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/*
* ReplayGainAnalysis - analyzes input samples and give the recommended dB change
* Copyright ( C ) 2001 - 2009 David Robinson and Glen Sawyer
* Improvements and optimizations added by Frank Klemm , and by Marcel M <EFBFBD> ller
*
* This library is free software ; you can redistribute it and / or
* modify it under the terms of the GNU Lesser General Public
* License as published by the Free Software Foundation ; either
* version 2.1 of the License , or ( at your option ) any later version .
*
* This library is distributed in the hope that it will be useful ,
* but WITHOUT ANY WARRANTY ; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE . See the GNU
* Lesser General Public License for more details .
*
* You should have received a copy of the GNU Lesser General Public
* License along with this library ; if not , write to the Free Software
* Foundation , Inc . , 59 Temple Place , Suite 330 , Boston , MA 02111 - 1307 USA
*
* concept and filter values by David Robinson ( David @ Robinson . org )
* - - blame him if you think the idea is flawed
* original coding by Glen Sawyer ( mp3gain @ hotmail . com )
* - - blame him if you think this runs too slowly , or the coding is otherwise flawed
*
* lots of code improvements by Frank Klemm ( http : //www.uni-jena.de/~pfk/mpp/ )
* - - credit him for all the _good_ programming ; )
*
*
* For an explanation of the concepts and the basic algorithms involved , go to :
* http : //www.replaygain.org/
*/
/*
* Here ' s the deal . Call
*
* InitGainAnalysis ( long samplefreq ) ;
*
* to initialize everything . Call
*
* AnalyzeSamples ( const Float_t * left_samples ,
* const Float_t * right_samples ,
* size_t num_samples ,
* int num_channels ) ;
*
* as many times as you want , with as many or as few samples as you want .
* If mono , pass the sample buffer in through left_samples , leave
* right_samples NULL , and make sure num_channels = 1.
*
* GetTitleGain ( )
*
* will return the recommended dB level change for all samples analyzed
* SINCE THE LAST TIME you called GetTitleGain ( ) OR InitGainAnalysis ( ) .
*
* GetAlbumGain ( )
*
* will return the recommended dB level change for all samples analyzed
* since InitGainAnalysis ( ) was called and finalized with GetTitleGain ( ) .
*
* Pseudo - code to process an album :
*
* Float_t l_samples [ 4096 ] ;
* Float_t r_samples [ 4096 ] ;
* size_t num_samples ;
* unsigned int num_songs ;
* unsigned int i ;
*
* InitGainAnalysis ( 44100 ) ;
* for ( i = 1 ; i < = num_songs ; i + + ) {
* while ( ( num_samples = getSongSamples ( song [ i ] , left_samples , right_samples ) ) > 0 )
* AnalyzeSamples ( left_samples , right_samples , num_samples , 2 ) ;
* fprintf ( " Recommended dB change for song %2d: %+6.2f dB \n " , i , GetTitleGain ( ) ) ;
* }
* fprintf ( " Recommended dB change for whole album: %+6.2f dB \n " , GetAlbumGain ( ) ) ;
*/
/*
* So here ' s the main source of potential code confusion :
*
* The filters applied to the incoming samples are IIR filters ,
* meaning they rely on up to < filter order > number of previous samples
* AND up to < filter order > number of previous filtered samples .
*
* I set up the AnalyzeSamples routine to minimize memory usage and interface
* complexity . The speed isn ' t compromised too much ( I don ' t think ) , but the
* internal complexity is higher than it should be for such a relatively
* simple routine .
*
* Optimization / clarity suggestions are welcome .
