cannam@173: /* -*- c-basic-offset: 4 indent-tabs-mode: nil -*-  vi:set ts=8 sts=4 sw=4: */
cannam@173: 
cannam@173: /*
cannam@173:     Vamp
cannam@173: 
cannam@173:     An API for audio analysis and feature extraction plugins.
cannam@173: 
cannam@173:     Centre for Digital Music, Queen Mary, University of London.
cannam@173:     Copyright 2006-2008 Chris Cannam and QMUL.
cannam@173:   
cannam@173:     Permission is hereby granted, free of charge, to any person
cannam@173:     obtaining a copy of this software and associated documentation
cannam@173:     files (the "Software"), to deal in the Software without
cannam@173:     restriction, including without limitation the rights to use, copy,
cannam@173:     modify, merge, publish, distribute, sublicense, and/or sell copies
cannam@173:     of the Software, and to permit persons to whom the Software is
cannam@173:     furnished to do so, subject to the following conditions:
cannam@173: 
cannam@173:     The above copyright notice and this permission notice shall be
cannam@173:     included in all copies or substantial portions of the Software.
cannam@173: 
cannam@173:     THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
cannam@173:     EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
cannam@173:     MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
cannam@173:     NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR
cannam@173:     ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF
cannam@173:     CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION
cannam@173:     WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
cannam@173: 
cannam@173:     Except as contained in this notice, the names of the Centre for
cannam@173:     Digital Music; Queen Mary, University of London; and Chris Cannam
cannam@173:     shall not be used in advertising or otherwise to promote the sale,
cannam@173:     use or other dealings in this Software without prior written
cannam@173:     authorization.
cannam@173: */
cannam@173: 
cannam@173: #ifndef _VAMP_PLUGIN_SUMMARISING_ADAPTER_H_
cannam@173: #define _VAMP_PLUGIN_SUMMARISING_ADAPTER_H_
cannam@173: 
cannam@173: #include "PluginWrapper.h"
cannam@173: 
cannam@174: #include <set>
cannam@174: 
cannam@173: namespace Vamp {
cannam@173: 
cannam@173: namespace HostExt {
cannam@173: 
cannam@197: /**
cannam@197:  * \class PluginSummarisingAdapter PluginSummarisingAdapter.h <vamp-sdk/hostext/PluginSummarisingAdapter.h>
cannam@197:  *
cannam@216:  * \note This class was introduced in version 2.0 of the Vamp plugin SDK.
cannam@197:  */
cannam@197: 
cannam@173: class PluginSummarisingAdapter : public PluginWrapper
cannam@173: {
cannam@173: public:
cannam@173:     PluginSummarisingAdapter(Plugin *plugin); // I take ownership of plugin
cannam@173:     virtual ~PluginSummarisingAdapter();
cannam@173: 
cannam@195:     bool initialise(size_t channels, size_t stepSize, size_t blockSize);
cannam@176: 
cannam@173:     FeatureSet process(const float *const *inputBuffers, RealTime timestamp);
cannam@173:     FeatureSet getRemainingFeatures();
cannam@173: 
cannam@173:     typedef std::set<RealTime> SegmentBoundaries;
cannam@173:     void setSummarySegmentBoundaries(const SegmentBoundaries &);
cannam@173: 
cannam@173:     enum SummaryType {
cannam@179:         Minimum            = 0,
cannam@179:         Maximum            = 1,
cannam@179:         Mean               = 2,
cannam@179:         Median             = 3,
cannam@179:         Mode               = 4,
cannam@179:         Sum                = 5,
cannam@179:         Variance           = 6,
cannam@179:         StandardDeviation  = 7,
cannam@179:         Count              = 8,
cannam@179: 
cannam@179:         UnknownSummaryType = 999
cannam@173:     };
cannam@173: 
cannam@180:     /**
cannam@180:      * AveragingMethod indicates how the adapter should handle
cannam@180:      * average-based summaries of features whose results are not
cannam@180:      * equally spaced in time.
cannam@180:      *
cannam@180:      * If SampleAverage is specified, summary types based on averages
cannam@180:      * will be calculated by treating each result individually without
cannam@180:      * regard to its time: for example, the mean will be the sum of
cannam@180:      * all values divided by the number of values.
cannam@180:      *
cannam@180:      * If ContinuousTimeAverage is specified, each feature will be
cannam@180:      * considered to have a duration, either as specified in the
cannam@180:      * feature's duration field, or until the following feature: thus,
cannam@180:      * for example, the mean will be the sum of the products of values
cannam@180:      * and durations, divided by the total duration.
cannam@180:      *
cannam@180:      * Although SampleAverage is useful for many types of feature,
cannam@180:      * ContinuousTimeAverage is essential for some situations, for
cannam@180:      * example finding the result that spans the largest proportion of
cannam@180:      * the input given a feature that emits a new result only when the
cannam@180:      * value changes (the modal value integrated over time).
cannam@180:      */
cannam@180:     enum AveragingMethod {
cannam@180:         SampleAverage         = 0,
cannam@180:         ContinuousTimeAverage = 1,
cannam@180:     };
cannam@180: 
cannam@180:     FeatureList getSummaryForOutput(int output,
cannam@180:                                     SummaryType type,
cannam@180:                                     AveragingMethod method = SampleAverage);
cannam@180: 
cannam@180:     FeatureSet getSummaryForAllOutputs(SummaryType type,
cannam@180:                                        AveragingMethod method = SampleAverage);
cannam@173: 
cannam@173: protected:
cannam@173:     class Impl;
cannam@173:     Impl *m_impl;
cannam@173: };
cannam@173: 
cannam@173: }
cannam@173: 
cannam@173: }
cannam@173: 
cannam@173: #endif