% STD_PLOTCURVE - plot ERP or spectral traces for a STUDY component
% or channel cluster
% Usage:
% >> std_plotcurve( axvals, data, 'key', 'val', ...)
% Inputs:
% axvals - [vector or cell array] axis values for the data.
% data - [cell array] mean data for each subject group and/or data
% condition. For example, to plot mean ERPs from a STUDY
% for epochs of 800 frames in two conditions from three groups
% of 12 subjects:
%
% >> data = { [800x12] [800x12] [800x12];... % 3 groups, cond 1
% [800x12] [800x12] [800x12] }; % 3 groups, cond 2
% >> std_plotcurve(erp_ms,data);
%
% By default, parametric statistics are computed across subjects
% in the three groups. (group,condition) ERP averages are plotted.
% See below and >> help statcond
% for more information about the statistical computations. For
% plotting multiple channels, use the second dimension. For
% example data = { [800x64x12] [800x64x12] } for 12 subjects,
% 64 channels and 800 data points. The 'chanlocs' option must be
% used as well to specify channel positions.
%
% Optional display parameters:
% 'datatype' - ['erp'|'spec'] data type {default: 'erp'}
% 'titles' - [cell array of string] titles for each of the subplots.
% { default: none}
%
% Statistics options:
% 'groupstats' - [cell] One p-value array per group {default: {}}
% 'condstats' - [cell] One p-value array per condition {default: {}}
% 'interstats' - [cell] Interaction p-value arrays {default: {}}
% 'threshold' - [NaN|real<<1] Significance threshold. NaN -> plot the
% p-values themselves on a different figure. When possible,
% significance regions are indicated below the data.
% {default: NaN}
%
% Curve plotting options (ERP and spectrum):
% 'plotgroups' - ['together'|'apart'] 'together' -> plot mean results
% for subject groups in the same figure panel in different
% colors. 'apart' -> plot group results on different figure
% panels {default: 'apart'}
% 'plotconditions' - ['together'|'apart'] 'together' -> plot mean results
% for data conditions on the same figure panel in
% different
% colors. 'apart' -> plot conditions on different figure
% panel. Note: 'plotgroups' and 'plotconditions' arguments
% cannot both be 'together' {default: 'apart'}
% 'legend' - ['on'|'off'] turn plot legend on/off {default: 'off'}
% 'colors' - [cell] cell array of colors
% 'plotdiff' - ['on'|'off'] plot difference between two groups
% or conditions plotted together.
% 'plotstderr' - ['on'|'off'|'diff'|'nocurve'|'diffnocurve'] plots in
% a surface indicating the standard error. 'diff' only
% does it for the difference (requires 'plotdiff' 'on'
% above). 'nocurve' does not plot the mean. This functionality
% does not work for all data configuration {default: 'off'}
% 'figure' - ['on'|'off'] creates a new figure ('on'). The 'off' mode
% plots all of the groups and conditions on the same panel.
% 'plotsubjects' - ['on'|'off'] overplot traces for individual components
% or channels {default: 'off'}
% 'singlesubject' - ['on'|'off'] set to 'on' to plot single subject.
