annotate src/BTrack.cpp @ 59:ba3fc238ccad

Renamed many variables, functions and arguments so they have more sensible names. Also removed an apparently redundant variable in OnsetDetectionFunction called wframe
author Adam Stark <adamstark@users.noreply.github.com>
date Fri, 24 Jan 2014 21:45:55 +0000
parents f84ccd07e17f
children bf256abf1dd4
rev   line source
adamstark@46 1 //=======================================================================
adamstark@46 2 /** @file BTrack.cpp
adamstark@47 3 * @brief BTrack - a real-time beat tracker
adamstark@46 4 * @author Adam Stark
adamstark@46 5 * @copyright Copyright (C) 2008-2014 Queen Mary University of London
adamstark@46 6 *
adamstark@46 7 * This program is free software: you can redistribute it and/or modify
adamstark@46 8 * it under the terms of the GNU General Public License as published by
adamstark@46 9 * the Free Software Foundation, either version 3 of the License, or
adamstark@46 10 * (at your option) any later version.
adamstark@46 11 *
adamstark@46 12 * This program is distributed in the hope that it will be useful,
adamstark@46 13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
adamstark@46 14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
adamstark@46 15 * GNU General Public License for more details.
adamstark@46 16 *
adamstark@46 17 * You should have received a copy of the GNU General Public License
adamstark@46 18 * along with this program. If not, see <http://www.gnu.org/licenses/>.
adamstark@46 19 */
adamstark@46 20 //=======================================================================
adamstark@46 21
adamstark@46 22 #include <cmath>
adamstark@52 23 #include <algorithm>
adamstark@46 24 #include "BTrack.h"
adamstark@46 25 #include "samplerate.h"
adamstark@46 26
adamstark@55 27 //=======================================================================
adamstark@57 28 BTrack::BTrack() : odf(512,1024,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@55 29 {
adamstark@55 30 initialise(512, 1024);
adamstark@55 31 }
adamstark@46 32
adamstark@51 33 //=======================================================================
adamstark@57 34 BTrack::BTrack(int hopSize_) : odf(hopSize_,2*hopSize_,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@46 35 {
adamstark@57 36 initialise(hopSize_, 2*hopSize_);
adamstark@55 37 }
adamstark@55 38
adamstark@55 39 //=======================================================================
adamstark@57 40 BTrack::BTrack(int hopSize_,int frameSize_) : odf(hopSize_,frameSize_,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@55 41 {
adamstark@57 42 initialise(hopSize_, frameSize_);
adamstark@55 43 }
adamstark@55 44
adamstark@55 45 //=======================================================================
adamstark@55 46 double BTrack::getBeatTimeInSeconds(long frameNumber,int hopSize,int fs)
adamstark@55 47 {
adamstark@55 48 double hop = (double) hopSize;
adamstark@55 49 double samplingFrequency = (double) fs;
adamstark@55 50 double frameNum = (double) frameNumber;
adamstark@55 51
adamstark@55 52 return ((hop / samplingFrequency) * frameNum);
adamstark@55 53 }
adamstark@55 54
adamstark@55 55 //=======================================================================
adamstark@55 56 double BTrack::getBeatTimeInSeconds(int frameNumber,int hopSize,int fs)
adamstark@55 57 {
adamstark@55 58 long frameNum = (long) frameNumber;
adamstark@55 59
