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