% {default: 'off'}
% 'ylim' - [min max] ordinate limits for ERP and spectrum plots
% {default: all available data}
%
% Scalp map plotting options:
% 'chanlocs' - [struct] channel locations structure
%
% Author: Arnaud Delorme, CERCO, CNRS, 2006-
%
% See also: POP_ERSPPARAMS, POP_ERPPARAMS, POP_SPECPARAMS, STATCOND
% Copyright (C) 2006 Arnaud Delorme
%
% 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 std_plotcurve(allx, data, varargin)
pgroup = [];
pcond = [];
if nargin < 2
help std_plotcurve;
return;
end
opt = finputcheck( varargin, { 'ylim' 'real' [] [];
'filter' 'real' [] [];
'threshold' 'real' [] NaN;
'unitx' 'string' { 'ms','hz','rmsms','rmshz','hzpsd','rmshzpsd' } 'ms';
'chanlocs' 'struct' [] struct('labels', {});
'plotsubjects' 'string' { 'on','off' } 'off';
'condnames' 'cell' [] {};
'groupnames' 'cell' [] {};
'figtag' 'string' [] 'tmp_curvetag';
'groupstats' 'cell' [] {};
'condstats' 'cell' [] {};
'interstats' 'cell' [] {};
'titles' 'cell' [] {};
'colors' 'cell' [] {};
'figure' 'string' { 'on','off' } 'on';
'effect' 'string' { 'main','marginal' } 'marginal';
'plottopo' 'string' { 'on','off' } 'off';
'plotstderr' 'string' { 'on','off','diff','nocurve' } 'off';
'plotdiff' 'string' { 'on','off' } 'off';
'legend' { 'string','cell' } { { 'on','off' } {} } 'off';
'datatype' 'string' { 'ersp','itc','erp','spec' } 'erp';
'plotgroups' 'string' { 'together','apart' } 'apart';
'plotmode', 'string', {'test', 'condensed'}, 'test';
'plotconditions', 'string', {'together', 'apart'}, 'apart'}, 'std_plotcurve');
% opt.figure = 'off'; % test by nima
if ischar(opt), error(opt); end
opt.singlesubject = 'off';
nc = size(data,1);
ng = size(data,2);
if length(opt.chanlocs) > 1, opt.plottopo = 'on'; end
if strcmpi(opt.plottopo, 'on') && size(data{1},3) == 1, opt.singlesubject = 'on'; end
%if size(data{1},2) == 1, opt.singlesubject = 'on'; end
if all(all(cellfun('size', data, 2)==1)), opt.singlesubject = 'on'; end
if any(any(cellfun('size', data, 2)==1)), opt.groupstats = {}; opt.condstats = {}; end
if strcmpi(opt.datatype, 'spec'), opt.unit = 'Hz'; end
if strcmpi(opt.plotsubjects, 'on')
opt.plotgroups = 'apart';
opt.plotconditions = 'apart';
end
if strcmpi(opt.effect, 'main') && nc > 1 && ng > 1 && (~isempty(opt.groupstats) || ~isempty(opt.condstats))
opt.plotgroups = 'apart';
opt.plotconditions = 'apart';
end
if strcmpi(opt.plotconditions, 'together') && ~isempty(opt.groupstats), opt.plotconditions = 'apart'; end
if strcmpi(opt.plotgroups, 'together') && ~isempty(opt.condstats) , opt.plotgroups = 'apart'; end
if ischar(opt.legend), opt.legend = {}; end
if isempty(opt.titles), opt.titles = cell(10,10); opt.titles(:) = { '' }; end
if length(data(:)) == length(opt.legend(:))
opt.legend = reshape(opt.legend, size(data))';
opt.legend(cellfun(@isempty, data)) = [];
opt.legend = (opt.legend)';
end
% color matrix
% -----------------------
onecol = { 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' 'b' };
manycol = { 'b' 'g' 'm' 'c' 'r' 'k' 'y' 'b' 'g' 'c' 'm' 'r' 'b' 'g' 'c' 'm' 'r' 'b' ...
