1 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
2 
3 /*
4     QM DSP Library
5 
6     Centre for Digital Music, Queen Mary, University of London.
7     This file copyright 2008-2009 Matthew Davies and QMUL.
8 
9     This program is free software; you can redistribute it and/or
10     modify it under the terms of the GNU General Public License as
11     published by the Free Software Foundation; either version 2 of the
12     License, or (at your option) any later version.  See the file
13     COPYING included with this distribution for more information.
14 */
15 
16 #include "TempoTrackV2.h"
17 
18 #include <cmath>
19 #include <cstdlib>
20 #include <iostream>
21 
22 #include "maths/MathUtilities.h"
23 
24 #define   EPS 0.0000008 // just some arbitrary small number
25 
TempoTrackV2(float rate,size_t increment)26 TempoTrackV2::TempoTrackV2(float rate, size_t increment) :
27     m_rate(rate), m_increment(increment) { }
~TempoTrackV2()28 TempoTrackV2::~TempoTrackV2() { }
29 
30 void
filter_df(d_vec_t & df)31 TempoTrackV2::filter_df(d_vec_t &df)
32 {
33     d_vec_t a(3);
34     d_vec_t b(3);
35     d_vec_t	lp_df(df.size());
36 
37     //equivalent in matlab to [b,a] = butter(2,0.4);
38     a[0] = 1.0000;
39     a[1] = -0.3695;
40     a[2] = 0.1958;
41     b[0] = 0.2066;
42     b[1] = 0.4131;
43     b[2] = 0.2066;
44 
45     double inp1 = 0.;
46     double inp2 = 0.;
47     double out1 = 0.;
48     double out2 = 0.;
49 
50 
51     // forwards filtering
52     for (unsigned int i = 0;i < df.size();i++)
53     {
54         lp_df[i] =  b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2;
55         inp2 = inp1;
56         inp1 = df[i];
57         out2 = out1;
58         out1 = lp_df[i];
59     }
60 
61     // copy forwards filtering to df...
62     // but, time-reversed, ready for backwards filtering
63     for (unsigned int i = 0;i < df.size();i++)
64     {
65         df[i] = lp_df[df.size()-i-1];
66     }
67 
68     for (unsigned int i = 0;i < df.size();i++)
69     {
70         lp_df[i] = 0.;
71     }
72 
73     inp1 = 0.; inp2 = 0.;
74     out1 = 0.; out2 = 0.;
75 
76   // backwards filetering on time-reversed df
77     for (unsigned int i = 0;i < df.size();i++)
78     {
79         lp_df[i] =  b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2;
80         inp2 = inp1;
81         inp1 = df[i];
82         out2 = out1;
83         out1 = lp_df[i];
84     }
85 
86   // write the re-reversed (i.e. forward) version back to df
87     for (unsigned int i = 0;i < df.size();i++)
88     {
89         df[i] = lp_df[df.size()-i-1];
90     }
91 }
92 
93 
94 // MEPD 28/11/12
95 // This function now allows for a user to specify an inputtempo (in BPM)
96 // and a flag "constraintempo" which replaces the general rayleigh weighting for periodicities
97 // with a gaussian which is centered around the input tempo
98 // Note, if inputtempo = 120 and constraintempo = false, then functionality is
99 // as it was before
100 void
calculateBeatPeriod(const vector<double> & df,vector<double> & beat_period,vector<double> & tempi,double inputtempo,bool constraintempo)101 TempoTrackV2::calculateBeatPeriod(const vector<double> &df,
102                                   vector<double> &beat_period,
103                                   vector<double> &tempi,
104                                   double inputtempo, bool constraintempo)
105 {
106     // to follow matlab.. split into 512 sample frames with a 128 hop size
107     // calculate the acf,
108     // then the rcf.. and then stick the rcfs as columns of a matrix
109     // then call viterbi decoding with weight vector and transition matrix
110     // and get best path
111 
112     unsigned int wv_len = 128;
113 
114     // MEPD 28/11/12
115     // the default value of inputtempo in the beat tracking plugin is 120
116     // so if the user specifies a different inputtempo, the rayparam will be updated
117     // accordingly.
