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sa_plotevent.m
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% sa_plotevent
% by Til Ole Bergmann 2013
% last modified 2017/10/04 by TOB
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% plots data around events from EEG data
%
% pe = plotevent structure
% pe.figurehandle = handle to figure
%
% cfg = [];
% [pe] = sa_inspectsleep(gcfg,data);
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function [pe] = sa_plotevent(varargin)
display('Plotting events...');
switch nargin
case 1
gcfg = varargin{1};
display('Not enough input arguments specified!');
return
case 2
gcfg = varargin{1};
timelock = varargin{2};
nrows = 1;
case 3
gcfg = varargin{1};
timelock = varargin{2};
freq = varargin{3};
nrows = 2;
end
% define channels to be plotted
if strcmp(gcfg.plotchannel,'all')
if strcmp(gcfg.channeltype,'raw'); % select raw channels only
procchannels = {'_bp','_rms'};
goodchan =[];
for i = 1:length(timelock.label)
for j = 1:length(procchannels) % loop over channels postfixes to exclude
k = strfind(timelock.label{i},procchannels{j});
goodchan(i,j) = isempty(k);
end
end
goodchan = logical(prod(goodchan,2));
gcfg.plotchannel = timelock.label(logical(goodchan));
else
gcfg.plotchannel = timelock.label;
end
end
% calculate indices
timelock.sem = sqrt(timelock.var)./sqrt(timelock.dof); % calculate SEM
% define colors
switch gcfg.colorset
case 'allblack'
colortable = zeros(length(timelock.label),3);
case 'mycolor'
for i = 1:length(timelock.label)
switch timelock.label{i}
case 'Cz'
colortable(i,:) = [0 0 1];
case 'HC'
colortable(i,:) = [0 1 0];
case 'HCA'
colortable(i,:) = [0 0.75 0];
case 'HCP'
colortable(i,:) = [0 0.5 0];
case 'RC'
colortable(i,:) = [1 0 0];
% case 'Cz_SO_bp'
% colortable(i,:) = [0 0 0.5];
% case 'HC_SO_bp'
% colortable(i,:) = [0 0.5 0];
otherwise
colortable(i,:) = [0 0 0];
end
end
case 'varycolor'
% colortable = circshift(varycolor(length(gcfg.plotchannel)),2);
colortable = circshift(varycolor(length(timelock.label)),2);
case 'distinguishable_colors'
colortable = distinguishable_colors(length(timelock.label));
case 'nautic'
colortable = zeros(length(gcfg.plotchannel),3);
TL_chanNum = 10; %sum(cell2mat(strfind(gcfg.plotchannel,'TL')));
TR_chanNum = 10; %sum(cell2mat(strfind(gcfg.plotchannel,'TR')));
for i = 1:length(gcfg.plotchannel)
if ~isempty(strfind(gcfg.plotchannel{i},'Cz'))
colortable(i,:) = [0 0 1];
elseif ~isempty(strfind(gcfg.plotchannel{i},'TL'))
k = strfind(gcfg.plotchannel{i},'TL');
chan = str2num(gcfg.plotchannel{i}(k+2:k+3));
colortable(i,:) = [0+(chan/TL_chanNum) 0 0];
elseif ~isempty(strfind(gcfg.plotchannel{i},'TR'))
k = strfind(gcfg.plotchannel{i},'TR');
chan = str2num(gcfg.plotchannel{i}(k+2:k+3));
colortable(i,:) = [0 0+(chan/TR_chanNum) 0];
end
end
case 'parula'
ct = parula;
colortable = ct(1:length(ct)/length(gcfg.plotchannel):end,:);
case 'jet'
ct = jet;
colortable = ct(1:length(ct)/length(gcfg.plotchannel):end,:);
case 'NNS1' % as in Staresina et al., NN 2015, Figure S1
colortable = [0,0,0;...
246,157,169;...
128,29,36;...
191,29,42;...
200,56,149;...
61,25,90;...
30,65,153;...
20,187,172;...
49,179,71;...
253,183,18;...
237,28,33];
colortable = colortable/255;
case 'customcolortable' % custom colortable
colortable = gcfg.colortable;
end % of switch
% !!!Insert to plot some filer related stuff!!!
