comparison dsp/tempotracking/TempoTrackV2.cpp @ 501:12b5a9244bb0

Style fixes: avoid unsigned, fix formatting
author Chris Cannam <cannam@all-day-breakfast.com>
date Wed, 05 Jun 2019 10:21:48 +0100
parents bb78ca3fe7de
children 162673c8f9de
comparison
equal deleted inserted replaced
500:8a8693f38b91 501:12b5a9244bb0
32 TempoTrackV2::~TempoTrackV2() { } 32 TempoTrackV2::~TempoTrackV2() { }
33 33
34 void 34 void
35 TempoTrackV2::filter_df(d_vec_t &df) 35 TempoTrackV2::filter_df(d_vec_t &df)
36 { 36 {
37 int df_len = int(df.size());
38
37 d_vec_t a(3); 39 d_vec_t a(3);
38 d_vec_t b(3); 40 d_vec_t b(3);
39 d_vec_t lp_df(df.size()); 41 d_vec_t lp_df(df_len);
40 42
41 //equivalent in matlab to [b,a] = butter(2,0.4); 43 //equivalent in matlab to [b,a] = butter(2,0.4);
42 a[0] = 1.0000; 44 a[0] = 1.0000;
43 a[1] = -0.3695; 45 a[1] = -0.3695;
44 a[2] = 0.1958; 46 a[2] = 0.1958;
51 double out1 = 0.; 53 double out1 = 0.;
52 double out2 = 0.; 54 double out2 = 0.;
53 55
54 56
55 // forwards filtering 57 // forwards filtering
56 for (unsigned int i = 0;i < df.size();i++) { 58 for (int i = 0; i < df_len; i++) {
57 lp_df[i] = b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2; 59 lp_df[i] = b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2;
58 inp2 = inp1; 60 inp2 = inp1;
59 inp1 = df[i]; 61 inp1 = df[i];
60 out2 = out1; 62 out2 = out1;
61 out1 = lp_df[i]; 63 out1 = lp_df[i];
62 } 64 }
63 65
64 // copy forwards filtering to df... 66 // copy forwards filtering to df...
65 // but, time-reversed, ready for backwards filtering 67 // but, time-reversed, ready for backwards filtering
66 for (unsigned int i = 0;i < df.size();i++) { 68 for (int i = 0; i < df_len; i++) {
67 df[i] = lp_df[df.size()-i-1]; 69 df[i] = lp_df[df_len - i - 1];
68 } 70 }
69 71
70 for (unsigned int i = 0;i < df.size();i++) { 72 for (int i = 0; i < df_len; i++) {
71 lp_df[i] = 0.; 73 lp_df[i] = 0.;
72 } 74 }
73 75
74 inp1 = 0.; inp2 = 0.; 76 inp1 = 0.; inp2 = 0.;
75 out1 = 0.; out2 = 0.; 77 out1 = 0.; out2 = 0.;
76 78
77 // backwards filetering on time-reversed df 79 // backwards filetering on time-reversed df
78 for (unsigned int i = 0;i < df.size();i++) { 80 for (int i = 0; i < df_len; i++) {
79 lp_df[i] = b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2; 81 lp_df[i] = b[0]*df[i] + b[1]*inp1 + b[2]*inp2 - a[1]*out1 - a[2]*out2;
80 inp2 = inp1; 82 inp2 = inp1;
81 inp1 = df[i]; 83 inp1 = df[i];
82 out2 = out1; 84 out2 = out1;
83 out1 = lp_df[i]; 85 out1 = lp_df[i];
84 } 86 }
85 87
86 // write the re-reversed (i.e. forward) version back to df 88 // write the re-reversed (i.e. forward) version back to df
87 for (unsigned int i = 0;i < df.size();i++) { 89 for (int i = 0; i < df_len; i++) {
88 df[i] = lp_df[df.size()-i-1]; 90 df[i] = lp_df[df_len - i - 1];
89 } 91 }
90 } 92 }
91 93
92 94
93 // MEPD 28/11/12 95 // MEPD 28/11/12
106 // calculate the acf, 108 // calculate the acf,
107 // then the rcf.. and then stick the rcfs as columns of a matrix 109 // then the rcf.. and then stick the rcfs as columns of a matrix
108 // then call viterbi decoding with weight vector and transition matrix 110 // then call viterbi decoding with weight vector and transition matrix
109 // and get best path 111 // and get best path
110 112
111 unsigned int wv_len = 128; 113 int wv_len = 128;
112 114
113 // MEPD 28/11/12 115 // MEPD 28/11/12
114 // the default value of inputtempo in the beat tracking plugin is 120 116 // the default value of inputtempo in the beat tracking plugin is 120
115 // so if the user specifies a different inputtempo, the rayparam will be updated 117 // so if the user specifies a different inputtempo, the rayparam will be updated
116 // accordingly. 118 // accordingly.