adamstark@55 60 return getBeatTimeInSeconds(frameNum, hopSize, fs);
adamstark@55 61 }
adamstark@55 62
adamstark@55 63
adamstark@55 64
adamstark@55 65 //=======================================================================
adamstark@57 66 void BTrack::initialise(int hopSize_, int frameSize_)
adamstark@55 67 {
adamstark@55 68 double rayparam = 43;
adamstark@54 69 double pi = 3.14159265;
adamstark@46 70
adamstark@46 71
adamstark@46 72 // initialise parameters
adamstark@46 73 tightness = 5;
adamstark@46 74 alpha = 0.9;
adamstark@46 75 tempo = 120;
adamstark@58 76 estimatedTempo = 120.0;
adamstark@59 77 tempoToLagFactor = 60.*44100./512.;
adamstark@46 78
adamstark@46 79 m0 = 10;
adamstark@58 80 beatCounter = -1;
adamstark@46 81
adamstark@57 82 beatDueInFrame = false;
adamstark@46 83
adamstark@58 84
adamstark@46 85 // create rayleigh weighting vector
adamstark@46 86 for (int n = 0;n < 128;n++)
adamstark@46 87 {
adamstark@58 88 weightingVector[n] = ((double) n / pow(rayparam,2)) * exp((-1*pow((double)-n,2)) / (2*pow(rayparam,2)));
adamstark@46 89 }
adamstark@46 90
adamstark@46 91 // initialise prev_delta
adamstark@46 92 for (int i = 0;i < 41;i++)
adamstark@46 93 {
adamstark@58 94 prevDelta[i] = 1;
adamstark@46 95 }
adamstark@46 96
adamstark@54 97 double t_mu = 41/2;
adamstark@54 98 double m_sig;
adamstark@54 99 double x;
adamstark@46 100 // create tempo transition matrix
adamstark@46 101 m_sig = 41/8;
adamstark@46 102 for (int i = 0;i < 41;i++)
adamstark@46 103 {
adamstark@46 104 for (int j = 0;j < 41;j++)
adamstark@46 105 {
adamstark@46 106 x = j+1;
adamstark@46 107 t_mu = i+1;
adamstark@58 108 tempoTransitionMatrix[i][j] = (1 / (m_sig * sqrt(2*pi))) * exp( (-1*pow((x-t_mu),2)) / (2*pow(m_sig,2)) );
adamstark@46 109 }
adamstark@55 110 }
adamstark@46 111
adamstark@46 112 // tempo is not fixed
adamstark@58 113 tempoFixed = false;
adamstark@58 114
adamstark@58 115 // initialise latest cumulative score value
adamstark@58 116 // in case it is requested before any processing takes place
adamstark@58 117 latestCumulativeScoreValue = 0;
adamstark@55 118
adamstark@55 119 // initialise algorithm given the hopsize
adamstark@57 120 setHopSize(hopSize_);
adamstark@46 121 }
adamstark@46 122
adamstark@51 123 //=======================================================================
adamstark@57 124 void BTrack::setHopSize(int hopSize_)
adamstark@46 125 {
adamstark@57 126 hopSize = hopSize_;
adamstark@58 127 onsetDFBufferSize = (512*512)/hopSize; // calculate df buffer size
adamstark@46 128
adamstark@57 129 beatPeriod = round(60/((((double) hopSize)/44100)*tempo));
adamstark@46 130
adamstark@58 131 onsetDF = new double[onsetDFBufferSize]; // create df_buffer
adamstark@58 132 cumulativeScore = new double[onsetDFBufferSize]; // create cumscore
adamstark@46 133
adamstark@46 134
adamstark@46 135 // initialise df_buffer to zeros
adamstark@58 136 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@46 137 {
adamstark@58 138 onsetDF[i] = 0;
adamstark@58 139 cumulativeScore[i] = 0;
adamstark@46 140
adamstark@46 141
adamstark@57 142 if ((i % ((int) round(beatPeriod))) == 0)
adamstark@46 143 {
adamstark@58 144 onsetDF[i] = 1;
adamstark@46 145 }
adamstark@46 146 }
adamstark@46 147 }
adamstark@46 148
adamstark@51 149 //=======================================================================
adamstark@57 150 bool BTrack::beatDueInCurrentFrame()
adamstark@57 151 {
adamstark@57 152 return beatDueInFrame;
