tip/code-docs/FixedTempoEstimator_8cpp_source.html

 /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */

 /*
     Vamp

     An API for audio analysis and feature extraction plugins.

     Centre for Digital Music, Queen Mary, University of London.
     Copyright 2006-2009 Chris Cannam and QMUL.

     Permission is hereby granted, free of charge, to any person
     obtaining a copy of this software and associated documentation
     files (the "Software"), to deal in the Software without
     restriction, including without limitation the rights to use, copy,
     modify, merge, publish, distribute, sublicense, and/or sell copies
     of the Software, and to permit persons to whom the Software is
     furnished to do so, subject to the following conditions:

     The above copyright notice and this permission notice shall be
     included in all copies or substantial portions of the Software.

     THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
     EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
     MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
     NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
     ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
     CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
     WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

     Except as contained in this notice, the names of the Centre for
     Digital Music; Queen Mary, University of London; and Chris Cannam
     shall not be used in advertising or otherwise to promote the sale,
     use or other dealings in this Software without prior written
     authorization.
 */

 #include "FixedTempoEstimator.h"

 using std::string;
 using std::vector;
 using std::cerr;
 using std::endl;

 using Vamp::RealTime;

 #include <cmath>
 #include <cstdio>


 class FixedTempoEstimator::D
 // this class just avoids us having to declare any data members in the header
 {
 public:
     D(float inputSampleRate);
     ~D();

     size_t getPreferredStepSize() const { return 64; }
     size_t getPreferredBlockSize() const { return 256; }

     ParameterList getParameterDescriptors() const;
     float getParameter(string id) const;
     void setParameter(string id, float value);

     OutputList getOutputDescriptors() const;

     bool initialise(size_t channels, size_t stepSize, size_t blockSize);
     void reset();
     FeatureSet process(const float *const *, RealTime);
     FeatureSet getRemainingFeatures();

 private:
     void calculate();
     FeatureSet assembleFeatures();

     float lag2tempo(int);
     int tempo2lag(float);

     float m_inputSampleRate;
     size_t m_stepSize;
     size_t m_blockSize;

     float m_minbpm;
     float m_maxbpm;
     float m_maxdflen;

     float *m_priorMagnitudes;

     size_t m_dfsize;
     float *m_df;
     float *m_r;
     float *m_fr;
     float *m_t;
     size_t m_n;

     Vamp::RealTime m_start;
     Vamp::RealTime m_lasttime;
 };

 FixedTempoEstimator::D::D(float inputSampleRate) :
     m_inputSampleRate(inputSampleRate),
     m_stepSize(0),
     m_blockSize(0),
     m_minbpm(50),
     m_maxbpm(190),
     m_maxdflen(10),
     m_priorMagnitudes(0),
     m_df(0),
     m_r(0),
     m_fr(0),
     m_t(0),
     m_n(0)
 {
 }

 FixedTempoEstimator::D::~D()
 {
     delete[] m_priorMagnitudes;
     delete[] m_df;
     delete[] m_r;
     delete[] m_fr;
     delete[] m_t;
 }

 FixedTempoEstimator::ParameterList
 FixedTempoEstimator::D::getParameterDescriptors() const
 {
     ParameterList list;

     ParameterDescriptor d;
     d.identifier = "minbpm";
     d.name = "Minimum estimated tempo";
     d.description = "Minimum beat-per-minute value which the tempo estimator is able to return";
     d.unit = "bpm";
     d.minValue = 10;
     d.maxValue = 360;
     d.defaultValue = 50;
     d.isQuantized = false;
     list.push_back(d);

     d.identifier = "maxbpm";
     d.name = "Maximum estimated tempo";
     d.description = "Maximum beat-per-minute value which the tempo estimator is able to return";
     d.defaultValue = 190;
     list.push_back(d);

     d.identifier = "maxdflen";
     d.name = "Input duration to study";
     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.";
     d.unit = "s";
     d.minValue = 2;
     d.maxValue = 40;
     d.defaultValue = 10;
     list.push_back(d);

     return list;
 }

 float
 FixedTempoEstimator::D::getParameter(string id) const
 {
     if (id == "minbpm") {
         return m_minbpm;
     } else if (id == "maxbpm") {
         return m_maxbpm;
     } else if (id == "maxdflen") {
         return m_maxdflen;
     }
     return 0.f;
 }

 void
 FixedTempoEstimator::D::setParameter(string id, float value)
 {
     if (id == "minbpm") {
         m_minbpm = value;
     } else if (id == "maxbpm") {
         m_maxbpm = value;
     } else if (id == "maxdflen") {
         m_maxdflen = value;
     }
 }

 static int TempoOutput = 0;
 static int CandidatesOutput = 1;
 static int DFOutput = 2;
 static int ACFOutput = 3;
 static int FilteredACFOutput = 4;

