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2024 update #37

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merged 4 commits into from
Feb 10, 2024
Merged

2024 update #37

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619cd5f
creating a version where the eyetracking is averagerd on a group level
DouweHorsthuis Feb 10, 2024
c822bdb
Minor changes so that they run perfect
DouweHorsthuis Feb 10, 2024
a30ad4f
fix
DouweHorsthuis Feb 10, 2024
35ccdb9
Adding a group dashboard to it
DouweHorsthuis Feb 10, 2024
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20 changes: 10 additions & 10 deletions testing/SWAT/C_manual_check.m
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Original file line number Diff line number Diff line change
Expand Up @@ -5,29 +5,29 @@
Group_list={'cystinosis' 'adult_controls'};
for gr=1:length(Group_list)
if strcmpi(Group_list{gr},'adult_controls')
subject_list = {'12091' '12709' '12883'};
subject_list = {'12091' '12709' '12883'};
elseif strcmpi(Group_list{gr},'cystinosis')
subject_list = {'9109' '9182' '9182'};
else
subject_list = {'9109' '9182' '9182'};
else
disp('not possible')
pause()
end
home_path = 'C:\Users\douwe\Desktop\processed\'; %place data is (something like 'C:\data\')
home_path = 'C:\Users\douwe\Desktop\processed\'; %place data is (something like 'C:\data\')
%need to add the folder with the functions
file_loc=[fileparts(matlab.desktop.editor.getActiveFilename),filesep];
addpath(genpath(file_loc));%adding path to your scripts so that the functions are found

for s=1:length(subject_list)
if s==1
group_del_channel=[]; %needed for the plot_group_deleted_chan_location function
if s==1
group_del_channel=[]; %needed for the plot_group_deleted_chan_location function
end
clear bad_chan;
fprintf('\n******\nProcessing subject %s\n******\n\n', subject_list{s});
data_path = [home_path subject_list{s} '\'];
EEG = pop_loadset('filename', [subject_list{s} '_exchn.set'], 'filepath', data_path);
pop_eegplot( EEG, 1, 1, 1);
prompt = 'Delete channels? If yes, input them all as strings inside {}. If none hit enter ';
bad_chan = input(prompt); %
%% bad_chan = input(prompt); %
if isempty(bad_chan) ~=1
EEG = pop_select( EEG, 'nochannel',bad_chan);
EEG = pop_saveset( EEG, 'filename',[subject_list{s} '_exchn.set'],'filepath', data_path);
Expand All @@ -36,9 +36,9 @@

%% creating figures with deleted and bridged channels
EEG=plot_deleted_chan_location(EEG,data_path); %plotting the location of deleted chan
% plotting a topoplot with how many channels get for everyone
% [EEG, group_del_channel]=plot_group_deleted_chan_location(EEG,group_del_channel,home_path,Group_list{gr},length(subject_list));
plotting a topoplot with how many channels get for everyone
[EEG, group_del_channel]=plot_group_deleted_chan_location(EEG,group_del_channel,home_path,Group_list{gr},length(subject_list));

%% group quality info, ID / % deleted data / seconds of data left / N - deleted channels
quality(s,:)=[str2double(subject_list{s}), str2double(Group_list{gr}) EEG.deleteddata_wboundries,round(EEG.xmax), length(EEG.del_chan)];
end
Expand Down
203 changes: 203 additions & 0 deletions testing/SWAT/F_building_dashboard_group.m
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Original file line number Diff line number Diff line change
@@ -0,0 +1,203 @@
clear all
home_path = 'C:\Users\douwe\Desktop\processed\'; %place data is (something like 'C:\data\')
Group_list={'adult_controls'};
%if the Eye tracking (ET) files were not saved as PGN add here the path to
%the edf files:
edf_path = 'C:\Users\douwe\Desktop\DATA\' ;
task_name = 'SWAT';
for gr=1:length(Group_list)
if strcmpi(Group_list{gr},'cystinosis' )
subject_list = { '9182' '9182' '9109'};
elseif strcmpi(Group_list{gr},'adult_controls')
subject_list = {'12709' '12091' '12883'};
elseif strcmpi(Group_list{gr},'grn')
subject_list = {'id_1' 'id_2'};
else
disp('not possible')
pause()
end
channels_names={'Fcz' 'Fc4' 'Fc3'}; %channels that you want ERP plots for
plotting_bins=[1:3]; %numbers of the bins you want to plot if
colors={'b-' 'm-' 'g-' };%'k-' 'r-'
epoch_time = [-50 500];
load([home_path 'participant_info_' Group_list{gr}]);
participant_info_full=participant_info;
for s=1:length(subject_list)
for i=1:height(participant_info_full)
if strcmpi(participant_info_full.('ID')(i),subject_list{s})
badchan= participant_info_full.('Deleted channels')(i);
Hit_green= participant_info_full.('hit green ')(i);
Hit_red= participant_info_full.('hit red ')(i);
Hit_all= participant_info_full.('All Hits')(i);

