gain_analysis.c 20 KB

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  1. /*
  2. * ReplayGainAnalysis - analyzes input samples and give the recommended dB change
  3. * Copyright (C) 2001 David Robinson and Glen Sawyer
  4. * Improvements and optimizations added by Frank Klemm, and by Marcel Muller
  5. *
  6. * This library is free software; you can redistribute it and/or
  7. * modify it under the terms of the GNU Lesser General Public
  8. * License as published by the Free Software Foundation; either
  9. * version 2.1 of the License, or (at your option) any later version.
  10. *
  11. * This library is distributed in the hope that it will be useful,
  12. * but WITHOUT ANY WARRANTY; without even the implied warranty of
  13. * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
  14. * Lesser General Public License for more details.
  15. *
  16. * You should have received a copy of the GNU Lesser General Public
  17. * License along with this library; if not, write to the Free Software
  18. * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
  19. *
  20. * concept and filter values by David Robinson ([email protected])
  21. * -- blame him if you think the idea is flawed
  22. * original coding by Glen Sawyer ([email protected])
  23. * -- blame him if you think this runs too slowly, or the coding is otherwise flawed
  24. *
  25. * lots of code improvements by Frank Klemm ( http://www.uni-jena.de/~pfk/mpp/ )
  26. * -- credit him for all the _good_ programming ;)
  27. *
  28. *
  29. * For an explanation of the concepts and the basic algorithms involved, go to:
  30. * http://www.replaygain.org/
  31. */
  32. /*
  33. * Here's the deal. Call
  34. *
  35. * InitGainAnalysis ( long samplefreq );
  36. *
  37. * to initialize everything. Call
  38. *
  39. * AnalyzeSamples ( const Float_t* left_samples,
  40. * const Float_t* right_samples,
  41. * size_t num_samples,
  42. * int num_channels );
  43. *
  44. * as many times as you want, with as many or as few samples as you want.
  45. * If mono, pass the sample buffer in through left_samples, leave
  46. * right_samples NULL, and make sure num_channels = 1.
  47. *
  48. * GetTitleGain()
  49. *
  50. * will return the recommended dB level change for all samples analyzed
  51. * SINCE THE LAST TIME you called GetTitleGain() OR InitGainAnalysis().
  52. *
  53. * GetAlbumGain()
  54. *
  55. * will return the recommended dB level change for all samples analyzed
  56. * since InitGainAnalysis() was called and finalized with GetTitleGain().
  57. *
  58. * Pseudo-code to process an album:
  59. *
  60. * Float_t l_samples [4096];
  61. * Float_t r_samples [4096];
  62. * size_t num_samples;
  63. * unsigned int num_songs;
  64. * unsigned int i;
  65. *
  66. * InitGainAnalysis ( 44100 );
  67. * for ( i = 1; i <= num_songs; i++ ) {
  68. * while ( ( num_samples = getSongSamples ( song[i], left_samples, right_samples ) ) > 0 )
  69. * AnalyzeSamples ( left_samples, right_samples, num_samples, 2 );
  70. * fprintf ("Recommended dB change for song %2d: %+6.2f dB\n", i, GetTitleGain() );
  71. * }
  72. * fprintf ("Recommended dB change for whole album: %+6.2f dB\n", GetAlbumGain() );
  73. */
  74. /*
  75. * So here's the main source of potential code confusion:
  76. *
  77. * The filters applied to the incoming samples are IIR filters,
  78. * meaning they rely on up to <filter order> number of previous samples
  79. * AND up to <filter order> number of previous filtered samples.
  80. *
  81. * I set up the AnalyzeSamples routine to minimize memory usage and interface
  82. * complexity. The speed isn't compromised too much (I don't think), but the
  83. * internal complexity is higher than it should be for such a relatively
  84. * simple routine.
  85. *
  86. * Optimization/clarity suggestions are welcome.