 FixedTempoEstimator::OutputList
 FixedTempoEstimator::D::getOutputDescriptors() const
 {
     OutputList list;

     OutputDescriptor d;
     d.identifier = "tempo";
     d.name = "Tempo";
     d.description = "Estimated tempo";
     d.unit = "bpm";
     d.hasFixedBinCount = true;
     d.binCount = 1;
     d.hasKnownExtents = false;
     d.isQuantized = false;
     d.sampleType = OutputDescriptor::VariableSampleRate;
     d.sampleRate = m_inputSampleRate;
     d.hasDuration = true; // our returned tempo spans a certain range
     list.push_back(d);

     d.identifier = "candidates";
     d.name = "Tempo candidates";
     d.description = "Possible tempo estimates, one per bin with the most likely in the first bin";
     d.unit = "bpm";
     d.hasFixedBinCount = false;
     list.push_back(d);

     d.identifier = "detectionfunction";
     d.name = "Detection Function";
     d.description = "Onset detection function";
     d.unit = "";
     d.hasFixedBinCount = 1;
     d.binCount = 1;
     d.hasKnownExtents = true;
     d.minValue = 0.0;
     d.maxValue = 1.0;
     d.isQuantized = false;
     d.quantizeStep = 0.0;
     d.sampleType = OutputDescriptor::FixedSampleRate;
     if (m_stepSize) {
         d.sampleRate = m_inputSampleRate / m_stepSize;
     } else {
         d.sampleRate = m_inputSampleRate / (getPreferredBlockSize()/2);
     }
     d.hasDuration = false;
     list.push_back(d);

     d.identifier = "acf";
     d.name = "Autocorrelation Function";
     d.description = "Autocorrelation of onset detection function";
     d.hasKnownExtents = false;
     d.unit = "r";
     list.push_back(d);

     d.identifier = "filtered_acf";
     d.name = "Filtered Autocorrelation";
     d.description = "Filtered autocorrelation of onset detection function";
     d.unit = "r";
     list.push_back(d);

     return list;
 }

 bool
 FixedTempoEstimator::D::initialise(size_t, size_t stepSize, size_t blockSize)
 {
     m_stepSize = stepSize;
     m_blockSize = blockSize;

     float dfLengthSecs = m_maxdflen;
     m_dfsize = (dfLengthSecs * m_inputSampleRate) / m_stepSize;

     m_priorMagnitudes = new float[m_blockSize/2];
     m_df = new float[m_dfsize];

     for (size_t i = 0; i < m_blockSize/2; ++i) {
         m_priorMagnitudes[i] = 0.f;
     }
     for (size_t i = 0; i < m_dfsize; ++i) {
         m_df[i] = 0.f;
     }

     m_n = 0;

     return true;
 }

 void
 FixedTempoEstimator::D::reset()
 {
     if (!m_priorMagnitudes) return;

     for (size_t i = 0; i < m_blockSize/2; ++i) {
         m_priorMagnitudes[i] = 0.f;
     }
     for (size_t i = 0; i < m_dfsize; ++i) {
         m_df[i] = 0.f;
     }

     delete[] m_r;
     m_r = 0;

     delete[] m_fr;
     m_fr = 0;

     delete[] m_t;
     m_t = 0;

     m_n = 0;

     m_start = RealTime::zeroTime;
     m_lasttime = RealTime::zeroTime;
 }

 FixedTempoEstimator::FeatureSet
 FixedTempoEstimator::D::process(const float *const *inputBuffers, RealTime ts)
 {
     FeatureSet fs;

     if (m_stepSize == 0) {
         cerr << "ERROR: FixedTempoEstimator::process: "
              << "FixedTempoEstimator has not been initialised"
              << endl;
         return fs;
     }

     if (m_n == 0) m_start = ts;
     m_lasttime = ts;

     if (m_n == m_dfsize) {
         // If we have seen enough input, do the estimation and return
         calculate();
         fs = assembleFeatures();
         ++m_n;
         return fs;
     }

     // If we have seen more than enough, just discard and return!
     if (m_n > m_dfsize) return FeatureSet();

     float value = 0.f;

