T_t y, T_t varX, T_t varY );
+
+// Clip the line defined by x0,y0 to x1,y1 into the rect defined by xMin,yMin xMax,yMax.
+bool cmVOT_ClipLine( T_t* x0, T_t* y0, T_t* x1, T_t* y1, T_t xMin, T_t yMin, T_t xMax, T_t yMax );
+
+// Return true if the line defined by x0,y0 to x1,y1 intersects with
+// the rectangle formed by xMin,yMin - xMax,yMax
+bool cmVOT_IsLineInRect( T_t x0, T_t y0, T_t x1, T_t y1, T_t xMin, T_t yMin, T_t xMax, T_t yMax );
+
+
+// Return the perpendicular distance from the line formed by x0,y0 and x1,y1
+// and the point px,py
+T_t cmVOT_PtToLineDistance( T_t x0, T_t y0, T_t x1, T_t y1, T_t px, T_t py);                              
+
+//======================================================================================================================
+//)
+
+//( { label:"Miscellaneous DSP" desc:"Common DSP algorithms." kw:[vop] }
+
+// Compute the complex transient detection function from successive spectral frames.
+// The spectral magntidue mag0V precedes mag1V and the phase (radians) spectrum phs0V precedes the phs1V which precedes phs2V.  
+// binCnt gives the length of each of the spectral vectors.
+T_t  cmVOT_ComplexDetect(const T_t* mag0V, const T_t* mag1V, const T_t* phs0V, const T_t* phs1V, const T_t* phs2V, unsigned binCnt );
+
+// Compute a set of DCT-II coefficients. Result dp[ coeffCnt, filtCnt ]
+T_t* cmVOT_DctMatrix( T_t* dp, unsigned coeffCnt, unsigned filtCnt );
+
+
+// Set the indexes of local peaks greater than threshold in dbp[].
+// Returns the number of peaks in dbp[]
+// The maximum number of peaks from n source values is max(0,floor((n-1)/2)).
+// Note that peaks will never be found at index 0 or index sn-1.
+unsigned cmVOT_PeakIndexes( unsigned* dbp, unsigned dn, const T_t* sbp, unsigned sn, T_t threshold );
+
+// Return the index of the bin containing v otherwise return kInvalidIdx if v is below sbp[0] or above sbp[ n-1 ]
+// The bin limits are contained in sbp[].
+// The value in spb[] are therefore expected to be in increasing order.
+// The value returned will be in the range 0:sn-1.
+unsigned cmVOT_BinIndex( const T_t* sbp, unsigned sn, T_t v );
+
+
+// Given the points x0[xy0N],y0[xy0N] fill y1[i] with the interpolated value of y0[] at
+// x1[i].  Note that x0[] and x1[] must be increasing monotonic.
+// This function is similar to the octave interp1() function.
+void cmVOT_Interp1(T_t* y1, const T_t* x1, unsigned xy1N, const T_t* x0, const T_t* y0, unsigned xy0N );
+ 
+//======================================================================================================================
+//)
+
+
+//( { label:"Matrix ops" desc:"Common 2D matrix operations and accessors." kw:[vop] }
+
+// 2D matrix accessors
+T_t* cmVOT_Col(    T_t* m, unsigned ci, unsigned rn, unsigned cn );
+T_t* cmVOT_Row(    T_t* m, unsigned ri, unsigned rn, unsigned cn );
+T_t* cmVOT_ElePtr( T_t* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
+T_t  cmVOT_Ele(    T_t* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
+void          cmVOT_Set(    T_t* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn, T_t v );
+
+const T_t* cmVOT_CCol(    const T_t* m, unsigned ci, unsigned rn, unsigned cn );
+const T_t* cmVOT_CRow(    const T_t* m, unsigned ri, unsigned rn, unsigned cn );
+const T_t* cmVOT_CElePtr( const T_t* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
+T_t        cmVOT_CEle(    const T_t* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
+
+
+// Set only the diagonal of a square mtx to sbp.
+T_t* cmVOT_Diag( T_t* dbp, unsigned n, const T_t* sbp );
+
+// Set the diagonal of a square mtx to db to sbp and set all other values to zero.
+T_t* cmVOT_DiagZ( T_t* dbp, unsigned n, const T_t* sbp ); 
+
+// Create an identity matrix (only sets 1's not zeros).
+T_t* cmVOT_Identity(  T_t* dbp, unsigned rn, unsigned cn );
+
+// Zero the matrix and then fill it as an identity matrix.
+T_t* cmVOT_IdentityZ( T_t* dbp, unsigned rn, unsigned cn );
+
+// Transpose the matrix sbp[srn,scn] into dbp[scn,srn]
+T_t* cmVOT_Transpose(  T_t* dbp, const T_t* sbp, unsigned srn, unsigned scn );
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Fill,move,copy" desc:"Basic data movement and initialization." kw:[vop] }
+
+// Fill a vector with a value. If value is 0 then the function is accellerated via memset().
+T_t* cmVOT_Fill( T_t* dbp, unsigned dn, T_t value  );
+
+// Fill a vector with zeros
+T_t* cmVOT_Zero( T_t* dbp, unsigned dn  );
+
+// Analogous to memmove()
+T_t* cmVOT_Move(  T_t* dbp, unsigned dn, const T_t* sp );
+
+// Fill the vector from various sources
+T_t* cmVOT_Copy(  T_t* dbp, unsigned dn, const T_t* sp );
+T_t* cmVOT_CopyN( T_t* dbp, unsigned dn, unsigned d_stride, const T_t* sp, unsigned s_stride );
+T_t* cmVOT_CopyU( T_t* dbp, unsigned dn, const unsigned* sp );
+T_t* cmVOT_CopyI( T_t* dbp, unsigned dn, const int* sp );
+T_t* cmVOT_CopyF( T_t* dbp, unsigned dn, const float* sp );
+T_t* cmVOT_CopyD( T_t* dbp, unsigned dn, const double* sp );
+T_t* cmVOT_CopyS( T_t* dbp, unsigned dn, const cmSample_t* sp );
+T_t* cmVOT_CopyR( T_t* dbp, unsigned dn, const cmReal_t* sp );
+
+// Fill the the destination vector from a source vector where the source vector contains
+// srcStride interleaved elements to be ignored. 
+T_t* cmVOT_CopyStride(  T_t* dbp, unsigned dn, const T_t* sp, unsigned srcStride );
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Shrink/Expand/Replace" desc:"Change the size of a vector." kw:[vop] }
+
+
+// Shrink the elemetns of dbp[dn] by copying all elements past t+tn to t.
+// This operation results in overwriting the elements in the range t[tn].
+// t[tn] must be entirely inside dbp[dn].
+T_t* cmVOT_Shrink( T_t* dbp, unsigned dn, const T_t* t, unsigned tn );
+
+// Expand dbp[[dn] by shifting all elements past t to t+tn.
+// This produces a set of empty elements in t[tn].
+// t must be inside or at the end of dbp[dn].
+// This results in a reallocation of dbp[]. Be sure to call cmMemFree(dbp)
+// to release the returned pointer.
+T_t* cmVOT_Expand( T_t* dbp, unsigned dn, const T_t* t, unsigned tn );                                                            
+
+// Replace the elements t[tn] with the elements in u[un]. 
+// t must be inside or at the end of dbp[dn].
+// This operation may result in a reallocation of dbp[]. Be sure to call cmMemFree(dbp)
+// to release the returned pointer.
+// IF dbp==NULL and tn==0 then the dbp[un] is allocated and returned 
+// with the contents of u[un].
+T_t* cmVOT_Replace(T_t* dbp, unsigned* dn, const T_t* t, unsigned tn, const T_t* u, unsigned un );
+
+//======================================================================================================================
+//)
+
+
+
+//( { label:"Rotate/Shift/Flip/Sequence" desc:"Modify/generate the vector sequence." kw:[vop] }
+
+// Assuming a row vector positive shiftCnt rotates right, negative shiftCnt rotates left.
+T_t* cmVOT_Rotate( T_t* dbp, unsigned dn, int shiftCnt );
+
+// Equivalent to Matlab circshift().
+T_t* cmVOT_RotateM( T_t* dbp, unsigned drn, unsigned dcn, const T_t* sbp, int rShift, int cShift  );
+
+// Assuming a row vector positive shiftCnt shifts right, negative shiftCnt shifts left.
+T_t* cmVOT_Shift( T_t* dbp, unsigned dn, int shiftCnt, T_t fill );
+
+// Reverse the contents of the vector.
+T_t* cmVOT_Flip(  T_t* dbp, unsigned dn);
+
+// Fill dbp[] with a sequence of values. Returns next value. 
+T_t  cmVOT_Seq( T_t* dbp, unsigned dn, T_t beg, T_t incr );
+
+
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Arithmetic" desc:"Add,Sub,Mult,Divde" kw:[vop] }
+
+T_t* cmVOT_SubVS(  T_t* dp, unsigned dn, T_t v );
+T_t* cmVOT_SubVV(  T_t* dp, unsigned dn, const T_t* v );
+T_t* cmVOT_SubVVS( T_t* dp, unsigned dn, const T_t* v, T_t s );
+T_t* cmVOT_SubVVNN(T_t* dp, unsigned dn, unsigned dnn, const T_t* sp, unsigned snn );
+T_t* cmVOT_SubVVV( T_t* dp, unsigned dn, const T_t* sb0p, const T_t* sb1p );
+T_t* cmVOT_SubVSV( T_t* dp, unsigned dn, const T_t  s0, const T_t* sb1p );
+
+T_t* cmVOT_AddVS(  T_t* dp, unsigned dn, T_t v );
+T_t* cmVOT_AddVV(  T_t* dp, unsigned dn, const T_t* v );
+T_t* cmVOT_AddVVS( T_t* dp, unsigned dn, const T_t* v, T_t s );
+T_t* cmVOT_AddVVNN(T_t* dp, unsigned dn, unsigned dnn, const T_t* sp, unsigned snn );
+T_t* cmVOT_AddVVV( T_t* dp, unsigned dn, const T_t* sb0p, const T_t* sb1p );
+
+T_t* cmVOT_MultVVV( T_t* dbp, unsigned dn, const T_t* sb0p, const T_t* sb1p );
+T_t* cmVOT_MultVV(  T_t* dbp, unsigned dn, const T_t* sbp );
+T_t* cmVOT_MultVVNN(T_t* dp,  unsigned dn, unsigned dnn, const T_t* sp, unsigned snn );
+T_t* cmVOT_MultVS(  T_t* dbp, unsigned dn, T_t s );
+T_t* cmVOT_MultVVS( T_t* dbp, unsigned dn, const T_t* sbp, T_t s );
+T_t* cmVOT_MultVaVS( T_t* dbp, unsigned dn, const T_t* sbp, T_t s );
+T_t* cmVOT_MultSumVVS(T_t* dbp, unsigned dn, const T_t* sbp, T_t s );
+
+T_t* cmVOT_DivVVS( T_t* dbp, unsigned dn, const T_t* sb0p, T_t sb1 );
+T_t* cmVOT_DivVVV( T_t* dbp, unsigned dn, const T_t* sb0p, const T_t* sb1p );
+T_t* cmVOT_DivVV(  T_t* dbp, unsigned dn, const T_t* sb0p );
+T_t* cmVOT_DivVVNN(T_t* dp,  unsigned dn, unsigned dnn, const T_t* sp, unsigned snn );
+T_t* cmVOT_DivVS(  T_t* dbp, unsigned dn, T_t s );
+T_t* cmVOT_DivVSV( T_t* dp,  unsigned dn, const T_t  s0, const T_t* sb1p );
+
+// Set dest to 0 if denominator is 0.
+T_t* cmVOT_DivVVVZ( T_t* dbp, unsigned dn, const T_t* sb0p, const T_t* sb1p );
+T_t* cmVOT_DivVVZ(  T_t* dbp, unsigned dn, const T_t* sb0p );
+
+// Divide columns of dp[:,i] by each value in the source vector sp[i]. 
+T_t*  cmVOT_DivMS(    T_t* dp, unsigned drn, unsigned dcn, const T_t* sp ); 
+
+//======================================================================================================================
+//)
+
+//( { label:"Sum vectors" desc:"Operations which take sum vector elements." kw:[vop] }
+
+T_t  cmVOT_Sum(      const T_t* sp, unsigned sn );
+T_t  cmVOT_SumN(     const T_t* sp, unsigned sn, unsigned stride );
+
+// Sum the columns of sp[srn,scn] into dp[scn]. 
+// dp[] is zeroed prior to computing the sum.
+T_t*  cmVOT_SumM(     const T_t* sp, unsigned srn, unsigned scn, T_t* dp );
+
+// Sum the rows of sp[srn,scn] into dp[srn]
+// dp[] is zeroed prior to computing the sum.
+T_t*  cmVOT_SumMN(    const T_t* sp, unsigned srn, unsigned scn, T_t* dp );
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Min/max/median/mode" desc:"Simple descriptive statistics." kw:[vop] }
+
+T_t  cmVOT_Median(   const T_t* sp, unsigned sn );
+unsigned      cmVOT_MinIndex( const T_t* sp, unsigned sn, unsigned stride );
+unsigned      cmVOT_MaxIndex( const T_t* sp, unsigned sn, unsigned stride );
+T_t  cmVOT_Min(      const T_t* sp, unsigned sn, unsigned stride );
+T_t  cmVOT_Max(      const T_t* sp, unsigned sn, unsigned stride );
+
+T_t*  cmVOT_MinVV( T_t* dp, unsigned dn, const T_t* sp );
+T_t*  cmVOT_MaxVV( T_t* dp, unsigned dn, const T_t* sp );
+
+
+// Return index of max/min value into dp[scn] of each column of sp[srn,scn]
+unsigned*  cmVOT_MinIndexM( unsigned* dp, const T_t* sp, unsigned srn, unsigned scn );
+unsigned*  cmVOT_MaxIndexM( unsigned* dp, const T_t* sp, unsigned srn, unsigned scn );
+
+// Return the most frequently occuring element in sp.
+T_t  cmVOT_Mode(     const T_t* sp, unsigned sn );
+
+//======================================================================================================================
+//)
+
+//( { label:"Compare/Find" desc:"Compare, find, replace and count elements in a vector." kw:[vop] }
+
+// Return true if s0p[sn] is equal to s1p[sn]
+bool       cmVOT_IsEqual( const T_t* s0p, const T_t* s1p, unsigned sn );
+
+// Return true if all elements of s0p[sn] are within 'eps' of s1p[sn].
+// This function is based on cmMath.h:cmIsCloseX()
+bool cmVOT_IsClose( const T_t* s0p, const T_t* s1p, unsigned sn, double eps );
+
+// Replace all values <= lteKeyVal with replaceVal.  sp==dp is legal.
+T_t* cmVOT_ReplaceLte( T_t* dp, unsigned dn, const T_t* sp, T_t lteKeyVal, T_t replaceVal );
+
+// Return the index of 'key' in sp[sn] or cmInvalidIdx if 'key' does not exist.
+unsigned cmVOT_Find( const T_t* sp, unsigned sn, T_t key );
+
+// Count the number of times 'key' occurs in sp[sn].
+unsigned cmVOT_Count(const T_t* sp, unsigned sn, T_t key );
+
+//======================================================================================================================
+//)
+
+
+
+//( { label:"Absolute value" desc:"Absolute value and signal rectification." kw:[vop] }
+
+T_t*   cmVOT_Abs(   T_t* dbp, unsigned dn );
+
+// Half wave rectify the source vector.
+// dbp[] = sbp<0 .* sbp 
+// Overlapping the source and dest is allowable as long as dbp <= sbp. 
+T_t* cmVOT_HalfWaveRectify(T_t* dbp, unsigned dn, const T_t* sp );
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Filter" desc:"Apply filtering to a vector taking into account vector begin/end conditions." kw:[vop] }
+
+// Apply a median or other filter of order wndN to xV[xN] and store the result in yV[xN].
+// When the window goes off either side of the vector the window is shortened.
+// This algorithm produces the same result as the fn_thresh function in MATLAB fv codebase.
+void cmVOT_FnThresh( const T_t* xV, unsigned xN, unsigned wndN, T_t* yV, unsigned yStride, T_t (*fnPtr)(const T_t*, unsigned) );
+
+
+// Apply a median filter of order wndN  to xV[xN] and store the result in yV[xN].
+// When the window goes off either side of the vector the missing elements are considered
+// to be 0.
+// This algorithm produces the same result as the MATLAB medfilt1() function.
+void cmVOT_MedianFilt( const T_t* xV, unsigned xN, unsigned wndN, T_t* yV, unsigned yStride );
+//======================================================================================================================
+//)
+
+
+//( { label:"Edit distance" desc:"Calculate the Levenshtein edit distance between vectors." kw:[vop] }
+
+// Allocate and initialize a matrix for use by LevEditDist().
+// This matrix can be released with a call to cmMemFree().
+unsigned* cmVOT_LevEditDistAllocMtx(unsigned mtxMaxN);
+
+// Return the Levenshtein edit distance between two vectors.
+// m must point to a matrix pre-allocated by cmVOT_InitiLevEditDistMtx(maxN).
+double  cmVOT_LevEditDist(unsigned mtxMaxN, unsigned* m, const T_t* s0, int n0, const T_t* s1, int n1, unsigned maxN );
+
+// Return the Levenshtein edit distance between two vectors.
+// Edit distance with a max cost threshold. This version of the algorithm
+// will run faster than LevEditDist() because it will stop execution as soon
+// as the distance exceeds 'maxCost'.
+// 'maxCost' must be between 0.0 and 1.0 or it is forced into this range.
+// The maximum distance returned will be 'maxCost'.
+// m must point to a matrix pre-allocated by cmVOT_InitiLevEditDistMtx(maxN).
+double cmVOT_LevEditDistWithCostThresh( int mtxMaxN, unsigned* m, const T_t* s0, int n0, const T_t* s1, int n1, double maxCost, unsigned maxN );
+
+//======================================================================================================================
+//)
+
+

