annotate src/BTrack.cpp @ 27:98f7a54faa0c develop

Changed all pointers to arrays in OnsetDetectionFunction into vectors
author Adam <adamstark.uk@gmail.com>
date Tue, 28 Jan 2014 00:19:21 +0000
parents e4d5f045064d
children 7af87d3f2ce2
rev   line source
adamstark@5 1 //=======================================================================
adamstark@5 2 /** @file BTrack.cpp
adamstark@6 3 * @brief BTrack - a real-time beat tracker
adamstark@5 4 * @author Adam Stark
adamstark@5 5 * @copyright Copyright (C) 2008-2014 Queen Mary University of London
adamstark@5 6 *
adamstark@5 7 * This program is free software: you can redistribute it and/or modify
adamstark@5 8 * it under the terms of the GNU General Public License as published by
adamstark@5 9 * the Free Software Foundation, either version 3 of the License, or
adamstark@5 10 * (at your option) any later version.
adamstark@5 11 *
adamstark@5 12 * This program is distributed in the hope that it will be useful,
adamstark@5 13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
adamstark@5 14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
adamstark@5 15 * GNU General Public License for more details.
adamstark@5 16 *
adamstark@5 17 * You should have received a copy of the GNU General Public License
adamstark@5 18 * along with this program. If not, see <http://www.gnu.org/licenses/>.
adamstark@5 19 */
adamstark@5 20 //=======================================================================
adamstark@5 21
adamstark@5 22 #include <cmath>
adamstark@15 23 #include <algorithm>
adamstark@5 24 #include "BTrack.h"
adamstark@5 25 #include "samplerate.h"
adamstark@5 26
adamstark@18 27 //=======================================================================
adamstark@20 28 BTrack::BTrack() : odf(512,1024,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@18 29 {
adamstark@18 30 initialise(512, 1024);
adamstark@18 31 }
adamstark@5 32
adamstark@14 33 //=======================================================================
adamstark@20 34 BTrack::BTrack(int hopSize_) : odf(hopSize_,2*hopSize_,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@5 35 {
adamstark@20 36 initialise(hopSize_, 2*hopSize_);
adamstark@18 37 }
adamstark@18 38
adamstark@18 39 //=======================================================================
adamstark@20 40 BTrack::BTrack(int hopSize_,int frameSize_) : odf(hopSize_,frameSize_,ComplexSpectralDifferenceHWR,HanningWindow)
adamstark@18 41 {
adamstark@20 42 initialise(hopSize_, frameSize_);
adamstark@18 43 }
adamstark@18 44
adamstark@18 45 //=======================================================================
adamstark@18 46 double BTrack::getBeatTimeInSeconds(long frameNumber,int hopSize,int fs)
adamstark@18 47 {
adamstark@18 48 double hop = (double) hopSize;
adamstark@18 49 double samplingFrequency = (double) fs;
adamstark@18 50 double frameNum = (double) frameNumber;
adamstark@18 51
adamstark@18 52 return ((hop / samplingFrequency) * frameNum);
adamstark@18 53 }
adamstark@18 54
adamstark@18 55 //=======================================================================
adamstark@18 56 double BTrack::getBeatTimeInSeconds(int frameNumber,int hopSize,int fs)
adamstark@18 57 {
adamstark@18 58 long frameNum = (long) frameNumber;
adamstark@18 59
adamstark@18 60 return getBeatTimeInSeconds(frameNum, hopSize, fs);
adamstark@18 61 }