  87. */
  88. #ifdef HAVE_CONFIG_H
  89. #include <config.h>
  90. #endif
  91. #include <stdio.h>
  92. #include <stdlib.h>
  93. #include <string.h>
  94. #include "lame.h"
  95. #include "machine.h"
  96. #include "gain_analysis.h"
  97. /* for each filter: */
  98. /* [0] 48 kHz, [1] 44.1 kHz, [2] 32 kHz, [3] 24 kHz, [4] 22050 Hz, [5] 16 kHz, [6] 12 kHz, [7] is 11025 Hz, [8] 8 kHz */
  99. #ifdef WIN32
  100. #pragma warning ( disable : 4305 )
  101. #endif
  102. /*lint -save -e736 loss of precision */
  103. static const Float_t ABYule[9][multiple_of(4, 2 * YULE_ORDER + 1)] = {
  104. /* 20 18 16 14 12 10 8 6 4 2 0 19 17 15 13 11 9 7 5 3 1 */
  105. { 0.00288463683916, 0.00012025322027, 0.00306428023191, 0.00594298065125, -0.02074045215285, 0.02161526843274, -0.01655260341619, -0.00009291677959, -0.00123395316851, -0.02160367184185, 0.03857599435200, 0.13919314567432, -0.86984376593551, 2.75465861874613, -5.87257861775999, 9.48293806319790,-12.28759895145294, 13.05504219327545,-11.34170355132042, 7.81501653005538, -3.84664617118067},
  106. {-0.00187763777362, 0.00674613682247, -0.00240879051584, 0.01624864962975, -0.02596338512915, 0.02245293253339, -0.00834990904936, -0.00851165645469, -0.00848709379851, -0.02911007808948, 0.05418656406430, 0.13149317958808, -0.75104302451432, 2.19611684890774, -4.39470996079559, 6.85401540936998, -8.81498681370155, 9.47693607801280, -8.54751527471874, 6.36317777566148, -3.47845948550071},
  107. {-0.00881362733839, 0.00651420667831, -0.01390589421898, 0.03174092540049, 0.00222312597743, 0.04781476674921, -0.05588393329856, 0.02163541888798, -0.06247880153653, -0.09331049056315, 0.15457299681924, 0.02347897407020, -0.05032077717131, 0.16378164858596, -0.45953458054983, 1.00595954808547, -1.67148153367602, 2.23697657451713, -2.64577170229825, 2.84868151156327, -2.37898834973084},
  108. {-0.02950134983287, 0.00205861885564, -0.00000828086748, 0.06276101321749, -0.00584456039913, -0.02364141202522, -0.00915702933434, 0.03282930172664, -0.08587323730772, -0.22613988682123, 0.30296907319327, 0.00302439095741, 0.02005851806501, 0.04500235387352, -0.22138138954925, 0.39120800788284, -0.22638893773906, -0.16276719120440, -0.25656257754070, 1.07977492259970, -1.61273165137247},
  109. {-0.01760176568150, -0.01635381384540, 0.00832043980773, 0.05724228140351, -0.00589500224440, -0.00469977914380, -0.07834489609479, 0.11921148675203, -0.11828570177555, -0.25572241425570, 0.33642304856132, 0.02977207319925, -0.04237348025746, 0.08333755284107, -0.04067510197014, -0.12453458140019, 0.47854794562326, -0.80774944671438, 0.12205022308084, 0.87350271418188, -1.49858979367799},
  110. { 0.00541907748707, -0.03193428438915, -0.01863887810927, 0.10478503600251, 0.04097565135648, -0.12398163381748, 0.04078262797139, -0.01419140100551, -0.22784394429749, -0.14351757464547, 0.44915256608450, 0.03222754072173, 0.05784820375801, 0.06747620744683, 0.00613424350682, 0.22199650564824, -0.42029820170918, 0.00213767857124, -0.37256372942400, 0.29661783706366, -0.62820619233671},
  111. {-0.00588215443421, -0.03788984554840, 0.08647503780351, 0.00647310677246, -0.27562961986224, 0.30931782841830, -0.18901604199609, 0.16744243493672, 0.16242137742230, -0.75464456939302, 0.56619470757641, 0.01807364323573, 0.01639907836189, -0.04784254229033, 0.06739368333110, -0.33032403314006, 0.45054734505008, 0.00819999645858, -0.26806001042947, 0.29156311971249, -1.04800335126349},
