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Diffstat (limited to 'libs/qm-dsp/dsp/rateconversion/Resampler.cpp')
| -rw-r--r-- | libs/qm-dsp/dsp/rateconversion/Resampler.cpp | 416 |
1 files changed, 416 insertions, 0 deletions
diff --git a/libs/qm-dsp/dsp/rateconversion/Resampler.cpp b/libs/qm-dsp/dsp/rateconversion/Resampler.cpp new file mode 100644 index 0000000000..f0598cab2c --- /dev/null +++ b/libs/qm-dsp/dsp/rateconversion/Resampler.cpp @@ -0,0 +1,416 @@ +/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */ +/* + QM DSP Library + + Centre for Digital Music, Queen Mary, University of London. + This file by Chris Cannam. + + This program is free software; you can redistribute it and/or + modify it under the terms of the GNU General Public License as + published by the Free Software Foundation; either version 2 of the + License, or (at your option) any later version. See the file + COPYING included with this distribution for more information. +*/ + +#include "Resampler.h" + +#include "maths/MathUtilities.h" +#include "base/KaiserWindow.h" +#include "base/SincWindow.h" +#include "thread/Thread.h" + +#include <iostream> +#include <vector> +#include <map> +#include <cassert> + +using std::vector; +using std::map; +using std::cerr; +using std::endl; + +//#define DEBUG_RESAMPLER 1 +//#define DEBUG_RESAMPLER_VERBOSE 1 + +Resampler::Resampler(int sourceRate, int targetRate) : + m_sourceRate(sourceRate), + m_targetRate(targetRate) +{ + initialise(100, 0.02); +} + +Resampler::Resampler(int sourceRate, int targetRate, + double snr, double bandwidth) : + m_sourceRate(sourceRate), + m_targetRate(targetRate) +{ + initialise(snr, bandwidth); +} + +Resampler::~Resampler() +{ + delete[] m_phaseData; +} + +// peakToPole -> length -> beta -> window +static map<double, map<int, map<double, vector<double> > > > +knownFilters; + +static Mutex +knownFilterMutex; + +void +Resampler::initialise(double snr, double bandwidth) +{ + int higher = std::max(m_sourceRate, m_targetRate); + int lower = std::min(m_sourceRate, m_targetRate); + + m_gcd = MathUtilities::gcd(lower, higher); + m_peakToPole = higher / m_gcd; + + if (m_targetRate < m_sourceRate) { + // antialiasing filter, should be slightly below nyquist + m_peakToPole = m_peakToPole / (1.0 - bandwidth/2.0); + } + + KaiserWindow::Parameters params = + KaiserWindow::parametersForBandwidth(snr, bandwidth, higher / m_gcd); + + params.length = + (params.length % 2 == 0 ? params.length + 1 : params.length); + + params.length = + (params.length > 200001 ? 200001 : params.length); + + m_filterLength = params.length; + + vector<double> filter; + knownFilterMutex.lock(); + + if (knownFilters[m_peakToPole][m_filterLength].find(params.beta) == + knownFilters[m_peakToPole][m_filterLength].end()) { + + KaiserWindow kw(params); + SincWindow sw(m_filterLength, m_peakToPole * 2); + + filter = vector<double>(m_filterLength, 0.0); + for (int i = 0; i < m_filterLength; ++i) filter[i] = 1.0; + sw.cut(filter.data()); + kw.cut(filter.data()); + + knownFilters[m_peakToPole][m_filterLength][params.beta] = filter; + } + + filter = knownFilters[m_peakToPole][m_filterLength][params.beta]; + knownFilterMutex.unlock(); + + int inputSpacing = m_targetRate / m_gcd; + int outputSpacing = m_sourceRate / m_gcd; + +#ifdef DEBUG_RESAMPLER + cerr << "resample " << m_sourceRate << " -> " << m_targetRate + << ": inputSpacing " << inputSpacing << ", outputSpacing " + << outputSpacing << ": filter length " << m_filterLength + << endl; +#endif + + // Now we have a filter of (odd) length flen in which the lower + // sample rate corresponds to every n'th point and the higher rate + // to every m'th where n and m are higher and lower rates divided + // by their gcd respectively. So if x coordinates are on the same + // scale as our filter resolution, then source sample i is at i * + // (targetRate / gcd) and target sample j is at j * (sourceRate / + // gcd). + + // To reconstruct a single target sample, we want a buffer (real + // or virtual) of flen values formed of source samples spaced at + // intervals of (targetRate / gcd), in our example case 3. This + // is initially formed with the first sample at the filter peak. + // + // 0 0 0 0 a 0 0 b 0 + // + // and of course we have our filter + // + // f1 f2 f3 f4 f5 f6 f7 f8 f9 + // + // We take the sum of products of non-zero values from this buffer + // with corresponding values in the filter + // + // a * f5 + b * f8 + // + // Then we drop (sourceRate / gcd) values, in our example case 4, + // from the start of the buffer and fill