1035 lines
47 KiB
C#
1035 lines
47 KiB
C#
/* Copyright (C) 2007-2008 Jean-Marc Valin
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Copyright (C) 2008 Thorvald Natvig
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Ported to C# by Logan Stromberg
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File: Resampler.cs
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Arbitrary resampling code
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Redistribution and use in source and binary forms, with or without
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modification, are permitted provided that the following conditions are
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met:
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1. Redistributions of source code must retain the above copyright notice,
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this list of conditions and the following disclaimer.
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2. Redistributions in binary form must reproduce the above copyright
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notice, this list of conditions and the following disclaimer in the
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documentation and/or other materials provided with the distribution.
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3. The name of the author may not be used to endorse or promote products
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derived from this software without specific prior written permission.
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THIS SOFTWARE IS PROVIDED BY THE AUTHOR ``AS IS'' AND ANY EXPRESS OR
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IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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DISCLAIMED. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY DIRECT,
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INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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(INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION)
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HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT,
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STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
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ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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POSSIBILITY OF SUCH DAMAGE.
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*/
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/*
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The design goals of this code are:
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- Very fast algorithm
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- SIMD-friendly algorithm
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- Low memory requirement
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- Good *perceptual* quality (and not best SNR)
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Warning: This resampler is relatively new. Although I think I got rid of
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all the major bugs and I don't expect the API to change anymore, there
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may be something I've missed. So use with caution.
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This algorithm is based on this original resampling algorithm:
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Smith, Julius O. Digital Audio Resampling Home Page
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Center for Computer Research in Music and Acoustics (CCRMA),
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Stanford University, 2007.
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Web published at http://www-ccrma.stanford.edu/~jos/resample/.
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There is one main difference, though. This resampler uses cubic
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interpolation instead of linear interpolation in the above paper. This
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makes the table much smaller and makes it possible to compute that table
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on a per-stream basis. In turn, being able to tweak the table for each
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stream makes it possible to both reduce complexity on simple ratios
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(e.g. 2/3), and get rid of the rounding operations in the inner loop.
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The latter both reduces CPU time and makes the algorithm more SIMD-friendly.
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*/
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using Concentus.Celt;
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using Concentus.Common.CPlusPlus;
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using System;
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namespace Concentus.Common
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{
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/// <summary>
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/// Arbitrary-rate audio resampler originally implemented for the Speex codec.
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/// </summary>
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public class SpeexResampler
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{
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private const int FIXED_STACK_ALLOC = 8192;
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#region Encoder state
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private int in_rate = 0;
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private int out_rate = 0;
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private int num_rate = 0;
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private int den_rate = 0;
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private int quality = 0;
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private int nb_channels = 0;
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private int filt_len = 0;
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private int mem_alloc_size = 0;
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private int buffer_size = 0;
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private int int_advance = 0;
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private int frac_advance = 0;
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private float cutoff = 0;
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private int oversample = 0;
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private int initialised = 0;
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private int started = 0;
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/* These are per-channel */
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private int[] last_sample = null;
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private int[] samp_frac_num = null;
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private int[] magic_samples = null;
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private short[] mem = null;
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private short[] sinc_table = null;
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private int sinc_table_length = 0;
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private resampler_basic_func resampler_ptr = null;
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int in_stride = 0;
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int out_stride = 0;
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#endregion