src/cmXml.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"XML file reader." kw[file] }
+
   enum
   {
     kOkXmlRC = cmOkRC,
@@ -101,6 +103,8 @@ extern "C" {
   
   
   cmXmlRC_t cmXmlTest( cmCtx_t* ctx, const cmChar_t* fn );
+
+  //)
   
 #ifdef __cpluspus
 }

src/dsp/cmDspBuiltIn.h

@@ -6,9 +6,13 @@
 extern "C" {
 #endif
 
+  
+  //( { file_desc:"Dataflow built-in process interface." kw:[snap] }
+
   // Returns NULL if index is outside of valid range.
   cmDspClassConsFunc_t cmDspClassGetBuiltIn( unsigned index );
 
+  //)
 
 
 #ifdef __cplusplus

src/dsp/cmDspCtx.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Dataflow global context interface." kw:[snap] }
+
   typedef cmHandle_t cmDspSysH_t;
   typedef cmHandle_t cmDspStoreH_t;
   
@@ -34,6 +36,8 @@ extern "C" {
     unsigned execDurUsecs;
   } cmDspCtx_t;
 
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/dsp/cmDspFx.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Large collection of real-time audio processing dataflow class descriptions originally developed for 'fluxo'." kw:[snap fluxo] }
+  
   struct cmDspClass_str* cmDelayClassCons(      cmDspCtx_t* ctx );
   struct cmDspClass_str* cmPShiftClassCons(     cmDspCtx_t* ctx );
   struct cmDspClass_str* cmLoopRecdClassCons(   cmDspCtx_t* ctx );
@@ -43,6 +45,8 @@ extern "C" {
   struct cmDspClass_str* cmBcastSymClassCons(   cmDspCtx_t* ctx );
   struct cmDspClass_str* cmSegLineClassCons(    cmDspCtx_t* ctx );
 
+  //)
+  
 #ifdef __cplusplus
 }
 #endif

src/dsp/cmDspPgm.h

@@ -5,6 +5,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Dataflow program instance interface." kw:[snap] }
+  
   typedef cmDspRC_t (*cmDspPgmFunc_t)( cmDspSysH_t h, void** userPtrPtr );
 
   typedef struct
@@ -20,7 +22,7 @@ extern "C" {
 
   _cmDspSysPgm_t* _cmDspSysPgmArrayBase();
   
-
+  //)
 
 #ifdef __cplusplus
 }

src/dsp/cmDspPgmKr.h

@@ -5,11 +5,15 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Dataflow pgm interfaces for 'GUTIM'." kw:[gutim snap] }
+  
   cmDspRC_t _cmDspSysPgm_TimeLine( cmDspSysH_t h, void** userPtrPtr );
   cmDspRC_t _cmDspSysPgm_TimeLineLite( cmDspSysH_t h, void** userPtrPtr );
   cmDspRC_t _cmDspSysPgm_TimeLineLiteAf( cmDspSysH_t h, void** userPtrPtr );
   cmDspRC_t _cmDspSysPgm_Tksb(cmDspSysH_t h, void** userPtrPtr );
   cmDspRC_t _cmDspSysPgm_TksbLite(cmDspSysH_t h, void** userPtrPtr );
+
+  //)
   
 #ifdef __cplusplus
   }

src/dsp/cmDspPgmKrChain.h

@@ -6,6 +6,8 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Signal processing chain implementation for 'GUTIM'." kw:[snap gutim] }
+
 typedef struct
 {
   const cmChar_t* tlFn;
@@ -44,6 +46,7 @@ void _cmDspSys_TlXformChain(
   unsigned        ach,
   unsigned        mch );
 
+  //)
 
 #ifdef __cplusplus
 }

src/dsp/cmDspPgmPPMain.h

@@ -1,6 +1,7 @@
 #ifndef cmDspPgmPPMain_h
 #define cmDspPgmPPMain_h
 
+//( { file_desc:"'fluxo' implementation header." kw:[fluxo] }
 
 cmDspInst_t*  _cmDspSys_PresetMgmt( cmDspSysH_t h, const cmChar_t* preLbl, unsigned presetGroupSymId );
 
@@ -44,6 +45,8 @@ const _cmDspPP_CircDesc_t* _cmDspPP_CircuitDesc( unsigned idx );
 cmDspRC_t _cmDspPP_CircuitSwitchAlloc( cmDspSysH_t h, _cmDspPP_Ctx_t* ctx, cmDspPP_CircuitSwitch_t* p, cmDspInst_t* reset, cmDspInst_t** csel, cmDspInst_t** ain, cmDspInst_t** ef );
 cmDspRC_t _cmDspPP_CircuitSwitchFree(  cmDspSysH_t h, cmDspPP_CircuitSwitch_t* p);
 
+//)
+
 #ifdef __cplusplus
 extern "C" {
 #endif

src/dsp/cmDspUi.h

@@ -8,7 +8,9 @@
 extern "C" {
 #endif
 
+  //( { file_desc:"Dataflow UI interfaces." kw:[snap] }
 
+  //)
 
 
 #ifdef __cplusplus

src/vop/cmVectOpsDoc.h

@@ -5,8 +5,9 @@
 // is generated using the gcc preprocessor.
 // switches: -E : Stop after preprocess
 //           -C : Do not strip comments.
-//           -P : Do not generate line markers 
-// gcc -E -C -P -o cmVectOpsDocOut.h cmVectOpsDoc.h
+//           -P : Do not generate line markers
+//           -traditional-cpp : preserve white space
+// gcc -E -C -P -traditional-cpp -o cmVectOpsDocOut.h cmVectOpsDoc.h
 
 
 #include "cmVectOpsTemplateUndef.h"
@@ -17,11 +18,9 @@
 #define VECT_OP_MIN        FLT_MIN
 #define VECT_OP_LAP_FUNC(F)        s##F
 #define VECT_OP_BLAS_FUNC(F) cblas_s##F
-
-//{
-//[
+//end_cut
+//( { file_desc:"Math vector operations." kw:[vop math] }
+//)
 #include "cmVectOpsTemplateHdr.h"
 #include "cmVectOpsRIHdr.h"
-//]
-//}
 

src/vop/cmVectOpsRICode.h

@@ -46,6 +46,57 @@ VECT_OP_TYPE VECT_OP_FUNC(CEle)( const VECT_OP_TYPE* m, unsigned ri, unsigned ci
 { return *VECT_OP_FUNC(CElePtr)(m,ri,ci,rn,cn); }
 
 
+VECT_OP_TYPE* VECT_OP_FUNC(Diag)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp )
+{
+  unsigned i,j;
+  for(i=0,j=0; i<n && j<n; ++i,++j)
+    dbp[ (i*n) + j ] = sbp[i];
+
+  return dbp;  
+}
+
+
+VECT_OP_TYPE* VECT_OP_FUNC(DiagZ)(VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp )
+{
+  VECT_OP_FUNC(Fill)(dbp,n*n,0);
+  return VECT_OP_FUNC(Diag)(dbp,n,sbp);
+}
+
+
+VECT_OP_TYPE* VECT_OP_FUNC(Identity)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn )
+{
+  unsigned i,j;
+  for(i=0,j=0; i<cn && j<rn; ++i,++j)
+      dbp[ (i*rn) + j ] = 1;
+
+  return dbp;
+}
+
+
+VECT_OP_TYPE* VECT_OP_FUNC(IdentityZ)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn )
+{
+  VECT_OP_FUNC(Fill)(dbp,rn*cn,0);
+  return VECT_OP_FUNC(Identity)(dbp,rn,cn);
+}
+
+
+VECT_OP_TYPE* VECT_OP_FUNC(Transpose)( VECT_OP_TYPE* dbp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn )
+{
+  VECT_OP_TYPE*       dp  = dbp;
+  const VECT_OP_TYPE* dep = dbp + (srn*scn);
+
+  while( dbp < dep )
+  {
+    const VECT_OP_TYPE* sbp = sp++;
+    const VECT_OP_TYPE* sep = sbp + (srn*scn);
+
+    for(; sbp < sep; sbp+=srn )
+      *dbp++ = *sbp;
+  }
+
+  return dp;
+}
+
 
 
 VECT_OP_TYPE* VECT_OP_FUNC(Fill)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE value  )
@@ -364,6 +415,17 @@ VECT_OP_TYPE* VECT_OP_FUNC(Flip)(  VECT_OP_TYPE* dbp, unsigned dn)
   return dbp;
 }
 
+VECT_OP_TYPE VECT_OP_FUNC(Seq)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE beg, VECT_OP_TYPE incr )
+{
+  const VECT_OP_TYPE* dep = dbp + dn;
+  unsigned i = 0;
+  for(; dbp<dep; ++i)
+    *dbp++ = beg + (incr*i);
+  return beg + (incr*i);
+}
+
+
+
 
 VECT_OP_TYPE* VECT_OP_FUNC(SubVS)( VECT_OP_TYPE* bp, unsigned n, VECT_OP_TYPE v )
 {
@@ -660,15 +722,6 @@ VECT_OP_TYPE*  VECT_OP_FUNC(SumMN)(const VECT_OP_TYPE* sp, unsigned srn, unsigne
   return dp;
 }
 
-VECT_OP_TYPE*   VECT_OP_FUNC(Abs)(   VECT_OP_TYPE* dbp, unsigned dn )
-{
-  unsigned i;
-  for(i=0; i<dn; ++i)
-    if( dbp[i]<0 )     
-      dbp[i] = -dbp[i];
-
-  return dbp;  
-}
 
 // mi is a target value - it holds the number of elements in ap[an] which must be be less than the median value.
 // If the initial array contains an even number of values then the median value is formed by averaging the two center values.
@@ -880,27 +933,6 @@ unsigned*  VECT_OP_FUNC(MaxIndexM)( unsigned* dp, const VECT_OP_TYPE* sp, unsign
   return dp;
 }
 
-bool VECT_OP_FUNC(IsEqual)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
-{
-  const VECT_OP_TYPE* ep = s0p + sn;
-  for(; s0p < ep; ++s0p,++s1p )
-    if( *s0p != *s1p )
-      return false;
-  return true;
-}
-
-bool VECT_OP_FUNC(IsClose)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn, double eps )
-{
-  const VECT_OP_TYPE* ep = s0p + sn;
-  for(; s0p < ep; ++s0p,++s1p )
-  {
-    if( !cmIsClose(*s0p,*s1p,eps) )
-      return false;
-  }
-  return true;
-}
-
-
 VECT_OP_TYPE  VECT_OP_FUNC(Mode)( const VECT_OP_TYPE* sp, unsigned sn )
 {
   unsigned     n[sn];
@@ -965,6 +997,49 @@ VECT_OP_TYPE  VECT_OP_FUNC(Mode)( const VECT_OP_TYPE* sp, unsigned sn )
   return v[j];
 }
 
+VECT_OP_TYPE*   VECT_OP_FUNC(Abs)(   VECT_OP_TYPE* dbp, unsigned dn )
+{
+  unsigned i;
+  for(i=0; i<dn; ++i)
+    if( dbp[i]<0 )     
+      dbp[i] = -dbp[i];
+
+  return dbp;  
+}
+
+VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
+{
+  VECT_OP_TYPE* dp = dbp;
+  VECT_OP_TYPE* ep = dbp + dn;
+  for(; dp < ep; ++dp,++sp )
+    *dp = *sp < 0 ? 0 : *sp;
+
+  return dbp;
+}
+
+
+
+bool VECT_OP_FUNC(IsEqual)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
+{
+  const VECT_OP_TYPE* ep = s0p + sn;
+  for(; s0p < ep; ++s0p,++s1p )
+    if( *s0p != *s1p )
+      return false;
+  return true;
+}
+
+bool VECT_OP_FUNC(IsClose)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn, double eps )
+{
+  const VECT_OP_TYPE* ep = s0p + sn;
+  for(; s0p < ep; ++s0p,++s1p )
+  {
+    if( !cmIsClose(*s0p,*s1p,eps) )
+      return false;
+  }
+  return true;
+}
+
+
 unsigned VECT_OP_FUNC(Find)( const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE key )
 {
   const VECT_OP_TYPE* sbp = sp;
@@ -1003,67 +1078,6 @@ VECT_OP_TYPE* VECT_OP_FUNC(ReplaceLte)( VECT_OP_TYPE* dp, unsigned dn, const VEC
   return rp;
 }
 
