/
limo_eeg.m
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limo_eeg.m
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function limo_eeg(varargin)
% LIMO_EEGLIMO - start up and master function of the LIMO_EEGLIMO toolbox
% Calling this function brings up different GUIs.
% Each time an option is used it calls subroutines.
% In this function is also implemented the call to the GLM, creating files
% etc .. see input
%
% LIMO_EEGLIMO is designed to perform a hierarchical LInear MOdeling of EEGLIMO data
% All analyses can be performed with this toolbox but the visualization
% relies heavily on EEGLIMOlab functions http://sccn.ucsd.edu/eeglab/
% In addition, the data format is the one used by EEGLIMOlab.
%
% INPUT limo_eeg(value,option)
% 1 - load the GUI
% 2,X - call limo_import (time X=1 or freuqency X=2), creating LIMO.mat file and call limo_egg(3)
% 3 - call limo_design_matrix and populate LIMO.design
% 4,fullfile - call limo_glm (mass univariate) or limo_glm2 (multivariate)
% 5 - shortcut to limo_results, look at possible results and print a report
% 6,C - shortcut to limo_contrast for the current directory,
% ask for a list of contrasts if not given as 2nd argument) and run them all
% e.g. C = [1 1 -1 -1; 1 -1 1 -1]; limo_eeg(6,C) would do those
% two contrasts for the data located in the current dir
%
% Cyril Pernet & Andrew Stewart v6 21/01/2014
% Cyril Pernet & Ramon Martinez-Cancino 23-10-2014 updates for components (ICA)
%
% ------------------------------
% Copyright (C) LIMO Team 2020
% make sure paths are ok
root = fileparts(which('limo_eeg'));
pathCell = regexp(path, pathsep, 'split');
onPath = all([sum(strcmp([root filesep 'help'],pathCell))~=0,...
sum(strcmp([root filesep 'limo_cluster_functions'],pathCell))~=0,...
sum(strcmp([root filesep 'external' filesep 'psom'],pathCell))~=0,...
sum(strcmp([root filesep 'deprecated'], pathCell))~=0]);
if onPath == 0
addpath([root filesep 'limo_cluster_functions'])
addpath([root filesep 'external'])
addpath([root filesep 'external' filesep 'psom'])
addpath([root filesep 'help'])
addpath([root filesep 'deprecated'])
end
% in case data are already there
if isempty(varargin)
varargin={1};
end
% start
switch varargin{1}
%------
case {1}
% ------------------------------------------------------------------------
% GUI
% ------------------------------------------------------------------------
% if not called via the eeglab menu but via the matlab command window
% show the GUI
disp(' ')
disp('LIMO_EEG was primarily designed by Cyril Pernet and Guillaume Rousselet.');
disp('Current maintenance is performed by Cyril Pernet, with support from Arnaud Delorme for EEGLAB integration');
disp('The list of contributors is in the contributors.md file');
disp('https://github.com/LIMO-EEG-Toolbox/limo_tools/blob/master/contributors.md');
disp('All these authors are thereafter referred to as the LIMO Team');
disp(' ')
disp('LIMO_EEG Copyright (C) 2021 LIMO TEAM');
disp('This program comes with ABSOLUTELY NO WARRANTY.');
disp('This is free software, and you are welcome to redistribute');
disp('it under certain conditions - type help limo_eeg for details');
disp(' ');
disp('Please use our boilerplate Citation and Reporting:')
disp('https://github.com/LIMO-EEG-Toolbox/limo_tools/wiki/Reporting-methods-and-results')
disp('References are in the citations.nbid file')
disp(' ')
limo_gui
%------
case {2}
% ------------------------------------------------------------------------
% IMPORT
% ------------------------------------------------------------------------
% the EEGLIMO data are not imported but path / name is saved in LIMO.mat
% Cat and Cont are imported manually from a txt or mat file
% Other informations are i) the starting time point (sec), ii) the method to
% use (if multivariate stats have to be computed) and iii) the working
% directory where all informations will be saved
clc;
if varargin{2} == 1
out = limo_import_t; % Data from electrodes over time in each trial
elseif varargin{2} == 2