118     // note: 60*44100/512 is a magic number
119     // this might (will?) break if a user specifies a different frame rate for the onset detection function
120     double rayparam = (60*44100/512)/inputtempo;
121 
122     // these debug statements can be removed.
123 //    std::cerr << "inputtempo" << inputtempo << std::endl;
124 //    std::cerr << "rayparam" << rayparam << std::endl;
125 //    std::cerr << "constraintempo" << constraintempo << std::endl;
126 
127     // make rayleigh weighting curve
128     d_vec_t wv(wv_len);
129 
130     // check whether or not to use rayleigh weighting (if constraintempo is false)
131     // or use gaussian weighting it (constraintempo is true)
132     if (constraintempo)
133     {
134         for (unsigned int i=0; i<wv.size(); i++)
135         {
136             // MEPD 28/11/12
137             // do a gaussian weighting instead of rayleigh
138             wv[i] = exp( (-1.*pow((static_cast<double> (i)-rayparam),2.)) / (2.*pow(rayparam/4.,2.)) );
139         }
140     }
141     else
142     {
143         for (unsigned int i=0; i<wv.size(); i++)
144         {
145             // MEPD 28/11/12
146             // standard rayleigh weighting over periodicities
147             wv[i] = (static_cast<double> (i) / pow(rayparam,2.)) * exp((-1.*pow(-static_cast<double> (i),2.)) / (2.*pow(rayparam,2.)));
148         }
149     }
150 
151     // beat tracking frame size (roughly 6 seconds) and hop (1.5 seconds)
152     unsigned int winlen = 512;
153     unsigned int step = 128;
154 
155     // matrix to store output of comb filter bank, increment column of matrix at each frame
156     d_mat_t rcfmat;
157     int col_counter = -1;
158 
159     // main loop for beat period calculation
160     for (unsigned int i=0; i+winlen<df.size(); i+=step)
161     {
162         // get dfframe
163         d_vec_t dfframe(winlen);
164         for (unsigned int k=0; k<winlen; k++)
165         {
166             dfframe[k] = df[i+k];
167         }
168         // get rcf vector for current frame
169         d_vec_t rcf(wv_len);
170         get_rcf(dfframe,wv,rcf);
171 
172         rcfmat.push_back( d_vec_t() ); // adds a new column
173         col_counter++;
174         for (unsigned int j=0; j<rcf.size(); j++)
175         {
176             rcfmat[col_counter].push_back( rcf[j] );
177         }
178     }
179 
180     // now call viterbi decoding function
181     viterbi_decode(rcfmat,wv,beat_period,tempi);
182 }
183 
184 
185 void
get_rcf(const d_vec_t & dfframe_in,const d_vec_t & wv,d_vec_t & rcf)186 TempoTrackV2::get_rcf(const d_vec_t &dfframe_in, const d_vec_t &wv, d_vec_t &rcf)
187 {
188     // calculate autocorrelation function
189     // then rcf
190     // just hard code for now... don't really need separate functions to do this
191 
192     // make acf
193 
194     d_vec_t dfframe(dfframe_in);
195 
196     MathUtilities::adaptiveThreshold(dfframe);
197 
198     d_vec_t acf(dfframe.size());
199 
200 
201     for (unsigned int lag=0; lag<dfframe.size(); lag++)
202     {
203         double sum = 0.;
204         double tmp = 0.;
205 
206         for (unsigned int n=0; n<(dfframe.size()-lag); n++)
207         {
208             tmp = dfframe[n] * dfframe[n+lag];
209             sum += tmp;
210         }
211         acf[lag] = static_cast<double> (sum/ (dfframe.size()-lag));
212     }
213 
214     // now apply comb filtering
215     int numelem = 4;
216 
217     for (unsigned int i = 2;i < rcf.size();i++) // max beat period
218     {
219         for (int a = 1;a <= numelem;a++) // number of comb elements
220         {
221             for (int b = 1-a;b <= a-1;b++) // general state using normalisation of comb elements
