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