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#region Helper classes and tables
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private class FuncDef
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{
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public FuncDef(double[] t, int os)
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{
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table = t;
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oversample = os;
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}
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public double[] table;
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public int oversample;
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public static readonly double[] kaiser12_table/*[68]*/ = {
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0.99859849, 1.00000000, 0.99859849, 0.99440475, 0.98745105, 0.97779076,
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0.96549770, 0.95066529, 0.93340547, 0.91384741, 0.89213598, 0.86843014,
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0.84290116, 0.81573067, 0.78710866, 0.75723148, 0.72629970, 0.69451601,
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0.66208321, 0.62920216, 0.59606986, 0.56287762, 0.52980938, 0.49704014,
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0.46473455, 0.43304576, 0.40211431, 0.37206735, 0.34301800, 0.31506490,
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0.28829195, 0.26276832, 0.23854851, 0.21567274, 0.19416736, 0.17404546,
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0.15530766, 0.13794294, 0.12192957, 0.10723616, 0.09382272, 0.08164178,
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0.07063950, 0.06075685, 0.05193064, 0.04409466, 0.03718069, 0.03111947,
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0.02584161, 0.02127838, 0.01736250, 0.01402878, 0.01121463, 0.00886058,
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0.00691064, 0.00531256, 0.00401805, 0.00298291, 0.00216702, 0.00153438,
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0.00105297, 0.00069463, 0.00043489, 0.00025272, 0.00013031, 0.0000527734,
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0.00001000, 0.00000000};
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/*
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static double kaiser12_table[36] = {
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0.99440475, 1.00000000, 0.99440475, 0.97779076, 0.95066529, 0.91384741,
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0.86843014, 0.81573067, 0.75723148, 0.69451601, 0.62920216, 0.56287762,
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0.49704014, 0.43304576, 0.37206735, 0.31506490, 0.26276832, 0.21567274,
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0.17404546, 0.13794294, 0.10723616, 0.08164178, 0.06075685, 0.04409466,
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0.03111947, 0.02127838, 0.01402878, 0.00886058, 0.00531256, 0.00298291,
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0.00153438, 0.00069463, 0.00025272, 0.0000527734, 0.00000500, 0.00000000};
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*/
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public static readonly double[] kaiser10_table/*[36]*/ = {
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0.99537781, 1.00000000, 0.99537781, 0.98162644, 0.95908712, 0.92831446,
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0.89005583, 0.84522401, 0.79486424, 0.74011713, 0.68217934, 0.62226347,
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0.56155915, 0.50119680, 0.44221549, 0.38553619, 0.33194107, 0.28205962,
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0.23636152, 0.19515633, 0.15859932, 0.12670280, 0.09935205, 0.07632451,
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0.05731132, 0.04193980, 0.02979584, 0.02044510, 0.01345224, 0.00839739,
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0.00488951, 0.00257636, 0.00115101, 0.00035515, 0.00000000, 0.00000000};
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public static readonly double[] kaiser8_table/*[36]*/ = {
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0.99635258, 1.00000000, 0.99635258, 0.98548012, 0.96759014, 0.94302200,
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0.91223751, 0.87580811, 0.83439927, 0.78875245, 0.73966538, 0.68797126,
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0.63451750, 0.58014482, 0.52566725, 0.47185369, 0.41941150, 0.36897272,
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0.32108304, 0.27619388, 0.23465776, 0.19672670, 0.16255380, 0.13219758,
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0.10562887, 0.08273982, 0.06335451, 0.04724088, 0.03412321, 0.02369490,
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0.01563093, 0.00959968, 0.00527363, 0.00233883, 0.00050000, 0.00000000};
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public static readonly double[] kaiser6_table/*[36]*/ = {
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0.99733006, 1.00000000, 0.99733006, 0.98935595, 0.97618418, 0.95799003,
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0.93501423, 0.90755855, 0.87598009, 0.84068475, 0.80211977, 0.76076565,
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0.71712752, 0.67172623, 0.62508937, 0.57774224, 0.53019925, 0.48295561,
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0.43647969, 0.39120616, 0.34752997, 0.30580127, 0.26632152, 0.22934058,
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0.19505503, 0.16360756, 0.13508755, 0.10953262, 0.08693120, 0.06722600,
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0.05031820, 0.03607231, 0.02432151, 0.01487334, 0.00752000, 0.00000000};
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};
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private class QualityMapping
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{
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public int base_length = 0;
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public int oversample = 0;
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public float downsample_bandwidth = 0;
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public float upsample_bandwidth = 0;
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public FuncDef window_func = null;
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private QualityMapping(int bl, int os, float dsb, float usb, FuncDef wf)
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{
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base_length = bl;
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oversample = os;
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downsample_bandwidth = dsb;
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upsample_bandwidth = usb;
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window_func = wf;
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}
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/* This table maps conversion quality to private parameters. There are two
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reasons that explain why the up-sampling bandwidth is larger than the
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down-sampling bandwidth:
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1) When up-sampling, we can assume that the spectrum is already attenuated
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close to the Nyquist rate (from an A/D or a previous resampling filter)
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2) Any aliasing that occurs very close to the Nyquist rate will be masked
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by the sinusoids/noise just below the Nyquist rate (guaranteed only for
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up-sampling).