end
end
data_path = [home_path subject_list{s} '/'];
EEG = pop_loadset('filename', [subject_list{s} '_excom.set'], 'filepath', data_path);
%figures to png
h1= openfig([data_path subject_list{s} '_deleted_channels.fig']);
print([data_path subject_list{s} '_deleted_channels.png'], '-dpng' ,'-r300');
h2= openfig([data_path subject_list{s} '_bridged_channels.fig']);
print([data_path subject_list{s} '_bridged_channels.png'], '-dpng' ,'-r300');
%creating erps
ERP = pop_loaderp( 'filename', [subject_list{s} '.erp'], 'filepath', data_path );

channels=zeros(1,length(channels_names));
for i = 1:length(channels_names)
for ii=1:length(ERP.chanlocs)
if strcmpi(channels_names(i), ERP.chanlocs(ii).labels)
channels(i)=ii;
end
end
end
for i=1:length(channels_names)
figure();
for ii=1:length(plotting_bins)
plot(ERP.times,ERP.bindata(plotting_bins(i),:,plotting_bins(ii))) %plotting_bins(channel),time,bin
hold on
%row=bins columns=channels inside those each row=1subject
end
legend(ERP.bindescr{plotting_bins(1)}, ERP.bindescr{plotting_bins(2)} , ERP.bindescr{plotting_bins(3)}) %if you want to plot more/less channels change this
title(channels_names(i))
xlim(epoch_time);
print([data_path subject_list{s} '_' strtrim(ERP.bindescr{i}) '_erp'], '-dpng' ,'-r300');
close all
end
%if the ET file was saved as a PGN then don't run this part
edf_path_ind=[edf_path subject_list{s} '\'];
edf_to_figure(edf_path_ind);
saveas(gcf,[edf_path_ind subject_list{s} '_ET'])
print([data_path subject_list{s} '_ET' ], '-dpng' ,'-r300');
close all

fig=figure('units','normalized','outerposition',[0 0 1 1]);
set(gcf,'color',[0.85 0.85 0.85])
%Deleted channels (topoplot if amount is >1)

%ERPS

for i=1:length(plotting_bins)
subplot(5,5,i+10);
imshow([data_path subject_list{s} '_' strtrim(ERP.bindescr{i}) '_erp.png']);
title('ERPs')
end
%information boxes
annotation('textbox', [0.1, 0.825, 0.1, 0.1], 'String', [EEG.date; EEG.age; EEG.sex; EEG.Hand; EEG.glasses; EEG.Exp;EEG.Externals;EEG.Light; EEG.Screen; EEG.Cap;])
annotation('textbox', [0.25, 0.825, 0.1, 0.1], 'String', [EEG.vision_info; EEG.vision; EEG.hearing_info; EEG.hz500; EEG.hz1000; EEG.hz2000; EEG.hz4000]);
annotation('textbox', [0.25, 0.65, 0.1, 0.1], 'String', EEG.Medication);
annotation('textbox', [0.1, 0.6, 0.1, 0.1], 'String', [...
"Lowpass filter: " + EEG.filter.lowpass_filter_hz(1) + "Hz";...
"Highpass filter: " + EEG.filter.highpass_filter_hz(1) + "Hz";...
"Data deleted: " + num2str(EEG.deleteddata_wboundries) + "%";...
"Bad chan: " + badchan;...
"Amount bridged chan: " + string(length(EEG.bridged));...
]);
annotation('textbox', [0.10, 0.345, 0.1, 0.1], 'String',EEG.notes)
annotation('textbox', [0.10, 0.15, 0.1, 0.1], 'String',[...
"N Hit Green trials " + Hit_green...
"N Hit Red trials " + Hit_red...
"N Hit all trials " + Hit_all...
])