'g' 'c' 'm' 'r' 'b' 'g' 'c' 'm' 'r' 'b' 'g' 'c' 'm' 'r' 'b' 'g' 'c' 'm' };
modifier = { '-' '--' '-.' ':' '-' '--' '-.' ':' '-' '--' '-.' ':' };
if strcmpi(opt.plotgroups, 'together') || strcmpi(opt.plotconditions, 'together') || strcmpi(opt.figure, 'off')
col = manycol;
else col = onecol;
end
if ~isempty(opt.colors), col = opt.colors; end
nonemptycell = find(~cellfun(@isempty, data));
if strcmpi(opt.plotsubjects, 'off')
% both group and conditions s
if strcmpi(opt.plotconditions, 'together') && strcmpi(opt.plotgroups, 'together')
dim1 = max(size(data));
dim2 = min(size(data));
coldata = col([1:dim1]);
for iRow = 2:dim2
coldata(iRow,:) = coldata(1,:);
for iCol = 1:dim1
coldata{iRow,iCol} = [ coldata{iRow,iCol} modifier{iRow} ];
end
end
if size(coldata,1) ~= size(data,1), coldata = coldata'; end
else
coldata = manycol;
end
while length(coldata) < length(data(:))
coldata = [ coldata coldata ];
end
coldata = reshape(coldata(1:length(data(:))), size(data));
else
coldata = cell(size(data));
end
% Fill empty cells with NaNs (This allow to plot all conditions on the same panel even when there is some missing data)
% --------------------------
if strcmpi(opt.plotconditions, 'together') || strcmpi(opt.plotgroups , 'together')
emptyindx = find(cellfun(@isempty,data));
if ~isempty(emptyindx)
for icell = 1:length(emptyindx)
if max(size(data{emptyindx(icell)})) == 0
data{emptyindx(icell)} = nan;
end
end
end
end
% remove empty entries
% --------------------
datapresent = ~cellfun(@isempty, data);
if size(data,1) > 1, for c = size(data,1):-1:1, if sum(datapresent(c,:)) == 0, data(c,:) = []; coldata(c,:) = []; if ~strcmpi(opt.plotconditions, 'together'), opt.titles(c,:) = []; end; if ~isempty(opt.groupstats), opt.groupstats(c) = []; end; end; end; end
if size(data,2) > 1, for g = size(data,2):-1:1, if sum(datapresent(:,g)) == 0, data(:,g) = []; coldata(:,g) = []; if ~strcmpi(opt.plotgroups , 'together'), opt.titles(:,g) = []; end; if ~isempty(opt.condstats ), opt.condstats( g) = []; end; end; end; end
if strcmpi(opt.plotsubjects, 'off'), tmpcol = coldata'; tmpcol = tmpcol(:)'; end
nc = size(data,1);
ng = size(data,2);
% number of columns and rows to plot
% ----------------------------------
if strcmpi(opt.plotgroups, 'together'), ngplot = 1; else ngplot = ng; end
if strcmpi(opt.plotconditions, 'together'), ncplot = 1; else ncplot = nc; end
if nc >= ng, opt.subplot = 'transpose';
else opt.subplot = 'normal';
end
if isempty(opt.condnames)
for c=1:nc, opt.condnames{c} = sprintf('Cond. %d', c); end
if nc == 1, opt.condnames = { '' }; end
end
if isempty(opt.groupnames)
for g=1:ng, opt.groupnames{g} = sprintf('Group. %d', g); end
if ng == 1, opt.groupnames = { '' }; end
end
% plotting parameters
% ------------------
if ng > 1 && ~isempty(opt.groupstats), addc = 1; else addc = 0; end
if nc > 1 && ~isempty(opt.condstats ), addr = 1; else addr = 0; end
if length(opt.threshold) > 1, opt.threshold = opt.threshold(1); end
if strcmpi(opt.singlesubject, 'off') ...
&& ( ~isempty(opt.condstats) || ~isempty(opt.groupstats) ) % only for curves
plottag = 0;
if strcmpi(opt.plotgroups, 'together') && isempty(opt.condstats) && ~isempty(opt.groupstats) && ~isnan(opt.threshold), addc = 0; plottag = 1; end
if strcmpi(opt.plotconditions , 'together') && ~isempty(opt.condstats) && isempty(opt.groupstats) && ~isnan(opt.threshold), addr = 0; plottag = 1; end
