annotate src/BTrack.cpp @ 63:1395895f6cdf

Replaced the pointers to arrays in BTrack with vectors
author Adam Stark <adamstark@users.noreply.github.com>
date Mon, 27 Jan 2014 23:54:18 +0000
parents bf256abf1dd4
children 105999275c2e
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@63 130
adamstark@63 131 // set size of onset detection function buffer
adamstark@63 132 onsetDF.resize(onsetDFBufferSize);
adamstark@63 133
adamstark@63 134 // set size of cumulative score buffer
adamstark@63 135 cumulativeScore.resize(onsetDFBufferSize);
adamstark@46 136
adamstark@46 137 // initialise df_buffer to zeros
adamstark@58 138 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@46 139 {
adamstark@58 140 onsetDF[i] = 0;
adamstark@58 141 cumulativeScore[i] = 0;
adamstark@46 142
adamstark@46 143
adamstark@57 144 if ((i % ((int) round(beatPeriod))) == 0)
adamstark@46 145 {
adamstark@58 146 onsetDF[i] = 1;
adamstark@46 147 }
adamstark@46 148 }
adamstark@46 149 }
adamstark@46 150
adamstark@51 151 //=======================================================================
adamstark@57 152 bool BTrack::beatDueInCurrentFrame()
adamstark@57 153 {
adamstark@57 154 return beatDueInFrame;
adamstark@57 155 }
adamstark@57 156
adamstark@57 157 //=======================================================================
adamstark@57 158 int BTrack::getHopSize()
adamstark@57 159 {
adamstark@57 160 return hopSize;
adamstark@57 161 }
adamstark@57 162
adamstark@57 163 //=======================================================================
adamstark@58 164 double BTrack::getLatestCumulativeScoreValue()
adamstark@58 165 {
adamstark@58 166 return latestCumulativeScoreValue;
adamstark@58 167 }
adamstark@58 168
adamstark@58 169 //=======================================================================
adamstark@55 170 void BTrack::processAudioFrame(double *frame)
adamstark@55 171 {
adamstark@55 172 // calculate the onset detection function sample for the frame
adamstark@59 173 double sample = odf.calculateOnsetDetectionFunctionSample(frame);
adamstark@55 174
adamstark@56 175
adamstark@55 176
adamstark@55 177 // process the new onset detection function sample in the beat tracking algorithm
adamstark@55 178 processOnsetDetectionFunctionSample(sample);
adamstark@55 179 }
adamstark@55 180
adamstark@55 181 //=======================================================================
adamstark@55 182 void BTrack::processOnsetDetectionFunctionSample(double newSample)
adamstark@56 183 {
adamstark@56 184 // we need to ensure that the onset
adamstark@56 185 // detection function sample is positive
adamstark@56 186 newSample = fabs(newSample);
adamstark@56 187
adamstark@56 188 // add a tiny constant to the sample to stop it from ever going
adamstark@56 189 // to zero. this is to avoid problems further down the line
adamstark@56 190 newSample = newSample + 0.0001;
adamstark@56 191
adamstark@46 192 m0--;
adamstark@58 193 beatCounter--;
adamstark@57 194 beatDueInFrame = false;
adamstark@46 195
adamstark@46 196 // move all samples back one step
adamstark@58 197 for (int i=0;i < (onsetDFBufferSize-1);i++)
adamstark@46 198 {
adamstark@58 199 onsetDF[i] = onsetDF[i+1];
adamstark@46 200 }
adamstark@46 201
adamstark@46 202 // add new sample at the end
adamstark@58 203 onsetDF[onsetDFBufferSize-1] = newSample;
adamstark@46 204
adamstark@46 205 // update cumulative score
adamstark@57 206 updateCumulativeScore(newSample);
adamstark@46 207
adamstark@46 208 // if we are halfway between beats
adamstark@46 209 if (m0 == 0)
adamstark@46 210 {
adamstark@57 211 predictBeat();
adamstark@46 212 }
adamstark@46 213