     // m_df will contain an onset detection function based on the rise
     // in overall power from one spectral frame to the next --
     // simplistic but reasonably effective for our purposes.

     for (size_t i = 1; i < m_blockSize/2; ++i) {

         float real = inputBuffers[0][i*2];
         float imag = inputBuffers[0][i*2 + 1];

         float sqrmag = real * real + imag * imag;
         value += fabsf(sqrmag - m_priorMagnitudes[i]);

         m_priorMagnitudes[i] = sqrmag;
     }

     m_df[m_n] = value;

     ++m_n;
     return fs;
 }

 FixedTempoEstimator::FeatureSet
 FixedTempoEstimator::D::getRemainingFeatures()
 {
     FeatureSet fs;
     if (m_n > m_dfsize) return fs;
     calculate();
     fs = assembleFeatures();
     ++m_n;
     return fs;
 }

 float
 FixedTempoEstimator::D::lag2tempo(int lag)
 {
     return 60.f / ((lag * m_stepSize) / m_inputSampleRate);
 }

 int
 FixedTempoEstimator::D::tempo2lag(float tempo)
 {
     return ((60.f / tempo) * m_inputSampleRate) / m_stepSize;
 }

 void
 FixedTempoEstimator::D::calculate()
 {
     if (m_r) {
         cerr << "FixedTempoEstimator::calculate: calculation already happened?" << endl;
         return;
     }

     if (m_n < m_dfsize / 9 &&
         m_n < (1.0 * m_inputSampleRate) / m_stepSize) { // 1 second
         cerr << "FixedTempoEstimator::calculate: Input is too short" << endl;
         return;
     }

     // This function takes m_df (the detection function array filled
     // out in process()) and calculates m_r (the raw autocorrelation)
     // and m_fr (the filtered autocorrelation from whose peaks tempo
     // estimates will be taken).

     int n = m_n; // length of actual df array (m_dfsize is the theoretical max)

     m_r  = new float[n/2]; // raw autocorrelation
     m_fr = new float[n/2]; // filtered autocorrelation
     m_t  = new float[n/2]; // averaged tempo estimate for each lag value

     for (int i = 0; i < n/2; ++i) {
         m_r[i]  = 0.f;
         m_fr[i] = 0.f;
         m_t[i]  = lag2tempo(i);
     }

     // Calculate the raw autocorrelation of the detection function

     for (int i = 0; i < n/2; ++i) {

         for (int j = i; j < n; ++j) {
             m_r[i] += m_df[j] * m_df[j - i];
         }

         m_r[i] /= n - i - 1;
     }

     // Filter the autocorrelation and average out the tempo estimates

     float related[] = { 0.5, 2, 4, 8 };

     for (int i = 1; i < n/2-1; ++i) {

         m_fr[i] = m_r[i];

         int div = 1;

         for (int j = 0; j < int(sizeof(related)/sizeof(related[0])); ++j) {

             // Check for an obvious peak at each metrically related lag

             int k0 = int(i * related[j] + 0.5);

             if (k0 >= 0 && k0 < int(n/2)) {

                 int kmax = 0;
                 float kvmax = 0, kvmin = 0;
                 bool have = false;

                 for (int k = k0 - 1; k <= k0 + 1; ++k) {

                     if (k < 0 || k >= n/2) continue;

                     if (!have || (m_r[k] > kvmax)) { kvmax = m_r[k]; kmax = k; }
                     if (!have || (m_r[k] < kvmin)) { kvmin = m_r[k]; }

                     have = true;
                 }

                 // Boost the original lag according to the strongest
                 // value found close to this related lag

                 m_fr[i] += m_r[kmax] / 5;

                 if ((kmax == 0 || m_r[kmax] > m_r[kmax-1]) &&
                     (kmax == n/2-1 || m_r[kmax] > m_r[kmax+1]) &&
                     kvmax > kvmin * 1.05) {

                     // The strongest value close to the related lag is
                     // also a pretty good looking peak, so use it to
                     // improve our tempo estimate for the original lag

                     m_t[i] = m_t[i] + lag2tempo(kmax) * related[j];
                     ++div;
                 }
             }
         }

         m_t[i] /= div;

         // Finally apply a primitive perceptual weighting (to prefer
         // tempi of around 120-130)

         float weight = 1.f - fabsf(128.f - lag2tempo(i)) * 0.005;
         if (weight < 0.f) weight = 0.f;
         weight = weight * weight * weight;

         m_fr[i] += m_fr[i] * (weight / 3);
     }
 }

 FixedTempoEstimator::FeatureSet
 FixedTempoEstimator::D::assembleFeatures()
 {
     FeatureSet fs;
     if (!m_r) return fs; // No autocorrelation: no results