adamstark@57 153 }
adamstark@57 154
adamstark@57 155 //=======================================================================
adamstark@57 156 int BTrack::getHopSize()
adamstark@57 157 {
adamstark@57 158 return hopSize;
adamstark@57 159 }
adamstark@57 160
adamstark@57 161 //=======================================================================
adamstark@58 162 double BTrack::getLatestCumulativeScoreValue()
adamstark@58 163 {
adamstark@58 164 return latestCumulativeScoreValue;
adamstark@58 165 }
adamstark@58 166
adamstark@58 167 //=======================================================================
adamstark@55 168 void BTrack::processAudioFrame(double *frame)
adamstark@55 169 {
adamstark@55 170 // calculate the onset detection function sample for the frame
adamstark@59 171 double sample = odf.calculateOnsetDetectionFunctionSample(frame);
adamstark@55 172
adamstark@56 173
adamstark@55 174
adamstark@55 175 // process the new onset detection function sample in the beat tracking algorithm
adamstark@55 176 processOnsetDetectionFunctionSample(sample);
adamstark@55 177 }
adamstark@55 178
adamstark@55 179 //=======================================================================
adamstark@55 180 void BTrack::processOnsetDetectionFunctionSample(double newSample)
adamstark@56 181 {
adamstark@56 182 // we need to ensure that the onset
adamstark@56 183 // detection function sample is positive
adamstark@56 184 newSample = fabs(newSample);
adamstark@56 185
adamstark@56 186 // add a tiny constant to the sample to stop it from ever going
adamstark@56 187 // to zero. this is to avoid problems further down the line
adamstark@56 188 newSample = newSample + 0.0001;
adamstark@56 189
adamstark@46 190 m0--;
adamstark@58 191 beatCounter--;
adamstark@57 192 beatDueInFrame = false;
adamstark@46 193
adamstark@46 194 // move all samples back one step
adamstark@58 195 for (int i=0;i < (onsetDFBufferSize-1);i++)
adamstark@46 196 {
adamstark@58 197 onsetDF[i] = onsetDF[i+1];
adamstark@46 198 }
adamstark@46 199
adamstark@46 200 // add new sample at the end
adamstark@58 201 onsetDF[onsetDFBufferSize-1] = newSample;
adamstark@46 202
adamstark@46 203 // update cumulative score
adamstark@57 204 updateCumulativeScore(newSample);
adamstark@46 205
adamstark@46 206 // if we are halfway between beats
adamstark@46 207 if (m0 == 0)
adamstark@46 208 {
adamstark@57 209 predictBeat();
adamstark@46 210 }
adamstark@46 211
adamstark@46 212 // if we are at a beat
adamstark@58 213 if (beatCounter == 0)
adamstark@46 214 {
adamstark@57 215 beatDueInFrame = true; // indicate a beat should be output
adamstark@46 216
adamstark@46 217 // recalculate the tempo
adamstark@57 218 resampleOnsetDetectionFunction();
adamstark@57 219 calculateTempo();
adamstark@46 220 }
adamstark@46 221 }
adamstark@46 222
adamstark@51 223 //=======================================================================
adamstark@57 224 void BTrack::setTempo(double tempo)
adamstark@46 225 {
adamstark@46 226
adamstark@46 227 /////////// TEMPO INDICATION RESET //////////////////
adamstark@46 228
adamstark@46 229 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@46 230 while (tempo > 160)
adamstark@46 231 {
adamstark@46 232 tempo = tempo/2;
adamstark@46 233 }
adamstark@46 234
adamstark@46 235 while (tempo < 80)
adamstark@46 236 {
adamstark@46 237 tempo = tempo * 2;
adamstark@46 238 }
adamstark@46 239
