% POP_PROP - plot the properties of a channel or of an independent

% component.

% Usage:

% >> pop_prop( EEG); % pops up a query window

% >> pop_prop( EEG, typecomp); % pops up a query window

% >> pop_prop( EEG, typecomp, chanorcomp, winhandle,spectopo_options);

%

% Inputs:

% EEG - EEGLAB dataset structure (see EEGGLOBAL)

%

% Optional inputs:

% typecomp - [0|1] 1 -> display channel properties

% 0 -> component properties {default: 1 = channel}

% chanorcomp - channel or component number[s] to display {default: 1}

%

% winhandle - if this parameter is present or non-NaN, buttons

% allowing the rejection of the component are drawn.

% If non-zero, this parameter is used to back-propagate

% the color of the rejection button.

% spectopo_options - [cell array] optional cell array of options for

% the SPECTOPO function.

% For example { 'freqrange' [2 50] }

%

% Note: Type "set(gcf, ''renderer'', ''painter'')" before saving the figure

% in postscript (epsc) or jpg format

%

% Author: Arnaud Delorme, CNL / Salk Institute, 2001

%

% See also: POP_RUNICA, EEGLAB

% Copyright (C) 2001 Arnaud Delorme, Salk Institute, arno@salk.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.

% hidden parameter winhandle

% 01-25-02 reformated help & license -ad

% 02-17-02 removed event index option -ad

% 03-17-02 debugging -ad & sm

% 03-18-02 text settings -ad & sm

% 03-18-02 added title -ad & sm

function com = pop_prop(EEG, typecomp, chanorcomp, winhandle, spec_opt)

com = '';

if nargin < 1

help pop_prop;

return;

end

if nargin < 5

spec_opt = {};

end

if nargin == 1

typecomp = 1; % defaults

chanorcomp = 1;

end

if typecomp == 0 && isempty(EEG.icaweights)

error('No ICA weights recorded for this dataset -- first run ICA on it');

end

chanoristr = '';

if nargin == 2

commandchan = 'tmpchanlocs = EEG(1).chanlocs; [tmp tmpval] = pop_chansel({tmpchanlocs.labels}, ''withindex'', ''on'', ''selectionmode'', ''single''); set(findobj(gcbf, ''tag'', ''chan''), ''string'',tmpval); clear tmp tmpchanlocs tmpval';

uitext = { { 'style' 'text' 'string' fastif(typecomp,'Channel index(ices) to plot:','Component index(ices) to plot:') } ...

{ 'style' 'edit' 'string' '1', 'tag', 'chan' } ...

{ 'style' 'pushbutton' 'string' '...', 'enable' fastif(~isempty(EEG(1).chanlocs) && typecomp, 'on', 'off') 'callback' commandchan } ...

{ 'style' 'text' 'string' 'Spectral options (see spectopo() help):' } ...

{ 'style' 'edit' 'string' '''freqrange'', [2 50]' } {} };

uigeom = { [2 1 0.5 ] [2 1 0.5] };

result = inputgui('geometry', uigeom, 'uilist', uitext, 'helpcom', 'pophelp(''pop_prop'');', ...

'title', fastif( typecomp, 'Channel properties - pop_prop()', 'Component properties - pop_prop()'));

if size(result, 1) == 0

return;

end

chanoristr = result{1};

chanorcomp = eeg_decodechan(EEG.chanlocs, result{1} );

spec_opt = eval( [ '{' result{2} '}' ] );

end

if ischar(chanorcomp)

chanoristr = chanorcomp;

chanorcomp = eeg_decodechan(EEG.chanlocs, chanorcomp );

elseif isempty(chanoristr)

chanoristr = int2str(chanorcomp);

end

% plotting several component properties

% -------------------------------------

if length(chanorcomp) > 1

for index = chanorcomp

pop_prop(EEG, typecomp, index, 0, spec_opt); % call recursively for each chanorcomp

end

com = sprintf('pop_prop( EEG, %d, [%s], NaN, %s);',...

typecomp, int2str(chanorcomp), vararg2str( { spec_opt } ));

return;

end

% should test for > number of components ??? -sm.