out = limo_import_f; % Data from electrodes spectral power in each trial
elseif varargin{2} == 3
out = limo_import_tf; % Data from electrodes spectral power over time in each trial
end
% if bootstrap with tfce - get the neighbourghing matrix now so
% the estimation and results can be all computed without any other
% input from user (see limo_eeg(5))
% if bootstrap do TFCE
if ~strcmp(out,'LIMO import aborded')
try
load LIMO
if LIMO.design.bootstrap == 1
if ~isfield(LIMO.data,'neighbouring_matrix')
answer = questdlg('load or compute neighbouring matrix?','channel neighbouring definition','Load','Compute','Compute');
if strcmp(answer,'Load')
[file,newpath,whatsup] = uigetfile('*.mat','select neighbourghing matrix (or expected chanloc file)');
if whatsup == 0
disp('selection aborded');
return
else
channeighbstructmat = load(sprintf('%s%s',chan_path,chan_file));
fn = fieldnames(channeighbstructmat);
index = find(ismember(fn,'channeighbstructmat'));
channeighbstructmat = getfield(channeighbstructmat,fn{index});
cd(LIMO.dir);
end
else
channeighbstructmat = limo_expected_chanlocs(LIMO.data.data, LIMO.data.data_dir);
end
LIMO.data.neighbouring_matrix = channeighbstructmat;
save LIMO LIMO
end
end
disp('import done');
catch
disp('errors related to bootstrap ?? ');
return
end
% now estimate the design matrix
limo_eeg(3)
else
disp('import aborded')
end
%------
case {3}
% ------------------------------------------------------------------------
% DESIGN MATRIX
% ------------------------------------------------------------------------
% returns the design matrix and some info about the matrix
% some files are also created to be filled during the model computation
% get the LIMO.mat
try
load LIMO
catch
[file,dir_newpath] = uigetfile('LIMO.mat','select a LIMO.mat file');
if file ==0
return
else
cd (dir_newpath); load LIMO.mat;
end
end
cd (LIMO.dir);
% Check data where specified and load
if exist('EEGLIMO','var')
if strcmp([LIMO.data.data_dir filesep LIMO.data.data],[EEGLIMO.filepath filesep EEGLIMO.filename])
disp('Using Global variable EEGLIMO')
else
cd (LIMO.data.data_dir);
disp('reloading data ..');
EEGLIMO=pop_loadset(LIMO.data.data);
end
else
cd (LIMO.data.data_dir);
disp('reloading data ..');
EEGLIMO=pop_loadset(LIMO.data.data);
end
% Load either elec voltage over time, elec power over frequency, or
% electrode time-frequency - depending on declared analysis
if strcmp(LIMO.Analysis,'Time')
if strcmp(LIMO.Type,'Components')
if isfield(EEGLIMO.etc.datafiles,'icaerp')
if ~iscell(EEGLIMO.etc.datafiles.icaerp) && strcmp(EEGLIMO.etc.datafiles.icaerp(end-3:end),'.mat')
Y = load(EEGLIMO.etc.datafiles.icaerp);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
else
try
signal = load('-mat',EEGLIMO.etc.datafiles.icaerp);
if isstruct(signal); signal = limo_struct2mat(signal); end
catch
for d=1:length(EEGLIMO.etc.datafiles.icaerp)
signal{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.icaerp(d)));
if isstruct(signal{d}); signal{d} = limo_struct2mat(signal{d}); end
end
end
signal = limo_concatcells(signal);
end
else
signal = eeg_getdatact(EEGLIMO,'component',[1:size(EEGLIMO.icawinv,2)]);
end
Y = signal(:,LIMO.data.trim1:LIMO.data.trim2,:); clear signal
else % channels
if isfield(EEGLIMO.etc,'datafiles.daterp')
if ~iscell(EEGLIMO.etc.datafiles.daterp) && strcmp(EEGLIMO.etc.datafiles.daterp(end-3:end),'.mat')
Y = load(EEGLIMO.etc.datafiles.daterp);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
else
for d=1:length(EEGLIMO.etc.datafiles.daterp)
Y{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.daterp(d)));
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y);
end
else
disp('the field EEG.etc.datspec pointing to the data is missing - using a hack')
try
cd(LIMO.data.data_dir); spec = dir('*.datspec');
for d=1:length(spec)
Y{d} = load('-mat',spec(d).name);
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y);
catch
Y = EEGLIMO.data;
end
end
Y = Y(:,LIMO.data.trim1:LIMO.data.trim2,:);
end
clear EEGLIMO
elseif strcmp(LIMO.Analysis,'Frequency')