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*/
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public static readonly QualityMapping[] quality_map = {
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new QualityMapping( 8, 4, 0.830f, 0.860f, new FuncDef(FuncDef.kaiser6_table, 32) ), /* Q0 */
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new QualityMapping( 16, 4, 0.850f, 0.880f, new FuncDef(FuncDef.kaiser6_table, 32) ), /* Q1 */
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new QualityMapping( 32, 4, 0.882f, 0.910f, new FuncDef(FuncDef.kaiser6_table, 32) ), /* Q2 */ /* 82.3% cutoff ( ~60 dB stop) 6 */
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new QualityMapping( 48, 8, 0.895f, 0.917f, new FuncDef(FuncDef.kaiser8_table, 32) ), /* Q3 */ /* 84.9% cutoff ( ~80 dB stop) 8 */
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new QualityMapping( 64, 8, 0.921f, 0.940f, new FuncDef(FuncDef.kaiser8_table, 32) ), /* Q4 */ /* 88.7% cutoff ( ~80 dB stop) 8 */
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new QualityMapping( 80, 16, 0.922f, 0.940f, new FuncDef(FuncDef.kaiser10_table, 32)), /* Q5 */ /* 89.1% cutoff (~100 dB stop) 10 */
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new QualityMapping( 96, 16, 0.940f, 0.945f, new FuncDef(FuncDef.kaiser10_table, 32)), /* Q6 */ /* 91.5% cutoff (~100 dB stop) 10 */
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new QualityMapping(128, 16, 0.950f, 0.950f, new FuncDef(FuncDef.kaiser10_table, 32)), /* Q7 */ /* 93.1% cutoff (~100 dB stop) 10 */
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new QualityMapping(160, 16, 0.960f, 0.960f, new FuncDef(FuncDef.kaiser10_table, 32)), /* Q8 */ /* 94.5% cutoff (~100 dB stop) 10 */
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new QualityMapping(192, 32, 0.968f, 0.968f, new FuncDef(FuncDef.kaiser12_table, 64)), /* Q9 */ /* 95.5% cutoff (~100 dB stop) 10 */
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new QualityMapping(256, 32, 0.975f, 0.975f, new FuncDef(FuncDef.kaiser12_table, 64)), /* Q10 */ /* 96.6% cutoff (~100 dB stop) 10 */
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};
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}
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#endregion
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#region Private code
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/// <summary>
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/// typedef int (* resampler_basic_func)(SpeexResamplerState*, int , Pointer<short>, int *, Pointer<short>, Pointer<int>);
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/// </summary>
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private delegate int resampler_basic_func(int channel_index, short[] input, int input_ptr, ref int in_len, short[] output, int output_ptr, ref int out_len);
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private static short WORD2INT(float x)
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{
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return x < short.MinValue ? short.MinValue : (x > short.MaxValue ? short.MaxValue : (short)x);
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}
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/*8,24,40,56,80,104,128,160,200,256,320*/
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private static double compute_func(float x, FuncDef func)
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{
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float y, frac;
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double interp0, interp1, interp2, interp3;
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int ind;
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y = x * func.oversample;
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ind = (int)Math.Floor(y);
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frac = (y - ind);
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/* CSE with handle the repeated powers */
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interp3 = -0.1666666667 * frac + 0.1666666667 * (frac * frac * frac);
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interp2 = frac + 0.5 * (frac * frac) - 0.5 * (frac * frac * frac);
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/*interp[2] = 1.f - 0.5f*frac - frac*frac + 0.5f*frac*frac*frac;*/
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interp0 = -0.3333333333 * frac + 0.5 * (frac * frac) - 0.1666666667 * (frac * frac * frac);
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/* Just to make sure we don't have rounding problems */
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interp1 = 1.0f - interp3 - interp2 - interp0;
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/*sum = frac*accum[1] + (1-frac)*accum[2];*/
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return interp0 * func.table[ind] + interp1 * func.table[ind + 1] + interp2 * func.table[ind + 2] + interp3 * func.table[ind + 3];
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}
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/* The slow way of computing a sinc for the table. Should improve that some day */
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private static short sinc(float cutoff, float x, int N, FuncDef window_func)
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{
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/*fprintf (stderr, "%f ", x);*/
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float xx = x * cutoff;
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if (Math.Abs(x) < 1e-6f)
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return WORD2INT(32768.0f * cutoff);
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else if (Math.Abs(x) > .5f * N)
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return 0;
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/*FIXME: Can it really be any slower than this? */
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return WORD2INT(32768.0f * cutoff * (float)Math.Sin((float)Math.PI * xx) / ((float)Math.PI * xx) * (float)compute_func(Math.Abs(2.0f * x / N), window_func));
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}
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private static void cubic_coef(short x, out short interp0, out short interp1, out short interp2, out short interp3)
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{
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/* Compute interpolation coefficients. I'm not sure whether this corresponds to cubic interpolation
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but I know it's MMSE-optimal on a sinc */
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short x2, x3;
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x2 = Inlines.MULT16_16_P15(x, x);
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x3 = Inlines.MULT16_16_P15(x, x2);
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interp0 = (short)Inlines.PSHR32(Inlines.MULT16_16(Inlines.QCONST16(-0.16667f, 15), x) + Inlines.MULT16_16(Inlines.QCONST16(0.16667f, 15), x3), 15);
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interp1 = Inlines.EXTRACT16(Inlines.EXTEND32(x) + Inlines.SHR32(Inlines.SUB32(Inlines.EXTEND32(x2), Inlines.EXTEND32(x3)), 1));
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interp3 = (short)Inlines.PSHR32(Inlines.MULT16_16(Inlines.QCONST16(-0.33333f, 15), x) + Inlines.MULT16_16(Inlines.QCONST16(.5f, 15), x2) - Inlines.MULT16_16(Inlines.QCONST16(0.16667f, 15), x3), 15);
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/* Just to make sure we don't have rounding problems */
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interp2 = (short)(CeltConstants.Q15_ONE - interp0 - interp1 - interp3);
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if (interp2 < 32767)
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interp2 += 1;