  112. {-0.00749618797172, -0.03721611395801, 0.06920467763959, 0.01628462406333, -0.25344790059353, 0.15558449135573, 0.02377945217615, 0.17520704835522, -0.14289799034253, -0.53174909058578, 0.58100494960553, 0.01818801111503, 0.02442357316099, -0.02505961724053, -0.05246019024463, -0.23313271880868, 0.38952639978999, 0.14728154134330, -0.20256413484477, -0.31863563325245, -0.51035327095184},
  113. {-0.02217936801134, 0.04788665548180, -0.04060034127000, -0.11202315195388, -0.02459864859345, 0.14590772289388, -0.10214864179676, 0.04267842219415, -0.00275953611929, -0.42163034350696, 0.53648789255105, 0.04704409688120, 0.05477720428674, -0.18823009262115, -0.17556493366449, 0.15113130533216, 0.26408300200955, -0.04678328784242, -0.03424681017675, -0.43193942311114, -0.25049871956020}
  114. };
  115. static const Float_t ABButter[9][multiple_of(4, 2 * BUTTER_ORDER + 1)] = {
  116. /* 5 4 3 2 1 */
  117. {0.98621192462708, 0.97261396931306, -1.97242384925416, -1.97223372919527, 0.98621192462708},
  118. {0.98500175787242, 0.97022847566350, -1.97000351574484, -1.96977855582618, 0.98500175787242},
  119. {0.97938932735214, 0.95920349965459, -1.95877865470428, -1.95835380975398, 0.97938932735214},
  120. {0.97531843204928, 0.95124613669835, -1.95063686409857, -1.95002759149878, 0.97531843204928},
  121. {0.97316523498161, 0.94705070426118, -1.94633046996323, -1.94561023566527, 0.97316523498161},
  122. {0.96454515552826, 0.93034775234268, -1.92909031105652, -1.92783286977036, 0.96454515552826},
  123. {0.96009142950541, 0.92177618768381, -1.92018285901082, -1.91858953033784, 0.96009142950541},
  124. {0.95856916599601, 0.91885558323625, -1.91713833199203, -1.91542108074780, 0.95856916599601},
  125. {0.94597685600279, 0.89487434461664, -1.89195371200558, -1.88903307939452, 0.94597685600279}
  126. };
  127. /*lint -restore */
  128. #ifdef WIN32
  129. #pragma warning ( default : 4305 )
  130. #endif
  131. /* When calling this procedure, make sure that ip[-order] and op[-order] point to real data! */
  132. static void
  133. filterYule(const Float_t * input, Float_t * output, size_t nSamples, const Float_t * const kernel)
  134. {
  135. while (nSamples--) {
  136. Float_t y0 = input[-10] * kernel[ 0];
  137. Float_t y2 = input[ -9] * kernel[ 1];
  138. Float_t y4 = input[ -8] * kernel[ 2];
  139. Float_t y6 = input[ -7] * kernel[ 3];
  140. Float_t s00 = y0 + y2 + y4 + y6;
  141. Float_t y8 = input[ -6] * kernel[ 4];
  142. Float_t yA = input[ -5] * kernel[ 5];
  143. Float_t yC = input[ -4] * kernel[ 6];
  144. Float_t yE = input[ -3] * kernel[ 7];
  145. Float_t s01 = y8 + yA + yC + yE;
  146. Float_t yG = input[ -2] * kernel[ 8] + input[ -1] * kernel[ 9];
  147. Float_t yK = input[ 0] * kernel[10];
  148. Float_t s1 = s00 + s01 + yG + yK;
  149. Float_t x1 = output[-10] * kernel[11] + output[ -9] * kernel[12];
  150. Float_t x5 = output[ -8] * kernel[13] + output[ -7] * kernel[14];
  151. Float_t x9 = output[ -6] * kernel[15] + output[ -5] * kernel[16];
  152. Float_t xD = output[ -4] * kernel[17] + output[ -3] * kernel[18];
  153. Float_t xH = output[ -2] * kernel[19] + output[ -1] * kernel[20];
  154. Float_t s2 = x1 + x5 + x9 + xD + xH;
  155. output[0] = (Float_t)(s1 - s2);
  156. ++output;
  157. ++input;
  158. }
  159. }
  160. static void
  161. filterButter(const Float_t * input, Float_t * output, size_t nSamples, const Float_t * const kernel)
  162. {
  163. while (nSamples--) {
  164. Float_t s1 = input[-2] * kernel[0] + input[-1] * kernel[2] + input[ 0] * kernel[4];
  165. Float_t s2 = output[-2] * kernel[1] + output[-1] * kernel[3];
  166. output[0] = (Float_t)(s1 - s2);
  167. ++output;
  168. ++input;
  169. }
  170. }
  171. static int ResetSampleFrequency(replaygain_t * rgData, long samplefreq);