adamstark@46 240 // convert tempo from bpm value to integer index of tempo probability
adamstark@46 241 int tempo_index = (int) round((tempo - 80)/2);
adamstark@46 242
adamstark@46 243 // now set previous tempo observations to zero
adamstark@46 244 for (int i=0;i < 41;i++)
adamstark@46 245 {
adamstark@58 246 prevDelta[i] = 0;
adamstark@46 247 }
adamstark@46 248
adamstark@46 249 // set desired tempo index to 1
adamstark@58 250 prevDelta[tempo_index] = 1;
adamstark@46 251
adamstark@46 252
adamstark@46 253 /////////// CUMULATIVE SCORE ARTIFICAL TEMPO UPDATE //////////////////
adamstark@46 254
adamstark@46 255 // calculate new beat period
adamstark@57 256 int new_bperiod = (int) round(60/((((double) hopSize)/44100)*tempo));
adamstark@46 257
adamstark@46 258 int bcounter = 1;
adamstark@46 259 // initialise df_buffer to zeros
adamstark@58 260 for (int i = (onsetDFBufferSize-1);i >= 0;i--)
adamstark@46 261 {
adamstark@46 262 if (bcounter == 1)
adamstark@46 263 {
adamstark@58 264 cumulativeScore[i] = 150;
adamstark@58 265 onsetDF[i] = 150;
adamstark@46 266 }
adamstark@46 267 else
adamstark@46 268 {
adamstark@58 269 cumulativeScore[i] = 10;
adamstark@58 270 onsetDF[i] = 10;
adamstark@46 271 }
adamstark@46 272
adamstark@46 273 bcounter++;
adamstark@46 274
adamstark@46 275 if (bcounter > new_bperiod)
adamstark@46 276 {
adamstark@46 277 bcounter = 1;
adamstark@46 278 }
adamstark@46 279 }
adamstark@46 280
adamstark@46 281 /////////// INDICATE THAT THIS IS A BEAT //////////////////
adamstark@46 282
adamstark@46 283 // beat is now
adamstark@58 284 beatCounter = 0;
adamstark@46 285
adamstark@46 286 // offbeat is half of new beat period away
adamstark@54 287 m0 = (int) round(((double) new_bperiod)/2);
adamstark@46 288 }
adamstark@46 289
adamstark@51 290 //=======================================================================
adamstark@57 291 void BTrack::fixTempo(double tempo)
adamstark@46 292 {
adamstark@46 293 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@46 294 while (tempo > 160)
adamstark@46 295 {
adamstark@46 296 tempo = tempo/2;
adamstark@46 297 }
adamstark@46 298
adamstark@46 299 while (tempo < 80)
adamstark@46 300 {
adamstark@46 301 tempo = tempo * 2;
adamstark@46 302 }
adamstark@46 303
adamstark@46 304 // convert tempo from bpm value to integer index of tempo probability
adamstark@46 305 int tempo_index = (int) round((tempo - 80)/2);
adamstark@46 306
adamstark@46 307 // now set previous fixed previous tempo observation values to zero
adamstark@46 308 for (int i=0;i < 41;i++)
adamstark@46 309 {
adamstark@58 310 prevDeltaFixed[i] = 0;
adamstark@46 311 }
adamstark@46 312
adamstark@46 313 // set desired tempo index to 1
adamstark@58 314 prevDeltaFixed[tempo_index] = 1;
adamstark@46 315
adamstark@46 316 // set the tempo fix flag
adamstark@58 317 tempoFixed = true;
adamstark@46 318 }
adamstark@46 319
adamstark@51 320 //=======================================================================
adamstark@57 321 void BTrack::doNotFixTempo()
adamstark@46 322 {
adamstark@46 323 // set the tempo fix flag
adamstark@58 324 tempoFixed = false;
adamstark@46 325 }
adamstark@46 326
adamstark@51 327 //=======================================================================
adamstark@57 328 void BTrack::resampleOnsetDetectionFunction()
adamstark@46 329 {
adamstark@46 330 float output[512];
adamstark@58 331 float input[onsetDFBufferSize];
adamstark@54 332
adamstark@58 333 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@54 334 {