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}
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private int resampler_basic_direct_single(int channel_index, short[] input, int input_ptr, ref int in_len, short[] output, int output_ptr, ref int out_len)
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{
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int N = this.filt_len;
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int out_sample = 0;
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int last_sample = this.last_sample[channel_index];
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int samp_frac_num = this.samp_frac_num[channel_index];
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int sum;
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while (!(last_sample >= in_len || out_sample >= out_len))
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{
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int sinct = (int)samp_frac_num * N;
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int iptr = input_ptr + last_sample;
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int j;
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sum = 0;
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for (j = 0; j < N; j++)
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{
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sum += Inlines.MULT16_16(this.sinc_table[sinct + j], input[iptr + j]);
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}
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output[output_ptr + (this.out_stride * out_sample++)] = Inlines.SATURATE16(Inlines.PSHR32(sum, 15));
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last_sample += this.int_advance;
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samp_frac_num += (int)this.frac_advance;
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if (samp_frac_num >= this.den_rate)
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{
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samp_frac_num -= this.den_rate;
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last_sample++;
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}
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}
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this.last_sample[channel_index] = last_sample;
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this.samp_frac_num[channel_index] = samp_frac_num;
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return out_sample;
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}
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private int resampler_basic_interpolate_single(int channel_index, short[] input, int input_ptr, ref int in_len, short[] output, int output_ptr, ref int out_len)
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{
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int N = this.filt_len;
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int out_sample = 0;
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int last_sample = this.last_sample[channel_index];
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int samp_frac_num = this.samp_frac_num[channel_index];
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int sum;
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while (!(last_sample >= in_len || out_sample >= out_len))
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{
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int iptr = input_ptr + last_sample;
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int offset = samp_frac_num * this.oversample / this.den_rate;
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short frac = (short)Inlines.PDIV32(Inlines.SHL32((samp_frac_num * this.oversample) % this.den_rate, 15), this.den_rate);
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short interp0, interp1, interp2, interp3;
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int j;
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int accum0 = 0;
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int accum1 = 0;
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int accum2 = 0;
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int accum3 = 0;
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for (j = 0; j < N; j++)
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{
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short curr_in = input[iptr + j];
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accum0 += Inlines.MULT16_16(curr_in, this.sinc_table[4 + (j + 1) * (int)this.oversample - offset - 2]);
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accum1 += Inlines.MULT16_16(curr_in, this.sinc_table[4 + (j + 1) * (int)this.oversample - offset - 1]);
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accum2 += Inlines.MULT16_16(curr_in, this.sinc_table[4 + (j + 1) * (int)this.oversample - offset]);
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accum3 += Inlines.MULT16_16(curr_in, this.sinc_table[4 + (j + 1) * (int)this.oversample - offset + 1]);
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}
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cubic_coef(frac, out interp0, out interp1, out interp2, out interp3);
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sum = Inlines.MULT16_32_Q15(interp0, Inlines.SHR32(accum0, 1)) +
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Inlines.MULT16_32_Q15(interp1, Inlines.SHR32(accum1, 1)) +
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Inlines.MULT16_32_Q15(interp2, Inlines.SHR32(accum2, 1)) +
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Inlines.MULT16_32_Q15(interp3, Inlines.SHR32(accum3, 1));
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output[output_ptr + (out_stride * out_sample++)] = Inlines.SATURATE16(Inlines.PSHR32(sum, 14));
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last_sample += int_advance;
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samp_frac_num += (int)frac_advance;
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if (samp_frac_num >= den_rate)
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{
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samp_frac_num -= den_rate;
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last_sample++;
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}
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}
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this.last_sample[channel_index] = last_sample;
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this.samp_frac_num[channel_index] = samp_frac_num;
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return out_sample;
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}
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private void update_filter()
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{
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int old_length;
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old_length = this.filt_len;
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this.oversample = QualityMapping.quality_map[this.quality].oversample;
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this.filt_len = QualityMapping.quality_map[this.quality].base_length;
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|
if (this.num_rate > this.den_rate)
|
|
{
|
|
/* down-sampling */
|
|
this.cutoff = QualityMapping.quality_map[this.quality].downsample_bandwidth * this.den_rate / this.num_rate;
|
|
/* FIXME: divide the numerator and denominator by a certain amount if they're too large */
|
|
this.filt_len = this.filt_len * this.num_rate / this.den_rate;
|
|
/* Round up to make sure we have a multiple of 8 */
|
|
this.filt_len = ((this.filt_len - 1) & (~0x7)) + 8;
|
|
if (2 * this.den_rate < this.num_rate)
|
|
this.oversample >>= 1;
|
|
if (4 * this.den_rate < this.num_rate)