*/
# include <stdio.h>
# include <string.h>
# include <stdint.h>
# include <math.h>
# include "gain_analysis.h"
# define RMS_PERCENTILE 0.95 // percentile which is louder than the proposed level
# define PINK_REF 64.82 //298640883795 // calibration value
// for each filter:
// [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
# ifdef WIN32
# ifndef __GNUC__
# pragma warning ( disable : 4305 )
# pragma warning ( disable : 4244 )
# endif
# endif
static const Float_t ABYule [ ] [ 2 * YULE_ORDER + 1 ] = {
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{ ( Float_t ) 0.006471345933032 , ( Float_t ) - 7.22103125152679 , ( Float_t ) - 0.02567678242161 , ( Float_t ) 24.7034187975904 , ( Float_t ) 0.049805860704367 , ( Float_t ) - 52.6825833623896 , ( Float_t ) - 0.05823001743528 , ( Float_t ) 77.4825736677539 , ( Float_t ) 0.040611847441914 , ( Float_t ) - 82.0074753444205 , ( Float_t ) - 0.010912036887501 , ( Float_t ) 63.1566097101925 , ( Float_t ) - 0.00901635868667 , ( Float_t ) - 34.889569769245 , ( Float_t ) 0.012448886238123 , ( Float_t ) 13.2126852760198 , ( Float_t ) - 0.007206683749426 , ( Float_t ) - 3.09445623301669 , ( Float_t ) 0.002167156433951 , ( Float_t ) 0.340344741393305 , ( Float_t ) - 0.000261819276949 } ,
{ ( Float_t ) 0.015415414474287 , ( Float_t ) - 7.19001570087017 , ( Float_t ) - 0.07691359399407 , ( Float_t ) 24.4109412087159 , ( Float_t ) 0.196677418516518 , ( Float_t ) - 51.6306373580801 , ( Float_t ) - 0.338855114128061 , ( Float_t ) 75.3978476863163 , ( Float_t ) 0.430094579594561 , ( Float_t ) - 79.4164552507386 , ( Float_t ) - 0.415015413747894 , ( Float_t ) 61.0373661948115 , ( Float_t ) 0.304942508151101 , ( Float_t ) - 33.7446462547014 , ( Float_t ) - 0.166191795926663 , ( Float_t ) 12.8168791146274 , ( Float_t ) 0.063198189938739 , ( Float_t ) - 3.01332198541437 , ( Float_t ) - 0.015003978694525 , ( Float_t ) 0.223619893831468 , ( Float_t ) 0.001748085184539 } ,
{ ( Float_t ) 0.021776466467053 , ( Float_t ) - 5.74819833657784 , ( Float_t ) - 0.062376961003801 , ( Float_t ) 16.246507961894 , ( Float_t ) 0.107731165328514 , ( Float_t ) - 29.9691822642542 , ( Float_t ) - 0.150994515142316 , ( Float_t ) 40.027597579378 , ( Float_t ) 0.170334807313632 , ( Float_t ) - 40.3209196052655 , ( Float_t ) - 0.157984942890531 , ( Float_t ) 30.8542077487718 , ( Float_t ) 0.121639833268721 , ( Float_t ) - 17.5965138737281 , ( Float_t ) - 0.074094040816409 , ( Float_t ) 7.10690214103873 , ( Float_t ) 0.031282852041061 , ( Float_t ) - 1.82175564515191 , ( Float_t ) - 0.00755421235941 , ( Float_t ) 0.223619893831468 , ( Float_t ) 0.00117925454213 } ,
{ ( Float_t ) 0.03857599435200 , ( Float_t ) - 3.84664617118067 , ( Float_t ) - 0.02160367184185 , ( Float_t ) 7.81501653005538 , ( Float_t ) - 0.00123395316851 , ( Float_t ) - 11.34170355132042 , ( Float_t ) - 0.00009291677959 , ( Float_t ) 13.05504219327545 , ( Float_t ) - 0.01655260341619 , ( Float_t ) - 12.28759895145294 , ( Float_t ) 0.02161526843274 , ( Float_t ) 9.48293806319790 , ( Float_t ) - 0.02074045215285 , ( Float_t ) - 5.87257861775999 , ( Float_t ) 0.00594298065125 , ( Float_t ) 2.75465861874613 , ( Float_t ) 0.00306428023191 , ( Float_t ) - 0.86984376593551 , ( Float_t ) 0.00012025322027 , ( Float_t ) 0.13919314567432 , ( Float_t ) 0.00288463683916 } ,