if strcmp(LIMO.Type,'Components')
if isfield(EEGLIMO.etc.datafiles,'icaspec')
if ~iscell(EEGLIMO.etc.datafiles.icaspec) && strcmp(EEGLIMO.etc.datafiles.icaspec(end-3:end),'.mat')
Y = load(EEGLIMO.etc.datafiles.icaspec);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
else
try
signal = load('-mat',EEGLIMO.etc.datafiles.icaspec);
if isstruct(signal); signal = limo_struct2mat(signal); end
catch
for d=1:length(EEGLIMO.etc.datafiles.icaspec)
signal{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.icaspec(d)));
if isstruct(signal{d}); signal{d} = limo_struct2mat(signal{d}); end
end
end
signal = limo_concatcells(signal);
end
else
signal = eeg_getdatact(EEGLIMO,'component',[1:length(EEGLIMO.icawinv)]);
end
Y = signal(:,LIMO.data.trim1:LIMO.data.trim2,:); clear signal
else % channels
if isfield(EEGLIMO.etc.datafiles,'datspec')
if ~iscell(EEGLIMO.etc.datafiles.datspec) && strcmp(EEGLIMO.etc.datafiles.datspec(end-3:end),'.mat')
Y = load(EEGLIMO.etc.datafiles.datspec);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
else
for d=1:length(EEGLIMO.etc.datafiles.datspec)
Y{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.datspec(d)));
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y); clear EEGLIMO
end
else
disp('the field EEG.etc.datspec pointing to the data is missing - using a hack')
try
cd(LIMO.data.data_dir); spec = dir('*.datspec');
for d=1:length(spec)
Y{d} = load('-mat',spec(d).name);
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y);
catch
Y = EEGLIMO.data;
end
end
Y = Y(:,LIMO.data.trim1:LIMO.data.trim2,:);
end
clear EEGLIMO
elseif strcmp(LIMO.Analysis,'Time-Frequency')
disp('Time-Frequency implementation - loading tf data...');
if strcmp(LIMO.Type,'Components')
if isfield(EEGLIMO.etc.datafiles,'icatimef')
try
signal = load('-mat',EEGLIMO.etc.datafiles.icatimef);
if isstruct(signal); signal = limo_struct2mat(signal); end
catch
for d=1:length(EEGLIMO.etc.datafiles.icaspec)
signal{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.icatimef(d)));
if isstruct(signal{d}); signal{d} = limo_struct2mat(signal{d}); end
end
end
signal = limo_concatcells(signal);
else
signal = eeg_getdatact(EEGLIMO,'component',[1:length(EEGLIMO.icawinv)]);
end
Y = signal(:,LIMO.data.trim_low_f:LIMO.data.trim_high_f,LIMO.data.trim1:LIMO.data.trim2,:); clear signal
else % channels
if isfield(EEGLIMO.etc.datafiles,'dattimef')
if exist(EEGLIMO.etc.datafiles.dattimef,'file')
for d=1:length(EEGLIMO.etc.datafiles.dattimef)
Y{d} = load('-mat',cell2mat(EEGLIMO.etc.datafiles.dattimef(d)));
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y);
clear EEGLIMO
else
error('The file %s \n in EEG.etc.datafile is not found', EEGLIMO.etc.datafiles.dattimef)
end
elseif EEGLIMO.etc.datafiles.datersp % .mat file
if exist(EEGLIMO.etc.datafiles.datersp,'file')
Y = load(EEGLIMO.etc.datafiles.datersp);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
else
[~,name,ext]=fileparts(EEGLIMO.etc.datafiles.datersp);
try
Y = load([LIMO.dir filesep name ext]);
if isstruct(Y)
Y = getfield(Y,cell2mat(fieldnames(Y)));
end
catch
Y = load('-mat',[LIMO.dir filesep name '.datersp']);
end
end
else
disp('no data found, the field EEG.etc.dattimef or EEGLIMO.etc.datersp pointing to the data is missing - using a hack')
try
cd(LIMO.data.data_dir); ersp = dir('*.dattimef');
for d=1:length(ersp)
Y{d} = load('-mat',ersp(d).name);
if isstruct(Y{d}); Y{d} = limo_struct2mat(Y{d}); end
end
Y = limo_concatcells(Y);
catch
Y = EEGLIMO.data;
end
end
Y = Y(:,LIMO.data.trim_low_f:LIMO.data.trim_high_f,LIMO.data.trim1:LIMO.data.trim2,:);
end
LIMO.data.size4D= size(Y);
LIMO.data.size3D= [LIMO.data.size4D(1) LIMO.data.size4D(2)*LIMO.data.size4D(3) LIMO.data.size4D(4)];
end
clear ALLCOM ALLEEGLIMO CURRENTSET CURRENTSTUDY LASTCOM STUDY
cd (LIMO.dir) ; save LIMO LIMO
% make the design matrix
disp('computing design matrix');
if strcmp(LIMO.Analysis,'Time-Frequency') % use limo_design_matrix_tf
[LIMO.design.X, LIMO.design.nb_conditions, LIMO.design.nb_interactions,...