% yes (max num components is not necessarily same as nbchan). -jri

if typecomp == 1

maxChanorcomp = EEG.nbchan;

else

maxChanorcomp = size(EEG.icaweights, 1);

end

if chanorcomp < 1 || chanorcomp > maxChanorcomp

error('Component index out of range');

end

% assumed input is chanorcomp

% -------------------------

try

icadefs;

catch

BACKCOLOR = [0.8 0.8 0.8];

GUIBUTTONCOLOR = [0.8 0.8 0.8];

end

basename = [fastif(typecomp,'Channel ', 'Component ') chanoristr ];

fhandle = figure('name', ['pop_prop() - ' basename ' properties'], 'color', BACKCOLOR, 'numbertitle', 'off', 'visible', 'off');

pos = get(fhandle,'Position');

set(fhandle,'Position', [pos(1) pos(2)-500+pos(4) 500 500], 'visible', 'on');

hh = axes('parent',fhandle);

pos = get(hh,'position'); % plot relative to current axes

q = [pos(1) pos(2) 0 0];

s = [pos(3) pos(4) pos(3) pos(4)]./100;

axis(hh,'off');

% plotting topoplot

% -----------------

h = axes('parent',fhandle,'Units','Normalized', 'Position',[-10 60 40 42].*s+q);

%topoplot( EEG.icawinv(:,chanorcomp), EEG.chanlocs); axis square;

if isfield(EEG.chanlocs, 'theta')

if typecomp == 1 % plot single channel locations

topoplot( chanorcomp, EEG.chanlocs, 'chaninfo', EEG.chaninfo, ...

'electrodes','off', 'style', 'blank', 'emarkersize1chan', 12); axis square;

else % plot component map

topoplot( EEG.icawinv(:,chanorcomp), EEG.chanlocs, 'chaninfo', EEG.chaninfo, ...

'shading', 'interp', 'numcontour', 3); axis square;

end

else

axis(h,'off');

end

basename = [fastif(typecomp,'Channel ', 'IC') chanoristr ];

% title([ basename fastif(typecomp, ' location', ' map')], 'fontsize', 14);

title(basename, 'fontsize', 14);

% plotting erpimage

% -----------------

hhh = axes('Parent', fhandle,'Units','Normalized', 'Position',[45 62 48 38].*s+q);

eeglab_options;

if EEG.trials > 1

% put title at top of erpimage

axis(hhh,'off');

hh = axes('Parent', fhandle,'Units','Normalized', 'Position',[45 62 48 38].*s+q);

EEG.times = linspace(EEG.xmin, EEG.xmax, EEG.pnts);

if EEG.trials < 6

ei_smooth = 1;

else

ei_smooth = 3;

end

if typecomp == 1 % plot channel

offset = nan_mean(EEG.data(chanorcomp,:));

erp=nan_mean(squeeze(EEG.data(chanorcomp,:,:))')-offset;

erp_limits=get_era_limits(erp);

erpimage( EEG.data(chanorcomp,:)-offset, ones(1,EEG.trials)*10000, EEG.times*1000, ...

'', ei_smooth, 1, 'caxis', 2/3, 'cbar','erp','erp_vltg_ticks',erp_limits);

else % plot component

icaacttmp = eeg_getdatact(EEG, 'component', chanorcomp);

offset = nan_mean(icaacttmp(:));

era = nan_mean(squeeze(icaacttmp)')-offset;

era_limits = get_era_limits(era);

erpimage( icaacttmp-offset, ones(1,EEG.trials)*10000, EEG.times*1000, ...