|
|
this.oversample >>= 1;
|
|
if (8 * this.den_rate < this.num_rate)
|
|
this.oversample >>= 1;
|
|
if (16 * this.den_rate < this.num_rate)
|
|
this.oversample >>= 1;
|
|
if (this.oversample < 1)
|
|
this.oversample = 1;
|
|
}
|
|
else {
|
|
/* up-sampling */
|
|
this.cutoff = QualityMapping.quality_map[this.quality].upsample_bandwidth;
|
|
}
|
|
|
|
if (this.den_rate <= 16 * (this.oversample + 8))
|
|
{
|
|
int i;
|
|
if (this.sinc_table == null)
|
|
this.sinc_table = new short[this.filt_len * this.den_rate];
|
|
else if (this.sinc_table_length < this.filt_len * this.den_rate)
|
|
{
|
|
this.sinc_table = new short[this.filt_len * this.den_rate];
|
|
this.sinc_table_length = this.filt_len * this.den_rate;
|
|
}
|
|
for (i = 0; i < this.den_rate; i++)
|
|
{
|
|
int j;
|
|
for (j = 0; j < this.filt_len; j++)
|
|
{
|
|
this.sinc_table[i * this.filt_len + j] = sinc(this.cutoff, ((j - (int)this.filt_len / 2 + 1) - ((float)i) / this.den_rate), this.filt_len, QualityMapping.quality_map[this.quality].window_func);
|
|
}
|
|
}
|
|
this.resampler_ptr = resampler_basic_direct_single;
|
|
/*fprintf (stderr, "resampler uses direct sinc table and normalised cutoff %f\n", cutoff);*/
|
|
}
|
|
else {
|
|
int i;
|
|
if (this.sinc_table == null)
|
|
this.sinc_table = new short[this.filt_len * this.oversample + 8];
|
|
else if (this.sinc_table_length < this.filt_len * this.oversample + 8)
|
|
{
|
|
this.sinc_table = new short[this.filt_len * this.oversample + 8];
|
|
this.sinc_table_length = this.filt_len * this.oversample + 8;
|
|
}
|
|
for (i = -4; i < (int)(this.oversample * this.filt_len + 4); i++)
|
|
this.sinc_table[i + 4] = sinc(this.cutoff, (i / (float)this.oversample - this.filt_len / 2), this.filt_len, QualityMapping.quality_map[this.quality].window_func);
|
|
this.resampler_ptr = resampler_basic_interpolate_single;
|
|
/*fprintf (stderr, "resampler uses interpolated sinc table and normalised cutoff %f\n", cutoff);*/
|
|
}
|
|
this.int_advance = this.num_rate / this.den_rate;
|
|
this.frac_advance = this.num_rate % this.den_rate;
|
|
|
|
|
|
/* Here's the place where we update the filter memory to take into account
|
|
the change in filter length. It's probably the messiest part of the code
|
|
due to handling of lots of corner cases. */
|
|
if (this.mem == null)
|
|
{
|
|
int i;
|
|
this.mem_alloc_size = this.filt_len - 1 + this.buffer_size;
|
|
this.mem = new short[this.nb_channels * this.mem_alloc_size];
|
|
for (i = 0; i < this.nb_channels * this.mem_alloc_size; i++)
|
|
this.mem[i] = 0;
|
|
/*speex_warning("init filter");*/
|
|
}
|
|
else if (this.started == 0)
|
|
{
|
|
int i;
|
|
this.mem_alloc_size = this.filt_len - 1 + this.buffer_size;
|
|
this.mem = new short[this.nb_channels * this.mem_alloc_size];
|
|
for (i = 0; i < this.nb_channels * this.mem_alloc_size; i++)
|
|
this.mem[i] = 0;
|
|
/*speex_warning("reinit filter");*/
|
|
}
|
|
else if (this.filt_len > old_length)
|
|
{
|
|
int i;
|
|
/* Increase the filter length */
|
|
/*speex_warning("increase filter size");*/
|
|
int old_alloc_size = this.mem_alloc_size;
|
|
if ((this.filt_len - 1 + this.buffer_size) > this.mem_alloc_size)
|
|
{
|
|
this.mem_alloc_size = this.filt_len - 1 + this.buffer_size;
|
|
this.mem = new short[this.nb_channels * this.mem_alloc_size];
|
|
}
|
|
for (i = this.nb_channels - 1; i >= 0; i--)
|
|
{
|
|
int j;
|
|
int olen = old_length;
|
|
/*if (st.magic_samples[i])*/
|
|
{
|
|
/* Try and remove the magic samples as if nothing had happened */
|
|
|
|
/* FIXME: This is wrong but for now we need it to avoid going over the array bounds */
|
|
olen = old_length + 2 * this.magic_samples[i];
|
|
for (j = old_length - 2 + this.magic_samples[i]; j >= 0; j--)
|
|
this.mem[i * this.mem_alloc_size + j + this.magic_samples[i]] = this.mem[i * old_alloc_size + j];
|
|
for (j = 0; j < this.magic_samples[i]; j++)
|
|
this.mem[i * this.mem_alloc_size + j] = 0;
|
|
this.magic_samples[i] = 0;
|
|
}
|
|
if (this.filt_len > olen)
|
|
{
|
|
/* If the new filter length is still bigger than the "augmented" length */
|
|
/* Copy data going backward */
|
|
for (j = 0; j < olen - 1; j++)
|
|
this.mem[i * this.mem_alloc_size + (this.filt_len - 2 - j)] = this.mem[i * this.mem_alloc_size + (olen - 2 - j)];
|
|
/* Then put zeros for lack of anything better */
|
|
for (; j < this.filt_len - 1; j++)
|
|
this.mem[i * this.mem_alloc_size + (this.filt_len - 2 - j)] = 0;
|
|
/* Adjust last_sample */
|
|
this.last_sample[i] += (this.filt_len - olen) / 2;
|
|
}
|
|
else {
|
|
/* Put back some of the magic! */
|
|
this.magic_samples[i] = (olen - this.filt_len) / 2;
|
|
for (j = 0; j < this.filt_len - 1 + this.magic_samples[i]; j++)
|
|
this.mem[i * this.mem_alloc_size + j] = this.mem[i * this.mem_alloc_size + j + this.magic_samples[i]];
|
|
}
|
|
}
|
|
}
|
|
else if (this.filt_len < old_length)
|
|
{
|
|
int i;
|
|
/* Reduce filter length, this a bit tricky. We need to store some of the memory as "magic"
|
|
samples so they can be used directly as input the next time(s) */
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
{
|
|
int j;
|
|
int old_magic = this.magic_samples[i];
|
|
this.magic_samples[i] = (old_length - this.filt_len) / 2;
|
|
/* We must copy some of the memory that's no longer used */
|
|
/* Copy data going backward */
|
|
for (j = 0; j < this.filt_len - 1 + this.magic_samples[i] + old_magic; j++)
|
|
this.mem[i * this.mem_alloc_size + j] = this.mem[i * this.mem_alloc_size + j + this.magic_samples[i]];
|
|
this.magic_samples[i] += old_magic;
|
|
}
|
|
}
|
|
}
|
|
|
|
private void speex_resampler_process_native(int channel_index, ref int in_len, short[] output, int output_ptr, ref int out_len)
|
|
{
|
|
int j = 0;
|
|
int N = this.filt_len;
|
|
int out_sample = 0;
|
|
int mem_ptr = channel_index * this.mem_alloc_size;
|
|
int ilen;
|
|
|
|
this.started = 1;
|
|
|
|
/* Call the right resampler through the function ptr */
|
|
out_sample = this.resampler_ptr(channel_index, this.mem, mem_ptr, ref in_len, output, output_ptr, ref out_len);
|
|
|
|
if (this.last_sample[channel_index] < (int)in_len)
|
|
in_len = this.last_sample[channel_index];
|
|
out_len = out_sample;
|
|
this.last_sample[channel_index] -= in_len;
|
|
|
|
ilen = in_len;
|
|
|
|
for (j = mem_ptr; j < N - 1 + mem_ptr; ++j)
|
|
this.mem[j] = this.mem[j + ilen];
|
|
}
|
|
|
|
private int speex_resampler_magic(int channel_index, short[] output, ref int output_ptr, int out_len)
|
|
{
|
|
int tmp_in_len = this.magic_samples[channel_index];
|
|
int mem_ptr = channel_index * this.mem_alloc_size;
|
|
int N = this.filt_len;
|
|
|
|
this.speex_resampler_process_native(channel_index, ref tmp_in_len, output, output_ptr, ref out_len);
|
|
|
|
this.magic_samples[channel_index] -= tmp_in_len;
|
|
|
|
/* If we couldn't process all "magic" input samples, save the rest for next time */
|
|
if (this.magic_samples[channel_index] != 0)
|
|
{
|
|
int i;
|
|
for (i = mem_ptr; i < this.magic_samples[channel_index] + mem_ptr; i++)
|
|
this.mem[N - 1 + i] = this.mem[N - 1 + i + tmp_in_len];
|
|
}
|
|
output_ptr += out_len * this.out_stride;
|
|
return out_len;
|
|
}
|
|
|
|
#endregion
|
|
|
|
#region Public API
|
|
|
|
/// <summary>
|
|
/// Create a new resampler with integer input and output rates (in hertz).
|
|
/// </summary>
|
|
/// <param name="nb_channels">The number of channels to be processed</param>
|
|
/// <param name="in_rate">Input sampling rate, in hertz</param>
|
|
/// <param name="out_rate">Output sampling rate, in hertz</param>
|
|
/// <param name="quality">Resampling quality, from 0 to 10</param>
|
|
public SpeexResampler(int nb_channels, int in_rate, int out_rate, int quality) : this(nb_channels, in_rate, out_rate, in_rate, out_rate, quality)
|
|
{
|
|
}
|
|
|
|
/// <summary>
|
|
/// Create a new resampler with fractional input/output rates. The sampling
|
|
/// rate ratio is an arbitrary rational number with both the numerator and
|
|
/// denominator being 32-bit integers.
