cannam@198: /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
cannam@198: 
cannam@198: /*
cannam@198:     Vamp
cannam@198: 
cannam@198:     An API for audio analysis and feature extraction plugins.
cannam@198: 
cannam@198:     Centre for Digital Music, Queen Mary, University of London.
cannam@198:     Copyright 2006-2008 Chris Cannam and QMUL.
cannam@198:   
cannam@198:     Permission is hereby granted, free of charge, to any person
cannam@198:     obtaining a copy of this software and associated documentation
cannam@198:     files (the "Software"), to deal in the Software without
cannam@198:     restriction, including without limitation the rights to use, copy,
cannam@198:     modify, merge, publish, distribute, sublicense, and/or sell copies
cannam@198:     of the Software, and to permit persons to whom the Software is
cannam@198:     furnished to do so, subject to the following conditions:
cannam@198: 
cannam@198:     The above copyright notice and this permission notice shall be
cannam@198:     included in all copies or substantial portions of the Software.
cannam@198: 
cannam@198:     THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
cannam@198:     EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
cannam@198:     MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
cannam@198:     NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
cannam@198:     ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
cannam@198:     CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
cannam@198:     WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
cannam@198: 
cannam@198:     Except as contained in this notice, the names of the Centre for
cannam@198:     Digital Music; Queen Mary, University of London; and Chris Cannam
cannam@198:     shall not be used in advertising or otherwise to promote the sale,
cannam@198:     use or other dealings in this Software without prior written
cannam@198:     authorization.
cannam@198: */
cannam@198: 
cannam@198: #include "FixedTempoEstimator.h"
cannam@198: 
cannam@198: using std::string;
cannam@198: using std::vector;
cannam@198: using std::cerr;
cannam@198: using std::endl;
cannam@198: 
cannam@198: using Vamp::RealTime;
cannam@198: 
cannam@198: #include <cmath>
cannam@198: 
cannam@198: 
cannam@243: class FixedTempoEstimator::D
cannam@243: {
cannam@243: public:
cannam@243:     D(float inputSampleRate);
cannam@243:     ~D();
cannam@243: 
cannam@243:     size_t getPreferredStepSize() const { return 64; }
cannam@243:     size_t getPreferredBlockSize() const { return 256; }
cannam@243: 
cannam@243:     ParameterList getParameterDescriptors() const;
cannam@243:     float getParameter(string id) const;
cannam@243:     void setParameter(string id, float value);
cannam@243: 
cannam@243:     OutputList getOutputDescriptors() const;
cannam@243: 
cannam@243:     bool initialise(size_t channels, size_t stepSize, size_t blockSize);
cannam@243:     void reset();
cannam@243:     FeatureSet process(const float *const *, RealTime);
cannam@243:     FeatureSet getRemainingFeatures();
cannam@243: 
cannam@243: private:
cannam@243:     void calculate();
cannam@243:     FeatureSet assembleFeatures();
cannam@243: 
cannam@243:     float lag2tempo(int);
cannam@243:     int tempo2lag(float);
cannam@243: 
cannam@243:     float m_inputSampleRate;