adamstark@46 214 // if we are at a beat
adamstark@58 215 if (beatCounter == 0)
adamstark@46 216 {
adamstark@57 217 beatDueInFrame = true; // indicate a beat should be output
adamstark@46 218
adamstark@46 219 // recalculate the tempo
adamstark@57 220 resampleOnsetDetectionFunction();
adamstark@57 221 calculateTempo();
adamstark@46 222 }
adamstark@46 223 }
adamstark@46 224
adamstark@51 225 //=======================================================================
adamstark@57 226 void BTrack::setTempo(double tempo)
adamstark@46 227 {
adamstark@46 228
adamstark@46 229 /////////// TEMPO INDICATION RESET //////////////////
adamstark@46 230
adamstark@46 231 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@46 232 while (tempo > 160)
adamstark@46 233 {
adamstark@46 234 tempo = tempo/2;
adamstark@46 235 }
adamstark@46 236
adamstark@46 237 while (tempo < 80)
adamstark@46 238 {
adamstark@46 239 tempo = tempo * 2;
adamstark@46 240 }
adamstark@46 241
adamstark@46 242 // convert tempo from bpm value to integer index of tempo probability
adamstark@46 243 int tempo_index = (int) round((tempo - 80)/2);
adamstark@46 244
adamstark@46 245 // now set previous tempo observations to zero
adamstark@46 246 for (int i=0;i < 41;i++)
adamstark@46 247 {
adamstark@58 248 prevDelta[i] = 0;
adamstark@46 249 }
adamstark@46 250
adamstark@46 251 // set desired tempo index to 1
adamstark@58 252 prevDelta[tempo_index] = 1;
adamstark@46 253
adamstark@46 254
adamstark@46 255 /////////// CUMULATIVE SCORE ARTIFICAL TEMPO UPDATE //////////////////
adamstark@46 256
adamstark@46 257 // calculate new beat period
adamstark@57 258 int new_bperiod = (int) round(60/((((double) hopSize)/44100)*tempo));
adamstark@46 259
adamstark@46 260 int bcounter = 1;
adamstark@46 261 // initialise df_buffer to zeros
adamstark@58 262 for (int i = (onsetDFBufferSize-1);i >= 0;i--)
adamstark@46 263 {
adamstark@46 264 if (bcounter == 1)
adamstark@46 265 {
adamstark@58 266 cumulativeScore[i] = 150;
adamstark@58 267 onsetDF[i] = 150;
adamstark@46 268 }
adamstark@46 269 else
adamstark@46 270 {
adamstark@58 271 cumulativeScore[i] = 10;
adamstark@58 272 onsetDF[i] = 10;
adamstark@46 273 }
adamstark@46 274
adamstark@46 275 bcounter++;
adamstark@46 276
adamstark@46 277 if (bcounter > new_bperiod)
adamstark@46 278 {
adamstark@46 279 bcounter = 1;
adamstark@46 280 }
adamstark@46 281 }
adamstark@46 282
adamstark@46 283 /////////// INDICATE THAT THIS IS A BEAT //////////////////
adamstark@46 284
adamstark@46 285 // beat is now
adamstark@58 286 beatCounter = 0;
adamstark@46 287
adamstark@46 288 // offbeat is half of new beat period away
adamstark@54 289 m0 = (int) round(((double) new_bperiod)/2);
adamstark@46 290 }
adamstark@46 291
adamstark@51 292 //=======================================================================
adamstark@57 293 void BTrack::fixTempo(double tempo)
adamstark@46 294 {
adamstark@46 295 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@46 296 while (tempo > 160)
adamstark@46 297 {
adamstark@46 298 tempo = tempo/2;
adamstark@46 299 }
adamstark@46 300
adamstark@46 301 while (tempo < 80)
adamstark@46 302 {
adamstark@46 303 tempo = tempo * 2;
adamstark@46 304 }
adamstark@46 305
adamstark@46 306 // convert tempo from bpm value to integer index of tempo probability
adamstark@46 307 int tempo_index = (int) round((tempo - 80)/2);
adamstark@46 308
adamstark@46 309 // now set previous fixed previous tempo observation values to zero
adamstark@46 310 for (int i=0;i < 41;i++)
adamstark@46 311 {
adamstark@58 312 prevDeltaFixed[i] = 0;
adamstark@46 313 }
adamstark@46 314
adamstark@46 315 // set desired tempo index to 1