|
|
/// </summary>
|
|
/// <param name="nb_channels">The number of channels to be processed</param>
|
|
/// <param name="ratio_num">Numerator of sampling rate ratio</param>
|
|
/// <param name="ratio_den">Denominator of sampling rate ratio</param>
|
|
/// <param name="in_rate">Input sample rate rounded to the nearest integer (in hz)</param>
|
|
/// <param name="out_rate">Output sample rate rounded to the nearest integer (in hz)</param>
|
|
/// <param name="quality">Resampling quality, from 0 to 10</param>
|
|
/// <returns>A newly created restampler</returns>
|
|
public SpeexResampler(int nb_channels, int ratio_num, int ratio_den, int in_rate, int out_rate, int quality)
|
|
{
|
|
int i;
|
|
if (quality > 10 || quality < 0)
|
|
{
|
|
throw new ArgumentException("Quality must be between 0 and 10");
|
|
}
|
|
this.initialised = 0;
|
|
this.started = 0;
|
|
this.in_rate = 0;
|
|
this.out_rate = 0;
|
|
this.num_rate = 0;
|
|
this.den_rate = 0;
|
|
this.quality = -1;
|
|
this.sinc_table_length = 0;
|
|
this.mem_alloc_size = 0;
|
|
this.filt_len = 0;
|
|
this.mem = null;
|
|
this.resampler_ptr = null;
|
|
this.cutoff = 1.0f;
|
|
this.nb_channels = nb_channels;
|
|
this.in_stride = 1;
|
|
this.out_stride = 1;
|
|
this.buffer_size = 160;
|
|
|
|
/* Per channel data */
|
|
this.last_sample = new int[nb_channels];
|
|
this.magic_samples = new int[nb_channels];
|
|
this.samp_frac_num = new int[nb_channels];
|
|
for (i = 0; i < nb_channels; i++)
|
|
{
|
|
this.last_sample[i] = 0;
|
|
this.magic_samples[i] = 0;
|
|
this.samp_frac_num[i] = 0;
|
|
}
|
|
|
|
this.Quality = quality;
|
|
this.SetRateFraction(ratio_num, ratio_den, in_rate, out_rate);
|
|
|
|
this.update_filter();
|
|
|
|
this.initialised = 1;
|
|
}
|
|
|
|
public static SpeexResampler Create(int nb_channels, int in_rate, int out_rate, int quality)
|
|
{
|
|
return new SpeexResampler(nb_channels, in_rate, out_rate, in_rate, out_rate, quality);
|
|
}
|
|
|
|
/// <summary>
|
|
/// DEPRECATED. Use the regular constructor instead.
|
|
/// </summary>
|
|
public static SpeexResampler Create(int nb_channels, int ratio_num, int ratio_den, int in_rate, int out_rate, int quality)
|
|
{
|
|
return new SpeexResampler(nb_channels, ratio_num, ratio_den, in_rate, out_rate, quality);
|
|
}
|
|
|
|
/// <summary>
|
|
/// Resample an int array. The input and output buffers must *not* overlap
|
|
/// </summary>
|
|
/// <param name="channel_index">The index of the channel to process (for multichannel input, 0 otherwise)</param>
|
|
/// <param name="input">Input buffer</param>
|
|
/// <param name="input_ptr">Offset to start from when reading input</param>
|
|
/// <param name="in_len">Number of input samples in the input buffer. After this function returns, this value
|
|
/// will be set to the number of input samples actually processed</param>
|
|
/// <param name="output">Output buffer</param>
|
|
/// <param name="output_ptr">Offset to start from when writing output</param>
|
|
/// <param name="out_len">Size of the output buffer. After this function returns, this value will be set to the number
|
|
/// of output samples actually produced</param>
|
|
public void Process(int channel_index, short[] input, int input_ptr, ref int in_len, short[] output, int output_ptr, ref int out_len)
|
|
{
|
|
int j;
|
|
int ilen = in_len;
|
|
int olen = out_len;
|
|
int x = channel_index * this.mem_alloc_size;
|
|
int filt_offs = this.filt_len - 1;
|
|
int xlen = this.mem_alloc_size - filt_offs;
|
|
int istride = this.in_stride;
|
|
|
|
if (this.magic_samples[channel_index] != 0)
|
|
{
|
|
|
|
olen -= this.speex_resampler_magic(channel_index, output, ref output_ptr, olen);
|
|
|
|
}
|
|
if (this.magic_samples[channel_index] == 0)
|
|
{
|
|
while (ilen != 0 && olen != 0)
|
|
{
|
|
int ichunk = (ilen > xlen) ? xlen : ilen;
|
|
int ochunk = olen;
|
|
|
|
if (input != null)
|
|
{
|
|
for (j = 0; j < ichunk; ++j)
|
|
this.mem[x + j + filt_offs] = input[input_ptr + j * istride];
|
|
}
|
|
else {
|
|
for (j = 0; j < ichunk; ++j)
|
|
|
|
this.mem[x + j + filt_offs] = 0;
|
|
}
|
|
this.speex_resampler_process_native(channel_index, ref ichunk, output, output_ptr, ref ochunk);
|
|
ilen -= ichunk;
|
|
olen -= ochunk;
|
|
output_ptr += ochunk * this.out_stride;
|
|
if (input != null)
|
|
|
|
input_ptr += ichunk * istride;
|
|
}
|
|
}
|
|
in_len -= ilen;
|
|
out_len -= olen;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Resample a float array array. The input and output buffers must *not* overlap
|
|
/// </summary>
|
|
/// <param name="channel_index">The index of the channel to process (for multichannel input, 0 otherwise)</param>
|
|
/// <param name="input">Input buffer</param>
|
|
/// <param name="input_ptr">Offset to start from when reading input</param>
|
|
/// <param name="in_len">Number of input samples in the input buffer. After this function returns, this value
|
|
/// will be set to the number of input samples actually processed</param>
|
|
/// <param name="output">Output buffer</param>
|
|
/// <param name="output_ptr">Offset to start from when writing output</param>
|
|
/// <param name="out_len">Size of the output buffer. After this function returns, this value will be set to the number
|
|
/// of output samples actually produced</param>
|
|
public void Process(int channel_index, float[] input, int input_ptr, ref int in_len, float[] output, int output_ptr, ref int out_len)