if ~isnan(opt.threshold) && plottag == 0 && strcmpi(opt.figure, 'on')
disp('Warning: cannot plot condition/group on the same panel while using a fixed');
disp(' threshold, unless you only compute statistics for ether groups or conditions');
opt.plotgroups = 'apart';
opt.plotconditions = 'apart';
end
end
% resize data to match points x channels x subjects
% or points x 1 x components
% -------------------------------------------------
for index = 1:length(data(:))
if length(opt.chanlocs) ~= size(data{index},2) && (length(opt.chanlocs) == 1 || isempty(opt.chanlocs))
data{index} = reshape(data{index}, [ size(data{index},1) 1 size(data{index},2) ]);
end
end
% compute significance mask
% --------------------------
pinterplot = {};
if strcmpi(opt.effect, 'marginal') || ng == 1 || nc == 1
if ~isnan(opt.threshold) && ( ~isempty(opt.groupstats) || ~isempty(opt.condstats) )
pcondplot = opt.condstats;
pgroupplot = opt.groupstats;
maxplot = 1;
else
for ind = 1:length(opt.condstats), pcondplot{ind} = -log10(opt.condstats{ind}); end
for ind = 1:length(opt.groupstats), pgroupplot{ind} = -log10(opt.groupstats{ind}); end
maxplot = 3;
end
elseif strcmpi(opt.effect, 'main') && ~isempty(opt.interstats)
if ~isnan(opt.threshold) && ( ~isempty(opt.groupstats) || ~isempty(opt.condstats) )
pcondplot = { opt.interstats{2} };
pgroupplot = { opt.interstats{1} };
pinterplot = opt.interstats{3};
maxplot = 1;
else
if ~isempty(opt.interstats{2}), pcondplot = { -log10(opt.interstats{2}) }; end
if ~isempty(opt.interstats{1}), pgroupplot = { -log10(opt.interstats{1}) }; end
if ~isempty(opt.interstats{3}), pinterplot = -log10(opt.interstats{3}); end
maxplot = 3;
end
else
pcondplot = { };
pgroupplot = { };
pinterplot = { };
maxplot = 1;
end
% labels
% ------
if strcmpi(opt.unitx, 'ms'), xlab = 'Time (ms)'; ylab = 'Potential (\muV)';
elseif strcmpi(opt.unitx, 'rmsms'), xlab = 'Time (ms)'; ylab = 'Potential (RMS \muV)';
elseif strcmpi(opt.unitx, 'hz'), xlab = 'Frequency (Hz)'; ylab = 'Log Power 10*log_{10}(\muV^{2})'; % ylab = 'Power (10*log_{10}(\muV^{2}))';
elseif strcmpi(opt.unitx, 'rmshz'), xlab = 'Frequency (Hz)'; ylab = 'Log Power 10*log_{10}(RMS \muV^{2})'; % ylab = 'Power (10*log_{10}(\muV^{2}))';
elseif strcmpi(opt.unitx, 'hzpsd'), xlab = 'Frequency (Hz)'; ylab = 'Log Power Spectral Density 10*log_{10}(\muV^{2}/Hz)'; % ylab = 'Power (10*log_{10}(\muV^{2}))';
elseif strcmpi(opt.unitx, 'rmshzpsd'), xlab = 'Frequency (Hz)'; ylab = 'Log Power Spectral Density 10*log_{10}(RMS \muV^{2}/Hz)'; % ylab = 'Power (10*log_{10}(\muV^{2}))';
end
if ~isnan(opt.threshold), statopt = { 'xlabel' xlab };
else statopt = { 'logpval' 'on' 'xlabel' xlab 'ylabel' '-log10(p)' 'ylim' [0 maxplot] };
end
% adjust figure size
% ------------------
if strcmpi(opt.figure, 'on')
figure('color', 'w','Tag', opt.figtag);
pos = get(gcf, 'position');
basewinsize = 200/max(nc,ng)*3;
if strcmpi(opt.plotgroups, 'together'), pos(3) = 200*(1+addc);
else pos(3) = 200*(ng+addc);
end
if strcmpi(opt.plotconditions , 'together'), pos(4) = 200*(1+addr);
else pos(4) = 200*(nc+addr);
end
if all(pos(3:4) == 200), pos(3:4) = 400; end % double figure size if 1x1
if strcmpi(opt.subplot, 'transpose'), set(gcf, 'position', [ pos(1) pos(2) pos(4) pos(3)]);
else set(gcf, 'position', pos);
end
else
opt.subplot = 'noplot';
end
if isempty(opt.ylim)
if strcmpi(opt.plotsubjects, 'off')