cannam@243:     size_t m_stepSize;
cannam@243:     size_t m_blockSize;
cannam@243: 
cannam@243:     float m_minbpm;
cannam@243:     float m_maxbpm;
cannam@243:     float m_maxdflen;
cannam@243: 
cannam@243:     float *m_priorMagnitudes;
cannam@243: 
cannam@243:     size_t m_dfsize;
cannam@243:     float *m_df;
cannam@243:     float *m_r;
cannam@243:     float *m_fr;
cannam@243:     float *m_t;
cannam@243:     size_t m_n;
cannam@243: 
cannam@243:     Vamp::RealTime m_start;
cannam@243:     Vamp::RealTime m_lasttime;
cannam@243: };
cannam@243: 
cannam@243: FixedTempoEstimator::D::D(float inputSampleRate) :
cannam@243:     m_inputSampleRate(inputSampleRate),
cannam@198:     m_stepSize(0),
cannam@198:     m_blockSize(0),
cannam@243:     m_minbpm(50),
cannam@243:     m_maxbpm(190),
cannam@243:     m_maxdflen(10),
cannam@198:     m_priorMagnitudes(0),
cannam@200:     m_df(0),
cannam@200:     m_r(0),
cannam@200:     m_fr(0),
cannam@204:     m_t(0),
cannam@200:     m_n(0)
cannam@198: {
cannam@198: }
cannam@198: 
cannam@243: FixedTempoEstimator::D::~D()
cannam@198: {
cannam@198:     delete[] m_priorMagnitudes;
cannam@198:     delete[] m_df;
cannam@200:     delete[] m_r;
cannam@200:     delete[] m_fr;
cannam@204:     delete[] m_t;
cannam@198: }
cannam@198: 
cannam@198: FixedTempoEstimator::ParameterList
cannam@243: FixedTempoEstimator::D::getParameterDescriptors() const
cannam@198: {
cannam@198:     ParameterList list;
cannam@243: 
cannam@243:     ParameterDescriptor d;
cannam@243:     d.identifier = "minbpm";
cannam@243:     d.name = "Minimum estimated tempo";
cannam@243:     d.description = "Minimum beat-per-minute value which the tempo estimator is able to return";
cannam@243:     d.unit = "bpm";
cannam@243:     d.minValue = 10;
cannam@243:     d.maxValue = 360;
cannam@243:     d.defaultValue = 50;
cannam@243:     d.isQuantized = false;
cannam@243:     list.push_back(d);
cannam@243: 
cannam@243:     d.identifier = "maxbpm";
cannam@243:     d.name = "Maximum estimated tempo";
cannam@243:     d.description = "Maximum beat-per-minute value which the tempo estimator is able to return";
cannam@243:     d.defaultValue = 190;
cannam@243:     list.push_back(d);
cannam@243: 
cannam@243:     d.identifier = "maxdflen";
cannam@243:     d.name = "Input duration to study";
cannam@243:     d.description = "Length of audio input, in seconds, which should be taken into account when estimating tempo.  There is no need to supply the plugin with any further input once this time has elapsed since the start of the audio.  The tempo estimator may use only the first part of this, up to eight times the slowest beat duration: increasing this value further than that is unlikely to improve results.";
cannam@243:     d.unit = "s";
cannam@243:     d.minValue = 2;
cannam@243:     d.maxValue = 40;
cannam@243:     d.defaultValue = 10;
cannam@243:     list.push_back(d);
cannam@243: 
cannam@198:     return list;
cannam@198: }
cannam@198: 
cannam@198: float
cannam@243: FixedTempoEstimator::D::getParameter(string id) const
cannam@198: {
cannam@243:     if (id == "minbpm") {
cannam@243:         return m_minbpm;
cannam@243:     } else if (id == "maxbpm") {
cannam@243:         return m_maxbpm;
cannam@243:     } else if (id == "maxdflen") {
cannam@243:         return m_maxdflen;
cannam@243:     }
cannam@198:     return 0.f;
cannam@198: }