adamstark@18 62
adamstark@18 63
adamstark@18 64
adamstark@18 65 //=======================================================================
adamstark@20 66 void BTrack::initialise(int hopSize_, int frameSize_)
adamstark@18 67 {
adamstark@18 68 double rayparam = 43;
adamstark@17 69 double pi = 3.14159265;
adamstark@5 70
adamstark@5 71
adamstark@5 72 // initialise parameters
adamstark@5 73 tightness = 5;
adamstark@5 74 alpha = 0.9;
adamstark@5 75 tempo = 120;
adamstark@21 76 estimatedTempo = 120.0;
adamstark@22 77 tempoToLagFactor = 60.*44100./512.;
adamstark@5 78
adamstark@5 79 m0 = 10;
adamstark@21 80 beatCounter = -1;
adamstark@5 81
adamstark@20 82 beatDueInFrame = false;
adamstark@5 83
adamstark@21 84
adamstark@5 85 // create rayleigh weighting vector
adamstark@5 86 for (int n = 0;n < 128;n++)
adamstark@5 87 {
adamstark@21 88 weightingVector[n] = ((double) n / pow(rayparam,2)) * exp((-1*pow((double)-n,2)) / (2*pow(rayparam,2)));
adamstark@5 89 }
adamstark@5 90
adamstark@5 91 // initialise prev_delta
adamstark@5 92 for (int i = 0;i < 41;i++)
adamstark@5 93 {
adamstark@21 94 prevDelta[i] = 1;
adamstark@5 95 }
adamstark@5 96
adamstark@17 97 double t_mu = 41/2;
adamstark@17 98 double m_sig;
adamstark@17 99 double x;
adamstark@5 100 // create tempo transition matrix
adamstark@5 101 m_sig = 41/8;
adamstark@5 102 for (int i = 0;i < 41;i++)
adamstark@5 103 {
adamstark@5 104 for (int j = 0;j < 41;j++)
adamstark@5 105 {
adamstark@5 106 x = j+1;
adamstark@5 107 t_mu = i+1;
adamstark@21 108 tempoTransitionMatrix[i][j] = (1 / (m_sig * sqrt(2*pi))) * exp( (-1*pow((x-t_mu),2)) / (2*pow(m_sig,2)) );
adamstark@5 109 }
adamstark@18 110 }
adamstark@5 111
adamstark@5 112 // tempo is not fixed
adamstark@21 113 tempoFixed = false;
adamstark@21 114
adamstark@21 115 // initialise latest cumulative score value
adamstark@21 116 // in case it is requested before any processing takes place
adamstark@21 117 latestCumulativeScoreValue = 0;
adamstark@18 118
adamstark@18 119 // initialise algorithm given the hopsize
adamstark@20 120 setHopSize(hopSize_);
adamstark@5 121 }
adamstark@5 122
adamstark@14 123 //=======================================================================
adamstark@20 124 void BTrack::setHopSize(int hopSize_)
adamstark@5 125 {
adamstark@20 126 hopSize = hopSize_;
adamstark@21 127 onsetDFBufferSize = (512*512)/hopSize; // calculate df buffer size
adamstark@5 128
adamstark@20 129 beatPeriod = round(60/((((double) hopSize)/44100)*tempo));
adamstark@26 130
adamstark@26 131 // set size of onset detection function buffer
adamstark@26 132 onsetDF.resize(onsetDFBufferSize);
adamstark@26 133
adamstark@26 134 // set size of cumulative score buffer
adamstark@26 135 cumulativeScore.resize(onsetDFBufferSize);
adamstark@5 136
adamstark@5 137 // initialise df_buffer to zeros
adamstark@21 138 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@5 139 {
adamstark@21 140 onsetDF[i] = 0;
adamstark@21 141 cumulativeScore[i] = 0;
adamstark@5 142
adamstark@5 143
adamstark@20 144 if ((i % ((int) round(beatPeriod))) == 0)
adamstark@5 145 {
adamstark@21 146 onsetDF[i] = 1;
adamstark@5 147 }
adamstark@5 148 }
adamstark@5 149 }
adamstark@5 150
adamstark@14 151 //=======================================================================
adamstark@20 152 bool BTrack::beatDueInCurrentFrame()
adamstark@20 153 {
adamstark@20 154 return beatDueInFrame;
