mfbox_temporalica_run.m

toolbox for spm 5 for data, model free analysis

function [params,A,W,S]=mfbox_temporalica_run(X,mask,params,runflag)
% run temporal ica based on pearson ica
%
% Usage:
%  [params,A,W,S]=mfbox_temporalica_run(X,mask,params,runflag)
%
%  X       - (NxT) data
%  mask    - data mask (XxYxZ) with sum(mask(:))==N
%  params  - struct with
%            numComponents        - number of components
%            maxNumIterations     - max number of iterations
%            epsilon              - epsilon
%            maxNumPastIterations - max number of past iterations
%            beta                 - beta in pearson
%            borderBase           - borderBase in pearsonica
%            borderSlope          - borderSlope in pearsonica
%            usepast              - use past for dimesion reduction
%  runflag - -1 get default parameter
%             0 interactive ask parameters
%             1 interactive ask parameters and run
%             2 run
%
% Copyright by Peter Gruber and Fabian J. Theis
% Signal Processing & Information Theory group
% Institute of Biophysics, University of Regensburg, Germany
% Homepage: http://research.fabian.theis.name
%           http://www-aglang.uni-regensburg.de
%
% This file is free software, subject to the 
% GNU GENERAL PUBLIC LICENSE, see gpl.txt

error(nargchk(1,4,nargin));
error(nargchk(1,4,nargout));

A = [];
W = [];
S = [];

s = size(X);
dim = s(1:(end-1));
if (length(dim)==1), dim = [dim,1]; end
n = s(end);

if (nargin<2), mask = logical(ones(dim)); end
if (nargin<3), params = []; end
if (nargin<4), runflag = 1; end

params = mfbox_checkparam(params,'mf','temporalica', ...
    struct('numComponents',10,'numComponents_min',1, ...
    'numComponents_max',20,'numComponents_type','int', ...
    'maxNumIterations',300,'maxNumIterations_min',100, ...
    'maxNumIterations_max',1000,'maxNumIterations_type', ...
    'int','epsilon',0.0001,'epsilon_min',0.00001, ...
    'epsilon_max',0.1,'epsilon_type','float', ...
    'maxNumPastIterations',1000,'maxNumPastIterations_min', ...
    100,'maxNumPastIterations_max',5000,'maxNumPastIterations_type', ...
    'float','beta','0.5','beta_min',0.1,'beta_max',0.9, ...
    'beta_type','float','borderBase',1,'borderSlope',1, ...
    'usepast','off','usepast_type','boolean'));

if (abs(runflag-0.5)<1)
    if (exist('OCTAVE_HOME')~=5)% matlab
        params = mfbox_temporalicag(X,mask,params,runflag);
    elseif (exist('OCTAVE_HOME')==5) %octave
        [params,runflag] = mfbox_getparam(params,runflag);
    end
end

if (runflag>0 && isstruct(params))
    borderBase = [2.6 4];
    borderSlope = [0 1];
    n = params.numComponents;
    plotting = 'on'; if (runflag>2), plotting = 'off'; end
    if (strcmp(plotting,'on')), f = figure; end
    if (strcmp(params.usepast,'on'))
        WP = mfbox_past(X,n,params.beta,params.maxNumPastIterations,strcmp(plotting,'on'));
    else
        [x,y] = eig(double(cov(X)));
        [y,p] = sort(diag(y),'descend');
        WP = x(:,p(1:n))'*X';
    end
    [A,tS] = mfbox_fasticapearson((WP*X)', ...
        params.epsilon,params.maxNumIterations, ...
        borderBase,borderSlope,n,1,n,plotting);
    if (strcmp(plotting,'on')), close(f); end
    if (nargout>2), W = pinv(A); end
    if (nargout>3), S = WP'*tS; end
end