|
|
{
|
|
int j;
|
|
int istride_save = this.in_stride;
|
|
int ostride_save = this.out_stride;
|
|
int ilen = in_len;
|
|
int olen = out_len;
|
|
int x = channel_index * this.mem_alloc_size;
|
|
int xlen = this.mem_alloc_size - (this.filt_len - 1);
|
|
int ylen = (olen < FIXED_STACK_ALLOC) ? olen : FIXED_STACK_ALLOC;
|
|
short[] ystack = new short[ylen];
|
|
|
|
this.out_stride = 1;
|
|
|
|
while (ilen != 0 && olen != 0)
|
|
{
|
|
|
|
int y = 0;
|
|
int ichunk = (ilen > xlen) ? xlen : ilen;
|
|
int ochunk = (olen > ylen) ? ylen : olen;
|
|
int omagic = 0;
|
|
|
|
if (this.magic_samples[channel_index] != 0)
|
|
{
|
|
|
|
omagic = this.speex_resampler_magic(channel_index, ystack, ref y, ochunk);
|
|
|
|
ochunk -= omagic;
|
|
olen -= omagic;
|
|
}
|
|
if (this.magic_samples[channel_index] == 0)
|
|
{
|
|
if (input != null)
|
|
{
|
|
for (j = 0; j < ichunk; ++j)
|
|
this.mem[x + j + this.filt_len - 1] = WORD2INT(input[input_ptr + j * istride_save]);
|
|
}
|
|
else {
|
|
for (j = 0; j < ichunk; ++j)
|
|
this.mem[x + j + this.filt_len - 1] = 0;
|
|
}
|
|
|
|
this.speex_resampler_process_native(channel_index, ref ichunk, ystack, y, ref ochunk);
|
|
}
|
|
else {
|
|
ichunk = 0;
|
|
ochunk = 0;
|
|
}
|
|
|
|
for (j = 0; j < ochunk + omagic; ++j)
|
|
output[output_ptr + j * ostride_save] = ystack[j];
|
|
|
|
ilen -= ichunk;
|
|
olen -= ochunk;
|
|
output_ptr += ((ochunk + omagic) * ostride_save);
|
|
if (input != null)
|
|
input_ptr += ichunk * istride_save;
|
|
}
|
|
this.out_stride = ostride_save;
|
|
in_len -= ilen;
|
|
out_len -= olen;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Resamples an interleaved int array. The stride is automatically determined by the number of channels of the resampler.
|
|
/// </summary>
|
|
/// <param name="input">Input buffer</param>
|
|
/// <param name="input_ptr">Offset to start from when reading input</param>
|
|
/// <param name="in_len">The number of samples *PER-CHANNEL* in the input buffer. After this function returns, this
|
|
/// value will be set to the number of input samples actually processed</param>
|
|
/// <param name="output">Output buffer</param>
|
|
/// <param name="output_ptr">Offset to start from when writing output</param>
|
|
/// <param name="out_len">The size of the output buffer in samples-per-channel. After this function returns, this value
|
|
/// will be set to the number of samples per channel actually produced</param>
|
|
public void ProcessInterleaved(float[] input, int input_ptr, ref int in_len, float[] output, int output_ptr, ref int out_len)
|
|
{
|
|
int i;
|
|
int istride_save, ostride_save;
|
|
int bak_out_len = out_len;
|
|
int bak_in_len = in_len;
|
|
istride_save = this.in_stride;
|
|
ostride_save = this.out_stride;
|
|
this.in_stride = this.out_stride = this.nb_channels;
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
{
|
|
out_len = bak_out_len;
|
|
in_len = bak_in_len;
|
|
if (input != null)
|
|
this.Process(i, input, input_ptr + i, ref in_len, output, output_ptr + i, ref out_len);
|
|
else
|
|
this.Process(i, null, 0, ref in_len, output, output_ptr + i, ref out_len);
|
|
}
|
|
this.in_stride = istride_save;
|
|
this.out_stride = ostride_save;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Resamples an interleaved float array. The stride is automatically determined by the number of channels of the resampler.
|
|
/// </summary>
|
|
/// <param name="input">Input buffer</param>
|
|
/// <param name="input_ptr">Offset to start from when reading input</param>
|
|
/// <param name="in_len">The number of samples *PER-CHANNEL* in the input buffer. After this function returns, this
|
|
/// value will be set to the number of input samples actually processed</param>
|
|
/// <param name="output">Output buffer</param>
|
|
/// <param name="output_ptr">Offset to start from when writing output</param>
|
|
/// <param name="out_len">The size of the output buffer in samples-per-channel. After this function returns, this value
|
|
/// will be set to the number of samples per channel actually produced</param>
|
|
public void ProcessInterleaved(short[] input, int input_ptr, ref int in_len, short[] output, int output_ptr, ref int out_len)
|
|
{
|
|
int i;
|
|
int istride_save, ostride_save;
|
|
int bak_out_len = out_len;
|
|
int bak_in_len = in_len;
|
|
istride_save = this.in_stride;
|
|
ostride_save = this.out_stride;
|
|
this.in_stride = this.out_stride = this.nb_channels;
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
{
|
|
out_len = bak_out_len;
|
|
in_len = bak_in_len;
|
|
if (input != null)
|
|
this.Process(i, input, input_ptr + i, ref in_len, output, output_ptr + i, ref out_len);
|
|
else
|
|
this.Process(i, null, 0, ref in_len, output, output_ptr + i, ref out_len);
|
|
}
|
|
this.in_stride = istride_save;
|
|
this.out_stride = ostride_save;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Make sure that the first samples to go out of the resamplers don't have
|
|
/// leading zeros. This is only useful before starting to use a newly created
|
|
/// resampler. It is recommended to use that when resampling an audio file, as
|
|
/// it will generate a file with the same length.For real-time processing,
|
|
/// it is probably easier not to use this call (so that the output duration
|
|
/// is the same for the first frame).