adamstark@58 316 prevDeltaFixed[tempo_index] = 1;
adamstark@46 317
adamstark@46 318 // set the tempo fix flag
adamstark@58 319 tempoFixed = true;
adamstark@46 320 }
adamstark@46 321
adamstark@51 322 //=======================================================================
adamstark@57 323 void BTrack::doNotFixTempo()
adamstark@46 324 {
adamstark@46 325 // set the tempo fix flag
adamstark@58 326 tempoFixed = false;
adamstark@46 327 }
adamstark@46 328
adamstark@51 329 //=======================================================================
adamstark@57 330 void BTrack::resampleOnsetDetectionFunction()
adamstark@46 331 {
adamstark@46 332 float output[512];
adamstark@58 333 float input[onsetDFBufferSize];
adamstark@54 334
adamstark@58 335 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@54 336 {
adamstark@58 337 input[i] = (float) onsetDF[i];
adamstark@54 338 }
adamstark@46 339
adamstark@58 340 double src_ratio = 512.0/((double) onsetDFBufferSize);
adamstark@58 341 int BUFFER_LEN = onsetDFBufferSize;
adamstark@46 342 int output_len;
adamstark@46 343 SRC_DATA src_data ;
adamstark@46 344
adamstark@46 345 //output_len = (int) floor (((double) BUFFER_LEN) * src_ratio) ;
adamstark@46 346 output_len = 512;
adamstark@46 347
adamstark@54 348 src_data.data_in = input;
adamstark@46 349 src_data.input_frames = BUFFER_LEN;
adamstark@46 350
adamstark@46 351 src_data.src_ratio = src_ratio;
adamstark@46 352
adamstark@46 353 src_data.data_out = output;
adamstark@46 354 src_data.output_frames = output_len;
adamstark@46 355
adamstark@46 356 src_simple (&src_data, SRC_SINC_BEST_QUALITY, 1);
adamstark@46 357
adamstark@46 358 for (int i = 0;i < output_len;i++)
adamstark@46 359 {
adamstark@58 360 resampledOnsetDF[i] = (double) src_data.data_out[i];
adamstark@46 361 }
adamstark@46 362 }
adamstark@46 363
adamstark@51 364 //=======================================================================
adamstark@57 365 void BTrack::calculateTempo()
adamstark@46 366 {
adamstark@46 367 // adaptive threshold on input
adamstark@58 368 adaptiveThreshold(resampledOnsetDF,512);
adamstark@46 369
adamstark@46 370 // calculate auto-correlation function of detection function
adamstark@58 371 calculateBalancedACF(resampledOnsetDF);
adamstark@46 372
adamstark@46 373 // calculate output of comb filterbank
adamstark@57 374 calculateOutputOfCombFilterBank();
adamstark@46 375
adamstark@46 376
adamstark@46 377 // adaptive threshold on rcf
adamstark@58 378 adaptiveThreshold(combFilterBankOutput,128);
adamstark@46 379
adamstark@46 380
adamstark@46 381 int t_index;
adamstark@46 382 int t_index2;
adamstark@59 383 // calculate tempo observation vector from beat period observation vector
adamstark@46 384 for (int i = 0;i < 41;i++)
adamstark@46 385 {
adamstark@59 386 t_index = (int) round(tempoToLagFactor / ((double) ((2*i)+80)));
adamstark@59 387 t_index2 = (int) round(tempoToLagFactor / ((double) ((4*i)+160)));
adamstark@46 388
adamstark@46 389
adamstark@58 390 tempoObservationVector[i] = combFilterBankOutput[t_index-1] + combFilterBankOutput[t_index2-1];
adamstark@46 391 }
adamstark@46 392
adamstark@46 393
adamstark@54 394 double maxval;
adamstark@54 395 double maxind;
adamstark@54 396 double curval;
adamstark@46 397
adamstark@46 398 // if tempo is fixed then always use a fixed set of tempi as the previous observation probability function
adamstark@58 399 if (tempoFixed)
adamstark@46 400 {
adamstark@46 401 for (int k = 0;k < 41;k++)
adamstark@46 402 {
adamstark@58 403 prevDelta[k] = prevDeltaFixed[k];
adamstark@46 404 }
adamstark@46 405 }
adamstark@46 406
adamstark@46 407 for (int j=0;j < 41;j++)
adamstark@46 408 {