122 d_vec_t wv(wv_len); 124 d_vec_t wv(wv_len);
123 125
124 // check whether or not to use rayleigh weighting (if constraintempo is false) 126 // check whether or not to use rayleigh weighting (if constraintempo is false)
125 // or use gaussian weighting it (constraintempo is true) 127 // or use gaussian weighting it (constraintempo is true)
126 if (constraintempo) { 128 if (constraintempo) {
127 for (unsigned int i=0; i<wv.size(); i++) { 129 for (int i = 0; i < wv_len; i++) {
128 // MEPD 28/11/12 130 // MEPD 28/11/12
129 // do a gaussian weighting instead of rayleigh 131 // do a gaussian weighting instead of rayleigh
130 wv[i] = exp( (-1.*pow((static_cast<double> (i)-rayparam),2.)) / (2.*pow(rayparam/4.,2.)) ); 132 wv[i] = exp( (-1.*pow((double(i)-rayparam),2.)) / (2.*pow(rayparam/4.,2.)) );
131 } 133 }
132 } else { 134 } else {
133 for (unsigned int i=0; i<wv.size(); i++) { 135 for (int i = 0; i < wv_len; i++) {
134 // MEPD 28/11/12 136 // MEPD 28/11/12
135 // standard rayleigh weighting over periodicities 137 // standard rayleigh weighting over periodicities
136 wv[i] = (static_cast<double> (i) / pow(rayparam,2.)) * exp((-1.*pow(-static_cast<double> (i),2.)) / (2.*pow(rayparam,2.))); 138 wv[i] = (double(i) / pow(rayparam,2.)) * exp((-1.*pow(-double(i),2.)) / (2.*pow(rayparam,2.)));
137 } 139 }
138 } 140 }
139 141
140 // beat tracking frame size (roughly 6 seconds) and hop (1.5 seconds) 142 // beat tracking frame size (roughly 6 seconds) and hop (1.5 seconds)
141 unsigned int winlen = 512; 143 int winlen = 512;
142 unsigned int step = 128; 144 int step = 128;
143 145
144 // matrix to store output of comb filter bank, increment column of matrix at each frame 146 // matrix to store output of comb filter bank, increment column of matrix at each frame
145 d_mat_t rcfmat; 147 d_mat_t rcfmat;
146 int col_counter = -1; 148 int col_counter = -1;
149 int df_len = int(df.size());
147 150
148 // main loop for beat period calculation 151 // main loop for beat period calculation
149 for (unsigned int i=0; i+winlen<df.size(); i+=step) { 152 for (int i = 0; i+winlen < df_len; i+=step) {
150 153
151 // get dfframe 154 // get dfframe
152 d_vec_t dfframe(winlen); 155 d_vec_t dfframe(winlen);
153 for (unsigned int k=0; k<winlen; k++) { 156 for (int k=0; k < winlen; k++) {
154 dfframe[k] = df[i+k]; 157 dfframe[k] = df[i+k];
155 } 158 }
156 // get rcf vector for current frame 159 // get rcf vector for current frame
157 d_vec_t rcf(wv_len); 160 d_vec_t rcf(wv_len);
158 get_rcf(dfframe,wv,rcf); 161 get_rcf(dfframe,wv,rcf);
159 162
160 rcfmat.push_back( d_vec_t() ); // adds a new column 163 rcfmat.push_back( d_vec_t() ); // adds a new column
161 col_counter++; 164 col_counter++;
162 for (unsigned int j=0; j<rcf.size(); j++) { 165 for (int j = 0; j < wv_len; j++) {
163 rcfmat[col_counter].push_back( rcf[j] ); 166 rcfmat[col_counter].push_back( rcf[j] );
164 } 167 }
165 } 168 }
166 169