% keyboard;
% nrows = 3;
% hpfilter = 12;
% freqwin = [80 90];
% timelock_fsample = round(1/mean(diff(timelock.time)));
% freq_fsample = round(1/mean(diff(freq.time)));
% usfactor = timelock_fsample / freq_fsample;
%
% % timelocked average of hf power modulation
% sphandle = subplot(nrows,1,3);
% if exist('freq', 'var')
% pos = get(sphandle,'position');
% pos(3) = pos(3)*0.85;
% set(sphandle, 'position', pos);
% end
% % hold on;
% % linecount = 0;
% % if isfield(gcfg, 'xlim') % reduce dataset to plot
% % HFpow.avg = HFpow.avg(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
% % HFpow.var = HFpow.var(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
% % HFpow.sem = HFpow.sem(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
% % HFpow.dof = HFpow.dof(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
% % HFpow.time = HFpow.time(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2)); % do this last!
% % end
%
% freqindex = freq.freq >= freqwin(1) & freq.freq <= freqwin(2);
% HF = squeeze(mean(freq.powspctrm(1,freqindex,:),2))';
% HF(isnan(HF)) = 0; % replace NaN by 0
% HFus = interp(HF,usfactor); % upsample to fit LF time resolution
% HFhp = ft_preproc_highpassfilter(HFus, double(timelock_fsample ), hpfilter, 3*fix(timelock_fsample /hpfilter)+1, 'fir', 'twopass'); % Mathilde's formula
% plot(HFhp, 'r');
pe.figurehandle = figure;
set(pe.figurehandle,'NumberTitle','off','units','normalized','outerposition',[0 0 1 1]);
% timelocked average
if exist('freq', 'var')
sphandle = subplot(nrows,1,2);
else
sphandle = subplot(nrows,1,1);
end
if exist('freq', 'var')
pos = get(sphandle,'position');
pos(3) = pos(3)*0.955;
set(sphandle, 'position', pos);
end
hold on;
linecount = 0;
if isfield(gcfg, 'xlim') % reduce dataset to plot
timelock.avg = timelock.avg(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
timelock.var = timelock.var(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
timelock.sem = timelock.sem(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
timelock.dof = timelock.dof(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2));
timelock.time = timelock.time(:, timelock.time >= gcfg.xlim(1) & timelock.time <= gcfg.xlim(2)); % do this last!
end
for chan = find(ismember(timelock.label, gcfg.plotchannel))'
linecount = linecount+1;
shadeHandle = fill([timelock.time, fliplr(timelock.time)],[timelock.avg(chan,:)+timelock.sem(chan,:), fliplr(timelock.avg(chan,:)-timelock.sem(chan,:))],colortable(chan,:));
set(shadeHandle,'edgecolor',colortable(chan,:));
alpha(0.25);
lineHandle(linecount) = plot(timelock.time,timelock.avg(chan,:), 'Color', colortable(chan,:), 'LineWidth', 2);
if chan == find(strcmp(gcfg.targetchannel,timelock.label)) % if targetchannel, emphasize with black dashes
lineHandle(linecount) = plot(timelock.time,timelock.avg(chan,:), 'Color', [0 0 0], 'LineWidth', 2, 'LineStyle','--');
end
end
line([timelock.time(1) timelock.time(end)], [0 0], 'Color', 'k', 'LineWidth', 1);
% y = get(gca,'ylim');
% line([0 0], y, 'Color', 'k', 'LineWidth', 1, 'LineStyle','--');
hold off;
if isfield(gcfg,'tl_ylim')
ylim(gcfg.tl_ylim);
end
% legend(lineHandle,timelock.label,'Location','NorthOutside','Orientation','horizontal','Interpreter','none');
legend(lineHandle,gcfg.plotchannel,'Location','NorthOutside','Orientation','horizontal','Interpreter','none');
title(['Average of ' num2str(max(unique(timelock.dof))) ' observations']);
% averaged TFR
if exist('freq', 'var')
subplot(nrows,1,1);
cfg = [];
cfg.channel = gcfg.plotTFRchannel;
if isfield(gcfg, 'baseline')
cfg.baseline = gcfg.baseline;
else
cfg.baseline = 'yes';
end
if isfield(gcfg, 'baselinetype')
cfg.baselinetype = gcfg.baselinetype;
else
cfg.baselinetype = 'relative';
end
if isfield(gcfg, 'zlim')
cfg.zlim = gcfg.zlim;
else
cfg.zlim = 'maxabs';
end
if isfield(gcfg, 'ylim')
cfg.ylim = gcfg.ylim;
end
if isfield(gcfg, 'xlim')
cfg.xlim = gcfg.xlim;
end
ft_singleplotTFR(cfg, freq);
end
pe.cfg = gcfg;
end % of function