-VECT_OP_TYPE* VECT_OP_FUNC(Diag)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp )
-{
-  unsigned i,j;
-  for(i=0,j=0; i<n && j<n; ++i,++j)
-    dbp[ (i*n) + j ] = sbp[i];
-
-  return dbp;  
-}
-
-
-VECT_OP_TYPE* VECT_OP_FUNC(DiagZ)(VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp )
-{
-  VECT_OP_FUNC(Fill)(dbp,n*n,0);
-  return VECT_OP_FUNC(Diag)(dbp,n,sbp);
-}
-
-
-VECT_OP_TYPE* VECT_OP_FUNC(Identity)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn )
-{
-  unsigned i,j;
-  for(i=0,j=0; i<cn && j<rn; ++i,++j)
-      dbp[ (i*rn) + j ] = 1;
-
-  return dbp;
-}
-
-
-VECT_OP_TYPE* VECT_OP_FUNC(IdentityZ)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn )
-{
-  VECT_OP_FUNC(Fill)(dbp,rn*cn,0);
-  return VECT_OP_FUNC(Identity)(dbp,rn,cn);
-}
-
-
-VECT_OP_TYPE* VECT_OP_FUNC(Transpose)( VECT_OP_TYPE* dbp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn )
-{
-  VECT_OP_TYPE*       dp  = dbp;
-  const VECT_OP_TYPE* dep = dbp + (srn*scn);
-
-  while( dbp < dep )
-  {
-    const VECT_OP_TYPE* sbp = sp++;
-    const VECT_OP_TYPE* sep = sbp + (srn*scn);
-
-    for(; sbp < sep; sbp+=srn )
-      *dbp++ = *sbp;
-  }
-
-  return dp;
-}
-
-VECT_OP_TYPE VECT_OP_FUNC(Seq)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE beg, VECT_OP_TYPE incr )
-{
-  const VECT_OP_TYPE* dep = dbp + dn;
-  unsigned i = 0;
-  for(; dbp<dep; ++i)
-    *dbp++ = beg + (incr*i);
-  return beg + (incr*i);
-}
-
-
 void VECT_OP_FUNC(FnThresh)( const VECT_OP_TYPE* xV, unsigned xN, unsigned wndN, VECT_OP_TYPE* yV, unsigned yStride, VECT_OP_TYPE (*fnPtr)(const VECT_OP_TYPE*, unsigned) )
 {
   int i0 = cmIsOddU(wndN) ?  (wndN-1)/2 : wndN/2;

src/vop/cmVectOpsRIHdr.h

@@ -1,4 +1,8 @@
 
+
+//( { label:"Matrix ops" desc:"Common 2D matrix operations and accessors." kw:[vop] }
+
+// 2D matrix accessors
 VECT_OP_TYPE* VECT_OP_FUNC(Col)(    VECT_OP_TYPE* m, unsigned ci, unsigned rn, unsigned cn );
 VECT_OP_TYPE* VECT_OP_FUNC(Row)(    VECT_OP_TYPE* m, unsigned ri, unsigned rn, unsigned cn );
 VECT_OP_TYPE* VECT_OP_FUNC(ElePtr)( VECT_OP_TYPE* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
@@ -11,17 +15,37 @@ const VECT_OP_TYPE* VECT_OP_FUNC(CElePtr)( const VECT_OP_TYPE* m, unsigned ri, u
 VECT_OP_TYPE        VECT_OP_FUNC(CEle)(    const VECT_OP_TYPE* m, unsigned ri, unsigned ci, unsigned rn, unsigned cn );
 
 
+// Set only the diagonal of a square mtx to sbp.
+VECT_OP_TYPE* VECT_OP_FUNC(Diag)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp );
+
+// Set the diagonal of a square mtx to db to sbp and set all other values to zero.
+VECT_OP_TYPE* VECT_OP_FUNC(DiagZ)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp ); 
+
+// Create an identity matrix (only sets 1's not zeros).
+VECT_OP_TYPE* VECT_OP_FUNC(Identity)(  VECT_OP_TYPE* dbp, unsigned rn, unsigned cn );
+
+// Zero the matrix and then fill it as an identity matrix.
+VECT_OP_TYPE* VECT_OP_FUNC(IdentityZ)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn );
+
+// Transpose the matrix sbp[srn,scn] into dbp[scn,srn]
+VECT_OP_TYPE* VECT_OP_FUNC(Transpose)(  VECT_OP_TYPE* dbp, const VECT_OP_TYPE* sbp, unsigned srn, unsigned scn );
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Fill,move,copy" desc:"Basic data movement and initialization." kw:[vop] }
 
-/// Fill a vector with a value. If value is 0 then the function is accellerated via memset().
+// Fill a vector with a value. If value is 0 then the function is accellerated via memset().
 VECT_OP_TYPE* VECT_OP_FUNC(Fill)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE value  );
 
 // Fill a vector with zeros
 VECT_OP_TYPE* VECT_OP_FUNC(Zero)( VECT_OP_TYPE* dbp, unsigned dn  );
 
-// analogous to memmove()
+// Analogous to memmove()
 VECT_OP_TYPE* VECT_OP_FUNC(Move)(  VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
 
-/// Fill the vector from various sources
+// Fill the vector from various sources
 VECT_OP_TYPE* VECT_OP_FUNC(Copy)(  VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
 VECT_OP_TYPE* VECT_OP_FUNC(CopyN)( VECT_OP_TYPE* dbp, unsigned dn, unsigned d_stride, const VECT_OP_TYPE* sp, unsigned s_stride );
 VECT_OP_TYPE* VECT_OP_FUNC(CopyU)( VECT_OP_TYPE* dbp, unsigned dn, const unsigned* sp );
@@ -31,6 +55,17 @@ VECT_OP_TYPE* VECT_OP_FUNC(CopyD)( VECT_OP_TYPE* dbp, unsigned dn, const double*
 VECT_OP_TYPE* VECT_OP_FUNC(CopyS)( VECT_OP_TYPE* dbp, unsigned dn, const cmSample_t* sp );
 VECT_OP_TYPE* VECT_OP_FUNC(CopyR)( VECT_OP_TYPE* dbp, unsigned dn, const cmReal_t* sp );
 
+// Fill the the destination vector from a source vector where the source vector contains
+// srcStride interleaved elements to be ignored. 
+VECT_OP_TYPE* VECT_OP_FUNC(CopyStride)(  VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, unsigned srcStride );
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Shrink/Expand/Replace" desc:"Change the size of a vector." kw:[vop] }
+
+
 // Shrink the elemetns of dbp[dn] by copying all elements past t+tn to t.
 // This operation results in overwriting the elements in the range t[tn].
 // t[tn] must be entirely inside dbp[dn].
@@ -51,24 +86,35 @@ VECT_OP_TYPE* VECT_OP_FUNC(Expand)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_O
 // with the contents of u[un].
 VECT_OP_TYPE* VECT_OP_FUNC(Replace)(VECT_OP_TYPE* dbp, unsigned* dn, const VECT_OP_TYPE* t, unsigned tn, const VECT_OP_TYPE* u, unsigned un );
 
-/// Fill the the destination vector from a source vector where the source vector contains
-/// srcStride interleaved elements to be ignored. 
-VECT_OP_TYPE* VECT_OP_FUNC(CopyStride)(  VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, unsigned srcStride );
+//======================================================================================================================
+//)
 
 
-/// Assuming a row vector positive shiftCnt rotates right, negative shiftCnt rotates left.
+
+//( { label:"Rotate/Shift/Flip/Sequence" desc:"Modify/generate the vector sequence." kw:[vop] }
+
+// Assuming a row vector positive shiftCnt rotates right, negative shiftCnt rotates left.
 VECT_OP_TYPE* VECT_OP_FUNC(Rotate)( VECT_OP_TYPE* dbp, unsigned dn, int shiftCnt );
 
-/// Equivalent to Matlab circshift().
+// Equivalent to Matlab circshift().
 VECT_OP_TYPE* VECT_OP_FUNC(RotateM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* sbp, int rShift, int cShift  );
 
-/// Assuming a row vector positive shiftCnt shifts right, negative shiftCnt shifts left.
+// Assuming a row vector positive shiftCnt shifts right, negative shiftCnt shifts left.
 VECT_OP_TYPE* VECT_OP_FUNC(Shift)( VECT_OP_TYPE* dbp, unsigned dn, int shiftCnt, VECT_OP_TYPE fill );
 
-/// Reverse the contents of the vector.
+// Reverse the contents of the vector.
 VECT_OP_TYPE* VECT_OP_FUNC(Flip)(  VECT_OP_TYPE* dbp, unsigned dn);
 
+// Fill dbp[] with a sequence of values. Returns next value. 
+VECT_OP_TYPE  VECT_OP_FUNC(Seq)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE beg, VECT_OP_TYPE incr );
+
+
+
 
+//======================================================================================================================
+//)
+
+//( { label:"Arithmetic" desc:"Add,Sub,Mult,Divde" kw:[vop] }
 
 VECT_OP_TYPE* VECT_OP_FUNC(SubVS)(  VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE v );
 VECT_OP_TYPE* VECT_OP_FUNC(SubVV)(  VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* v );
@@ -105,6 +151,10 @@ VECT_OP_TYPE* VECT_OP_FUNC(DivVVZ)(  VECT_OP_TYPE* dbp, unsigned dn, const VECT_
 // Divide columns of dp[:,i] by each value in the source vector sp[i]. 
 VECT_OP_TYPE*  VECT_OP_FUNC(DivMS)(    VECT_OP_TYPE* dp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* sp ); 
 
+//======================================================================================================================
+//)
+
+//( { label:"Sum vectors" desc:"Operations which take sum vector elements." kw:[vop] }
 
 VECT_OP_TYPE  VECT_OP_FUNC(Sum)(      const VECT_OP_TYPE* sp, unsigned sn );
 VECT_OP_TYPE  VECT_OP_FUNC(SumN)(     const VECT_OP_TYPE* sp, unsigned sn, unsigned stride );
@@ -117,9 +167,12 @@ VECT_OP_TYPE*  VECT_OP_FUNC(SumM)(     const VECT_OP_TYPE* sp, unsigned srn, uns
 // dp[] is zeroed prior to computing the sum.
 VECT_OP_TYPE*  VECT_OP_FUNC(SumMN)(    const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, VECT_OP_TYPE* dp );
 
-VECT_OP_TYPE*   VECT_OP_FUNC(Abs)(   VECT_OP_TYPE* dbp, unsigned dn );
+//======================================================================================================================
+//)
 
 
+//( { label:"Min/max/median/mode" desc:"Simple descriptive statistics." kw:[vop] }
+
 VECT_OP_TYPE  VECT_OP_FUNC(Median)(   const VECT_OP_TYPE* sp, unsigned sn );
 unsigned      VECT_OP_FUNC(MinIndex)( const VECT_OP_TYPE* sp, unsigned sn, unsigned stride );
 unsigned      VECT_OP_FUNC(MaxIndex)( const VECT_OP_TYPE* sp, unsigned sn, unsigned stride );
@@ -130,75 +183,88 @@ VECT_OP_TYPE*  VECT_OP_FUNC(MinVV)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP
 VECT_OP_TYPE*  VECT_OP_FUNC(MaxVV)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* sp );
 
 
-/// Return index of max/min value into dp[scn] of each column of sp[srn,scn]
+// Return index of max/min value into dp[scn] of each column of sp[srn,scn]
 unsigned*  VECT_OP_FUNC(MinIndexM)( unsigned* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn );
 unsigned*  VECT_OP_FUNC(MaxIndexM)( unsigned* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn );
 
-/// Return true if s0p[sn] is equal to s1p[sn]
+// Return the most frequently occuring element in sp.
+VECT_OP_TYPE  VECT_OP_FUNC(Mode)(     const VECT_OP_TYPE* sp, unsigned sn );
+
+//======================================================================================================================
+//)
+
+//( { label:"Compare/Find" desc:"Compare, find, replace and count elements in a vector." kw:[vop] }
+
+// Return true if s0p[sn] is equal to s1p[sn]
 bool       VECT_OP_FUNC(IsEqual)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn );
 
-/// Return true if all elements of s0p[sn] are within 'eps' of s1p[sn].
-/// This function is based on cmMath.h:cmIsCloseX()
+// Return true if all elements of s0p[sn] are within 'eps' of s1p[sn].
+// This function is based on cmMath.h:cmIsCloseX()
 bool VECT_OP_FUNC(IsClose)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn, double eps );
 
-/// Return the most frequently occuring element in sp.
-VECT_OP_TYPE  VECT_OP_FUNC(Mode)(     const VECT_OP_TYPE* sp, unsigned sn );
-
-/// Replace all values <= lteKeyVal with replaceVal.  sp==dp is legal.
+// Replace all values <= lteKeyVal with replaceVal.  sp==dp is legal.
 VECT_OP_TYPE* VECT_OP_FUNC(ReplaceLte)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE lteKeyVal, VECT_OP_TYPE replaceVal );
 
-/// Return the index of 'key' in sp[sn] or cmInvalidIdx if 'key' does not exist.
+// Return the index of 'key' in sp[sn] or cmInvalidIdx if 'key' does not exist.
 unsigned VECT_OP_FUNC(Find)( const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE key );
 
-/// Count the number of times 'key' occurs in sp[sn].
+// Count the number of times 'key' occurs in sp[sn].
 unsigned VECT_OP_FUNC(Count)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE key );
 
-/// Set only the diagonal of a square mtx to sbp.
-VECT_OP_TYPE* VECT_OP_FUNC(Diag)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp );
+//======================================================================================================================
+//)
 
-/// Set the diagonal of a square mtx to db to sbp and set all other values to zero.
-VECT_OP_TYPE* VECT_OP_FUNC(DiagZ)( VECT_OP_TYPE* dbp, unsigned n, const VECT_OP_TYPE* sbp ); 
 
-/// Create an identity matrix (only sets 1's not zeros).
-VECT_OP_TYPE* VECT_OP_FUNC(Identity)(  VECT_OP_TYPE* dbp, unsigned rn, unsigned cn );
 
-/// Zero the matrix and then fill it as an identity matrix.
-VECT_OP_TYPE* VECT_OP_FUNC(IdentityZ)( VECT_OP_TYPE* dbp, unsigned rn, unsigned cn );
+//( { label:"Absolute value" desc:"Absolute value and signal rectification." kw:[vop] }
 
-/// Transpose the matrix sbp[srn,scn] into dbp[scn,srn]
-VECT_OP_TYPE* VECT_OP_FUNC(Transpose)(  VECT_OP_TYPE* dbp, const VECT_OP_TYPE* sbp, unsigned srn, unsigned scn );
+VECT_OP_TYPE*   VECT_OP_FUNC(Abs)(   VECT_OP_TYPE* dbp, unsigned dn );
 
-/// Fill dbp[] with a sequence of values. Returns next value. 
-VECT_OP_TYPE  VECT_OP_FUNC(Seq)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE beg, VECT_OP_TYPE incr );
+// Half wave rectify the source vector.
+// dbp[] = sbp<0 .* sbp 
+// Overlapping the source and dest is allowable as long as dbp <= sbp. 
+VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
+
+//======================================================================================================================
+//)
 
 
-/// Apply a median or other filter of order wndN to xV[xN] and store the result in yV[xN].
-/// When the window goes off either side of the vector the window is shortened.
-/// This algorithm produces the same result as the fn_thresh function in MATLAB fv codebase.
+//( { label:"Filter" desc:"Apply filtering to a vector taking into account vector begin/end conditions." kw:[vop] }
+
+// Apply a median or other filter of order wndN to xV[xN] and store the result in yV[xN].
+// When the window goes off either side of the vector the window is shortened.
+// This algorithm produces the same result as the fn_thresh function in MATLAB fv codebase.
 void VECT_OP_FUNC(FnThresh)( const VECT_OP_TYPE* xV, unsigned xN, unsigned wndN, VECT_OP_TYPE* yV, unsigned yStride, VECT_OP_TYPE (*fnPtr)(const VECT_OP_TYPE*, unsigned) );
 