     Feature feature;
     feature.hasTimestamp = true;
     feature.hasDuration = false;
     feature.label = "";
     feature.values.clear();
     feature.values.push_back(0.f);

     char buffer[40];

     int n = m_n;

     for (int i = 0; i < n; ++i) {

         // Return the detection function in the DF output

         feature.timestamp = m_start +
             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
         feature.values[0] = m_df[i];
         feature.label = "";
         fs[DFOutput].push_back(feature);
     }

     for (int i = 1; i < n/2; ++i) {

         // Return the raw autocorrelation in the ACF output, each
         // value labelled according to its corresponding tempo

         feature.timestamp = m_start +
             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
         feature.values[0] = m_r[i];
         sprintf(buffer, "%.1f bpm", lag2tempo(i));
         if (i == n/2-1) feature.label = "";
         else feature.label = buffer;
         fs[ACFOutput].push_back(feature);
     }

     float t0 = m_minbpm; // our minimum detected tempo
     float t1 = m_maxbpm; // our maximum detected tempo

     int p0 = tempo2lag(t1);
     int p1 = tempo2lag(t0);

     std::map<float, int> candidates;

     for (int i = p0; i <= p1 && i+1 < n/2; ++i) {

         if (m_fr[i] > m_fr[i-1] &&
             m_fr[i] > m_fr[i+1]) {

             // This is a peak in the filtered autocorrelation: stick
             // it into the map from filtered autocorrelation to lag
             // index -- this sorts our peaks by filtered acf value

             candidates[m_fr[i]] = i;
         }

         // Also return the filtered autocorrelation in its own output

         feature.timestamp = m_start +
             RealTime::frame2RealTime(i * m_stepSize, m_inputSampleRate);
         feature.values[0] = m_fr[i];
         sprintf(buffer, "%.1f bpm", lag2tempo(i));
         if (i == p1 || i == n/2-2) feature.label = "";
         else feature.label = buffer;
         fs[FilteredACFOutput].push_back(feature);
     }

     if (candidates.empty()) {
         cerr << "No tempo candidates!" << endl;
         return fs;
     }

     feature.hasTimestamp = true;
     feature.timestamp = m_start;

     feature.hasDuration = true;
     feature.duration = m_lasttime - m_start;

     // The map contains only peaks and is sorted by filtered acf
     // value, so the final element in it is our "best" tempo guess

     std::map<float, int>::const_iterator ci = candidates.end();
     --ci;
     int maxpi = ci->second;

     if (m_t[maxpi] > 0) {

         // This lag has an adjusted tempo from the averaging process:
         // use it

         feature.values[0] = m_t[maxpi];

     } else {

         // shouldn't happen -- it would imply that this high value was
         // not a peak!

         feature.values[0] = lag2tempo(maxpi);
         cerr << "WARNING: No stored tempo for index " << maxpi << endl;
     }

     sprintf(buffer, "%.1f bpm", feature.values[0]);
     feature.label = buffer;

     // Return the best tempo in the main output

     fs[TempoOutput].push_back(feature);

     // And return the other estimates (up to the arbitrarily chosen
     // number of 10 of them) in the candidates output

     feature.values.clear();
     feature.label = "";

     while (feature.values.size() < 10) {
         if (m_t[ci->second] > 0) {
             feature.values.push_back(m_t[ci->second]);
         } else {
             feature.values.push_back(lag2tempo(ci->second));
         }
         if (ci == candidates.begin()) break;
         --ci;
     }

     fs[CandidatesOutput].push_back(feature);

     return fs;
 }


 FixedTempoEstimator::FixedTempoEstimator(float inputSampleRate) :
     Plugin(inputSampleRate),
     m_d(new D(inputSampleRate))
 {
 }