cannam@198: 
cannam@198: void
cannam@243: FixedTempoEstimator::D::setParameter(string id, float value)
cannam@198: {
cannam@243:     if (id == "minbpm") {
cannam@243:         m_minbpm = value;
cannam@243:     } else if (id == "maxbpm") {
cannam@243:         m_maxbpm = value;
cannam@243:     } else if (id == "maxdflen") {
cannam@243:         m_maxdflen = value;
cannam@243:     }
cannam@198: }
cannam@198: 
cannam@200: static int TempoOutput = 0;
cannam@200: static int CandidatesOutput = 1;
cannam@200: static int DFOutput = 2;
cannam@200: static int ACFOutput = 3;
cannam@200: static int FilteredACFOutput = 4;
cannam@200: 
cannam@198: FixedTempoEstimator::OutputList
cannam@243: FixedTempoEstimator::D::getOutputDescriptors() const
cannam@198: {
cannam@198:     OutputList list;
cannam@198: 
cannam@198:     OutputDescriptor d;
cannam@198:     d.identifier = "tempo";
cannam@198:     d.name = "Tempo";
cannam@198:     d.description = "Estimated tempo";
cannam@198:     d.unit = "bpm";
cannam@198:     d.hasFixedBinCount = true;
cannam@198:     d.binCount = 1;
cannam@198:     d.hasKnownExtents = false;
cannam@198:     d.isQuantized = false;
cannam@198:     d.sampleType = OutputDescriptor::VariableSampleRate;
cannam@198:     d.sampleRate = m_inputSampleRate;
cannam@198:     d.hasDuration = true; // our returned tempo spans a certain range
cannam@198:     list.push_back(d);
cannam@198: 
cannam@200:     d.identifier = "candidates";
cannam@200:     d.name = "Tempo candidates";
cannam@200:     d.description = "Possible tempo estimates, one per bin with the most likely in the first bin";
cannam@200:     d.unit = "bpm";
cannam@200:     d.hasFixedBinCount = false;
cannam@200:     list.push_back(d);
cannam@200: 
cannam@198:     d.identifier = "detectionfunction";
cannam@198:     d.name = "Detection Function";
cannam@198:     d.description = "Onset detection function";
cannam@198:     d.unit = "";
cannam@198:     d.hasFixedBinCount = 1;
cannam@198:     d.binCount = 1;
cannam@198:     d.hasKnownExtents = true;
cannam@198:     d.minValue = 0.0;
cannam@198:     d.maxValue = 1.0;
cannam@198:     d.isQuantized = false;
cannam@198:     d.quantizeStep = 0.0;
cannam@198:     d.sampleType = OutputDescriptor::FixedSampleRate;
cannam@198:     if (m_stepSize) {
cannam@198:         d.sampleRate = m_inputSampleRate / m_stepSize;
cannam@198:     } else {
cannam@198:         d.sampleRate = m_inputSampleRate / (getPreferredBlockSize()/2);
cannam@198:     }
cannam@198:     d.hasDuration = false;
cannam@198:     list.push_back(d);
cannam@198: 
cannam@198:     d.identifier = "acf";
cannam@198:     d.name = "Autocorrelation Function";
cannam@198:     d.description = "Autocorrelation of onset detection function";
cannam@198:     d.hasKnownExtents = false;
cannam@201:     d.unit = "r";
cannam@198:     list.push_back(d);
cannam@198: 
cannam@198:     d.identifier = "filtered_acf";
cannam@198:     d.name = "Filtered Autocorrelation";
cannam@198:     d.description = "Filtered autocorrelation of onset detection function";
cannam@201:     d.unit = "r";
cannam@198:     list.push_back(d);
cannam@198: 
cannam@198:     return list;
cannam@198: }
cannam@198: 
cannam@243: bool
cannam@243: FixedTempoEstimator::D::initialise(size_t channels,
cannam@243:                                    size_t stepSize, size_t blockSize)
cannam@243: {