adamstark@58 335 input[i] = (float) onsetDF[i];
adamstark@54 336 }
adamstark@46 337
adamstark@58 338 double src_ratio = 512.0/((double) onsetDFBufferSize);
adamstark@58 339 int BUFFER_LEN = onsetDFBufferSize;
adamstark@46 340 int output_len;
adamstark@46 341 SRC_DATA src_data ;
adamstark@46 342
adamstark@46 343 //output_len = (int) floor (((double) BUFFER_LEN) * src_ratio) ;
adamstark@46 344 output_len = 512;
adamstark@46 345
adamstark@54 346 src_data.data_in = input;
adamstark@46 347 src_data.input_frames = BUFFER_LEN;
adamstark@46 348
adamstark@46 349 src_data.src_ratio = src_ratio;
adamstark@46 350
adamstark@46 351 src_data.data_out = output;
adamstark@46 352 src_data.output_frames = output_len;
adamstark@46 353
adamstark@46 354 src_simple (&src_data, SRC_SINC_BEST_QUALITY, 1);
adamstark@46 355
adamstark@46 356 for (int i = 0;i < output_len;i++)
adamstark@46 357 {
adamstark@58 358 resampledOnsetDF[i] = (double) src_data.data_out[i];
adamstark@46 359 }
adamstark@46 360 }
adamstark@46 361
adamstark@51 362 //=======================================================================
adamstark@57 363 void BTrack::calculateTempo()
adamstark@46 364 {
adamstark@46 365 // adaptive threshold on input
adamstark@58 366 adaptiveThreshold(resampledOnsetDF,512);
adamstark@46 367
adamstark@46 368 // calculate auto-correlation function of detection function
adamstark@58 369 calculateBalancedACF(resampledOnsetDF);
adamstark@46 370
adamstark@46 371 // calculate output of comb filterbank
adamstark@57 372 calculateOutputOfCombFilterBank();
adamstark@46 373
adamstark@46 374
adamstark@46 375 // adaptive threshold on rcf
adamstark@58 376 adaptiveThreshold(combFilterBankOutput,128);
adamstark@46 377
adamstark@46 378
adamstark@46 379 int t_index;
adamstark@46 380 int t_index2;
adamstark@59 381 // calculate tempo observation vector from beat period observation vector
adamstark@46 382 for (int i = 0;i < 41;i++)
adamstark@46 383 {
adamstark@59 384 t_index = (int) round(tempoToLagFactor / ((double) ((2*i)+80)));
adamstark@59 385 t_index2 = (int) round(tempoToLagFactor / ((double) ((4*i)+160)));
adamstark@46 386
adamstark@46 387
adamstark@58 388 tempoObservationVector[i] = combFilterBankOutput[t_index-1] + combFilterBankOutput[t_index2-1];
adamstark@46 389 }
adamstark@46 390
adamstark@46 391
adamstark@54 392 double maxval;
adamstark@54 393 double maxind;
adamstark@54 394 double curval;
adamstark@46 395
adamstark@46 396 // if tempo is fixed then always use a fixed set of tempi as the previous observation probability function
adamstark@58 397 if (tempoFixed)
adamstark@46 398 {
adamstark@46 399 for (int k = 0;k < 41;k++)
adamstark@46 400 {
adamstark@58 401 prevDelta[k] = prevDeltaFixed[k];
adamstark@46 402 }
adamstark@46 403 }
adamstark@46 404
adamstark@46 405 for (int j=0;j < 41;j++)
adamstark@46 406 {
adamstark@46 407 maxval = -1;
adamstark@46 408 for (int i = 0;i < 41;i++)
adamstark@46 409 {
adamstark@58 410 curval = prevDelta[i]*tempoTransitionMatrix[i][j];
adamstark@46 411
adamstark@46 412 if (curval > maxval)
adamstark@46 413 {
adamstark@46 414 maxval = curval;
adamstark@46 415 }
adamstark@46 416 }
adamstark@46 417
adamstark@58 418 delta[j] = maxval*tempoObservationVector[j];
adamstark@46 419 }
adamstark@46 420
adamstark@46 421
adamstark@57 422 normaliseArray(delta,41);
adamstark@46 423
adamstark@46 424 maxind = -1;
adamstark@46 425 maxval = -1;