 FixedTempoEstimator::~FixedTempoEstimator()
 {
     delete m_d;
 }

 string
 FixedTempoEstimator::getIdentifier() const
 {
     return "fixedtempo";
 }

 string
 FixedTempoEstimator::getName() const
 {
     return "Simple Fixed Tempo Estimator";
 }

 string
 FixedTempoEstimator::getDescription() const
 {
     return "Study a short section of audio and estimate its tempo, assuming the tempo is constant";
 }

 string
 FixedTempoEstimator::getMaker() const
 {
     return "Vamp SDK Example Plugins";
 }

 int
 FixedTempoEstimator::getPluginVersion() const
 {
     return 1;
 }

 string
 FixedTempoEstimator::getCopyright() const
 {
     return "Code copyright 2008 Queen Mary, University of London.  Freely redistributable (BSD license)";
 }

 size_t
 FixedTempoEstimator::getPreferredStepSize() const
 {
     return m_d->getPreferredStepSize();
 }

 size_t
 FixedTempoEstimator::getPreferredBlockSize() const
 {
     return m_d->getPreferredBlockSize();
 }

 bool
 FixedTempoEstimator::initialise(size_t channels, size_t stepSize, size_t blockSize)
 {
     if (channels < getMinChannelCount() ||
         channels > getMaxChannelCount()) return false;

     return m_d->initialise(channels, stepSize, blockSize);
 }

 void
 FixedTempoEstimator::reset()
 {
     return m_d->reset();
 }

 FixedTempoEstimator::ParameterList
 FixedTempoEstimator::getParameterDescriptors() const
 {
     return m_d->getParameterDescriptors();
 }

 float
 FixedTempoEstimator::getParameter(std::string id) const
 {
     return m_d->getParameter(id);
 }

 void
 FixedTempoEstimator::setParameter(std::string id, float value)
 {
     m_d->setParameter(id, value);
 }

 FixedTempoEstimator::OutputList
 FixedTempoEstimator::getOutputDescriptors() const
 {
     return m_d->getOutputDescriptors();
 }

 FixedTempoEstimator::FeatureSet
 FixedTempoEstimator::process(const float *const *inputBuffers, RealTime ts)
 {
     return m_d->process(inputBuffers, ts);
 }

 FixedTempoEstimator::FeatureSet
 FixedTempoEstimator::getRemainingFeatures()
 {
     return m_d->getRemainingFeatures();
 }
Vamp::Plugin::OutputList
std::vector< OutputDescriptor > OutputList
Definition: vamp-sdk/Plugin.h:335

Chris@6: FixedTempoEstimator::getPreferredStepSize
size_t getPreferredStepSize() const
Get the preferred step size (window increment – the distance in sample frames between the start fram...
Definition: FixedTempoEstimator.cpp:665

Chris@6: FixedTempoEstimator::D::m_priorMagnitudes
float * m_priorMagnitudes
Definition: FixedTempoEstimator.cpp:86

Chris@6: FixedTempoEstimator::getOutputDescriptors
OutputList getOutputDescriptors() const
Get the outputs of this plugin.
Definition: FixedTempoEstimator.cpp:710

Chris@6: Vamp::Plugin::OutputDescriptor::hasDuration
bool hasDuration
True if the returned results for this output are known to have a duration field.
Definition: vamp-sdk/Plugin.h:320

Chris@6: ACFOutput
static int ACFOutput
Definition: FixedTempoEstimator.cpp:186

Chris@6: Vamp::Plugin::Feature::label
std::string label
Label for the sample of this feature.
Definition: vamp-sdk/Plugin.h:387

Chris@6: FixedTempoEstimator::D::m_maxbpm
float m_maxbpm
Definition: FixedTempoEstimator.cpp:83

Chris@6: Vamp::Plugin::OutputDescriptor
Definition: vamp-sdk/Plugin.h:206

Chris@6: FixedTempoEstimator::process
FeatureSet process(const float *const *inputBuffers, Vamp::RealTime timestamp)
Process a single block of input data.
Definition: FixedTempoEstimator.cpp:716

Chris@6: Vamp::Plugin::OutputDescriptor::sampleRate
float sampleRate
Sample rate of the output results, as samples per second.
Definition: vamp-sdk/Plugin.h:314

Chris@6: FixedTempoEstimator::D::getRemainingFeatures
FeatureSet getRemainingFeatures()
Definition: FixedTempoEstimator.cpp:352

Chris@6: Vamp::Plugin::OutputDescriptor::hasFixedBinCount
bool hasFixedBinCount
True if the output has the same number of values per sample for every output sample.
Definition: vamp-sdk/Plugin.h:239

Chris@6: Vamp::Plugin::Feature::values
std::vector< float > values
Results for a single sample of this feature.
Definition: vamp-sdk/Plugin.h:382

Chris@6: Vamp::Plugin::OutputDescriptor::FixedSampleRate
Results are evenly spaced in time (sampleRate specified below)
Definition: vamp-sdk/Plugin.h:293