167 // now call viterbi decoding function 170 // now call viterbi decoding function
180 183
181 d_vec_t dfframe(dfframe_in); 184 d_vec_t dfframe(dfframe_in);
182 185
183 MathUtilities::adaptiveThreshold(dfframe); 186 MathUtilities::adaptiveThreshold(dfframe);
184 187
185 d_vec_t acf(dfframe.size()); 188 int dfframe_len = int(dfframe.size());
186 189 int rcf_len = int(rcf.size());
187 for (unsigned int lag=0; lag<dfframe.size(); lag++) { 190
191 d_vec_t acf(dfframe_len);
192
193 for (int lag = 0; lag < dfframe_len; lag++) {
188 double sum = 0.; 194 double sum = 0.;
189 double tmp = 0.; 195 double tmp = 0.;
190 196
191 for (unsigned int n=0; n<(dfframe.size()-lag); n++) { 197 for (int n = 0; n < (dfframe_len - lag); n++) {
192 tmp = dfframe[n] * dfframe[n+lag]; 198 tmp = dfframe[n] * dfframe[n + lag];
193 sum += tmp; 199 sum += tmp;
194 } 200 }
195 acf[lag] = static_cast<double> (sum/ (dfframe.size()-lag)); 201 acf[lag] = double(sum/ (dfframe_len - lag));
196 } 202 }
197 203
198 // now apply comb filtering 204 // now apply comb filtering
199 int numelem = 4; 205 int numelem = 4;
200 206
201 for (unsigned int i = 2;i < rcf.size();i++) { // max beat period 207 for (int i = 2; i < rcf_len; i++) { // max beat period
202 for (int a = 1;a <= numelem;a++) { // number of comb elements 208 for (int a = 1; a <= numelem; a++) { // number of comb elements
203 for (int b = 1-a;b <= a-1;b++) { // general state using normalisation of comb elements 209 for (int b = 1-a; b <= a-1; b++) { // general state using normalisation of comb elements
204 rcf[i-1] += ( acf[(a*i+b)-1]*wv[i-1] ) / (2.*a-1.); // calculate value for comb filter row 210 rcf[i-1] += ( acf[(a*i+b)-1]*wv[i-1] ) / (2.*a-1.); // calculate value for comb filter row
205 } 211 }
206 } 212 }
207 } 213 }
208 214
209 // apply adaptive threshold to rcf 215 // apply adaptive threshold to rcf
210 MathUtilities::adaptiveThreshold(rcf); 216 MathUtilities::adaptiveThreshold(rcf);
211 217
212 double rcfsum =0.; 218 double rcfsum =0.;
213 for (unsigned int i=0; i<rcf.size(); i++) { 219 for (int i = 0; i < rcf_len; i++) {
214 rcf[i] += EPS ; 220 rcf[i] += EPS ;
215 rcfsum += rcf[i]; 221 rcfsum += rcf[i];
216 } 222 }
217 223
218 // normalise rcf to sum to unity 224 // normalise rcf to sum to unity
219 for (unsigned int i=0; i<rcf.size(); i++) { 225 for (int i = 0; i < rcf_len; i++) {
220 rcf[i] /= (rcfsum + EPS); 226 rcf[i] /= (rcfsum + EPS);
221 } 227 }
222 } 228 }
223 229
224 void 230 void
225 TempoTrackV2::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)
226 { 232 {
227 // following Kevin Murphy's Viterbi decoding to get best path of 233 // following Kevin Murphy's Viterbi decoding to get best path of
228 // beat periods through rfcmat 234 // beat periods through rfcmat
229 235
236 int wv_len = int(wv.size());
237
230 // make transition matrix 238 // make transition matrix
231 d_mat_t tmat; 239 d_mat_t tmat;