cannam@243:     m_stepSize = stepSize;
cannam@243:     m_blockSize = blockSize;
cannam@243: 
cannam@243:     float dfLengthSecs = m_maxdflen;
cannam@243:     m_dfsize = (dfLengthSecs * m_inputSampleRate) / m_stepSize;
cannam@243: 
cannam@243:     m_priorMagnitudes = new float[m_blockSize/2];
cannam@243:     m_df = new float[m_dfsize];
cannam@243: 
cannam@243:     for (size_t i = 0; i < m_blockSize/2; ++i) {
cannam@243:         m_priorMagnitudes[i] = 0.f;
cannam@243:     }
cannam@243:     for (size_t i = 0; i < m_dfsize; ++i) {
cannam@243:         m_df[i] = 0.f;
cannam@243:     }
cannam@243: 
cannam@243:     m_n = 0;
cannam@243: 
cannam@243:     return true;
cannam@243: }
cannam@243: 
cannam@243: void
cannam@243: FixedTempoEstimator::D::reset()
cannam@243: {
cannam@243:     if (!m_priorMagnitudes) return;
cannam@243: 
cannam@243:     for (size_t i = 0; i < m_blockSize/2; ++i) {
cannam@243:         m_priorMagnitudes[i] = 0.f;
cannam@243:     }
cannam@243:     for (size_t i = 0; i < m_dfsize; ++i) {
cannam@243:         m_df[i] = 0.f;
cannam@243:     }
cannam@243: 
cannam@243:     delete[] m_r;
cannam@243:     m_r = 0;
cannam@243: 
cannam@243:     delete[] m_fr; 
cannam@243:     m_fr = 0;
cannam@243: 
cannam@243:     delete[] m_t; 
cannam@243:     m_t = 0;
cannam@243: 
cannam@243:     m_n = 0;
cannam@243: 
cannam@243:     m_start = RealTime::zeroTime;
cannam@243:     m_lasttime = RealTime::zeroTime;
cannam@243: }
cannam@243: 
cannam@198: FixedTempoEstimator::FeatureSet
cannam@243: FixedTempoEstimator::D::process(const float *const *inputBuffers, RealTime ts)
cannam@198: {
cannam@198:     FeatureSet fs;
cannam@198: 
cannam@198:     if (m_stepSize == 0) {
cannam@198: 	cerr << "ERROR: FixedTempoEstimator::process: "
cannam@198: 	     << "FixedTempoEstimator has not been initialised"
cannam@198: 	     << endl;
cannam@198: 	return fs;
cannam@198:     }
cannam@198: 
cannam@198:     if (m_n == 0) m_start = ts;
cannam@198:     m_lasttime = ts;
cannam@198: 
cannam@198:     if (m_n == m_dfsize) {
cannam@200:         calculate();
cannam@200:         fs = assembleFeatures();
cannam@198:         ++m_n;
cannam@198:         return fs;
cannam@198:     }
cannam@198: 
cannam@198:     if (m_n > m_dfsize) return FeatureSet();
cannam@198: 
cannam@207:     float value = 0.f;
cannam@207: 
cannam@198:     for (size_t i = 1; i < m_blockSize/2; ++i) {
cannam@198: 
cannam@198:         float real = inputBuffers[0][i*2];
cannam@198:         float imag = inputBuffers[0][i*2 + 1];
cannam@198: 
cannam@198:         float sqrmag = real * real + imag * imag;
cannam@207:         value += fabsf(sqrmag - m_priorMagnitudes[i]);
cannam@198: 
cannam@198:         m_priorMagnitudes[i] = sqrmag;
cannam@198:     }
cannam@198: 
cannam@207:     m_df[m_n] = value;
cannam@207: 
cannam@198:     ++m_n;
cannam@198:     return fs;
cannam@243: }    
cannam@198: 
cannam@198: FixedTempoEstimator::FeatureSet
cannam@243: FixedTempoEstimator::D::getRemainingFeatures()
cannam@198: {
cannam@198:     FeatureSet fs;
cannam@198:     if (m_n > m_dfsize) return fs;
cannam@200:     calculate();
cannam@200:     fs = assembleFeatures();
cannam@198:     ++m_n;
cannam@198:     return fs;
cannam@198: }
cannam@198: 
cannam@198: float
cannam@243: FixedTempoEstimator::D::lag2tempo(int lag)
cannam@199: {
cannam@198:     return 60.f / ((lag * m_stepSize) / m_inputSampleRate);