'', ei_smooth, 1, 'caxis', 2/3, 'cbar','erp', 'yerplabel', '','erp_vltg_ticks',era_limits);

end

axes(hhh);

title(sprintf('%s activity \\fontsize{10}(global offset %3.3f)', basename, offset), 'fontsize', 14);

else

% put title at top of erpimage

EI_TITLE = 'Continous data';

axis(hhh,'off');

hh = axes('Parent', fhandle,'Units','Normalized', 'Position',[45 62 48 38].*s+q);

ERPIMAGELINES = 200; % show 200-line erpimage

while size(EEG.data,2) < ERPIMAGELINES*EEG.srate

ERPIMAGELINES = 0.9 * ERPIMAGELINES;

end

ERPIMAGELINES = round(ERPIMAGELINES);

if ERPIMAGELINES > 2 % give up if data too small

if ERPIMAGELINES < 10

ei_smooth = 1;

else

ei_smooth = 3;

end

erpimageframes = floor(size(EEG.data,2)/ERPIMAGELINES);

erpimageframestot = erpimageframes*ERPIMAGELINES;

eegtimes = linspace(0, erpimageframes-1, length(erpimageframes)); % 05/27/2014 Ramon: length(erpimageframes) by EEG.srate/1000 in eegtimes = linspace(0, erpimageframes-1, EEG.srate/1000);

if typecomp == 1 % plot channel

offset = nan_mean(EEG.data(chanorcomp,:));

% Note: we don't need to worry about ERP limits, since ERPs

% aren't visualized for continuous data

erpimage( reshape(EEG.data(chanorcomp,1:erpimageframestot),erpimageframes,ERPIMAGELINES)-offset, ones(1,ERPIMAGELINES)*10000, eegtimes , ...

EI_TITLE, ei_smooth, 1, 'caxis', 2/3, 'cbar');

else % plot component

icaacttmp = eeg_getdatact(EEG, 'component', chanorcomp);

offset = nan_mean(icaacttmp(:));

erpimage(reshape(icaacttmp(:,1:erpimageframestot),erpimageframes,ERPIMAGELINES)-offset,ones(1,ERPIMAGELINES)*10000, eegtimes , ...

EI_TITLE, ei_smooth, 1, 'caxis', 2/3, 'cbar','yerplabel', '');

end

else

axis(hh,'off');

text(0.1, 0.3, [ 'No erpimage plotted' 10 'for small continuous data']);

end

axes(hhh);

end

% plotting spectrum

% -----------------

if ~exist('winhandle')

winhandle = NaN;

end

if ishandle(winhandle)

h = axes('Parent', fhandle,'units','normalized', 'position',[5 10 95 35].*s+q);

else

h = axes('Parent', fhandle,'units','normalized', 'position',[5 0 95 40].*s+q);

end

%h = axes('units','normalized', 'position',[45 5 60 40].*s+q);

try

eeglab_options;

if typecomp == 1

[spectra, freqs] = spectopo( EEG.data(chanorcomp,:), EEG.pnts, EEG.srate, spec_opt{:} );

else

if option_computeica

[spectra, freqs] = spectopo( EEG.icaact(chanorcomp,:), EEG.pnts, EEG.srate, 'mapnorm', EEG.icawinv(:,chanorcomp), spec_opt{:} );

else

icaacttmp = (EEG.icaweights(chanorcomp,:)*EEG.icasphere)*reshape(EEG.data(EEG.icachansind,:,:), length(EEG.icachansind), EEG.trials*EEG.pnts);

[spectra, freqs] = spectopo( icaacttmp, EEG.pnts, EEG.srate, 'mapnorm', EEG.icawinv(:,chanorcomp), spec_opt{:} );

end

end

% set up new limits

% -----------------

%freqslim = 50;

%set(gca, 'xlim', [0 min(freqslim, EEG.srate/2)]);

%spectra = spectra(find(freqs <= freqslim));

%set(gca, 'ylim', [min(spectra) max(spectra)]);

%tmpy = get(gca, 'ylim');

%set(gca, 'ylim', [max(tmpy(1),-1) tmpy(2)]);

set( get(h, 'ylabel'), 'string', 'Power 10*log_{10}(\muV^{2}/Hz)', 'fontsize', 14);

set( get(h, 'xlabel'), 'string', 'Frequency (Hz)', 'fontsize', 14);

title('Activity power spectrum', 'fontsize', 14);

catch err

axis off;

text(0.1, 0.3, [ 'Error: no spectrum plotted' 10 err.message 10]);

