comparison core/magnatagatune/DistMeasureMahal.m @ 0:e9a9cd732c1e tip

first hg version after svn

+% ---
+% The DistMeasureMahal class states a wrapper for 
+% special Mahalanobis similarity distance, and is compatible with the 
+% DistMeasure class
+% ---
+classdef DistMeasureMahal <  handle
+    
+    properties (SetAccess = private)
+        
+        mahalW;
+        
+        featX;
+        
+        ids;
+        ret_ids;
+        
+        % special delta parameters
+        deltafun;
+        deltafun_params;
+    end
+
+    methods
+        
+    % ---
+    % constructor
+    % ---
+    function m = DistMeasureMahal(clips, mahalW, featX, deltafun, deltafun_params)
+
+        if nargin < 4 && (size(featX, 2) ~= numel(clips) || size(featX, 1) ~= length(mahalW))
+            error 'wrong input format'
+        end
+
+        % fill index and generate matrix;
+        m.ids = [clips.id];
+
+        % reverse index
+        m.ret_ids = sparse(numel(m.ids),1);
+        m.ret_ids(m.ids) = 1:numel(m.ids);
+
+        % ---
+        % save mahal Matrix and lazy-copy features
+        % ---
+        if size(mahalW, 1) ~= size(mahalW, 2)
+            
+            m.mahalW = diag(mahalW);
+        else
+            
+            m.mahalW = mahalW;
+        end
+        
+        m.featX = featX;
+        
+        % ---
+        % special deltas
+        % ---
+        if nargin > 3
+            m.deltafun = deltafun;
+            m.deltafun_params = deltafun_params;
+        else 
+            m.deltafun = [];
+        end
+    end
+    
+
+    % ---
+    % this compability function returns the
+    % mahalanobis similarity of two clip indices
+    % --- 
+    function out = mat(m, idxa, idxb)
+    
+        if nargin == 1
+            idxa = 1:numel(m.ids);
+            idxb = 1:numel(m.ids);
+        end
+        
+        % ---
+        % account for different delta functions
+        % ---
+        if ~isempty(m.deltafun)
+            out = zeros(numel(idxa),numel(idxb));
+            for i=1:numel(idxa)
+                for j=1:numel(idxb)
+                    
+                    % calculate new distance
+                    tmp = m.deltafun(m.featX(:,idxa), m.featX(:,idxb),m.deltafun_params{:});
+                    out(i,j) = tmp' * m.mahalW * tmp;
+                end
+            end
+        else
+        % Standard Mahaldist is much faster to calculate
+            out = sqdist( m.featX(:,idxa), m.featX(:,idxb), m.mahalW);
+        end
+    end
+  
+    % ---
+    % returns the distance for the two input clips
+    % ---
+    function out = distance(m, clipa, clipb)
+        posa = m.get_clip_pos(clipa);
+        posb = m.get_clip_pos(clipb);
+        
+        out = m.mat(posa, posb);
+    end
+    
+    % ---
+    % returns a list of n (default = 10) clips most 
+    % similar to the  input
+    % ---
+    function [clips, dist] = get_nearest(m, clip, n)
+    % list = get_nearest(m, clip, n)
+    % 
+    % returns a list of n (default = 10) clips most 
+    % similar to the  input
+
+        % default number of results
+        if nargin == 2 
+
+            n = 10;
+        end
+        
+        % return all clips in case n = 0
+        if n == 0; n = numel(m.ids); end
+
+        % get clip positions
+        pos = m.get_clip_pos(clip);
+
+        % sort according to distance
+        [sc, idx] = sort( m.mat(pos, 1:numel(m.ids)), 'ascend');
+
+        % we only output relevant data
+        idx = idx(sc < inf);
+
+        if numel(idx) > 0
+            % create clips form best ids
+            clips = MTTClip( m.ids( idx(1:min(n, end))));
+            dist = m.mat(pos, idx(1:min(n, end)));
+
+        else
+            clips = [];
+            dist = [];
+        end
+    end
+    
+    
+
+    function [clips, dist] = present_nearest(m, clip, n)
+    % plays and shows the n best hits for a given clip    
+
+        % default number of results
+        if nargin == 2 
+
+            n = 3;
+        end
+
+        % get best list
+        [clips, dist] = get_nearest(m, clip, n);
+
+        clip.audio_features_basicsm.visualise();
+        for i = 1:numel(clips)
+            fprintf('\n\n\n- Rank %d, distance: %1.4f \n\n',i, dist(i));
+
+            clips(i).audio_features_basicsm.visualise();
+            h = gcf();
+            t = clips(i).play(20);
+            pause(t);
+            close(h);
+        end
+    end
+
+    function a = visualise(m)
+
+        figure;
+
+        % plot data
+
+        imagesc(m.mat);
+
+        a = gca;
+        set(a,'YTick',[1:numel(m.ids)], 'YTickLabel',m.ids);
+        set(a,'XTick',[1:numel(m.ids)], 'XTickLabel', m.ids);
+
+        axis xy;
+        colormap(hot);
+    end
+
+    % end methods
+    end
+    
+    % ---
+    % private methods
+    % ---
+    methods(Access = private)
+        
+    function out = get_clip_pos(m, clip)
+        % returns position in mat for given clip
+
+        out = m.ret_ids(clip.id);
+    end
+        
+    end
+    
+end