  172. /* returns a INIT_GAIN_ANALYSIS_OK if successful, INIT_GAIN_ANALYSIS_ERROR if not */
  173. int
  174. ResetSampleFrequency(replaygain_t * rgData, long samplefreq)
  175. {
  176. /* zero out initial values, only first MAX_ORDER values */
  177. memset(rgData->linprebuf, 0, MAX_ORDER * sizeof(*rgData->linprebuf));
  178. memset(rgData->rinprebuf, 0, MAX_ORDER * sizeof(*rgData->rinprebuf));
  179. memset(rgData->lstepbuf, 0, MAX_ORDER * sizeof(*rgData->lstepbuf));
  180. memset(rgData->rstepbuf, 0, MAX_ORDER * sizeof(*rgData->rstepbuf));
  181. memset(rgData->loutbuf, 0, MAX_ORDER * sizeof(*rgData->loutbuf));
  182. memset(rgData->routbuf, 0, MAX_ORDER * sizeof(*rgData->routbuf));
  183. switch ((int) (samplefreq)) {
  184. case 48000:
  185. rgData->freqindex = 0;
  186. break;
  187. case 44100:
  188. rgData->freqindex = 1;
  189. break;
  190. case 32000:
  191. rgData->freqindex = 2;
  192. break;
  193. case 24000:
  194. rgData->freqindex = 3;
  195. break;
  196. case 22050:
  197. rgData->freqindex = 4;
  198. break;
  199. case 16000:
  200. rgData->freqindex = 5;
  201. break;
  202. case 12000:
  203. rgData->freqindex = 6;
  204. break;
  205. case 11025:
  206. rgData->freqindex = 7;
  207. break;
  208. case 8000:
  209. rgData->freqindex = 8;
  210. break;
  211. default:
  212. return INIT_GAIN_ANALYSIS_ERROR;
  213. }
  214. rgData->sampleWindow =
  215. (samplefreq * RMS_WINDOW_TIME_NUMERATOR + RMS_WINDOW_TIME_DENOMINATOR -
  216. 1) / RMS_WINDOW_TIME_DENOMINATOR;
  217. rgData->lsum = 0.;
  218. rgData->rsum = 0.;
  219. rgData->totsamp = 0;
  220. memset(rgData->A, 0, sizeof(rgData->A));
  221. return INIT_GAIN_ANALYSIS_OK;
  222. }
  223. int
  224. InitGainAnalysis(replaygain_t * rgData, long samplefreq)
  225. {
  226. if (ResetSampleFrequency(rgData, samplefreq) != INIT_GAIN_ANALYSIS_OK) {
  227. return INIT_GAIN_ANALYSIS_ERROR;
  228. }
  229. rgData->linpre = rgData->linprebuf + MAX_ORDER;
  230. rgData->rinpre = rgData->rinprebuf + MAX_ORDER;
  231. rgData->lstep = rgData->lstepbuf + MAX_ORDER;
  232. rgData->rstep = rgData->rstepbuf + MAX_ORDER;
  233. rgData->lout = rgData->loutbuf + MAX_ORDER;
  234. rgData->rout = rgData->routbuf + MAX_ORDER;
  235. memset(rgData->B, 0, sizeof(rgData->B));
  236. return INIT_GAIN_ANALYSIS_OK;
  237. }
  238. /* returns GAIN_ANALYSIS_OK if successful, GAIN_ANALYSIS_ERROR if not */
  239. int
  240. AnalyzeSamples(replaygain_t * rgData, const Float_t * left_samples, const Float_t * right_samples,
  241. size_t num_samples, int num_channels)
  242. {
  243. const Float_t *curleft;
  244. const Float_t *curright;
  245. long batchsamples;
  246. long cursamples;
  247. long cursamplepos;
  248. int i;
  249. Float_t sum_l, sum_r;
  250. if (num_samples == 0)
  251. return GAIN_ANALYSIS_OK;
  252. cursamplepos = 0;
  253. batchsamples = (long) num_samples;
  254. switch (num_channels) {
  255. case 1:
  256. right_samples = left_samples;
  257. break;
  258. case 2:
  259. break;
  260. default:
  261. return GAIN_ANALYSIS_ERROR;
  262. }
  263. if (num_samples < MAX_ORDER) {
  264. memcpy(rgData->linprebuf + MAX_ORDER, left_samples, num_samples * sizeof(Float_t));
  265. memcpy(rgData->rinprebuf + MAX_ORDER, right_samples, num_samples * sizeof(Float_t));
  266. }
  267. else {
  268. memcpy(rgData->linprebuf + MAX_ORDER, left_samples, MAX_ORDER * sizeof(Float_t));
  269. memcpy(rgData->rinprebuf + MAX_ORDER, right_samples, MAX_ORDER * sizeof(Float_t));
  270. }
  271. while (batchsamples > 0) {
  272. cursamples = batchsamples > rgData->sampleWindow - rgData->totsamp ?