%Bridged channels (topoplot if amount is >1)
subplot(10,10,[5:6 15:16 25:26]);
if ~isempty(EEG.bridged)
imshow([data_path subject_list{s} '_bridged_channels.png']);
title('Bridged channels')
else
title('There are NO bridged channels')
end
subplot(10,10,[7:10 17:20 27:30]);
imshow([data_path subject_list{s} '_deleted_channels.png']);
title('Deleted channels')

subplot(10,10,[71:75 81:85 91:95]);
imshow([data_path subject_list{s} '_Bad_ICs_topos.png']);
title('Bad components')

subplot(10,10,[75:76 85:86 95:96]);
imshow([data_path subject_list{s} '_remaining_ICs_topos.png']);
title('Remaining components')

subplot(10,10,[77:80 87:90 97:100]);
imshow([data_path subject_list{s} '_ET.png']);
title('Eye Tracking')


%Final adjustments for the PDF
sgtitle(['Quality of ' subject_list{s} 's data while doing the ' task_name ' task']);
set(gcf, 'PaperSize', [16 10]);
% print(fig,[data_path subject_list{s} '_data_quality'],'-dpdf') % then print it
% print(fig,['D:\cystinosis\Flanker\Quality Check\' subject_list{s} '_data_quality'], '-dpdf');
close all
end %end of subject level
%% Start of group level plotting
%eye tracking at a group level
%input needs to be: edf_path=loctation with the participant folders (their names need to match the subject IDs,
%subject_list = list with all the subject IDs
edf_to_figure_group(edf_path,subject_list);
saveas(gcf,[home_path Group_list{gr} '_ET'])
print([home_path Group_list{gr} '_ET' ], '-dpng' ,'-r300');
close all
%ERP at group level needs to exist for this , this is identical to the
%individual level, but on the group erp
ERP = pop_loaderp( 'filename', [Group_list{gr} '.erp'], 'filepath', home_path );
for i=1:length(channels_names)
figure();
for ii=1:length(plotting_bins)
plot(ERP.times,ERP.bindata(plotting_bins(i),:,plotting_bins(ii))) %plotting_bins(channel),time,bin
hold on
%row=bins columns=channels inside those each row=1subject
end
legend(ERP.bindescr{plotting_bins(1)}, ERP.bindescr{plotting_bins(2)} , ERP.bindescr{plotting_bins(3)}) %if you want to plot more/less channels change this
title(channels_names(i))
xlim(epoch_time);
print([home_path Group_list{gr} '_' strtrim(ERP.bindescr{i}) '_erp'], '-dpng' ,'-r300');
close all
end
%starting the group dashboard
fig=figure('units','normalized','outerposition',[0 0 1 1]);
set(gcf,'color',[0.85 0.85 0.85])
full_group_name = strrep(Group_list{gr},'_',' ');
subplot(10,10,[4:6 14:16 24:26 34:36]);
imshow([home_path Group_list{gr} '_ET.png']);
title('Eye Tracking')
%If you want more than 3 ERPs than you need to change here the size
%of the subplots.
x=[0,3,6];
for i=1:length(plotting_bins)
subplot(10,10,[61+x(i):63+x(i) 71+x(i):73+x(i) 81+x(i):83+x(i) 91+x(i):93+x(i)]);%
imshow([home_path Group_list{gr} '_' strtrim(ERP.bindescr{i}) '_erp.png']);
title('ERPs')
end

subplot(10,10,[7:10 17:20 27:30 37:40]);
imshow([home_path Group_list{gr} '_deleted_channels.png']);
title('Deleted channels')
%looking for some info to write down
main_folder=dir(home_path);
for l=1:length(main_folder)
%looking for the group ERP date
if strcmpi([Group_list{gr} '.erp'],main_folder(l).name)
create_date=['The grand average ' full_group_name '.erp was created on ' main_folder(l).date];
end
end
group_size= ['There are ' num2str(length(ERP.workfiles)) ' participants in this group'];
date_dashboard = ["This group dashboard was created on " + datestr(datetime("today"))];
%Here you can add more info per group
annotation('textbox', [0.1, 0.800, 0.1, 0.1], 'String', [date_dashboard; ...
create_date; ...
group_size;...
"Lowpass filter: " + EEG.filter.lowpass_filter_hz(1) + "Hz";...
"Highpass filter: " + EEG.filter.highpass_filter_hz(1) + "Hz";...
"During the experiment (based on last participant):";...
EEG.Light;...
EEG.Screen])