 
-/// Apply a median filter of order wndN  to xV[xN] and store the result in yV[xN].
-/// When the window goes off either side of the vector the missing elements are considered
-/// to be 0.
-/// This algorithm produces the same result as the MATLAB medfilt1() function.
+// Apply a median filter of order wndN  to xV[xN] and store the result in yV[xN].
+// When the window goes off either side of the vector the missing elements are considered
+// to be 0.
+// This algorithm produces the same result as the MATLAB medfilt1() function.
 void VECT_OP_FUNC(MedianFilt)( const VECT_OP_TYPE* xV, unsigned xN, unsigned wndN, VECT_OP_TYPE* yV, unsigned yStride );
+//======================================================================================================================
+//)
 
 
+//( { label:"Edit distance" desc:"Calculate the Levenshtein edit distance between vectors." kw:[vop] }
 
-/// Allocate and initialize a matrix for use by LevEditDist().
-/// This matrix can be released with a call to cmMemFree().
+// Allocate and initialize a matrix for use by LevEditDist().
+// This matrix can be released with a call to cmMemFree().
 unsigned* VECT_OP_FUNC(LevEditDistAllocMtx)(unsigned mtxMaxN);
 
-/// Return the Levenshtein edit distance between two vectors.
-/// m must point to a matrix pre-allocated by VECT_OP_FUNC(InitiLevEditDistMtx)(maxN).
+// Return the Levenshtein edit distance between two vectors.
+// m must point to a matrix pre-allocated by VECT_OP_FUNC(InitiLevEditDistMtx)(maxN).
 double  VECT_OP_FUNC(LevEditDist)(unsigned mtxMaxN, unsigned* m, const VECT_OP_TYPE* s0, int n0, const VECT_OP_TYPE* s1, int n1, unsigned maxN );
 
-/// Return the Levenshtein edit distance between two vectors.
-/// Edit distance with a max cost threshold. This version of the algorithm
-/// will run faster than LevEditDist() because it will stop execution as soon
-/// as the distance exceeds 'maxCost'.
-/// 'maxCost' must be between 0.0 and 1.0 or it is forced into this range.
-/// The maximum distance returned will be 'maxCost'.
-/// m must point to a matrix pre-allocated by VECT_OP_FUNC(InitiLevEditDistMtx)(maxN).
+// Return the Levenshtein edit distance between two vectors.
+// Edit distance with a max cost threshold. This version of the algorithm
+// will run faster than LevEditDist() because it will stop execution as soon
+// as the distance exceeds 'maxCost'.
+// 'maxCost' must be between 0.0 and 1.0 or it is forced into this range.
+// The maximum distance returned will be 'maxCost'.
+// m must point to a matrix pre-allocated by VECT_OP_FUNC(InitiLevEditDistMtx)(maxN).
 double VECT_OP_FUNC(LevEditDistWithCostThresh)( int mtxMaxN, unsigned* m, const VECT_OP_TYPE* s0, int n0, const VECT_OP_TYPE* s1, int n1, double maxCost, unsigned maxN );
+
+//======================================================================================================================
+//)
+

src/vop/cmVectOpsTemplateCode.h

@@ -1,5 +1,38 @@
 #ifdef cmVectOpsTemplateCode_h
 
+VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
+{
+  VECT_OP_TYPE* dep = dbp + dn;
+  VECT_OP_TYPE*  rp = dbp;
+  VECT_OP_TYPE sum = 0;
+  while( dbp < dep )
+  {
+    sum += *sbp++;
+    *dbp++ = sum;
+
+  }
+  return rp;
+}
+
+bool          VECT_OP_FUNC(Equal)(    const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
+{
+  const VECT_OP_TYPE* ep = s0p + sn;
+  while( s0p < ep )
+    if( *s0p++ != *s1p++ )
+      return false;
+  return true;
+}
+
+VECT_OP_TYPE*  VECT_OP_FUNC(LinSpace)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE base, VECT_OP_TYPE limit )
+{
+  unsigned i = 0;
+  for(; i<dn; ++i)
+    dbp[i] = base + i*(limit-base)/(dn-1);
+  return dbp;
+}
+
+
+
 void          VECT_OP_FUNC(VPrint)( cmRpt_t* rpt, const char* fmt, ... )
 {
   va_list vl;
@@ -189,31 +222,43 @@ VECT_OP_TYPE* VECT_OP_FUNC(StandardizeCols)( VECT_OP_TYPE* dbp, unsigned drn, un
   return dbp;
 }
 
-
-VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp )
+unsigned  VECT_OP_FUNC(NormToMax)(    VECT_OP_TYPE* dp, unsigned dn )
 {
-  VECT_OP_TYPE* dp = dbp;
-  VECT_OP_TYPE* ep = dbp + dn;
-  for(; dp < ep; ++dp,++sp )
-    *dp = *sp < 0 ? 0 : *sp;
+  unsigned i = VECT_OP_FUNC(MaxIndex)(dp,dn,1);
 
-  return dbp;
+  if( i != cmInvalidIdx )
+  {  
+    VECT_OP_TYPE v = dp[i];
+    VECT_OP_FUNC(DivVS)(dp,dn,v);
+  }
+
+  return i;
 }
 
-VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp)
+unsigned VECT_OP_FUNC(NormToAbsMax)(   VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE fact )
 {
-  VECT_OP_TYPE* dep = dbp + dn;
-  VECT_OP_TYPE*  rp = dbp;
-  VECT_OP_TYPE sum = 0;
-  while( dbp < dep )
-  {
-    sum += *sbp++;
-    *dbp++ = sum;
+  if( dn == 0 )
+    return cmInvalidIdx;
 
-  }
-  return rp;
+  unsigned     i  = 0;
+  unsigned     mi = 0;
+  VECT_OP_TYPE mx = cmAbs(dp[0]);
+
+  for(i=1; i<dn; ++i)
+    if( cmAbs(dp[i])>mx )
+    {
+      mi = i;
+      mx = cmAbs(dp[i]);
+    }
+
+  VECT_OP_FUNC(MultVS)(dp,dn,fact/mx);
+  
+  return mi;
+  
 }
 
+
+
 VECT_OP_TYPE  VECT_OP_FUNC(Mean)( const VECT_OP_TYPE* bp, unsigned n )
 {  return VECT_OP_FUNC(Sum)(bp,n)/n; }
 
@@ -312,52 +357,6 @@ VECT_OP_TYPE*  VECT_OP_FUNC(VarianceM)(VECT_OP_TYPE* dp,  const VECT_OP_TYPE* sp
   return dp;  
 }
 
-unsigned  VECT_OP_FUNC(NormToMax)(    VECT_OP_TYPE* dp, unsigned dn )
-{
-  unsigned i = VECT_OP_FUNC(MaxIndex)(dp,dn,1);
-
-  if( i != cmInvalidIdx )
-  {  
-    VECT_OP_TYPE v = dp[i];
-    VECT_OP_FUNC(DivVS)(dp,dn,v);
-  }
-
-  return i;
-}
-
-unsigned VECT_OP_FUNC(NormToAbsMax)(   VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE fact )
-{
-  if( dn == 0 )
-    return cmInvalidIdx;
-
-  unsigned     i  = 0;
-  unsigned     mi = 0;
-  VECT_OP_TYPE mx = cmAbs(dp[0]);
-
-  for(i=1; i<dn; ++i)
-    if( cmAbs(dp[i])>mx )
-    {
-      mi = i;
-      mx = cmAbs(dp[i]);
-    }
-
-  VECT_OP_FUNC(MultVS)(dp,dn,fact/mx);
-  
-  return mi;
-  
-}
-
-
-VECT_OP_TYPE  VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha )
-{
-  double sum = 0;
-  const VECT_OP_TYPE* bp = sp;
-  const VECT_OP_TYPE* ep = sp + sn;
-  while( bp < ep )
-    sum += pow(fabs(*bp++),alpha);
-
-  return (VECT_OP_TYPE)pow(sum/sn,1.0/alpha);
-}
 
 void  VECT_OP_FUNC(GaussCovariance)(VECT_OP_TYPE* yM, unsigned D, const VECT_OP_TYPE* xM, unsigned xN, const VECT_OP_TYPE* uV, const unsigned* selIdxV, unsigned selKey )
 {
@@ -468,14 +467,6 @@ void  VECT_OP_FUNC(GaussCovariance2)(VECT_OP_TYPE* yM, unsigned D, const VECT_OP
 }
 
 
-bool          VECT_OP_FUNC(Equal)(    const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn )
-{
-  const VECT_OP_TYPE* ep = s0p + sn;
-  while( s0p < ep )
-    if( *s0p++ != *s1p++ )
-      return false;
-  return true;
-}
 
 bool          VECT_OP_FUNC(IsNormal)( const VECT_OP_TYPE* sp, unsigned sn )
 {
@@ -584,6 +575,19 @@ VECT_OP_TYPE* VECT_OP_FUNC(RmsV)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_T
 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)); }
 
+
+VECT_OP_TYPE  VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha )
+{
+  double sum = 0;
+  const VECT_OP_TYPE* bp = sp;
+  const VECT_OP_TYPE* ep = sp + sn;
+  while( bp < ep )
+    sum += pow(fabs(*bp++),alpha);
+
+  return (VECT_OP_TYPE)pow(sum/sn,1.0/alpha);
+}
+
+
 /*
 From:http://www.ee.ic.ac.uk/hp/staff/dmb/voicebox/doc/voicebox/distitpf.html
 [nf1,p2]=size(pf1);
@@ -1150,47 +1154,6 @@ VECT_OP_TYPE* VECT_OP_FUNC(LogV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_
   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;
@@ -1420,6 +1383,43 @@ VECT_OP_TYPE* VECT_OP_FUNC(CholZ)(VECT_OP_TYPE* A, unsigned an )
   return A;
 }
 
+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;      
+
+}
+
+
+
 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)));
@@ -1739,34 +1739,150 @@ VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussMM)( VECT_OP_TYPE* dbp, unsigned drn, unsi
   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  )
+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 )
 {
-  unsigned i;
-  for(i=0; i<dn; ++i)
-  {
-    double a = 2.0*M_PI*i/(dn-1);
+  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;
 
-    dbp[ i ]    = (VECT_OP_TYPE)(varX * cos(a) + x);
-    dbp[ i+dn ] = (VECT_OP_TYPE)(varY * sin(a) + y);
-  }
+  for(; dbp < dep; ++sbp )
+    *dbp++ = fact0 * exp( -((*sbp-mean)*(*sbp-mean))/ fact1 );
 
-  return dbp;
+  return rp;
 }
 
-
-unsigned      VECT_OP_FUNC(SynthSine)(      VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
+/// 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 )
 {
-    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;
-}
+  VECT_OP_TYPE det0;
 
-unsigned      VECT_OP_FUNC(SynthCosine)(    VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz )
-{
+  // 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;
+}
+
+
+
+
+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;
 
@@ -1929,15 +2045,48 @@ VECT_OP_TYPE VECT_OP_FUNC(SynthPinkNoise)( VECT_OP_TYPE* dbp, unsigned n, VECT_O
   return *sp;
 }
 
-VECT_OP_TYPE*  VECT_OP_FUNC(LinSpace)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE base, VECT_OP_TYPE limit )
+VECT_OP_TYPE* VECT_OP_FUNC(AmplToDbVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, VECT_OP_TYPE minDb )
 {
-  unsigned i = 0;
-  for(; i<dn; ++i)
-    dbp[i] = base + i*(limit-base)/(dn-1);
+  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(LinearToDb)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE mult )
 {
   const VECT_OP_TYPE* dep = dbp + dn;
@@ -2371,41 +2520,6 @@ VECT_OP_TYPE* VECT_OP_FUNC(LP_Sinc)(VECT_OP_TYPE* dp, unsigned dn, const VECT_OP
   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 )
 {
@@ -2614,107 +2728,45 @@ VECT_OP_TYPE* VECT_OP_FUNC(ShroederSpreadingFunc)(VECT_OP_TYPE* m, unsigned band
   return m;
 }
 
-
-VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt )
+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
+) 
 {
-  VECT_OP_TYPE* dbp = dp;
-
-  double c0 = 1.0/sqrt(filtCnt/2); // row 1-coeffCnt factor
-  double c1 = c0 * sqrt(2)/2;      // row 0 factor
-
-  unsigned i,j;
+  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;
 
-  // 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);
+  // if a data point selection vector was given
+  if( selIdxV != NULL )
+  {
+    selN = 0;
 
-  return dbp;
-}
+    for(i=0; i<N; ++i)
+    {
+      selN        += selIdxV[i]==selKey;
+      classIdxV[i] = K;
+    }
+  }
 
-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++;
 
+  assert(K<=selN);
 
-  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 )
+  // 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)
@@ -2913,136 +2965,6 @@ unsigned VECT_OP_FUNC(Kmeans2)(
   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]
@@ -3117,6 +3039,22 @@ void VECT_OP_FUNC(DiscreteViterbi)(unsigned* stateV, unsigned tN, unsigned sN, c
   cmMemPtrFree( &dV );
 }
 
+
+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;
+}
+
+
 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 )
 {
 
@@ -3226,43 +3164,106 @@ VECT_OP_TYPE VECT_OP_FUNC(PtToLineDistance)( VECT_OP_TYPE x0, VECT_OP_TYPE y0, V
   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  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 )
 {
-  VECT_OP_TYPE sx = 0;
-  VECT_OP_TYPE sy = 0;
-  VECT_OP_TYPE sx_2 = 0;
-  VECT_OP_TYPE sxy  = 0;
-  unsigned i;  
+  double              sum  = 0;
+  const VECT_OP_TYPE*  ep  = mag0V + binCnt;
 
-  if( x == NULL )
+  unsigned i = 0;
+
+  for(;  mag0V < ep; ++i )
   {
-    for(i=0; i<n; ++i)
-    {
-      VECT_OP_TYPE xx = i;
-      sx   += xx;
-      sx_2 += xx * xx;
-      sxy  += xx * y[i];
-      sy   += y[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 );
+
   }
-  else
+
+  return (VECT_OP_TYPE)sum; 
+}
+
+VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt )
+{
+  VECT_OP_TYPE* dbp = dp;
+
+  double c0 = 1.0/sqrt(filtCnt/2); // row 1-coeffCnt factor
+  double c1 = c0 * sqrt(2)/2;      // row 0 factor
+
+  unsigned i,j;
+
+  // for each column
+  for(i=0; i<filtCnt; ++i)
+    // for each row
+    for(j=0; j<coeffCnt; ++j)
+      *dp++ = (j==0 ? c1 : c0) * cos( (0.5 + i) * M_PI * j / filtCnt);
+
+  return dbp;
+}
+
+
+unsigned VECT_OP_FUNC(PeakIndexes)( unsigned* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE threshold )
+{
+  unsigned pkCnt = 0;
+  const unsigned*     dep = dbp + dn;
+  const VECT_OP_TYPE* sep = sbp + sn;
+  const VECT_OP_TYPE* s2p = sbp;
+  const VECT_OP_TYPE* s0p = s2p++;
+  const VECT_OP_TYPE* s1p = s2p++;
+
+
+  while( dbp < dep && s2p < sep )
   {
-    for(i=0; i<n; ++i)
+    if( (*s0p < *s1p) && (*s1p > *s2p) && (*s1p >= threshold) )
     {
-      sx   += x[i];
-      sx_2 += x[i] * x[i];
-      sxy  += x[i] * y[i];
-      sy   += y[i];
+      *dbp++ = s1p - sbp;
+      s0p    = s2p++;
+      s1p    = s2p++;
+      ++pkCnt;
+    }
+    else
+    {
+      s0p = s1p;
+      s1p = s2p++;     
     }
   }
+  
+  return pkCnt;
+}
 