adamstark@20 155 }
adamstark@20 156
adamstark@20 157 //=======================================================================
adamstark@20 158 int BTrack::getHopSize()
adamstark@20 159 {
adamstark@20 160 return hopSize;
adamstark@20 161 }
adamstark@20 162
adamstark@20 163 //=======================================================================
adamstark@21 164 double BTrack::getLatestCumulativeScoreValue()
adamstark@21 165 {
adamstark@21 166 return latestCumulativeScoreValue;
adamstark@21 167 }
adamstark@21 168
adamstark@21 169 //=======================================================================
adamstark@18 170 void BTrack::processAudioFrame(double *frame)
adamstark@18 171 {
adamstark@18 172 // calculate the onset detection function sample for the frame
adamstark@22 173 double sample = odf.calculateOnsetDetectionFunctionSample(frame);
adamstark@18 174
adamstark@19 175
adamstark@18 176
adamstark@18 177 // process the new onset detection function sample in the beat tracking algorithm
adamstark@18 178 processOnsetDetectionFunctionSample(sample);
adamstark@18 179 }
adamstark@18 180
adamstark@18 181 //=======================================================================
adamstark@18 182 void BTrack::processOnsetDetectionFunctionSample(double newSample)
adamstark@19 183 {
adamstark@19 184 // we need to ensure that the onset
adamstark@19 185 // detection function sample is positive
adamstark@19 186 newSample = fabs(newSample);
adamstark@19 187
adamstark@19 188 // add a tiny constant to the sample to stop it from ever going
adamstark@19 189 // to zero. this is to avoid problems further down the line
adamstark@19 190 newSample = newSample + 0.0001;
adamstark@19 191
adamstark@5 192 m0--;
adamstark@21 193 beatCounter--;
adamstark@20 194 beatDueInFrame = false;
adamstark@5 195
adamstark@5 196 // move all samples back one step
adamstark@21 197 for (int i=0;i < (onsetDFBufferSize-1);i++)
adamstark@5 198 {
adamstark@21 199 onsetDF[i] = onsetDF[i+1];
adamstark@5 200 }
adamstark@5 201
adamstark@5 202 // add new sample at the end
adamstark@21 203 onsetDF[onsetDFBufferSize-1] = newSample;
adamstark@5 204
adamstark@5 205 // update cumulative score
adamstark@20 206 updateCumulativeScore(newSample);
adamstark@5 207
adamstark@5 208 // if we are halfway between beats
adamstark@5 209 if (m0 == 0)
adamstark@5 210 {
adamstark@20 211 predictBeat();
adamstark@5 212 }
adamstark@5 213
adamstark@5 214 // if we are at a beat
adamstark@21 215 if (beatCounter == 0)
adamstark@5 216 {
adamstark@20 217 beatDueInFrame = true; // indicate a beat should be output
adamstark@5 218
adamstark@5 219 // recalculate the tempo
adamstark@20 220 resampleOnsetDetectionFunction();
adamstark@20 221 calculateTempo();
adamstark@5 222 }
adamstark@5 223 }
adamstark@5 224
adamstark@14 225 //=======================================================================
adamstark@20 226 void BTrack::setTempo(double tempo)
adamstark@5 227 {
adamstark@5 228
adamstark@5 229 /////////// TEMPO INDICATION RESET //////////////////
adamstark@5 230
adamstark@5 231 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@5 232 while (tempo > 160)
adamstark@5 233 {
adamstark@5 234 tempo = tempo/2;
adamstark@5 235 }
adamstark@5 236
adamstark@5 237 while (tempo < 80)
adamstark@5 238 {
adamstark@5 239 tempo = tempo * 2;
adamstark@5 240 }
adamstark@5 241