opt.ylim = [min(cellfun(@(x)single(min(min(mean(x,3)))), data(:))) max(cellfun(@(x)single(max(max(mean(x,3)))), data(:)))];
else
opt.ylim = [min(cellfun(@(x)single(min(x(:))), data(:))) max(cellfun(@(x)single(max(x(:))), data(:)))];
end
end
colcount = 1; % only when plotting all conditions on the same figure
tmpcol = col;
for c = 1:ncplot
for g = 1:ngplot
if strcmpi(opt.figure, 'off'), tmpcol(1) = []; end % knock off colors ----- rows col ind
if strcmpi(opt.plotgroups, 'together'), hdl(c,g)=mysubplot(ncplot+addr, ngplot+addc, c, 1, opt.subplot); ci = g;
elseif strcmpi(opt.plotconditions, 'together'), hdl(c,g)=mysubplot(ncplot+addr, ngplot+addc, 1, g, opt.subplot); ci = c;
else hdl(c,g)=mysubplot(ncplot+addr, ngplot+addc, c, g, opt.subplot); ci = 1;
end
if ~isempty(data{c,g})
% read all data from one condition or group
% -----------------------------------------
dimreduced_sizediffers = 0;
if ncplot ~= nc && ngplot ~= ng
maxdim = max(max(cellfun(@(x)(size(x, ndims(x))), data)));
for cc = 1:size(data,1)
for gg = 1:size(data,2)
tmptmpdata = real(data{cc,gg});
if cc == 1 && gg == 1, tmpdata = NaN*zeros([size(tmptmpdata,1) size(tmptmpdata,2) maxdim length(data(:))]); end
tmpdata(:,:,1:size(tmptmpdata,3),gg+((cc-1)*ng)) = tmptmpdata;
end
end
elseif ncplot ~= nc % plot conditions together
for ind = 2:size(data,1), if numel(size(data{ind,1})) ~= numel(size(data{1})) || any(size(data{ind,1}) ~= size(data{1})), dimreduced_sizediffers = 1; end; end
for cc = 1:nc
[trash,order] = sort(cellfun(@length,data(:,g)),'descend'); clear trash;
tmptmpdata = real(data{order(cc),g});
if dimreduced_sizediffers
tmptmpdata = nan_mean(tmptmpdata,ndims(tmptmpdata)); % average across last dim
end
if cc == 1 && ndims(tmptmpdata) == 3, tmpdata = zeros([size(tmptmpdata) nc]); end
if cc == 1 && ndims(tmptmpdata) == 2, tmpdata = zeros([size(tmptmpdata) 1 nc]); end
if ~any(isnan(tmptmpdata))
tmpdata(:,:,:,order(cc)) = tmptmpdata;
else
tmpdata(:,:,:,order(cc)) = nan;
end
end
elseif ngplot ~= ng % plot groups together
for ind = 2:size(data,2), if numel(size(data{c,ind})) ~= numel(size(data{c})) || any((size(data{c,ind}) ~= size(data{c}))), dimreduced_sizediffers = 1; end; end
for gg = 1:ng
[trash,order] = sort(cellfun(@length,data(c,:)),'descend'); clear trash;
tmptmpdata = real(data{c,order(gg)});
if dimreduced_sizediffers
tmptmpdata = nan_mean(tmptmpdata,ndims(tmptmpdata));
end
if gg == 1 && ndims(tmptmpdata) == 3, tmpdata = zeros([size(tmptmpdata) ng]); end
if gg == 1 && ndims(tmptmpdata) == 2, tmpdata = zeros([size(tmptmpdata) 1 ng]); end
if ~any(isnan(tmptmpdata))
tmpdata(:,:,:,order(gg)) = tmptmpdata;
else
tmpdata(:,:,:,order(gg)) = nan;
end
end
else
tmpdata = real(data{c,g});
end
% plot difference
% ---------------
if ~strcmpi(opt.plotdiff, 'off')
if ngplot ~= ng || ncplot ~= nc
if size(tmpdata,3) == 2
tmpdata(:,:,end+1) = tmpdata(:,:,2)-tmpdata(:,:,1);
opt.legend{end+1} = [ opt.legend{2} '-' opt.legend{1} ];
elseif size(tmpdata,4) == 2
tmpdata(:,:,:,end+1) = tmpdata(:,:,:,2)-tmpdata(:,:,:,1);
opt.legend{end+1} = [ opt.legend{2} '-' opt.legend{1} ];
else
disp('Cannot plot difference, more than 2 indep. variable values');
end
else
disp('Cannot plot difference, indep. variable value must be plotted together');
end
end
if ~isempty(opt.filter), tmpdata = myfilt(tmpdata, 1000/(allx(2)-allx(1)), 0, opt.filter); end
% plotting options
% ----------------
plotopt = { allx };