{ ( Float_t ) 0.05418656406430 , ( Float_t ) - 3.47845948550071 , ( Float_t ) - 0.02911007808948 , ( Float_t ) 6.36317777566148 , ( Float_t ) - 0.00848709379851 , ( Float_t ) - 8.54751527471874 , ( Float_t ) - 0.00851165645469 , ( Float_t ) 9.47693607801280 , ( Float_t ) - 0.00834990904936 , ( Float_t ) - 8.81498681370155 , ( Float_t ) 0.02245293253339 , ( Float_t ) 6.85401540936998 , ( Float_t ) - 0.02596338512915 , ( Float_t ) - 4.39470996079559 , ( Float_t ) 0.01624864962975 , ( Float_t ) 2.19611684890774 , ( Float_t ) - 0.00240879051584 , ( Float_t ) - 0.75104302451432 , ( Float_t ) 0.00674613682247 , ( Float_t ) 0.13149317958808 , ( Float_t ) - 0.00187763777362 } ,
{ ( Float_t ) 0.15457299681924 , ( Float_t ) - 2.37898834973084 , ( Float_t ) - 0.09331049056315 , ( Float_t ) 2.84868151156327 , ( Float_t ) - 0.06247880153653 , ( Float_t ) - 2.64577170229825 , ( Float_t ) 0.02163541888798 , ( Float_t ) 2.23697657451713 , ( Float_t ) - 0.05588393329856 , ( Float_t ) - 1.67148153367602 , ( Float_t ) 0.04781476674921 , ( Float_t ) 1.00595954808547 , ( Float_t ) 0.00222312597743 , ( Float_t ) - 0.45953458054983 , ( Float_t ) 0.03174092540049 , ( Float_t ) 0.16378164858596 , ( Float_t ) - 0.01390589421898 , ( Float_t ) - 0.05032077717131 , ( Float_t ) 0.00651420667831 , ( Float_t ) 0.02347897407020 , ( Float_t ) - 0.00881362733839 } ,
{ ( Float_t ) 0.30296907319327 , ( Float_t ) - 1.61273165137247 , ( Float_t ) - 0.22613988682123 , ( Float_t ) 1.07977492259970 , ( Float_t ) - 0.08587323730772 , ( Float_t ) - 0.25656257754070 , ( Float_t ) 0.03282930172664 , ( Float_t ) - 0.16276719120440 , ( Float_t ) - 0.00915702933434 , ( Float_t ) - 0.22638893773906 , ( Float_t ) - 0.02364141202522 , ( Float_t ) 0.39120800788284 , ( Float_t ) - 0.00584456039913 , ( Float_t ) - 0.22138138954925 , ( Float_t ) 0.06276101321749 , ( Float_t ) 0.04500235387352 , ( Float_t ) - 0.00000828086748 , ( Float_t ) 0.02005851806501 , ( Float_t ) 0.00205861885564 , ( Float_t ) 0.00302439095741 , ( Float_t ) - 0.02950134983287 } ,
{ ( Float_t ) 0.33642304856132 , ( Float_t ) - 1.49858979367799 , ( Float_t ) - 0.25572241425570 , ( Float_t ) 0.87350271418188 , ( Float_t ) - 0.11828570177555 , ( Float_t ) 0.12205022308084 , ( Float_t ) 0.11921148675203 , ( Float_t ) - 0.80774944671438 , ( Float_t ) - 0.07834489609479 , ( Float_t ) 0.47854794562326 , ( Float_t ) - 0.00469977914380 , ( Float_t ) - 0.12453458140019 , ( Float_t ) - 0.00589500224440 , ( Float_t ) - 0.04067510197014 , ( Float_t ) 0.05724228140351 , ( Float_t ) 0.08333755284107 , ( Float_t ) 0.00832043980773 , ( Float_t ) - 0.04237348025746 , ( Float_t ) - 0.01635381384540 , ( Float_t ) 0.02977207319925 , ( Float_t ) - 0.01760176568150 } ,
{ ( Float_t ) 0.44915256608450 , ( Float_t ) - 0.62820619233671 , ( Float_t ) - 0.14351757464547 , ( Float_t ) 0.29661783706366 , ( Float_t ) - 0.22784394429749 , ( Float_t ) - 0.37256372942400 , ( Float_t ) - 0.01419140100551 , ( Float_t ) 0.00213767857124 , ( Float_t ) 0.04078262797139 , ( Float_t ) - 0.42029820170918 , ( Float_t ) - 0.12398163381748 , ( Float_t ) 0.22199650564824 , ( Float_t ) 0.04097565135648 , ( Float_t ) 0.00613424350682 , ( Float_t ) 0.10478503600251 , ( Float_t ) 0.06747620744683 , ( Float_t ) - 0.01863887810927 , ( Float_t ) 0.05784820375801 , ( Float_t ) - 0.03193428438915 , ( Float_t ) 0.03222754072173 , ( Float_t ) 0.00541907748707 } ,
