Mercurial > hg > svcore
view data/model/FFTModel.cpp @ 1247:8f076d02569a piper
Make SVDEBUG always write to a log file -- formerly this was disabled in NDEBUG builds. I think there's little use to that, it just means that we keep adding more cerr debug output because we aren't getting the log we need. And SVDEBUG logging is not usually used in tight loops, I don't think the performance overhead is too serious.
Also update the About box.
author | Chris Cannam |
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date | Thu, 03 Nov 2016 14:57:00 +0000 |
parents | 6b847a59d908 |
children | d8d6d01505ed |
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/* -*- c-basic-offset: 4 indent-tabs-mode: nil -*- vi:set ts=8 sts=4 sw=4: */ /* Sonic Visualiser An audio file viewer and annotation editor. Centre for Digital Music, Queen Mary, University of London. This file copyright 2006 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 "FFTModel.h" #include "DenseTimeValueModel.h" #include "base/Profiler.h" #include "base/Pitch.h" #include <algorithm> #include <cassert> #include <deque> using namespace std; FFTModel::FFTModel(const DenseTimeValueModel *model, int channel, WindowType windowType, int windowSize, int windowIncrement, int fftSize) : m_model(model), m_channel(channel), m_windowType(windowType), m_windowSize(windowSize), m_windowIncrement(windowIncrement), m_fftSize(fftSize), m_windower(windowType, windowSize), m_fft(fftSize), m_cacheSize(3) { if (m_windowSize > m_fftSize) { cerr << "ERROR: FFTModel::FFTModel: window size (" << m_windowSize << ") must be at least FFT size (" << m_fftSize << ")" << endl; throw invalid_argument("FFTModel window size must be at least FFT size"); } connect(model, SIGNAL(modelChanged()), this, SIGNAL(modelChanged())); connect(model, SIGNAL(modelChangedWithin(sv_frame_t, sv_frame_t)), this, SIGNAL(modelChangedWithin(sv_frame_t, sv_frame_t))); } FFTModel::~FFTModel() { } void FFTModel::sourceModelAboutToBeDeleted() { if (m_model) { cerr << "FFTModel[" << this << "]::sourceModelAboutToBeDeleted(" << m_model << ")" << endl; m_model = 0; } } int FFTModel::getWidth() const { if (!m_model) return 0; return int((m_model->getEndFrame() - m_model->getStartFrame()) / m_windowIncrement) + 1; } int FFTModel::getHeight() const { return m_fftSize / 2 + 1; } QString FFTModel::getBinName(int n) const { sv_samplerate_t sr = getSampleRate(); if (!sr) return ""; QString name = tr("%1 Hz").arg((n * sr) / ((getHeight()-1) * 2)); return name; } FFTModel::Column FFTModel::getColumn(int x) const { auto cplx = getFFTColumn(x); Column col; col.reserve(cplx.size()); for (auto c: cplx) col.push_back(abs(c)); return move(col); } FFTModel::Column FFTModel::getPhases(int x) const { auto cplx = getFFTColumn(x); Column col; col.reserve(cplx.size()); for (auto c: cplx) { col.push_back(arg(c)); } return move(col); } float FFTModel::getMagnitudeAt(int x, int y) const { if (x < 0 || x >= getWidth() || y < 0 || y >= getHeight()) return 0.f; auto col = getFFTColumn(x); return abs(col[y]); } float FFTModel::getMaximumMagnitudeAt(int x) const { Column col(getColumn(x)); float max = 0.f; int n = int(col.size()); for (int i = 0; i < n; ++i) { if (col[i] > max) max = col[i]; } return max; } float FFTModel::getPhaseAt(int x, int y) const { if (x < 0 || x >= getWidth() || y < 0 || y >= getHeight()) return 0.f; return arg(getFFTColumn(x)[y]); } void FFTModel::getValuesAt(int x, int y, float &re, float &im) const { auto col = getFFTColumn(x); re = col[y].real(); im = col[y].imag(); } bool FFTModel::getMagnitudesAt(int x, float *values, int minbin, int count) const { if (count == 0) count = getHeight(); auto col = getFFTColumn(x); for (int i = 0; i < count; ++i) { values[i] = abs(col[minbin + i]); } return true; } bool FFTModel::getPhasesAt(int x, float *values, int minbin, int count) const { if (count == 0) count = getHeight(); auto col = getFFTColumn(x); for (int i = 0; i < count; ++i) { values[i] = arg(col[minbin + i]); } return true; } bool FFTModel::getValuesAt(int x, float *reals, float *imags, int minbin, int count) const { if (count == 0) count = getHeight(); auto col = getFFTColumn(x); for (int i = 0; i < count; ++i) { reals[i] = col[minbin + i].real(); } for (int i = 0; i < count; ++i) { imags[i] = col[minbin + i].imag(); } return true; } vector<float> FFTModel::getSourceSamples(int column) const { // m_fftSize may be greater than m_windowSize, but not the reverse // cerr << "getSourceSamples(" << column << ")" << endl; auto range = getSourceSampleRange(column); auto data = getSourceData(range); int off = (m_fftSize - m_windowSize) / 2; if (off == 0) { return data; } else { vector<float> pad(off, 0.f); vector<float> padded; padded.reserve(m_fftSize); padded.insert(padded.end(), pad.begin(), pad.end()); padded.insert(padded.end(), data.begin(), data.end()); padded.insert(padded.end(), pad.begin(), pad.end()); return padded; } } vector<float> FFTModel::getSourceData(pair<sv_frame_t, sv_frame_t> range) const { // cerr << "getSourceData(" << range.first << "," << range.second // << "): saved range is (" << m_savedData.range.first // << "," << m_savedData.range.second << ")" << endl; if (m_savedData.range == range) { return m_savedData.data; } if (range.first < m_savedData.range.second && range.first >= m_savedData.range.first && range.second > m_savedData.range.second) { sv_frame_t discard = range.first - m_savedData.range.first; vector<float> acc(m_savedData.data.begin() + discard, m_savedData.data.end()); vector<float> rest = getSourceDataUncached({ m_savedData.range.second, range.second }); acc.insert(acc.end(), rest.begin(), rest.end()); m_savedData = { range, acc }; return acc; } else { auto data = getSourceDataUncached(range); m_savedData = { range, data }; return data; } } vector<float> FFTModel::getSourceDataUncached(pair<sv_frame_t, sv_frame_t> range) const { decltype(range.first) pfx = 0; if (range.first < 0) { pfx = -range.first; range = { 0, range.second }; } auto data = m_model->getData(m_channel, range.first, range.second - range.first); // don't return a partial frame data.resize(range.second - range.first, 0.f); if (pfx > 0) { vector<float> pad(pfx, 0.f); data.insert(data.begin(), pad.begin(), pad.end()); } if (m_channel == -1) { int channels = m_model->getChannelCount(); if (channels > 1) { int n = int(data.size()); float factor = 1.f / float(channels); // use mean instead of sum for fft model input for (int i = 0; i < n; ++i) { data[i] *= factor; } } } return data; } vector<complex<float>> FFTModel::getFFTColumn(int n) const { for (auto &incache : m_cached) { if (incache.n == n) { return incache.col; } } auto samples = getSourceSamples(n); m_windower.cut(samples.data()); auto col = m_fft.process(samples); SavedColumn sc { n, col }; if (m_cached.size() >= m_cacheSize) { m_cached.pop_front(); } m_cached.push_back(sc); return move(col); } bool FFTModel::estimateStableFrequency(int x, int y, double &frequency) { if (!isOK()) return false; frequency = double(y * getSampleRate()) / m_fftSize; if (x+1 >= getWidth()) return false; // At frequency f, a phase shift of 2pi (one cycle) happens in 1/f sec. // At hopsize h and sample rate sr, one hop happens in h/sr sec. // At window size w, for bin b, f is b*sr/w. // thus 2pi phase shift happens in w/(b*sr) sec. // We need to know what phase shift we expect from h/sr sec. // -> 2pi * ((h/sr) / (w/(b*sr))) // = 2pi * ((h * b * sr) / (w * sr)) // = 2pi * (h * b) / w. double oldPhase = getPhaseAt(x, y); double newPhase = getPhaseAt(x+1, y); int incr = getResolution(); double expectedPhase = oldPhase + (2.0 * M_PI * y * incr) / m_fftSize; double phaseError = princarg(newPhase - expectedPhase); // The new frequency estimate based on the phase error resulting // from assuming the "native" frequency of this bin frequency = (getSampleRate() * (expectedPhase + phaseError - oldPhase)) / (2.0 * M_PI * incr); return true; } FFTModel::PeakLocationSet FFTModel::getPeaks(PeakPickType type, int x, int ymin, int ymax) const { Profiler profiler("FFTModel::getPeaks"); FFTModel::PeakLocationSet peaks; if (!isOK()) return peaks; if (ymax == 0 || ymax > getHeight() - 1) { ymax = getHeight() - 1; } if (type == AllPeaks) { int minbin = ymin; if (minbin > 0) minbin = minbin - 1; int maxbin = ymax; if (maxbin < getHeight() - 