annotate vamp-hostsdk/PluginSummarisingAdapter.h @ 241:70e6826adc64

* Add Power Spectrum example plugin

/* -*- 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 2006-2008 Chris Cannam and QMUL.
  
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    obtaining a copy of this software and associated documentation
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    of the Software, and to permit persons to whom the Software is
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    The above copyright notice and this permission notice shall be
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    Except as contained in this notice, the names of the Centre for
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*/

#ifndef _VAMP_PLUGIN_SUMMARISING_ADAPTER_H_
#define _VAMP_PLUGIN_SUMMARISING_ADAPTER_H_

#include "PluginWrapper.h"

#include <set>

namespace Vamp {

namespace HostExt {

/**
 * \class PluginSummarisingAdapter PluginSummarisingAdapter.h <vamp-hostsdk/PluginSummarisingAdapter.h>
 *
 * \note This class was introduced in version 2.0 of the Vamp plugin SDK.
 */

class PluginSummarisingAdapter : public PluginWrapper
{
public:
    PluginSummarisingAdapter(Plugin *plugin); // I take ownership of plugin
    virtual ~PluginSummarisingAdapter();

    bool initialise(size_t channels, size_t stepSize, size_t blockSize);

    FeatureSet process(const float *const *inputBuffers, RealTime timestamp);
    FeatureSet getRemainingFeatures();

    typedef std::set<RealTime> SegmentBoundaries;
    void setSummarySegmentBoundaries(const SegmentBoundaries &);

    enum SummaryType {
        Minimum            = 0,
        Maximum            = 1,
        Mean               = 2,
        Median             = 3,
        Mode               = 4,
        Sum                = 5,
        Variance           = 6,
        StandardDeviation  = 7,
        Count              = 8,

        UnknownSummaryType = 999
    };

    /**
     * AveragingMethod indicates how the adapter should handle
     * average-based summaries of features whose results are not
     * equally spaced in time.
     *
     * If SampleAverage is specified, summary types based on averages
     * will be calculated by treating each result individually without
     * regard to its time: for example, the mean will be the sum of
     * all values divided by the number of values.
     *
     * If ContinuousTimeAverage is specified, each feature will be
     * considered to have a duration, either as specified in the
     * feature's duration field, or until the following feature: thus,
     * for example, the mean will be the sum of the products of values
     * and durations, divided by the total duration.
     *
     * Although SampleAverage is useful for many types of feature,
     * ContinuousTimeAverage is essential for some situations, for
     * example finding the result that spans the largest proportion of
     * the input given a feature that emits a new result only when the
     * value changes (the modal value integrated over time).
     */
    enum AveragingMethod {
        SampleAverage         = 0,
        ContinuousTimeAverage = 1,
    };

    FeatureList getSummaryForOutput(int output,
                                    SummaryType type,
                                    AveragingMethod method = SampleAverage);

    FeatureSet getSummaryForAllOutputs(SummaryType type,
                                       AveragingMethod method = SampleAverage);

protected:
    class Impl;
    Impl *m_impl;
};

}

}

#endif