232 for (unsigned int i=0;i<wv.size();i++) { 240 for (int i = 0; i < wv_len; i++) {
233 tmat.push_back ( d_vec_t() ); // adds a new column 241 tmat.push_back ( d_vec_t() ); // adds a new column
234 for (unsigned int j=0; j<wv.size(); j++) { 242 for (int j = 0; j < wv_len; j++) {
235 tmat[i].push_back(0.); // fill with zeros initially 243 tmat[i].push_back(0.); // fill with zeros initially
236 } 244 }
237 } 245 }
238 246
239 // variance of Gaussians in transition matrix 247 // variance of Gaussians in transition matrix
240 // formed of Gaussians on diagonal - implies slow tempo change 248 // formed of Gaussians on diagonal - implies slow tempo change
241 double sigma = 8.; 249 double sigma = 8.;
242 // don't want really short beat periods, or really long ones 250 // don't want really short beat periods, or really long ones
243 for (unsigned int i=20;i <wv.size()-20; i++) { 251 for (int i = 20; i < wv_len - 20; i++) {
244 for (unsigned int j=20; j<wv.size()-20; j++) { 252 for (int j = 20; j < wv_len - 20; j++) {
245 double mu = static_cast<double>(i); 253 double mu = double(i);
246 tmat[i][j] = exp( (-1.*pow((j-mu),2.)) / (2.*pow(sigma,2.)) ); 254 tmat[i][j] = exp( (-1.*pow((j-mu),2.)) / (2.*pow(sigma,2.)) );
247 } 255 }
248 } 256 }
249 257
250 // parameters for Viterbi decoding... this part is taken from 258 // parameters for Viterbi decoding... this part is taken from
251 // Murphy's matlab 259 // Murphy's matlab
252 260
253 d_mat_t delta; 261 d_mat_t delta;
254 i_mat_t psi; 262 i_mat_t psi;
255 for (unsigned int i=0;i <rcfmat.size(); i++) { 263 for (int i = 0; i < int(rcfmat.size()); i++) {
256 delta.push_back( d_vec_t()); 264 delta.push_back(d_vec_t());
257 psi.push_back( i_vec_t()); 265 psi.push_back(i_vec_t());
258 for (unsigned int j=0; j<rcfmat[i].size(); j++) { 266 for (int j = 0; j < int(rcfmat[i].size()); j++) {
259 delta[i].push_back(0.); // fill with zeros initially 267 delta[i].push_back(0.); // fill with zeros initially
260 psi[i].push_back(0); // fill with zeros initially 268 psi[i].push_back(0); // fill with zeros initially
261 } 269 }
262 } 270 }
263 271
264 unsigned int T = delta.size(); 272 int T = delta.size();
265 273
266 if (T < 2) return; // can't do anything at all meaningful 274 if (T < 2) return; // can't do anything at all meaningful
267 275
268 unsigned int Q = delta[0].size(); 276 int Q = delta[0].size();
269 277
270 // initialize first column of delta 278 // initialize first column of delta
271 for (unsigned int j=0; j<Q; j++) { 279 for (int j = 0; j < Q; j++) {
272 delta[0][j] = wv[j] * rcfmat[0][j]; 280 delta[0][j] = wv[j] * rcfmat[0][j];
273 psi[0][j] = 0; 281 psi[0][j] = 0;
274 } 282 }
275 283
276 double deltasum = 0.; 284 double deltasum = 0.;
277 for (unsigned int i=0; i<Q; i++) { 285 for (int i = 0; i < Q; i++) {
278 deltasum += delta[0][i]; 286 deltasum += delta[0][i];
279 } 287 }
280 for (unsigned int i=0; i<Q; i++) { 288 for (int i = 0; i < Q; i++) {