  273. rgData->sampleWindow - rgData->totsamp : batchsamples;
  274. if (cursamplepos < MAX_ORDER) {
  275. curleft = rgData->linpre + cursamplepos;
  276. curright = rgData->rinpre + cursamplepos;
  277. if (cursamples > MAX_ORDER - cursamplepos)
  278. cursamples = MAX_ORDER - cursamplepos;
  279. }
  280. else {
  281. curleft = left_samples + cursamplepos;
  282. curright = right_samples + cursamplepos;
  283. }
  284. YULE_FILTER(curleft, rgData->lstep + rgData->totsamp, cursamples,
  285. ABYule[rgData->freqindex]);
  286. YULE_FILTER(curright, rgData->rstep + rgData->totsamp, cursamples,
  287. ABYule[rgData->freqindex]);
  288. BUTTER_FILTER(rgData->lstep + rgData->totsamp, rgData->lout + rgData->totsamp, cursamples,
  289. ABButter[rgData->freqindex]);
  290. BUTTER_FILTER(rgData->rstep + rgData->totsamp, rgData->rout + rgData->totsamp, cursamples,
  291. ABButter[rgData->freqindex]);
  292. curleft = rgData->lout + rgData->totsamp; /* Get the squared values */
  293. curright = rgData->rout + rgData->totsamp;
  294. sum_l = 0;
  295. sum_r = 0;
  296. i = cursamples & 0x03;
  297. while (i--) {
  298. Float_t const l = *curleft++;
  299. Float_t const r = *curright++;
  300. sum_l += l * l;
  301. sum_r += r * r;
  302. }
  303. i = cursamples / 4;
  304. while (i--) {
  305. Float_t l0 = curleft[0] * curleft[0];
  306. Float_t l1 = curleft[1] * curleft[1];
  307. Float_t l2 = curleft[2] * curleft[2];
  308. Float_t l3 = curleft[3] * curleft[3];
  309. Float_t sl = l0 + l1 + l2 + l3;
  310. Float_t r0 = curright[0] * curright[0];
  311. Float_t r1 = curright[1] * curright[1];
  312. Float_t r2 = curright[2] * curright[2];
  313. Float_t r3 = curright[3] * curright[3];
  314. Float_t sr = r0 + r1 + r2 + r3;
  315. sum_l += sl;
  316. curleft += 4;
  317. sum_r += sr;
  318. curright += 4;
  319. }
  320. rgData->lsum += sum_l;
  321. rgData->rsum += sum_r;
  322. batchsamples -= cursamples;
  323. cursamplepos += cursamples;
  324. rgData->totsamp += cursamples;
  325. if (rgData->totsamp == rgData->sampleWindow) { /* Get the Root Mean Square (RMS) for this set of samples */
  326. double const val =
  327. STEPS_per_dB * 10. * log10((rgData->lsum + rgData->rsum) / rgData->totsamp * 0.5 +
  328. 1.e-37);
  329. size_t ival = (val <= 0) ? 0 : (size_t) val;
  330. if (ival >= sizeof(rgData->A) / sizeof(*(rgData->A)))
  331. ival = sizeof(rgData->A) / sizeof(*(rgData->A)) - 1;
  332. rgData->A[ival]++;
  333. rgData->lsum = rgData->rsum = 0.;
  334. memmove(rgData->loutbuf, rgData->loutbuf + rgData->totsamp,
  335. MAX_ORDER * sizeof(Float_t));
  336. memmove(rgData->routbuf, rgData->routbuf + rgData->totsamp,
  337. MAX_ORDER * sizeof(Float_t));
  338. memmove(rgData->lstepbuf, rgData->lstepbuf + rgData->totsamp,