LIMO.design.nb_continuous] = limo_design_matrix_tf(Y, LIMO,1);
else % for time or power use limo_design_matrix
[LIMO.design.X, LIMO.design.nb_conditions, LIMO.design.nb_interactions,...
LIMO.design.nb_continuous] = limo_design_matrix(Y, LIMO,1);
end
% update LIMO.mat
if prod(LIMO.design.nb_conditions) > 0 && LIMO.design.nb_continuous == 0
if length(LIMO.design.nb_conditions) == 1
if LIMO.design.nb_conditions == 2
LIMO.design.name = sprintf('GLM Categorical: T-test i.e. %g conditions',LIMO.design.nb_conditions);
else
LIMO.design.name = sprintf('GLM Categorical: 1 way ANOVA with %g conditions',LIMO.design.nb_conditions);
end
else
LIMO.design.name = sprintf('GLM Categorical: N way ANOVA with %g factors',length(LIMO.design.nb_conditions));
end
elseif prod(LIMO.design.nb_conditions) == 0 && LIMO.design.nb_continuous > 0
if LIMO.design.nb_continuous == 1
LIMO.design.name = sprintf('GLM Continuous: Simple Regression');
else
LIMO.design.name = sprintf('GLM Continuous: Multiple Regression with %g continuous variables',LIMO.design.nb_continuous);
end
elseif prod(LIMO.design.nb_conditions) > 0 && LIMO.design.nb_continuous > 0
if length(LIMO.design.nb_conditions) == 1
LIMO.design.name = sprintf('GLM AnCOVA with %g conditions and %g continuous variable(s)',LIMO.design.nb_conditions,LIMO.design.nb_continuous);
else
LIMO.design.name = sprintf('GLM AnCOVA with %g factors and %g continuous variable(s)',length(LIMO.design.nb_conditions),LIMO.design.nb_continuous);
end
else
LIMO.design.name = 'Mean';
end
% if you run several subjects in a row with
% the GUI and use contrasts - a new subject can have a contrast field
if isfield(LIMO,'contrast')
LIMO = removefields(LIMO, 'contrast');
end
disp('design matrix done ...')