%Final adjustments for the PDF
sgtitle(['Quality of the ' full_group_name ' group data while doing the ' task_name ' task']);
set(gcf, 'PaperSize', [16 10]);
print(fig,[home_path Group_list{gr} '_data_quality'],'-dpdf') % then print it
print(fig,['D:\cystinosis\Flanker\Quality Check\' Group_list{gr} '_data_quality'], '-dpdf');
end
4 changes: 2 additions & 2 deletions testing/SWAT/G_grandmeans.m
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
clear variables
eeglab
%% Subject info for each script
Group_list={ 'adult_controls' };
Group_list={ 'adult_controls' 'cystinosis' };
for gr=1:length(Group_list)
if strcmpi(Group_list{gr},'cystinosis' )
subject_list = { '9182' '9182' '9109'};
Expand All @@ -28,5 +28,5 @@
ERP = pop_savemyerp(ERP, 'erpname', Group_list{gr},...
'filename', [Group_list{gr} '.erp'], 'filepath', home_path, 'Warning', 'on');
%% plotting grandmean
ERP = pop_ploterps( ERP,1:3,1:64 , 'Axsize', [ 0.05 0.08], 'BinNum', 'on', 'Blc', 'pre', 'Box', [ 8 8], 'ChLabel', 'on', 'FontSizeChan',10, 'FontSizeLeg',12, 'FontSizeTicks',10, 'LegPos', 'bottom', 'Linespec', {'k-' , 'r-' , 'b-' , 'g-' , 'c-' }, 'LineWidth',1, 'Maximize', 'on', 'Position', [ 103.714 28 106.857 31.9412], 'Style', 'Classic', 'Tag', 'ERP_figure', 'Transparency',0, 'xscale', [ -50.0 394.0 -25 0:100:300 ], 'YDir', 'normal', 'yscale', [ -4.0 5 -10:2.5:5 ]);
% ERP = pop_ploterps( ERP,1:3,1:64 , 'Axsize', [ 0.05 0.08], 'BinNum', 'on', 'Blc', 'pre', 'Box', [ 8 8], 'ChLabel', 'on', 'FontSizeChan',10, 'FontSizeLeg',12, 'FontSizeTicks',10, 'LegPos', 'bottom', 'Linespec', {'k-' , 'r-' , 'b-' , 'g-' , 'c-' }, 'LineWidth',1, 'Maximize', 'on', 'Position', [ 103.714 28 106.857 31.9412], 'Style', 'Classic', 'Tag', 'ERP_figure', 'Transparency',0, 'xscale', [ -50.0 394.0 -25 0:100:300 ], 'YDir', 'normal', 'yscale', [ -4.0 5 -10:2.5:5 ]);
end
126 changes: 126 additions & 0 deletions testing/SWAT/functions/edf_to_figure_group.m
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Original file line number Diff line number Diff line change
@@ -0,0 +1,126 @@
function [eyetrHeatMap] = edf_to_figure_group(data_path,id)
%% edf_to_figure is a combination of functions from @EDF2Mat.
% Edf2Mat is created by 'Adrian Etter, Marc Biedermann'
% edf_to_figure is created by Douwe John Horsthuis (2022)
% this is the followup where it combines the eyetracking of a group
% This function generates one figure with the heatmap of the gaze positions of all the data.
% It needs the data_path (where the .EDF files are of each participant)
% It needs the screen ratio of the screen the partiicpant was looking e.g. [16:10]

