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487 lines
25 KiB
C++
487 lines
25 KiB
C++
/*
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* ReplayGainAnalysis - analyzes input samples and give the recommended dB change
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* Copyright (C) 2001-2009 David Robinson and Glen Sawyer
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* Improvements and optimizations added by Frank Klemm, and by Marcel M<>ller
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*
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* This library is free software; you can redistribute it and/or
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* modify it under the terms of the GNU Lesser General Public
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* License as published by the Free Software Foundation; either
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* version 2.1 of the License, or (at your option) any later version.
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*
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* This library is distributed in the hope that it will be useful,
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* but WITHOUT ANY WARRANTY; without even the implied warranty of
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* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
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* Lesser General Public License for more details.
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*
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* You should have received a copy of the GNU Lesser General Public
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* License along with this library; if not, write to the Free Software
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* Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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*
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* concept and filter values by David Robinson (David@Robinson.org)
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* -- blame him if you think the idea is flawed
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* original coding by Glen Sawyer (mp3gain@hotmail.com)
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* -- blame him if you think this runs too slowly, or the coding is otherwise flawed
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*
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* lots of code improvements by Frank Klemm ( http://www.uni-jena.de/~pfk/mpp/ )
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* -- credit him for all the _good_ programming ;)
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*
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*
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* For an explanation of the concepts and the basic algorithms involved, go to:
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* http://www.replaygain.org/
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*/
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/*
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* Here's the deal. Call
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*
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* InitGainAnalysis ( long samplefreq );
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*
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* to initialize everything. Call
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*
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* AnalyzeSamples ( const Float_t* left_samples,
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* const Float_t* right_samples,
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* size_t num_samples,
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* int num_channels );
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*
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* as many times as you want, with as many or as few samples as you want.
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* If mono, pass the sample buffer in through left_samples, leave
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* right_samples NULL, and make sure num_channels = 1.
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*
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* GetTitleGain()
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*
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* will return the recommended dB level change for all samples analyzed
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* SINCE THE LAST TIME you called GetTitleGain() OR InitGainAnalysis().
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*
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* GetAlbumGain()
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*
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* will return the recommended dB level change for all samples analyzed
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* since InitGainAnalysis() was called and finalized with GetTitleGain().
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*
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* Pseudo-code to process an album:
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*
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* Float_t l_samples [4096];
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* Float_t r_samples [4096];
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* size_t num_samples;
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* unsigned int num_songs;
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* unsigned int i;
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*
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* InitGainAnalysis ( 44100 );
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* for ( i = 1; i <= num_songs; i++ ) {
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* while ( ( num_samples = getSongSamples ( song[i], left_samples, right_samples ) ) > 0 )
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* AnalyzeSamples ( left_samples, right_samples, num_samples, 2 );
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* fprintf ("Recommended dB change for song %2d: %+6.2f dB\n", i, GetTitleGain() );
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* }
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* fprintf ("Recommended dB change for whole album: %+6.2f dB\n", GetAlbumGain() );
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*/
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/*
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* So here's the main source of potential code confusion:
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*
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* The filters applied to the incoming samples are IIR filters,
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* meaning they rely on up to <filter order> number of previous samples
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* AND up to <filter order> number of previous filtered samples.
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*
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* I set up the AnalyzeSamples routine to minimize memory usage and interface
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* complexity. The speed isn't compromised too much (I don't think), but the
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* internal complexity is higher than it should be for such a relatively
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* simple routine.
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*
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* Optimization/clarity suggestions are welcome.