222             {
223                 rcf[i-1] += ( acf[(a*i+b)-1]*wv[i-1] ) / (2.*a-1.);	// calculate value for comb filter row
224             }
225         }
226     }
227 
228     // apply adaptive threshold to rcf
229     MathUtilities::adaptiveThreshold(rcf);
230 
231     double rcfsum =0.;
232     for (unsigned int i=0; i<rcf.size(); i++)
233     {
234         rcf[i] += EPS ;
235         rcfsum += rcf[i];
236     }
237 
238     // normalise rcf to sum to unity
239     for (unsigned int i=0; i<rcf.size(); i++)
240     {
241         rcf[i] /= (rcfsum + EPS);
242     }
243 }
244 
245 void
viterbi_decode(const d_mat_t & rcfmat,const d_vec_t & wv,d_vec_t & beat_period,d_vec_t & tempi)246 TempoTrackV2::viterbi_decode(const d_mat_t &rcfmat, const d_vec_t &wv, d_vec_t &beat_period, d_vec_t &tempi)
247 {
248     // following Kevin Murphy's Viterbi decoding to get best path of
249     // beat periods through rfcmat
250 
251     // make transition matrix
252     d_mat_t tmat;
253     for (unsigned int i=0;i<wv.size();i++)
254     {
255         tmat.push_back ( d_vec_t() ); // adds a new column
256         for (unsigned int j=0; j<wv.size(); j++)
257         {
258             tmat[i].push_back(0.); // fill with zeros initially
259         }
260     }
261 
262     // variance of Gaussians in transition matrix
263     // formed of Gaussians on diagonal - implies slow tempo change
264     double sigma = 8.;
265     // don't want really short beat periods, or really long ones
266     for (unsigned int i=20;i <wv.size()-20; i++)
267     {
268         for (unsigned int j=20; j<wv.size()-20; j++)
269         {
270             double mu = static_cast<double>(i);
271             tmat[i][j] = exp( (-1.*pow((j-mu),2.)) / (2.*pow(sigma,2.)) );
272         }
273     }
274 
275     // parameters for Viterbi decoding... this part is taken from
276     // Murphy's matlab
277 
278     d_mat_t delta;
279     i_mat_t psi;
280     for (unsigned int i=0;i <rcfmat.size(); i++)
281     {
282         delta.push_back( d_vec_t());
283         psi.push_back( i_vec_t());
284         for (unsigned int j=0; j<rcfmat[i].size(); j++)
285         {
286             delta[i].push_back(0.); // fill with zeros initially
287             psi[i].push_back(0); // fill with zeros initially
288         }
289     }
290 
291 
292     unsigned int T = delta.size();
293 
294     if (T < 2) return; // can't do anything at all meaningful
295 
296     unsigned int Q = delta[0].size();
297 
298     // initialize first column of delta
299     for (unsigned int j=0; j<Q; j++)
300     {
301         delta[0][j] = wv[j] * rcfmat[0][j];
302         psi[0][j] = 0;
303     }
304 
305     double deltasum = 0.;
306     for (unsigned int i=0; i<Q; i++)
307     {
308         deltasum += delta[0][i];
309     }
310     for (unsigned int i=0; i<Q; i++)
311     {
312         delta[0][i] /= (deltasum + EPS);
313     }
314 
315 
316     for (unsigned int t=1; t<T; t++)
317     {
318         d_vec_t tmp_vec(Q);
319 
320         for (unsigned int j=0; j<Q; j++)
321         {
322             for (unsigned int i=0; i<Q; i++)
323             {
324                 tmp_vec[i] = delta[t-1][i] * tmat[j][i];
325             }
326 
327             delta[t][j] = get_max_val(tmp_vec);
328 
329             psi[t][j] = get_max_ind(tmp_vec);
330 
331             delta[t][j] *= rcfmat[t][j];
332         }
333 
334         // normalise current delta column
335         double deltasum = 0.;
336         for (unsigned int i=0; i<Q; i++)
337         {
338             deltasum += delta[t][i];
339         }
340         for (unsigned int i=0; i<Q; i++)
341         {