cannam@198: }
cannam@198: 
cannam@207: int
cannam@243: FixedTempoEstimator::D::tempo2lag(float tempo)
cannam@207: {
cannam@207:     return ((60.f / tempo) * m_inputSampleRate) / m_stepSize;
cannam@207: }
cannam@207: 
cannam@200: void
cannam@243: FixedTempoEstimator::D::calculate()
cannam@200: {    
cannam@200:     if (m_r) {
cannam@207:         cerr << "FixedTempoEstimator::calculate: calculation already happened?" << endl;
cannam@200:         return;
cannam@200:     }
cannam@200: 
cannam@243:     if (m_n < m_dfsize / 9 &&
cannam@243:         m_n < (1.0 * m_inputSampleRate) / m_stepSize) { // 1 second
cannam@243:         cerr << "FixedTempoEstimator::calculate: Input is too short" << endl;
cannam@243:         return;
cannam@200:     }
cannam@200: 
cannam@200:     int n = m_n;
cannam@200: 
cannam@200:     m_r = new float[n/2];
cannam@200:     m_fr = new float[n/2];
cannam@204:     m_t = new float[n/2];
cannam@200: 
cannam@200:     for (int i = 0; i < n/2; ++i) {
cannam@200:         m_r[i] = 0.f;
cannam@200:         m_fr[i] = 0.f;
cannam@207:         m_t[i] = lag2tempo(i);
cannam@200:     }
cannam@200: 
cannam@200:     for (int i = 0; i < n/2; ++i) {
cannam@200: 
cannam@200:         for (int j = i; j < n-1; ++j) {
cannam@200:             m_r[i] += m_df[j] * m_df[j - i];
cannam@200:         }
cannam@200: 
cannam@200:         m_r[i] /= n - i - 1;
cannam@200:     }
cannam@200: 
cannam@246:     float related[] = { 0.5, 2, 4, 8 };
cannam@208: 
cannam@209:     for (int i = 1; i < n/2-1; ++i) {
cannam@204: 
cannam@209:         float weight = 1.f - fabsf(128.f - lag2tempo(i)) * 0.005;
cannam@209:         if (weight < 0.f) weight = 0.f;
cannam@215:         weight = weight * weight * weight;
cannam@209: 
cannam@209:         m_fr[i] = m_r[i];
cannam@204: 
cannam@200:         int div = 1;
cannam@200: 
cannam@215:         for (int j = 0; j < int(sizeof(related)/sizeof(related[0])); ++j) {
cannam@204: 
cannam@215:             int k0 = int(i * related[j] + 0.5);
cannam@209: 
cannam@215:             if (k0 >= 0 && k0 < int(n/2)) {
cannam@204: 
cannam@207:                 int kmax = 0, kmin = 0;
cannam@207:                 float kvmax = 0, kvmin = 0;
cannam@209:                 bool have = false;
cannam@204: 
cannam@209:                 for (int k = k0 - 1; k <= k0 + 1; ++k) {
cannam@204: 
cannam@209:                     if (k < 0 || k >= n/2) continue;
cannam@209: 
cannam@215:                     if (!have || (m_r[k] > kvmax)) { kmax = k; kvmax = m_r[k]; }
cannam@215:                     if (!have || (m_r[k] < kvmin)) { kmin = k; kvmin = m_r[k]; }
cannam@209:                     
cannam@209:                     have = true;
cannam@204:                 }
cannam@209:                 
cannam@215:                 m_fr[i] += m_r[kmax] / 5;
cannam@209: 
cannam@209:                 if ((kmax == 0 || m_r[kmax] > m_r[kmax-1]) &&
cannam@209:                     (kmax == n/2-1 || m_r[kmax] > m_r[kmax+1]) &&
cannam@207:                     kvmax > kvmin * 1.05) {
cannam@209:                     
cannam@207:                     m_t[i] = m_t[i] + lag2tempo(kmax) * related[j];
cannam@207:                     ++div;
cannam@207:                 }
cannam@204:             }
cannam@204:         }
cannam@209:         
cannam@204:         m_t[i] /= div;
cannam@204:         