{ ( Float_t ) 0.56619470757641 , ( Float_t ) - 1.04800335126349 , ( Float_t ) - 0.75464456939302 , ( Float_t ) 0.29156311971249 , ( Float_t ) 0.16242137742230 , ( Float_t ) - 0.26806001042947 , ( Float_t ) 0.16744243493672 , ( Float_t ) 0.00819999645858 , ( Float_t ) - 0.18901604199609 , ( Float_t ) 0.45054734505008 , ( Float_t ) 0.30931782841830 , ( Float_t ) - 0.33032403314006 , ( Float_t ) - 0.27562961986224 , ( Float_t ) 0.06739368333110 , ( Float_t ) 0.00647310677246 , ( Float_t ) - 0.04784254229033 , ( Float_t ) 0.08647503780351 , ( Float_t ) 0.01639907836189 , ( Float_t ) - 0.03788984554840 , ( Float_t ) 0.01807364323573 , ( Float_t ) - 0.00588215443421 } ,
{ ( Float_t ) 0.58100494960553 , ( Float_t ) - 0.51035327095184 , ( Float_t ) - 0.53174909058578 , ( Float_t ) - 0.31863563325245 , ( Float_t ) - 0.14289799034253 , ( Float_t ) - 0.20256413484477 , ( Float_t ) 0.17520704835522 , ( Float_t ) 0.14728154134330 , ( Float_t ) 0.02377945217615 , ( Float_t ) 0.38952639978999 , ( Float_t ) 0.15558449135573 , ( Float_t ) - 0.23313271880868 , ( Float_t ) - 0.25344790059353 , ( Float_t ) - 0.05246019024463 , ( Float_t ) 0.01628462406333 , ( Float_t ) - 0.02505961724053 , ( Float_t ) 0.06920467763959 , ( Float_t ) 0.02442357316099 , ( Float_t ) - 0.03721611395801 , ( Float_t ) 0.01818801111503 , ( Float_t ) - 0.00749618797172 } ,
{ ( Float_t ) 0.53648789255105 , ( Float_t ) - 0.25049871956020 , ( Float_t ) - 0.42163034350696 , ( Float_t ) - 0.43193942311114 , ( Float_t ) - 0.00275953611929 , ( Float_t ) - 0.03424681017675 , ( Float_t ) 0.04267842219415 , ( Float_t ) - 0.04678328784242 , ( Float_t ) - 0.10214864179676 , ( Float_t ) 0.26408300200955 , ( Float_t ) 0.14590772289388 , ( Float_t ) 0.15113130533216 , ( Float_t ) - 0.02459864859345 , ( Float_t ) - 0.17556493366449 , ( Float_t ) - 0.11202315195388 , ( Float_t ) - 0.18823009262115 , ( Float_t ) - 0.04060034127000 , ( Float_t ) 0.05477720428674 , ( Float_t ) 0.04788665548180 , ( Float_t ) 0.04704409688120 , ( Float_t ) - 0.02217936801134 } ,
{ ( Float_t ) 0.38524531015142 , ( Float_t ) - 1.29708918404534 , ( Float_t ) - 0.27682212062067 , ( Float_t ) 0.90399339674203 , ( Float_t ) - 0.09980181488805 , ( Float_t ) - 0.29613799017877 , ( Float_t ) 0.09951486755646 , ( Float_t ) - 0.42326645916207 , ( Float_t ) - 0.08934020156622 , ( Float_t ) 0.37934887402200 , ( Float_t ) - 0.00322369330199 , ( Float_t ) - 0.37919795944938 , ( Float_t ) - 0.00110329090689 , ( Float_t ) 0.23410283284785 , ( Float_t ) 0.03784509844682 , ( Float_t ) - 0.03892971758879 , ( Float_t ) 0.01683906213303 , ( Float_t ) 0.00403009552351 , ( Float_t ) - 0.01147039862572 , ( Float_t ) 0.03640166626278 , ( Float_t ) - 0.01941767987192 } ,