% -------------------------------------------------------------
% tmpdata is of size "points x channels x subject x conditions"
% or "points x 1 x components x conditions"
% -------------------------------------------------------------
if ~dimreduced_sizediffers && strcmpi(opt.plotsubjects, 'off') % average across subjects
tmpstd = squeeze(real(std(tmpdata,[],3)))/sqrt(size(tmpdata,3)); tmpstd = squeeze(permute(tmpstd, [2 1 3])); tmpdata = squeeze(real(nan_mean(tmpdata,3)));
end
tmpdata = squeeze(permute(tmpdata, [2 1 3 4]));
% -----------------------------------------------------------------
% tmpdata is now of size "channels x points x subject x conditions"
% -----------------------------------------------------------------
if strcmpi(opt.plottopo, 'on'), highlight = 'background'; else highlight = 'bottom'; end
if strcmpi(opt.plotgroups, 'together') && isempty(opt.condstats) && ...
~isnan(opt.threshold) && ~isempty(opt.groupstats)
plotopt = { plotopt{:} 'maskarray' };
tmpdata = { tmpdata pgroupplot{c}' };
elseif strcmpi(opt.plotconditions, 'together') && isempty(opt.groupstats) && ...
~isnan(opt.threshold) && ~isempty(opt.condstats)
plotopt = { plotopt{:} 'maskarray' };
tmpdata = { tmpdata pcondplot{g}' };
end
plotopt = { plotopt{:} 'highlightmode', highlight };
if strcmpi(opt.plotsubjects, 'on')
plotopt = { plotopt{:} 'plotmean' 'on' 'plotindiv' 'on' };
else
plotopt = { plotopt{:} 'plotmean' 'off' };
end
plotopt = { plotopt{:} 'ylim' opt.ylim 'xlabel' xlab 'ylabel' ylab };
if ncplot ~= nc || ngplot ~= ng
plotopt = { plotopt{:} 'legend' opt.legend };
end
if strcmpi(opt.plottopo, 'on') && length(opt.chanlocs) > 1
metaplottopo(tmpdata, 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { plotopt{:} }, 'axcopycom', 'on', 'datapos', [2 3], 'title', opt.titles{c,g});
elseif iscell(tmpdata)
if ~all(isnan(tmpdata{1}))
plotcurve( allx, tmpdata{1}, 'colors', tmpcol, 'maskarray', tmpdata{2}, plotopt{3:end}, 'title', opt.titles{c,g});
else
plotcurve( allx, nan(size(tmpdata{1},2),length(allx)), 'colors', tmpcol, 'maskarray', tmpdata{2}, plotopt{3:end}, 'title', opt.titles{c,g});
end
else
if isempty(findstr(opt.plotstderr, 'nocurve'))
if all(isnan(tmpdata))
plotcurve( allx, nan(size(tmpdata,2),length(allx)), 'colors', tmpcol, plotopt{2:end}, 'traceinfo', 'on', 'title', opt.titles{c,g});
else
plotcurve( allx, tmpdata, 'colors', tmpcol, plotopt{2:end}, 'traceinfo', 'on', 'title', opt.titles{c,g});
end
end
if ~strcmpi(opt.plotstderr, 'off')
if ~dimreduced_sizediffers
if ~isempty(findstr(opt.plotstderr, 'diff')), begind = 3; else begind = 1; end
set(gcf, 'renderer', 'OpenGL')
for tmpi = begind:size(tmpdata,1)
hold on; chandle = fillcurves( allx, tmpdata(tmpi,:)-tmpstd(tmpi,:), tmpdata(tmpi,:)+tmpstd(tmpi,:), tmpcol{tmpi}); hold on;
numfaces = size(get(chandle(1), 'Vertices'),1);
set(chandle(1), 'FaceVertexCData', repmat([1 1 1], [numfaces 1]), 'Cdatamapping', 'direct', 'facealpha', 0.3, 'edgecolor', 'none');
end
else
disp('Some conditions have more subjects than others, cannot plot standard error');
end
end
end
end
% statistics across groups
% -------------------------
if g == ngplot && ng > 1 && ~isempty(opt.groupstats)
if ~strcmpi(opt.plotgroups, 'together') || ~isempty(opt.condstats) || isnan(opt.threshold)
if strcmpi(opt.effect, 'marginal') || (strcmpi(opt.effect, 'main') && c == 1)
if strcmpi(opt.effect, 'main') && nc>1, centerc = nc/2-0.5; else centerc = 0; end