adamstark@46 409 maxval = -1;
adamstark@46 410 for (int i = 0;i < 41;i++)
adamstark@46 411 {
adamstark@58 412 curval = prevDelta[i]*tempoTransitionMatrix[i][j];
adamstark@46 413
adamstark@46 414 if (curval > maxval)
adamstark@46 415 {
adamstark@46 416 maxval = curval;
adamstark@46 417 }
adamstark@46 418 }
adamstark@46 419
adamstark@58 420 delta[j] = maxval*tempoObservationVector[j];
adamstark@46 421 }
adamstark@46 422
adamstark@46 423
adamstark@57 424 normaliseArray(delta,41);
adamstark@46 425
adamstark@46 426 maxind = -1;
adamstark@46 427 maxval = -1;
adamstark@46 428
adamstark@46 429 for (int j=0;j < 41;j++)
adamstark@46 430 {
adamstark@46 431 if (delta[j] > maxval)
adamstark@46 432 {
adamstark@46 433 maxval = delta[j];
adamstark@46 434 maxind = j;
adamstark@46 435 }
adamstark@46 436
adamstark@58 437 prevDelta[j] = delta[j];
adamstark@46 438 }
adamstark@46 439
adamstark@57 440 beatPeriod = round((60.0*44100.0)/(((2*maxind)+80)*((double) hopSize)));
adamstark@46 441
adamstark@57 442 if (beatPeriod > 0)
adamstark@46 443 {
adamstark@58 444 estimatedTempo = 60.0/((((double) hopSize) / 44100.0)*beatPeriod);
adamstark@46 445 }
adamstark@46 446 }
adamstark@46 447
adamstark@51 448 //=======================================================================
adamstark@57 449 void BTrack::adaptiveThreshold(double *x,int N)
adamstark@46 450 {
adamstark@46 451 int i = 0;
adamstark@46 452 int k,t = 0;
adamstark@54 453 double x_thresh[N];
adamstark@46 454
adamstark@46 455 int p_post = 7;
adamstark@46 456 int p_pre = 8;
adamstark@46 457
adamstark@52 458 t = std::min(N,p_post); // what is smaller, p_post of df size. This is to avoid accessing outside of arrays
adamstark@46 459
adamstark@46 460 // find threshold for first 't' samples, where a full average cannot be computed yet
adamstark@46 461 for (i = 0;i <= t;i++)
adamstark@46 462 {
adamstark@52 463 k = std::min((i+p_pre),N);
adamstark@57 464 x_thresh[i] = calculateMeanOfArray(x,1,k);
adamstark@46 465 }
adamstark@46 466 // find threshold for bulk of samples across a moving average from [i-p_pre,i+p_post]
adamstark@46 467 for (i = t+1;i < N-p_post;i++)
adamstark@46 468 {
adamstark@57 469 x_thresh[i] = calculateMeanOfArray(x,i-p_pre,i+p_post);
adamstark@46 470 }
adamstark@46 471 // for last few samples calculate threshold, again, not enough samples to do as above
adamstark@46 472 for (i = N-p_post;i < N;i++)
adamstark@46 473 {
adamstark@52 474 k = std::max((i-p_post),1);
adamstark@57 475 x_thresh[i] = calculateMeanOfArray(x,k,N);
adamstark@46 476 }
adamstark@46 477
adamstark@46 478 // subtract the threshold from the detection function and check that it is not less than 0
adamstark@46 479 for (i = 0;i < N;i++)
adamstark@46 480 {
adamstark@46 481 x[i] = x[i] - x_thresh[i];
adamstark@46 482 if (x[i] < 0)
adamstark@46 483 {
adamstark@46 484 x[i] = 0;
adamstark@46 485 }
adamstark@46 486 }
adamstark@46 487 }
adamstark@46 488
adamstark@51 489 //=======================================================================
adamstark@57 490 void BTrack::calculateOutputOfCombFilterBank()
adamstark@46 491 {
adamstark@46 492 int numelem;
adamstark@46 493
adamstark@46 494 for (int i = 0;i < 128;i++)
adamstark@46 495 {
adamstark@58 496 combFilterBankOutput[i] = 0;
adamstark@46 497 }
adamstark@46 498
adamstark@46 499 numelem = 4;
adamstark@46 500
adamstark@46 501 for (int i = 2;i <= 127;i++) // max beat period
adamstark@46 502 {
adamstark@46 503 for (int a = 1;a <= numelem;a++) // number of comb elements
adamstark@46 504 {
adamstark@46 505 for (int b = 1-a;b <= a-1;b++) // general state using normalisation of comb elements
adamstark@46 506 {