1) maxbin = maxbin + 1; const int n = maxbin - minbin + 1; float *values = new float[n]; getMagnitudesAt(x, values, minbin, maxbin - minbin + 1); for (int bin = ymin; bin <= ymax; ++bin) { if (bin == minbin || bin == maxbin) continue; if (values[bin - minbin] > values[bin - minbin - 1] && values[bin - minbin] > values[bin - minbin + 1]) { peaks.insert(bin); } } delete[] values; return peaks; } Column values = getColumn(x); int nv = int(values.size()); float mean = 0.f; for (int i = 0; i < nv; ++i) mean += values[i]; if (nv > 0) mean = mean / float(values.size()); // For peak picking we use a moving median window, picking the // highest value within each continuous region of values that // exceed the median. For pitch adaptivity, we adjust the window // size to a roughly constant pitch range (about four tones). sv_samplerate_t sampleRate = getSampleRate(); deque<float> window; vector<int> inrange; float dist = 0.5; int medianWinSize = getPeakPickWindowSize(type, sampleRate, ymin, dist); int halfWin = medianWinSize/2; int binmin; if (ymin > halfWin) binmin = ymin - halfWin; else binmin = 0; int binmax; if (ymax + halfWin < nv) binmax = ymax + halfWin; else binmax = nv - 1; int prevcentre = 0; for (int bin = binmin; bin <= binmax; ++bin) { float value = values[bin]; window.push_back(value); // so-called median will actually be the dist*100'th percentile medianWinSize = getPeakPickWindowSize(type, sampleRate, bin, dist); halfWin = medianWinSize/2; while ((int)window.size() > medianWinSize) { window.pop_front(); } int actualSize = int(window.size()); if (type == MajorPitchAdaptivePeaks) { if (ymax + halfWin < nv) binmax = ymax + halfWin; else binmax = nv - 1; } deque<float> sorted(window); sort(sorted.begin(), sorted.end()); float median = sorted[int(float(sorted.size()) * dist)]; int centrebin = 0; if (bin > actualSize/2) centrebin = bin - actualSize/2; while (centrebin > prevcentre || bin == binmin) { if (centrebin > prevcentre) ++prevcentre; float centre = values[prevcentre]; if (centre > median) { inrange.push_back(centrebin); } if (centre <= median || centrebin+1 == nv) { if (!inrange.empty()) { int peakbin = 0; float peakval = 0.f; for (int i = 0; i < (int)inrange.size(); ++i) { if (i == 0 || values[inrange[i]] > peakval) { peakval = values[inrange[i]]; peakbin = inrange[i]; } } inrange.clear(); if (peakbin >= ymin && peakbin <= ymax) { peaks.insert(peakbin); } } } if (bin == binmin) break; } } return peaks; } int FFTModel::getPeakPickWindowSize(PeakPickType type, sv_samplerate_t sampleRate, int bin, float &percentile) const { percentile = 0.5; if (type == MajorPeaks) return 10; if (bin == 0) return 3; double binfreq = (sampleRate * bin) / m_fftSize; double hifreq = Pitch::getFrequencyForPitch(73, 0, binfreq); int hibin = int(lrint((hifreq * m_fftSize) / sampleRate)); int medianWinSize = hibin - bin; if (medianWinSize < 3) medianWinSize = 3; percentile = 0.5f + float(binfreq / sampleRate); return medianWinSize; } FFTModel::PeakSet FFTModel::getPeakFrequencies(PeakPickType type, int x, int ymin, int ymax) const { Profiler profiler("FFTModel::getPeakFrequencies"); PeakSet peaks; if (!isOK()) return peaks; PeakLocationSet locations = getPeaks(type, x, ymin, ymax); sv_samplerate_t sampleRate = getSampleRate(); int incr = getResolution(); // This duplicates some of the work of estimateStableFrequency to // allow us to retrieve the phases in two separate vertical // columns, instead of jumping back and forth between columns x and // x+1, which may be significantly slower if re-seeking is needed vector<float> phases; for (PeakLocationSet::iterator i = locations.begin(); i != locations.end(); ++i) { phases.push_back(getPhaseAt(x, *i)); } int phaseIndex = 0; for (PeakLocationSet::iterator i = locations.begin(); i != locations.end(); ++i) { double oldPhase = phases[phaseIndex]; double newPhase = getPhaseAt(x+1, *i); double expectedPhase = oldPhase + (2.0 * M_PI * *i * incr) / m_fftSize; double phaseError = princarg(newPhase - expectedPhase); double frequency = (sampleRate * (expectedPhase + phaseError - oldPhase)) / (2 * M_PI * incr); peaks[*i] = frequency; ++phaseIndex; } return peaks; }