% lasterror

% text(0.1, 0.3, [ 'Error: no spectrum plotted' 10 ' make sure you have the ' 10 'signal processing toolbox']);

end

% display buttons

% ---------------

if ishandle(winhandle)

COLREJ = '[1 0.6 0.6]';

COLACC = '[0.75 1 0.75]';

% CANCEL button

% -------------

h = uicontrol(fhandle, 'Style', 'pushbutton', 'backgroundcolor', GUIBUTTONCOLOR, 'string', 'Cancel', 'Units','Normalized','Position',[-10 -10 15 6].*s+q, 'callback', 'close(gcf);');

% VALUE button

% -------------

hval = uicontrol(fhandle, 'Style', 'pushbutton', 'backgroundcolor', GUIBUTTONCOLOR, 'string', 'Values', 'Units','Normalized', 'Position', [15 -10 15 6].*s+q);

% REJECT button

% -------------

if ~isempty(EEG.reject.gcompreject)

status = EEG.reject.gcompreject(chanorcomp);

else

status = 0;

end

hr = uicontrol(fhandle, 'Style', 'pushbutton', 'backgroundcolor', eval(fastif(status,COLREJ,COLACC)), ...

'string', fastif(status, 'REJECT', 'ACCEPT'), 'Units','Normalized', 'Position', [40 -10 15 6].*s+q, 'userdata', status, 'tag', 'rejstatus');

command = [ 'set(gcbo, ''userdata'', ~get(gcbo, ''userdata''));' ...

'if get(gcbo, ''userdata''),' ...

' set( gcbo, ''backgroundcolor'',' COLREJ ', ''string'', ''REJECT'');' ...

'else ' ...

' set( gcbo, ''backgroundcolor'',' COLACC ', ''string'', ''ACCEPT'');' ...

'end;' ];

set(hr, 'callback', command);

% HELP button

% -------------

h = uicontrol(fhandle, 'Style', 'pushbutton', 'backgroundcolor', GUIBUTTONCOLOR, 'string', 'HELP', 'Units','Normalized', 'Position', [65 -10 15 6].*s+q, 'callback', 'pophelp(''pop_prop'');');

% OK button

% ---------

command = [ 'global EEG;' ...

'tmpstatus = get( findobj(''parent'', gcbf, ''tag'', ''rejstatus''), ''userdata'');' ...

'EEG.reject.gcompreject(' num2str(chanorcomp) ') = tmpstatus;' ];

if winhandle ~= 0

if VERS < 8.04

command = [ command ...

sprintf('if tmpstatus set(%3.15f, ''backgroundcolor'', %s); else set(%3.15f, ''backgroundcolor'', %s); end;', ...

winhandle, COLREJ, winhandle, COLACC)];

elseif VERS >= 8.04

command = [ command ...

sprintf('if tmpstatus set(findobj(''Tag'', ''%s''), ''backgroundcolor'', %s); else set(findobj(''Tag'',''%s''), ''backgroundcolor'', %s); end;', ...

winhandle.Tag, COLREJ, winhandle.Tag, COLACC)];

end

end

command = [ command 'close(gcf); clear tmpstatus' ];

h = uicontrol(fhandle, 'Style', 'pushbutton', 'string', 'OK', 'backgroundcolor', GUIBUTTONCOLOR, 'Units','Normalized', 'Position',[90 -10 15 6].*s+q, 'callback', command);

% draw the figure for statistical values

% --------------------------------------

index = num2str( chanorcomp );

command = [ ...

'figure(''MenuBar'', ''none'', ''name'', ''Statistics of the component'', ''numbertitle'', ''off'');' ...

'' ...

'pos = get(gcf,''Position'');' ...

'set(gcf,''Position'', [pos(1) pos(2) 340 340]);' ...

'pos = get(gca,''position'');' ...

'q = [pos(1) pos(2) 0 0];' ...

