Mercurial > hg > qm-dsp
view dsp/rateconversion/Resampler.cpp @ 145:fe267879e022
Avoid vector reallocation on every reconstructed output sample
author | Chris Cannam |
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date | Wed, 16 Oct 2013 13:33:18 +0100 |
parents | a4aa37f7af28 |
children | 235b99c7d4ce |
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/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */ #include "Resampler.h" #include "qm-dsp/maths/MathUtilities.h" #include "qm-dsp/base/KaiserWindow.h" #include "qm-dsp/base/SincWindow.h" #include <iostream> #include <vector> #include <map> using std::vector; using std::map; //#define DEBUG_RESAMPLER 1 Resampler::Resampler(int sourceRate, int targetRate) : m_sourceRate(sourceRate), m_targetRate(targetRate) { initialise(); } Resampler::~Resampler() { delete[] m_phaseData; } void Resampler::initialise() { int higher = std::max(m_sourceRate, m_targetRate); int lower = std::min(m_sourceRate, m_targetRate); m_gcd = MathUtilities::gcd(lower, higher); int peakToPole = higher / m_gcd; KaiserWindow::Parameters params = KaiserWindow::parametersForBandwidth(100, 0.02, peakToPole); params.length = (params.length % 2 == 0 ? params.length + 1 : params.length); m_filterLength = params.length; KaiserWindow kw(params); SincWindow sw(m_filterLength, peakToPole * 2); vector<double> filter(m_filterLength, 0.0); for (int i = 0; i < m_filterLength; ++i) filter[i] = 1.0; sw.cut(filter.data()); kw.cut(filter.data()); int inputSpacing = m_targetRate / m_gcd; int outputSpacing = m_sourceRate / m_gcd; #ifdef DEBUG_RESAMPLER std::cerr << "resample " << m_sourceRate << " -> " << m_targetRate << ": inputSpacing " << inputSpacing << ", outputSpacing " << outputSpacing << ": filter length " << m_filterLength << std::endl; #endif 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; } // 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?) m_phase = (m_filterLength/2) % inputSpacing; m_buffer = vector<double>(m_phaseData[0].filter.size(), 0); m_bufferOrigin = 0; m_latency = ((m_buffer.size() * inputSpacing) - (m_filterLength/2)) / outputSpacing + m_phase; #ifdef DEBUG_RESAMPLER std::cerr << "initial phase " << m_phase << " (as " << (m_filterLength/2) << " % " << inputSpacing << ")" << ", latency " << m_latency << std::endl; #endif } double Resampler::reconstructOne() { Phase &pd = m_phaseData[m_phase]; double v = 0.0; int n = pd.filter.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 std::cerr << "process: buf siz " << m_buffer.size() << " filt siz for phase " << m_phase << " " << m_phaseData[m_phase].filter.size() << std::endl; #endif double scaleFactor = 1.0; if (m_targetRate < m_sourceRate) { scaleFactor = double(m_targetRate) / double(m_sourceRate); } 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; } std::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)); // std::cerr << "n = " << n << ", sourceRate = " << sourceRate << ", targetRate = " << targetRate << ", m = " << m << ", latency = " << latency << ", m1 = " << m1 << ", n1 = " << n1 << ", n1 - n = " << n1 - n << std::endl; vector<double> pad(n1 - n, 0.0); vector<double> out(m1 + 1, 0.0); int got = r.process(data, out.data(), n); got += r.process(pad.data(), out.data() + got, pad.size()); #ifdef DEBUG_RESAMPLER std::cerr << "resample: " << n << " in, " << got << " out" << std::endl; for (int i = 0; i < got; ++i) { if (i % 5 == 0) std::cout << std::endl << i << "... "; std::cout << (float) out[i] << " "; } std::cout << std::endl; #endif int toReturn = got - latency; if (toReturn > m) toReturn = m; return vector<double>(out.begin() + latency, out.begin() + latency + toReturn); }