{ ( Float_t ) 0.08717879977844 , ( Float_t ) - 2.62816311472146 , ( Float_t ) - 0.01000374016172 , ( Float_t ) 3.53734535817992 , ( Float_t ) - 0.06265852122368 , ( Float_t ) - 3.81003448678921 , ( Float_t ) - 0.01119328800950 , ( Float_t ) 3.91291636730132 , ( Float_t ) - 0.00114279372960 , ( Float_t ) - 3.53518605896288 , ( Float_t ) 0.02081333954769 , ( Float_t ) 2.71356866157873 , ( Float_t ) - 0.01603261863207 , ( Float_t ) - 1.86723311846592 , ( Float_t ) 0.01936763028546 , ( Float_t ) 1.12075382367659 , ( Float_t ) 0.00760044736442 , ( Float_t ) - 0.48574086886890 , ( Float_t ) - 0.00303979112271 , ( Float_t ) 0.11330544663849 , ( Float_t ) - 0.00075088605788 } ,
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} ;
static const Float_t ABButter [ ] [ 2 * BUTTER_ORDER + 1 ] = {
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{ ( Float_t ) 0.99308203517541 , ( Float_t ) - 1.98611621154089 , ( Float_t ) - 1.98616407035082 , ( Float_t ) 0.986211929160751 , ( Float_t ) 0.99308203517541 } ,
{ ( Float_t ) 0.992472550461293 , ( Float_t ) - 1.98488843762334 , ( Float_t ) - 1.98494510092258 , ( Float_t ) 0.979389350028798 , ( Float_t ) 0.992472550461293 } ,
{ ( Float_t ) 0.989641019334721 , ( Float_t ) - 1.97917472731008 , ( Float_t ) - 1.97928203866944 , ( Float_t ) 0.979389350028798 , ( Float_t ) 0.989641019334721 } ,
{ ( Float_t ) 0.98621192462708 , ( Float_t ) - 1.97223372919527 , ( Float_t ) - 1.97242384925416 , ( Float_t ) 0.97261396931306 , ( Float_t ) 0.98621192462708 } ,
{ ( Float_t ) 0.98500175787242 , ( Float_t ) - 1.96977855582618 , ( Float_t ) - 1.97000351574484 , ( Float_t ) 0.97022847566350 , ( Float_t ) 0.98500175787242 } ,
{ ( Float_t ) 0.97938932735214 , ( Float_t ) - 1.95835380975398 , ( Float_t ) - 1.95877865470428 , ( Float_t ) 0.95920349965459 , ( Float_t ) 0.97938932735214 } ,
{ ( Float_t ) 0.97531843204928 , ( Float_t ) - 1.95002759149878 , ( Float_t ) - 1.95063686409857 , ( Float_t ) 0.95124613669835 , ( Float_t ) 0.97531843204928 } ,
{ ( Float_t ) 0.97316523498161 , ( Float_t ) - 1.94561023566527 , ( Float_t ) - 1.94633046996323 , ( Float_t ) 0.94705070426118 , ( Float_t ) 0.97316523498161 } ,
{ ( Float_t ) 0.96454515552826 , ( Float_t ) - 1.92783286977036 , ( Float_t ) - 1.92909031105652 , ( Float_t ) 0.93034775234268 , ( Float_t ) 0.96454515552826 } ,
{ ( Float_t ) 0.96009142950541 , ( Float_t ) - 1.91858953033784 , ( Float_t ) - 1.92018285901082 , ( Float_t ) 0.92177618768381 , ( Float_t ) 0.96009142950541 } ,
{ ( Float_t ) 0.95856916599601 , ( Float_t ) - 1.91542108074780 , ( Float_t ) - 1.91713833199203 , ( Float_t ) 0.91885558323625 , ( Float_t ) 0.95856916599601 } ,
{ ( Float_t ) 0.94597685600279 , ( Float_t ) - 1.88903307939452 , ( Float_t ) - 1.89195371200558 , ( Float_t ) 0.89487434461664 , ( Float_t ) 0.94597685600279 } ,
{ ( Float_t ) 0.96535326815829 , ( Float_t ) - 1.92950577983524 , ( Float_t ) - 1.93070653631658 , ( Float_t ) 0.93190729279793 , ( Float_t ) 0.96535326815829 } ,
{ ( Float_t ) 0.98252400815195 , ( Float_t ) - 1.96474258269041 , ( Float_t ) - 1.96504801630391 , ( Float_t ) 0.96535344991740 , ( Float_t ) 0.98252400815195 } ,
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} ;
# ifdef WIN32
# ifndef __GNUC__
# pragma warning ( default : 4305 )
# endif
# endif
// When calling these filter procedures, make sure that ip[-order] and op[-order] point to real data!