if strcmpi(opt.plotgroups, 'together'), mysubplot(ncplot+addr, ngplot+addc, c+centerc, 2, opt.subplot); ci = g;
elseif strcmpi(opt.plotconditions, 'together'), mysubplot(ncplot+addr, ngplot+addc, 1, ngplot + 1, opt.subplot); ci = c;
else mysubplot(ncplot+addr, ngplot+addc, c+centerc, ngplot + 1, opt.subplot); ci = 1;
end
if strcmpi(opt.plotconditions, 'together'), condnames = 'Conditions'; else condnames = opt.condnames{c}; end
if ~isnan(opt.threshold)
if strcmpi(opt.plottopo, 'on')
metaplottopo({zeros(size(pgroupplot{c}')) pgroupplot{c}'}, 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx 'maskarray' statopt{:} }, 'datapos', [2 3], 'title', opt.titles{c, g+1});
else plotcurve(allx, zeros(size(allx)), 'maskarray', mean(pgroupplot{c},2), 'ylim', [0.1 1], 'title', opt.titles{c, g+1}, statopt{:});
end
else
if strcmpi(opt.plottopo, 'on')
metaplottopo(pgroupplot{c}', 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx statopt{:} }, 'datapos', [2 3], 'title', opt.titles{c, g+1});
else plotcurve(allx, mean(pgroupplot{c},2), 'title', opt.titles{c, g+1}, statopt{:});
end
end
end
end
end
end
end
% statistics across conditions
% -----------------------------
if ~isempty(opt.condstats) && nc > 1 && (~strcmpi(opt.plotconditions, 'together') || ~isempty(opt.groupstats) || isnan(opt.threshold))
for g = 1:ng
if strcmpi(opt.effect, 'marginal') || (strcmpi(opt.effect, 'main') && g == 1)
if strcmpi(opt.effect, 'main') && ng>1, centerg = ng/2-0.5; else centerg = 0; end
if strcmpi(opt.plotgroups, 'together'), mysubplot(ncplot+addr, ngplot+addc, ncplot+addr, 1, opt.subplot);
elseif strcmpi(opt.plotconditions, 'together'), mysubplot(ncplot+addr, ngplot+addc, 2, g+centerg, opt.subplot);
else mysubplot(ncplot+addr, ngplot+addc, ncplot+addr, g+centerg, opt.subplot);
end
if strcmpi(opt.plotgroups, 'together'), groupnames = 'Groups'; else groupnames = opt.groupnames{g}; end
if ~isnan(opt.threshold)
if strcmpi(opt.plottopo, 'on')
metaplottopo({zeros(size(pcondplot{g}')) pcondplot{g}'}, 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx 'maskarray' statopt{:} }, 'datapos', [2 3], 'title', opt.titles{end, g});
else plotcurve(allx, zeros(size(allx)), 'maskarray', mean(pcondplot{g},2), 'ylim', [0.1 1], 'title', opt.titles{end, g}, statopt{:});
end
else
if strcmpi(opt.plottopo, 'on')
metaplottopo(pcondplot{g}', 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx statopt{:} }, 'datapos', [2 3], 'title', opt.titles{end, g});
else plotcurve(allx, mean(pcondplot{g},2), 'title', opt.titles{end, g}, statopt{:});
end
end
end
end
end
% statistics across group and conditions
% ---------------------------------------
if ~isempty(opt.groupstats) && ~isempty(opt.condstats) && ng > 1 && nc > 1
mysubplot(ncplot+addr, ngplot+addc, ncplot+addr, ngplot + 1, opt.subplot);
if ~isempty(pinterplot)
if ~isnan(opt.threshold)
if strcmpi(opt.plottopo, 'on')
metaplottopo({zeros(size(pinterplot')) pinterplot'}, 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx 'maskarray' statopt{:} }, 'datapos', [2 3], 'title', opt.titles{end, end});
else plotcurve(allx, zeros(size(allx)), 'maskarray', mean(pinterplot,2), 'ylim', [0.1 1], 'title', opt.titles{end, end}, statopt{:});
xlabel(xlab); ylabel('-log10(p)');
end
else
if strcmpi(opt.plottopo, 'on')
metaplottopo(pinterplot', 'chanlocs', opt.chanlocs, 'plotfunc', 'plotcurve', ...