-  *b1 = (sxy * n - sx * sy) / (sx_2 * n - sx*sx);
-  *b0 = (sy - (*b1) * sx) / n;      
-
+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;
 }
 
 
 
+
 void VECT_OP_FUNC(Interp1)(VECT_OP_TYPE* y1, const VECT_OP_TYPE* x1, unsigned xy1N, const VECT_OP_TYPE* x0, const VECT_OP_TYPE* y0, unsigned xy0N )
 {
   unsigned i,j;

src/vop/cmVectOpsTemplateHdr.h

@@ -1,7 +1,21 @@
-// \file cmVectOpsTemplateHdr.h
-/// Vector operations interface.
+//( { label:misc desc:"Miscellaneous vector operations." kw:[vop] }
 
-/// Setting fieldWidth or decPltCnt to to negative values result in fieldWidth == 10 or decPlCnt == 4
+// Compute the cummulative sum of sbp[dn]. Equivalent to Matlab cumsum().
+VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp ); 
+
+// Returns true if all values in each vector are equal.
+bool          VECT_OP_FUNC(Equal)(    const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn );
+
+// Same as Matlab linspace() v[i] = i * (limit-1)/n
+VECT_OP_TYPE*  VECT_OP_FUNC(LinSpace)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE base, VECT_OP_TYPE limit );
+
+//======================================================================================================================
+//)
+
+
+//( { label:Print desc:"Vector printing functions." kw:[vop] }
+// Setting fieldWidth or decPltCnt to to negative values result in fieldWidth == 10 or decPlCnt == 4
+//
 void          VECT_OP_FUNC(Printf)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp, int fieldWidth, int decPlCnt, const char* fmt, unsigned flags );
 void          VECT_OP_FUNC(Print)(  cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp );
 void          VECT_OP_FUNC(PrintE)( cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp );
@@ -9,64 +23,68 @@ void          VECT_OP_FUNC(PrintE)( cmRpt_t* rpt, unsigned rn, unsigned cn, cons
 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 );
 void          VECT_OP_FUNC(PrintL)(  const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp );
 void          VECT_OP_FUNC(PrintLE)( const char* label, cmRpt_t* rpt, unsigned rn, unsigned cn, const VECT_OP_TYPE* dbp );
+//======================================================================================================================
+//)
 
 
+//( { label:Normalization desc:"Normalization and standardization functions." kw:[vop] }
 
-/// Normalize the vector of proabilities by dividing through by the sum.
-/// This leaves the relative proportions of each value unchanged while producing a total probability of 1.0.
+// Normalize the vector of proabilities by dividing through by the sum.
+// This leaves the relative proportions of each value unchanged while producing a total probability of 1.0.
+//
 VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityVV)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp);
 VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbability)(VECT_OP_TYPE* dbp, unsigned dn);
 VECT_OP_TYPE* VECT_OP_FUNC(NormalizeProbabilityN)(VECT_OP_TYPE* dbp, unsigned dn, unsigned stride);
-
-/// Standardize the columns of the matrix by subtracting the mean and dividing by the standard deviation.
-/// uV[dcn] returns the mean of the data and is optional.
-/// sdV[dcn] return the standard deviation of the data and is optional.
+//
+// Standardize the columns of the matrix by subtracting the mean and dividing by the standard deviation.
+// uV[dcn] returns the mean of the data and is optional.
+// sdV[dcn] return the standard deviation of the data and is optional.
 VECT_OP_TYPE* VECT_OP_FUNC(StandardizeRows)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV );
 VECT_OP_TYPE* VECT_OP_FUNC(StandardizeCols)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, VECT_OP_TYPE* uV, VECT_OP_TYPE* sdV );
+//
+// Normalize by dividing through by the max. value.
+// dp[] ./= max(dp). Returns the index of the max value.
+unsigned  VECT_OP_FUNC(NormToMax)(    VECT_OP_TYPE* dp, unsigned dn );
+//
+// Normalize by dividing through by the max. absolute value.
+// db[] .*= fact / abs(max(dp));
+unsigned VECT_OP_FUNC(NormToAbsMax)(   VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE fact );
+//======================================================================================================================
+//)
 
-/// dbp[] = sbp<0 .* sbp 
-/// Overlapping the source and dest is allowable as long as dbp <= sbp. 
-VECT_OP_TYPE* VECT_OP_FUNC(HalfWaveRectify)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
 
-/// Compute the cummulative sum of sbp[dn]. Equivalent to Matlab cumsum().
-VECT_OP_TYPE* VECT_OP_FUNC(CumSum)(VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp ); 
+//( { label:"Mean and variance" desc:"Compute mean and variance." kw:[vop] }
 
 VECT_OP_TYPE  VECT_OP_FUNC(Mean)(     const VECT_OP_TYPE* sp, unsigned sn );
 VECT_OP_TYPE  VECT_OP_FUNC(MeanN)(    const VECT_OP_TYPE* sp, unsigned sn, unsigned stride  );
-
+//
 // Take the mean of each column/row of a matrix.
 // Set 'dim' to 0 to return mean of columns else return mean of rows.
 VECT_OP_TYPE*  VECT_OP_FUNC(MeanM)(    VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, unsigned dim );
-
+//
 // Take the mean of the first 'cnt' element of each column/row of a matrix.
 // Set 'dim' to 0 to return mean of columns else return mean of rows.
 // If 'cnt' is greater than the number of elements in the column/row then 'cnt' is
 // reduced to the number of elements in the column/row.
 VECT_OP_TYPE*  VECT_OP_FUNC(MeanM2)(    VECT_OP_TYPE* dp, const VECT_OP_TYPE* sp, unsigned srn, unsigned scn, unsigned dim, unsigned cnt );
-
+//
 // Find the mean of the  data points returned by srcFuncPtr(argPtr,i) and return it in dp[dim].
 // 'dim' is both the size of dp[] and the length of each data point returned by srcFuncPtr().
 // srcFuncPtr() will be called 'cnt' times but it may return NULL on some calls if the associated
 // data point should not be included in the mean calculation.
 VECT_OP_TYPE*  VECT_OP_FUNC(Mean2)(   VECT_OP_TYPE* dp, const VECT_OP_TYPE* (*srcFuncPtr)(void* arg, unsigned idx ), unsigned dim, unsigned cnt, void* argPtr );
-
-
+//
 // avgPtr is optional - set to NULL to compute the average
 VECT_OP_TYPE  VECT_OP_FUNC(Variance)( const VECT_OP_TYPE* sp, unsigned sn, const VECT_OP_TYPE* avgPtr );
 VECT_OP_TYPE  VECT_OP_FUNC(VarianceN)(const VECT_OP_TYPE* sp, unsigned sn, unsigned stride, const VECT_OP_TYPE* avgPtr );
-
+//
 // Set dim=0 to return variance of columns otherwise return variance or rows.
 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 );
+//======================================================================================================================
+//)
 
-// dp[] ./= max(dp). Returns the index of the max value.
-unsigned  VECT_OP_FUNC(NormToMax)(    VECT_OP_TYPE* dp, unsigned dn );
-
-// db[] .*= fact / abs(max(dp));
-unsigned VECT_OP_FUNC(NormToAbsMax)(   VECT_OP_TYPE* dp, unsigned dn, VECT_OP_TYPE fact );
-
-
-VECT_OP_TYPE  VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha );
 
+//( { label:"Covariance" desc:"Matrix covariance" kw:[vop] }
 
 // Calculate the sample covariance matrix from a set of Gaussian distributed multidimensional data.
 // sp[dn,scn] is the data set.
@@ -92,8 +110,10 @@ void  VECT_OP_FUNC(GaussCovariance)(VECT_OP_TYPE* dp, unsigned dn, const VECT_OP
 // through the 'sn' data points.  
 // The result of this function are identical to the octave cov() function.
 void  VECT_OP_FUNC(GaussCovariance2)(VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* (*srcFuncPtr)(void* userPtr, unsigned idx), unsigned sn, void* userPtr, const VECT_OP_TYPE* uV, const unsigned* selIdxV, unsigned selKey );
+//======================================================================================================================
+//)
 
-bool          VECT_OP_FUNC(Equal)(    const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn );
+//( { label:"Float point normal" desc:"Evaluate the 'normalness of floating point values." kw:[vop] }
 
 // Returns true if all values are 'normal' according the the C macro 'isnormal'.
 // This function will return false if any of the values are zero.
@@ -107,80 +127,90 @@ bool          VECT_OP_FUNC(IsNormalZ)(const VECT_OP_TYPE* sp, unsigned sn );
 // Returns the count of indexes stored in dp[].
 unsigned      VECT_OP_FUNC(FindNonNormal)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sp );
 unsigned      VECT_OP_FUNC(FindNonNormalZ)( unsigned* dp, unsigned dn, const VECT_OP_TYPE* sp );
+//======================================================================================================================
+//)
 
 
-/// Successive call to to ZeroCrossCount should preserve the value pointed to by delaySmpPtr.
+//( { label:"Measure" desc:"Measure features of a vector." kw:[vop] }
+
+// Successive call to to ZeroCrossCount should preserve the value pointed to by delaySmpPtr.
 unsigned      VECT_OP_FUNC(ZeroCrossCount)( const VECT_OP_TYPE* sp, unsigned n, VECT_OP_TYPE* delaySmpPtr);
 
 // Calculuate the sum of the squares of all elements in bp[bn]. 
 VECT_OP_TYPE VECT_OP_FUNC(SquaredSum)( const VECT_OP_TYPE* bp, unsigned bn );
 
-/// sn must be <= wndSmpCnt. If sn < wndSmpCnt then sp[sn] is treated as a
-/// a partially filled buffer padded with wndSmpCnt-sn zeros.
-/// rms = sqrt( sum(sp[1:sn] .* sp[1:sn]) / wndSmpCnt )
+// sn must be <= wndSmpCnt. If sn < wndSmpCnt then sp[sn] is treated as a
+// a partially filled buffer padded with wndSmpCnt-sn zeros.
+// rms = sqrt( sum(sp[1:sn] .* sp[1:sn]) / wndSmpCnt )
 VECT_OP_TYPE  VECT_OP_FUNC(RMS)( const VECT_OP_TYPE* sp, unsigned sn, unsigned wndSmpCnt );
 
-/// This function handles the case were sn is not an integer multiple of 
-/// wndSmpCnt or hopSmpCnt.  In this case the function computes zero 
-/// padded RMS values for windows which go past the end of sp[sn].
+// This function handles the case were sn is not an integer multiple of 
+// wndSmpCnt or hopSmpCnt.  In this case the function computes zero 
+// padded RMS values for windows which go past the end of sp[sn].
 VECT_OP_TYPE* VECT_OP_FUNC(RmsV)( VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* sp, unsigned sn, unsigned wndSmpCnt, unsigned hopSmpCnt );
 
-
-/// Return the magnitude (Euclidean Norm) of a vector.
+// Return the magnitude (Euclidean Norm) of a vector.
 VECT_OP_TYPE  VECT_OP_FUNC(EuclidNorm)( const VECT_OP_TYPE* sp, unsigned sn );
 
+VECT_OP_TYPE  VECT_OP_FUNC(AlphaNorm)(const VECT_OP_TYPE* sp, unsigned sn, VECT_OP_TYPE alpha );
+
+//======================================================================================================================
+//)
+
+
+
+//( { label:"Distance" desc:"Calculate various vector distances." kw:[vop] }
+
 // Return the Itakura-Saito distance between a modelled power spectrum (up) and another power spectrum (sp).
 VECT_OP_TYPE VECT_OP_FUNC(ItakuraDistance)( const VECT_OP_TYPE* up, const VECT_OP_TYPE* sp, unsigned sn );
 
-/// Return the cosine distance between two vectors.
+// Return the cosine distance between two vectors.
 VECT_OP_TYPE  VECT_OP_FUNC(CosineDistance)( const VECT_OP_TYPE* s0P, const VECT_OP_TYPE* s1p, unsigned sn );
 
-/// Return the Euclidean distance between two vectors
+// Return the Euclidean distance between two vectors
 VECT_OP_TYPE  VECT_OP_FUNC(EuclidDistance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn );
 
-/// Return the Manhattan distance between two vectors
+// Return the Manhattan distance between two vectors
 VECT_OP_TYPE  VECT_OP_FUNC(L1Distance)( const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn );
 
-/// Return the Mahalanobis distance between a vector and the mean of the distribution.
-/// The mean vector could be replaced with another vector drawn from the same distribution in which
-/// case the returned value would reflect the distance between the two vectors.
-/// 'sn' is the dimensionality of the data.
-/// up[D] and invCovM[sn,sn] are the mean and inverse of the covariance matrix of the distribution from 
-/// which sp[D] is drawn. 
+// Return the Mahalanobis distance between a vector and the mean of the distribution.
+// The mean vector could be replaced with another vector drawn from the same distribution in which
+// case the returned value would reflect the distance between the two vectors.
+// 'sn' is the dimensionality of the data.
+// up[D] and invCovM[sn,sn] are the mean and inverse of the covariance matrix of the distribution from 
+// which sp[D] is drawn. 
 VECT_OP_TYPE  VECT_OP_FUNC(MahalanobisDistance)( const VECT_OP_TYPE* sp, unsigned sn, const VECT_OP_TYPE* up, const VECT_OP_TYPE* invCovM );
 
-/// Return the KL distance between two probability distributions up[sn] and sp[sn].
-/// Since up[] and sp[] are probability distributions they must sum to 1.0.
+// Return the KL distance between two probability distributions up[sn] and sp[sn].
+// Since up[] and sp[] are probability distributions they must sum to 1.0.
 VECT_OP_TYPE VECT_OP_FUNC(KL_Distance)( const VECT_OP_TYPE* up, const VECT_OP_TYPE* sp, unsigned sn );
 
-/// Return the KL distance between a prototype vector up[sn] and another vector sp[sn].
-/// This function first normalizes the two vectors to sum to 1.0 before calling
+// Return the KL distance between a prototype vector up[sn] and another vector sp[sn].
+// This function first normalizes the two vectors to sum to 1.0 before calling
 // VECT_OP_FUNC(KL_Distance)(up,sp,sn);
 VECT_OP_TYPE VECT_OP_FUNC(KL_Distance2)( const VECT_OP_TYPE* up, const VECT_OP_TYPE* sp, unsigned sn );
 
 
-/// Measure the Euclidean distance between a vector and all the columns in a matrix.
-/// If dv[scn] is no 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[].
+// Measure the Euclidean distance between a vector and all the columns in a matrix.
+// If dv[scn] is no 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 );
 