adamstark@58 507 combFilterBankOutput[i-1] = combFilterBankOutput[i-1] + (acf[(a*i+b)-1]*weightingVector[i-1])/(2*a-1); // calculate value for comb filter row
adamstark@46 508 }
adamstark@46 509 }
adamstark@46 510 }
adamstark@46 511 }
adamstark@46 512
adamstark@51 513 //=======================================================================
adamstark@60 514 void BTrack::calculateBalancedACF(double *onsetDetectionFunction)
adamstark@46 515 {
adamstark@46 516 int l, n = 0;
adamstark@54 517 double sum, tmp;
adamstark@46 518
adamstark@46 519 // for l lags from 0-511
adamstark@46 520 for (l = 0;l < 512;l++)
adamstark@46 521 {
adamstark@46 522 sum = 0;
adamstark@46 523
adamstark@46 524 // for n samples from 0 - (512-lag)
adamstark@46 525 for (n = 0;n < (512-l);n++)
adamstark@46 526 {
adamstark@60 527 tmp = onsetDetectionFunction[n] * onsetDetectionFunction[n+l]; // multiply current sample n by sample (n+l)
adamstark@46 528 sum = sum + tmp; // add to sum
adamstark@46 529 }
adamstark@46 530
adamstark@46 531 acf[l] = sum / (512-l); // weight by number of mults and add to acf buffer
adamstark@46 532 }
adamstark@46 533 }
adamstark@46 534
adamstark@51 535 //=======================================================================
adamstark@59 536 double BTrack::calculateMeanOfArray(double *array,int startIndex,int endIndex)
adamstark@46 537 {
adamstark@46 538 int i;
adamstark@47 539 double sum = 0;
adamstark@47 540
adamstark@59 541 int length = endIndex - startIndex;
adamstark@46 542
adamstark@46 543 // find sum
adamstark@59 544 for (i = startIndex;i < endIndex;i++)
adamstark@46 545 {
adamstark@46 546 sum = sum + array[i];
adamstark@46 547 }
adamstark@46 548
adamstark@47 549 if (length > 0)
adamstark@47 550 {
adamstark@47 551 return sum / length; // average and return
adamstark@47 552 }
adamstark@47 553 else
adamstark@47 554 {
adamstark@47 555 return 0;
adamstark@47 556 }
adamstark@46 557 }
adamstark@46 558
adamstark@51 559 //=======================================================================
adamstark@57 560 void BTrack::normaliseArray(double *array,int N)
adamstark@46 561 {
adamstark@46 562 double sum = 0;
adamstark@46 563
adamstark@46 564 for (int i = 0;i < N;i++)
adamstark@46 565 {
adamstark@46 566 if (array[i] > 0)
adamstark@46 567 {
adamstark@46 568 sum = sum + array[i];
adamstark@46 569 }
adamstark@46 570 }
adamstark@46 571
adamstark@46 572 if (sum > 0)
adamstark@46 573 {
adamstark@46 574 for (int i = 0;i < N;i++)
adamstark@46 575 {
adamstark@46 576 array[i] = array[i] / sum;
adamstark@46 577 }
adamstark@46 578 }
adamstark@46 579 }
adamstark@46 580
adamstark@51 581 //=======================================================================
adamstark@59 582 void BTrack::updateCumulativeScore(double odfSample)
adamstark@46 583 {
adamstark@46 584 int start, end, winsize;
adamstark@54 585 double max;
adamstark@46 586
adamstark@58 587 start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@58 588 end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@46 589 winsize = end-start+1;
adamstark@46 590
adamstark@54 591 double w1[winsize];
adamstark@57 592 double v = -2*beatPeriod;
adamstark@54 593 double wcumscore;
adamstark@46 594
adamstark@46 595
adamstark@46 596 // create window
adamstark@46 597 for (int i = 0;i < winsize;i++)
adamstark@46 598 {
adamstark@57 599 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@46 600 v = v+1;
adamstark@46 601 }
adamstark@46 602
adamstark@46 603 // calculate new cumulative score value
adamstark@46 604 max = 0;
adamstark@46 605 int n = 0;
adamstark@46 606 for (int i=start;i <= end;i++)
adamstark@46 607 {