281 delta[0][i] /= (deltasum + EPS); 289 delta[0][i] /= (deltasum + EPS);
282 } 290 }
283 291
284 for (unsigned int t=1; t<T; t++) 292 for (int t=1; t < T; t++)
285 { 293 {
286 d_vec_t tmp_vec(Q); 294 d_vec_t tmp_vec(Q);
287 295
288 for (unsigned int j=0; j<Q; j++) { 296 for (int j = 0; j < Q; j++) {
289 for (unsigned int i=0; i<Q; i++) { 297 for (int i = 0; i < Q; i++) {
290 tmp_vec[i] = delta[t-1][i] * tmat[j][i]; 298 tmp_vec[i] = delta[t-1][i] * tmat[j][i];
291 } 299 }
292 300
293 delta[t][j] = get_max_val(tmp_vec); 301 delta[t][j] = get_max_val(tmp_vec);
294 302
297 delta[t][j] *= rcfmat[t][j]; 305 delta[t][j] *= rcfmat[t][j];
298 } 306 }
299 307
300 // normalise current delta column 308 // normalise current delta column
301 double deltasum = 0.; 309 double deltasum = 0.;
302 for (unsigned int i=0; i<Q; i++) { 310 for (int i = 0; i < Q; i++) {
303 deltasum += delta[t][i]; 311 deltasum += delta[t][i];
304 } 312 }
305 for (unsigned int i=0; i<Q; i++) { 313 for (int i = 0; i < Q; i++) {
306 delta[t][i] /= (deltasum + EPS); 314 delta[t][i] /= (deltasum + EPS);
307 } 315 }
308 } 316 }
309 317
310 i_vec_t bestpath(T); 318 i_vec_t bestpath(T);
311 d_vec_t tmp_vec(Q); 319 d_vec_t tmp_vec(Q);
312 for (unsigned int i=0; i<Q; i++) { 320 for (int i = 0; i < Q; i++) {
313 tmp_vec[i] = delta[T-1][i]; 321 tmp_vec[i] = delta[T-1][i];
314 } 322 }
315 323
316 // find starting point - best beat period for "last" frame 324 // find starting point - best beat period for "last" frame
317 bestpath[T-1] = get_max_ind(tmp_vec); 325 bestpath[T-1] = get_max_ind(tmp_vec);
318 326
319 // backtrace through index of maximum values in psi 327 // backtrace through index of maximum values in psi
320 for (unsigned int t=T-2; t>0 ;t--) { 328 for (int t=T-2; t>0 ;t--) {
321 bestpath[t] = psi[t+1][bestpath[t+1]]; 329 bestpath[t] = psi[t+1][bestpath[t+1]];
322 } 330 }
323 331
324 // weird but necessary hack -- couldn't get above loop to terminate at t >= 0 332 // weird but necessary hack -- couldn't get above loop to terminate at t >= 0
325 bestpath[0] = psi[1][bestpath[1]]; 333 bestpath[0] = psi[1][bestpath[1]];
326 334
327 unsigned int lastind = 0; 335 int lastind = 0;
328 for (unsigned int i=0; i<T; i++) { 336 for (int i = 0; i < T; i++) {
329 unsigned int step = 128; 337 int step = 128;
330 for (unsigned int j=0; j<step; j++) { 338 for (int j = 0; j < step; j++) {
331 lastind = i*step+j; 339 lastind = i*step+j;
332 beat_period[lastind] = bestpath[i]; 340 beat_period[lastind] = bestpath[i];
333 } 341 }
334 // std::cerr << "bestpath[" << i << "] = " << bestpath[i] << " (used for beat_periods " << i*step << " to " << i*step+step-1 << ")" << std::endl; 342 // std::cerr << "bestpath[" << i << "] = " << bestpath[i] << " (used for beat_periods " << i*step << " to " << i*step+step-1 << ")" << std::endl;
335 } 343 }
336 344
337 //fill in the last values... 345 // fill in the last values...