-
-
-/// Measure the distance between each column in s0M[ rn, s0cn ] and 
-/// each column in s1M[rn, s1cn ]. If dM is non-NULL store the 
-/// result in dM[s1cn, s0cn]. The difference between s0M[:,0] and s1M[:,0] 
-/// is stored in dM[0,0], the diff. between s0M[:,1] and s1M[:,1] is stored 
-/// in dM[1,0], etc.  If mvV[s0cn] is non-NULL then  minV[i] is set with
-/// the distance from s0M[:,i] to the nearest column in s1M[]. If miV[s0cn]
-/// is non-NULL then it is set with the column index of s1M[] which is
-/// closest to s0M[:,i].  In other words mvV[i] gives the distance to column
-/// miV[i] from column s0M[:,i].
-/// In those cases where the distane from a prototype (centroid) to the data point
-/// is not the same as from the data point to the centroid then s1M[] is considered
-/// to hold the prototypes and s0M[] is considered to hold the data points.
-/// The distance function returns the distance from a prototype 'cV[dimN]' to
-/// an datapoint dV[dimN]. 'dimN' is the dimensionality of the data vector
-/// and is threfore equal to 'rn'.
+// Measure the distance between each column in s0M[ rn, s0cn ] and 
+// each column in s1M[rn, s1cn ]. If dM is non-NULL store the 
+// result in dM[s1cn, s0cn]. The difference between s0M[:,0] and s1M[:,0] 
+// is stored in dM[0,0], the diff. between s0M[:,1] and s1M[:,1] is stored 
+// in dM[1,0], etc.  If mvV[s0cn] is non-NULL then  minV[i] is set with
+// the distance from s0M[:,i] to the nearest column in s1M[]. If miV[s0cn]
+// is non-NULL then it is set with the column index of s1M[] which is
+// closest to s0M[:,i].  In other words mvV[i] gives the distance to column
+// miV[i] from column s0M[:,i].
+// In those cases where the distane from a prototype (centroid) to the data point
+// is not the same as from the data point to the centroid then s1M[] is considered
+// to hold the prototypes and s0M[] is considered to hold the data points.
+// The distance function returns the distance from a prototype 'cV[dimN]' to
+// an datapoint dV[dimN]. 'dimN' is the dimensionality of the data vector
+// and is threfore equal to 'rn'.
 void VECT_OP_FUNC(DistVMM)( 
   VECT_OP_TYPE*       dM,    // dM[s1cn,s0cn] return distance mtx (optional) 
   VECT_OP_TYPE*       mvV,   // mvV[s0cn] distance to closest data point in s0M[]. (optional)
@@ -193,192 +223,238 @@ void VECT_OP_FUNC(DistVMM)(
   VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* cV, const VECT_OP_TYPE* dV, unsigned dimN ), 
   void*               userPtr );
 
-/// Select 'selIdxN' columns from sM[srn,scn].
-/// dM[srn,selIdxN] receives copies of the selected columns.
-/// selIdxV[selIdxN] receives the column indexes of the selected columns.
-/// Both dM[] and selIdxV[] are optional.
-/// In each case the first selected point is chosen at random.
-/// SelectRandom() then selects the following selIdxN-1 points at random.
-/// SelectMaxDist() selects the next selIdxN-1 points by selecting 
-/// the point whose combined distance to the previously selected points
-/// is greatest. SelectMaxAvgDist() selectes the points whose combined
-/// average distance is greatest relative the the previously selected
-/// points.
+//======================================================================================================================
+//)
+
+//( { label:"Select columns" desc:"Select columns based on distance." kw:[vop] }
+
+// Select 'selIdxN' columns from sM[srn,scn].
+// dM[srn,selIdxN] receives copies of the selected columns.
+// selIdxV[selIdxN] receives the column indexes of the selected columns.
+// Both dM[] and selIdxV[] are optional.
+// In each case the first selected point is chosen at random.
+// SelectRandom() then selects the following selIdxN-1 points at random.
+// SelectMaxDist() selects the next selIdxN-1 points by selecting 
+// the point whose combined distance to the previously selected points
+// is greatest. SelectMaxAvgDist() selectes the points whose combined
+// average distance is greatest relative the the previously selected
+// points.
 void VECT_OP_FUNC(SelectRandom)(     VECT_OP_TYPE* dM, unsigned* selIdxV, unsigned selIdxN, const VECT_OP_TYPE* sM, unsigned srn, unsigned scn );
 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* distUserPtr );
 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* distUserPtr ); 
 
-/// Return the sum of the products (dot product)
+//======================================================================================================================
+//)
+
+//( { label:"Matrix multiplication" desc:"Various matrix multiplication operations." kw:[vop] }
+
+// Return the sum of the products (dot product)
 VECT_OP_TYPE VECT_OP_FUNC(MultSumVV)(  const VECT_OP_TYPE* s0p, const VECT_OP_TYPE* s1p, unsigned sn  );
 VECT_OP_TYPE VECT_OP_FUNC(MultSumVS)(  const VECT_OP_TYPE* s0p, unsigned sn, VECT_OP_TYPE s );
 
-/// Number of elements in the dest vector is expected to be the same 
-/// as the number of source matrix rows.
-/// mcn gives the number of columns in the source matrix which is 
+// Number of elements in the dest vector is expected to be the same 
+// as the number of source matrix rows.
+// mcn gives the number of columns in the source matrix which is 
 //  expected to match the number of elements in the source vector.
-/// dbp[dn,1] = mp[dn,mcn] * vp[mcn,1] 
+// dbp[dn,1] = mp[dn,mcn] * vp[mcn,1] 
 VECT_OP_TYPE* VECT_OP_FUNC(MultVMV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* mp, unsigned mcn, const VECT_OP_TYPE* vp ); 
 
-/// Multiply a row vector with a matrix to produce a row vector. 
-/// dbp[1,dn] = v[1,vn] * m[vn,dn]
+// Multiply a row vector with a matrix to produce a row vector. 
+// dbp[1,dn] = v[1,vn] * m[vn,dn]
 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 ); 
 
-/// Same as MultVMtV() except M is transposed as part of the multiply.  
-/// mrn gives the number of rows in m[] and number of elements in vp[]
-/// dpb[dn] = mp[mrn,dn] * vp[mrn]
+// Same as MultVMtV() except M is transposed as part of the multiply.  
+// mrn gives the number of rows in m[] and number of elements in vp[]
+// dpb[dn] = mp[mrn,dn] * vp[mrn]
 VECT_OP_TYPE* VECT_OP_FUNC(MultVMtV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* mp, unsigned mrn, const VECT_OP_TYPE* vp ); 
 
-/// Same as MultVMV() but where the matrix is diagonal.
+// Same as MultVMV() but where the matrix is diagonal.
 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 ); 
 
-/// Generalized matrix multiply.
-/// If transposition is selected for M0 or M1 then the given dimension represent the size of the matrix 'after' the transposion. 
-/// d[drn,dcn] = alpha * op(m0[drn,m0cn_m1rn]) * op(m1[m0cn_m1rn,dcn]) + beta * d[drn,dcn]
-//// See enum { kTranpsoseM0Fl=0x01, kTransposeM1Fl=0x02 } in cmVectOps for flags.
+// Generalized matrix multiply.
+// If transposition is selected for M0 or M1 then the given dimension represent the size of the matrix 'after' the transposion. 
+// d[drn,dcn] = alpha * op(m0[drn,m0cn_m1rn]) * op(m1[m0cn_m1rn,dcn]) + beta * d[drn,dcn]
+/// See enum { kTranpsoseM0Fl=0x01, kTransposeM1Fl=0x02 } in cmVectOps for flags.
 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 m0cn_m1rn, VECT_OP_TYPE beta, unsigned flags );
 
-/// Same a VECT_OP_FUNC(MultMMM1) except allows the operation on a sub-matrix by providing the physical (memory) row count rather than the logical (matrix) row count.
+// Same a VECT_OP_FUNC(MultMMM1) except allows the operation on a sub-matrix by providing the physical (memory) row count rather than the logical (matrix) row count.
 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 m0cn_m1rn, VECT_OP_TYPE beta, unsigned flags, unsigned dprn, unsigned m0prn, unsigned m1prn );
 
-/// d[drn,dcn] = m0[drn,m0cn] * m1[m1rn,dcn] 
+// d[drn,dcn] = m0[drn,m0cn] * m1[m1rn,dcn] 
 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 );
 
-/// same as MultMMM() except second source matrix is transposed prior to the multiply
+// same as MultMMM() except second source matrix is transposed prior to the multiply
 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 );
-                                   
 
-// Raise dbp[] to the power 'expon'
-VECT_OP_TYPE* VECT_OP_FUNC(PowVS)(  VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE expon );
-VECT_OP_TYPE* VECT_OP_FUNC(PowVVS)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE expon );
+//======================================================================================================================
+//)
 
-// Take the natural log of all values in sbp[dn]. It is allowable for sbp point to the same array as dbp=.
-VECT_OP_TYPE* VECT_OP_FUNC(LogV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp );
+//( { label:"Linear algebra" desc:"Miscellaneous linear algebra operations. Determinant, Inversion, Cholesky decompostion. Linear system solver." kw:[vop] }
 
-// Convert a magnitude (amplitude) spectrum to/from decibels. 
-// It is allowable for dbp==sbp.
-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* VECT_OP_FUNC(DbToAmplVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp);
-
-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* VECT_OP_FUNC(DbToPowVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp);
-
-/// Initialize dbp[dn,dn] as a square symetric positive definite matrix using values
-/// from a random uniform distribution. This is useful for initializing random 
-/// covariance matrices as used by multivariate Gaussian distributions
-/// If t is non-NULL it must point to a block of scratch memory of t[dn,dn].
-/// If t is NULL then scratch memory is internally allocated and deallocated.
+// Initialize dbp[dn,dn] as a square symetric positive definite matrix using values
+// from a random uniform distribution. This is useful for initializing random 
+// covariance matrices as used by multivariate Gaussian distributions
+// If t is non-NULL it must point to a block of scratch memory of t[dn,dn].
+// If t is NULL then scratch memory is internally allocated and deallocated.
 VECT_OP_TYPE* VECT_OP_FUNC(RandSymPosDef)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE* t );
 
 
-
-/// Compute the determinant of any square matrix.
+// Compute the determinant of any square matrix.
 VECT_OP_TYPE  VECT_OP_FUNC(DetM)(    const VECT_OP_TYPE* sp, unsigned srn );
 
-/// Compute the determinant of a diagonal matrix.
+// Compute the determinant of a diagonal matrix.
 VECT_OP_TYPE  VECT_OP_FUNC(DetDiagM)(    const VECT_OP_TYPE* sp, unsigned srn);
 
-/// Compute the log determinant of any square matrix.
+// Compute the log determinant of any square matrix.
 VECT_OP_TYPE  VECT_OP_FUNC(LogDetM)(    const VECT_OP_TYPE* sp, unsigned srn );
 
-/// Compute the log determinant of a diagonal matrix.
+// Compute the log determinant of a diagonal matrix.
 VECT_OP_TYPE  VECT_OP_FUNC(LogDetDiagM)(    const VECT_OP_TYPE* sp, unsigned srn);
 
 
-/// Compute the inverse of a square matrix.  Returns NULL if the matrix is not invertable.
-/// 'drn' is the dimensionality of the data.
+// Compute the inverse of a square matrix.  Returns NULL if the matrix is not invertable.
+// 'drn' is the dimensionality of the data.
 VECT_OP_TYPE* VECT_OP_FUNC(InvM)(    VECT_OP_TYPE* dp, unsigned drn );
 
-/// Compute the inverse of a diagonal matrix. Returns NULL if the matrix is not invertable.
+// Compute the inverse of a diagonal matrix. Returns NULL if the matrix is not invertable.
 VECT_OP_TYPE* VECT_OP_FUNC(InvDiagM)(    VECT_OP_TYPE* dp, unsigned drn );
 
-/// Solve a linear system of the form AX=B where A[an,an] is square. 
-/// Since A is square B must have 'an' rows.
-/// Result is returned in B.
-/// Returns a pointer to B on success or NULL on fail.
-/// NOTE: Both A and B are overwritten by this operation.
+// Solve a linear system of the form AX=B where A[an,an] is square. 
+// Since A is square B must have 'an' rows.
+// Result is returned in B.
+// Returns a pointer to B on success or NULL on fail.
+// NOTE: Both A and B are overwritten by this operation.
 VECT_OP_TYPE* VECT_OP_FUNC(SolveLS)( VECT_OP_TYPE* A, unsigned an, VECT_OP_TYPE* B, unsigned bcn ); 
 
-/// Perform a Cholesky decomposition of the square symetric matrix U[un,un].
-/// The factorization has the form: A=U'TU.
-/// If the factorization is successful A is set to U and a pointer to A is returned.
-/// Note that the lower triangle of A is not overwritten. See CholZ().
-/// If the factorization fails NULL is returned.
+// Perform a Cholesky decomposition of the square symetric matrix U[un,un].
+// The factorization has the form: A=U'TU.
+// If the factorization is successful A is set to U and a pointer to A is returned.
+// Note that the lower triangle of A is not overwritten. See CholZ().
+// If the factorization fails NULL is returned.
 VECT_OP_TYPE* VECT_OP_FUNC(Chol)(VECT_OP_TYPE* A, unsigned an );
 
-/// Same as Chol() but sets the lower triangle of U to zero. 
-/// This is equivalent ot the Matlab version.
+// Same as Chol() but sets the lower triangle of U to zero. 
+// This is equivalent ot the Matlab version.
 VECT_OP_TYPE* VECT_OP_FUNC(CholZ)(VECT_OP_TYPE* U, unsigned un );
 
+// Calculate the best fit line: b0 + b1*x_i through the points x_i,y_i.
+// Set x to NULL if it uses sequential integers [0,1,2,3...]
+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 );
+
+
+//======================================================================================================================
+//)
+
+//( { label:"Stretch/Shrink" desc:"Stretch or shrink a vector by resampling." kw:[vop] }
 
-/// Return the average value of the contents of sbp[] between two fractional indexes
+// Return the average value of the contents of sbp[] between two fractional indexes
 VECT_OP_TYPE  VECT_OP_FUNC(FracAvg)( double bi, double ei, const VECT_OP_TYPE* sbp, unsigned sn );
 
-/// Shrinking function - Decrease the size of sbp[] by averaging blocks of values into single values in dbp[]
+// Shrinking function - Decrease the size of sbp[] by averaging blocks of values into single values in dbp[]
 VECT_OP_TYPE* VECT_OP_FUNC(DownSampleAvg)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn );
 
-/// Stretching function - linear interpolate between points in sbp[] to fill dbp[] ... where dn > sn
+// Stretching function - linear interpolate between points in sbp[] to fill dbp[] ... where dn > sn
 VECT_OP_TYPE* VECT_OP_FUNC(UpSampleInterp)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn );
 
-/// Stretch or shrink the sbp[] to fit into dbp[]
+// Stretch or shrink the sbp[] to fit into dbp[]
 VECT_OP_TYPE* VECT_OP_FUNC(FitToSize)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn );
 
