comparison toolboxes/MIRtoolbox1.3.2/MIRToolbox/mirentropy.m @ 0:e9a9cd732c1e tip

first hg version after svn

+function varargout = mirentropy(x,varargin)
+%   h = mirentropy(a) calculates the relative entropy of a.
+%   (Cf. User's Manual.)
+%   mirentropy(..., ?Center?) centers the input data before
+%       transforming it into a probability distribution.
+
+        center.key = 'Center';
+        center.type = 'Boolean';
+        center.default = 0;
+    option.center = center;
+    
+specif.option = option;
+
+varargout = mirfunction(@mirentropy,x,varargin,nargout,specif,@init,@main);
+
+
+function [x type] = init(x,option)
+if isamir(x,'miraudio')
+    x = mirspectrum(x);
+end
+type = 'mirscalar';
+
+
+function h = main(x,option,postoption)
+if iscell(x)
+    x = x{1};
+end
+m = get(x,'Data');
+v = cell(1,length(m));
+for h = 1:length(m)
+    v{h} = cell(1,length(m{h}));
+    for k = 1:length(m{h})
+        mk = m{h}{k};
+        mn = mk;
+        if isa(x,'mirhisto') || isa(x,'mirscalar')
+            mn = mn';
+        end
+        
+        if option.center
+            mn = center(mn);
+        end
+        
+        % Negative data is trimmed:
+        mn(mn<0) = 0;
+        
+        % Data is normalized such that the sum is equal to 1.
+        mn = mn./repmat(sum(mn)+repmat(1e-12,...
+                            [1 size(mn,2) size(mn,3) size(mn,4)]),...
+                       [size(mn,1) 1 1 1]);
+                   
+        % Actual computation of entropy
+        v{h}{k} = -sum(mn.*log(mn + 1e-12))./log(size(mn,1));
+        
+        if isa(x,'mirhisto') || isa(x,'mirscalar')
+            v{h}{k} = v{h}{k}';
+        end
+    end
+end
+t = ['Entropy of ',get(x,'Title')];
+h = mirscalar(x,'Data',v,'Title',t);