'plotargs', { allx statopt{:} }, 'datapos', [2 3], 'title', opt.titles{end, end});
else plotcurve(allx, mean(pinterplot,2), 'title', opt.titles{end, end}, statopt{:});
end
end
else
text(0,0.6, [ 'Plot main effect ' 10 'to see interaction' 10 '("Stat" button option)']);
axis off;
end
end
if strcmpi(opt.plottopo, 'off') && length(hdl(:)) > 1
axcopy;
% remove axis labels (for most but not all)
% ------------------
if strcmpi(opt.subplot, 'transpose')
for c = 1:size(hdl,2)
for g = 1:size(hdl,1)
axes(hdl(g,c));
if c ~= 1 && size(hdl,2) ~=1, xlabel(''); legend off; end
if g ~= 1 && size(hdl,1) ~= 1, ylabel(''); legend off; end
end
end
else
for c = 1:size(hdl,1)
for g = 1:size(hdl,2)
axes(hdl(c,g));
if g ~= 1 && size(hdl,2) ~=1, ylabel(''); legend off; end
if c ~= size(hdl,1) && size(hdl,1) ~= 1, xlabel(''); legend off; end
end
end
end
end
% mysubplot (allow to transpose if necessary)
% -------------------------------------------
function hdl = mysubplot(nr,nc,r,c,subplottype)
cmargin = 0.2/nc;
rmargin = 0.2/nr;
if strcmpi(subplottype, 'transpose'), hdl = subplot('position',[(r-1)/nr+rmargin (nc-c)/nc+cmargin 1/nr-2*rmargin 1/nc-2*cmargin]);
elseif strcmpi(subplottype, 'normal'), hdl = subplot('position',[(c-1)/nc+cmargin (nr-r)/nr+rmargin 1/nc-2*cmargin 1/nr-2*rmargin]);
elseif strcmpi(subplottype, 'noplot'), hdl = gca;
else error('Unknown subplot type');
end
% rapid filtering for ERP
% -----------------------
function tmpdata2 = myfilt(tmpdata, srate, lowpass, highpass)
bscorrect = 1;
if bscorrect
% Getting initial baseline
bs_val1 = mean(tmpdata,1);
bs1 = repmat(bs_val1, size(tmpdata,1), 1);
end
% Filtering
tmpdata2 = reshape(tmpdata, size(tmpdata,1), size(tmpdata,2)*size(tmpdata,3)*size(tmpdata,4));
tmpdata2 = eegfiltfft(tmpdata2',srate, lowpass, highpass)';
tmpdata2 = reshape(tmpdata2, size(tmpdata,1), size(tmpdata,2), size(tmpdata,3), size(tmpdata,4));
if bscorrect
% Getting after-filter baseline
bs_val2 = mean(tmpdata2,1);
bs2 = repmat(bs_val2, size(tmpdata2,1), 1);
% Correcting the baseline
realbs = bs1-bs2;
tmpdata2 = tmpdata2 + realbs;
end
Datasets
Models