adamstark@58 608 wcumscore = cumulativeScore[i]*w1[n];
adamstark@46 609
adamstark@46 610 if (wcumscore > max)
adamstark@46 611 {
adamstark@46 612 max = wcumscore;
adamstark@46 613 }
adamstark@46 614 n++;
adamstark@46 615 }
adamstark@46 616
adamstark@46 617
adamstark@46 618 // shift cumulative score back one
adamstark@58 619 for (int i = 0;i < (onsetDFBufferSize-1);i++)
adamstark@46 620 {
adamstark@58 621 cumulativeScore[i] = cumulativeScore[i+1];
adamstark@46 622 }
adamstark@46 623
adamstark@46 624 // add new value to cumulative score
adamstark@59 625 cumulativeScore[onsetDFBufferSize-1] = ((1-alpha)*odfSample) + (alpha*max);
adamstark@46 626
adamstark@58 627 latestCumulativeScoreValue = cumulativeScore[onsetDFBufferSize-1];
adamstark@58 628
adamstark@46 629 }
adamstark@46 630
adamstark@51 631 //=======================================================================
adamstark@57 632 void BTrack::predictBeat()
adamstark@46 633 {
adamstark@58 634 int windowSize = (int) beatPeriod;
adamstark@58 635 double futureCumulativeScore[onsetDFBufferSize + windowSize];
adamstark@58 636 double w2[windowSize];
adamstark@46 637 // copy cumscore to first part of fcumscore
adamstark@58 638 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@46 639 {
adamstark@58 640 futureCumulativeScore[i] = cumulativeScore[i];
adamstark@46 641 }
adamstark@46 642
adamstark@46 643 // create future window
adamstark@54 644 double v = 1;
adamstark@58 645 for (int i = 0;i < windowSize;i++)
adamstark@46 646 {
adamstark@57 647 w2[i] = exp((-1*pow((v - (beatPeriod/2)),2)) / (2*pow((beatPeriod/2) ,2)));
adamstark@46 648 v++;
adamstark@46 649 }
adamstark@46 650
adamstark@46 651 // create past window
adamstark@57 652 v = -2*beatPeriod;
adamstark@58 653 int start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@58 654 int end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@46 655 int pastwinsize = end-start+1;
adamstark@54 656 double w1[pastwinsize];
adamstark@46 657
adamstark@46 658 for (int i = 0;i < pastwinsize;i++)
adamstark@46 659 {
adamstark@57 660 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@46 661 v = v+1;
adamstark@46 662 }
adamstark@46 663
adamstark@46 664
adamstark@46 665
adamstark@46 666 // calculate future cumulative score
adamstark@54 667 double max;
adamstark@46 668 int n;
adamstark@54 669 double wcumscore;
adamstark@58 670 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@46 671 {
adamstark@57 672 start = i - round(2*beatPeriod);
adamstark@57 673 end = i - round(beatPeriod/2);
adamstark@46 674
adamstark@46 675 max = 0;
adamstark@46 676 n = 0;
adamstark@46 677 for (int k=start;k <= end;k++)
adamstark@46 678 {
adamstark@58 679 wcumscore = futureCumulativeScore[k]*w1[n];
adamstark@46 680
adamstark@46 681 if (wcumscore > max)
adamstark@46 682 {
adamstark@46 683 max = wcumscore;
adamstark@46 684 }
adamstark@46 685 n++;
adamstark@46 686 }
adamstark@46 687
adamstark@58 688 futureCumulativeScore[i] = max;
adamstark@46 689 }
adamstark@46 690
adamstark@46 691
adamstark@46 692 // predict beat
adamstark@46 693 max = 0;
adamstark@46 694 n = 0;
adamstark@46 695
adamstark@58 696 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@46 697 {
adamstark@58 698 wcumscore = futureCumulativeScore[i]*w2[n];
adamstark@46 699
adamstark@46 700 if (wcumscore > max)
adamstark@46 701 {
adamstark@46 702 max = wcumscore;
adamstark@58 703 beatCounter = n;
adamstark@46 704 }
adamstark@46 705
adamstark@46 706 n++;
adamstark@46 707 }
adamstark@46 708
adamstark@46 709 // set next prediction time
adamstark@58 710 m0 = beatCounter+round(beatPeriod/2);
adamstark@46 711
adamstark@46 712
adamstark@46 713 }