-/// Stretch or shrink sV[] to fit into dV[] using a simple linear mapping.
-/// When stretching (sn<dn) each source element is repeated dn/sn times
-/// and the last fraction position is interpolated.  When shrinking 
-/// (sn>dn) each dest value is formed by the average of sequential segments
-/// of sn/dn source elements. Fractional values are used at the beginning
-/// and end of each segment.
+// Stretch or shrink sV[] to fit into dV[] using a simple linear mapping.
+// When stretching (sn<dn) each source element is repeated dn/sn times
+// and the last fraction position is interpolated.  When shrinking 
+// (sn>dn) each dest value is formed by the average of sequential segments
+// of sn/dn source elements. Fractional values are used at the beginning
+// and end of each segment.
 VECT_OP_TYPE* VECT_OP_FUNC(LinearMap)(VECT_OP_TYPE* dV, unsigned dn, VECT_OP_TYPE* sV, unsigned sn );
 
-/// Generate a vector of uniformly distributed random numbers in the range minVal to maxVal.
+//======================================================================================================================
+//)
+
+//( { label:"Random number generation" desc:"Generate random numbers." kw:[vop] }
+
+// Generate a vector of uniformly distributed random numbers in the range minVal to maxVal.
 VECT_OP_TYPE* VECT_OP_FUNC(Random)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE minVal, VECT_OP_TYPE maxVal );
 
-/// Generate dn random numbers integers between 0 and wn-1 based on a the relative 
-/// weights in wp[wn].  Note thtat the weights do not have to sum to 1.0.
+// Generate dn random numbers integers between 0 and wn-1 based on a the relative 
+// weights in wp[wn].  Note thtat the weights do not have to sum to 1.0.
 unsigned*  VECT_OP_FUNC(WeightedRandInt)( unsigned* dbp, unsigned dn, const VECT_OP_TYPE* wp, unsigned wn );
 
-/// Generate a vector of normally distributed univariate random numbers 
+// Generate a vector of normally distributed univariate random numbers 
 VECT_OP_TYPE* VECT_OP_FUNC(RandomGauss)(  VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE mean, VECT_OP_TYPE var );
 
-/// Generate a vector of normally distributed univariate random numbers where each value has been drawn from a 
-/// seperately parameterized Gaussian distribution. meanV[] and varV[] must both contain dn velues.
+// Generate a vector of normally distributed univariate random numbers where each value has been drawn from a 
+// seperately parameterized Gaussian distribution. meanV[] and varV[] must both contain dn velues.
 VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* varV );
 
-/// Generate a matrix of multi-dimensional random values. Each column represents a single vector value and each row contains a dimension.
-/// meanV[] and varV[] must both contain drn elements where each meanV[i],varV[i] pair parameterize one dimensions Gaussian distribution.
+// Generate a matrix of multi-dimensional random values. Each column represents a single vector value and each row contains a dimension.
+// meanV[] and varV[] must both contain drn elements where each meanV[i],varV[i] pair parameterize one dimensions Gaussian distribution.
 VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* varV );
 VECT_OP_TYPE* VECT_OP_FUNC(RandomGaussDiagM)( VECT_OP_TYPE* dbp, unsigned drn, unsigned dcn, const VECT_OP_TYPE* meanV, const VECT_OP_TYPE* diagCovarM );
 
-/// Generate a matrix of multivariate random values drawn from a normal distribution.
-/// The dimensionality of the values are 'drn'.
-/// The count of returned values is 'dcn'.
-/// meanV[drn] and covarM[drn,drn] parameterize the normal distribution.
-/// The covariance matrix must be symetric and positive definite. 
-/// t[(drn*drn) ] points to scratch memory or is set to NULL if the function should
-///   allocate the memory internally.
-/// Based on octave function mvrnd.m.
+// Generate a matrix of multivariate random values drawn from a normal distribution.
+// The dimensionality of the values are 'drn'.
+// The count of returned values is 'dcn'.
+// meanV[drn] and covarM[drn,drn] parameterize the normal distribution.
+// The covariance matrix must be symetric and positive definite. 
+// t[(drn*drn) ] points to scratch memory or is set to NULL if the function should
+//   allocate the memory internally.
+// Based on octave function mvrnd.m.
 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 );
 
-/// Same as RandomGaussNonDiagM() except requires the upper trianglular 
-/// Cholesky factor of the covar matrix in 'uM'. 
+// Same as RandomGaussNonDiagM() except requires the upper trianglular 
+// Cholesky factor of the covar matrix in 'uM'. 
 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 );
 
 
-/// Generate a matrix of N*K multi-dimensional data points.
-/// Where D is the dimensionality of the data. (D == drn).
-/// K is the number of multi-dimensional PDF's (clusters).
-/// N is the number of data points to generate per cluster. 
-/// dbp[ D, N*K ] contains the returned data point. 
-/// The first N columns is associated with the cluster 0, 
-/// the next N columns is associated with cluster 1, ...
-/// meanM[ D, K ] and varM[D,K] parameterize the generating PDF.s for each cluster
+// Generate a matrix of N*K multi-dimensional data points.
+// Where D is the dimensionality of the data. (D == drn).
+// K is the number of multi-dimensional PDF's (clusters).
+// N is the number of data points to generate per cluster. 
+// dbp[ D, N*K ] contains the returned data point. 
+// The first N columns is associated with the cluster 0, 
+// the next N columns is associated with cluster 1, ...
+// meanM[ D, K ] and varM[D,K] parameterize the generating PDF.s for each cluster
 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 );
 
-/// Generate the set of coordinates which describe a circle with a center at x,y.
-/// dbp[dn,2] must contain 2*dn elements.  The first column holds the x coord and and the second holds the y coord.
-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 );
 
-/// The following functions all return the phase of the next value. 
+// Evaluate the univariate normal distribution defined by 'mean' and 'stdDev'.
+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 );
+
+// 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].  D is the dimensionality of the data. N is the number of
+// data points to evaluate and values to return in yV[N]. 
+// Set diagFl to true if covarM is diagonal.
+// The function fails and returns false if the covariance matrix is singular.
+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 );
+
+// Same as multVarGaussPDF[] except takes the inverse covar mtx invCovarM[D,D] 
+// and log determinant of covar mtx. 
+// Always returns yV[].
+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* invCovarM, VECT_OP_TYPE logDet, unsigned D, unsigned N, bool diagFl );
+
+// Same as multVarGaussPDF[] except uses a function to obtain the data vectors.
+// srcFunc() can filter the data points by returning NULL if the data vector at frmIdx should
+// not be evaluated against the PDF. In this case yV[frmIdx] will be set to 0.
+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* invCovarM, 
+  VECT_OP_TYPE        logDet, 
+  unsigned            D, 
+  unsigned            N, 
+  bool                diagFl );
+
+
+//======================================================================================================================
+//)
+
+
+//( { label:"Signal generators" desc:"Generate periodic signals." kw:[vop] }
+
+// The following functions all return the phase of the next value. 
 unsigned      VECT_OP_FUNC(SynthSine)(      VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz );
 unsigned      VECT_OP_FUNC(SynthCosine)(    VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz );
 unsigned      VECT_OP_FUNC(SynthSquare)(    VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz, unsigned otCnt );
@@ -389,11 +465,33 @@ unsigned      VECT_OP_FUNC(SynthImpulse)(   VECT_OP_TYPE* dbp, unsigned dn, unsi
 unsigned      VECT_OP_FUNC(SynthPhasor)(    VECT_OP_TYPE* dbp, unsigned dn, unsigned phase, double srate, double hz ); 
 
 
-/// Return value should be passed back via delaySmp on the next call.
+// Return value should be passed back via delaySmp on the next call.
 VECT_OP_TYPE  VECT_OP_FUNC(SynthPinkNoise)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE delaySmp );
 
-/// Same as Matlab linspace() v[i] = i * (limit-1)/n
-VECT_OP_TYPE*  VECT_OP_FUNC(LinSpace)( VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE base, VECT_OP_TYPE limit );
+//======================================================================================================================
+//)
+
+//( { label:"Exponential conversion" desc:"pow() and log() functions." kw:[vop] }
+
+// Raise dbp[] to the power 'expon'
+VECT_OP_TYPE* VECT_OP_FUNC(PowVS)(  VECT_OP_TYPE* dbp, unsigned dn, VECT_OP_TYPE expon );
+VECT_OP_TYPE* VECT_OP_FUNC(PowVVS)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE expon );
+
+// Take the natural log of all values in sbp[dn]. It is allowable for sbp point to the same array as dbp=.
+VECT_OP_TYPE* VECT_OP_FUNC(LogV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp );
+
+//======================================================================================================================
+//)
+
+//( { label:"dB Conversions" desc:"Convert vectors between dB,linear and power representations." kw:[vop] }
+
+// Convert a magnitude (amplitude) spectrum to/from decibels. 
+// It is allowable for dbp==sbp.
+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* VECT_OP_FUNC(DbToAmplVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp);
+
+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* VECT_OP_FUNC(DbToPowVV)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sbp);
 
 VECT_OP_TYPE* VECT_OP_FUNC(LinearToDb)(    VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE mult );
 VECT_OP_TYPE* VECT_OP_FUNC(dBToLinear)(    VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp, VECT_OP_TYPE mult );
@@ -401,6 +499,10 @@ VECT_OP_TYPE* VECT_OP_FUNC(AmplitudeToDb)( VECT_OP_TYPE* dbp, unsigned dn, const
 VECT_OP_TYPE* VECT_OP_FUNC(PowerToDb)(     VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
 VECT_OP_TYPE* VECT_OP_FUNC(dBToAmplitude)( VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
 VECT_OP_TYPE* VECT_OP_FUNC(dBToPower)(     VECT_OP_TYPE* dbp, unsigned dn, const VECT_OP_TYPE* sp );
+//======================================================================================================================
+//)
+
+//( { label:"DSP Windows" desc:"DSP windowing functions." kw:[vop] }
 
 VECT_OP_TYPE  VECT_OP_FUNC(KaiserBetaFromSidelobeReject)(  double sidelobeRejectDb );
 VECT_OP_TYPE  VECT_OP_FUNC(KaiserFreqResolutionFactor)( double sidelobeRejectDb );
@@ -410,84 +512,86 @@ VECT_OP_TYPE* VECT_OP_FUNC(Hamming)( VECT_OP_TYPE* dbp, unsigned dn );
 VECT_OP_TYPE* VECT_OP_FUNC(Hann)(    VECT_OP_TYPE* dbp, unsigned dn );
 VECT_OP_TYPE* VECT_OP_FUNC(Triangle)(VECT_OP_TYPE* dbp, unsigned dn );
 
-/// The MATLAB equivalent Hamming and Hann windows.
+// The MATLAB equivalent Hamming and Hann windows.
 //VECT_OP_TYPE* VECT_OP_FUNC(HammingMatlab)(VECT_OP_TYPE* dbp, unsigned dn );
 VECT_OP_TYPE* VECT_OP_FUNC(HannMatlab)(   VECT_OP_TYPE* dbp, unsigned dn );
 
-/// Simulates the MATLAB GaussWin function. Set arg to 2.5 to simulate the default arg
-/// as used by MATLAB.
+// Simulates the MATLAB GaussWin function. Set arg to 2.5 to simulate the default arg
+// as used by MATLAB.
 VECT_OP_TYPE*	VECT_OP_FUNC(GaussWin)( VECT_OP_TYPE* dbp, unsigned dn, double arg );
-
-
-/// Direct form II algorithm based on the MATLAB implmentation
-/// http://www.mathworks.com/access/helpdesk/help/techdoc/ref/filter.html#f83-1015962
-/// The only difference between this function and the equivalent MATLAB filter() function
-/// is that the first feedforward coeff is given as a seperate value. The first  b coefficient
-///  in this function is therefore the same as the second coefficient in the MATLAB function.
-///  and the first a[] coefficient (which is generally set to 1.0) is skipped.
-///  Example:
-///  Matlab:         b=[.5 .4 .3]  a=[1 .2 .1]
-///  Equiv:  b0 = .5 b=[   .4 .3]  a=[  .2 .1]; 
-///
-/// y[yn] - output vector 
-/// x[xn] - input vector. xn must be <= yn. if xn < yn then the end of y[] is set to zero.
-/// b0 - signal scale. This can also be seen as b[0] (which is not included in b[])
-/// b[dn] - feedforward coeff's b[1..dn-1]
-/// a[dn] - feedback coeff's    a[1..dn-1]
-/// d[dn+1] - delay registers - note that this array must be one element longer than the coeff arrays.
-/// 
+//======================================================================================================================
+//)
+
+//( { label:"DSP Filters" desc:"DSP filtering functions." kw:[vop] }
+
+// Direct form II algorithm based on the MATLAB implmentation
+// http://www.mathworks.com/access/helpdesk/help/techdoc/ref/filter.html#f83-1015962
+// The only difference between this function and the equivalent MATLAB filter() function
+// is that the first feedforward coeff is given as a seperate value. The first  b coefficient
+//  in this function is therefore the same as the second coefficient in the MATLAB function.
+//  and the first a[] coefficient (which is generally set to 1.0) is skipped.
+//  Example:
+//  Matlab:         b=[.5 .4 .3]  a=[1 .2 .1]
+//  Equiv:  b0 = .5 b=[   .4 .3]  a=[  .2 .1]; 
+//
+// y[yn] - output vector 
+// x[xn] - input vector. xn must be <= yn. if xn < yn then the end of y[] is set to zero.
+// b0 - signal scale. This can also be seen as b[0] (which is not included in b[])
+// b[dn] - feedforward coeff's b[1..dn-1]
+// a[dn] - feedback coeff's    a[1..dn-1]
+// d[dn+1] - delay registers - note that this array must be one element longer than the coeff arrays.
+// 
 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 );
 
 struct cmFilter_str;
 //typedef cmRC_t (*VECT_OP_FUNC(FiltExecFunc_t))( struct acFilter_str* f,  const VECT_OP_TYPE* x, unsigned xn, VECT_OP_TYPE* y, unsigned yn );
 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 );
 
-/// Compute the coefficients of a low/high pass FIR filter
-/// wndV[dn] gives the window function used to truncate the ideal low-pass impulse response.
-/// Set wndV to NULL to use a unity window.
-/// See enum { kHighPass_LPSincFl=0x01, kNormalize_LPSincFl=0x02 } in cmVectOps.h
+// Compute the coefficients of a low/high pass FIR filter
+// wndV[dn] gives the window function used to truncate the ideal low-pass impulse response.
+// Set wndV to NULL to use a unity window.
+// See enum { kHighPass_LPSincFl=0x01, kNormalize_LPSincFl=0x02 } in cmVectOps.h
 VECT_OP_TYPE* VECT_OP_FUNC(LP_Sinc)(VECT_OP_TYPE* dp, unsigned dn, const VECT_OP_TYPE* wndV, double srate, double fcHz, unsigned flags );
 
-/// Compute the complex transient detection function from successive spectral frames.
-/// The spectral magntidue mag0V precedes mag1V and the phase (radians) spectrum phs0V precedes the phs1V which precedes phs2V.  
-/// binCnt gives the length of each of the spectral vectors.
-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 );
 
 
-/// Compute a set of filterCnt mel filter masks for wieghting magnitude spectra consisting of binCnt bins.
-/// The spectrum is divided into bandCnt equal bands in the mel domain
-/// Each row of the matrix contains the mask for a single filter band consisting of binCnt elements.  
-/// See enum{ kShiftMelFl=0x01, kNormalizeMelFl=0x02 } in cmVectOps.h
-/// Set kShiftMelFl to shift the mel bands onto the nearest FFT bin.
-/// Set kNormalizeMelFl to normalize the combined filters for unity gain.
-VECT_OP_TYPE* VECT_OP_FUNC(MelMask)( VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, double srate, unsigned flags );
+//======================================================================================================================
+//)
 