adamstark@46 426
adamstark@46 427 for (int j=0;j < 41;j++)
adamstark@46 428 {
adamstark@46 429 if (delta[j] > maxval)
adamstark@46 430 {
adamstark@46 431 maxval = delta[j];
adamstark@46 432 maxind = j;
adamstark@46 433 }
adamstark@46 434
adamstark@58 435 prevDelta[j] = delta[j];
adamstark@46 436 }
adamstark@46 437
adamstark@57 438 beatPeriod = round((60.0*44100.0)/(((2*maxind)+80)*((double) hopSize)));
adamstark@46 439
adamstark@57 440 if (beatPeriod > 0)
adamstark@46 441 {
adamstark@58 442 estimatedTempo = 60.0/((((double) hopSize) / 44100.0)*beatPeriod);
adamstark@46 443 }
adamstark@46 444 }
adamstark@46 445
adamstark@51 446 //=======================================================================
adamstark@57 447 void BTrack::adaptiveThreshold(double *x,int N)
adamstark@46 448 {
adamstark@46 449 int i = 0;
adamstark@46 450 int k,t = 0;
adamstark@54 451 double x_thresh[N];
adamstark@46 452
adamstark@46 453 int p_post = 7;
adamstark@46 454 int p_pre = 8;
adamstark@46 455
adamstark@52 456 t = std::min(N,p_post); // what is smaller, p_post of df size. This is to avoid accessing outside of arrays
adamstark@46 457
adamstark@46 458 // find threshold for first 't' samples, where a full average cannot be computed yet
adamstark@46 459 for (i = 0;i <= t;i++)
adamstark@46 460 {
adamstark@52 461 k = std::min((i+p_pre),N);
adamstark@57 462 x_thresh[i] = calculateMeanOfArray(x,1,k);
adamstark@46 463 }
adamstark@46 464 // find threshold for bulk of samples across a moving average from [i-p_pre,i+p_post]
adamstark@46 465 for (i = t+1;i < N-p_post;i++)
adamstark@46 466 {
adamstark@57 467 x_thresh[i] = calculateMeanOfArray(x,i-p_pre,i+p_post);
adamstark@46 468 }
adamstark@46 469 // for last few samples calculate threshold, again, not enough samples to do as above
adamstark@46 470 for (i = N-p_post;i < N;i++)
adamstark@46 471 {
adamstark@52 472 k = std::max((i-p_post),1);
adamstark@57 473 x_thresh[i] = calculateMeanOfArray(x,k,N);
adamstark@46 474 }
adamstark@46 475
adamstark@46 476 // subtract the threshold from the detection function and check that it is not less than 0
adamstark@46 477 for (i = 0;i < N;i++)
adamstark@46 478 {
adamstark@46 479 x[i] = x[i] - x_thresh[i];
adamstark@46 480 if (x[i] < 0)
adamstark@46 481 {
adamstark@46 482 x[i] = 0;
adamstark@46 483 }
adamstark@46 484 }
adamstark@46 485 }
adamstark@46 486
adamstark@51 487 //=======================================================================
adamstark@57 488 void BTrack::calculateOutputOfCombFilterBank()
adamstark@46 489 {
adamstark@46 490 int numelem;
adamstark@46 491
adamstark@46 492 for (int i = 0;i < 128;i++)
adamstark@46 493 {
adamstark@58 494 combFilterBankOutput[i] = 0;
adamstark@46 495 }
adamstark@46 496
adamstark@46 497 numelem = 4;
adamstark@46 498
adamstark@46 499 for (int i = 2;i <= 127;i++) // max beat period
adamstark@46 500 {
adamstark@46 501 for (int a = 1;a <= numelem;a++) // number of comb elements
adamstark@46 502 {
adamstark@46 503 for (int b = 1-a;b <= a-1;b++) // general state using normalisation of comb elements
adamstark@46 504 {
adamstark@58 505 combFilterBankOutput[i-1] = combFilterBankOutput[i-1] + (acf[(a*i+b)-1]*weightingVector[i-1])/(2*a-1); // calculate value for comb filter row
adamstark@46 506 }
adamstark@46 507 }
adamstark@46 508 }
adamstark@46 509 }
adamstark@46 510
adamstark@51 511 //=======================================================================