338 for (unsigned int i=lastind; i<beat_period.size(); i++) { 346 for (int i = lastind; i < int(beat_period.size()); i++) {
339 beat_period[i] = beat_period[lastind]; 347 beat_period[i] = beat_period[lastind];
340 } 348 }
341 349
342 for (unsigned int i = 0; i < beat_period.size(); i++) { 350 for (int i = 0; i < int(beat_period.size()); i++) {
343 tempi.push_back((60. * m_rate / m_increment)/beat_period[i]); 351 tempi.push_back((60. * m_rate / m_increment)/beat_period[i]);
344 } 352 }
345 } 353 }
346 354
347 double 355 double
348 TempoTrackV2::get_max_val(const d_vec_t &df) 356 TempoTrackV2::get_max_val(const d_vec_t &df)
349 { 357 {
350 double maxval = 0.; 358 double maxval = 0.;
351 for (unsigned int i=0; i<df.size(); i++) { 359 int df_len = int(df.size());
360
361 for (int i = 0; i < df_len; i++) {
352 if (maxval < df[i]) { 362 if (maxval < df[i]) {
353 maxval = df[i]; 363 maxval = df[i];
354 } 364 }
355 } 365 }
356 366
360 int 370 int
361 TempoTrackV2::get_max_ind(const d_vec_t &df) 371 TempoTrackV2::get_max_ind(const d_vec_t &df)
362 { 372 {
363 double maxval = 0.; 373 double maxval = 0.;
364 int ind = 0; 374 int ind = 0;
365 for (unsigned int i=0; i<df.size(); i++) { 375 int df_len = int(df.size());
376
377 for (int i = 0; i < df_len; i++) {
366 if (maxval < df[i]) { 378 if (maxval < df[i]) {
367 maxval = df[i]; 379 maxval = df[i];
368 ind = i; 380 ind = i;
369 } 381 }
370 } 382 }
374 386
375 void 387 void
376 TempoTrackV2::normalise_vec(d_vec_t &df) 388 TempoTrackV2::normalise_vec(d_vec_t &df)
377 { 389 {
378 double sum = 0.; 390 double sum = 0.;
379 for (unsigned int i=0; i<df.size(); i++) { 391 int df_len = int(df.size());
392
393 for (int i = 0; i < df_len; i++) {
380 sum += df[i]; 394 sum += df[i];
381 } 395 }
382 396
383 for (unsigned int i=0; i<df.size(); i++) { 397 for (int i = 0; i < df_len; i++) {
384 df[i]/= (sum + EPS); 398 df[i]/= (sum + EPS);
385 } 399 }
386 } 400 }
387 401
388 // MEPD 28/11/12 402 // MEPD 28/11/12
394 const vector<double> &beat_period, 408 const vector<double> &beat_period,
395 vector<double> &beats, double alpha, double tightness) 409 vector<double> &beats, double alpha, double tightness)
396 { 410 {
397 if (df.empty() || beat_period.empty()) return; 411 if (df.empty() || beat_period.empty()) return;
398 412
399 d_vec_t cumscore(df.size()); // store cumulative score 413 int df_len = int(df.size());
400 i_vec_t backlink(df.size()); // backlink (stores best beat locations at each time instant) 414
401 d_vec_t localscore(df.size()); // localscore, for now this is the same as the detection function 415 d_vec_t cumscore(df_len); // store cumulative score
402 416 i_vec_t backlink(df_len); // backlink (stores best beat locations at each time instant)
403 for (unsigned int i=0; i<df.size(); i++) { 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++) {
404 localscore[i] = df[i]; 420 localscore[i] = df[i];
405 backlink[i] = -1; 421 backlink[i] = -1;
406 } 422 }
407 423
408 //double tightness = 4.; 424 //double tightness = 4.;
411 // debug statements that can be removed. 427 // debug statements that can be removed.