Chris@6: FixedTempoEstimator::~FixedTempoEstimator
virtual ~FixedTempoEstimator()
Definition: FixedTempoEstimator.cpp:623

Chris@6: Vamp::Plugin::FeatureSet
std::map< int, FeatureList > FeatureSet
Definition: vamp-sdk/Plugin.h:395

Chris@6: Vamp::Plugin::OutputDescriptor::quantizeStep
float quantizeStep
Quantization resolution of the output values (e.g.
Definition: vamp-sdk/Plugin.h:285

Chris@6: FixedTempoEstimator::getParameter
float getParameter(std::string id) const
Get the value of a named parameter.
Definition: FixedTempoEstimator.cpp:698

Chris@6: FixedTempoEstimator::getMaker
std::string getMaker() const
Get the name of the author or vendor of the plugin in human-readable form.
Definition: FixedTempoEstimator.cpp:647

Chris@6: FixedTempoEstimator::getCopyright
std::string getCopyright() const
Get the copyright statement or licensing summary for the plugin.
Definition: FixedTempoEstimator.cpp:659

Chris@6: Vamp::Plugin::Feature::timestamp
RealTime timestamp
Timestamp of the output feature.
Definition: vamp-sdk/Plugin.h:360

Chris@6: Vamp::PluginBase::ParameterDescriptor::identifier
std::string identifier
The name of the parameter, in computer-usable form.
Definition: vamp-sdk/PluginBase.h:133

Chris@6: Vamp::Plugin::OutputDescriptor::description
std::string description
A human-readable short text describing the output.
Definition: vamp-sdk/Plugin.h:227

Chris@6: Vamp::Plugin::Plugin
Plugin(float inputSampleRate)
Definition: vamp-sdk/Plugin.h:441

Chris@6: FixedTempoEstimator::reset
void reset()
Reset the plugin after use, to prepare it for another clean run.
Definition: FixedTempoEstimator.cpp:686

Chris@6: FixedTempoEstimator::D::getParameterDescriptors
ParameterList getParameterDescriptors() const
Definition: FixedTempoEstimator.cpp:125

Chris@6: Vamp::Plugin::OutputDescriptor::identifier
std::string identifier
The name of the output, in computer-usable form.
Definition: vamp-sdk/Plugin.h:214

Chris@6: Vamp::Plugin::OutputDescriptor::minValue
float minValue
Minimum value of the results in the output.
Definition: vamp-sdk/Plugin.h:266

Chris@6: FixedTempoEstimator::D::tempo2lag
int tempo2lag(float)
Definition: FixedTempoEstimator.cpp:369

Chris@6: FixedTempoEstimator::getName
std::string getName() const
Get a human-readable name or title of the plugin.
Definition: FixedTempoEstimator.cpp:635

Chris@6: FixedTempoEstimator::D::m_minbpm
float m_minbpm
Definition: FixedTempoEstimator.cpp:82

Chris@6: Vamp::PluginBase::ParameterDescriptor::name
std::string name
The human-readable name of the parameter.
Definition: vamp-sdk/PluginBase.h:138

Chris@6: Vamp::Plugin::Feature
Definition: vamp-sdk/Plugin.h:344

Chris@6: FixedTempoEstimator::D
Definition: FixedTempoEstimator.cpp:50

Chris@6: FixedTempoEstimator::D::m_stepSize
size_t m_stepSize
Definition: FixedTempoEstimator.cpp:79

Chris@6: Vamp::Plugin::OutputDescriptor::maxValue
float maxValue
Maximum value of the results in the output.
Definition: vamp-sdk/Plugin.h:272

Chris@6: FixedTempoEstimator::D::m_lasttime
Vamp::RealTime m_lasttime
Definition: FixedTempoEstimator.cpp:96

Chris@6: DFOutput
static int DFOutput
Definition: FixedTempoEstimator.cpp:185

Chris@6: Vamp::Plugin::Feature::duration
RealTime duration
Duration of the output feature.
Definition: vamp-sdk/Plugin.h:375

Chris@6: FixedTempoEstimator::D::m_dfsize
size_t m_dfsize
Definition: FixedTempoEstimator.cpp:88

Chris@6: Vamp::PluginBase::ParameterDescriptor::minValue
float minValue
The minimum value of the parameter.
Definition: vamp-sdk/PluginBase.h:154

Chris@6: FixedTempoEstimator::D::m_r
float * m_r
Definition: FixedTempoEstimator.cpp:90

