wolffd@0: classdef MTTMixedFeatureGenreBasicSm < MTTAudioFeature & handle
wolffd@0:     % ---
wolffd@0:     %
wolffd@0:     % The usual worklow for these features constist of three steps
wolffd@0:     % 1. extract: extracts the basic single-file dependent features
wolffd@0:     % 2. define_global_transform: calculates the global feature
wolffd@0:     %       transformation parameters
wolffd@0:     % 3. finalise: applies the common transformations to a specific feature
wolffd@0:     % ---
wolffd@0:     
wolffd@0:     properties(Constant = true)
wolffd@0:         
wolffd@0:         % svn hook
wolffd@0:         my_revision = str2double(substr('$Rev$',  5, -1));
wolffd@0:     end
wolffd@0:        
wolffd@0:     properties
wolffd@0:         % ---
wolffd@0:         % Set default parameters
wolffd@0:         % ---
wolffd@0:         my_params = MTTAudioFeature.inherited_params(...
wolffd@0:             'MTTAudioFeatureBasicSm', ...
wolffd@0:             ... % ---
wolffd@0:             ... % following are GenreBasic parameters
wolffd@0:             ... % --- 
wolffd@0:             'pct_genres', 1 ... % 1/100 percentile genre tags used
wolffd@0:         );
wolffd@0:     end
wolffd@0:     
wolffd@0:     % ---
wolffd@0:     % member functions
wolffd@0:     % ---
wolffd@0:     methods
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % constructor: pointer to feature in database
wolffd@0:         % ---
wolffd@0:         function feature = MTTMixedFeatureGenreBasicSm(varargin)
wolffd@0: 
wolffd@0:             feature = feature@MTTAudioFeature(varargin{:});
wolffd@0:         end
wolffd@0: 
wolffd@0:         % ---
wolffd@0:         % extract feature data by combining genre adn basicsm features
wolffd@0:         % ---
wolffd@0:         function data = extract(feature, clip)
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % get Basic Summary audio features. this includes possible
wolffd@0:             % local normalisations
wolffd@0:             % ---
wolffd@0:             basicsm = clip.audio_features_basicsm(feature.my_params);
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % get genre tag features
wolffd@0:             % ---
wolffd@0:             
wolffd@0:             genrebasic = clip.genre_features_basic(feature.my_params);
wolffd@0:             
wolffd@0:             % save to features data field
wolffd@0:             data.audio = basicsm;
wolffd@0:             data.tags = genrebasic;
wolffd@0:             
wolffd@0:             % prepare field for final features
wolffd@0:             data.final.vector = [];
wolffd@0:             data.final.vector_info = struct(); 
wolffd@0:             data.final.dim = 0;
wolffd@0:            
wolffd@0:             % save info data
wolffd@0:             data.info.type = 'MTTMixedFeatureGenreBasicSm';
wolffd@0:             data.info.owner_id = clip.id;
wolffd@0:             data.info.creatorrev = feature.my_revision;
wolffd@0:             
wolffd@0:             % save parameters
wolffd@0:             data.info.params = feature.my_params;
wolffd@0:         end
wolffd@0:         
wolffd@0:         function define_global_transform(features)
wolffd@0:         % calculate and set normalization factors from the group of 
wolffd@0:         % input features. These features will be set for the full database
wolffd@0:         
wolffd@0:             if numel(features) == 1
wolffd@0:                 error ('Insert feature array for this method');
wolffd@0:             end
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % We collect all the relevant basicsm 
wolffd@0:             % features and get the transform on this basis.
wolffd@0:             % ---
wolffd@0:             for i = 1:numel(features)
wolffd@0:             	basicsm(i) = features(i).data.audio;
wolffd@0:             end
wolffd@0:             
wolffd@0:             % call the features own transsform function
wolffd@0:             basicsm.define_global_transform();
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % We collect all the relevant genretag 
wolffd@0:             % features and get the transform on this basis.
wolffd@0:             % ---
wolffd@0:             for i = 1:numel(features)
wolffd@0:             	genrebasic(i) = features(i).data.tags;
wolffd@0:             end
wolffd@0:             
wolffd@0:             % call the features own transsform function
wolffd@0:             genrebasic.define_global_transform();
wolffd@0:             
wolffd@0:             % ---
wolffd@0:             % set common feature values for mixed features
wolffd@0:             % ---
wolffd@0:             features(1).my_db.set_common([1]); %trivial common
wolffd@0:         end
wolffd@0:         
wolffd@0:         
wolffd@0:         function finalise(feature)
wolffd@0:         % applies a final transformation and collects the 
wolffd@0:         % information of this feature within a single vector
wolffd@0:         % see info for types in specific dimensions
wolffd@0: 
wolffd@0:             for i = 1:numel(feature)
wolffd@0:                 
wolffd@0:                 % check for neccesary parameters
wolffd@0:                 if isempty(feature(i).my_db.commondb)
wolffd@0: 
wolffd@0:                     error('Define the global transformation first');
wolffd@0:                 end
wolffd@0:                 
wolffd@0:                 % ---
wolffd@0:                 % finalise audio feature and get vector
wolffd@0:                 % ---
wolffd@0:                 basicsm = feature(i).data.audio;
wolffd@0:                 basicsm.finalise();
wolffd@0:                 
wolffd@0:                 % finalise tag features
wolffd@0:                 genrebasic = feature(i).data.tags;
wolffd@0:                 genrebasic.finalise;
wolffd@0:                 
wolffd@0:                 % ---
wolffd@0:                 % final data assembly
wolffd@0:                 % ---
wolffd@0:                 
wolffd@0:                 % concatenate vectors
wolffd@0:                 feature(i).data.final.vector = ...
wolffd@0:                     [basicsm.vector() ; genrebasic.vector()];
wolffd@0:                 
wolffd@0:                 % add feature dimensions
wolffd@0:                 feature(i).data.final.dim = basicsm.dim + genrebasic.dim;
wolffd@0:                 
wolffd@0:                 % concatenate labels
wolffd@0:                 feature(i).data.final.vector_info.labels = ...
wolffd@0:                     {basicsm.data.final.vector_info.labels{:}, ...
wolffd@0:                     genrebasic.data.final.vector_info.labels{:}};
wolffd@0:             end
wolffd@0:         end
wolffd@0:         
wolffd@0:         % ---
wolffd@0:         % destructor: do we really want to remove this 
wolffd@0:         % from the database? No, but 
wolffd@0:         % TODO: create marker for unused objects in db, and a cleanup
wolffd@0:         %  function
wolffd@0:         % ---
wolffd@0:         function delete(feature)
wolffd@0:             
wolffd@0:         end
wolffd@0:        
wolffd@0:         function visualise(feature)
wolffd@0:         % ---
wolffd@0:         % plots the different data types collected in this feature
wolffd@0:         % ---
wolffd@0:             for i = 1:numel(feature)
wolffd@0:                 clip = MTTClip(feature(i).owner_id());
wolffd@0:             end
wolffd@0:         end
wolffd@0:     end
wolffd@0: end