412 // std::cerr << "alpha" << alpha << std::endl; 428 // std::cerr << "alpha" << alpha << std::endl;
413 // std::cerr << "tightness" << tightness << std::endl; 429 // std::cerr << "tightness" << tightness << std::endl;
414 430
415 // main loop 431 // main loop
416 for (unsigned int i=0; i<localscore.size(); i++) { 432 for (int i = 0; i < df_len; i++) {
417 433
418 int prange_min = -2*beat_period[i]; 434 int prange_min = -2*beat_period[i];
419 int prange_max = round(-0.5*beat_period[i]); 435 int prange_max = round(-0.5*beat_period[i]);
420 436
421 // transition range 437 // transition range
422 d_vec_t txwt (prange_max - prange_min + 1); 438 int txwt_len = prange_max - prange_min + 1;
423 d_vec_t scorecands (txwt.size()); 439 d_vec_t txwt (txwt_len);
424 440 d_vec_t scorecands (txwt_len);
425 for (unsigned int j=0;j<txwt.size();j++) { 441
442 for (int j = 0; j < txwt_len; j++) {
426 443
427 double mu = static_cast<double> (beat_period[i]); 444 double mu = double(beat_period[i]);
428 txwt[j] = exp( -0.5*pow(tightness * log((round(2*mu)-j)/mu),2)); 445 txwt[j] = exp( -0.5*pow(tightness * log((round(2*mu)-j)/mu),2));
429 446
430 // IF IN THE ALLOWED RANGE, THEN LOOK AT CUMSCORE[I+PRANGE_MIN+J 447 // IF IN THE ALLOWED RANGE, THEN LOOK AT CUMSCORE[I+PRANGE_MIN+J
431 // ELSE LEAVE AT DEFAULT VALUE FROM INITIALISATION: D_VEC_T SCORECANDS (TXWT.SIZE()); 448 // ELSE LEAVE AT DEFAULT VALUE FROM INITIALISATION: D_VEC_T SCORECANDS (TXWT.SIZE());
432 449
433 int cscore_ind = i+prange_min+j; 450 int cscore_ind = i + prange_min + j;
434 if (cscore_ind >= 0) { 451 if (cscore_ind >= 0) {
435 scorecands[j] = txwt[j] * cumscore[cscore_ind]; 452 scorecands[j] = txwt[j] * cumscore[cscore_ind];
436 } 453 }
437 } 454 }
438 455
446 // std::cerr << "backlink[" << i << "] <= " << backlink[i] << std::endl; 463 // std::cerr << "backlink[" << i << "] <= " << backlink[i] << std::endl;
447 } 464 }
448 465
449 // STARTING POINT, I.E. LAST BEAT.. PICK A STRONG POINT IN cumscore VECTOR 466 // STARTING POINT, I.E. LAST BEAT.. PICK A STRONG POINT IN cumscore VECTOR
450 d_vec_t tmp_vec; 467 d_vec_t tmp_vec;
451 for (unsigned int i=cumscore.size() - beat_period[beat_period.size()-1] ; i<cumscore.size(); i++) { 468 for (int i = df_len - beat_period[beat_period.size()-1] ; i < df_len; i++) {
452 tmp_vec.push_back(cumscore[i]); 469 tmp_vec.push_back(cumscore[i]);
453 } 470 }
454 471
455 int startpoint = get_max_ind(tmp_vec) + 472 int startpoint = get_max_ind(tmp_vec) +
456 cumscore.size() - beat_period[beat_period.size()-1] ; 473 df_len - beat_period[beat_period.size()-1] ;
457 474
458 // can happen if no results obtained earlier (e.g. input too short) 475 // can happen if no results obtained earlier (e.g. input too short)
459 if (startpoint >= (int)backlink.size()) { 476 if (startpoint >= int(backlink.size())) {
460 startpoint = backlink.size()-1; 477 startpoint = int(backlink.size()) - 1;
461 } 478 }
462 479
463 // USE BACKLINK TO GET EACH NEW BEAT (TOWARDS THE BEGINNING OF THE FILE) 480 // USE BACKLINK TO GET EACH NEW BEAT (TOWARDS THE BEGINNING OF THE FILE)
464 // BACKTRACKING FROM THE END TO THE BEGINNING.. MAKING SURE NOT TO GO BEFORE SAMPLE 0 481 // BACKTRACKING FROM THE END TO THE BEGINNING.. MAKING SURE NOT TO GO BEFORE SAMPLE 0
465 i_vec_t ibeats; 482 i_vec_t ibeats;
471 if (backlink[b] == b) break; // shouldn't happen... haha 488 if (backlink[b] == b) break; // shouldn't happen... haha
472 ibeats.push_back(backlink[b]); 489 ibeats.push_back(backlink[b]);
473 } 490 }
474 491
475 // REVERSE SEQUENCE OF IBEATS AND STORE AS BEATS 492 // REVERSE SEQUENCE OF IBEATS AND STORE AS BEATS
476 for (unsigned int i=0; i<ibeats.size(); i++) { 493 for (int i = 0; i < int(ibeats.size()); i++) {
477 beats.push_back( static_cast<double>(ibeats[ibeats.size()-i-1]) ); 494 beats.push_back(double(ibeats[ibeats.size() - i - 1]));
478 } 495 }
479 } 496 }
480 497
481 498