TE.rar_TE 数据_matlab_transfer function_数据差异分析

function TEgroup_conditionstatssingle(cfg, data1, data2) % TECONDITIONSTATS: Performs a permutation test on results of transfer % entropy analysis for a single subject under two conditions (data1 and % data2). TEgroup_prepare has to be run on all data sets and TE values have % to be estimated using InteractionDelayReconstruction_calculate (or % TEsurrogatestats/_ensemble.m). % % % !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! % !!! The function TEgroup_prepare has to be run on all datasets first! !!! % !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! % % You can call this function directly as follows: % TEgroup_conditionstatssingle(cfg, data1, data2) % % % * REFERENCE INFORMATION % % - transfer entropy % - The concept of TE appears in Schreiber's article, % "Measuring Information Transfer", Phys. Rev. Lett. 85, 461 - 464 % (2000). % - For the estimation of probability densities needed for the TE % computation, the function implements the Kraskov-Stoegbauer- % Grassberger estimator described in Kraskov et al. "Estimating % mutual information", Phys. Rev. E 69 (6) 066138, (2004). % % - permutation test % - Maris & Oostenveld (2007). Nonparametric statistical testing of % EEG- and MEG-data. J. of Neuroscience Methods, 164, 177-190. % % % * DEPENDENCIES % - The following Matlab toolboxes: % - statistic toolbox % - The functions % - TEperm % - TEconsoleoutput % % % * INPUT PARAMETERS % % data1, data2 = results structures for two single subjects returned by % InteractionDelayReconstruction_calculate, % TEsurrogatestats*; structures have to contain: % .TEmat = no. channels x trials, matrix of TE values for all % channel conbinations and trials % .groupprepare = field with results from running TEgroup_prepare on % all data sets % .sgncmb = labels of channel combinations % % AND % % cfg: % % The configuration MUST contain: % cfg.fileidout = string for the output path and the first part of the % output filename. The function will write a result % file with the suffix 'TEpermtestcondsingle_output.mat' % to disk (containing the output of the statistical % test). % % Optional arguments: % % cfg.alpha = significance level for statistical shift test, % permutation test and correction for multiple % comparison (default = 0.05) % cfg.numpermutation = nr of permutations in permutation test % (default = 190100) % cfg.permstatstype = 'mean' to use the distribution of the mean % differences and 'depsamplesT' or % 'indepsamplesT' for distribution of the % t-values. (default = 'mean') % cfg.tail = 1 tail or 2 tailed test of significance (for the % permutation tests) (default = 2) % cfg.correctm = correction method used for correction of the multiple % comparison problem - False discovery rate 'FDR' or % Bonferroni correction 'BONF' (default = 'FDR') % % % OUTPUT PARAMETERS % % TEpermtestcondsingle % .TEpermvalues = matrix with size: % (channelpair x value) % The last dimension "value" includes: % 1 - p_values of the statistic within the % distribution given by the permutations % 2 - 1 (0), if the statistics is significant at % the prescribed alpha level (or not) % 3 - 1 (0), if the statistics is significant % after correction for mulitple comparisons % (or not) % 4 - 1 (0), mean difference or tvalue of mean % difference depending on cfg.permstatstype % 5 - 1 (0), if instantaneous mixing (volume % conduction) exists (or not) % 6 - reconstructed interaction delay of the % condition with stronger TE for that channel % combination % % .nr2cmc = number used for correction for multiple % comparisons (returned by TEcmc) % .correctm = method used for correction for multiple % comparisons (returned by TEcmc) % .dimord = dimensions of TEpermvalues % .cfg = configuration file used to conduct the % permutation test % .sgncmb = labels of channel combinations (source -> % target) % .numpermutation = number of permutations % .nrtrials = [1 x 2] vector with no. trials in data1 and % data2 respectively % .TEgroupprepare = results of the function TEprepare from the % data % % % % This program 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; % % This program is distributed in the hope that it will be useful, % but WITHOUT ANY WARRANTY; % % Version 3.0 by Patricia Wollstadt, Michael Lindner, Raul Vicente, % Michael Wibral % Frankfurt 2015 % %% define logging levels % verbosity is taken from TEprepare % LOG_INFO_MAJOR = 1; LOG_INFO_MINOR = 2; %% check data % ------------------------------------------------------------------------- % check data for TEprepare/TEproupprepare structure if ~isfield(data1, 'groupprepare') || ~isfield(data2, 'groupprepare') error('TRENTOOL ERROR: Field .groupprepare is missing in one of the datasets!'); end % check code if data1.groupprepare.code ~= data2.groupprepare.code error('TRENTOOL ERROR: Only datasets, which were prepared together with TEgroup_prepare can be analysed together! Code is not identical') end % get the max no. trials in any of the data sets that enter the test cfg.maxtrials = max([max(data1.TEprepare.nrtrials(:,2)) max(data2.TEprepare.nrtrials(:,2))]); %% compare new cfg and cfg from TEprepare if equal entries exist % ------------------------------------------------------------------------- doublefields = 0; cfgTEprepare = data1.TEprepare.cfg; cfgfields = fieldnames(cfgTEprepare); cfgfields2 = fieldnames(cfg); for ii = 1:size(cfgfields,1) for jj = 1:size(cfgfields2,1) if strcmp(cfgfields{ii},cfgfields2{jj}) doublefields = doublefields + 1; end end end if doublefields > 0 fprintf('\n') error(['TRENTOOL ERROR: Illegal attempt to overwrite entry generated ' ... 'by or used for TEprepare! Change cfg or rerun TEprepare. (see help)']) end % add structures and values of data.TEprepare.cfg to cfg nr1 = size(cfgfields,1); for ii = 1:nr1 eval(strcat('cfg.',cfgfields{ii},' = getfield(cfgTEprepare, {1}, cfgfields{ii});')); end %% check cfg % ------------------------------------------------------------------------- if ~isfield(cfg, 'alpha'), cfg.alpha = 0.05; end if ~isfield(cfg, 'correctm'), cfg.correctm = 'FDR'; end if ~isfield(cfg, 'tail'), cfg.tail = 2; end cfg.verbosity = data1.TEprepare.cfg.verbosity; if ~isfield(cfg, 'permstatstype'), cfg.permstatstype = 'mean'; end if ~strcmp(cfg.permstatstype , 'mea