's = [pos(3) pos(4) pos(3) pos(4)]./100;' ...

'axis off;' ...

'' ...

'txt1 = sprintf(''(\n' ...

'Entropy of component activity\t\t%2.2f\n' ...

'> Rejection threshold \t\t%2.2f\n\n' ...

' AND \t\t\t----\n\n' ...

'Kurtosis of component activity\t\t%2.2f\n' ...

'> Rejection threshold \t\t%2.2f\n\n' ...

') OR \t\t\t----\n\n' ...

'Kurtosis distribution \t\t\t%2.2f\n' ...

'> Rejection threshold\t\t\t%2.2f\n\n' ...

'\n' ...

'Current thresholds sujest to %s the component\n\n' ...

'(after manually accepting/rejecting the component, you may recalibrate thresholds for future automatic rejection on other datasets)'',' ...

'EEG.stats.compenta(' index '), EEG.reject.threshentropy, EEG.stats.compkurta(' index '), ' ...

'EEG.reject.threshkurtact, EEG.stats.compkurtdist(' index '), EEG.reject.threshkurtdist, fastif(EEG.reject.gcompreject(' index '), ''REJECT'', ''ACCEPT''));' ...

'' ...

'uicontrol(gcf, ''Units'',''Normalized'', ''Position'',[-11 4 117 100].*s+q, ''Style'', ''frame'' );' ...

'uicontrol(gcf, ''Units'',''Normalized'', ''Position'',[-5 5 100 95].*s+q, ''String'', txt1, ''Style'',''text'', ''HorizontalAlignment'', ''left'' );' ...

'h = uicontrol(gcf, ''Style'', ''pushbutton'', ''string'', ''Close'', ''Units'',''Normalized'', ''Position'', [35 -10 25 10].*s+q, ''callback'', ''close(gcf);'');' ...

'clear txt1 q s h pos;' ];

set( hval, 'callback', command);

if isempty( EEG.stats.compenta )

set(hval, 'enable', 'off');

end

com = sprintf('pop_prop( EEG, %d, %d, 0, %s);', typecomp, chanorcomp, vararg2str( { spec_opt } ) );

else

com = sprintf('pop_prop( EEG, %d, %d, NaN, %s);', typecomp, chanorcomp, vararg2str( { spec_opt } ) );

end

disp('Note: Type "set(gcf, ''renderer'', ''painter'')" before saving the figure in postscript (epsc) or jpg format');

return;

function out = nan_mean(in)

nans = find(isnan(in));

in(nans) = 0;

sums = sum(in);

nonnans = ones(size(in));

nonnans(nans) = 0;

nonnans = sum(nonnans);

nononnans = find(nonnans==0);

nonnans(nononnans) = 1;

out = sum(in)./nonnans;

out(nononnans) = NaN;

function era_limits=get_era_limits(era)

%function era_limits=get_era_limits(era)

%

% Returns the minimum and maximum value of an event-related

% activation/potential waveform (after rounding according to the order of

% magnitude of the ERA/ERP)

%

% Inputs:

% era - [vector] Event related activation or potential

%

% Output:

% era_limits - [min max] minimum and maximum value of an event-related

% activation/potential waveform (after rounding according to the order of

% magnitude of the ERA/ERP)

mn=min(era);

mx=max(era);

mn=orderofmag(mn)*round(mn/orderofmag(mn));

mx=orderofmag(mx)*round(mx/orderofmag(mx));

era_limits=[mn mx];

function ord=orderofmag(val)

%function ord=orderofmag(val)

%

% Returns the order of magnitude of the value of 'val' in multiples of 10

% (e.g., 10^-1, 10^0, 10^1, 10^2, etc ...)

% used for computing erpimage trial axis tick labels as an alternative for

% plotting sorting variable

val=abs(val);

if val>=1

ord=1;

val=floor(val/10);

while val>=1

ord=ord*10;

val=floor(val/10);

end

return;

else

ord=1/10;

val=val*10;

while val<1

ord=ord/10;

val=val*10;

end

return;

end