// If your compiler complains that "'operation on 'output' may be undefined", you can
// either ignore the warnings or uncomment the three "y" lines (and comment out the indicated line)
void
GainAnalyzer : : filterYule ( const Float_t * input , Float_t * output , size_t nSamples , const Float_t * kernel )
{
while ( nSamples - - ) {
* output = 1e-10 f /* 1e-10 is a hack to avoid slowdown because of denormals */
+ input [ 0 ] * kernel [ 0 ]
- output [ - 1 ] * kernel [ 1 ]
+ input [ - 1 ] * kernel [ 2 ]
- output [ - 2 ] * kernel [ 3 ]
+ input [ - 2 ] * kernel [ 4 ]
- output [ - 3 ] * kernel [ 5 ]
+ input [ - 3 ] * kernel [ 6 ]
- output [ - 4 ] * kernel [ 7 ]
+ input [ - 4 ] * kernel [ 8 ]
- output [ - 5 ] * kernel [ 9 ]
+ input [ - 5 ] * kernel [ 10 ]
- output [ - 6 ] * kernel [ 11 ]
+ input [ - 6 ] * kernel [ 12 ]
- output [ - 7 ] * kernel [ 13 ]
+ input [ - 7 ] * kernel [ 14 ]
- output [ - 8 ] * kernel [ 15 ]
+ input [ - 8 ] * kernel [ 16 ]
- output [ - 9 ] * kernel [ 17 ]
+ input [ - 9 ] * kernel [ 18 ]
- output [ - 10 ] * kernel [ 19 ]
+ input [ - 10 ] * kernel [ 20 ] ;
+ + output ;
+ + input ;
}
}
void
GainAnalyzer : : filterButter ( const Float_t * input , Float_t * output , size_t nSamples , const Float_t * kernel ) {
while ( nSamples - - ) {
* output =
input [ 0 ] * kernel [ 0 ]
- output [ - 1 ] * kernel [ 1 ]
+ input [ - 1 ] * kernel [ 2 ]
- output [ - 2 ] * kernel [ 3 ]
+ input [ - 2 ] * kernel [ 4 ] ;
+ + output ;
+ + input ;
}
}
// returns a INIT_GAIN_ANALYSIS_OK if successful, INIT_GAIN_ANALYSIS_ERROR if not
int
GainAnalyzer : : ResetSampleFrequency ( int samplefreq ) {
int i ;
// zero out initial values
for ( i = 0 ; i < MAX_ORDER ; i + + )
linprebuf [ i ] = lstepbuf [ i ] = loutbuf [ i ] = rinprebuf [ i ] = rstepbuf [ i ] = routbuf [ i ] = ( Float_t ) 0. ;
switch ( ( int ) ( samplefreq ) ) {
case 96000 :
freqindex = 0 ;
break ;
case 88200 :
freqindex = 1 ;
break ;
case 64000 :
freqindex = 2 ;
break ;
case 49716 : // I could not find a table for this but we need to be able to handle this frequency for OPL, even if this means not getting the proper level.
case 48000 :
freqindex = 3 ;
break ;
case 44100 :
freqindex = 4 ;
break ;
case 32000 :
freqindex = 5 ;
break ;
case 24000 :
freqindex = 6 ;
break ;
case 22050 :
freqindex = 7 ;
break ;
case 16000 :
freqindex = 8 ;
break ;
case 12000 :
freqindex = 9 ;
break ;
case 11025 :
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case 11111 : // SW shareware tries to play a VOC with this frequency as music. This is close enough to 11025 to use the same table.
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freqindex = 10 ;
break ;
case 8000 :
freqindex = 11 ;
break ;
// These two were added for XA support.