|
|
/// </summary>
|
|
public void SkipZeroes()
|
|
{
|
|
int i;
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
this.last_sample[i] = this.filt_len / 2;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Clears the resampler buffers so a new (unrelated) stream can be processed.
|
|
/// </summary>
|
|
public void ResetMem()
|
|
{
|
|
int i;
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
{
|
|
this.last_sample[i] = 0;
|
|
this.magic_samples[i] = 0;
|
|
this.samp_frac_num[i] = 0;
|
|
}
|
|
for (i = 0; i < this.nb_channels * (this.filt_len - 1); i++)
|
|
this.mem[i] = 0;
|
|
}
|
|
|
|
#endregion
|
|
|
|
#region Getters and Setters
|
|
|
|
/// <summary>
|
|
/// Sets the input and output rates
|
|
/// </summary>
|
|
/// <param name="in_rate">Input sampling rate, in hertz</param>
|
|
/// <param name="out_rate">Output sampling rate, in hertz</param>
|
|
public void SetRates(int in_rate, int out_rate)
|
|
{
|
|
this.SetRateFraction(in_rate, out_rate, in_rate, out_rate);
|
|
}
|
|
|
|
/// <summary>
|
|
/// Get the current input/output sampling rates (integer value).
|
|
/// </summary>
|
|
/// <param name="in_rate">(Output) Sampling rate of input</param>
|
|
/// <param name="out_rate">(Output) Sampling rate of output</param>
|
|
public void GetRates(out int in_rate, out int out_rate)
|
|
{
|
|
in_rate = this.in_rate;
|
|
out_rate = this.out_rate;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Sets the input/output sampling rates and resampling ration (fractional values in Hz supported)
|
|
/// </summary>
|
|
/// <param name="ratio_num">Numerator of the sampling rate ratio</param>
|
|
/// <param name="ratio_den">Denominator of the sampling rate ratio</param>
|
|
/// <param name="in_rate">Input sampling rate rounded to the nearest integer (in Hz)</param>
|
|
/// <param name="out_rate">Output sampling rate rounded to the nearest integer (in Hz)</param>
|
|
public void SetRateFraction(int ratio_num, int ratio_den, int in_rate, int out_rate)
|
|
{
|
|
int fact;
|
|
int old_den;
|
|
int i;
|
|
if (this.in_rate == in_rate && this.out_rate == out_rate && this.num_rate == ratio_num && this.den_rate == ratio_den)
|
|
return;
|
|
|
|
old_den = this.den_rate;
|
|
this.in_rate = in_rate;
|
|
this.out_rate = out_rate;
|
|
this.num_rate = ratio_num;
|
|
this.den_rate = ratio_den;
|
|
/* FIXME: This is terribly inefficient, but who cares (at least for now)? */
|
|
for (fact = 2; fact <= Inlines.IMIN(this.num_rate, this.den_rate); fact++)
|
|
{
|
|
while ((this.num_rate % fact == 0) && (this.den_rate % fact == 0))
|
|
{
|
|
this.num_rate /= fact;
|
|
this.den_rate /= fact;
|
|
}
|
|
}
|
|
|
|
if (old_den > 0)
|
|
{
|
|
for (i = 0; i < this.nb_channels; i++)
|
|
{
|
|
this.samp_frac_num[i] = this.samp_frac_num[i] * this.den_rate / old_den;
|
|
/* Safety net */
|
|
if (this.samp_frac_num[i] >= this.den_rate)
|
|
this.samp_frac_num[i] = this.den_rate - 1;
|
|
}
|
|
}
|
|
|
|
if (this.initialised != 0)
|
|
this.update_filter();
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets the current resampling ratio. This will be reduced to the least common denominator
|
|
/// </summary>
|
|
/// <param name="ratio_num">(Output) numerator of the sampling rate ratio</param>
|
|
/// <param name="ratio_den">(Output) denominator of the sampling rate ratio</param>
|
|
public void GetRateFraction(out int ratio_num, out int ratio_den)
|
|
{
|
|
ratio_num = this.num_rate;
|
|
ratio_den = this.den_rate;
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets or sets the resampling quality between 0 and 10, where 0 has poor
|
|
/// quality and 10 has very high quality.
|
|
/// </summary>
|
|
public int Quality
|
|
{
|
|
get
|
|
{
|
|
return this.quality;
|
|
}
|
|
set
|
|
{
|
|
if (value > 10 || value < 0)
|
|
throw new ArgumentException("Quality must be between 0 and 10");
|
|
if (this.quality == value)
|
|
return;
|
|
this.quality = value;
|
|
if (this.initialised != 0)
|
|
this.update_filter();
|
|
}
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets or sets the input stride
|
|
/// </summary>
|
|
public int InputStride
|
|
{
|
|
get
|
|
{
|
|
return this.in_stride;
|
|
}
|
|
set
|
|
{
|
|
this.in_stride = value;
|
|
}
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets or sets the output stride
|
|
/// </summary>
|
|
public int OutputStride
|
|
{
|
|
get
|
|
{
|
|
return this.out_stride;
|
|
}
|
|
set
|
|
{
|
|
this.out_stride = value;
|
|
}
|
|
}
|
|
|
|
/// <summary>
|
|
/// Get the latency introduced by the resampler measured in input samples.
|
|
/// </summary>
|
|
public int InputLatency
|
|
{
|
|
get
|
|
{
|
|
return this.filt_len / 2;
|
|
}
|
|
}
|
|
|
|
/// <summary>
|
|
/// Gets the latency introduced by the resampler measured in output samples.
|
|
/// </summary>
|
|
public int OutputLatency
|
|
{
|
|
get
|
|
{
|
|
return ((this.filt_len / 2) * this.den_rate + (this.num_rate >> 1)) / this.num_rate;
|
|
}
|
|
}
|
|
|
|
#endregion
|
|
}
|
|
} |