adamstark@5 242 // convert tempo from bpm value to integer index of tempo probability
adamstark@5 243 int tempo_index = (int) round((tempo - 80)/2);
adamstark@5 244
adamstark@5 245 // now set previous tempo observations to zero
adamstark@5 246 for (int i=0;i < 41;i++)
adamstark@5 247 {
adamstark@21 248 prevDelta[i] = 0;
adamstark@5 249 }
adamstark@5 250
adamstark@5 251 // set desired tempo index to 1
adamstark@21 252 prevDelta[tempo_index] = 1;
adamstark@5 253
adamstark@5 254
adamstark@5 255 /////////// CUMULATIVE SCORE ARTIFICAL TEMPO UPDATE //////////////////
adamstark@5 256
adamstark@5 257 // calculate new beat period
adamstark@20 258 int new_bperiod = (int) round(60/((((double) hopSize)/44100)*tempo));
adamstark@5 259
adamstark@5 260 int bcounter = 1;
adamstark@5 261 // initialise df_buffer to zeros
adamstark@21 262 for (int i = (onsetDFBufferSize-1);i >= 0;i--)
adamstark@5 263 {
adamstark@5 264 if (bcounter == 1)
adamstark@5 265 {
adamstark@21 266 cumulativeScore[i] = 150;
adamstark@21 267 onsetDF[i] = 150;
adamstark@5 268 }
adamstark@5 269 else
adamstark@5 270 {
adamstark@21 271 cumulativeScore[i] = 10;
adamstark@21 272 onsetDF[i] = 10;
adamstark@5 273 }
adamstark@5 274
adamstark@5 275 bcounter++;
adamstark@5 276
adamstark@5 277 if (bcounter > new_bperiod)
adamstark@5 278 {
adamstark@5 279 bcounter = 1;
adamstark@5 280 }
adamstark@5 281 }
adamstark@5 282
adamstark@5 283 /////////// INDICATE THAT THIS IS A BEAT //////////////////
adamstark@5 284
adamstark@5 285 // beat is now
adamstark@21 286 beatCounter = 0;
adamstark@5 287
adamstark@5 288 // offbeat is half of new beat period away
adamstark@17 289 m0 = (int) round(((double) new_bperiod)/2);
adamstark@5 290 }
adamstark@5 291
adamstark@14 292 //=======================================================================
adamstark@20 293 void BTrack::fixTempo(double tempo)
adamstark@5 294 {
adamstark@5 295 // firstly make sure tempo is between 80 and 160 bpm..
adamstark@5 296 while (tempo > 160)
adamstark@5 297 {
adamstark@5 298 tempo = tempo/2;
adamstark@5 299 }
adamstark@5 300
adamstark@5 301 while (tempo < 80)
adamstark@5 302 {
adamstark@5 303 tempo = tempo * 2;
adamstark@5 304 }
adamstark@5 305
adamstark@5 306 // convert tempo from bpm value to integer index of tempo probability
adamstark@5 307 int tempo_index = (int) round((tempo - 80)/2);
adamstark@5 308
adamstark@5 309 // now set previous fixed previous tempo observation values to zero
adamstark@5 310 for (int i=0;i < 41;i++)
adamstark@5 311 {
adamstark@21 312 prevDeltaFixed[i] = 0;
adamstark@5 313 }
adamstark@5 314
adamstark@5 315 // set desired tempo index to 1
adamstark@21 316 prevDeltaFixed[tempo_index] = 1;
adamstark@5 317
adamstark@5 318 // set the tempo fix flag
adamstark@21 319 tempoFixed = true;
adamstark@5 320 }
adamstark@5 321
adamstark@14 322 //=======================================================================
adamstark@20 323 void BTrack::doNotFixTempo()
adamstark@5 324 {
adamstark@5 325 // set the tempo fix flag
adamstark@21 326 tempoFixed = false;
adamstark@5 327 }
adamstark@5 328
adamstark@14 329 //=======================================================================
adamstark@20 330 void BTrack::resampleOnsetDetectionFunction()
adamstark@5 331 {
adamstark@5 332 float output[512];
adamstark@21 333 float input[onsetDFBufferSize];
adamstark@17 334
adamstark@21 335 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@17 336 {