342             delta[t][i] /= (deltasum + EPS);
343         }
344     }
345 
346     i_vec_t bestpath(T);
347     d_vec_t tmp_vec(Q);
348     for (unsigned int i=0; i<Q; i++)
349     {
350         tmp_vec[i] = delta[T-1][i];
351     }
352 
353     // find starting point - best beat period for "last" frame
354     bestpath[T-1] = get_max_ind(tmp_vec);
355 
356     // backtrace through index of maximum values in psi
357     for (unsigned int t=T-2; t>0 ;t--)
358     {
359         bestpath[t] = psi[t+1][bestpath[t+1]];
360     }
361 
362     // weird but necessary hack -- couldn't get above loop to terminate at t >= 0
363     bestpath[0] = psi[1][bestpath[1]];
364 
365     unsigned int lastind = 0;
366     for (unsigned int i=0; i<T; i++)
367     {
368         unsigned int step = 128;
369         for (unsigned int j=0; j<step; j++)
370         {
371             lastind = i*step+j;
372             beat_period[lastind] = bestpath[i];
373         }
374 //        std::cerr << "bestpath[" << i << "] = " << bestpath[i] << " (used for beat_periods " << i*step << " to " << i*step+step-1 << ")" << std::endl;
375     }
376 
377     //fill in the last values...
378     for (unsigned int i=lastind; i<beat_period.size(); i++)
379     {
380         beat_period[i] = beat_period[lastind];
381     }
382 
383     for (unsigned int i = 0; i < beat_period.size(); i++)
384     {
385         tempi.push_back((60. * m_rate / m_increment)/beat_period[i]);
386     }
387 }
388 
389 double
get_max_val(const d_vec_t & df)390 TempoTrackV2::get_max_val(const d_vec_t &df)
391 {
392     double maxval = 0.;
393     for (unsigned int i=0; i<df.size(); i++)
394     {
395         if (maxval < df[i])
396         {
397             maxval = df[i];
398         }
399     }
400 
401     return maxval;
402 }
403 
404 int
get_max_ind(const d_vec_t & df)405 TempoTrackV2::get_max_ind(const d_vec_t &df)
406 {
407     double maxval = 0.;
408     int ind = 0;
409     for (unsigned int i=0; i<df.size(); i++)
410     {
411         if (maxval < df[i])
412         {
413             maxval = df[i];
414             ind = i;
415         }
416     }
417 
418     return ind;
419 }
420 
421 void
normalise_vec(d_vec_t & df)422 TempoTrackV2::normalise_vec(d_vec_t &df)
423 {
424     double sum = 0.;
425     for (unsigned int i=0; i<df.size(); i++)
426     {
427         sum += df[i];
428     }
429 
430     for (unsigned int i=0; i<df.size(); i++)
431     {
432         df[i]/= (sum + EPS);
433     }
434 }
435 
436 // MEPD 28/11/12
437 // this function has been updated to allow the "alpha" and "tightness" parameters
438 // of the dynamic program to be set by the user
439 // the default value of alpha = 0.9 and tightness = 4
440 void
calculateBeats(const vector<double> & df,const vector<double> & beat_period,vector<double> & beats,double alpha,double tightness)441 TempoTrackV2::calculateBeats(const vector<double> &df,
442                              const vector<double> &beat_period,
443                              vector<double> &beats, double alpha, double tightness)
444 {
445     if (df.empty() || beat_period.empty()) return;
446 
447     d_vec_t cumscore(df.size()); // store cumulative score
448     i_vec_t backlink(df.size()); // backlink (stores best beat locations at each time instant)
449     d_vec_t localscore(df.size()); // localscore, for now this is the same as the detection function
450 
451     for (unsigned int i=0; i<df.size(); i++)
452     {
453         localscore[i] = df[i];
454         backlink[i] = -1;
455     }
456 
457     //double tightness = 4.;
458     //double alpha = 0.9;
459     // MEPD 28/11/12
460     // debug statements that can be removed.