% ---------------
LIMO.design.status = 'to do';
save LIMO LIMO; clear Y
a = questdlg('run the analysis?','Start GLM analysis','Yes','No','Yes');
if strcmp(a,'Yes')
limo_eeg(4); clear LIMO; limo_gui
else
return
end
%% ------------------------------------------------------------------------
% ANALYZE
% ------------------------------------------------------------------------
% estimates the model specified in (2)
% save all info onto disk
case{4}
% NBOOT (updated if specified in LIMO.design)
% ------------------------------------------
% get the LIMO.mat
if nargin == 2
if ischar(varargin{2})
if isfolder(varargin{2})
varargin{2} = [varargin{2} filesep 'LIMO.mat'];
end
LIMO = load(varargin{2});
if ~isfield(LIMO,'LIMO')
error('input file not recognized as a LIMO.mat structure')
end
else
LIMO = varargin{2};
end
elseif exist(fullfile(pwd,'LIMO.mat'),'file')
% maybe just here in the current directory
LIMO = load('LIMO.mat');
else % ask user
[file,dir_newpath,ind] = uigetfile('LIMO.mat','select a LIMO.mat file');
if ind ==0
return
else
if strcmpi(file,'LIMO')
LIMO = load(fullfile(dir_newpath,'LIMO.mat'));
else
error('not a LIMO.mat file')
end
end
end
if isfield(LIMO,'LIMO')
LIMO = LIMO.LIMO;
end
% ---------------- univariate analysis ------------------
% --------------------------------------------------------
if strcmp(LIMO.design.type_of_analysis,'Mass-univariate')
limo_glm_handling(LIMO)
% ----------------------------------------------------------
%% ---------------- multivariate analysis ------------------
% --------------------------------------------------------
elseif strcmp(LIMO.design.type_of_analysis,'Multivariate')
% to do limo_glm_handling(LIMO)
update = 1;
% --------- load files created by limo_design_matrix ------------------
load Yr; load Yhat; load Res; load Betas;
% ------------- prepare weight matrice -------------------------------------
if strcmp(LIMO.design.method,'WLS') || strcmp(LIMO.design.method,'OLS')
W = ones(size(Yr,1),size(Yr,3));
elseif strcmp(LIMO.design.method,'IRLS')
W = ones(size(Yr));
end
% -------------- loop the analysis time frames per time frames
if strcmp(LIMO.design.status,'to do')
% 1st get weights based on time
if strcmp(LIMO.design.method,'WLS')
fprintf('getting trial weights \n')
array = find(~isnan(Yr(:,1,1))); % skip empty electrodes
for e = 1:size(Yr,1)
electrode = array(e); [Betas,W(e,:)] = limo_WLS(LIMO.design.X,squeeze(Yr(electrode,:,:))');
end
LIMO.design.weights = W;
end
% 2nd run the multivariate analysis over electrodes
for t = 1:size(Yr,2)
fprintf('analysing time frame %g/%g \n',t,size(Yr,2));
model = limo_mglm(squeeze(Yr(:,t,:))',LIMO); warning off;
% update the LIMO.mat
if update == 1
if LIMO.design.nb_conditions ~=0
LIMO.model.conditions_df = [model.conditions.Roy.df' model.conditions.Roy.dfe' model.conditions.Pillai.df' model.conditions.Pillai.dfe'];
end
if LIMO.design.nb_interactions ~=0
LIMO.model.interactions_df = [model.interactions.Roy.df' model.interactions.Roy.dfe' model.interactions.Pillai.df' model.interactions.Pillai.dfe' ];
end
if LIMO.design.nb_continuous ~=0
LIMO.model.continuous_df = [model.continuous.Roy.df model.continuous.Roy.dfe];
end
update = 0;
end
% update the files to be stored on the disk
fitted_data = LIMO.design.X*model.betas;
Yhat(:,t,:) = fitted_data';
Res(:,t,:) = squeeze(Yr(:,t,:)) - fitted_data'; clear fitted_data
R2{t} = model.R2;
Betas(:,t,:) = model.betas';
if prod(LIMO.design.nb_conditions) ~=0
if length(LIMO.design.nb_conditions) == 1
tmp_Condition_effect{t} = model.conditions;
else
for i=1:length(LIMO.design.nb_conditions)
tmp_Condition_effect{t}(i).EV = model.conditions.EV(i,:);
tmp_Condition_effect{t}(i).Roy.F = model.conditions.Roy.F(i);
tmp_Condition_effect{t}(i).Roy.p = model.conditions.Roy.p(i);
tmp_Condition_effect{t}(i).Pillai.F = model.conditions.Pillai.F(i);
tmp_Condition_effect{t}(i).Pillai.p = model.conditions.Pillai.p(i);
end
end
end
if LIMO.design.fullfactorial == 1
if length(LIMO.design.nb_interactions) == 1
tmp_Interaction_effect{t} = model.interactions;
else
for i=1:length(LIMO.design.nb_interactions)
tmp_Interaction_effect{t}(i).EV = model.conditions.EV(i,:);
tmp_Interaction_effect{t}(i).Roy.F = model.conditions.Roy.F(i);
tmp_Interaction_effect{t}(i).Roy.p = model.conditions.Roy.p(i);
tmp_Interaction_effect{t}(i).Pillai.F = model.conditions.Pillai.F(i);
tmp_Interaction_effect{t}(i).Pillai.p = model.conditions.Pillai.p(i);
end
end
end
if LIMO.design.nb_continuous ~=0
if LIMO.design.nb_continuous == 1
tmp_Covariate_effect{t} = model.continuous;
else
for i=1:LIMO.design.nb_continuous
tmp_Covariate_effect{t}(i).EV = model.conditions.EV(i,:);
tmp_Covariate_effect{t}(i).Roy.F = model.conditions.Roy.F(i);
tmp_Covariate_effect{t}(i).Roy.p = model.conditions.Roy.p(i);
tmp_Covariate_effect{t}(i).Pillai.F = model.conditions.Pillai.F(i);
tmp_Covariate_effect{t}(i).Pillai.p = model.conditions.Pillai.p(i);
end
end
end
end
% save data on the disk and clean out
LIMO.design.weights = W;
LIMO.design.status = 'done';
save LIMO LIMO; save Yhat Yhat;
save Res Res; save Betas Betas;
clear Yhat Res Betas
% R2 data
name = sprintf('R2_EV',i); R2_EV = NaN(size(Yr,1),size(Yr,2));
for t=1:size(Yr,2); R2_EV(:,t) = real(R2{t}.EV); end
save(name,'R2_EV','-v7.3')
name = sprintf('R2'); tmp = NaN(size(Yr,2),5);
for t=1:size(Yr,2); tmp(t,:) = [R2{t}.V R2{t}.Roy.F R2{t}.Roy.p R2{t}.Pillai.F R2{t}.Pillai.p]; end
R2 = tmp; save(name,'R2','-v7.3')
% condition effects
if prod(LIMO.design.nb_conditions) ~=0
for i=1:length(LIMO.design.nb_conditions)
name = sprintf('Condition_effect_%g_EV',i);
if length(LIMO.design.nb_conditions) == 1
for t=1:size(Yr,2); Condition_effect_EV(:,t) = real(tmp_Condition_effect{t}.EV); end
save(name,'Condition_effect_EV','-v7.3')
name = sprintf('Condition_effect_%g',i);
for t=1:size(Yr,2); Condition_effect(t,:) = [tmp_Condition_effect{t}.Roy.F tmp_Condition_effect{t}.Roy.p tmp_Condition_effect{t}.Pillai.F tmp_Condition_effect{t}.Pillai.p]; end
save(name,'Condition_effect','-v7.3')
else
for t=1:size(Yr,2); Condition_effect_EV(:,t) = real(tmp_Condition_effect{t}(i).EV); end
save(name,'Condition_effect_EV','-v7.3')
name = sprintf('Condition_effect_%g',i);
for t=1:size(Yr,2); Condition_effect(t,:) = [tmp_Condition_effect{t}(i).Roy.F tmp_Condition_effect{t}(i).Roy.p tmp_Condition_effect{t}(i).Pillai.F tmp_Condition_effect{t}(i).Pillai.p]; end
save(name,'Condition_effect','-v7.3')
end
end
clear Condition_effect Condition_effect_EV tmp_Condition_effect
end
% interaction effects
if LIMO.design.fullfactorial == 1
for i=1:length(LIMO.design.nb_interactions)
name = sprintf('Interaction_effect_%g_EV',i);
if length(LIMO.design.nb_interactions) == 1
for t=1:size(Yr,2); Interaction_effect_EV(:,t) = real(tmp_Interaction_effect{t}.EV); end
save(name,'Interaction_effect_EV','-v7.3')
name = sprintf('Interaction_effect_%g',i);
for t=1:size(Yr,2); Interaction_effect(t,:) = [tmp_Interaction_effect{t}.Roy.F tmp_Interaction_effect{t}.Roy.p tmp_Interaction_effect{t}.Pillai.F tmp_Interaction_effect{t}.Pillai.p]; end
save(name,'Interaction_effect','-v7.3')
else
for t=1:size(Yr,2); Interaction_effect_EV(:,t) = real(tmp_Interaction_effect{t}(i).EV); end
save(name,'Interaction_effect_EV','-v7.3')
name = sprintf('Interaction_effect_%g',i);
for t=1:size(Yr,2); Interaction_effect(t,:) = [tmp_Interaction_effect{t}(i).Roy.F tmp_Interaction_effect{t}(i).Roy.p tmp_Interaction_effect{t}(i).Pillai.F tmp_Interaction_effect{t}(i).Pillai.p]; end
save(name,'Interaction_effectV','-v7.3')
end
end
clear Interaction_effect Interaction_effect_EV tmp_Interaction_effect
end
if LIMO.design.nb_continuous ~=0
for i=1:LIMO.design.nb_continuous
name = sprintf('Covariate_effect_%g_EV',i);
if LIMO.design.nb_continuous == 1
for t=1:size(Yr,2); Covariate_effect_EV(:,t) = real(tmp_Covariate_effect{t}.EV); end
save(name,'Covariate_effect_EV','-v7.3')
name = sprintf('Covariate_effect_%g',i);
for t=1:size(Yr,2); Covariate_effect(t,:) = [tmp_Covariate_effect{t}.Roy.F tmp_Covariate_effect{t}.Roy.p tmp_Covariate_effect{t}.Pillai.F tmp_Covariate_effect{t}.Pillai.p]; end
save(name,'Covariate_effect','-v7.3')
else
for t=1:size(Yr,2); Covariate_effect_EV(:,t) = real(tmp_Covariate_effect{t}(i).EV); end
save(name,'Covariate_effect_EV','-v7.3')
name = sprintf('Covariate_effect_%g',i);
for t=1:size(Yr,2); Covariate_effect(t,:) = [tmp_Covariate_effect{t}(i).Roy.F tmp_Covariate_effect{t}(i).Roy.p tmp_Covariate_effect{t}(i).Pillai.F tmp_Covariate_effect{t}(i).Pillai.p]; end
save(name,'Covariate_effect','-v7.3')
end
end
clear Covariate_effect Covariate_effect_EV tmp_Covariate_effect
end
clear file electrode filename model reg dir i W
end
% if bootsrrap
if LIMO.design.bootstrap == 1
end
% TFCE if requested
if LIMO.design.tfce == 1
end
end
warning on;
case{5}
%% ------------------------------------------------------------------------
% Results
% ------------------------------------------------------------------------
% short cut to limo_results
% check which files are there
% -------------------------
try
LIMO = load('LIMO.mat');
LIMO = LIMO.LIMO;
catch
[file,dir_newpath] = uigetfile('LIMO.mat','select a LIMO.mat file');
if file ==0
return
else
cd(dir_newpath);
LIMO = load('LIMO.mat');
LIMO = LIMO.LIMO;
end
end
cd(LIMO.dir);
% R2
% ---
if exist('R2.mat','file')
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,'R2.mat',pwd,0.05,3,LIMO,0);
else
limo_display_results(1,'R2.mat',pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,'R2.mat',pwd,0.05,1,LIMO,0);
end
saveas(gcf, 'R2.fig','fig'); close(gcf)
clear R2.mat
end
% conditions
if isfield(LIMO.design,'nb_conditions') ...
&& ~contains(LIMO.design.name,'Repeated','IgnoreCase',true)
if prod(LIMO.design.nb_conditions) ~=0
for i=1:length(LIMO.design.nb_conditions)
name = sprintf('Condition_effect_%g.mat',i);
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,name,pwd,0.05,3,LIMO,0);
else
limo_display_results(1,name,pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,name,pwd,0.05,1,LIMO,0);
end
savename = sprintf('Condition_effect_%g.fig',i);
saveas(gcf, savename,'fig'); close(gcf)
end
end
end
% interactions
if isfield(LIMO.design,'nb_interactions') ...
&& ~contains(LIMO.design.name,'Repeated','IgnoreCase',true)
if LIMO.design.fullfactorial == 1
for i=1:length(LIMO.design.nb_interactions)
name = sprintf('Interaction_effect_%g.mat',i);
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,name,pwd,0.05,3,LIMO,0);
else
limo_display_results(1,name,pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,name,pwd,0.05,1,LIMO,0);
end
savename = sprintf('Interaction_effect_%g.fig',i);
saveas(gcf, savename,'fig'); close(gcf)
end
end
end
% covariates / continuous regressors
if isfield(LIMO.design,'nb_continuous')
if LIMO.design.nb_continuous ~=0
for i=1:LIMO.design.nb_continuous
name = sprintf('Covariate_effect_%g.mat',i);
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,name,pwd,0.05,3,LIMO,0);
else
limo_display_results(1,name,pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,name,pwd,0.05,1,LIMO,0);
end
savename = sprintf('Covariate_effect_%g.fig',i);
saveas(gcf, savename,'fig'); close(gcf)
end
end
end
check_semi = dir('semi_partial_coef*.mat');
if ~isempty(check_semi)
for i=1:size(check_semi,2)
name = sprintf('semi_partial_coef_%g.mat',i);
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,name,pwd,0.05,3,LIMO,0);
else
limo_display_results(1,name,pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,name,pwd,0.05,1,LIMO,0);
end
savename = sprintf('semi_partial_coef_%g.fig',i);
saveas(gcf, savename,'fig'); close(gcf)
end
end
other_names = {'*ttest*.mat','Rep_ANOVA*.mat','con*.mat','ess*.mat'};
for check = 1:length(other_names)
check_test = dir(cell2mat(other_names(check)));
if ~isempty(check_test)
for file = 1:size(check_test,1)
name = check_test(file).name;
if LIMO.design.bootstrap ~=0
if LIMO.design.tfce == 1
limo_display_results(1,name,pwd,0.05,3,LIMO,0);
else
limo_display_results(1,name,pwd,0.05,2,LIMO,0);
end
else
limo_display_results(1,name,pwd,0.05,1,LIMO,0);
end
if ~strcmpi(LIMO.Analysis,'Time-Frequency')
savename = sprintf('%s.fig',name(1:end-4));
saveas(gcf, savename,'fig'); close(gcf)
end
end
end
end
case{6}
%% ------------------------------------------------------------------------
% Contrast
% ------------------------------------------------------------------------
% from the result GUI call the contrast manager; here we load a
% series contrast -- this could be commented and put the contrast
% right away. IMPORTANT by using limo_eeg(6) the .mat for the
% contrast must be called C (also the name used in the contrast
% manager. This bit is usuful for batching (replicate some part of
% code of the contrast manager)
% load LIMO and C
if exist('LIMO.mat','file')
load LIMO; F = getfield(LIMO,'contrast');
for f=1:length(F)
C(f,:) = F{f}.C;
end
else
[LIMO_file,LIMO_dir] = uigetfile('.mat','select a LIMO.mat file');
cd (LIMO_dir); load LIMO.mat;
end
previous_con = 0;
if ~exist('C','var')
[contrast_file,contrast_dir] = uigetfile({'*.mat';'*.txt'},'select your contrast file');
cd (contrast_dir); load(contrast_file); % problm here it has to be named C
if strcmp(FileName(end-3:end),'.txt')
C = importdata(contrast_file);
elseif strcmp(FileName(end-3:end),'.mat')
contrast_file = load(contrast_file);
C = getfield(contrast_file,cell2mat(fieldnames(contrast_file)));
end
cd (LIMO.dir);
if isfield(LIMO,'contrast')
previous_con = size(LIMO.contrast,2);
end
end
% Check dimensions
C = limo_contrast_checking(LIMO.dir, LIMO.design.X, C);
% Perform the analysis
load Yr; load Betas;
for i=1:size(C,1) % for each contrast
% check validity
go = limo_contrast_checking(C(i,:),LIMO.design.X);
if go == 0
fprintf('the contrast %g is not valid',i)
error('error line 281 in limo_eeg')
end
% update LIMO.mat
LIMO.contrast{previous_con+i}.C = C(i,:);
% create con file
con = zeros(size(Yr,1),size(Yr,2),3); % dim 3 =F/t/p
filename = sprintf('con_%g.mat',(i+previous_con));
save ([filename], 'con'); clear con;
% update con file
fprintf('computing contrast %g',i); disp(' ');
result = limo_contrast(Yr, Betas, LIMO, 0,1);
% update multivariate results
if strfind(LIMO.design.type_of_analysis,'multivariate')
LIMO.contrast{i}.multivariate = result;
end
save LIMO LIMO
end
clear Yr LIMO_dir LIMO_file contrast_dir contrast_file electrode filename previous_con result C;
case{7}
% ------------------------------------------------------------------------
% Gp Effects
% ------------------------------------------------------------------------
limo_random_effect
end