%% Merge all the data into one file
data_folder = dir(data_path);
obj = struct('Samples', struct('posX', [], 'posY', [])); % Initialize obj
amount = 0;
for s = 1:length(id) %length of all participants
for l=1:length(data_folder) %look at all the IDs in the datafolder dir
if strcmpi(id{s},data_folder(l).name)%if the id of the participant has a folder
data_folder_indv = dir([data_path id{s} '\']); %create a dir to the individual
amount = amount + 1;
for i = 1:length(data_folder_indv)
if endsWith(data_folder_indv(i).name, '.edf')
edf_temp = Edf2Mat([data_path id{s} filesep data_folder_indv(i).name]); % Reading the eye tracking files
obj.Samples.posX = [obj.Samples.posX; edf_temp.Samples.posX]; % Combining all of them
obj.Samples.posY = [obj.Samples.posY; edf_temp.Samples.posY]; % Combining all of them
end
end
end
end
end
exist edf_temp;
if ans == 0
disp('No EDF file, creating empty figure')
figure;

title(['This participant did not have an EDF file']);
xlabel(['This is an empty placeholder']);
elseif ans==1
%% Perform the rest (from Edf2Mat)
startIdx = 1;
endIdx = numel(obj.Samples.posX);
eye = 1;

range = startIdx:endIdx;
if numel(range) <= 0
error('Edf2Mat:plot:range', 'Start Index == End Index, nothing to be plotted');
end

%% Variables
gaussSize = 80;
gaussSigma = 20;

posX = obj.Samples.posX(range, eye);
posY = obj.Samples.posY(range, eye);

%% Generate data for heatmap
gazedata = [posY, posX];


% Set minimum x and y to zero
% for i = 1:size(gazedata, 2)
% gazedata(:, i) = gazedata(:, i) - min(gazedata(:, i));
% end

%finding screen size
for i = 1:length(edf_temp.RawEdf.FEVENT)
if contains(edf_temp.RawEdf.FEVENT(i).codestring, 'MESSAGEEVENT')
if contains(edf_temp.RawEdf.FEVENT(i).message, 'DISPLAY_COORDS')
display_coords= str2num(edf_temp.RawEdf.FEVENT(i).message(end-9:end));
end
end
end
%turning all gazes outsized of screen size to NaN
for i = 1:size(gazedata, 1)
if gazedata(i, 1) < 0 || gazedata(i, 2) < 0
gazedata(i, :) = [NaN, NaN];
elseif gazedata(i, :) > [display_coords(2),display_coords(1)]
gazedata(i, :) = [NaN, NaN];
elseif gazedata(i, 1) > [display_coords(2)]
gazedata(i, :) = [NaN, NaN];
elseif gazedata(i, 2) > [display_coords(1)]
gazedata(i, :) = [NaN, NaN];
end
end
gazedata = gazedata(~isnan(gazedata(:, 1)), :);

gazedata = ceil(gazedata) + 1;
data = accumarray(gazedata, 1, [max(gazedata(:, 1)), max(gazedata(:, 2))]);
data = flipud(data);

%% Smooth the Data
cut = mean(data(:));
data(data > cut) = cut;

size_1 = gaussSize;
sigma = gaussSigma;
[Xm, Ym] = meshgrid(linspace(-.5, .5, size_1));

s = sigma / size_1; % Gaussian width as fraction of imageSize
kernel = exp(-(((Xm.^2) + (Ym.^2)) ./ (2 * s^2))); % Formula for 2D gaussian

eyetrHeatMap = conv2(data, kernel, 'same');

% Map with gaze points on the value of the mean of the heatmap
gaze = mean(eyetrHeatMap(data > 0));
% Calculate percentage of eye tracking time
total_time = numel(range);
eye_tracking_time = sum(~isnan(posX));
eye_tracking_percentage = (eye_tracking_time / total_time) * 100;
if isempty(eyetrHeatMap)
disp('EDF File is empty')
figure;

title(['This participant has no data inside the eyetracking file']);
xlabel(['This is an empty placeholder']);
else
% Create figure
figure;
imagesc(eyetrHeatMap);
%changing range by using the pixel of the screen the subject looked at
plotRange=[0 display_coords(1) 0 display_coords(2)];
axis(plotRange);
colorbar;
title(['Heat map of the eye movement for ' num2str(amount) ' participants out of the ' num2str(length(id))]);
xlabel(['Percentage of Eye Tracking Time: ' num2str(eye_tracking_percentage) '%']);
end
end
end
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