Chris@6: FixedTempoEstimator::D::m_start
Vamp::RealTime m_start
Definition: FixedTempoEstimator.cpp:95

Chris@6: Vamp::PluginBase::ParameterDescriptor::unit
std::string unit
The unit of the parameter, in human-readable form.
Definition: vamp-sdk/PluginBase.h:149

Chris@6: Vamp::Plugin::OutputDescriptor::unit
std::string unit
The unit of the output, in human-readable form.
Definition: vamp-sdk/Plugin.h:232

Chris@6: Vamp::Plugin::getMinChannelCount
virtual size_t getMinChannelCount() const
Get the minimum supported number of input channels.
Definition: vamp-sdk/Plugin.h:199

Chris@6: FixedTempoEstimator.h

Chris@6: Vamp::Plugin::OutputDescriptor::name
std::string name
The human-readable name of the output.
Definition: vamp-sdk/Plugin.h:220

Chris@6: FixedTempoEstimator::D::getOutputDescriptors
OutputList getOutputDescriptors() const
Definition: FixedTempoEstimator.cpp:190

Chris@6: FixedTempoEstimator::D::getPreferredBlockSize
size_t getPreferredBlockSize() const
Definition: FixedTempoEstimator.cpp:58

Chris@6: Vamp::Plugin::getMaxChannelCount
virtual size_t getMaxChannelCount() const
Get the maximum supported number of input channels.
Definition: vamp-sdk/Plugin.h:204

Chris@6: FixedTempoEstimator::getIdentifier
std::string getIdentifier() const
Get the computer-usable name of the plugin.
Definition: FixedTempoEstimator.cpp:629

Chris@6: Vamp::RealTime
RealTime represents time values to nanosecond precision with accurate arithmetic and frame-rate conve...
Definition: vamp-sdk/RealTime.h:66

Chris@6: Vamp::Plugin::Feature::hasTimestamp
bool hasTimestamp
True if an output feature has its own timestamp.
Definition: vamp-sdk/Plugin.h:352

Chris@6: FixedTempoEstimator::D::m_t
float * m_t
Definition: FixedTempoEstimator.cpp:92

Chris@6: FixedTempoEstimator::getRemainingFeatures
FeatureSet getRemainingFeatures()
After all blocks have been processed, calculate and return any remaining features derived from the co...
Definition: FixedTempoEstimator.cpp:722

Chris@6: FixedTempoEstimator::D::getPreferredStepSize
size_t getPreferredStepSize() const
Definition: FixedTempoEstimator.cpp:57

Chris@6: FixedTempoEstimator::setParameter
void setParameter(std::string id, float value)
Set a named parameter.
Definition: FixedTempoEstimator.cpp:704

Chris@6: Vamp::PluginBase::ParameterDescriptor::description
std::string description
A human-readable short text describing the parameter.
Definition: vamp-sdk/PluginBase.h:144

Chris@6: Vamp::PluginBase::ParameterDescriptor
Definition: vamp-sdk/PluginBase.h:126

Chris@6: Vamp::PluginBase::ParameterDescriptor::maxValue
float maxValue
The maximum value of the parameter.
Definition: vamp-sdk/PluginBase.h:159

Chris@6: CandidatesOutput
static int CandidatesOutput
Definition: FixedTempoEstimator.cpp:184

Chris@6: FixedTempoEstimator::getPreferredBlockSize
size_t getPreferredBlockSize() const
Get the preferred block size (window size – the number of sample frames passed in each block to the ...
Definition: FixedTempoEstimator.cpp:671

Chris@6: FixedTempoEstimator::m_d
D * m_d
Definition: FixedTempoEstimator.h:79

Chris@6: FixedTempoEstimator::D::process
FeatureSet process(const float *const *, RealTime)
Definition: FixedTempoEstimator.cpp:303

Chris@6: FixedTempoEstimator::D::m_inputSampleRate
float m_inputSampleRate
Definition: FixedTempoEstimator.cpp:78

Chris@6: FixedTempoEstimator::D::m_blockSize
size_t m_blockSize
Definition: FixedTempoEstimator.cpp:80

Chris@6: FixedTempoEstimator::getParameterDescriptors
ParameterList getParameterDescriptors() const
Get the controllable parameters of this plugin.
Definition: FixedTempoEstimator.cpp:692

Chris@6: Vamp::Plugin::Feature::hasDuration
bool hasDuration
True if an output feature has a specified duration.
Definition: vamp-sdk/Plugin.h:368