adamstark@21 337 input[i] = (float) onsetDF[i];
adamstark@17 338 }
adamstark@5 339
adamstark@21 340 double src_ratio = 512.0/((double) onsetDFBufferSize);
adamstark@21 341 int BUFFER_LEN = onsetDFBufferSize;
adamstark@5 342 int output_len;
adamstark@5 343 SRC_DATA src_data ;
adamstark@5 344
adamstark@5 345 //output_len = (int) floor (((double) BUFFER_LEN) * src_ratio) ;
adamstark@5 346 output_len = 512;
adamstark@5 347
adamstark@17 348 src_data.data_in = input;
adamstark@5 349 src_data.input_frames = BUFFER_LEN;
adamstark@5 350
adamstark@5 351 src_data.src_ratio = src_ratio;
adamstark@5 352
adamstark@5 353 src_data.data_out = output;
adamstark@5 354 src_data.output_frames = output_len;
adamstark@5 355
adamstark@5 356 src_simple (&src_data, SRC_SINC_BEST_QUALITY, 1);
adamstark@5 357
adamstark@5 358 for (int i = 0;i < output_len;i++)
adamstark@5 359 {
adamstark@21 360 resampledOnsetDF[i] = (double) src_data.data_out[i];
adamstark@5 361 }
adamstark@5 362 }
adamstark@5 363
adamstark@14 364 //=======================================================================
adamstark@20 365 void BTrack::calculateTempo()
adamstark@5 366 {
adamstark@5 367 // adaptive threshold on input
adamstark@21 368 adaptiveThreshold(resampledOnsetDF,512);
adamstark@5 369
adamstark@5 370 // calculate auto-correlation function of detection function
adamstark@21 371 calculateBalancedACF(resampledOnsetDF);
adamstark@5 372
adamstark@5 373 // calculate output of comb filterbank
adamstark@20 374 calculateOutputOfCombFilterBank();
adamstark@5 375
adamstark@5 376
adamstark@5 377 // adaptive threshold on rcf
adamstark@21 378 adaptiveThreshold(combFilterBankOutput,128);
adamstark@5 379
adamstark@5 380
adamstark@5 381 int t_index;
adamstark@5 382 int t_index2;
adamstark@22 383 // calculate tempo observation vector from beat period observation vector
adamstark@5 384 for (int i = 0;i < 41;i++)
adamstark@5 385 {
adamstark@22 386 t_index = (int) round(tempoToLagFactor / ((double) ((2*i)+80)));
adamstark@22 387 t_index2 = (int) round(tempoToLagFactor / ((double) ((4*i)+160)));
adamstark@5 388
adamstark@5 389
adamstark@21 390 tempoObservationVector[i] = combFilterBankOutput[t_index-1] + combFilterBankOutput[t_index2-1];
adamstark@5 391 }
adamstark@5 392
adamstark@5 393
adamstark@17 394 double maxval;
adamstark@17 395 double maxind;
adamstark@17 396 double curval;
adamstark@5 397
adamstark@5 398 // if tempo is fixed then always use a fixed set of tempi as the previous observation probability function
adamstark@21 399 if (tempoFixed)
adamstark@5 400 {
adamstark@5 401 for (int k = 0;k < 41;k++)
adamstark@5 402 {
adamstark@21 403 prevDelta[k] = prevDeltaFixed[k];
adamstark@5 404 }
adamstark@5 405 }
adamstark@5 406
adamstark@5 407 for (int j=0;j < 41;j++)
adamstark@5 408 {
adamstark@5 409 maxval = -1;
adamstark@5 410 for (int i = 0;i < 41;i++)
adamstark@5 411 {
adamstark@21 412 curval = prevDelta[i]*tempoTransitionMatrix[i][j];
adamstark@5 413
adamstark@5 414 if (curval > maxval)
adamstark@5 415 {
adamstark@5 416 maxval = curval;
adamstark@5 417 }
adamstark@5 418 }
adamstark@5 419
adamstark@21 420 delta[j] = maxval*tempoObservationVector[j];
adamstark@5 421 }
adamstark@5 422
adamstark@5 423
adamstark@20 424 normaliseArray(delta,41);
adamstark@5 425
adamstark@5 426 maxind = -1;
adamstark@5 427 maxval = -1;
adamstark@5 428
adamstark@5 429 for (int j=0;j < 41;j++)
adamstark@5 430 {
adamstark@5 431 if (delta[j] > maxval)
adamstark@5 432 {
adamstark@5 433 maxval = delta[j];
adamstark@5 434 maxind = j;
adamstark@5 435 }
adamstark@5 436
adamstark@21 437 prevDelta[j] = delta[j];
adamstark@5 438 }
adamstark@5 439
adamstark@20 440 beatPeriod = round((60.0*44100.0)/(((2*maxind)+80)*((double) hopSize)));
adamstark@5 441
adamstark@20 442 if (beatPeriod > 0)
adamstark@5 443 {
adamstark@21 444 estimatedTempo = 60.0/((((double) hopSize) / 44100.0)*beatPeriod);
adamstark@5 445 }
adamstark@5 446 }
adamstark@5 447
adamstark@14 448 //=======================================================================
adamstark@20 449 void BTrack::adaptiveThreshold(double *x,int N)
adamstark@5 450 {
adamstark@5 451 int i = 0;
adamstark@5 452 int k,t = 0;
adamstark@17 453 double x_thresh[N];
adamstark@5 454
adamstark@5 455 int p_post = 7;
adamstark@5 456 int p_pre = 8;
adamstark@5 457
adamstark@15 458 t = std::min(N,p_post); // what is smaller, p_post of df size. This is to avoid accessing outside of arrays
adamstark@5 459
adamstark@5 460 // find threshold for first 't' samples, where a full average cannot be computed yet
adamstark@5 461 for (i = 0;i <= t;i++)
adamstark@5 462 {
adamstark@15 463 k = std::min((i+p_pre),N);
adamstark@20 464 x_thresh[i] = calculateMeanOfArray(x,1,k);
adamstark@5 465 }
adamstark@5 466 // find threshold for bulk of samples across a moving average from [i-p_pre,i+p_post]
adamstark@5 467 for (i = t+1;i < N-p_post;i++)
adamstark@5 468 {
adamstark@20 469 x_thresh[i] = calculateMeanOfArray(x,i-p_pre,i+p_post);
adamstark@5 470 }
adamstark@5 471 // for last few samples calculate threshold, again, not enough samples to do as above
adamstark@5 472 for (i = N-p_post;i < N;i++)
adamstark@5 473 {
adamstark@15 474 k = std::max((i-p_post),1);
adamstark@20 475 x_thresh[i] = calculateMeanOfArray(x,k,N);
adamstark@5 476 }
adamstark@5 477
adamstark@5 478 // subtract the threshold from the detection function and check that it is not less than 0
adamstark@5 479 for (i = 0;i < N;i++)
adamstark@5 480 {
adamstark@5 481 x[i] = x[i] - x_thresh[i];
adamstark@5 482 if (x[i] < 0)
adamstark@5 483 {
adamstark@5 484 x[i] = 0;
adamstark@5 485 }
adamstark@5 486 }
adamstark@5 487 }
adamstark@5 488
adamstark@14 489 //=======================================================================
adamstark@20 490 void BTrack::calculateOutputOfCombFilterBank()
adamstark@5 491 {
adamstark@5 492 int numelem;
adamstark@5 493
adamstark@5 494 for (int i = 0;i < 128;i++)
adamstark@5 495 {
adamstark@21 496 combFilterBankOutput[i] = 0;
adamstark@5 497 }
adamstark@5 498
adamstark@5 499 numelem = 4;
adamstark@5 500
adamstark@5 501 for (int i = 2;i <= 127;i++) // max beat period
adamstark@5 502 {
adamstark@5 503 for (int a = 1;a <= numelem;a++) // number of comb elements
adamstark@5 504 {
adamstark@5 505 for (int b = 1-a;b <= a-1;b++) // general state using normalisation of comb elements
adamstark@5 506 {
adamstark@21 507 combFilterBankOutput[i-1] = combFilterBankOutput[i-1] + (acf[(a*i+b)-1]*weightingVector[i-1])/(2*a-1); // calculate value for comb filter row
adamstark@5 508 }
adamstark@5 509 }
adamstark@5 510 }
adamstark@5 511 }
adamstark@5 512
adamstark@14 513 //=======================================================================
adamstark@23 514 void BTrack::calculateBalancedACF(double *onsetDetectionFunction)
adamstark@5 515 {
adamstark@5 516 int l, n = 0;
adamstark@17 517 double sum, tmp;
adamstark@5 518
adamstark@5 519 // for l lags from 0-511
adamstark@5 520 for (l = 0;l < 512;l++)
adamstark@5 521 {
adamstark@5 522 sum = 0;
adamstark@5 523
adamstark@5 524 // for n samples from 0 - (512-lag)
adamstark@5 525 for (n = 0;n < (512-l);n++)
adamstark@5 526 {
adamstark@23 527 tmp = onsetDetectionFunction[n] * onsetDetectionFunction[n+l]; // multiply current sample n by sample (n+l)
adamstark@5 528 sum = sum + tmp; // add to sum
adamstark@5 529 }
adamstark@5 530
adamstark@5 531 acf[l] = sum / (512-l); // weight by number of mults and add to acf buffer
adamstark@5 532 }
adamstark@5 533 }
adamstark@5 534
adamstark@14 535 //=======================================================================
adamstark@22 536 double BTrack::calculateMeanOfArray(double *array,int startIndex,int endIndex)
adamstark@5 537 {
adamstark@5 538 int i;
adamstark@6 539 double sum = 0;
adamstark@6 540
adamstark@22 541 int length = endIndex - startIndex;
adamstark@5 542
adamstark@5 543 // find sum
adamstark@22 544 for (i = startIndex;i < endIndex;i++)
adamstark@5 545 {
adamstark@5 546 sum = sum + array[i];
adamstark@5 547 }
adamstark@5 548
adamstark@6 549 if (length > 0)
adamstark@6 550 {
adamstark@6 551 return sum / length; // average and return
adamstark@6 552 }
adamstark@6 553 else
adamstark@6 554 {
adamstark@6 555 return 0;
adamstark@6 556 }
adamstark@5 557 }
adamstark@5 558
adamstark@14 559 //=======================================================================
adamstark@20 560 void BTrack::normaliseArray(double *array,int N)
adamstark@5 561 {
adamstark@5 562 double sum = 0;
adamstark@5 563
adamstark@5 564 for (int i = 0;i < N;i++)
adamstark@5 565 {
adamstark@5 566 if (array[i] > 0)
adamstark@5 567 {
adamstark@5 568 sum = sum + array[i];
adamstark@5 569 }
adamstark@5 570 }
adamstark@5 571
adamstark@5 572 if (sum > 0)
adamstark@5 573 {
adamstark@5 574 for (int i = 0;i < N;i++)
adamstark@5 575 {
adamstark@5 576 array[i] = array[i] / sum;
adamstark@5 577 }
adamstark@5 578 }
adamstark@5 579 }
adamstark@5 580
adamstark@14 581 //=======================================================================
adamstark@22 582 void BTrack::updateCumulativeScore(double odfSample)
adamstark@5 583 {
adamstark@5 584 int start, end, winsize;
adamstark@17 585 double max;
adamstark@5 586
adamstark@21 587 start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@21 588 end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@5 589 winsize = end-start+1;
adamstark@5 590
adamstark@17 591 double w1[winsize];
adamstark@20 592 double v = -2*beatPeriod;
adamstark@17 593 double wcumscore;
adamstark@5 594
adamstark@5 595
adamstark@5 596 // create window
adamstark@5 597 for (int i = 0;i < winsize;i++)
adamstark@5 598 {
adamstark@20 599 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@5 600 v = v+1;
adamstark@5 601 }
adamstark@5 602
adamstark@5 603 // calculate new cumulative score value
adamstark@5 604 max = 0;
adamstark@5 605 int n = 0;
adamstark@5 606 for (int i=start;i <= end;i++)
adamstark@5 607 {
adamstark@21 608 wcumscore = cumulativeScore[i]*w1[n];
adamstark@5 609
adamstark@5 610 if (wcumscore > max)
adamstark@5 611 {
adamstark@5 612 max = wcumscore;
adamstark@5 613 }
adamstark@5 614 n++;
adamstark@5 615 }
adamstark@5 616
adamstark@5 617
adamstark@5 618 // shift cumulative score back one
adamstark@21 619 for (int i = 0;i < (onsetDFBufferSize-1);i++)
adamstark@5 620 {
adamstark@21 621 cumulativeScore[i] = cumulativeScore[i+1];
adamstark@5 622 }
adamstark@5 623
adamstark@5 624 // add new value to cumulative score
adamstark@22 625 cumulativeScore[onsetDFBufferSize-1] = ((1-alpha)*odfSample) + (alpha*max);
adamstark@5 626
adamstark@21 627 latestCumulativeScoreValue = cumulativeScore[onsetDFBufferSize-1];
adamstark@21 628
adamstark@5 629 }
adamstark@5 630
adamstark@14 631 //=======================================================================
adamstark@20 632 void BTrack::predictBeat()
adamstark@5 633 {
adamstark@21 634 int windowSize = (int) beatPeriod;
adamstark@21 635 double futureCumulativeScore[onsetDFBufferSize + windowSize];
adamstark@21 636 double w2[windowSize];
adamstark@5 637 // copy cumscore to first part of fcumscore
adamstark@21 638 for (int i = 0;i < onsetDFBufferSize;i++)
adamstark@5 639 {
adamstark@21 640 futureCumulativeScore[i] = cumulativeScore[i];
adamstark@5 641 }
adamstark@5 642
adamstark@5 643 // create future window
adamstark@17 644 double v = 1;
adamstark@21 645 for (int i = 0;i < windowSize;i++)
adamstark@5 646 {
adamstark@20 647 w2[i] = exp((-1*pow((v - (beatPeriod/2)),2)) / (2*pow((beatPeriod/2) ,2)));
adamstark@5 648 v++;
adamstark@5 649 }
adamstark@5 650
adamstark@5 651 // create past window
adamstark@20 652 v = -2*beatPeriod;
adamstark@21 653 int start = onsetDFBufferSize - round(2*beatPeriod);
adamstark@21 654 int end = onsetDFBufferSize - round(beatPeriod/2);
adamstark@5 655 int pastwinsize = end-start+1;
adamstark@17 656 double w1[pastwinsize];
adamstark@5 657
adamstark@5 658 for (int i = 0;i < pastwinsize;i++)
adamstark@5 659 {
adamstark@20 660 w1[i] = exp((-1*pow(tightness*log(-v/beatPeriod),2))/2);
adamstark@5 661 v = v+1;
adamstark@5 662 }
adamstark@5 663
adamstark@5 664
adamstark@5 665
adamstark@5 666 // calculate future cumulative score
adamstark@17 667 double max;
adamstark@5 668 int n;
adamstark@17 669 double wcumscore;
adamstark@21 670 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@5 671 {
adamstark@20 672 start = i - round(2*beatPeriod);
adamstark@20 673 end = i - round(beatPeriod/2);
adamstark@5 674
adamstark@5 675 max = 0;
adamstark@5 676 n = 0;
adamstark@5 677 for (int k=start;k <= end;k++)
adamstark@5 678 {
adamstark@21 679 wcumscore = futureCumulativeScore[k]*w1[n];
adamstark@5 680
adamstark@5 681 if (wcumscore > max)
adamstark@5 682 {
adamstark@5 683 max = wcumscore;
adamstark@5 684 }
adamstark@5 685 n++;
adamstark@5 686 }
adamstark@5 687
adamstark@21 688 futureCumulativeScore[i] = max;
adamstark@5 689 }
adamstark@5 690
adamstark@5 691
adamstark@5 692 // predict beat
adamstark@5 693 max = 0;
adamstark@5 694 n = 0;
adamstark@5 695
adamstark@21 696 for (int i = onsetDFBufferSize;i < (onsetDFBufferSize+windowSize);i++)
adamstark@5 697 {
adamstark@21 698 wcumscore = futureCumulativeScore[i]*w2[n];
adamstark@5 699
adamstark@5 700 if (wcumscore > max)
adamstark@5 701 {
adamstark@5 702 max = wcumscore;
adamstark@21 703 beatCounter = n;
adamstark@5 704 }
adamstark@5 705
adamstark@5 706 n++;
adamstark@5 707 }
adamstark@5 708
adamstark@5 709 // set next prediction time
adamstark@21 710 m0 = beatCounter+round(beatPeriod/2);
adamstark@5 711
adamstark@5 712
adamstark@5 713 }