+//( { label:"Spectral Masking" desc:"A collection of spectral masking functions." kw:[vop] }
 
+// Compute a set of filterCnt mel filter masks for wieghting magnitude spectra consisting of binCnt bins.
+// The spectrum is divided into bandCnt equal bands in the mel domain
+// Each row of the matrix contains the mask for a single filter band consisting of binCnt elements.  
+// See enum{ kShiftMelFl=0x01, kNormalizeMelFl=0x02 } in cmVectOps.h
+// Set kShiftMelFl to shift the mel bands onto the nearest FFT bin.
+// Set kNormalizeMelFl to normalize the combined filters for unity gain.
+VECT_OP_TYPE* VECT_OP_FUNC(MelMask)( VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, double srate, unsigned flags );
 
-/// Fill binIdxV[bandCnt] and cntV[bandCnt] with a bin to band map.
-/// binIdx[] contains the first (minimum) bin index for a given band.
-/// cntV[]   contains the count of bins for each band.
-/// bandCnt is the number of bark bands to return 
-/// The function returns the actual number of bands mapped which will always be <= 23.
+// Fill binIdxV[bandCnt] and cntV[bandCnt] with a bin to band map.
+// binIdx[] contains the first (minimum) bin index for a given band.
+// cntV[]   contains the count of bins for each band.
+// bandCnt is the number of bark bands to return 
+// The function returns the actual number of bands mapped which will always be <= 23.
 unsigned VECT_OP_FUNC(BarkMap)(unsigned* binIdxV, unsigned* cntV, unsigned bandCnt, unsigned binCnt, double srate );
 
-/// Calc a set of triangle fitler masks into each row of maskMtx.
-/// maskMtx[ bandCnt, binCnt ] - result matrix
-/// binHz - freq resolution of the output filters.
-/// stSpread - Semi-tone spread above and below each center frequency (stSpread*2) is the total bandwidth. 
-///            (Only used if lowHzV or uprHzV are NULL)
-/// lowHz[ bandCnt ] - set of upper frequency limits for each band.
-/// ctrHz[ bandCnt ] set to the center value in Hz for each band
-/// uprHz[ bandCnt ] - set of lower frequency limits for each band.
-/// Note if lowHz[] and uprHz[] are set to NULL then stSpread is used to set the bandwidth of each band.
+// Calc a set of triangle fitler masks into each row of maskMtx.
+// maskMtx[ bandCnt, binCnt ] - result matrix
+// binHz - freq resolution of the output filters.
+// stSpread - Semi-tone spread above and below each center frequency (stSpread*2) is the total bandwidth. 
+//            (Only used if lowHzV or uprHzV are NULL)
+// lowHz[ bandCnt ] - set of upper frequency limits for each band.
+// ctrHz[ bandCnt ] set to the center value in Hz for each band
+// uprHz[ bandCnt ] - set of lower frequency limits for each band.
+// Note if lowHz[] and uprHz[] are set to NULL then stSpread is used to set the bandwidth of each band.
 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* lowHzV, const VECT_OP_TYPE* uprHzV );
 
-/// Calculate a set of Bark band triangle filters into maskMtx.
-/// Each row of maskMtx contains the filter for one band.
-/// maskMtx[ bandCnt, binCnt ]
-/// bandCnt - the number of triangle bankds. If bandCnt is > 24 it will be reduced to 24.
-/// binCnt - the number of bins in the filters.
-/// binHz - the width of each bin in Hz.
+// Calculate a set of Bark band triangle filters into maskMtx.
+// Each row of maskMtx contains the filter for one band.
+// maskMtx[ bandCnt, binCnt ]
+// bandCnt - the number of triangle bankds. If bandCnt is > 24 it will be reduced to 24.
+// binCnt - the number of bins in the filters.
+// binHz - the width of each bin in Hz.
 VECT_OP_TYPE* VECT_OP_FUNC(BarkMask)(VECT_OP_TYPE* maskMtx, unsigned bandCnt, unsigned binCnt, double binHz );
 
 // Terhardt 1979 (Calculating virtual pitch, Hearing Research #1, pp 155-182)
@@ -497,39 +601,27 @@ VECT_OP_TYPE* VECT_OP_FUNC(TerhardtThresholdMask)(VECT_OP_TYPE* maskV, unsigned
 //Schroeder et al., 1979, JASA, Optimizing digital speech coders by exploiting masking properties of the human ear
 VECT_OP_TYPE* VECT_OP_FUNC(ShroederSpreadingFunc)(VECT_OP_TYPE* m, unsigned bandCnt, double srate);
 
-/// Compute a set of DCT-II coefficients. Result dp[ coeffCnt, filtCnt ]
-VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt );
-
-
-/// Set the indexes of local peaks greater than threshold in dbp[].
-/// Returns the number of peaks in dbp[]
-/// The maximum number of peaks from n source values is max(0,floor((n-1)/2)).
-/// Note that peaks will never be found at index 0 or index sn-1.
-unsigned VECT_OP_FUNC(PeakIndexes)( unsigned* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE threshold );
-
-/// Return the index of the bin containing v or acInvalidIdx if v is below sbp[0] or above sbp[ n-1 ]
-/// The bin limits are contained in sbp[].
-/// The value in spb[] are therefore expected to be in increasing order.
-/// The value returned will be in the range 0:sn-1.
-unsigned VECT_OP_FUNC(BinIndex)( const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE v );
-
-
-/// Assign each data point to one of k clusters using an expectation-maximization algorithm.
-/// k gives the number of clusters to identify
-/// Each column of sp[ srn, scn ] contains a multidimensional data point. 
-/// srn therefore defines the dimensionality of the data.
-/// Each column of centroidV[ srn, k ] is set to the centroid of each of k clusters.
-/// classIdxV[ scn ] assigns the index (0 to k-1) of a cluster to each soure data point
-/// The function returns the number of iterations required for the EM process to converge.
-/// selIdxV[ scn ] is optional and contains a list of id's assoc'd with each column of sM.
-/// selKey is a integer value.
-/// If selIdxV is non-NULL then only columns of sM[] where selIdxV[] == selKey will be clustered.
-/// All columns of sM[] where the associated column in selIdxV[] do not match will be ignored.
-/// Set 'initFromCentroidFl' to true if the initial centroids should be taken from centroidM[].
-/// otherwise the initial centroids are selected from 'k' random data points in sp[].
-/// The distance function distFunc(cV,dV,dN) is called to determine the distance from a 
-/// centroid the centroid 'cV[dN]' to a data point 'dV[dN]'. 'dN' is the dimensionality of the
-/// feature vector and is therefore equal to 'srn'.
+//======================================================================================================================
+//)
+
+//( { label:"Machine learning" desc:"K-means clustering and Viterbi algorithms." kw:[vop] }
+
+// Assign each data point to one of k clusters using an expectation-maximization algorithm.
+// k gives the number of clusters to identify
+// Each column of sp[ srn, scn ] contains a multidimensional data point. 
+// srn therefore defines the dimensionality of the data.
+// Each column of centroidV[ srn, k ] is set to the centroid of each of k clusters.
+// classIdxV[ scn ] assigns the index (0 to k-1) of a cluster to each soure data point
+// The function returns the number of iterations required for the EM process to converge.
+// selIdxV[ scn ] is optional and contains a list of id's assoc'd with each column of sM.
+// selKey is a integer value.
+// If selIdxV is non-NULL then only columns of sM[] where selIdxV[] == selKey will be clustered.
+// All columns of sM[] where the associated column in selIdxV[] do not match will be ignored.
+// Set 'initFromCentroidFl' to true if the initial centroids should be taken from centroidM[].
+// otherwise the initial centroids are selected from 'k' random data points in sp[].
+// The distance function distFunc(cV,dV,dN) is called to determine the distance from a 
+// centroid the centroid 'cV[dN]' to a data point 'dV[dN]'. 'dN' is the dimensionality of the
+// feature vector and is therefore equal to 'srn'.
 unsigned VECT_OP_FUNC(Kmeans)( 
   unsigned*           classIdxV, 
   VECT_OP_TYPE*       centroidM, 
@@ -543,9 +635,9 @@ unsigned VECT_OP_FUNC(Kmeans)(
   VECT_OP_TYPE (*distFunc)( void* userPtr, const VECT_OP_TYPE* cV, const VECT_OP_TYPE* dV, unsigned dN ), 
   void*               userDistPtr ); 
 
-/// 'srcFunc() should return NULL if the data point located at 'frmIdx' should not be included in the clustering.
-/// Clustering is considered to be complete after 'maxIterCnt' iterations or when
-/// 'deltaStopCnt' or fewer data points change class on a single iteration
+// 'srcFunc() should return NULL if the data point located at 'frmIdx' should not be included in the clustering.
+// Clustering is considered to be complete after 'maxIterCnt' iterations or when
+// 'deltaStopCnt' or fewer data points change class on a single iteration
 unsigned VECT_OP_FUNC(Kmeans2)( 
   unsigned*           classIdxV,         // classIdxV[scn] - data point class assignments
   VECT_OP_TYPE*       centroidM,         // centroidM[srn,K] - cluster centroids
@@ -559,64 +651,67 @@ unsigned VECT_OP_FUNC(Kmeans2)(
   int                iterCnt,            // max. number of iterations (-1 to ignore)
   int                deltaStopCnt);      // if less than deltaStopCnt data points change classes on a given iteration then convergence occurs.
 
-/// Evaluate the univariate normal distribution defined by 'mean' and 'stdDev'.
-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 );
-
-/// 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].  D is the dimensionality of the data. N is the number of
-/// data points to evaluate and values to return in yV[N]. 
-/// Set diagFl to true if covarM is diagonal.
-/// The function fails and returns false if the covariance matrix is singular.
-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 );
+// Determine the most likely state sequece stateV[timeN] given a 
+// transition matrix a[stateN,stateN], 
+// observation probability matrix b[stateN,timeN] and 
+// initial state probability vector phi[stateN].  
+// a[i,j] is the probability of transitioning from state i to state j.
+// b[i,t] is the probability of state i emitting the obj t.
+void VECT_OP_FUNC(DiscreteViterbi)(unsigned* stateV, unsigned timeN, unsigned stateN, const VECT_OP_TYPE* phi, const VECT_OP_TYPE* a, const VECT_OP_TYPE* b );
 
-/// Same as multVarGaussPDF[] except takes the inverse covar mtx invCovarM[D,D] 
-/// and log determinant of covar mtx. 
-/// Always returns yV[].
-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* invCovarM, VECT_OP_TYPE logDet, unsigned D, unsigned N, bool diagFl );
 
-/// Same as multVarGaussPDF[] except uses a function to obtain the data vectors.
-/// srcFunc() can filter the data points by returning NULL if the data vector at frmIdx should
-/// not be evaluated against the PDF. In this case yV[frmIdx] will be set to 0.
-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* invCovarM, 
-  VECT_OP_TYPE        logDet, 
-  unsigned            D, 
-  unsigned            N, 
-  bool                diagFl );
+//======================================================================================================================
+//)
 
-/// Determine the most likely state sequece stateV[timeN] given a 
-/// transition matrix a[stateN,stateN], 
-/// observation probability matrix b[stateN,timeN] and 
-/// initial state probability vector phi[stateN].  
-/// a[i,j] is the probability of transitioning from state i to state j.
-/// b[i,t] is the probability of state i emitting the obj t.
-void VECT_OP_FUNC(DiscreteViterbi)(unsigned* stateV, unsigned timeN, unsigned stateN, const VECT_OP_TYPE* phi, const VECT_OP_TYPE* a, const VECT_OP_TYPE* b );
+//( { label:"Graphics" desc:"Graphics related algorithms." kw:[vop] }
 
+// Generate the set of coordinates which describe a circle with a center at x,y.
+// dbp[dn,2] must contain 2*dn elements.  The first column holds the x coord and and the second holds the y coord.
+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 );
 
-/// Clip the line defined by x0,y0 to x1,y1 into the rect defined by xMin,yMin xMax,yMax.
+// Clip the line defined by x0,y0 to x1,y1 into the rect defined by xMin,yMin xMax,yMax.
 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 );
 
-/// Return true if the line defined by x0,y0 to x1,y1 intersects with
-/// the rectangle formed by xMin,yMin - xMax,yMax
+// Return true if the line defined by x0,y0 to x1,y1 intersects with
+// the rectangle formed by xMin,yMin - xMax,yMax
 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 );
 
 
-/// Return the perpendicular distance from the line formed by x0,y0 and x1,y1
-/// and the point px,py
+// Return the perpendicular distance from the line formed by x0,y0 and x1,y1
+// and the point px,py
 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);                              
 
-/// Calculate the best fit line: b0 + b1*x_i through the points x_i,y_i.
-/// Set x to NULL if it uses sequential integers [0,1,2,3...]
-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 );
+//======================================================================================================================
+//)
+
+//( { label:"Miscellaneous DSP" desc:"Common DSP algorithms." kw:[vop] }
+
+// Compute the complex transient detection function from successive spectral frames.
+// The spectral magntidue mag0V precedes mag1V and the phase (radians) spectrum phs0V precedes the phs1V which precedes phs2V.  
+// binCnt gives the length of each of the spectral vectors.
+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 );
+
+// Compute a set of DCT-II coefficients. Result dp[ coeffCnt, filtCnt ]
+VECT_OP_TYPE* VECT_OP_FUNC(DctMatrix)( VECT_OP_TYPE* dp, unsigned coeffCnt, unsigned filtCnt );
+
+
+// Set the indexes of local peaks greater than threshold in dbp[].
+// Returns the number of peaks in dbp[]
+// The maximum number of peaks from n source values is max(0,floor((n-1)/2)).
+// Note that peaks will never be found at index 0 or index sn-1.
+unsigned VECT_OP_FUNC(PeakIndexes)( unsigned* dbp, unsigned dn, const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE threshold );
+
+// Return the index of the bin containing v otherwise return kInvalidIdx if v is below sbp[0] or above sbp[ n-1 ]
+// The bin limits are contained in sbp[].
+// The value in spb[] are therefore expected to be in increasing order.
+// The value returned will be in the range 0:sn-1.
+unsigned VECT_OP_FUNC(BinIndex)( const VECT_OP_TYPE* sbp, unsigned sn, VECT_OP_TYPE v );
 
 
-/// Given the points x0[xy0N],y0[xy0N] fill y1[i] with the interpolated value of y0[] at
-/// x1[i].  Note that x0[] and x1[] must be increasing monotonic.
-/// This function is similar to the octave interp1() function.
+// Given the points x0[xy0N],y0[xy0N] fill y1[i] with the interpolated value of y0[] at
+// x1[i].  Note that x0[] and x1[] must be increasing monotonic.
+// This function is similar to the octave interp1() function.
 void VECT_OP_FUNC(Interp1)(VECT_OP_TYPE* y1, const VECT_OP_TYPE* x1, unsigned xy1N, const VECT_OP_TYPE* x0, const VECT_OP_TYPE* y0, unsigned xy0N );
  
+//======================================================================================================================
+//)