461 //    std::cerr << "alpha" << alpha << std::endl;
462 //    std::cerr << "tightness" << tightness << std::endl;
463 
464     // main loop
465     for (unsigned int i=0; i<localscore.size(); i++)
466     {
467         int prange_min = -2*beat_period[i];
468         int prange_max = round(-0.5*beat_period[i]);
469 
470         // transition range
471         d_vec_t txwt (prange_max - prange_min + 1);
472         d_vec_t scorecands (txwt.size());
473 
474         for (unsigned int j=0;j<txwt.size();j++)
475         {
476             double mu = static_cast<double> (beat_period[i]);
477             txwt[j] = exp( -0.5*pow(tightness * log((round(2*mu)-j)/mu),2));
478 
479             // IF IN THE ALLOWED RANGE, THEN LOOK AT CUMSCORE[I+PRANGE_MIN+J
480             // ELSE LEAVE AT DEFAULT VALUE FROM INITIALISATION:  D_VEC_T SCORECANDS (TXWT.SIZE());
481 
482             int cscore_ind = i+prange_min+j;
483             if (cscore_ind >= 0)
484             {
485                 scorecands[j] = txwt[j] * cumscore[cscore_ind];
486             }
487         }
488 
489         // find max value and index of maximum value
490         double vv = get_max_val(scorecands);
491         int xx = get_max_ind(scorecands);
492 
493         cumscore[i] = alpha*vv + (1.-alpha)*localscore[i];
494         backlink[i] = i+prange_min+xx;
495 
496 //        std::cerr << "backlink[" << i << "] <= " << backlink[i] << std::endl;
497     }
498 
499     // STARTING POINT, I.E. LAST BEAT.. PICK A STRONG POINT IN cumscore VECTOR
500     d_vec_t tmp_vec;
501     for (unsigned int i=cumscore.size() - beat_period[beat_period.size()-1] ; i<cumscore.size(); i++)
502     {
503         tmp_vec.push_back(cumscore[i]);
504     }
505 
506     int startpoint = get_max_ind(tmp_vec) + cumscore.size() - beat_period[beat_period.size()-1] ;
507 
508     // can happen if no results obtained earlier (e.g. input too short)
509     if (startpoint >= (int)backlink.size()) startpoint = backlink.size()-1;
510 
511     // USE BACKLINK TO GET EACH NEW BEAT (TOWARDS THE BEGINNING OF THE FILE)
512     //  BACKTRACKING FROM THE END TO THE BEGINNING.. MAKING SURE NOT TO GO BEFORE SAMPLE 0
513     i_vec_t ibeats;
514     ibeats.push_back(startpoint);
515 //    std::cerr << "startpoint = " << startpoint << std::endl;
516     while (backlink[ibeats.back()] > 0)
517     {
518 //        std::cerr << "backlink[" << ibeats.back() << "] = " << backlink[ibeats.back()] << std::endl;
519         int b = ibeats.back();
520         if (backlink[b] == b) break; // shouldn't happen... haha
521         ibeats.push_back(backlink[b]);
522     }
523 
524     // REVERSE SEQUENCE OF IBEATS AND STORE AS BEATS
525     for (unsigned int i=0; i<ibeats.size(); i++)
526     {
527         beats.push_back( static_cast<double>(ibeats[ibeats.size()-i-1]) );
528     }
529 }
530 
531 
532