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*/
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#include <stdio.h>
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#include <string.h>
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#include <stdint.h>
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#include <math.h>
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#include "gain_analysis.h"
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#define RMS_PERCENTILE 0.95 // percentile which is louder than the proposed level
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#define PINK_REF 64.82 //298640883795 // calibration value
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// for each filter:
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// [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
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#ifdef WIN32
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#ifndef __GNUC__
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#pragma warning ( disable : 4305 )
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#pragma warning ( disable : 4244 )
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#endif
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#endif
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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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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},
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{(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 },
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{(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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};
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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},
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{(Float_t) 0.992472550461293, (Float_t) -1.98488843762334, (Float_t) -1.98494510092258, (Float_t) 0.979389350028798, (Float_t) 0.992472550461293},
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{(Float_t) 0.989641019334721, (Float_t) -1.97917472731008, (Float_t) -1.97928203866944, (Float_t) 0.979389350028798, (Float_t) 0.989641019334721},
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{(Float_t) 0.98621192462708, (Float_t) -1.97223372919527, (Float_t) -1.97242384925416, (Float_t) 0.97261396931306, (Float_t) 0.98621192462708},
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{(Float_t) 0.98500175787242, (Float_t) -1.96977855582618, (Float_t) -1.97000351574484, (Float_t) 0.97022847566350, (Float_t) 0.98500175787242},
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{(Float_t) 0.97938932735214, (Float_t) -1.95835380975398, (Float_t) -1.95877865470428, (Float_t) 0.95920349965459, (Float_t) 0.97938932735214},
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{(Float_t) 0.97531843204928, (Float_t) -1.95002759149878, (Float_t) -1.95063686409857, (Float_t) 0.95124613669835, (Float_t) 0.97531843204928},
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{(Float_t) 0.97316523498161, (Float_t) -1.94561023566527, (Float_t) -1.94633046996323, (Float_t) 0.94705070426118, (Float_t) 0.97316523498161},
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{(Float_t) 0.96454515552826, (Float_t) -1.92783286977036, (Float_t) -1.92909031105652, (Float_t) 0.93034775234268, (Float_t) 0.96454515552826},
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{(Float_t) 0.96009142950541, (Float_t) -1.91858953033784, (Float_t) -1.92018285901082, (Float_t) 0.92177618768381, (Float_t) 0.96009142950541},
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{(Float_t) 0.95856916599601, (Float_t) -1.91542108074780, (Float_t) -1.91713833199203, (Float_t) 0.91885558323625, (Float_t) 0.95856916599601},
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{(Float_t) 0.94597685600279, (Float_t) -1.88903307939452, (Float_t) -1.89195371200558, (Float_t) 0.89487434461664, (Float_t) 0.94597685600279},
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{(Float_t)0.96535326815829, (Float_t)-1.92950577983524, (Float_t)-1.93070653631658, (Float_t)0.93190729279793, (Float_t)0.96535326815829 },
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{(Float_t)0.98252400815195, (Float_t)-1.96474258269041, (Float_t)-1.96504801630391, (Float_t)0.96535344991740, (Float_t)0.98252400815195 },
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};
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#ifdef WIN32
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#ifndef __GNUC__
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#pragma warning ( default : 4305 )
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#endif
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#endif
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// When calling these filter procedures, make sure that ip[-order] and op[-order] point to real data!
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// If your compiler complains that "'operation on 'output' may be undefined", you can
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// either ignore the warnings or uncomment the three "y" lines (and comment out the indicated line)
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void
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GainAnalyzer::filterYule(const Float_t *input, Float_t *output, size_t nSamples, const Float_t *kernel)
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{
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while (nSamples--) {
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*output = 1e-10f /* 1e-10 is a hack to avoid slowdown because of denormals */
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+ input[0] * kernel[0]
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- output[-1] * kernel[1]
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+ input[-1] * kernel[2]
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- output[-2] * kernel[3]
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+ input[-2] * kernel[4]
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- output[-3] * kernel[5]
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+ input[-3] * kernel[6]
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- output[-4] * kernel[7]
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+ input[-4] * kernel[8]
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- output[-5] * kernel[9]
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+ input[-5] * kernel[10]
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- output[-6] * kernel[11]
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+ input[-6] * kernel[12]
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- output[-7] * kernel[13]
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+ input[-7] * kernel[14]
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- output[-8] * kernel[15]
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+ input[-8] * kernel[16]
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- output[-9] * kernel[17]
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+ input[-9] * kernel[18]
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- output[-10] * kernel[19]
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||
+ 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:
|
||
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.
|
||
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) {
|
||
*this = {};
|
||
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 */
|