case 18900 :
freqindex = 12 ;
break ;
case 37800 :
freqindex = 13 ;
break ;
default :
return INIT_GAIN_ANALYSIS_ERROR ;
}
sampleWindow = ( int ) ceil ( samplefreq * RMS_WINDOW_TIME ) ;
lsum = 0. ;
rsum = 0. ;
totsamp = 0 ;
memset ( A , 0 , sizeof ( A ) ) ;
return INIT_GAIN_ANALYSIS_OK ;
}
int
GainAnalyzer : : InitGainAnalysis ( int samplefreq ) {
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memset ( this , 0 , sizeof ( * this ) ) ;
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if ( ResetSampleFrequency ( samplefreq ) ! = INIT_GAIN_ANALYSIS_OK ) {
return INIT_GAIN_ANALYSIS_ERROR ;
}
linpre = linprebuf + MAX_ORDER ;
rinpre = rinprebuf + MAX_ORDER ;
lstep = lstepbuf + MAX_ORDER ;
rstep = rstepbuf + MAX_ORDER ;
lout = loutbuf + MAX_ORDER ;
rout = routbuf + MAX_ORDER ;
memset ( B , 0 , sizeof ( B ) ) ;
return INIT_GAIN_ANALYSIS_OK ;
}
// returns GAIN_ANALYSIS_OK if successful, GAIN_ANALYSIS_ERROR if not
static __inline double fsqr ( const double d ) {
return d * d ;
}
int
GainAnalyzer : : AnalyzeSamples ( const Float_t * left_samples , const Float_t * right_samples , size_t num_samples , int num_channels ) {
const Float_t * curleft ;
const Float_t * curright ;
int64_t batchsamples ;
int64_t cursamples ;
int64_t cursamplepos ;
int i ;
if ( num_samples = = 0 )
return GAIN_ANALYSIS_OK ;
cursamplepos = 0 ;
batchsamples = ( int64_t ) num_samples ;
switch ( num_channels ) {
case 1 :
right_samples = left_samples ;
case 2 :
break ;
default :
return GAIN_ANALYSIS_ERROR ;
}
if ( num_samples < MAX_ORDER ) {
memcpy ( linprebuf + MAX_ORDER , left_samples , num_samples * sizeof ( Float_t ) ) ;
memcpy ( rinprebuf + MAX_ORDER , right_samples , num_samples * sizeof ( Float_t ) ) ;
} else {
memcpy ( linprebuf + MAX_ORDER , left_samples , MAX_ORDER * sizeof ( Float_t ) ) ;
memcpy ( rinprebuf + MAX_ORDER , right_samples , MAX_ORDER * sizeof ( Float_t ) ) ;
}
while ( batchsamples > 0 ) {
cursamples = batchsamples > sampleWindow - totsamp ? sampleWindow - totsamp : batchsamples ;
if ( cursamplepos < MAX_ORDER ) {
curleft = linpre + cursamplepos ;
curright = rinpre + cursamplepos ;
if ( cursamples > MAX_ORDER - cursamplepos )
cursamples = MAX_ORDER - cursamplepos ;
} else {
curleft = left_samples + cursamplepos ;
curright = right_samples + cursamplepos ;
}
filterYule ( curleft , lstep + totsamp , cursamples , ABYule [ freqindex ] ) ;
filterYule ( curright , rstep + totsamp , cursamples , ABYule [ freqindex ] ) ;
filterButter ( lstep + totsamp , lout + totsamp , cursamples , ABButter [ freqindex ] ) ;
filterButter ( rstep + totsamp , rout + totsamp , cursamples , ABButter [ freqindex ] ) ;
curleft = lout + totsamp ; // Get the squared values
curright = rout + totsamp ;
i = cursamples % 16 ;
while ( i - - ) {
lsum + = fsqr ( * curleft + + ) ;
rsum + = fsqr ( * curright + + ) ;
}
i = cursamples / 16 ;
while ( i - - ) {
lsum + = fsqr ( curleft [ 0 ] )
+ fsqr ( curleft [ 1 ] )
+ fsqr ( curleft [ 2 ] )
+ fsqr ( curleft [ 3 ] )
+ fsqr ( curleft [ 4 ] )
+ fsqr ( curleft [ 5 ] )
+ fsqr ( curleft [ 6 ] )
+ fsqr ( curleft [ 7 ] )
+ fsqr ( curleft [ 8 ] )
+ fsqr ( curleft [ 9 ] )
+ fsqr ( curleft [ 10 ] )
+ fsqr ( curleft [ 11 ] )
+ fsqr ( curleft [ 12 ] )
+ fsqr ( curleft [ 13 ] )
