Commits

Zoltan Szabo committed 0da37f9

'IGV_estimation.m': added (#2); documentation: modified accordingly.

Comments (0)

Files changed (5)

+-IGV_estimation: added (#2); documentation: modified accordingly.
+
 v0.20 (Nov 19, 2012):
 -Two Shannon entropy estimators based on the distance (KL divergence) from the uniform/Gaussian distributions: added; see 'HShannon_DShannon_U_initialization.m', 'HShannon_DShannon_U_estimation.m', 'HShannon_DShannon_N_initialization.m', 'HShannon_DShannon_N_estimation.m'.
 -Shannon entropy estimator based on Voronoi regions: added; see 'HShannon_Voronoi_initialization.m', 'HShannon_Voronoi_estimation.m'.

code/H_I_D/base_estimators/IGV_estimation.m

+function [I] = IGV_estimation(Y,ds,co)
+%Estimates the generalized variance (I). 
+%
+%INPUT:
+%   Y: Y(:,t) is the t^th sample.
+%  ds: subspace dimensions. 
+%  co: initialized mutual information estimator object.
+%REFERENCE:
+%   Zoltan Szabo and Andras Lorincz. Real and Complex Independent Subspace Analysis by Generalized Variance. ICA Research Network International Workshop (ICARN), pages 85-88, 2006.
+%
+%Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "szzoli (at) cs (dot) elte (dot) hu")
+%
+%This file is part of the ITE (Information Theoretical Estimators) Matlab/Octave toolbox.
+%
+%ITE is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by
+%the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+%
+%This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
+%MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+%
+%You should have received a copy of the GNU General Public License along with ITE. If not, see <http://www.gnu.org/licenses/>.
+
+%co.mult:OK.
+
+if one_dimensional_problem(ds) && length(ds)==2
+    %initialization:
+        fs = IGV_dependency_functions;
+        num_of_functions = length(fs);
+        num_of_samples = size(Y,2);
+        I = 0;
+    %query for the current working environment:
+        environment_Matlab = working_environment_Matlab;
+        
+    %I computation:
+        for k = 1 : num_of_functions %pick the k^th function (fs{k})
+            fY = feval(fs{k},Y).';
+            if strcmp(co.dependency,'cov')
+                c = (fY(:,1)-mean(fY(:,1))).' * (fY(:,2)-mean(fY(:,2))) / (num_of_samples-1);
+                I = I + c.^2; %cov instead of corr
+            else %corr/cor
+                if environment_Matlab%Matlab
+                    I = I + (corr(fY(:,1),fY(:,2))).^2; %corr instead of cov        
+                else%Octave
+                    I = I + (cor(fY(:,1),fY(:,2))).^2; %cor (and not 'corr') instead of cov        
+                end
+            end
+        end    
+else
+    error('There must be 2 pieces of one-dimensional subspaces (coordinates) for this estimator.');
+end

code/H_I_D/base_estimators/IGV_initialization.m

 %Note: 
 %   1)The estimator is treated as a cost object (co).
 %	2)We make use of the naming convention 'I<name>_initialization', to ease embedding new mutual information estimation methods.
-%	3)For GV, the corresponding 'IGV_estimation.m' procedure has not been implemented, since GV is used in case of cost_type = 'Ipairwise1d', where the similarity matrix can be computed more
-%	efficiently for GV (see 'I_similarity_matrix.m').
 %
 %INPUT:
 %   mult: is a multiplicative constant relevant (needed) in the estimation; '=1' means yes, '=0' no.

code/H_I_D/utilities/IGV_dependency_functions.m

+function [fs] = IGV_dependency_functions()
+%Creates functions for measuring f-covariance / f-correlation for the generalized variance (GV) measure.
+%
+%OUTPUT:
+%   fs: cell array; Assumption: elements of fs can be applied by feval to a matrix (e.g.: functions operating coordinatewise).
+%
+%Copyright (C) 2012 Zoltan Szabo ("http://nipg.inf.elte.hu/szzoli", "szzoli (at) cs (dot) elte (dot) hu")
+%
+%This file is part of the ITE (Information Theoretical Estimators) Matlab/Octave toolbox.
+%
+%ITE is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by
+%the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
+%
+%This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of
+%MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU General Public License for more details.
+%
+%You should have received a copy of the GNU General Public License along with ITE. If not, see <http://www.gnu.org/licenses/>.
+
+f1 = 'cos';
+f2 = @(t)cos(2*t); %Matlab-7
+%f2 = inline('cos(2*t)','t'); %Matlab-6
+    
+fs = {f1,f2};

code/H_I_D/utilities/IGV_similarity_matrix.m

 %You should have received a copy of the GNU General Public License along with ITE. If not, see <http://www.gnu.org/licenses/>.
 
 %initialization:
-    fs = GV_dependency_functions;
+    fs = IGV_dependency_functions;
     num_of_functions = length(fs);
     C =  zeros(size(Y,1));
     %query for the current working environment:
         end
     end
 end
-
-%-------------------------------
-function [fs] = GV_dependency_functions()
-%Creates functions for measuring f-covariance / f-correlation.
-%
-%OUTPUT:
-%   fs: cell array; Assumption: elements of fs can be applied by feval to a matrix (e.g.: functions operating coordinatewise).
-
-f1 = 'cos';
-f2 = @(t)cos(2*t); %Matlab-7
-%f2 = inline('cos(2*t)','t'); %Matlab-6
-    
-fs = {f1,f2};
Tip: Filter by directory path e.g. /media app.js to search for public/media/app.js.
Tip: Use camelCasing e.g. ProjME to search for ProjectModifiedEvent.java.
Tip: Filter by extension type e.g. /repo .js to search for all .js files in the /repo directory.
Tip: Separate your search with spaces e.g. /ssh pom.xml to search for src/ssh/pom.xml.
Tip: Use ↑ and ↓ arrow keys to navigate and return to view the file.
Tip: You can also navigate files with Ctrl+j (next) and Ctrl+k (previous) and view the file with Ctrl+o.
Tip: You can also navigate files with Alt+j (next) and Alt+k (previous) and view the file with Alt+o.