adamstark@57 512 void BTrack::calculateBalancedACF(double *df_thresh)
adamstark@46 513 {
adamstark@46 514 int l, n = 0;
adamstark@54 515 double sum, tmp;
adamstark@46 516
adamstark@46 517 // for l lags from 0-511
adamstark@46 518 for (l = 0;l < 512;l++)
adamstark@46 519 {
adamstark@46 520 sum = 0;
adamstark@46 521
adamstark@46 522 // for n samples from 0 - (512-lag)
adamstark@46 523 for (n = 0;n < (512-l);n++)
adamstark@46 524 {
adamstark@46 525 tmp = df_thresh[n] * df_thresh[n+l]; // multiply current sample n by sample (n+l)
adamstark@46 526 sum = sum + tmp; // add to sum
adamstark@46 527 }
adamstark@46 528
adamstark@46 529 acf[l] = sum / (512-l); // weight by number of mults and add to acf buffer
adamstark@46 530 }
adamstark@46 531 }
adamstark@46 532
adamstark@51 533 //=======================================================================
adamstark@59 534 double BTrack::calculateMeanOfArray(double *array,int startIndex,int endIndex)
adamstark@46 535 {
adamstark@46 536 int i;
adamstark@47 537 double sum = 0;
adamstark@47 538
adamstark@59 539 int length = endIndex - startIndex;
adamstark@46 540
adamstark@46 541 // find sum
adamstark@59 542 for (i = startIndex;i < endIndex;i++)
adamstark@46 543 {
adamstark@46 544 sum = sum + array[i];
adamstark@46 545 }
adamstark@46 546
adamstark@47 547 if (length > 0)
adamstark@47 548 {
adamstark@47 549 return sum / length; // average and return
adamstark@47 550 }
adamstark@47 551 else
adamstark@47 552 {
adamstark@47 553 return 0;
adamstark@47 554 }
adamstark@46 555 }
adamstark@46 556
adamstark@51 557 //=======================================================================
adamstark@57 558 void BTrack::normaliseArray(double *array,int N)
adamstark@46 559 {
adamstark@46 560 double sum = 0;
adamstark@46 561
adamstark@46 562 for (int i = 0;i < N;i++)
adamstark@46 563 {
adamstark@46 564 if (array[i] > 0)
adamstark@46 565 {
adamstark@46 566 sum = sum + array[i];
adamstark@46 567 }
adamstark@46 568 }
adamstark@46 569
adamstark@46 570 if (sum > 0)
adamstark@46 571 {
adamstark@46 572 for (int i = 0;i < N;i++)
adamstark@46 573 {
adamstark@46 574 array[i] = array[i] / sum;
adamstark@46 575 }
adamstark@46 576 }
adamstark@46 577 }
adamstark@46 578
adamstark@51 579 //=======================================================================
adamstark@59 580 void BTrack::updateCumulativeScore(double odfSample)
adamstark@46 581 {
adamstark@46 582 int start, end, winsize;
adamstark@54 583 double max;
adamstark@46 584
adamstark@58 585 start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@58 586 end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@46 587 winsize = end-start+1;
adamstark@46 588
adamstark@54 589 double w1[winsize];
adamstark@57 590 double v = -2*beatPeriod;
adamstark@54 591 double wcumscore;
adamstark@46 592
adamstark@46 593
adamstark@46 594 // create window
adamstark@46 595 for (int i = 0;i < winsize;i++)
adamstark@46 596 {
adamstark@57 597 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@46 598 v = v+1;
adamstark@46 599 }
adamstark@46 600
adamstark@46 601 // calculate new cumulative score value
adamstark@46 602 max = 0;
adamstark@46 603 int n = 0;
adamstark@46 604 for (int i=start;i <= end;i++)
adamstark@46 605 {
adamstark@58 606 wcumscore = cumulativeScore[i]*w1[n];
adamstark@46 607
adamstark@46 608 if (wcumscore > max)
adamstark@46 609 {
adamstark@46 610 max = wcumscore;
adamstark@46 611 }
adamstark@46 612 n++;