until it has flen values + // again + // + // a 0 0 b 0 0 c 0 0 + // + // repeat to reconstruct the next target sample + // + // a * f1 + b * f4 + c * f7 + // + // and so on. + // + // Above I said the buffer could be "real or virtual" -- ours is + // virtual. We don't actually store all the zero spacing values, + // except for padding at the start; normally we store only the + // values that actually came from the source stream, along with a + // phase value that tells us how many virtual zeroes there are at + // the start of the virtual buffer. So the two examples above are + // + // 0 a b [ with phase 1 ] + // a b c [ with phase 0 ] + // + // Having thus broken down the buffer so that only the elements we + // need to multiply are present, we can also unzip the filter into + // every-nth-element subsets at each phase, allowing us to do the + // filter multiplication as a simply vector multiply. That is, rather + // than store + // + // f1 f2 f3 f4 f5 f6 f7 f8 f9 + // + // we store separately + // + // f1 f4 f7 + // f2 f5 f8 + // f3 f6 f9 + // + // Each time we complete a multiply-and-sum, we need to work out + // how many (real) samples to drop from the start of our buffer, + // and how many to add at the end of it for the next multiply. We + // know we want to drop enough real samples to move along by one + // computed output sample, which is our outputSpacing number of + // virtual buffer samples. Depending on the relationship between + // input and output spacings, this may mean dropping several real + // samples, one real sample, or none at all (and simply moving to + // a different "phase"). + + m_phaseData = new Phase[inputSpacing]; + + for (int phase = 0; phase < inputSpacing; ++phase) { + + Phase p; + + p.nextPhase = phase - outputSpacing; + while (p.nextPhase < 0) p.nextPhase += inputSpacing; + p.nextPhase %= inputSpacing; + + p.drop = int(ceil(std::max(0.0, double(outputSpacing - phase)) + / inputSpacing)); + + int filtZipLength = int(ceil(double(m_filterLength - phase) + / inputSpacing)); + + for (int i = 0; i < filtZipLength; ++i) { + p.filter.push_back(filter[i * inputSpacing + phase]); + } + + m_phaseData[phase] = p; + } + +#ifdef DEBUG_RESAMPLER + int cp = 0; + int totDrop = 0; + for (int i = 0; i < inputSpacing; ++i) { + cerr << "phase = " << cp << ", drop = " << m_phaseData[cp].drop + << ", filter length = " << m_phaseData[cp].filter.size() + << ", next phase = " << m_phaseData[cp].nextPhase << endl; + totDrop += m_phaseData[cp].drop; + cp = m_phaseData[cp].nextPhase; + } + cerr << "total drop = " << totDrop << endl; +#endif + + // The May implementation of this uses a pull model -- we ask the + // resampler for a certain number of output samples, and it asks + // its source stream for as many as it needs to calculate + // those. This means (among other things) that the source stream + // can be asked for enough samples up-front to fill the buffer + // before the first output sample is generated. + // + // In this implementation we're using a push model in which a + // certain number of source samples is provided and we're asked + // for as many output samples as that makes available. But we + // can't return any samples from the beginning until half the + // filter length has been provided as input. This means we must + // either return a very variable number of samples (none at all + // until the filter fills, then half the filter length at once) or + // else have a lengthy declared latency on the output. We do the + // latter. (What do other implementations do?) + // + // We want to make sure the first "real" sample will eventually be + // aligned with the centre sample in the filter (it's tidier, and + // easier to do diagnostic calculations that way). So we need to + // pick the initial phase and buffer fill accordingly. + // + // Example: if the inputSpacing is 2, outputSpacing is 3, and + // filter length is 7, + // + // x x x x a b c ... input samples + // 0 1 2 3 4 5 6 7 8 9 10 11 12 13 ... + // i j k l ... output samples + // [--------|--------] <- filter with centre mark + // + // Let h be the index of the centre mark, here 3 (generally + // int(filterLength/2) for odd-length filters). + // + // The smallest n such that h + n * outputSpacing > filterLength + // is 2 (that is, ceil((filterLength - h) / outputSpacing)), and + // (h + 2 * outputSpacing) % inputSpacing == 1, so the initial + // phase is 1. + // + // To achieve our n, we need to pre-fill the "virtual" buffer with + // 4 zero samples: the x's above. This is int((h + n * + // outputSpacing) / inputSpacing). It's the phase that makes this + // buffer get dealt with in such a way as to give us an effective + // index for sample a of 9 rather than 8 or 10 or whatever. + // + // This gives us output latency of 2 (== n), i.e. output samples i + // and j will appear before the one in which input sample a is at + // the centre of the filter. + + int h = int(m_filterLength / 2); + int n = ceil(double(m_filterLength - h) / outputSpacing); + + m_phase = (h + n * outputSpacing) % inputSpacing; + + int fill = (h + n * outputSpacing) / inputSpacing; + + m_latency = n; + + m_buffer = vector<double>(fill, 0); + m_bufferOrigin = 0; + +#ifdef DEBUG_RESAMPLER + cerr << "initial phase " << m_phase << " (as " << (m_filterLength/2) << " % " << inputSpacing << ")" + << ", latency " << m_latency << endl; +#endif +} + +double +Resampler::reconstructOne() +{ + Phase &pd = m_phaseData[m_phase]; + double v = 0.0; + int n = pd.filter.size(); + + assert(n + m_bufferOrigin <= (int)m_buffer.size()); + + const double *const __restrict__ buf = m_buffer.data() + m_bufferOrigin; + const double *const __restrict__ filt = pd.filter.data(); + + for (int i = 0; i < n; ++i) { + // NB gcc can only vectorize this with -ffast-math + v += buf[i] * filt[i]; + } + + m_bufferOrigin += pd.drop; + m_phase = pd.nextPhase; + return v; +} + +int +Resampler::process(const double *src, double *dst, int n) +{ + for (int i = 0; i < n; ++i) { + m_buffer.push_back(src[i]); + } + + int maxout = int(ceil(double(n) * m_targetRate / m_sourceRate)); + int outidx = 0; + +#ifdef DEBUG_RESAMPLER + cerr << "process: buf siz " << m_buffer.size() << " filt siz for phase " << m_phase << " " << m_phaseData[m_phase].filter.size() << endl; +#endif + + double scaleFactor = (double(m_targetRate) / m_gcd) / m_peakToPole; + + while (outidx < maxout && + m_buffer.size() >= m_phaseData[m_phase].filter.size() + m_bufferOrigin) { + dst[outidx] = scaleFactor * reconstructOne(); + outidx++; + } + + m_buffer = vector<double>(m_buffer.begin() + m_bufferOrigin, m_buffer.end()); + m_bufferOrigin = 0; + + return outidx; +} + +vector<double> +Resampler::process(const double *src, int n) +{ + int maxout = int(ceil(double(n) * m_targetRate / m_sourceRate)); + vector<double> out(maxout, 0.0); + int got = process(src, out.data(), n); + assert(got <= maxout); + if (got < maxout) out.resize(got); + return out; +} + +vector<double> +Resampler::resample(int sourceRate, int targetRate, const double *data, int n) +{ + Resampler r(sourceRate, targetRate); + + int latency = r.getLatency(); + + // latency is the output latency. We need to provide enough + // padding input samples at the end of input to guarantee at + // *least* the latency's worth of output samples. that is, + + int inputPad = int(ceil((double(latency) * sourceRate) / targetRate)); + + // that means we are providing this much input in total: + + int n1 = n + inputPad; + + // and obtaining this much output in total: + + int m1 = int(ceil((double(n1) * targetRate) / sourceRate)); + + // in order to return this much output to the user: + + int m = int(ceil((double(n) * targetRate) / sourceRate)); + +#ifdef DEBUG_RESAMPLER + cerr << "n = " << n << ", sourceRate = " << sourceRate << ", targetRate = " << targetRate << ", m = " << m << ", latency = " << latency << ", inputPad = " << inputPad << ", m1 = " << m1 << ", n1 = " << n1 << ", n1 - n = " << n1 - n << endl; +#endif + + vector<double> pad(n1 - n, 0.0); + vector<double> out(m1 + 1, 0.0); + + int gotData = r.process(data, out.data(), n); + int gotPad = r.process(pad.data(), out.data() + gotData, pad.size()); + int got = gotData + gotPad; + +#ifdef DEBUG_RESAMPLER + cerr << "resample: " << n << " in, " << pad.size() << " padding, " << got << " out (" << gotData << " data, " << gotPad << " padding, latency = " << latency << ")" << endl; +#endif +#ifdef DEBUG_RESAMPLER_VERBOSE + int printN = 50; + cerr << "first " << printN << " in:" << endl; + for (int i = 0; i < printN && i < n; ++i) { + if (i % 5 == 0) cerr << endl << i << "... "; + cerr << data[i] << " "; + } + cerr << endl; +#endif + + int toReturn = got - latency; + if (toReturn > m) toReturn = m; + + vector<double> sliced(out.begin() + latency, + out.begin() + latency + toReturn); + +#ifdef DEBUG_RESAMPLER_VERBOSE + cerr << "first " << printN << " out (after latency compensation), length " << sliced.size() << ":"; + for (int i = 0; i < printN && i < sliced.size(); ++i) { + if (i % 5 == 0) cerr << endl << i << "... "; + cerr << sliced[i] << " "; + } + cerr << endl; +#endif + + return sliced; +} + |