cannam@215:         m_fr[i] += m_fr[i] * (weight / 3);
cannam@207:     }
cannam@200: }
cannam@200:     
cannam@198: FixedTempoEstimator::FeatureSet
cannam@243: FixedTempoEstimator::D::assembleFeatures()
cannam@198: {
cannam@198:     FeatureSet fs;
cannam@200:     if (!m_r) return fs; // No results
cannam@200: 
cannam@198:     Feature feature;
cannam@198:     feature.hasTimestamp = true;
cannam@198:     feature.hasDuration = false;
cannam@198:     feature.label = "";
cannam@198:     feature.values.clear();
cannam@198:     feature.values.push_back(0.f);
cannam@198: 
cannam@200:     char buffer[40];
cannam@198: 
cannam@198:     int n = m_n;
cannam@198: 
cannam@198:     for (int i = 0; i < n; ++i) {
cannam@208:         feature.timestamp = m_start +
cannam@208:             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
cannam@200:         feature.values[0] = m_df[i];
cannam@198:         feature.label = "";
cannam@200:         fs[DFOutput].push_back(feature);
cannam@198:     }
cannam@198: 
cannam@199:     for (int i = 1; i < n/2; ++i) {
cannam@208:         feature.timestamp = m_start +
cannam@208:             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
cannam@200:         feature.values[0] = m_r[i];
cannam@199:         sprintf(buffer, "%.1f bpm", lag2tempo(i));
cannam@200:         if (i == n/2-1) feature.label = "";
cannam@200:         else feature.label = buffer;
cannam@200:         fs[ACFOutput].push_back(feature);
cannam@198:     }
cannam@198: 
cannam@243:     float t0 = m_minbpm; // our minimum detected tempo
cannam@243:     float t1 = m_maxbpm; // our maximum detected tempo
cannam@216: 
cannam@207:     int p0 = tempo2lag(t1);
cannam@207:     int p1 = tempo2lag(t0);
cannam@198: 
cannam@200:     std::map<float, int> candidates;
cannam@198: 
cannam@200:     for (int i = p0; i <= p1 && i < n/2-1; ++i) {
cannam@198: 
cannam@209:         if (m_fr[i] > m_fr[i-1] &&
cannam@209:             m_fr[i] > m_fr[i+1]) {
cannam@209:             candidates[m_fr[i]] = i;
cannam@209:         }
cannam@198: 
cannam@208:         feature.timestamp = m_start +
cannam@208:             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
cannam@200:         feature.values[0] = m_fr[i];
cannam@199:         sprintf(buffer, "%.1f bpm", lag2tempo(i));
cannam@200:         if (i == p1 || i == n/2-2) feature.label = "";
cannam@200:         else feature.label = buffer;
cannam@200:         fs[FilteredACFOutput].push_back(feature);
cannam@198:     }
cannam@198: 
cannam@200:     if (candidates.empty()) {
cannam@207:         cerr << "No tempo candidates!" << endl;
cannam@200:         return fs;
cannam@200:     }
cannam@198: 
cannam@198:     feature.hasTimestamp = true;
cannam@198:     feature.timestamp = m_start;
cannam@198:     
cannam@198:     feature.hasDuration = true;
cannam@198:     feature.duration = m_lasttime - m_start;
cannam@198: 
cannam@200:     std::map<float, int>::const_iterator ci = candidates.end();
cannam@200:     --ci;
cannam@200:     int maxpi = ci->second;
cannam@198: 
cannam@204:     if (m_t[maxpi] > 0) {
cannam@207:         cerr << "*** Using adjusted tempo " << m_t[maxpi] << " instead of lag tempo " << lag2tempo(maxpi) << endl;
cannam@204:         feature.values[0] = m_t[maxpi];
cannam@204:     } else {
cannam@204:         // shouldn't happen -- it would imply that this high value was not a peak!