  339. MAX_ORDER * sizeof(Float_t));
  340. memmove(rgData->rstepbuf, rgData->rstepbuf + rgData->totsamp,
  341. MAX_ORDER * sizeof(Float_t));
  342. rgData->totsamp = 0;
  343. }
  344. if (rgData->totsamp > rgData->sampleWindow) /* somehow I really screwed up: Error in programming! Contact author about totsamp > sampleWindow */
  345. return GAIN_ANALYSIS_ERROR;
  346. }
  347. if (num_samples < MAX_ORDER) {
  348. memmove(rgData->linprebuf, rgData->linprebuf + num_samples,
  349. (MAX_ORDER - num_samples) * sizeof(Float_t));
  350. memmove(rgData->rinprebuf, rgData->rinprebuf + num_samples,
  351. (MAX_ORDER - num_samples) * sizeof(Float_t));
  352. memcpy(rgData->linprebuf + MAX_ORDER - num_samples, left_samples,
  353. num_samples * sizeof(Float_t));
  354. memcpy(rgData->rinprebuf + MAX_ORDER - num_samples, right_samples,
  355. num_samples * sizeof(Float_t));
  356. }
  357. else {
  358. memcpy(rgData->linprebuf, left_samples + num_samples - MAX_ORDER,
  359. MAX_ORDER * sizeof(Float_t));
  360. memcpy(rgData->rinprebuf, right_samples + num_samples - MAX_ORDER,
  361. MAX_ORDER * sizeof(Float_t));
  362. }
  363. return GAIN_ANALYSIS_OK;
  364. }
  365. static Float_t
  366. analyzeResult(uint32_t const *Array, size_t len)
  367. {
  368. uint32_t elems;
  369. uint32_t upper;
  370. uint32_t sum;
  371. size_t i;
  372. elems = 0;
  373. for (i = 0; i < len; i++)
  374. elems += Array[i];
  375. if (elems == 0)
  376. return GAIN_NOT_ENOUGH_SAMPLES;
  377. upper = (uint32_t) ceil(elems * (1. - RMS_PERCENTILE));
  378. sum = 0;
  379. for (i = len; i-- > 0;) {
  380. sum += Array[i];
  381. if (sum >= upper) {
  382. break;
  383. }
  384. }
  385. return (Float_t) ((Float_t) PINK_REF - (Float_t) i / (Float_t) STEPS_per_dB);
  386. }
  387. Float_t
  388. GetTitleGain(replaygain_t * rgData)
  389. {
  390. Float_t retval;
  391. unsigned int i;
  392. retval = analyzeResult(rgData->A, sizeof(rgData->A) / sizeof(*(rgData->A)));
  393. for (i = 0; i < sizeof(rgData->A) / sizeof(*(rgData->A)); i++) {
  394. rgData->B[i] += rgData->A[i];
  395. rgData->A[i] = 0;
  396. }
  397. for (i = 0; i < MAX_ORDER; i++)
  398. rgData->linprebuf[i] = rgData->lstepbuf[i]
  399. = rgData->loutbuf[i]
  400. = rgData->rinprebuf[i]
  401. = rgData->rstepbuf[i]
  402. = rgData->routbuf[i] = 0.f;
  403. rgData->totsamp = 0;
  404. rgData->lsum = rgData->rsum = 0.;
  405. return retval;
  406. }
  407. #if 0
  408. static Float_t GetAlbumGain(replaygain_t const* rgData);
  409. Float_t
  410. GetAlbumGain(replaygain_t const* rgData)
  411. {
  412. return analyzeResult(rgData->B, sizeof(rgData->B) / sizeof(*(rgData->B)));
  413. }
  414. #endif
  415. /* end of gain_analysis.c */