Chris@6: FixedTempoEstimator::getDescription
std::string getDescription() const
Get a human-readable description for the plugin, typically a line of text that may optionally be disp...
Definition: FixedTempoEstimator.cpp:641

Chris@6: FixedTempoEstimator::D::m_n
size_t m_n
Definition: FixedTempoEstimator.cpp:93

Chris@6: FixedTempoEstimator::D::m_df
float * m_df
Definition: FixedTempoEstimator.cpp:89

Chris@6: FixedTempoEstimator::D::getParameter
float getParameter(string id) const
Definition: FixedTempoEstimator.cpp:159

Chris@6: FixedTempoEstimator::D::~D
~D()
Definition: FixedTempoEstimator.cpp:115

Chris@6: FilteredACFOutput
static int FilteredACFOutput
Definition: FixedTempoEstimator.cpp:187

Chris@6: Vamp::Plugin::OutputDescriptor::binCount
size_t binCount
The number of values per result of the output.
Definition: vamp-sdk/Plugin.h:247

Chris@6: FixedTempoEstimator::D::setParameter
void setParameter(string id, float value)
Definition: FixedTempoEstimator.cpp:172

Chris@6: FixedTempoEstimator::D::m_maxdflen
float m_maxdflen
Definition: FixedTempoEstimator.cpp:84

Chris@6: FixedTempoEstimator::initialise
bool initialise(size_t channels, size_t stepSize, size_t blockSize)
Initialise a plugin to prepare it for use with the given number of input channels, step size (window increment, in sample frames) and block size (window size, in sample frames).
Definition: FixedTempoEstimator.cpp:677

Chris@6: FixedTempoEstimator::D::initialise
bool initialise(size_t channels, size_t stepSize, size_t blockSize)
Definition: FixedTempoEstimator.cpp:252

Chris@6: FixedTempoEstimator::D::calculate
void calculate()
Definition: FixedTempoEstimator.cpp:375

Chris@6: Vamp::Plugin::OutputDescriptor::isQuantized
bool isQuantized
True if the output values are quantized to a particular resolution.
Definition: vamp-sdk/Plugin.h:278

Chris@6: FixedTempoEstimator::D::lag2tempo
float lag2tempo(int)
Definition: FixedTempoEstimator.cpp:363

Chris@6: TempoOutput
static int TempoOutput
Definition: FixedTempoEstimator.cpp:183

Chris@6: Vamp::PluginBase::ParameterDescriptor::defaultValue
float defaultValue
The default value of the parameter.
Definition: vamp-sdk/PluginBase.h:167

Chris@6: FixedTempoEstimator::D::reset
void reset()
Definition: FixedTempoEstimator.cpp:276

Chris@6: FixedTempoEstimator::getPluginVersion
int getPluginVersion() const
Get the version number of the plugin.
Definition: FixedTempoEstimator.cpp:653

Chris@6: Vamp::PluginBase::ParameterDescriptor::isQuantized
bool isQuantized
True if the parameter values are quantized to a particular resolution.
Definition: vamp-sdk/PluginBase.h:173

Chris@6: FixedTempoEstimator::D::assembleFeatures
FeatureSet assembleFeatures()
Definition: FixedTempoEstimator.cpp:481

Chris@6: FixedTempoEstimator::FixedTempoEstimator
FixedTempoEstimator(float inputSampleRate)
Definition: FixedTempoEstimator.cpp:617

Chris@6: FixedTempoEstimator::D::m_fr
float * m_fr
Definition: FixedTempoEstimator.cpp:91

Chris@6: Vamp::Plugin::OutputDescriptor::sampleType
SampleType sampleType
Positioning in time of the output results.
Definition: vamp-sdk/Plugin.h:302

Chris@6: FixedTempoEstimator::D::D
D(float inputSampleRate)
Definition: FixedTempoEstimator.cpp:99

Chris@6: Vamp::Plugin::OutputDescriptor::VariableSampleRate
Results are unevenly spaced and have individual timestamps.
Definition: vamp-sdk/Plugin.h:296

Chris@6: Vamp::Plugin::OutputDescriptor::hasKnownExtents
bool hasKnownExtents
True if the results in each output bin fall within a fixed numeric range (minimum and maximum values)...
Definition: vamp-sdk/Plugin.h:260

Chris@6: Vamp::PluginBase::ParameterList
std::vector< ParameterDescriptor > ParameterList
Definition: vamp-sdk/PluginBase.h:203

Chris@6: