% POP_CLUSTEDIT - graphic user interface (GUI)-based function with editing and plotting
% options for visualizing and manipulating an input STUDY structure.
% Only component measures (e.g., dipole locations, scalp maps, spectra,
% ERPs, ERSPs, ITCs) that have been computed and saved in the study EEG
% datasets can be visualized. These can be computed during pre-clustering
% using the GUI-based function POP_PRECLUST or the equivalent command
% line functions STD_PRECLUST. To use dipole locations for clustering,
% they must first be stored in the EEG dataset structures using DIPFIT.
% Supported cluster editing functions include new cluster creation, cluster
% merging, outlier rejection, and cluster renaming. Components can also be
% moved from one cluster to another or to the outlier cluster.
% Usage:
% >> STUDY = pop_clustedit(STUDY, ALLEEG, clusters, addui, addgeom);
% Inputs:
% ALLEEG - Top-level EEGLAB vector of loaded EEG structures for the dataset(s)
% in the STUDY. ALLEEG for a STUDY set is typically loaded using
% POP_LOADSTUDY, or in creating a new STUDY, using POP_CREATESTUDY.
% STUDY - EEGLAB STUDY set comprising some or all of the EEG datasets in ALLEEG.
%
% Optional inputs:
% clusters - [integer vector] of cluster numbers. These clusters will be visualized
% and manipulated in the POP_CLUSTEDIT graphic interface. There are
% restrictions on which clusters can be loaded together. The clusters must
% either originate from the same clustering (same PRE_CLUSTERING and
% subsequent POP_CLUST execution), or they must all be leaf clusters
% (i.e., clusters with no child clusters) {default: all leaf clusters}.
% addui - [struct] additional uicontrols entries for the graphic
% interface. Must contains the fields "uilist", "geometry".
%
% Outputs:
% STUDY - The input STUDY set structure modified according to specified user edits,
% if any. Plotted cluster measure means (maps, ERSPs, etc.) are added to
% the STUDY structure after they are first plotted to allow quick replotting.
%
% Graphic interface buttons:
% "Select cluster to plot" - [list box] Displays available clusters to plot (format is
% 'cluster name (number of components)'). The presented clusters depend
% on the optional input variable 'clusters'. Selecting (clicking on) a
% cluster from the list will display the selected cluster components in the
% "Select component(s) to plot" list box. Use the plotting buttons below
% to plot selected measures of the selected cluster. Additional editing
% options (renaming the cluster, rejecting outliers, moving components to
% another cluster) are also available. The option 'All N cluster centroids'
% at the top of the list displays all the clusters in the list except the
% 'Notcluster', 'Outlier' and 'ParentCluster' clusters. Selecting this option
% will plot the cluster centroids (i.e. ERP, ERSP, ...) in a single figure.
% "Select component(s) to plot" - [list box] Displays the ICA components of the currently
% selected cluster (in the "Select cluster to plot" list box). Each component
% has the format: 'subject name, component index'. Multiple components can be
% selected from the list. Use the plotting buttons below to plot different
% measures of the selected components on different figures. Selecting the
% "All components" option is equivalent to using the cluster plotting buttons.
% Additional editing options are reassigning the selected components to
% another cluster or moving them to the outlier cluster.
% "Plot Cluster properties" - [button] Displays in one figure all the mean cluster measures
% (e.g., dipole locations, scalp maps, spectra, etc.) that were calculated
% and saved in the EEG datasets. If there is more than one condition, the ERP
% and the spectrum will have different colors for each condition. The ERSP
% and ITC plots will show only the first condition; clicking on the subplot
% will open a new figure with the different conditions displayed together.
% Uses the command line function STD_PROPPLOT.
% "Plot scalp maps" - [button] Displays the scalp maps of cluster components.
% If applied to a cluster, scalp maps of the cluster components
% are plotted along with the cluster mean scalp map in one figure.
% If "All # cluster centroids" option is selected, all cluster scalp map
% means are plotted in the same figure. If applied to components, displays
% the scalp maps of the specified cluster components in separate figures.
% Uses the command line functions STD_TOPOPLOT.
% "Plot ERSPs" - [button] Displays the cluster component ERSPs.
% If applied to a cluster, component ERSPs are plotted in one figure
% (per condition) with the cluster mean ERSP. If "All # cluster centroids"
% option is selected, plots all average ERSPs of the clusters in one figure
% per condition. If applied to components, display the ERSP images of specified
% cluster components in separate figures, using one figure for all conditions.
% Uses the command line functions STD_ERSPPLOT.
% "Plot ITCs" - [button] Same as "Plot ERSPs" but with ITC.
% Uses the command line functions STD_ITCPLOT.
% "Plot dipoles" - [button] Displays the dipoles of the cluster components.
% If applied to a cluster, plots the cluster component dipoles (in blue)
% plus the average cluster dipole (in red). If "All # cluster centroids" option
% is selected, all cluster plots are displayed in one figure each cluster in
% a separate subplot. If applied to components, displays the ERSP images of the
% specified cluster. For specific components displays components dipole (in blue)
% plus the average cluster dipole (in Red) in separate figures.
% Uses the command line functions STD_DIPPLOT.
% "Plot spectra" - [button] Displays the cluster component spectra.
% If applied to a cluster, displays component spectra plus the average cluster
% spectrum in bold. For a specific cluster, displays the cluster component
% spectra plus the average cluster spectrum (in bold) in one figure per condition.
% If the "All # cluster centroids" option is selected, displays the average
% spectrum of all clusters in the same figure, with spectrum for different
% conditions (if any) plotted in different colors.
% If applied to components, displays the spectrum of specified cluster
% components in separate figures using one figure for all conditions.
% Uses the command line functions STD_SPECPLOT.
% "Plot ERPs" - [button] Same as "Plot spectra" but for ERPs.
% Uses the command line functions STD_ERPPLOT.
% "Plot ERPimage" - [button] Same as "Plot ERP" but for ERPimave.
% Uses the command line functions STD_ERPIMPLOT.
% "Create new cluster" - [button] Creates a new empty cluster.
% Opens a popup window in which a name for the new cluster can be entered.
% If no name is given the default name is 'Cls #', where '#' is the next
% available cluster number. For changes to take place, press the popup
% window 'OK' button, else press the 'Cancel' button. After the empty
% cluster is created, components can be moved into it using,
% 'Reassign selected component(s)' (see below). Uses the command line
% function STD_CREATECLUST.
% "Rename selected cluster" - [button] Renames a cluster using the selected (mnemonic) name.
% Opens a popup window in which a new name for the selected cluster can be
% entered. For changes to take place, press the popup window 'OK' button,
% else press the 'Cancel' button. Uses the command line function STD_RENAMECLUST.
% "Reject outlier components" - [button] rejects outlier components to an outlier cluster.
% Opens a popup window to specify the outlier threshold. Move outlier
% components that are more than x standard deviations devs from the
% cluster centroid to an outlier cluster. For changes to take place,
% press the popup window 'OK' button, else press the 'Cancel' button.
% Uses the command line function STD_REJECTOUTLIERS.
% "Merge clusters" - [button] Merges several clusters into one cluster.
% Opens a popup window in which the clusters to merge may be specified
% An optional name can be given to the merged cluster. If no name is given,
% the default name is 'Cls #', where '#' is the next available cluster number.
% For changes to take place, press the popup window 'OK' button, else press
% the 'Cancel' button. Uses the command line function STD_MERGECLUST.
% "Remove selected outlier component(s)" - [button] Moves selected component(s) to the
% outlier cluster. The components that will be moved are the ones selected
% in the "Select component(s) to plot" list box. Opens a popup window in which
% a list of the selected component(s) is presented. For changes to take place,
% press the popup window 'OK' button, else press the 'Cancel' button.
% Uses the command line function STD_MOVEOUTLIER.
% "Reassign selected component(s)" - [button] Moves selected component(s) from one cluster
% to another. The components that will reassign are the ones selected in the
% "Select component(s) to plot" list box. Opens a popup window in which
% a list of possible clusters to which to move the selected component(s) is
% presented. For changes to take place, press the popup window 'OK' button,
% else press the 'Cancel' button. Uses the command line function STD_MOVECOMP.
% "Save STUDY set to disk" - [check box] Saves the STUDY set structure modified according
% to specified user edits to the disk. If no file name is entered will
% overwrite the current STUDY set file.
%
% See also: POP_PRECLUST, POP_CLUST.
%
% Authors: Arnaud Delorme, Hilit Serby, Scott Makeig, SCCN/INC/UCSD, October 11, 2004
% Copyright (C) Hilit Serby, SCCN, INC, UCSD, October 11, 2004, hilit@sccn.ucsd.edu
%
% This file is part of EEGLAB, see http://www.eeglab.org
% for the documentation and details.
%
% Redistribution and use in source and binary forms, with or without
% modification, are permitted provided that the following conditions are met:
%
% 1. Redistributions of source code must retain the above copyright notice,
% this list of conditions and the following disclaimer.
%
% 2. Redistributions in binary form must reproduce the above copyright notice,
% this list of conditions and the following disclaimer in the documentation
% and/or other materials provided with the distribution.
%
% THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
% AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
% IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
% ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE
% LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
% CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
% SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
% INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
% CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
% ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF
% THE POSSIBILITY OF SUCH DAMAGE.
function [STUDY, com] = pop_clustedit(varargin)
icadefs;
if nargin < 2
help pop_clustedit;
return;
end
if ~ischar(varargin{1})
STUDY = varargin{1};
STUDY.etc.erpparams.topotime = NaN; % [] for channels and NaN for components
STUDY.etc.specparams.topofreq = NaN; % NaN -> GUI disabled
STUDY.etc.erspparams.topotime = NaN;
STUDY.etc.erspparams.topofreq = NaN;
STUDY.etc.erpimparams.topotime = NaN;
STUDY.etc.erpimparams.topotrial = NaN;
STUDY.tmphist = '';
ALLEEG = varargin{2};
clus_comps = 0; % the number of clustered components
if nargin > 2 && ~isempty(varargin{3}) % load specific clusters
cls = varargin{3}; %cluster numbers
N = length(cls); %number of clusters
% Check clusters are either from the same level (same parents) or are
% all leaf clusters.
% Check all input clusters have the same parent
sameparent = 1;
for k = 1: N
% Assess the number of clustered components
if (~strncmpi('Notclust',STUDY.cluster(cls(k)).name,8)) && (~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13))
clus_comps = clus_comps + length(STUDY.cluster(cls(k)).comps);
end
if k == 1
parent = STUDY.cluster(cls(k)).parent;
else
if isempty(parent) % if the first cluster was the parent cluster
parent = STUDY.cluster(cls(k)).parent;
end
% For any other case verify that all clusters have the same parents
if ~(sum(strcmp(STUDY.cluster(cls(k)).parent, parent)) == length(parent)) % different parent
if ~strcmp(STUDY.cluster(cls(k)).parent,'manual') && ~strcmp(parent, 'manual')
% if neither is an empty cluster (which was created manually)
sameparent = 0; % then the clusters have different parents
end
end
end
end
% If not same parent check if all leaf clusters
% ---------------------------------------------
if ~sameparent
for k = 1: N %check if all leaves
if ~isempty(STUDY.cluster(cls(k)).child)
error([ 'pop_clustedit(): All clusters must be from the same level \n' ...
' (i.e., have the same parents or not be child clusters)' ]);
end
end
end
% plotting text etc ...
% --------------------
num_cls = 0;
for k = 1:N
show_options{k+1} = [STUDY.cluster(cls(k)).name ' (' num2str(length(STUDY.cluster(cls(k)).comps)) ' ICs)'];
if (~strncmpi('Notclust',STUDY.cluster(cls(k)).name,8)) && (~strncmpi('Outliers',STUDY.cluster(cls(k)).name,8)) && ...
(~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13))
num_cls = num_cls + 1;
end
end
show_options{1} = ['All ' num2str(num_cls) ' cluster centroids'];
else % load leaf clusters
sameparent = 1;
cls = [];
for k = 2:length(STUDY.cluster)
if isempty(STUDY.cluster(k).child)
if isempty(cls)
parent = STUDY.cluster(k).parent;
elseif ~isempty(STUDY.cluster(k).parent) || ~isempty(parent) % if not both empty
% Check if all parents are the same
if ~(sum(strcmp(STUDY.cluster(k).parent, parent)) == length(parent)) % different parent
if ~strcmp(STUDY.cluster(k).parent,'manual') && ~strcmp(parent, 'manual')
sameparent = 0;
end
end
end
cls = [ cls k];
if ~strncmpi('Notclust',STUDY.cluster(k).name,8)
clus_comps = clus_comps + length(STUDY.cluster(k).comps);
end
end
end
% Plot clusters hierarchically
% ----------------------------
num_cls = 0;
cls = 1:length(STUDY.cluster);
N = length(cls); %number of clusters
show_options{1} = [STUDY.cluster(1).name ' (' num2str(length(STUDY.cluster(1).comps)) ' ICs)'];
cls(1) = 1;
count = 2;
for index1 = 1:length(STUDY.cluster(1).child)
indclust1 = strmatch( STUDY.cluster(1).child(index1), { STUDY.cluster.name }, 'exact');
show_options{count} = [' ' STUDY.cluster(indclust1).name ' (' num2str(length(STUDY.cluster(indclust1).comps)) ' ICs)'];
cls(count) = indclust1;
count = count+1;
for index2 = 1:length( STUDY.cluster(indclust1).child )
indclust2 = strmatch( STUDY.cluster(indclust1).child(index2), { STUDY.cluster.name }, 'exact');
show_options{count} = [' ' STUDY.cluster(indclust2).name ' (' num2str(length(STUDY.cluster(indclust2).comps)) ' ICs)'];
cls(count) = indclust2;
count = count+1;
for index3 = 1:length( STUDY.cluster(indclust2).child )
indclust3 = strmatch( STUDY.cluster(indclust2).child(index3), { STUDY.cluster.name }, 'exact');
show_options{count} = [' ' STUDY.cluster(indclust3).name ' (' num2str(length(STUDY.cluster(indclust3).comps)) ' ICs)'];
cls(count) = indclust3;
count = count+1;
end
end
end
show_options = { ['All cluster centroids'] show_options{:} };
end
all_comps = length(STUDY.cluster(1).comps);
show_clust_gcf = [ 'pop_clustedit(''showclust'',gcf);'];
show_clust = [ 'pop_clustedit(''showclust'',gcbf);'];
show_comps = [ 'pop_clustedit(''showcomplist'',gcbf);'];
plot_clus_maps = [ 'pop_clustedit(''topoplot'',gcbf); '];
plot_comp_maps = [ 'pop_clustedit(''plotcomptopo'',gcbf); '];
plot_clus_ersps = ['pop_clustedit(''erspplot'',gcbf); '];
plot_comp_ersps = ['pop_clustedit(''plotcompersp'',gcbf); '];
plot_clus_itcs = ['pop_clustedit(''itcplot'',gcbf); '];
plot_comp_itcs = ['pop_clustedit(''plotcompitc'',gcbf); '];
plot_clus_erpim = ['pop_clustedit(''erpimageplot'',gcbf); '];
plot_comp_erpim = ['pop_clustedit(''plotcomperpimage'',gcbf); '];
plot_clus_spectra = ['pop_clustedit(''specplot'',gcbf); '];
plot_comp_spectra = ['pop_clustedit(''plotcompspec'',gcbf); '];
plot_clus_erp = ['pop_clustedit(''erpplot'',gcbf); '];
plot_comp_erp = ['pop_clustedit(''plotcomperp'',gcbf); '];
plot_clus_dip = ['pop_clustedit(''dipplot'',gcbf); '];
plot_comp_dip = ['pop_clustedit(''plotcompdip'',gcbf); '];
plot_clus_sum = ['pop_clustedit(''plotsum'',gcbf); '];
plot_comp_sum = ['pop_clustedit(''plotcompsum'',gcbf); '];
rename_clust = ['pop_clustedit(''renameclust'',gcbf);'];
move_comp = ['pop_clustedit(''movecomp'',gcbf);'];
move_outlier = ['pop_clustedit(''moveoutlier'',gcbf);'];
create_clus = ['pop_clustedit(''createclust'',gcbf);'];
reject_outliers = ['pop_clustedit(''rejectoutliers'',gcbf);'];
merge_clusters = ['pop_clustedit(''mergeclusters'',gcbf);'];
dip_opt = ['pop_clustedit(''dip_opt'',gcbf);'];
erp_opt = ['pop_clustedit(''erp_opt'',gcbf);'];
spec_opt = ['pop_clustedit(''spec_opt'',gcbf);'];
ersp_opt = ['pop_clustedit(''ersp_opt'',gcbf);'];
erpim_opt = ['pop_clustedit(''erpim_opt'',gcbf);'];
stat_opt = ['pop_clustedit(''stat_opt'',gcbf);'];
saveSTUDY = [ 'set(findobj(''parent'', gcbf, ''userdata'', ''save''), ''enable'', fastif(get(gcbo, ''value'')==1, ''on'', ''off''));' ];
browsesave = [ '[filename, filepath] = uiputfile2(''*.study'', ''Save STUDY with .study extension -- pop_clust()''); ' ...
'set(findobj(''parent'', gcbf, ''tag'', ''studyfile''), ''string'', [filepath filename]);' ];
% Create default ERSP / ITC time/freq. parameters
% ----------------------------------------------
if isempty(ALLEEG)
error('STUDY contains no datasets');
end
% enable buttons
% --------------
filename = fullfile(STUDY.datasetinfo(1).filepath, STUDY.datasetinfo(1).subject);
if ~isempty(dir([filename '*.icaspec'])), spec_enable = 'on'; else spec_enable = 'off'; end
if ~isempty(dir([filename '*.icaerp'] )) , erp_enable = 'on'; else erp_enable = 'off'; end
if ~isempty(dir([filename '*.icaerpim'] )), erpim_enable = 'on'; else erpim_enable = 'off'; end
if ~isempty(dir([filename '*.icatimef'])) , ersp_enable = 'on'; else ersp_enable = 'off'; end
filename = fullfile( ALLEEG(1).filepath, ALLEEG(1).filename(1:end-4));
if ~isempty(dir([filename '*.icatopo'])), scalp_enable = 'on'; else scalp_enable = 'off'; end
if isfield(ALLEEG(1).dipfit, 'model'), dip_enable = 'on'; else dip_enable = 'off'; end
% userdata below
% --------------
fig_arg{1}{1} = ALLEEG;
fig_arg{1}{2} = STUDY;
fig_arg{1}{3} = cls;
fig_arg{2} = N;
str_name = sprintf('STUDY ''%s'' - ''%s'' component clusters', STUDY.name, STUDY.design(STUDY.currentdesign).name);
if length(str_name) > 80, str_name = [ str_name(1:80) '...''' ]; end
if length(cls) > 1, vallist = 1; else vallist = 2; end
geomline = [1 0.35 1];
geometry = { [0.8 3] [1] geomline geomline geomline geomline geomline geomline geomline geomline ...
geomline [1] geomline geomline }; %geomline };
geomvert = [ 1 .5 1 3 1 1 1 1 1 1 1 1 1 1 ]; %1];
uilist = { ...
{'style' 'text' 'string' 'Select design:' 'FontWeight' 'Bold' 'HorizontalAlignment' 'center'} ...
{'style' 'popupmenu' 'string' { STUDY.design.name } 'FontWeight' 'Bold' 'tag' 'design' 'value' STUDY.currentdesign } ...
{ } ...
{'style' 'text' 'string' 'Select cluster to plot' 'FontWeight' 'Bold' } {} ...
{'style' 'text' 'string' 'Select component to plot ' 'FontWeight' 'Bold'} ...
{'style' 'listbox' 'string' show_options 'value' vallist 'tag' 'clus_list' 'Callback' show_clust } ...
{'style' 'pushbutton' 'enable' 'on' 'string' 'STATS' 'Callback' stat_opt } ...
{'style' 'listbox' 'string' '' 'tag' 'clust_comp' 'max' 2 'min' 1 'callback' show_comps } ...
{'style' 'pushbutton' 'enable' scalp_enable 'string' 'Plot scalp maps' 'Callback' plot_clus_maps} {} ...
{'style' 'pushbutton' 'enable' scalp_enable 'string' 'Plot scalp map(s)' 'Callback' plot_comp_maps}...
{'style' 'pushbutton' 'enable' dip_enable 'string' 'Plot dipoles' 'Callback' plot_clus_dip} ...
{'style' 'pushbutton' 'enable' dip_enable 'string' 'Params' 'Callback' dip_opt } ...
{'style' 'pushbutton' 'enable' dip_enable 'string' 'Plot dipole(s)' 'Callback' plot_comp_dip}...
{'style' 'pushbutton' 'enable' erp_enable 'string' 'Plot ERPs' 'Callback' plot_clus_erp} ...
{'style' 'pushbutton' 'enable' erp_enable 'string' 'Params' 'Callback' erp_opt } ...
{'style' 'pushbutton' 'enable' erp_enable 'string' 'Plot ERP(s)' 'Callback' plot_comp_erp} ...
{'style' 'pushbutton' 'enable' spec_enable 'string' 'Plot spectra' 'Callback' plot_clus_spectra} ...
{'style' 'pushbutton' 'enable' spec_enable 'string' 'Params' 'Callback' spec_opt } ...
{'style' 'pushbutton' 'enable' spec_enable 'string' 'Plot spectra' 'Callback' plot_comp_spectra} ...
{'style' 'pushbutton' 'enable' erpim_enable 'string' 'Plot ERPimage' 'Callback' plot_clus_erpim} ...
{'style' 'pushbutton' 'enable' erpim_enable 'string' 'Params' 'Callback' erpim_opt } ...
{'style' 'pushbutton' 'enable' erpim_enable 'string' 'Plot ERPimage(s)' 'Callback' plot_comp_erpim} ...
{'style' 'pushbutton' 'enable' ersp_enable 'string' 'Plot ERSPs' 'Callback' plot_clus_ersps} ...
{'vertexpand' 2.1 'style' 'pushbutton' 'enable' ersp_enable 'string' 'Params' 'Callback' ersp_opt } ...
{'style' 'pushbutton' 'enable' ersp_enable 'string' 'Plot ERSP(s)' 'Callback' plot_comp_ersps} ...
{'style' 'pushbutton' 'enable' ersp_enable 'string' 'Plot ITCs' 'Callback' plot_clus_itcs} { } ...
{'style' 'pushbutton' 'enable' ersp_enable 'string' 'Plot ITC(s)' 'Callback' plot_comp_itcs} ...
... % {} {}... %{'style' 'pushbutton' 'string' 'Plot cluster properties' 'Callback' plot_clus_sum 'enable' 'off'} {} ...
... % {'style' 'pushbutton' 'string' 'Plot component properties' 'Callback' plot_comp_sum 'enable' 'on'} ... % nima, was off
{} ...
{'style' 'pushbutton' 'string' 'Create new cluster' 'Callback' create_clus} {} ...
{'style' 'pushbutton' 'string' 'Reassign selected component(s)' 'Callback' move_comp} ...
{'style' 'pushbutton' 'string' 'Rename selected cluster' 'Callback' rename_clust } {} ...
{'style' 'pushbutton' 'string' 'Remove selected outlier comps.' 'Callback' move_outlier} };
% {'style' 'pushbutton' 'string' 'Merge clusters' 'Callback' merge_clusters } {} ...
% {'style' 'pushbutton' 'string' 'Auto-reject outlier components' 'Callback' reject_outliers } };
% additional UI given on the command line
% ---------------------------------------
if nargin > 3
addui = varargin{4};
if ~isfield(addui, 'uilist')
error('Additional GUI definition (argument 4) requires the field "uilist"');
end
if ~isfield(addui, 'geometry')
addui.geometry = mat2cell(ones(1,length(addui.uilist)));
end
uilist = { uilist{:}, addui.uilist{:} };
geometry = { geometry{:} addui.geometry{:} };
geomvert = [ geomvert ones(1,length(addui.geometry)) ];
end
[out_param, userdat] = inputgui( 'geometry' , geometry, 'uilist', uilist, ...
'helpcom', 'pophelp(''pop_clustedit'')', ...
'title', 'View and edit current component clusters -- pop_clustedit()' , 'userdata', fig_arg, ...
'geomvert', geomvert, 'eval', show_clust_gcf );
if ~isempty(userdat)
ALLEEG = userdat{1}{1};
STUDY = userdat{1}{2};
end
% history
% -------
com = STUDY.tmphist;
STUDY = rmfield(STUDY, 'tmphist');
else
hdl = varargin{2}; %figure handle
userdat = get(varargin{2}, 'userdat');
ALLEEG = userdat{1}{1};
STUDY = userdat{1}{2};
cls = userdat{1}{3};
design = get(findobj('parent', hdl, 'tag', 'design') , 'value');
if ~std_checkdesign(STUDY, design)
return;
end
clus = get(findobj('parent', hdl, 'tag', 'clus_list'), 'value');
comp_ind = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'Value');
if clus == 1 && length(cls) == 1
warndlg2('No cluster', 'No cluster');
return;
end
try
switch varargin{1}
case {'plotcomptopo', 'plotcompersp','plotcompitc','plotcompspec', 'plotcomperp', 'plotcompdip', 'plotcomperpimage'}
plotting_option = varargin{1};
plotting_option = [ plotting_option(9:end) 'plot' ];
if (clus ~= 1 ) %specific cluster
if comp_ind(1) ~= 1 % check that not all comps in cluster are requested
subject = STUDY.datasetinfo( STUDY.cluster(cls(clus-1)).sets(1,comp_ind-1)).subject;
a = ['STUDY = std_' plotting_option '(STUDY,ALLEEG,''clusters'',' num2str(cls(clus-1)) ', ''comps'', ' num2str(comp_ind-1) ', ''design'', ' int2str(design) ' );' ];
eval(a); STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
else
a = ['STUDY = std_' plotting_option '(STUDY,ALLEEG,''clusters'',' num2str(cls(clus-1)) ', ''design'', ' int2str(design) ', ''plotsubjects'', ''on'' );' ];
eval(a); STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
end
else
comp_list = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'String');
comp_name = comp_list(comp_ind);
for ci = 1:length(comp_name)
num_comps = 0;
tmp = strfind(comp_name{ci},'''');
clust_name = comp_name{ci}(tmp(1)+1:tmp(end)-1);
for k = 1:length(cls)
if ~strncmpi('Notclust',STUDY.cluster(cls(k)).name,8) && ~strncmpi('Outliers',STUDY.cluster(cls(k)).name,8) && ...
(~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13))
if strcmpi(STUDY.cluster(cls(k)).name, clust_name)
cind = comp_ind(ci) - num_comps; % component index in the cluster
subject = STUDY.datasetinfo( STUDY.cluster(cls(k)).sets(1,cind)).subject;
a = ['STUDY = std_' plotting_option '(STUDY,ALLEEG,''clusters'',' num2str(cls(k)) ', ''design'', ' int2str(design) ', ''comps'',' num2str(cind) ' );' ];
eval(a); STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
break;
else
num_comps = num_comps + length(STUDY.cluster(cls(k)).comps);
end
end
end
end
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
case {'topoplot', 'erspplot', 'itcplot', 'specplot', 'erpplot', 'dipplot', 'erpimageplot' }
plotting_option = varargin{1};
plotting_option = [ plotting_option(1:end-4) 'plot' ];
if (clus ~= 1 ) % specific cluster option
if ~isempty(STUDY.cluster(cls(clus-1)).comps)
a = ['STUDY = std_' plotting_option '(STUDY,ALLEEG,''clusters'',' num2str(cls(clus-1)) ', ''design'', ' int2str(design) ');' ];
eval(a); STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
end
else % all clusters
% All clusters does not include 'Notclust' 'ParentCluster' and 'Outliers' clusters.
tmpcls = [];
for k = 1:length(cls)
if ~strncmpi(STUDY.cluster(cls(k)).name,'Notclust',8) && ~strncmpi(STUDY.cluster(cls(k)).name,'Outliers',8) && ...
(~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13)) && ~isempty(STUDY.cluster(cls(k)).comps)
tmpcls = [ tmpcls cls(k)];
end
end
a = ['STUDY = std_' plotting_option '(STUDY,ALLEEG,''clusters'',[' num2str(tmpcls) '], ''design'', ' int2str(design) ');' ];
%if strcmpi(plotting_option, 'dipplot'), a = [a(1:end-2) ',''mode'', ''together'');' ]; end
eval(a); STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
case 'dip_opt' % save the list of selected chaners
[STUDY, com] = pop_dipparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'erp_opt' % save the list of selected chaners
[STUDY, com] = pop_erpparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'stat_opt' % save the list of selected chaners
[STUDY, com] = pop_statparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'spec_opt' % save the list of selected channels
[STUDY, com] = pop_specparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'erpim_opt' % save the list of selected channels
[STUDY, com] = pop_erpimparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'ersp_opt' % save the list of selected channels
[STUDY, com] = pop_erspparams(STUDY);
if ~isempty(com)
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, com);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'showcomplist' % save the list of selected clusters
clust = get(findobj('parent', hdl, 'tag', 'clus_list') , 'value');
comp = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'value');
N = userdat{2};
count = 1;
if clust ~= 1 %specific cluster
STUDY.cluster(cls(clust-1)).selected = comp;
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update information (STUDY)
case 'showclust'
cind = get(findobj('parent', hdl, 'tag', 'clus_list'), 'value');
N = userdat{2};
count = 1;
selected = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'value');
if cind ~= 1 %specific cluster
len = length(STUDY.cluster(cls(cind-1)).comps);
compid = cell(len+1,1);
compid{1} = 'All components';
% Convert from components numbering to the indexing form 'setXcomY'
for l = 1:len % go over the components of the cluster
if ~isnan(STUDY.cluster(cls(cind-1)).sets(1,l))
subject = STUDY.datasetinfo(STUDY.cluster(cls(cind-1)).sets(1,l)).subject;
compid{l+1} = [ subject ' IC' num2str(STUDY.cluster(cls(cind-1)).comps(1,l)) ];
end
end
if isfield(STUDY.cluster, 'selected')
if ~isempty(STUDY.cluster(cls(cind-1)).selected)
selected = min(STUDY.cluster(cls(cind-1)).selected, 1+length(STUDY.cluster(cls(cind-1)).comps(1,:)));
STUDY.cluster(cls(cind-1)).selected = selected;
end
end
else % All clusters accept 'Notclust' and 'Outliers'
count = 1;
for k = 1: length(cls)
if ~strncmpi('Notclust',STUDY.cluster(cls(k)).name,8) && ~strncmpi('Outliers',STUDY.cluster(cls(k)).name,8) && ...
(~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13))
for l = 1: length(STUDY.cluster(cls(k)).comps)
if ~isnan(STUDY.cluster(cls(k)).sets(1,l))
subject = STUDY.datasetinfo(STUDY.cluster(cls(k)).sets(1,l)).subject; % This line chokes on NaNs. TF 2007.05.31
compid{count} = [ '''' STUDY.cluster(cls(k)).name ''' comp. ' ...
num2str(l) ' (' subject ' IC' num2str(STUDY.cluster(cls(k)).comps(l)) ')'];
count = count +1;
end
end
end
end
end
if selected > length(compid), selected = 1; end
set(findobj('parent', hdl, 'tag', 'clust_comp'), 'value', selected, 'String', compid);
case 'plotsum'
if clus ~= 1 % specific cluster option
[STUDY] = std_propplot(STUDY, ALLEEG, 'cluster', cls(clus-1));
% update Study history
a = ['STUDY = std_propplot(STUDY, ALLEEG, ''cluster'', ' num2str(cls(clus-1)) ' );' ];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
else % all clusters
% All clusters does not include 'Notclust' and 'Outliers' clusters.
tmpcls = [];
for k = 1:length(cls)
if ~strncmpi(STUDY.cluster(cls(k)).name,'Notclust',8) && ~strncmpi(STUDY.cluster(cls(k)).name,'Outliers',8) && ...
(~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13))
tmpcls = [tmpcls cls(k)];
end
end
[STUDY] = std_propplot(STUDY, ALLEEG, 'cluster', tmpcls);
% update Study history
a = ['STUDY = std_propplot(STUDY, ALLEEG, ''cluster'', [' num2str(tmpcls) '] );' ];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
end
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
case 'plotcompsum'
for ci = 1 : length(comp_ind)
% place holder for component properties % nima
end
case 'renameclust'
STUDY.saved = 'no';
clus_name_list = get(findobj('parent', hdl, 'tag', 'clus_list'), 'String');
clus_num = get(findobj('parent', hdl, 'tag', 'clus_list'), 'Value') -1;
if clus_num == 0 % 'all clusters' option
return;
end
% Don't rename 'Notclust' and 'Outliers' clusters.
if strncmpi('Notclust',STUDY.cluster(cls(clus_num)).name,8) || strncmpi('Outliers',STUDY.cluster(cls(clus_num)).name,8) || ...
strncmpi('ParentCluster',STUDY.cluster(cls(clus_num)).name,13)
warndlg2('The ParentCluster, Outliers, and Notclust clusters cannot be renamed');
return;
end
old_name = STUDY.cluster(cls(clus_num)).name;
rename_param = inputgui( { [1] [1] [1]}, ...
{ {'style' 'text' 'string' ['Rename ' old_name] 'FontWeight' 'Bold'} {'style' 'edit' 'string' '' 'tag' 'clus_rename' } {} }, ...
'', 'Rename cluster - from pop_clustedit()' );
if ~isempty(rename_param) %if not canceled
new_name = rename_param{1};
STUDY = std_renameclust(STUDY, ALLEEG, cls(clus_num), new_name);
% update Study history
a = ['STUDY = std_renameclust(STUDY, ALLEEG, ' num2str(cls(clus_num)) ', ' STUDY.cluster(cls(clus_num)).name ');'];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
% Renaming cluster in list
new_name = [ STUDY.cluster(cls(clus_num)).name ' (' num2str(length(STUDY.cluster(cls(clus_num)).comps)) ' ICs)'];
clus_name_list{clus_num+1} = renameclust( clus_name_list{clus_num+1}, new_name);
% Renaming Outlier cluster if exist
outlier_clust = std_findoutlierclust(STUDY,cls(clus_num));
if outlier_clust ~= 0
new_outliername = [ STUDY.cluster(cls(outlier_clust)).name ' (' num2str(length(STUDY.cluster(cls(outlier_clust)).comps)) ' ICs)'];
clus_name_list{outlier_clust+1} = renameclust( clus_name_list{outlier_clust+1}, new_outliername);
end
set(findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_name_list);
set(findobj('parent', hdl, 'tag', 'clus_rename'), 'String', '');
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat); %update STUDY
end
case 'movecomp'
STUDY.saved = 'no';
old_clus = get(findobj('parent', hdl, 'tag', 'clus_list'), 'value') -1;
comp_ind = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'Value');
if old_clus == 0 % 'all clusters' option
return;
end
% Don't reassign components of 'Notclust' or the 'ParentCluster'.
if strncmpi('ParentCluster',STUDY.cluster(cls(old_clus)).name,13)
warndlg2('Cannot reassign components of ''ParentCluster''.');
return;
end
old_name = STUDY.cluster(cls(old_clus)).name;
ncomp = length(comp_ind); % number of selected components
optionalcls =[];
for k = 1:length(cls)
if (~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13)) && (k~= old_clus)
optionalcls = [optionalcls cls(k)];
end
end
reassign_param = inputgui( { [1] [1] [1]}, ...
{ {'style' 'text' 'string' strvcat(['Reassign ' fastif(ncomp >1, [num2str(length(comp_ind)) ' currently selected components'], ...
'currently selected component') ], ...
[' from ' old_name ' to the cluster selected below']) 'FontWeight' 'Bold'} ...
{'style' 'listbox' 'string' {STUDY.cluster(optionalcls).name} 'tag' 'new_clus'} {} }, ...
'', 'Reassign cluster - from pop_clustedit()' ,[] , 'normal', [2 3 1] );
if ~isempty(reassign_param) %if not canceled
new_clus = reassign_param{1};
comp_to_disp = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'String');
if strcmp(comp_to_disp{comp_ind(1)},'All components')
warndlg2('Cannot move all the components of the cluster - abort move components', 'Aborting move components');
return;
end
STUDY = std_movecomp(STUDY, ALLEEG, cls(old_clus), optionalcls(new_clus), comp_ind - 1);
% update Study history
a = ['STUDY = std_movecomp(STUDY, ALLEEG, ' num2str(cls(old_clus)) ', ' num2str(optionalcls(new_clus)) ', [' num2str(comp_ind - 1) ']);'];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
newind = find(cls == optionalcls(new_clus));
% update GUI
% ----------
clus_name_list = get(findobj('parent', hdl, 'tag', 'clus_list'), 'String');
newname = [STUDY.cluster(optionalcls(new_clus)).name ' (' num2str(length(STUDY.cluster(optionalcls(new_clus)).comps)) ' ICs)'];
clus_name_list{newind+1} = renameclust( clus_name_list{newind+1}, newname);
newname = [STUDY.cluster(cls(old_clus)).name ' (' num2str(length(STUDY.cluster(cls(old_clus)).comps)) ' ICs)'];
clus_name_list{old_clus+1} = renameclust( clus_name_list{old_clus+1}, newname);
set( findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_name_list);
STUDY.cache = [];
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
pop_clustedit('showclust',hdl);
end
case 'moveoutlier'
STUDY.saved = 'no';
old_clus = get(findobj('parent', hdl, 'tag', 'clus_list'), 'value') -1;
comp_ind = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'Value');
if ~isempty(find(comp_ind ==1))
warndlg2('Cannot remove all the cluster components');
return;
end
if old_clus == 0 % 'all clusters' option
return;
end
if strncmpi('Notclust',STUDY.cluster(cls(old_clus)).name,8) || strncmpi('ParentCluster',STUDY.cluster(cls(old_clus)).name,13) % There are no outliers to 'Notclust'
warndlg2('Cannot reassign components of ''Notclust'' or ''ParentCluster''.');
return;
end
comp_list = get(findobj('parent', hdl, 'tag', 'clust_comp'), 'String');
ncomp = length(comp_ind);
old_name = STUDY.cluster(cls(old_clus)).name;
if strncmpi('Outliers',STUDY.cluster(cls(old_clus)).name,8) % There are no outliers of 'Outliers'
warndlg2('Cannot use ''Outliers'' clusters for this option.');
return;
end
reassign_param = inputgui( { [1] [1] [1]}, ...
{ {'style' 'text' 'string' ['Remove ' fastif(ncomp >1, [num2str(length(comp_ind)) ' currently selected components below '], 'currently selected component below ') ...
'from ' old_name ' to its outlier cluster?'] 'FontWeight' 'Bold'} ...
{'style' 'listbox' 'string' {comp_list{comp_ind}} 'tag' 'new_clus'} {} }, ...
'', 'Remove outliers - from pop_clustedit()' ,[] , 'normal', [1 3 1] );
if ~isempty(reassign_param) %if not canceled
STUDY = std_moveoutlier(STUDY, ALLEEG, cls(old_clus), comp_ind - 1);
clus_name_list = get(findobj('parent', hdl, 'tag', 'clus_list'), 'String');
outlier_clust = std_findoutlierclust(STUDY,cls(old_clus)); %find the outlier cluster for this cluster
oind = find(cls == outlier_clust); % the outlier clust index (if already exist) in the cluster list GUI
if ~isempty(oind) % the outlier clust is already presented in the cluster list GUI
newname = [STUDY.cluster(outlier_clust).name ' (' num2str(length(STUDY.cluster(outlier_clust).comps)) ' ICs)'];
clus_name_list{oind+1} = renameclust( clus_name_list{oind+1}, newname);
elseif outlier_clust == length(STUDY.cluster) % update the list with the Outlier cluster (if didn't exist before)
clus_name_list{end+1} = [STUDY.cluster(outlier_clust).name ' (' num2str(length(STUDY.cluster(outlier_clust).comps)) ' ICs)'];
userdat{2} = userdat{2} + 1; % update N, number of clusters in edit window
cls(end +1) = length(STUDY.cluster); % update the GUI clusters list with the outlier cluster
userdat{1}{3} = cls; % update cls, the cluster indices in edit window
end
newname = [STUDY.cluster(cls(old_clus)).name ' (' num2str(length(STUDY.cluster(cls(old_clus)).comps)) ' ICs)'];
clus_name_list{old_clus+1} = renameclust(clus_name_list{old_clus+1}, newname);
set(findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_name_list);
% update Study history
a = ['STUDY = std_moveoutlier(STUDY, ALLEEG, ' num2str(cls(old_clus)) ', [' num2str(comp_ind - 1) ']);'];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
STUDY.cache = [];
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
pop_clustedit('showclust',hdl);
end
case 'rejectoutliers'
STUDY.saved = 'no';
clus = get(findobj('parent', hdl, 'tag', 'clus_list'), 'Value') -1;
if clus
std_name = STUDY.cluster(cls(clus)).name;
% Cannot reject outliers from 'Notclust', 'ParentCluster' and 'Outlier' clusters
if strncmpi('Notclust',std_name,8) || strncmpi('ParentCluster', std_name,13) || ...
strncmpi('Outliers',std_name,8)
warndlg2('Cannot reject outliers of ''Notclust'' or ''Outliers'' or ''ParentCluster'' clusters.');
return;
end
clusters = cls(clus);
else
std_name = 'All clusters';
clusters = [];
for k = 1:length(cls)
if ~strncmpi('Notclust',STUDY.cluster(cls(k)).name,8) && ~strncmpi('Outliers',STUDY.cluster(cls(k)).name,8) && ...
~strncmpi('ParentCluster',STUDY.cluster(cls(k)).name,13)
clusters = [ clusters cls(k)];
end
end
end
reject_param = inputgui( { [1] [1] [4 1 2] [1]}, ...
{ {'style' 'text' 'string' ['Reject "' std_name '" outliers ' ] 'FontWeight' 'Bold'} {} ...
{'style' 'text' 'string' 'Move outlier components that are more than'} {'style' 'edit' 'string' '3' 'tag' 'outliers_std' } ...
{'style' 'text' 'string' 'standard deviations' } ...
{'style' 'text' 'string' [ 'from the "' std_name '" centroid to an outlier cluster.']} }, ...
'', 'Reject outliers - from pop_clustedit()' );
if ~isempty(reject_param) %if not canceled
ostd = reject_param{1}; % the requested outlier std
[STUDY] = std_rejectoutliers(STUDY, ALLEEG, clusters, str2num(ostd));
% update Study history
a = ['STUDY = std_rejectoutliers(STUDY, ALLEEG, [ ' num2str(clusters) ' ], ' ostd ');'];
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
clus_name_list = get(findobj('parent', hdl, 'tag', 'clus_list'), 'String');
for k = 1:length(clusters)
outlier_clust = std_findoutlierclust(STUDY,clusters(k)); %find the outlier cluster for this cluster
oind = find(cls == outlier_clust); % the outlier clust index (if already exist) in the cluster list GUI
if ~isempty(oind) % the outlier clust is already presented in the cluster list GUI
newname = [STUDY.cluster(outlier_clust).name ' (' num2str(length(STUDY.cluster(outlier_clust).comps)) ' ICs)'];
clus_name_list{oind+1} = renameclust( clus_name_list{oind+1}, newname);
else % update the list with the outlier cluster
clus_name_list{end+1} = [STUDY.cluster(outlier_clust).name ' (' num2str(length(STUDY.cluster(outlier_clust).comps)) ' ICs)'];
userdat{2} = userdat{2} + 1; % update N, number of clusters in edit window
cls(end +1) = outlier_clust; % update the GUI clusters list with the outlier cluster
userdat{1}{3} = cls; % update cls, the cluster indices in edit window
end
clsind = find(cls == clusters(k));
newname = [STUDY.cluster(clusters(k)).name ' (' num2str(length(STUDY.cluster(clusters(k)).comps)) ' ICs)'];
clus_name_list{clsind+1} = renameclust( clus_name_list{clsind+1}, newname);
set(findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_name_list);
end
% If outlier cluster doesn't exist in the GUI window add it
STUDY.cache = [];
userdat{1}{2} = STUDY;
set(hdl, 'userdat',userdat);
pop_clustedit('showclust',hdl);
end
case 'createclust'
STUDY.saved = 'no';
create_param = inputgui( { [1] [1 1] [1]}, ...
{ {'style' 'text' 'string' 'Create new empty cluster' 'FontWeight' 'Bold'} ...
{'style' 'text' 'string' 'Enter cluster name:'} {'style' 'edit' 'string' '' } {} }, ...
'', 'Create new empty cluster - from pop_clustedit()' );
if ~isempty(create_param) %if not canceled
clus_name = create_param{1}; % the name of the new cluster
[STUDY] = std_createclust(STUDY, ALLEEG, 'name', clus_name);
% Update cluster list
clus_name_list = get(findobj('parent', hdl, 'tag', 'clus_list'), 'String');
clus_name_list{end+1} = [STUDY.cluster(end).name ' (0 ICs)']; %update the cluster list with the new cluster
% update the first option on the GUI list : 'All 10 cluster centroids'
% with the new number of cluster centroids
ti = strfind(clus_name_list{1},'cluster'); %get the number of clusters centroid
cent = num2str(str2num(clus_name_list{1}(5:ti-2))+1); % new number of centroids
clus_name_list{1} = [clus_name_list{1}(1:4) cent clus_name_list{1}(ti-1:end)]; %update list
set(findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_name_list);
% update Study history
if isempty(clus_name)
a = ['STUDY = std_createclust(STUDY, ALLEEG);'];
else
a = ['STUDY = std_createclust(STUDY, ALLEEG, ''name'', ' clus_name ');'];
end
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
STUDY.cache = [];
userdat{1}{2} = STUDY;
userdat{2} = userdat{2} + 1; % update N, the number of cluster options in edit window
cls(end +1) = length(STUDY.cluster); % update the GUI clusters list with the new cluster
userdat{1}{3} = cls; % update cls, the cluster indices in edit window
set(hdl, 'userdat',userdat); %update STUDY, cls and N
end
case 'mergeclusters'
STUDY.saved = 'no';
clus_names = get(findobj('parent', hdl, 'tag', 'clus_list'), 'string') ;
optionalcls =[];
for k = 2:length(clus_names)
if (~strncmpi('Notclust',clus_names{k},8)) && (~strncmpi('Outliers',clus_names{k},8)) && ...
(~strncmpi('ParentCluster',clus_names{k},13))
optionalcls = [optionalcls k];
end
end
reassign_param = inputgui( { [1] [1] [1] [2 1] [1]}, ...
{ {'style' 'text' 'string' 'Select clusters to Merge' 'FontWeight' 'Bold'} ...
{'style' 'listbox' 'string' clus_names(optionalcls) 'tag' 'new_clus' 'max' 3 'min' 1} {} ...
{'style' 'text' 'string' 'Optional, enter a name for the merged cluster:' 'FontWeight' 'Bold'} ...
{'style' 'edit' 'string' ''} {} }, ...
'', 'Merge clusters - from pop_clustedit()' ,[] , 'normal', [1 3 1 1 1] );
if ~isempty(reassign_param)
std_mrg = cls(optionalcls(reassign_param{1})-1);
name = reassign_param{2};
allleaves = 1;
N = userdat{2};
for k = 1: N %check if all leaves
if ~isempty(STUDY.cluster(cls(k)).child)
allleaves = 0;
end
end
[STUDY] = std_mergeclust(STUDY, ALLEEG, std_mrg, name);
%
% update Study history
%
if isempty(name)
a = ['STUDY = std_mergeclust(STUDY, ALLEEG, [' num2str(std_mrg) ']);'];
else
a = ['STUDY = std_mergeclust(STUDY, ALLEEG, [' num2str(std_mrg) '], ' name ');'];
end
STUDY.tmphist = sprintf('%s\n%s', STUDY.tmphist, a);
STUDY.cache = [];
userdat{1}{2} = STUDY;
%
% Replace the merged clusters with the one new merged cluster
% in the GUI if all clusters are leaves
%
if allleaves
%
% Update cluster list
%
clus_names{end+1} = [STUDY.cluster(end).name ' (' num2str(length(STUDY.cluster(end).comps)) ' ICs)'];
%
% update the cluster list with the new cluster
%
clus_names([optionalcls(reassign_param{1})]) = [];
cls = setdiff_bc(cls, std_mrg); % remove from the GUI clusters list the merged clusters
cls(end+1) = length(STUDY.cluster); % update the GUI clusters list with the new cluster
N = length(cls);
%
% update the first option on the GUI list : 'All 10 cluster centroids'
% with the new number of cluster centroids
%
ti = strfind(clus_names{1},'cluster'); %get the number of clusters centroid
cent = num2str(str2num(clus_names{1}(5:ti-2))+1- length(std_mrg)); % new number of centroids
clus_names{1} = [clus_names{1}(1:4) cent clus_names{1}(ti-1:end)]; %update list
set(findobj('parent', hdl, 'tag', 'clus_list'), 'String', clus_names);
%
% update Study history
%
userdat{2} = N; % update N, the number of cluster options in edit window
userdat{1}{3} = cls; % update cls, the cluster indices in edit window
end
set(hdl, 'userdat',userdat); %update information (STUDY)
pop_clustedit('showclust',hdl);
end
end
catch
eeglab_error;
end
end
function newname = renameclust(oldname, newname)
tmpname = deblank(oldname(end:-1:1));
strpos = strfind(oldname, tmpname(end:-1:1));
newname = [ oldname(1:strpos-1) newname ];
Datasets
Models