+ fsqr ( curleft [ 14 ] )
+ fsqr ( curleft [ 15 ] ) ;
curleft + = 16 ;
rsum + = fsqr ( curright [ 0 ] )
+ fsqr ( curright [ 1 ] )
+ fsqr ( curright [ 2 ] )
+ fsqr ( curright [ 3 ] )
+ fsqr ( curright [ 4 ] )
+ fsqr ( curright [ 5 ] )
+ fsqr ( curright [ 6 ] )
+ fsqr ( curright [ 7 ] )
+ fsqr ( curright [ 8 ] )
+ fsqr ( curright [ 9 ] )
+ fsqr ( curright [ 10 ] )
+ fsqr ( curright [ 11 ] )
+ fsqr ( curright [ 12 ] )
+ fsqr ( curright [ 13 ] )
+ fsqr ( curright [ 14 ] )
+ fsqr ( curright [ 15 ] ) ;
curright + = 16 ;
}
batchsamples - = cursamples ;
cursamplepos + = cursamples ;
totsamp + = cursamples ;
if ( totsamp = = sampleWindow ) { // Get the Root Mean Square (RMS) for this set of samples
double val = STEPS_per_dB * 10. * log10 ( ( lsum + rsum ) / totsamp * 0.5 + 1.e-37 ) ;
int ival = ( int ) val ;
if ( ival < 0 ) ival = 0 ;
if ( ival > = ( int ) ( sizeof ( A ) / sizeof ( * A ) ) ) ival = sizeof ( A ) / sizeof ( * A ) - 1 ;
A [ ival ] + + ;
lsum = rsum = 0. ;
memmove ( loutbuf , loutbuf + totsamp , MAX_ORDER * sizeof ( Float_t ) ) ;
memmove ( routbuf , routbuf + totsamp , MAX_ORDER * sizeof ( Float_t ) ) ;
memmove ( lstepbuf , lstepbuf + totsamp , MAX_ORDER * sizeof ( Float_t ) ) ;
memmove ( rstepbuf , rstepbuf + totsamp , MAX_ORDER * sizeof ( Float_t ) ) ;
totsamp = 0 ;
}
if ( totsamp >
sampleWindow ) // somehow I really screwed up: Error in programming! Contact author about totsamp > sampleWindow
return GAIN_ANALYSIS_ERROR ;
}
if ( num_samples < MAX_ORDER ) {
memmove ( linprebuf , linprebuf + num_samples , ( MAX_ORDER - num_samples ) * sizeof ( Float_t ) ) ;
memmove ( rinprebuf , rinprebuf + num_samples , ( MAX_ORDER - num_samples ) * sizeof ( Float_t ) ) ;
memcpy ( linprebuf + MAX_ORDER - num_samples , left_samples , num_samples * sizeof ( Float_t ) ) ;
memcpy ( rinprebuf + MAX_ORDER - num_samples , right_samples , num_samples * sizeof ( Float_t ) ) ;
} else {
memcpy ( linprebuf , left_samples + num_samples - MAX_ORDER , MAX_ORDER * sizeof ( Float_t ) ) ;
memcpy ( rinprebuf , right_samples + num_samples - MAX_ORDER , MAX_ORDER * sizeof ( Float_t ) ) ;
}
return GAIN_ANALYSIS_OK ;
}
Float_t
GainAnalyzer : : analyzeResult ( const unsigned int * Array , size_t len ) {
unsigned int elems ;
signed int upper ;
size_t i ;
elems = 0 ;
for ( i = 0 ; i < len ; i + + )
elems + = Array [ i ] ;
if ( elems = = 0 )
return GAIN_NOT_ENOUGH_SAMPLES ;
upper = ( signed int ) ceil ( elems * ( 1. - RMS_PERCENTILE ) ) ;
for ( i = len ; i - - > 0 ; ) {
if ( ( upper - = Array [ i ] ) < = 0 )
break ;
}
return ( Float_t ) ( ( Float_t ) PINK_REF - ( Float_t ) i / ( Float_t ) STEPS_per_dB ) ;
}
Float_t
GainAnalyzer : : GetTitleGain ( void ) {
Float_t retval ;
int i ;
retval = analyzeResult ( A , sizeof ( A ) / sizeof ( * A ) ) ;
for ( i = 0 ; i < ( int ) ( sizeof ( A ) / sizeof ( * A ) ) ; i + + ) {
B [ i ] + = A [ i ] ;
A [ i ] = 0 ;
}
for ( i = 0 ; i < MAX_ORDER ; i + + )
linprebuf [ i ] = lstepbuf [ i ] = loutbuf [ i ] = rinprebuf [ i ] = rstepbuf [ i ] = routbuf [ i ] = 0.f ;
totsamp = 0 ;
lsum = rsum = 0. ;
return retval ;
}
Float_t
GainAnalyzer : : GetAlbumGain ( void ) {
return analyzeResult ( B , sizeof ( B ) / sizeof ( * B ) ) ;
}
/* end of gain_analysis.c */