cannam@204:         feature.values[0] = lag2tempo(maxpi);
cannam@207:         cerr << "WARNING: No stored tempo for index " << maxpi << endl;
cannam@204:     }
cannam@204: 
cannam@204:     sprintf(buffer, "%.1f bpm", feature.values[0]);
cannam@199:     feature.label = buffer;
cannam@199: 
cannam@200:     fs[TempoOutput].push_back(feature);
cannam@198: 
cannam@200:     feature.values.clear();
cannam@200:     feature.label = "";
cannam@200: 
cannam@200:     while (feature.values.size() < 8) {
cannam@207:         if (m_t[ci->second] > 0) {
cannam@207:             feature.values.push_back(m_t[ci->second]);
cannam@207:         } else {
cannam@207:             feature.values.push_back(lag2tempo(ci->second));
cannam@207:         }
cannam@200:         if (ci == candidates.begin()) break;
cannam@200:         --ci;
cannam@200:     }
cannam@200: 
cannam@200:     fs[CandidatesOutput].push_back(feature);
cannam@200:     
cannam@198:     return fs;
cannam@198: }
cannam@243: 
cannam@243:     
cannam@243: 
cannam@243: FixedTempoEstimator::FixedTempoEstimator(float inputSampleRate) :
cannam@243:     Plugin(inputSampleRate),
cannam@243:     m_d(new D(inputSampleRate))
cannam@243: {
cannam@243: }
cannam@243: 
cannam@243: FixedTempoEstimator::~FixedTempoEstimator()
cannam@243: {
cannam@243: }
cannam@243: 
cannam@243: string
cannam@243: FixedTempoEstimator::getIdentifier() const
cannam@243: {
cannam@243:     return "fixedtempo";
cannam@243: }
cannam@243: 
cannam@243: string
cannam@243: FixedTempoEstimator::getName() const
cannam@243: {
cannam@243:     return "Simple Fixed Tempo Estimator";
cannam@243: }
cannam@243: 
cannam@243: string
cannam@243: FixedTempoEstimator::getDescription() const
cannam@243: {
cannam@243:     return "Study a short section of audio and estimate its tempo, assuming the tempo is constant";
cannam@243: }
cannam@243: 
cannam@243: string
cannam@243: FixedTempoEstimator::getMaker() const
cannam@243: {
cannam@243:     return "Vamp SDK Example Plugins";
cannam@243: }
cannam@243: 
cannam@243: int
cannam@243: FixedTempoEstimator::getPluginVersion() const
cannam@243: {
cannam@243:     return 1;
cannam@243: }
cannam@243: 
cannam@243: string
cannam@243: FixedTempoEstimator::getCopyright() const
cannam@243: {
cannam@243:     return "Code copyright 2008 Queen Mary, University of London.  Freely redistributable (BSD license)";
cannam@243: }
cannam@243: 
cannam@243: size_t
cannam@243: FixedTempoEstimator::getPreferredStepSize() const
cannam@243: {
cannam@243:     return m_d->getPreferredStepSize();
cannam@243: }
cannam@243: 
cannam@243: size_t
cannam@243: FixedTempoEstimator::getPreferredBlockSize() const
cannam@243: {
cannam@243:     return m_d->getPreferredBlockSize();
cannam@243: }
cannam@243: 
cannam@243: bool
cannam@243: FixedTempoEstimator::initialise(size_t channels, size_t stepSize, size_t blockSize)
cannam@243: {
cannam@243:     if (channels < getMinChannelCount() ||
cannam@243: 	channels > getMaxChannelCount()) return false;
cannam@243: 
cannam@243:     return m_d->initialise(channels, stepSize, blockSize);
cannam@243: }
cannam@243: 
cannam@243: void
cannam@243: FixedTempoEstimator::reset()
cannam@243: {
cannam@243:     return m_d->reset();
cannam@243: }
cannam@243: 
cannam@243: FixedTempoEstimator::ParameterList
cannam@243: FixedTempoEstimator::getParameterDescriptors() const
cannam@243: {
cannam@243:     return m_d->getParameterDescriptors();
cannam@243: }
cannam@243: 
cannam@243: float
cannam@243: FixedTempoEstimator::getParameter(std::string id) const
cannam@243: {
cannam@243:     return m_d->getParameter(id);
cannam@243: }
cannam@243: 
cannam@243: void
cannam@243: FixedTempoEstimator::setParameter(std::string id, float value)
cannam@243: {
cannam@243:     m_d->setParameter(id, value);
cannam@243: }
cannam@243: 
cannam@243: FixedTempoEstimator::OutputList
cannam@243: FixedTempoEstimator::getOutputDescriptors() const
cannam@243: {
cannam@243:     return m_d->getOutputDescriptors();
cannam@243: }
cannam@243: 
cannam@243: FixedTempoEstimator::FeatureSet
cannam@243: FixedTempoEstimator::process(const float *const *inputBuffers, RealTime ts)
cannam@243: {
cannam@243:     return m_d->process(inputBuffers, ts);
cannam@243: }
cannam@243: 
cannam@243: FixedTempoEstimator::FeatureSet
cannam@243: FixedTempoEstimator::getRemainingFeatures()
cannam@243: {
cannam@243:     return m_d->getRemainingFeatures();
cannam@243: }