adamstark@46 613 }
adamstark@46 614
adamstark@46 615
adamstark@46 616 // shift cumulative score back one
adamstark@58 617 for (int i = 0;i < (onsetDFBufferSize-1);i++)
adamstark@46 618 {
adamstark@58 619 cumulativeScore[i] = cumulativeScore[i+1];
adamstark@46 620 }
adamstark@46 621
adamstark@46 622 // add new value to cumulative score
adamstark@59 623 cumulativeScore[onsetDFBufferSize-1] = ((1-alpha)*odfSample) + (alpha*max);
adamstark@46 624
adamstark@58 625 latestCumulativeScoreValue = cumulativeScore[onsetDFBufferSize-1];
adamstark@58 626
adamstark@46 627 }
adamstark@46 628
adamstark@51 629 //=======================================================================
adamstark@57 630 void BTrack::predictBeat()
adamstark@46 631 {
adamstark@58 632 int windowSize = (int) beatPeriod;
adamstark@58 633 double futureCumulativeScore[onsetDFBufferSize + windowSize];
adamstark@58 634 double w2[windowSize];
adamstark@46 635 // copy cumscore to first part of fcumscore
adamstark@58 636 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@46 637 {
adamstark@58 638 futureCumulativeScore[i] = cumulativeScore[i];
adamstark@46 639 }
adamstark@46 640
adamstark@46 641 // create future window
adamstark@54 642 double v = 1;
adamstark@58 643 for (int i = 0;i < windowSize;i++)
adamstark@46 644 {
adamstark@57 645 w2[i] = exp((-1*pow((v - (beatPeriod/2)),2)) / (2*pow((beatPeriod/2) ,2)));
adamstark@46 646 v++;
adamstark@46 647 }
adamstark@46 648
adamstark@46 649 // create past window
adamstark@57 650 v = -2*beatPeriod;
adamstark@58 651 int start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@58 652 int end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@46 653 int pastwinsize = end-start+1;
adamstark@54 654 double w1[pastwinsize];
adamstark@46 655
adamstark@46 656 for (int i = 0;i < pastwinsize;i++)
adamstark@46 657 {
adamstark@57 658 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@46 659 v = v+1;
adamstark@46 660 }
adamstark@46 661
adamstark@46 662
adamstark@46 663
adamstark@46 664 // calculate future cumulative score
adamstark@54 665 double max;
adamstark@46 666 int n;
adamstark@54 667 double wcumscore;
adamstark@58 668 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@46 669 {
adamstark@57 670 start = i - round(2*beatPeriod);
adamstark@57 671 end = i - round(beatPeriod/2);
adamstark@46 672
adamstark@46 673 max = 0;
adamstark@46 674 n = 0;
adamstark@46 675 for (int k=start;k <= end;k++)
adamstark@46 676 {
adamstark@58 677 wcumscore = futureCumulativeScore[k]*w1[n];
adamstark@46 678
adamstark@46 679 if (wcumscore > max)
adamstark@46 680 {
adamstark@46 681 max = wcumscore;
adamstark@46 682 }
adamstark@46 683 n++;
adamstark@46 684 }
adamstark@46 685
adamstark@58 686 futureCumulativeScore[i] = max;
adamstark@46 687 }
adamstark@46 688
adamstark@46 689
adamstark@46 690 // predict beat
adamstark@46 691 max = 0;
adamstark@46 692 n = 0;
adamstark@46 693
adamstark@58 694 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@46 695 {
adamstark@58 696 wcumscore = futureCumulativeScore[i]*w2[n];
adamstark@46 697
adamstark@46 698 if (wcumscore > max)
adamstark@46 699 {
adamstark@46 700 max = wcumscore;
adamstark@58 701 beatCounter = n;
adamstark@46 702 }
adamstark@46 703
adamstark@46 704 n++;
adamstark@46 705 }
adamstark@46 706
adamstark@46 707 // set next prediction time
adamstark@58 708 m0 = beatCounter+round(beatPeriod/2);
adamstark@46 709
adamstark@46 710
adamstark@46 711 }